Resource Type: Report
Authors: Gajinder Pal Singh, Jordan Tuchman, and Michael P. Rodriguez
Published: May 31, 2014
Resource Description:
The Government of India has prioritized 184 of the 640 districts in the country for focused maternal and child health interventions under an integrated program called the Reproductive, Maternal, Neonatal, Child and Adolescent Health (RMNCH+A) initiative. A key factor in the success of this initiative is the ability of the government to effectively track health outcomes through the routine collection of data from service delivery points across the high-priority districts.
The National Rural Health Mission (NRHM)1 is responsible for monitoring RMNCH+A indicators across the country and has leveraged the rollout of a web-based national health management information (HMIS) for this purpose. In several states, another information system – the web-based District Health Information System (DHIS) 2.0 – is used. A number of reviews of the data produced through the national HMIS have indicated that there are data quality issues. However, there are limited reviews of data quality taking place across the NRHM facilities and no systematic assessment mechanism is currently in place.
To address these issues, the Haryana State NRHM partnered with the HFG Project to conduct a data quality audit (DQA) across four of the state’s high-priority districts. The DQA exercise took place in December 2013, beginning with a presentation of the methodology to a cadre of Haryana NRHM Program Managers, HMIS Officers, and District Monitoring and Evaluation (M&E) Officers. Presented here is a brief summary of the findings and recommendations, sorted by the five domains evaluated in the DQA exercise.
Haryana Health Officials Praise New Geographic Information SystemHFG Project
The new Haryana Health Geographic Information System (HHGIS) is an important step to improve data quality and use in Haryana, India. HHGIS allows public health staff like Ms. Babita, the district M&E Officer for Jind, to more easily access, analyze, and compare data from different health information systems. It overcomes challenges like the tedious process of manual data comparison and communication of complex data. HHGIS is expected to significantly reduce the time and effort required for data analysis tasks. With its visualization of data on maps and drill-down capabilities, HHGIS makes data more accessible and usable for informed decision making.
Data Quality Assessment Pilot Highlights Focus on Improving HMIS Data Quality...HFG Project
Dr. Vishnu Kant Srivastava leads the Statistics Division at India’s Ministry of Health and Family Welfare (MoHFW). Having managed statistical initiatives at different departments and levels of the government, Dr. Srivastava recognizes the value of quality data for effective decision making. He spoke with USAID’s Health Finance and Governance (HFG) project on the findings of the data quality assessment pilot the HFG team conducted.
National Identification Number for Healthcare Facilities of India PaperPankaj Gupta
This document discusses India's efforts to build a master health facility list (MFL) to facilitate data sharing across different health information systems. It describes how facility data from two existing national health reporting systems were mapped and verified to initially populate an online MFL portal. Currently the portal contains over 200,000 verified public health facilities. However, limitations from the original systems like inconsistent facility naming and lack of standardized facility hierarchies were carried over. Sustaining and evolving the MFL over time will require integrating other data sources, establishing governance mechanisms, conducting data quality audits, and addressing issues related to institutional adoption. The MFL is an important step for India but further innovations are still needed for it to reach its full potential.
Strengthening Country Routine Health Information Systems (RHIS): Strategic ap...MEASURE Evaluation
The document discusses strengthening routine health information systems (RHIS) through strategic approaches by the MEASURE Evaluation Project. It highlights the importance of RHIS in health system strengthening and integration. MEASURE Evaluation aims to improve RHIS performance by addressing technical, organizational, and behavioral factors using the PRISM framework. Key strategies include coordinating multi-stakeholder initiatives, strengthening governance and planning, regionalizing capacity building, and establishing advocacy and knowledge networks. The document proposes creating an RHIS subgroup under the Asia eHealth Information Network to further support RHIS strengthening efforts in Asia.
The importance of data quality assurance in improving grant implementation a...Alexander Decker
This document summarizes the findings of data quality assurance exercises conducted in health facilities in three Nigerian states. The exercises found deficiencies in data management systems and incomplete or discrepant HIV data reported in some facilities. Regular data auditing and supervisory visits were recommended to improve grant implementation and ensure accurate, valid HIV program data. Conducting data quality assurance is important for monitoring grant progress and performance, as well as improving service delivery and data integrity.
The Health Finance and Governance project works with countries to improve health systems and expand access to healthcare. In Ghana, the project worked with the National Health Insurance Authority to make the National Health Insurance Scheme more sustainable and effective. This included developing dashboards to monitor enrollment and claims data, conducting research to examine challenges, and laying the groundwork for capitation payments to primary care providers. The project helped institutionalize processes for using evidence to guide decision-making and reform policies to strengthen Ghana's progress toward universal health coverage.
This document provides a progress report for the Health Data Collaborative (HDC) for 2020-2021. It acknowledges contributions from HDC partners and technical working groups. It outlines changes to HDC governance and membership to improve partner alignment behind country health data priorities. It also summarizes updates and activities from the 7 HDC working groups focused on areas like civil registration, community data, and digital health. The report concludes that renewed focus on quality health data due to COVID-19 has increased interest and membership in HDC, bringing more diverse perspectives to strengthen support for country impact.
Haryana Health Officials Praise New Geographic Information SystemHFG Project
The new Haryana Health Geographic Information System (HHGIS) is an important step to improve data quality and use in Haryana, India. HHGIS allows public health staff like Ms. Babita, the district M&E Officer for Jind, to more easily access, analyze, and compare data from different health information systems. It overcomes challenges like the tedious process of manual data comparison and communication of complex data. HHGIS is expected to significantly reduce the time and effort required for data analysis tasks. With its visualization of data on maps and drill-down capabilities, HHGIS makes data more accessible and usable for informed decision making.
Data Quality Assessment Pilot Highlights Focus on Improving HMIS Data Quality...HFG Project
Dr. Vishnu Kant Srivastava leads the Statistics Division at India’s Ministry of Health and Family Welfare (MoHFW). Having managed statistical initiatives at different departments and levels of the government, Dr. Srivastava recognizes the value of quality data for effective decision making. He spoke with USAID’s Health Finance and Governance (HFG) project on the findings of the data quality assessment pilot the HFG team conducted.
National Identification Number for Healthcare Facilities of India PaperPankaj Gupta
This document discusses India's efforts to build a master health facility list (MFL) to facilitate data sharing across different health information systems. It describes how facility data from two existing national health reporting systems were mapped and verified to initially populate an online MFL portal. Currently the portal contains over 200,000 verified public health facilities. However, limitations from the original systems like inconsistent facility naming and lack of standardized facility hierarchies were carried over. Sustaining and evolving the MFL over time will require integrating other data sources, establishing governance mechanisms, conducting data quality audits, and addressing issues related to institutional adoption. The MFL is an important step for India but further innovations are still needed for it to reach its full potential.
Strengthening Country Routine Health Information Systems (RHIS): Strategic ap...MEASURE Evaluation
The document discusses strengthening routine health information systems (RHIS) through strategic approaches by the MEASURE Evaluation Project. It highlights the importance of RHIS in health system strengthening and integration. MEASURE Evaluation aims to improve RHIS performance by addressing technical, organizational, and behavioral factors using the PRISM framework. Key strategies include coordinating multi-stakeholder initiatives, strengthening governance and planning, regionalizing capacity building, and establishing advocacy and knowledge networks. The document proposes creating an RHIS subgroup under the Asia eHealth Information Network to further support RHIS strengthening efforts in Asia.
The importance of data quality assurance in improving grant implementation a...Alexander Decker
This document summarizes the findings of data quality assurance exercises conducted in health facilities in three Nigerian states. The exercises found deficiencies in data management systems and incomplete or discrepant HIV data reported in some facilities. Regular data auditing and supervisory visits were recommended to improve grant implementation and ensure accurate, valid HIV program data. Conducting data quality assurance is important for monitoring grant progress and performance, as well as improving service delivery and data integrity.
The Health Finance and Governance project works with countries to improve health systems and expand access to healthcare. In Ghana, the project worked with the National Health Insurance Authority to make the National Health Insurance Scheme more sustainable and effective. This included developing dashboards to monitor enrollment and claims data, conducting research to examine challenges, and laying the groundwork for capitation payments to primary care providers. The project helped institutionalize processes for using evidence to guide decision-making and reform policies to strengthen Ghana's progress toward universal health coverage.
This document provides a progress report for the Health Data Collaborative (HDC) for 2020-2021. It acknowledges contributions from HDC partners and technical working groups. It outlines changes to HDC governance and membership to improve partner alignment behind country health data priorities. It also summarizes updates and activities from the 7 HDC working groups focused on areas like civil registration, community data, and digital health. The report concludes that renewed focus on quality health data due to COVID-19 has increased interest and membership in HDC, bringing more diverse perspectives to strengthen support for country impact.
The document summarizes capacity building efforts of the USAID-funded Innovations in Family Planning Services (IFPS) Project in India from 1992-2012. The project focused on building capacities at individual, institutional, and societal levels. At the national level, it collaborated with the National Institute of Health and Family Welfare to conduct training courses and supported the creation of the National Health Systems Resource Center. In the states of Uttar Pradesh, Uttarakhand, and Jharkhand, the project strengthened state health institutes, implemented quality assurance programs, established mechanisms for decentralized planning, and built capacities of organizations implementing public-private partnerships for family planning services. Overall, the IFPS Project worked to develop sustainable
The Health Finance and Governance project in Ukraine worked to improve the country's health system through strategic purchasing approaches. It demonstrated the effectiveness of integrating HIV testing into primary care, improving efficiency of the TB hospital system by developing monitoring and simulation tools, and laying the groundwork for strategic purchasing reforms across the broader hospital sector. Key results included increasing HIV testing and detection rates while lowering costs, helping restructure TB hospitals based on data to improve care and achieve savings, and establishing cost accounting methods and a case-based payment system pilot to enhance the performance and efficiency of hospitals nationwide.
Do Better Laws and Regulations Promote Universal Health Coverage? A Review of...HFG Project
The importance of policies, laws, and regulations (referred to collectively below as “policy instances”) as instruments to support progress towards Universal Health Coverage (UHC) in low- and middle-income countries cannot be understated. However, there has been insufficient focus in the literature on the role of these instruments, leading to a lack of evidence as to what constitutes a supportive legal environment that can consistently provide a strong basis for UHC reform processes. In this review, we explore how policies implemented in different country contexts have had an impact on their achievement of UHC goals.
In order to better differentiate the effect of various policy instances on the achievement of UHC goals, we developed a typology for policy instances and then ascribed the different aspects of governance to the instances identified in the literature, based on how they were designed and implemented. Finally, we considered the success of each policy instance identified, in terms of achieving intended UHC-related outcomes.
Governments may have political and process constraints on the number of policy instances they can design and implement in a period leading up to and during health sector reform. In terms of which health system component to focus such change on, we have more evidence for policy instances focused on health financing, given that designing effective financing mechanisms can shape the entire health
sector. Following this, policy instances that address human resources for health and supply chain management should be prioritized as they appear to have key strengthening effects on the provision of healthcare by increasing efficiency, equity, and quality.
This review of the evidence to date of governments’ policy-making experience highlights the importance of effective policy design and implementation with a clear orientation towards better governance, and in particular increased responsiveness and accountability.
The USAID Health Finance and Governance project helps improve health in developing countries by expanding access to healthcare. Led by Abt Associates, the project works with partner countries to increase domestic health funding, better manage resources, and make wise purchasing decisions. In Nigeria, the project collaborated with government and partners from 2012-2018 to address challenges like underfunding, donor reliance, and weak governance. Key accomplishments included expanding an innovative mobile technology to improve TB response, increasing domestic funding for HIV and primary healthcare, establishing state health insurance schemes, and enhancing multisectoral collaboration around health financing reform.
The document provides an overview of the Directorate General of Nursing and Midwifery's (DGNM) digital activities as of December 2018. It discusses the establishment of the DGNM-PMIS software to digitally manage workforce data, with over 28,000 employees currently entered. It also outlines other digital initiatives like the Nurse-Midwife Education Management System to track student performance, and connections to the national digital roadmap to further develop e-services by 2021. The report highlights DGNM's progress toward a more digital future to better support the health sector in Bangladesh.
Strengthening Primary Care Through Performance - Based Incentive SystemHFG Project
The document summarizes the findings from two cycles of research on Indonesia's primary care incentive system under its national health insurance program. The research found that:
1) Health workers' incomes come from various sources, including government salary, capitation payments, regional allowances, and private practice, but the capitation system does not adequately motivate individual performance.
2) There is wide variation in health workers' incomes between districts and facilities based on local policies and patient volumes.
3) While incentive systems exist, they are often based more on attendance and processes rather than quality metrics or achievement of health targets. Respondents recommended revising incentives and indicators to better promote quality primary care performance.
Johan Vendrig
GM Information Services – healthAlliance
Andrew Terris
Programme Director, Patients First
Darrin Hackett
GM HIQ, Acting CIO Waikato DHB
Martin Wilson
GP, Sexual Health Physician, Clinical Leader
Pegasus, executive NICLG
Tony Cooke
Manager Health Systems Investment and
Planning, Information Group, NHB
(Thursday, 4.15, Panel)
Guyana 2016 Health Accounts - Statistical ReportHFG Project
The document provides an overview of Guyana's 2016 Health Accounts methodology. It summarizes key aspects of the System of Health Accounts 2011 framework used, including boundaries, classifications, and definitions. Data was collected from government, households, NGOs, employers, insurers, and donors to track financial flows for health for 2016. The results help understand Guyana's health financing and answer questions on spending patterns.
Essential Package of Health Services Country Snapshot Series: 24 Priority Cou...HFG Project
The document summarizes findings from analyzing essential packages of health services (EPHS) in 24 priority countries. Key findings include:
- 23 of 24 countries defined an EPHS, though specificity of packages varied. Most included the majority of priority reproductive and maternal health interventions.
- Countries delivered EPHS through community health workers and public facilities. Some used EPHS to standardize private sector provision.
- Governments addressed equity through EPHS-related policies on populations and financial protection, though mechanisms varied.
- Priority setting for EPHS appeared limited, with most listing all services rather than prioritizing based on resources. EPHS purposes also varied between guiding service delivery,
2015 Accomplishments in Integrated Healthcare for DWMHA (Recovered)Audrey E. Smith
The document summarizes the accomplishments of the Detroit Wayne Mental Health Authority (DWMHA) in integrated healthcare initiatives in 2015. Key accomplishments include:
1) Implementing a standardized integrated bio-psychosocial assessment across providers.
2) Increasing coordination between behavioral health providers and primary care providers, with 13 providers having on-site primary care and 75% of providers at the highest level of integration.
3) Training 95% of providers on an assessment tool to evaluate their level of integrated care capabilities.
The Health Metrics Network (HMN) was launched in 2005 with the goal of increasing the availability and use of timely and reliable health information. It aims to do this by coordinating investments in core country health information systems. The HMN has three main objectives: establish a common health information system framework, strengthen individual country health information systems, and improve access to and use of health data. It has provided tools like an assessment tool and strategic planning tool to help countries evaluate and improve their health information systems. To date, the HMN has facilitated health information system assessments and planning in over 66 countries.
Data Driven Decision Making in Ministry of Health and Family WelfareData Portal India
Data Driven Decision Making in Ministry of Health and Family Welfare presentation by Dr. Vishnu Kant Srivastava, Chief Director D/o Health & Family Welfare.
The document provides an evaluation of UNRWA's e-health project, which aimed to implement an electronic health information system to improve healthcare services for Palestinian refugees. While the e-health system showed potential, its rollout faced financial constraints, management challenges, and inadequate resources. As a result, it was only partially implemented across health centers. The evaluation found that the e-health system's benefits had not yet been fully realized due to the slow and inconsistent implementation process. It recommended fully rolling out a consistent e-health version across all fields within two years to allow the system's full potential to improve healthcare delivery, efficiency, and decision-making to be achieved.
A Scoping Review of the Uses and Institutionalization of Knowledge for Health...HFG Project
There is growing interest in the ways different forms of knowledge can be used to strengthen policymaking in low- and middle-income country (LMIC) health systems. Additionally, health policy and systems researchers are increasingly aware of the need to design effective institutions for supporting knowledge utilization in LMICs. In order to clarify the use and institutionalization of knowledge as well as effects on health systems, a scoping review was conducted using the Arksey and O’Malley framework.
The following research question guided our analysis: “What is known from the existing health literature about how actors use and incorporate knowledge into health system policymaking and what sorts of institutional arrangements facilitate this process in LMICs?”
While there is some evidence of how different uses and institutionalization of knowledge can strengthen health systems, the evidence on how these processes can ultimately improve health outcomes remains unclear. Further research on the ways in which knowledge can be effectively utilized and institutionalized is needed to advance collective understanding of the governance dimensions of health systems strengthening and enhance appropriate policy formulation.
MeHI Regional Health IT Meetings - Taunton, MA - Oct, 2013MassEHealth
The MeHI is the designated state agency for promoting health IT adoption and use in Massachusetts. It oversees the implementation of the statewide HIE called the Massachusetts Health Information Highway (Mass HIway). The Last Mile Program aims to connect all eligible providers to the Mass HIway and demonstrate improvements in care quality, population health, and costs through HIE use. Initiatives include connection support, education, and implementation grants.
Routine data quality assessment tool june 2008swiss1234
This document provides instructions for conducting a Routine Data Quality Assessment (RDQA) to evaluate program or project monitoring and evaluation systems. The RDQA involves selecting levels of the data reporting system to review, identifying indicators and time periods to assess, conducting site visits using checklists, and developing an action plan to strengthen areas of weakness. Site visits include verifying reported data against source documents, assessing data management processes, and providing recommendations. Dashboards then summarize findings to prioritize improvements to data quality.
Building Vibrant Communities - Erfolgreiche Einführung von Enterprise 2.0Peter H. Reiser
Datum: Freitag, 24.6.2011
Ort: FHNW, Riggenbachstrasse 16, CH-4600 Olten
http://www.fhnw.ch/kontakt/lageplan/fhnw_hw-ortsplaene.pdf
Raum: wird am Display in der Eingangshalle angezeigt
Moderation: Daniel Ebneter, Carpathia Consulting, Zürich
Programm ( jeweils 60‘ Vortrag, 30‘ Diskussion):
08:45-10:15 Thomas Lang, Geschäftsführer, Carpathia Consulting, Zürich
Trends im E-Commerce und Chancen für Schweizer Anbieter
10:45-12:15 Peter Reiser, Principal Architect, Oracle
Building Vibrant Communities - Erfolgreiche Einführung von Enterprise 2.0
13:15-14:45 Marcus Beyer, Archtitect Security Awareness, iSPIN, Zürich
Awareness schaffen – ohne Waffen
15:15-16:45 Robin Unger, Managing Partner – Consulting, Gartner, Dietikon
Reimagining IT: The 2011 CIO Agenda
The document summarizes capacity building efforts of the USAID-funded Innovations in Family Planning Services (IFPS) Project in India from 1992-2012. The project focused on building capacities at individual, institutional, and societal levels. At the national level, it collaborated with the National Institute of Health and Family Welfare to conduct training courses and supported the creation of the National Health Systems Resource Center. In the states of Uttar Pradesh, Uttarakhand, and Jharkhand, the project strengthened state health institutes, implemented quality assurance programs, established mechanisms for decentralized planning, and built capacities of organizations implementing public-private partnerships for family planning services. Overall, the IFPS Project worked to develop sustainable
The Health Finance and Governance project in Ukraine worked to improve the country's health system through strategic purchasing approaches. It demonstrated the effectiveness of integrating HIV testing into primary care, improving efficiency of the TB hospital system by developing monitoring and simulation tools, and laying the groundwork for strategic purchasing reforms across the broader hospital sector. Key results included increasing HIV testing and detection rates while lowering costs, helping restructure TB hospitals based on data to improve care and achieve savings, and establishing cost accounting methods and a case-based payment system pilot to enhance the performance and efficiency of hospitals nationwide.
Do Better Laws and Regulations Promote Universal Health Coverage? A Review of...HFG Project
The importance of policies, laws, and regulations (referred to collectively below as “policy instances”) as instruments to support progress towards Universal Health Coverage (UHC) in low- and middle-income countries cannot be understated. However, there has been insufficient focus in the literature on the role of these instruments, leading to a lack of evidence as to what constitutes a supportive legal environment that can consistently provide a strong basis for UHC reform processes. In this review, we explore how policies implemented in different country contexts have had an impact on their achievement of UHC goals.
In order to better differentiate the effect of various policy instances on the achievement of UHC goals, we developed a typology for policy instances and then ascribed the different aspects of governance to the instances identified in the literature, based on how they were designed and implemented. Finally, we considered the success of each policy instance identified, in terms of achieving intended UHC-related outcomes.
Governments may have political and process constraints on the number of policy instances they can design and implement in a period leading up to and during health sector reform. In terms of which health system component to focus such change on, we have more evidence for policy instances focused on health financing, given that designing effective financing mechanisms can shape the entire health
sector. Following this, policy instances that address human resources for health and supply chain management should be prioritized as they appear to have key strengthening effects on the provision of healthcare by increasing efficiency, equity, and quality.
This review of the evidence to date of governments’ policy-making experience highlights the importance of effective policy design and implementation with a clear orientation towards better governance, and in particular increased responsiveness and accountability.
The USAID Health Finance and Governance project helps improve health in developing countries by expanding access to healthcare. Led by Abt Associates, the project works with partner countries to increase domestic health funding, better manage resources, and make wise purchasing decisions. In Nigeria, the project collaborated with government and partners from 2012-2018 to address challenges like underfunding, donor reliance, and weak governance. Key accomplishments included expanding an innovative mobile technology to improve TB response, increasing domestic funding for HIV and primary healthcare, establishing state health insurance schemes, and enhancing multisectoral collaboration around health financing reform.
The document provides an overview of the Directorate General of Nursing and Midwifery's (DGNM) digital activities as of December 2018. It discusses the establishment of the DGNM-PMIS software to digitally manage workforce data, with over 28,000 employees currently entered. It also outlines other digital initiatives like the Nurse-Midwife Education Management System to track student performance, and connections to the national digital roadmap to further develop e-services by 2021. The report highlights DGNM's progress toward a more digital future to better support the health sector in Bangladesh.
Strengthening Primary Care Through Performance - Based Incentive SystemHFG Project
The document summarizes the findings from two cycles of research on Indonesia's primary care incentive system under its national health insurance program. The research found that:
1) Health workers' incomes come from various sources, including government salary, capitation payments, regional allowances, and private practice, but the capitation system does not adequately motivate individual performance.
2) There is wide variation in health workers' incomes between districts and facilities based on local policies and patient volumes.
3) While incentive systems exist, they are often based more on attendance and processes rather than quality metrics or achievement of health targets. Respondents recommended revising incentives and indicators to better promote quality primary care performance.
Johan Vendrig
GM Information Services – healthAlliance
Andrew Terris
Programme Director, Patients First
Darrin Hackett
GM HIQ, Acting CIO Waikato DHB
Martin Wilson
GP, Sexual Health Physician, Clinical Leader
Pegasus, executive NICLG
Tony Cooke
Manager Health Systems Investment and
Planning, Information Group, NHB
(Thursday, 4.15, Panel)
Guyana 2016 Health Accounts - Statistical ReportHFG Project
The document provides an overview of Guyana's 2016 Health Accounts methodology. It summarizes key aspects of the System of Health Accounts 2011 framework used, including boundaries, classifications, and definitions. Data was collected from government, households, NGOs, employers, insurers, and donors to track financial flows for health for 2016. The results help understand Guyana's health financing and answer questions on spending patterns.
Essential Package of Health Services Country Snapshot Series: 24 Priority Cou...HFG Project
The document summarizes findings from analyzing essential packages of health services (EPHS) in 24 priority countries. Key findings include:
- 23 of 24 countries defined an EPHS, though specificity of packages varied. Most included the majority of priority reproductive and maternal health interventions.
- Countries delivered EPHS through community health workers and public facilities. Some used EPHS to standardize private sector provision.
- Governments addressed equity through EPHS-related policies on populations and financial protection, though mechanisms varied.
- Priority setting for EPHS appeared limited, with most listing all services rather than prioritizing based on resources. EPHS purposes also varied between guiding service delivery,
2015 Accomplishments in Integrated Healthcare for DWMHA (Recovered)Audrey E. Smith
The document summarizes the accomplishments of the Detroit Wayne Mental Health Authority (DWMHA) in integrated healthcare initiatives in 2015. Key accomplishments include:
1) Implementing a standardized integrated bio-psychosocial assessment across providers.
2) Increasing coordination between behavioral health providers and primary care providers, with 13 providers having on-site primary care and 75% of providers at the highest level of integration.
3) Training 95% of providers on an assessment tool to evaluate their level of integrated care capabilities.
The Health Metrics Network (HMN) was launched in 2005 with the goal of increasing the availability and use of timely and reliable health information. It aims to do this by coordinating investments in core country health information systems. The HMN has three main objectives: establish a common health information system framework, strengthen individual country health information systems, and improve access to and use of health data. It has provided tools like an assessment tool and strategic planning tool to help countries evaluate and improve their health information systems. To date, the HMN has facilitated health information system assessments and planning in over 66 countries.
Data Driven Decision Making in Ministry of Health and Family WelfareData Portal India
Data Driven Decision Making in Ministry of Health and Family Welfare presentation by Dr. Vishnu Kant Srivastava, Chief Director D/o Health & Family Welfare.
The document provides an evaluation of UNRWA's e-health project, which aimed to implement an electronic health information system to improve healthcare services for Palestinian refugees. While the e-health system showed potential, its rollout faced financial constraints, management challenges, and inadequate resources. As a result, it was only partially implemented across health centers. The evaluation found that the e-health system's benefits had not yet been fully realized due to the slow and inconsistent implementation process. It recommended fully rolling out a consistent e-health version across all fields within two years to allow the system's full potential to improve healthcare delivery, efficiency, and decision-making to be achieved.
A Scoping Review of the Uses and Institutionalization of Knowledge for Health...HFG Project
There is growing interest in the ways different forms of knowledge can be used to strengthen policymaking in low- and middle-income country (LMIC) health systems. Additionally, health policy and systems researchers are increasingly aware of the need to design effective institutions for supporting knowledge utilization in LMICs. In order to clarify the use and institutionalization of knowledge as well as effects on health systems, a scoping review was conducted using the Arksey and O’Malley framework.
The following research question guided our analysis: “What is known from the existing health literature about how actors use and incorporate knowledge into health system policymaking and what sorts of institutional arrangements facilitate this process in LMICs?”
While there is some evidence of how different uses and institutionalization of knowledge can strengthen health systems, the evidence on how these processes can ultimately improve health outcomes remains unclear. Further research on the ways in which knowledge can be effectively utilized and institutionalized is needed to advance collective understanding of the governance dimensions of health systems strengthening and enhance appropriate policy formulation.
MeHI Regional Health IT Meetings - Taunton, MA - Oct, 2013MassEHealth
The MeHI is the designated state agency for promoting health IT adoption and use in Massachusetts. It oversees the implementation of the statewide HIE called the Massachusetts Health Information Highway (Mass HIway). The Last Mile Program aims to connect all eligible providers to the Mass HIway and demonstrate improvements in care quality, population health, and costs through HIE use. Initiatives include connection support, education, and implementation grants.
Routine data quality assessment tool june 2008swiss1234
This document provides instructions for conducting a Routine Data Quality Assessment (RDQA) to evaluate program or project monitoring and evaluation systems. The RDQA involves selecting levels of the data reporting system to review, identifying indicators and time periods to assess, conducting site visits using checklists, and developing an action plan to strengthen areas of weakness. Site visits include verifying reported data against source documents, assessing data management processes, and providing recommendations. Dashboards then summarize findings to prioritize improvements to data quality.
Building Vibrant Communities - Erfolgreiche Einführung von Enterprise 2.0Peter H. Reiser
Datum: Freitag, 24.6.2011
Ort: FHNW, Riggenbachstrasse 16, CH-4600 Olten
http://www.fhnw.ch/kontakt/lageplan/fhnw_hw-ortsplaene.pdf
Raum: wird am Display in der Eingangshalle angezeigt
Moderation: Daniel Ebneter, Carpathia Consulting, Zürich
Programm ( jeweils 60‘ Vortrag, 30‘ Diskussion):
08:45-10:15 Thomas Lang, Geschäftsführer, Carpathia Consulting, Zürich
Trends im E-Commerce und Chancen für Schweizer Anbieter
10:45-12:15 Peter Reiser, Principal Architect, Oracle
Building Vibrant Communities - Erfolgreiche Einführung von Enterprise 2.0
13:15-14:45 Marcus Beyer, Archtitect Security Awareness, iSPIN, Zürich
Awareness schaffen – ohne Waffen
15:15-16:45 Robin Unger, Managing Partner – Consulting, Gartner, Dietikon
Reimagining IT: The 2011 CIO Agenda
Duncan Allen :: Supporting Healthcare Systems Interoperabilitygeorge.james
- InterSystems Ensemble is a healthcare integration platform that allows for rapid application development, data integration across various systems and standards, and messaging between healthcare organizations.
- It provides a single runtime environment, abstraction layer, repository, and tools for execution, messaging, business processes, workflows, analytics and application development.
- Ensemble has been implemented successfully by many healthcare providers worldwide to integrate disparate clinical and administrative systems and develop new applications. It is rated the number one integration engine by KLAS.
eScience, Education and Knowledge ManagementLeo Plugge
The document discusses how information and communication technologies (ICT) have changed research and education by enabling knowledge sharing and collaboration through e-science. It describes how ICT facilitates a knowledge-driven research infrastructure by allowing data and resources to be shared over grids and clouds. This has industrialized information technology and increased the number of services available to researchers from global repositories and suppliers in the cloud.
This document provides an overview and instructions for using three DHIS 2 Android apps:
1) The Event Capture app allows users to create, view, modify and sync anonymous events not linked to registered entities.
2) The Aggregate Data Capture app allows users to enter and save aggregate data on Android devices for syncing to a DHIS 2 server.
3) The Tracker Capture app allows users to view, create, modify and sync individual-level data (enrollments and events) linked to tracked entities registered in DHIS 2.
Presented enterprise applications capacity planning methodology providing estimate of utilization of hardware resources
as well as transaction response times
Responsive Design and Information Architecture with Oracle Web Center Content...Dmitri Khanine
This whitepaper provides understanding of Responsive Design principles (RDP) and how they apply to your Oracle Content Management system. It also introduces the basic principles of Information Architecture and User Experience Management and shows real world examples of the impact of implementing the RDP.
It’s here to help Oracle professionals to quickly identify areas of sub-standard performance and sub-par user experience in their WebCenter implementation and provide practical recommendations to designers and administrators on boosting user productivity.
PEPFAR’s DATIM4U and Associated Interoperability ComponentsMEASURE Evaluation
DATIM4U is a standalone version of PEPFAR's global DATIM application designed for country teams and partners. It allows monthly monitoring and evaluation results to be entered, aggregated, and automatically sent to the global DATIM database with the click of a button. Key features include preconfigured data entry forms, customization options, and automatic synchronization of data and metadata with global DATIM using DHIS2 and OpenHIE technologies. It is currently being piloted with country teams.
Health Information System: Interoperability and Integration to Maximize Effec...MEASURE Evaluation
This document summarizes a presentation on health information system (HIS) interoperability and integration given by Manish Kumar and Sam Wambugu of MEASURE Evaluation. It describes issues with HIS in low and middle income countries like weak systems, lack of standards and data quality. It discusses the importance of interoperability, data standards, and collaboration. Country experiences from Liberia and Swaziland show efforts to develop HIS strategies, integrate systems, and use data for decision making. Key messages are promoting country ownership, stakeholder collaboration, agreed information architecture and standards, and institutional data use.
Institute of Electrical and Electronic Engineers (IEEE);
History of creation of IEEE;
Distinguished memebers of IEEE;
IEEE Societies;
Benefits of IEEE Membership;
IEEE Boumerdes University Student Branch;
This presentation provides an overview of OpenStand (www.open-stand.org), a multifaceted initiative that began with the drafting and joint affirmation of the OpenStand principles in August of 2012. Find out how OpenStand principles do more than align standards organizations – they lay out a new paradigm for technology development that is open, inclusive and market-driven from the bottom up. Find out how open standards benefit people, industry, markets, nations and the world.
Oracle architecture with details-yogiji creationsYogiji Creations
Oracle is a database management system with a multi-tiered architecture. It consists of a database on disk that contains tables, indexes and other objects. An Oracle instance contains a memory area called the System Global Area that services requests from client applications. Background processes facilitate communication between the memory structures and database files on disk. Logical database structures like tablespaces, segments, extents and blocks help organize and manage the physical storage of data.
Database Consolidation using the Oracle Multitenant ArchitecturePini Dibask
The document discusses Oracle's Multitenant architecture, which allows multiple pluggable databases (PDBs) to consolidate within a single multitenant container database (CDB). It describes how Multitenant provides advantages like simplified upgrades, cloning, and migration of PDBs. The document also covers ensuring quality of service for PDBs using resource management, and how RAC supports high availability and scalability in a Multitenant environment. It concludes with a discussion of performance monitoring of workloads across PDBs.
The document discusses Oracle's integration architecture for Oracle E-Business Suite. It outlines key integration challenges and describes Oracle's Business Integration Architecture, including the Oracle E-Business Suite Integrated SOA Gateway and Oracle E-Business Suite Adapter. The presentation agenda includes a discussion of business use cases, the product roadmap, and a Q&A section.
Fusion Middleware Oracle Data IntegratorMark Rabne
Oracle Data Integration can help improve information agility by enabling unified information management across organizations. It provides optimized data loading and real-time integration capabilities. This allows businesses to gain improved insights, reduce IT costs, and enhance agility through features like declarative design, knowledge modules, and data quality tools. Customers have seen benefits such as cost savings, increased revenues, and better decision making through using Oracle Data Integration.
This document provides an overview of Unix shell scripting, including special characters, different types of shells, and control structures like if/then statements, for loops, and case statements. It also reviews common Unix commands for navigating the file system, manipulating files and directories, and pattern matching. Shell scripts allow running commands, programs, and scripts in a shell environment and can be executed via the shell path or by declaring the shell type.
This session will first discuss basic analysis of a Linux system with pre-installed tools. You will learn several commands to help you understand Linux issues better.
In the second step, you will learn how to fix a broken Linux system. The session will teach some major troubleshooting techniques and will be filled with lots of demos that will show you how to fix real problems on real broken systems.
This document outlines Harold Dost III's presentation on troubleshooting Oracle SOA Suite 11g. The presentation covers various troubleshooting methodologies including starting with infrastructure issues, using logs and thread dumps to diagnose problems, and examples of different types of issues seen in production. The agenda includes an introduction, sections on infrastructure issues, performance issues, and deployment issues, and a summary.
WOA (Web Oriented Architecture) is an architectural style based on REST principles that uses resources and URIs to identify types of web objects. It provides a unified information architecture that is scalable, reusable, and federated. WOA focuses on resources rather than explicit services and uses HTTP as the primary interaction protocol. It is a substyle of SOA but emphasizes bottom-up design and loose coupling between services. Key technologies from Oracle that support WOA include WebLogic Portal, Oracle Coherence Data Grid, and RESTful APIs.
This presentation will examine the purpose and application of information architecture for the so-called ‘next generation’ of information tools, including blogs and wikis. We will introduce ‘needs based’ information architecture, the methodology used for organising and designing information-rich environments in a way that allows people to use them more easily. We will then look at how the best practice principles behind this approach apply equally well to emerging technologies.
Presented at Open Publish 2007, by Patrick Kennedy of Step Two Designs.
Synthesis Report of Health Information Systems in IndiaHFG Project
Resource Type: Report
Authors: Michael P. Rodriguez, Gajinder Pal Singh and Jim Setzer
Published: May 31, 2014
Resource Description:
A highly functioning national health information system (HIS) facilitates transparent and evidence-based decision making that ultimately leads to improvements in the health status of a country’s population.1 Rather than reflecting a single structure through which routine health statistics in a country are reported, most country health information systems are made up of multiple sub-systems that may or may not be well-coordinated, potentially collect some of the same information, and typically place the largest burden for reporting on those at the lowest levels of the health system, the primary health care facility staff. All of these characteristics present risks to the ability of the health system to function efficiently and effectively. The Health Metrics Network (HMN) Framework, published in 2008, provides a useful lens for viewing the efforts of the Republic of India to improve the production and availability of health information at all levels of its health system, from health facility to district, state, national and international levels, and to use that information to improve health outcomes.
The objectives of this report are to use the HMN Framework to examine, organize and summarize some of the publicly available written information on the Indian HIS and to serve as a resource tool for stakeholders throughout the Indian health system pursuing efforts to strengthen the HIS. This report is intended to highlight the progress that has been made to date and to discuss some of the gaps in the Indian HIS using the HMN Framework, which can then form the basis of discussions on HIS strengthening priorities.
Summary RHIS Evaluation Report for the Punjab National Health Mission Using t...HFG Project
Resource Type: Evaluation/Report
Authors: Nehal Jain, Vunnava Janardhan Rao and Michael P. Rodriguez
Published: May 31, 2014
Resource Description:
The Health Finance and Governance project has worked with the National Health Mission in Punjab to conduct an assessment of the routine health information systems across three districts in the state. The assessment team utilized the Performance of Routine Information Systems (PRISM) Framework to conduct the exercise, including the Performance Diagnostic Tool, the Overview and Facility/Office Checklist, the Management Assessment Tool and the Organizational and Behavioral Assessment Tool (OBAT). Site visits for data collection and interviews were conducted over a six-week period from mid-June 2014 to late-July 2014. Based on the data collected and analyzed from 24 health facilities across the three districts of Barnala, Mansa and Patiala, this report contains the key findings and recommendations from the PRISM assessment.
Data Quality Assessment Pilot Highlights Focus on Improving HMIS Data Quality...HFG Project
As Director of the Statistics Division within India's Ministry of Health and Family Welfare, Ms. Deepti Srivatasva held responsibility for the country's health management and information system. Ms. Srivastava worked closely with USAID''s Health Finance and Governance project team on conducting a data quality assessment pilot.
Improved Data Quality and Use: Dual Goals of HMIS StrengtheningHFG Project
The document discusses efforts to improve health management information systems (HMIS) in India through strengthening data quality and use. It outlines work conducted by the USAID-supported Health Finance and Governance project in collaboration with various partners to apply best practices for health information systems. This includes assessing HMIS data quality in several Indian states using a routine data quality assessment methodology, building capacity of local staff on monitoring and evaluation, and developing tools to enhance access and analysis of health data for decision-making. The overall goal is to help ensure a robust health system by generating and utilizing high-quality, timely data.
Antoine Mafwilla, MD, MPH, Chief of Monitoring and Evaluation, SANRU shares the challenges of performing evidence-based monitoring and evaluation on health programs in SANRU's program in the Democratic Republic of the Congo.
This document provides guidance on developing and using key performance indicators (KPIs) in the health sector. It discusses how KPIs can help health sector decision-makers track progress toward strategic goals, set performance standards and targets, measure improvements over time, and demonstrate results to stakeholders like the Ministry of Finance. The document emphasizes that KPIs should be linked to a sector's strategic framework and developed through strategic planning processes. It introduces the concept of a logic model to illustrate the logical linkages between problems, policies/measures, and goals. Developing the right KPIs involves aligning them with a sector's overarching strategic goals and objectives.
Performance Based Incentives to Strengthen Primary Health Care in Haryana Sta...HFG Project
Authors: Susan Gigli, Jenna Wright, Francis Raj and Mudeit Agarwa
Published: February 28, 2015
The Government of Haryana is interested in adopting a performance-based incentive (PBI) scheme aimed at strengthening primary health care results. In December 2014, the HFG project conducted a qualitative investigation among 10 public health facilities in two Blocks in Haryana in order to understand the existing incentive and operating environments and to inform the design of a PBI scheme. This report presents the findings of the formative investigation and relevant contextual information on the health system in the selected districts with a view toward supporting an effective PBI scheme in Haryana. The findings and considerations fed into a stakeholder PBI design workshop in early 2015.
The study suggested strongly that a PBI scheme—communicated clearly and perceived as fair—could lead to a change in the overall work culture from one that inadvertently encourages passivity to one that promotes teamwork, engagement, initiative, transparency and accountability.
PBI-to-Strengthen-Primary-Health-Care-in-Haryana_Findings-from-a-Formative-In...Dr. M. K. Agarwal
This formative investigation sought to understand the existing incentive environment and operating conditions in public health facilities in Haryana State, India in order to inform the design of a potential performance-based incentive (PBI) scheme. The investigation involved focus groups and interviews at 10 public health facilities across two districts. Key findings included an overall positive yet cautious reaction to PBI among participants. Participants recognized room for improved performance but had concerns about targets and external barriers. Existing government systems like the District Health Information System could potentially support PBI implementation if strengthened. Challenges in the current environment like staffing shortages, pay disparities, and weak performance management would also need to be addressed for PBI to be effective. The investigation provides considerations
The document describes a health facility management strengthening program implemented in 5 peripheral health facilities in Arghakhanchi District, Nepal to build the capacity of Health Facility Operation and Management Committees through trainings, reviews, and monitoring visits using materials from Nepal's Ministry of Health and Population. The program aimed to improve maternal and newborn health by empowering communities to better manage their local health facilities and identify, priorize, and address health issues through increased coordination, planning, resource mobilization, and monitoring of services. An assessment found that the committees demonstrated improved capacity in key areas of health facility management after participating in the strengthening program.
Modern HRIS systems can analyze workforce problems and solutions as well as link HR and service delivery data. An effective HRIS depends on being practical, user-friendly, flexible, and able to generate accurate timely information. It provides the foundation for strong workforce planning, development and management.
IntraHealth recommends establishing a stakeholder group to ensure local ownership of HRIS efforts. The group should assess existing systems and data to identify opportunities for linkage and gaps to address. After agreeing on key issues, customized software solutions should be identified and staff capacity built for implementation and use of data in decision making. Ensuring sustainability also requires continuous engagement of health leaders.
Pilots of HRIS in Bihar and Jhark
This document provides key performance and quality indicators for monitoring high impact interventions under India's Reproductive, Maternal, Newborn, Child and Adolescent Health (RMNCH+A) strategy. It begins with introductions by senior officials at the Ministry of Health and Family Welfare emphasizing the importance of these indicators for measuring progress and improving service delivery quality. The document then lists the indicators under each of the 5 areas of the strategy: reproductive health, maternal health, newborn health, child health, and adolescent health. It aims to help program managers at all levels accelerate progress, especially in India's 184 high priority districts.
The Link between Provider Payment and Quality of Maternal Health Services: Ca...HFG Project
This paper presents case studies of provider payment systems in the Kyrgyz Republic, Nigeria, and Zambia that link a quality improvement initiative with provider payment. It documents these programs’ experience with design and implementation and lessons learned for other health care payers seeking to improve quality at the point of care through redesign of a provider payment system.
Haryana 2014/15 State Health Accounts: Methodological ReportHFG Project
This Methodological Report provides an overview of the System of Health Accounts (SHA) 2011 framework as used for Haryana State’s 2014/15 Health Accounts (HA) estimation. It documents the data collection approaches and results, analytical steps taken, and assumptions made. It is intended for HA practitioners and researchers who wish to understand how the estimations were generated in Haryana and who need the detailed expenditure flow information for other operational and scientific research.
The purpose of an HA exercise is to estimate the amount and flow of health spending through a health system – in this instance, the Haryana health system, for fiscal 2014/15, April 1. 2014 to March 31, 2015. In addition to estimating general health expenditures, this analysis examined spending on priority diseases, levels of risk pooling (e.g., via government-sponsored insurance schemes), and contributions by the private sector. The HA team worked with the Haryana State Health Resource Centre (HSHRC) to determine the health policy questions of most relevance to Haryana, answers to which HA findings will inform. For more information on the HA findings and their policy implications, please see the main HA report, which complements this Methodological Report.
Haryana 2014/15 State Health Accounts: Methodological ReportHFG Project
This document provides a methodological report on the 2014/15 health accounts for Haryana, India. It describes the conceptual framework used, which follows the System of Health Accounts 2011 methodology to estimate health spending flows. Key classifications examined include financing schemes, providers, functions, and beneficiary characteristics. The report outlines the data sources and analysis conducted, including distribution of spending across primary, secondary and tertiary care. It documents the process undertaken from May 2015 to June 2016, which involved secondary data collection, primary surveys, data analysis using the Health Accounts Production Tool, and stakeholder validation. The tables in Chapter 4 present the results of the health accounts according to the SHA 2011 framework.
The Link between Provider Payment and Quality of Maternal Health Services: A ...HFG Project
This paper explores a growing trend among health care payers to combine a quality measurement initiative with a redesigned provider payment system. It presents a conceptual framework of how provider payment links with quality of maternal health services and analyzes real provider payment systems in low- and middle-income countries where payment is linked with quality measurement. It discusses how provider payment systems have been redesigned to improve quality, how quality is defined and measured, whether provider behavior changed in response to the payment mechanism, and reasons for why the payment mechanism did or did not work to achieve improved quality of maternal health services at the point of care.
Botswana’s Integration of Health Data Quality Assurance Into Standard Operati...MEASURE Evaluation
The document describes the development of data quality assurance procedures for Botswana's health ministry (MoH) in collaboration with MEASURE Evaluation. Key deliverables included standard operating procedures for data quality, a routine data quality assessment tool customized for Botswana, and a data quality curriculum and training workshops. The process took 16 months and $300,000. It established guidelines for ensuring quality data collection and use at service delivery, district, and national levels in Botswana.
Better Health? Composite Evidence from Four Literature ReviewsHFG Project
The Marshaling the Evidence secretariat agreed that a cross-cutting synthesis paper was necessary to frame the work in the wider context of governance in health systems, drawing distinctions and consensus across all four TWG papers. Members of the secretariat, some of whom also were members of the TWGs, conducted the analysis across each TWG report and wrote the synthesis report. The report compiles results from the TWGs into a searchable database, contained in Annex 1. The report also lays the foundation for future action—from dissemination to further research agendas and policy plans.
This document provides an overview of results-based financing (RBF) for family planning and discusses opportunities and challenges. RBF aims to shift payment in health systems from funding inputs to paying for outputs or outcomes achieved. For family planning, RBF presents opportunities to increase access to voluntary services and enhance quality. However, it also poses challenges in ensuring payment systems support principles of voluntarism, informed choice, quality and accountability. The document provides guidance on how to design RBF for family planning to avoid unintended consequences and maximize benefits while upholding individuals' reproductive rights and choices.
Similar to Improving Data for Decision-Making: Leveraging Data Quality Audits in Haryana, India (20)
This document outlines a training manual for a hospital costing workshop. It provides an agenda for the 3-day workshop covering topics like the fundamentals of costing, the MASH costing tool, and calculating unit costs. The workshop aims to teach participants how to conduct costing exercises to understand their hospital's costs and improve management. Sessions include introductions, an overview of costing concepts, the costing process, and a demonstration of the MASH tool which is an Excel-based framework for tracking and analyzing hospital resources, services, and costs.
Trinidad and Tobago 2015 Health Accounts - Main ReportHFG Project
This document summarizes the key findings of the 2015 health accounts report for Trinidad and Tobago. It finds that total health expenditure was 4.5 billion TT dollars in 2015, equivalent to 4.1% of GDP. The government financed 41% of health spending, while households financed 35% through direct out-of-pocket payments. Noncommunicable diseases accounted for the largest share of recurrent health spending at 42%. Out-of-pocket payments remain high, comprising over a third of total health expenditure. The report recommends strengthening government commitment to health financing, increasing risk pooling to reduce out-of-pocket spending, improving access to services, and institutionalizing ongoing health accounts estimations.
Guyana 2016 Health Accounts - Dissemination BriefHFG Project
The 2016 Guyana Health Accounts study found that:
1) Total health expenditure in Guyana was $28.6 billion (Guyanese dollars), with the government contributing 81% of funding.
2) The majority (71%) of health funds were spent on public health facilities like hospitals and clinics.
3) Most funds (64%) were spent on curative care services, while non-communicable diseases received the largest share (34%) of funds.
4) Government funding represents the largest source of financing for HIV/AIDS programs and services in Guyana, providing 62% of funds.
Guyana 2016 Health Accounts - Main ReportHFG Project
The document summarizes the key findings of Guyana's first Health Accounts exercise for fiscal year 2016. It found that total health expenditure was G$ 28.6 billion, with the government contributing 81% of funding. Household out-of-pocket spending accounted for 9% of total spending. Non-communicable diseases received the largest share of spending at 34%. The analysis aims to inform strategic health financing decisions and assess domestic resource mobilization as external donor funding declines. Recommendations include increasing prevention spending and strengthening financial commitment to HIV programs.
The Next Frontier to Support Health Resource TrackingHFG Project
The document discusses challenges and opportunities for institutionalizing health resource tracking (HRT) in low- and middle-income countries. It identifies three key elements needed for institutionalization: strong demand for HRT data; sustainable local capacity to produce HRT data; and use of HRT results in policy and decision making. It outlines remaining challenges in each area and suggestions for future investments to address challenges, such as building understanding of HRT's value, maintaining local expertise, improving health information systems, and strengthening communication and use of HRT findings.
Rivers State has a population of over 7 million people from various ethnic groups. The main occupations are fishing, farming, and trading. The state has high rates of tuberculosis, neonatal and under-5 mortality, and HIV prevalence. Key stakeholders in health include the Ministry of Health, Ministry of Finance, and various agencies. The USAID Health Finance and Governance project worked to increase domestic health financing through advocacy, establishing a health insurance scheme, and capacity building. These efforts led to increased health budgets, establishment of healthcare financing units, and improved sustainability of health financing in Rivers State.
ASSESSMENT OF RMNCH FUNCTIONALITY IN HEALTH FACILITIES IN BAUCHI STATE, NIGERIAHFG Project
This document summarizes an assessment of reproductive, maternal, newborn and child health (RMNCH) services in health facilities in Bauchi State, Nigeria. It found that infrastructure like electricity, water and toilets were lacking in many facilities. There were also shortages of skilled healthcare workers, especially midwives, and staff training. While many facilities offered antenatal care and immunizations, availability of emergency obstetric and newborn care and services like postnatal care and post-abortion care were more limited. Supplies of essential medicines, equipment and guidelines were also often inadequate. Community outreach was provided by some facilities but could be expanded.
BAUCHI STATE, NIGERIA PUBLIC EXPENDITURE REVIEW 2012-2016 HFG Project
This document summarizes a public expenditure review of health spending in Bauchi State, Nigeria from 2012 to 2016. It finds that while Bauchi State's health budget increased over this period, actual health spending lagged behind budgeted amounts. Specifically, health spending accounted for a small and declining share of the state's total budget and expenditure. The review recommends that Bauchi State increase and better target public health funding to improve health outcomes and progress toward universal health coverage goals.
HEALTH INSURANCE: PRICING REPORT FOR MINIMUM HEALTH BENEFITS PACKAGE, RIVERS ...HFG Project
This document provides a pricing report for a Minimum Health Benefit Package (MHBP) being developed by Rivers State government in Nigeria. It analyzes the cost of 6 scenarios for the package, including individual and household premiums, based on medical claims data from hospitals in Rivers State from 2014-2017. The recommended annual premiums range from N14,026 to N111,734 for individuals and N79,946 to N636,882 for households, depending on the benefits included and the percentage of the state's population covered. The report provides context on data sources and actuarial assumptions used to determine the premiums.
The document is an actuarial report for Kano State's contributory healthcare benefit package in Nigeria. It analyzes 4 scenarios for the package - a basic minimum package alone or plus HIV/AIDS, tuberculosis, or family planning services. The report finds that the estimated annual premium per individual would be between N12,180-N12,600 depending on the scenario, while the estimated annual premium per household of 6 would be between N73,081-N75,595. It provides these estimates by analyzing the state's population data, healthcare facilities, utilization rates, and costs to determine the risk premiums, administrative costs, marketing costs, and contingency margins for each scenario. The report recommends rounding the premium estimates and includes
Supplementary Actuarial Analysis of Tuberculosis, LAGOS STATE, NIGERIA HEALTH...HFG Project
This document provides an actuarial analysis of including tuberculosis (TB) coverage in the Lagos State Health Scheme in Nigeria. It analyzes 3 different TB treatment regimens and estimates the additional premium required. Based on historical TB case data from 2013-2016, it projects the number of cases and costs for the next 3 years. The analysis finds the additional premium to be 488.79 Naira on average per person to cover TB screening tests and the 3 treatment regimens. It acknowledges limitations in the source data and outlines key assumptions made in the projections.
Supplementary Actuarial Analysis of HIV/AIDS in Lagos State, NigeriaHFG Project
This document provides a supplementary actuarial analysis of including HIV/AIDS coverage in the Lagos State Health Scheme benefit package in Nigeria. It estimates the total additional medical cost to cover HIV/AIDS services would be 209.40 Naira per person per year, broken down into costs for HIV testing and counseling (13.60), antiretroviral therapy (133.05), and preventing mother-to-child transmission (15.96). The analysis is based on HIV service data from 2012-2016 and projected population and drug cost data from the Lagos State Ministry of Health. It assumes a 90% continuation and conversion rate for antiretroviral therapy and a 6.5% annual medical cost trend.
Assessment Of RMNCH Functionality In Health Facilities in Osun State, NigeriaHFG Project
This document summarizes an assessment of reproductive, maternal, newborn and child health functionality in health facilities in Osun State, Nigeria. It was conducted by Abt Associates in collaboration with other organizations as part of the USAID Health Finance and Governance Project. The assessment aimed to determine service delivery readiness in primary health centers for the Basic Health Care Provision Fund pilot. Key findings included inadequate health facility infrastructure, shortages of health workers and equipment, and gaps in administrative and referral systems. The results provide baseline data on capacity for implementing health financing reforms in Osun State under the National Health Act.
OSUN STATE, NIGERIA FISCAL SPACE ANALYSIS FOR HEALTH SECTORHFG Project
This document analyzes fiscal space for health in Osun State, Nigeria. It examines options for increasing fiscal space such as prioritizing health spending, earmarking taxes for health, and improving efficiency. The analysis finds that covering the state's population under the Osun State Health Insurance Scheme at a premium of N7,660 per person annually would cost over N30 billion, exceeding currently available resources. Additional funding sources or subsidies for vulnerable groups would be required to achieve universal health coverage in Osun State.
ANALYZING FISCAL SPACE FOR HEALTH IN NASARAWA STATE, NIGERIAHFG Project
This document analyzes potential fiscal space for health in Nasarawa State, Nigeria. It identifies several options for increasing funding available for the health sector, including leveraging conducive macroeconomic conditions, increasing the priority of health in sectoral budget allocations, earmarking portions of taxes and fees for health, obtaining external grants, and improving efficiency. Collectively, these options could provide tens of millions of additional naira annually that could be directed towards expanding health coverage and services. The document recommends that Nasarawa State prioritize these funding avenues and implement reforms to fully capitalize on the fiscal space available.
At Apollo Hospital, Lucknow, U.P., we provide specialized care for children experiencing dehydration and other symptoms. We also offer NICU & PICU Ambulance Facility Services. Consult our expert today for the best pediatric emergency care.
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Address: Singar Nagar, LDA Colony, Lucknow, Uttar Pradesh 226012
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Healthy Eating Habits:
Understanding Nutrition Labels: Teaches how to read and interpret food labels, focusing on serving sizes, calorie intake, and nutrients to limit or include.
Tips for Healthy Eating: Offers practical advice such as incorporating a variety of foods, practicing moderation, staying hydrated, and eating mindfully.
Benefits of Regular Exercise:
Physical Benefits: Discusses how exercise aids in weight management, muscle and bone health, cardiovascular health, and flexibility.
Mental Benefits: Explains the psychological advantages, including stress reduction, improved mood, and better sleep.
Tips for Staying Active:
Encourages consistency, variety in exercises, setting realistic goals, and finding enjoyable activities to maintain motivation.
Maintaining a Balanced Lifestyle:
Integrating Nutrition and Exercise: Suggests meal planning and incorporating physical activity into daily routines.
Monitoring Progress: Recommends tracking food intake and exercise, regular health check-ups, and provides tips for achieving balance, such as getting sufficient sleep, managing stress, and staying socially active.
Let's Talk About It: Breast Cancer (What is Mindset and Does it Really Matter?)bkling
Your mindset is the way you make sense of the world around you. This lens influences the way you think, the way you feel, and how you might behave in certain situations. Let's talk about mindset myths that can get us into trouble and ways to cultivate a mindset to support your cancer survivorship in authentic ways. Let’s Talk About It!
International Cancer Survivors Day is celebrated during June, placing the spotlight not only on cancer survivors, but also their caregivers.
CANSA has compiled a list of tips and guidelines of support:
https://cansa.org.za/who-cares-for-cancer-patients-caregivers/
Gemma Wean- Nutritional solution for Artemiasmuskaan0008
GEMMA Wean is a high end larval co-feeding and weaning diet aimed at Artemia optimisation and is fortified with a high level of proteins and phospholipids. GEMMA Wean provides the early weaned juveniles with dedicated fish nutrition and is an ideal follow on from GEMMA Micro or Artemia.
GEMMA Wean has an optimised nutritional balance and physical quality so that it flows more freely and spreads readily on the water surface. The balance of phospholipid classes to- gether with the production technology based on a low temperature extrusion process improve the physical aspect of the pellets while still retaining the high phospholipid content.
GEMMA Wean is available in 0.1mm, 0.2mm and 0.3mm. There is also a 0.5mm micro-pellet, GEMMA Wean Diamond, which covers the early nursery stage from post-weaning to pre-growing.
Can coffee help me lose weight? Yes, 25,422 users in the USA use it for that ...nirahealhty
The South Beach Coffee Java Diet is a variation of the popular South Beach Diet, which was developed by cardiologist Dr. Arthur Agatston. The original South Beach Diet focuses on consuming lean proteins, healthy fats, and low-glycemic index carbohydrates. The South Beach Coffee Java Diet adds the element of coffee, specifically caffeine, to enhance weight loss and improve energy levels.
Hypertension and it's role of physiotherapy in it.Vishal kr Thakur
This particular slides consist of- what is hypertension,what are it's causes and it's effect on body, risk factors, symptoms,complications, diagnosis and role of physiotherapy in it.
This slide is very helpful for physiotherapy students and also for other medical and healthcare students.
Here is summary of hypertension -
Hypertension, also known as high blood pressure, is a serious medical condition that occurs when blood pressure in the body's arteries is consistently too high. Blood pressure is the force of blood pushing against the walls of blood vessels as the heart pumps it. Hypertension can increase the risk of heart disease, brain disease, kidney disease, and premature death.
2024 HIPAA Compliance Training Guide to the Compliance OfficersConference Panel
Join us for a comprehensive 90-minute lesson designed specifically for Compliance Officers and Practice/Business Managers. This 2024 HIPAA Training session will guide you through the critical steps needed to ensure your practice is fully prepared for upcoming audits. Key updates and significant changes under the Omnibus Rule will be covered, along with the latest applicable updates for 2024.
Key Areas Covered:
Texting and Email Communication: Understand the compliance requirements for electronic communication.
Encryption Standards: Learn what is necessary and what is overhyped.
Medical Messaging and Voice Data: Ensure secure handling of sensitive information.
IT Risk Factors: Identify and mitigate risks related to your IT infrastructure.
Why Attend:
Expert Instructor: Brian Tuttle, with over 20 years in Health IT and Compliance Consulting, brings invaluable experience and knowledge, including insights from over 1000 risk assessments and direct dealings with Office of Civil Rights HIPAA auditors.
Actionable Insights: Receive practical advice on preparing for audits and avoiding common mistakes.
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Ensure your compliance strategy is up-to-date and effective. Enroll now and be prepared for the 2024 HIPAA audits.
Enroll Now to secure your spot in this crucial training session and ensure your HIPAA compliance is robust and audit-ready.
https://conferencepanel.com/conference/hipaa-training-for-the-compliance-officer-2024-updates
Comprehensive Rainy Season Advisory: Safety and Preparedness Tips.pdfDr Rachana Gujar
The "Comprehensive Rainy Season Advisory: Safety and Preparedness Tips" offers essential guidance for navigating rainy weather conditions. It covers strategies for staying safe during storms, flood prevention measures, and advice on preparing for inclement weather. This advisory aims to ensure individuals are equipped with the knowledge and resources to handle the challenges of the rainy season effectively, emphasizing safety, preparedness, and resilience.
PET CT beginners Guide covers some of the underrepresented topics in PET CTMiadAlsulami
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- Primary pleural tumors and pleural metastases.
- Distinguishing between MPM and Talc Pleurodesis.
- Urological tumors.
- The role of FDG PET in NET.
LGBTQ+ Adults: Unique Opportunities and Inclusive Approaches to CareVITASAuthor
This webinar helps clinicians understand the unique healthcare needs of the LGBTQ+ community, primarily in relation to end-of-life care. Topics include social and cultural background and challenges, healthcare disparities, advanced care planning, and strategies for reaching the community and improving quality of care.
DR SHAMIN EABENSON - JOURNAL CLUB - NEEDLE STICK INJURY
Improving Data for Decision-Making: Leveraging Data Quality Audits in Haryana, India
1. IMPROVING DATA FOR DECISION-MAKING:
LEVERAGING DATA QUALITY AUDITS
IN HARYANA, INDIA
May 2014
DISCLAIMER
The author’s views expressed in this publication do not necessarily reflect the views of the United States Agency for International
Development (USAID) or the United States Government.
This publication was produced for review by the United States Agency for International Development and the Haryana National Rural
Health Mission. It was prepared by Gajinder Pal Singh, Jordan Tuchman, and Michael P. Rodriguez of the Health Finance and Governance
Project.
2. The Health Finance and Governance Project
USAID’s Health Finance and Governance (HFG) project will improve health in developing countries by expanding
people’s access to health care. Led by Abt Associates, the project team will work with partner countries to
increase their domestic resources for health, manage those precious resources more effectively, and make wise
purchasing decisions. As a result, this five-year, $209 million global project will increase the use of both primary
and priority health services, including HIV/AIDS, tuberculosis, malaria, and reproductive health services. Designed
to fundamentally strengthen health systems, HFG will support countries as they navigate the economic transitions
needed to achieve universal health care.
May 2014
Cooperative Agreement No: AID-OAA-A-12-00080
Submitted to: Scott Stewart, AOR
Office of Health Systems
Bureau for Global Health
And
Ekta Saroha, Project Management Specialist
Strategic Information and Policy
Health Office
USAID India
Recommended Citation: Singh, Gajinder Pal, Jordan Tuchman, and Michael P. Rodriguez. May 2014. Improving
Data for Decision-making: Leveraging Data Quality Audits in Haryana, India. Delhi, India: Health Finance and
Governance Project, Abt Associates.
Abt Associates Inc. | 4550 Montgomery Avenue, Suite 800 North | Bethesda, Maryland 20814
T: 301.347.5000 | F: 301.652.3916 | www.abtassociates.com
Broad Branch Associates | Development Alternatives Inc. (DAI) | Futures Institute
| Johns Hopkins Bloomberg School of Public Health (JHSPH) | Results for Development Institute (R4D)
| RTI International | Training Resources Group, Inc. (TRG)
3. IMPROVING DATA FOR DECISION-
MAKING: LEVERAGING DATA QUALITY
AUDITS IN HARYANA, INDIA
DISCLAIMER
The author’s views expressed in this publication do not necessarily reflect the views of the United States Agency
for International Development (USAID) or the United States Government.
4.
5. CONTENTS
Acronyms................................................................................................................. iii
Executive Summary .............................................................................................. vii
1. Introduction ......................................................................................................... 1
2. Data Quality Audit Findings .............................................................................. 9
3. Recommendations and Next Steps................................................................. 17
Annex 1: DQA Protocol 1 Questions.................................................................. 23
List of Tables
Table 1: Verification Factor for DQA Indicators..........................................................................ix
Table 2: Site Visit Schedule..................................................................................................................8
Table 3: Assessment of Data Management and Reporting Systems.........................................9
Table 4: Trace and Verify: Institutional Deliveries to ANC Registrations ...........................13
Table 5: Trace and Verify: Newborns Weighing Less than 2.5 kg to Total Newborns....14
Table 6: Trace and Verify: Cases of Pregnant Women with Complications and Attended
at Public Facilities to Reported Deliveries..................................................................14
Table 7: Trace and Verify: Postpartum Sterilizations to Total Sterilizations.......................15
List of Figures
Figure 1: Spider Graph of Protocol 1 Summary ......................................................................... viii
Figure 2: NRHM Indicators in Relation to the RMNCH+A Continuum of Care.................1
Figure 3: Health Management Information System Data Flow in Haryana.............................3
Figure 4: The Five Domains of the Monitoring and Evaluation System...................................5
Figure 5: NRHM Classification of Districts in Haryana................................................................7
i
6.
7. ACRONYMS
ANC Antenatal Care
CHC Community Health Centre
DHIS District Health Information System
DQA Data Quality Audit
HFG Health Finance and Governance project
HIS Health Information System
HMIS Health Management Information System
M&E Monitoring and Evaluation
MCTS Mother and Child Tracking System
MOHFW Ministry of Health and Family Welfare
NHSRC National Health Systems Resource Centre
NRHM National Rural Health Mission (now known as National Health Mission)
PEPFAR President’s Emergency Plan for AIDS Relief
PHC Primary Health Centre
RMNCH+A Reproductive, Maternal, Newborn, Child and Adolescent Health
RDQA Routine Data Quality Assessment
TT Tetanus Toxoid
USAID United States Agency for International Development
iii
8.
9. ACKNOWLEDGEMENTS
The success of this data quality audit exercise was made possible by the support of Haryana State National Rural
Health Mission (NRHM), Mission Director Dr. Rakesh Gupta, NRHM Director Dr. Ravi Kant Gupta, the Project
Officer for Information Technology Mr. Harish Bisht, and the District Civil Surgeons and District Monitoring and
Evaluation Officers in the districts of Bhiwani, Narnaul, Mewat, and Palwal. The Health Finance and Governance
project gratefully acknowledges the assistance provided by the NRHM teams at both the state and district levels in
coordinating and confirming the site visits to health facilities for the audit.
v
10.
11. EXECUTIVE SUMMARY
The Government of India has initiated a Call to Action intended to accelerate progress toward attaining
Millennium Development Goals 4 and 5: reduction of under-five mortality and improvement of maternal
health outcomes. The government has prioritized 184 of the 640 districts in the country for focused
maternal and child health interventions under an integrated program called the Reproductive, Maternal,
Neonatal, Child and Adolescent Health (RMNCH+A) initiative. A key factor in the success of this
initiative is the ability of the government to effectively track health outcomes through the routine
collection of data from service delivery points across the high-priority districts.
The National Rural Health Mission (NRHM)1 is responsible for monitoring RMNCH+A indicators across
the country and has leveraged the rollout of a web-based national health management information
(HMIS) since 2008 for this purpose. In several states, another information system – the web-based
District Health Information System (DHIS) 2.0 – is used to compile routine data up to the state level,
where the data are then uploaded separately to the national HMIS portal. A number of reviews of the
data produced through the national HMIS have indicated that there are data quality issues. However,
there are limited reviews of data quality taking place across the NRHM facilities and no systematic
assessment mechanism is currently in place.
To address these issues, the Haryana State NRHM partnered with the USAID-funded Health Finance
and Governance Project (HFG) to conduct a data quality audit (DQA) across four of the state’s high-
priority districts using a methodology and set of tools intended to assess underlying systems and
structures supporting the flow of health data. The DQA exercise took place from 4 – 13 December
2013, beginning with a presentation of the methodology to a cadre of Haryana NRHM Program
Managers, HMIS Officers, and District Monitoring and Evaluation (M&E) Officers. The DQA
methodology used was comprised of two components (Protocol 1 and Protocol 2), which looked at the
systems in place to support data reporting and the factors impacting the validity and timeliness of data
submissions, respectively.
The DQA exercise was conducted by HFG as an audit using a purposive sample of 10 health facilities
across the four districts of Bhiwani, Narnaul, Mewat, and Palwal. At each of the facilities visited, the
DQA team examined the systems in place to support data reporting and validated the accuracy and
timeliness of reporting of four indicators with multiple data elements monitored by NRHM to track
RMNCH+A progress. In addition, discussions with the Haryana NRHM M&E staff provided insights into
the reporting of data into the national HMIS web portal after initial compilation of data in the District
Health Information System 2.0 (DHIS 2.0). The findings from the qualitative components of the DQA
exercise are visually summarized in the spider graph shown below, which resulted from data gathered
using Protocol 1. The spider graph, where a 3 is the best possible score and a 1 the lowest, shows that
the Data Management Processes were the weakest overall component evaluated with a composite score
of 1.90, while Monitoring and Evaluation Structure, Functions and Capabilities scored the highest with a
2.74 rating.
1 NRHM has been merged with the National Urban Health Mission to be known as the National Health Mission; NRHM is
maintained throughout the report as it reflects the status of the agency during the study period.
vii
12. Figure 1: Spider Graph of Protocol 1 Summary
Presented here is a brief summary of the findings and recommendations, sorted by the five domains
evaluated in the DQA exercise:
M&E Structure, Functions, and Capabilities
There is a clear assignment of duties for data management and reporting within health facilities,
including the review of data for consistency prior to submission into the DHIS 2.0, although there
are no formal written job descriptions for Information Assistants.
Health facilities are consistently staffed with and well-supported by a cadre of Information Assistants
who have been trained on the use of the DHIS 2.0.
Once data are entered into the DHIS, there is very little feedback to health facility staff on the
impact, quality or utility of the data being reported. The absence of a routine monitoring and
feedback loop leads to a disconnect between the data compilers and the data being reported.
Data are rarely being used by health facilities to track their own progress over time and/or to
engage with their target populations to better meet their catchment area’s needs.
Indicator Definitions and Reporting Guidelines
While written guidelines and data definitions have been compiled and distributed across districts,
copies of the written guidelines are not available to the staff recording routine data at the health
facilities and few of them have been formally trained on the indicators.
For some indicators (e.g., ‘newborns less than 2.5 kg’ and ‘women with obstetrical complications’),
unclear definitions directly led to inaccurate data being reported. In one case it resulted in the
viii
13. -
wrong indicator being reported as the units counted were ‘pills distributed’ rather than the ‘number
of women receiving the pills.’
For the indicators reviewed, there are mixed results with data validity. Using a verification factor
that reflects over-reporting (greater than 1.0), under-reporting (less than 1.0) or an accurate match
(exactly 1.0) between counted and reported, the following were the overall data validation results:
Table 1: Verification Factor for DQA Indicators
Facility Name
Institutional
Deliveries to
ANC
Registrations
Newborns
Weighing less
than 2.5kg to
Newborns
Weighed at Birth
Cases of
pregnant women
with obstetric
complications
and attended at
public facilities to
reported
deliveries
Post Partum
Sterilization as a
ratio to Total
Female
Sterilization
Bhiwani District
Hospital
1.00 1.00 1.00 1.00
CHC Loharu 1.00 1.00 1.00 1.00
CHC Tosham 1.00 0.65 N/A 1.13
Narnaul District
Hospital
0.99 0.97 1.00 0.95
CHC Kanina N/A N/A 1.00 1.00
CHC Nangal
Choudhary
1.00 0.38 1.00 1.00
Mewat District
Hospital
1.00 0.53 0.61 1.00
CHC Ferozpur
Zirka
0.98 1.05 N/A N/A
CHC Nuh 0.88 0.42 2.82 N/A
CHC Hathin 1.07 1.00 N/A N/A
ix
14. Data Collection and Reporting Forms / Tools
The use of the DHIS 2.0 for reporting purposes streamlines and simplifies the data aggregation
process within districts and across the state.
All facilities visited have sufficient information technology infrastructure in place to support the
routine reporting of data, including working computers and regular access to the Internet.
Although the DHIS 2.0 is uniformly being used for reporting data, there is a wide variation among
health facilities with regard to the source documents being utilized. Standard, pre-printed registers
for data collection are not available to most health facilities, resulting in multiple reporting formats
and increasing the possibility of data reporting errors.
Data Management Processes
Staff members responsible for collecting and recording data to the source documents (i.e. individual
patient records and/or consolidated registers) are performing well given the absence of formal
training and notable resource constraints.
Reporting deadlines are widely known and consistently followed across most health facilities visited.
However, the timeliness of reporting submission from the health facilities could not be documented
during the DQA exercise due to the absence of DHIS 2.0 generated reports showing which facilities
submitted their reports on time for the review period. This functionality does exist within the DHIS
2.0 but is not being effectively utilized.
Links with National Reporting System
Due to the lack of compatibility between the DHIS 2.0 and the national HMIS web portal, extensive
data management activities must take place at the state level in order to comply with the GoI
reporting requirements.
The existence of multiple information systems at the health facility level (i.e. DHIS and Mother and
Child Tracking System) leads to duplicative data entry and extra workloads on data reporting staff.
RECOMMENDED WAY FORWARD
The distribution to all health facilities of written indicator definitions, data reporting guidelines, and
standardized RMNCH+A registers (in both English and Hindi) will likely improve data consistency.
Development and implementation of a routine data reporting training plan will likely increase the
understanding and knowledge of health facility staff on the indicators they are reporting.
Establishment of a routine data feedback mechanism by the Haryana NRHM to all facility staff
involved in the collection, recording, and compilation of facility data can improve the likelihood that
data will be used by the health facilities. Implementation of the data feedback mechanism could be
rolled out with the routine training discussed above.
Implementation of a routine data quality assessment process within the existing NRHM supportive
supervision structure by the District M&E Officers may facilitate regular dialogue on data and open
opportunities for data usage.
x
15. Recognizing that this effort is beyond the state NRHM controls, the development and
implementation over the long-term of a nationally integrated electronic health information system
based on unique patient identifiers, unique health facility identifiers, and patient-level data captured
on a daily basis may eliminate some of the duplicative reporting and the time associated with those
processes. The GoI has the resources, technology, and skills to implement such a system with the
appropriate level of prioritization from the national level.
Overall, the Haryana NRHM health facilities are leveraging limited resources to routinely compile and
report required data. Data-gathering burdens on service delivery staff are very high given the volume of
indicators required to be reported and the lack of staff dedicated exclusively to the recording of facility
data. Data quality can likely be improved with the implementation of several key interventions requiring
a moderate increase in resources. The opportunity exists for Haryana NRHM to significantly improve
the reporting of health data so that indicators tracking progress toward the key Millennium
Development Goals of reduced maternal and infant mortality are more readily available and trusted to
inform decision-making around improving the impact of the RMNCH+A initiative.
xi
16.
17. 1. INTRODUCTION
The Government of India’s strategic approach to the Reproductive, Maternal, Newborn, Child and
Adolescent Health (RMNCH+A) initiative is based on the central tenets of equity, universal access to
care, entitlement, and accountability. Furthermore, it envisions a comprehensive continuum of care with
integrated service delivery at various life stages: adolescence, pre-pregnancy, childbirth and the postnatal
period, childhood, and through the reproductive ages. Within each of the RMNCH+A program areas, a
set of priority interventions shown to have a notable impact are being rolled out across India, with
emphasis on a set of 184 high-priority districts with high maternal and child morbidity and mortality
indicators. The National Rural Health Mission (NRHM) has been tracking a set of 16 indicators that
measure the impact of these interventions and is promoting the use of a dashboard based on data
generated by the Health Management Information System (HMIS). The dashboard seeks to improve
state accountability for RMNCH+A indicators and catalyze states into using the HMIS data for improved
decision-making. Figure 2 shows the indicator set in relation to the RMNCH+A continuum of care
structure.
Figure 2: NRHM Indicators in Relation to the RMNCH+A Continuum of Care
Note: ANC = antenatal care, IFA = iron folic acid, TT = tetanus toxoid, SBA = skilled birth attendant, IUD = intrauterine device
1
18. Monitoring of the RMNCH+A strategy is not solely based on data from the national HMIS. A set of 19
outcome and service coverage indicators related to health, nutrition, and sanitation are drawn from
various national and subnational surveys and are supposed to be reviewed on an annual basis. Although
much of the data from these surveys are captured by the HMIS (e.g. maternal mortality rates and
immunization coverage) concerns with HMIS data quality prompt the utilization of alternative data
sources for program planning and decision-making. The District Health Information System (DHIS) 2.0 is
used by health facilities to report their data electronically up to the State NRHM level; district-level
information (i.e. all health facilities within a district) is automatically aggregated within the system. At the
state level the NRHM team is using DHIS 2.0 monthly data to create the RMNCH+A dashboard.
However, the Information Assistants at the facilities are also required to export their DHIS 2.0 data into
a Microsoft Excel format and then upload it into the national HMIS web portal in order to meet the
national NRHM reporting requirements.
In addition, health facilities are responsible for capturing patient-specific data within the Maternal and
Child Tracking System (MCTS) to track care of pregnant mothers and children. Much of the information
captured in the MCTS could also be used to track the RMNCH+A indicators, yet there is no connection
(electronic or otherwise) between the MCTS, DHIS 2.0 or the national HMIS. The presence of multiple
systems results in significant levels of duplicate data entry at the health facility level and a heavy
reporting burden on both the Auxiliary Nurse Midwives and the Information Assistants, who are
involved in recording and reporting the data, respectively, as represented in the data flow diagram
provided in Figure 2 on the next page.
2
19. -
-
Figure 3: Health Management Information System Data Flow in Haryana
STEPIII
STEPII
STEPI
Primary Health Centre
(PHC and linked HSC)
Parallel Monthly Data Entry in the HMIS Web Portal of
Ministry of Health and FamilyWelfare (MoHFW)
Monthly Data Entry in DHIS 2.0
Haryana Reporting Portal
Health Sub Centres (HSC)
(Primary Data from Multiple Paper Registers,
Uploaded electronically)
Community Health Centre (CHC)
Sub Divisional Hospital
(SDH)
District Hospital
(DH)
STEP I: Facility Wise Data uploaded to the DHIS 2.0 and to the Mother and Child Tracking
System (MCTS)
STEP II: Data downloaded in MS Excel from DHIS 2.0 in MoHFW format for uploading to
national HMIS portal. As there is no electronic bridge between DHIS 2.0 and HMIS, each facility
downloads the monthly data in MoHFW format in MS Excel from DHIS 2.0 every month.
STEP III: Each facility uploads data (exported from DHIS 2.0 in MS Excel format) to the
MoHFW HMIS portal every month by the 5th
of the following month of reporting.
3
20. The Health Finance and Governance (HFG) project, funded by USAID, has been tasked with supporting
six states and territories in India, particularly the RMNCH+A high-priority districts, to strengthen the
domains of health finance, human resources for health and health information systems (HIS). A key
domain within HIS that HFG is supporting is in improving the production and usage of high-quality health
data. At meetings in October 2013, the HFG and Haryana NRHM teams began discussions about
concerns that NRHM had with the quality of data being reported through the state-sponsored DHIS 2.0
and agreed to develop a work plan to implement a data quality audit (DQA) across key districts in
Haryana. This was followed on 4 December 2013 by a workshop in Panchkula with the district health
teams and state NRHM program officers to share the DQA methodology and to develop a timeline for
field visits. The field visits took place during the week of 6 December 2013 and the initial phase of the
DQA exercise concluded with a debriefing in Panchkula for the Mission Director NRHM’s
representative on 13 December 2013.
DQA METHODOLOGY
Reviews in the spring of 2013 by the National Health Systems Resource Centre (NHSRC) in Haryana
noted that there was routine over-reporting of data across many districts in Haryana State. For
example, looking at data reported through the DHIS 2.0 for the period of April 2012–March 2013,
NHSRC found that the Palwal District reported that antenatal care (ANC) registrations were 47
percent higher than the total number of expected deliveries; reported deliveries were 11 percent higher
than expected deliveries; and measles vaccines administered were 16 percent higher than the number of
live births reported. Overall, NHSRC found that only one district (out of 21 in Haryana) did not have
reported occurrences (e.g. immunization rates, deliveries, children weighed) higher than their population
totals.2
An effective means to evaluate the validity of data generated by a routine HIS in compiling and reporting
health information system is to perform a DQA. The DQA methodology, as implemented in Haryana by
HFG India, was designed to accomplish the following tasks:
Verify that appropriate data management systems are in place in Haryana;
Verify the quality of reported data for key RMNCH+A indicators at selected sites; and
Contribute to monitoring and evaluation (M&E) systems strengthening and capacity building for
NRHM.
The DQA methodology used in Haryana is based on two distinct protocols built into a Microsoft Excel
template; the methodology was first piloted in mid-2006 by a group of international partners including
the President’s Emergency Plan for AIDS Relief (PEPFAR), the United States Agency for International
Development (USAID), the World Health Organization, the Global Fund to Fight Tuberculosis, AIDS,
and Malaria and the MEASURE Evaluation project.3 Protocol I is intended to assess the underlying
systems and structures supporting the flow of health data through the routine NRHM reporting system,
while Protocol 2 is intended to assess, on a limited scale, if health facilities are collecting and reporting
data in an accurate and timely manner.
2 National Health Systems Resource Centre, HMIS Analysis: Haryana – Palwal – April 2012 – March 2013 (, National Health
Systems Resource Centre, May 2013).
3 Data Quality Tool: Guidelines for Implementation, MS-08-29, 2008.
4
21. Figure 4: The Five Domains of the Monitoring and Evaluation System
M&E Structures,
Functions and
Capabilities
Indicator
Definitions and
Reporting
Guidelines
Data Collection and
Reporting Forms
and Tools
Data
Management
Processes
Links with
National
Reporting System
Protocol 1 is comprised of a series of questions across five domains that support the M&E system
(Figure 4). The full set of 39 questions can be found in Annex I. Answers to the questions in Protocol 1
across these categories provide a systematic way to catalogue common issues found across multiple
facilities and to compile recommendations for system improvements. Protocol I includes such questions
as: whether or not staff had written copies of data definitions; whether written manuals documenting
how to compile data and how the electronic reporting tools function had been distributed to each and
every facility; and whether the appropriate and routine training had been provided to staff to build their
capacity. The overall objective of this Protocol is to document whether the appropriate system
structures are in place to promote the collection and reporting of high-quality data on a timely basis.
Each question is then scored by the reviewer using a three point rating scale. Full compliance with the
elements of a question elicits a “Yes, completely” response and equates to a 3 score. “Partly” refers to
some criteria for a given measure being met and equates to a 2. “No – not at all” is used when none of
the criteria for a question are met by the health facility, district team or, as applicable, by the state level
NRHM team, and results in a score of 1. Each question can also be marked “N/A” by the reviewer if it is
not applicable, which will keep that specific question from being used to calculate the resulting DQA
scores by category.
Protocol 2 focuses on verifying that the data being captured at the facility level (i.e. on source
documents used by health facility staff and ultimately entered into the DHIS 2.0) are consistently
compiled on an accurate and timely basis. In Haryana, the DHIS 2.0 electronic reporting system allows
each health facility with an internet connected computer and a user identification for the DHIS 2.0 to
directly enter their facilities monthly report. The DHIS 2.0 electronically stores the information by
facility, but has been programmed to compile district level reports by aggregating data from all health
facilities within the district. Thus, for Protocol 2, the DQA teams reviewed reports of the selected
DQA indicators generated by the DHIS 2.0 for each of the facilities and then conducted field visits to
the facilities to review the source documentation for those indicators. In most cases, the field visits
5
22. required the DQA teams to review two or three distinct paper registers at the facilities to compare the
individual records for the relevant time periods with the compiled reports from the DHIS 2.0.
INDICATOR SELECTION
To initiate work on the DQA, four indicators were selected for review from the 16 being used for
RMNCH+A benchmarking in Haryana. Each of the indicators selected comprises multiple data elements,
which required the review of multiple data sources at each facility. The following are the indicators that
were used in the DQA exercise, with definitions taken from the Health Programme Managers’ Manual
published by NRHM, and the guidelines for where this data should be recorded at each facility4:
Institutional deliveries to ANC registration
Data sources: Labour Room Register, Delivery Register, Antenatal Register, Pregnancy Register
Newborns weighing less than 2.5kg to newborns weighed at birth
Data sources: Pregnancy Register, Labour Room Register
Cases of pregnant women with obstetric complications and attended at public facilities to reported
deliveries
Data sources: Labour Room Register, In-patient Department (IPD) Register, Obstetric IPD
Register, Obstetric Out-patient Department (OPD) Register
Post-partum sterilization to total female sterilization
Data sources: Family Planning Register, Operation Theatre Register
According to the official definitions provided for the indicators above, examining the selected data
elements could require the review of no fewer than nine different registers (see Findings section for the
full discussions of issues related to indicator definitions). In reality, none of the health facilities visited by
the DQA team maintained distinct registers as defined above. In most cases, there were two or three
registers to review and often these registers had been drawn by hand in empty log books rather than
being pre-printed with the requisite columns, definitions, and guidelines as defined above. In all site visits
the DQA team found that the data being audited was being recorded on the registers, even when they
were printed by hand.
In addition to the facility reviews detailed in Protocols 1 and 2, a number of system assessment
questions were addressed to the District and State Data Officers in order to obtain multiple
perspectives on the data reporting system. The results from each of the interviews and site visits were
compiled to provide a summary overview of the data reporting processes which make up the findings
for this exercise.
4 Service Provider’s Manual: Understanding Health Management Information Systems, Volume I, National Rural Health Mission,
Ministry of Health and Family Welfare, Government of India, Service Provider’s Manual: Understanding Health Management
Information Systems, Volume I (Nirman Bhavan, New Delhi, January 2011).
6
23. SITE SELECTION
The Haryana NRHM data management team classified its districts into four quadrants based on their
performance relative to India as whole against the RMNCH+A indicators for the dashboard as shown in
Figure 5.
Figure 5: NRHM Classification of Districts in Haryana
High Performance Districts Promising Districts
Kaithal, Kurukshetra, Mahendragarh/ Narnaul,
Panchkula, Rohtak
Ambala, Jhajjar, Rewari,
Sirsa, Yamunanagar
Low Performance Districts Very Low Performance Districts
Faridabad, Gurgaon, Jind,
Karnal, Sonipat
Bhiwani, Fatehabad, Hisar,
Mewat, Palwal, Panipat
Source: HMIS Data April 2012- March 2013
The DQA team proposed using a purposive selection process that would stratify facilities from across
Haryana based on the varying volumes of services and ensuring that most were relevant to the
indicators selected (i.e. not all intensive services, such as complicated pregnancies, are managed at
lower-level facilities). As it turned out, there were some facilities visited for which the indicators were
not relevant (in the case of ‘post-partum sterilizations’) due to community preferences rather than the
service not being offered. Discussions between the NRHM State Program Managers and the DQA team
led to the selection of three Very Low Performance Districts (Bhiwani, Mewat, and Palwal) and one
High Performance District (Mahendragarh/Narnaul) in order to provide a varied, but not fully random
or representative sample. A total of 10 health facilities from across these four districts were selected to
allow for multiple facility types to be included in the sample. Based on discussions with the State NRHM
team, the accessibility of the facilities within the time available to the DQA team (limited to one week of
field visits) was used to determine the sites to visit.
The Haryana state Data Manager facilitated introductions of the DQA teams to the M&E Officers from
each district, who in turn arranged for the two DQA teams to visit the selected district hospitals and
community health centers (CHCs) during the week of 6 – 11 December 2013.
7
24. Table 2: Site Visit Schedule
Facility Name
Bhiwani District Hospital
District
Bhiwani
Date of Visit
6 December 2013
CHC Loharu Bhiwani 7 December 2013
CHC Tosham Bhiwani 7 December 2013
Narnaul District Hospital Narnaul 9 December 2013
CHC Kanina Narnaul 9 December 2013
CHC Nangal Choudhary Narnaul 9 December 2013
Mewat District Hospital Mewat 10 December 2013
CHC Ferozpur Zirka Mewat 10 December 2013
CHC Nuh Mewat 10 December 2013
CHC Hathin Palwal 11 December 2013
8
25. 2. DATA QUALITY AUDIT FINDINGS
The Haryana DQA exercise resulted in a relatively uniform set of findings across the sites visited.
Overall, data are being reported on a timely basis with all staff involved in the process aware of the
deadlines and required formats for monthly reporting of data. All facilities use the DHIS 2.0 electronic
web portal to transmit monthly data, submitted by a trained Information Assistant specifically assigned
to each health facility. The DQA team found no significant reports of problems in accessing the DHIS
2.0 or with the computers and IT infrastructure used to conduct the monthly reporting exercises.
As noted in the methodology section, the DQA tools score each facility based on answers to questions
on a 1-3 point scale, with 1 being the lowest. Provided below in the Table 3 is a numerical
representation of the qualitative findings from Protocol 1 (shown in Appendix 1). The table is color-
coded based on the 1-3 ratings to Protocol 1 questions as follows:
Color Code for Protocol 1 ratings
Green 2.5 - 3.0 Yes, completely
Yellow 1.5 - 2.5 Partly
Red 1.0 - 1.5 No - not at all
Overall, Section IV, Data Management Processes, was the lowest scoring component of the review. This
reflects, in large part, the absence of routine data quality reviews, the use of nonstandardized (and in
many cases handwritten) registers and the absence of unique identifiers across health facilities to track
patients and avoid potential double counting. These are structural components of the reporting system
that have a direct impact on the compilation and reporting of data across the system.
Table 3: Assessment of Data Management and Reporting Systems
Facility Name
M&E
Structure,
Functions and
Capabilities
Indicator
Definitions
and Reporting
Guidelines
Data Collection
and Reporting
Forms/Tools
Data
Management
Processes
Links with
National
Reporting
System
Average
(persite)
Bhiwani District
Hospital
3.00 3.00 2.67 1.80 2.50 2.59
CHC Loharu 3.00 2.00 2.33 2.60 2.25 2.44
CHC Tosham 2.67 2.25 2.33 2.00 2.00 2.25
Narnaul District
Hospital
2.33 2.00 2.00 1.60 1.75 1.94
CHC Kanina 3.00 2.00 2.33 1.40 2.00 2.15
CHC Nangal
Choudhary
2.67 2.00 2.33 2.25 2.00 2.25
Mewat District
Hospital
2.67 2.00 2.00 2.00 2.25 2.18
CHC Ferozpur Zirka 2.67 1.50 2.33 1.80 1.75 2.01
CHC Nuh 3.00 2.00 2.33 1.80 1.75 2.18
CHC Hathin 2.67 3.00 2.67 2.00 2.50 2.57
Average (per
functional area)
2.74 2.13 2.36 1.90 2.10 2.25
9
26. The highest-scoring component overall was Section I, M&E Structure, Functions, and Capabilities, which
is largely due to the use of the DHIS 2.0 at all facilities and districts, the ability of staff to easily navigate
the system, and the consistent availability of access to the DHIS 2.0 via computers and Internet
connections. The DQA team also found that the DHIS 2.0 facilitates the compilation of data across the
NRHM system as a number of the 16 indicators used in the RMNCHA+A dashboard are automatically
calculated rather than requiring the health facility staff to calculate them on their own. For example, the
“Number of cases of pregnant women with obstetric complications and attended at public facilities” is
automatically calculated from the sub-data elements comprising “obstetric complications: those treated
with antibiotics, those treated for eclampsia, those treated with antihypertensive injections, those
receiving blood transfusions after having severe anaemia (Hb < 7 mg),” and those “receiving 100 IFA
tablets to treat iron deficiencies.” This automatic aggregation simplifies the reporting process and
minimizes potential aggregation errors.
Based on the implementation of Protocol 1, the following are the findings, by domain:
M&E Structure, Functions, and Capabilities
District hospitals and CHCs are well supported by trained Information Assistants. The Information
Assistants were clear about the timeframes, tools, and process for compiling monthly data and
entering that data into the DHIS 2.0.
Duties for data management, reporting, and review of data prior to submission are clearly assigned.
While none of the health facilities visited had written job descriptions, there was no confusion as to
who was responsible for data capture, review, and reporting.
At all of the facilities visited, the computer and Internet connections were found to be in working
order with no significant reports of system outages.
While there is regular reporting of information up from the facilities, there is a clear lack of routine
feedback to facilities on the data that they have reported.
In line with the prior finding, there is also minimal use of gathered information at the facility level for
reviewing such targets as population coverage for immunizations or outreach for various services.
These two findings appear to be a function of district-facility interactions, rather than of DHIS 2.0
functionality, as the monthly reports can be directly accessed by facility level staff if they so choose.
Indicator Definitions and Reporting Guidelines
Submission dates and processes were found to be well known and followed; written reporting
guidelines, however, are not widely distributed. There were several reports of the guidelines having
been distributed at some point, but none of the facilities visited could provide the DQA team with a
copy of these guidelines.
There were found to be varying interpretations of indicator definitions among the reporting staff at
the sites visited. For example, for the indicator “Newborns Weighing less than 2.5 kg to Newborns
Weighed at Birth” staff members at some facilities were including newborn weights of 2.5 kg exactly
within the numerator, while the definition clearly states only those weighing less than 2.5 kg.
In another example, the “obstetric complications” indicator as defined did not directly correspond
to the reporting formats on the monthly HMIS forms. The definition focuses on the diagnosis and
provides examples of symptoms that qualify as complications: eclampsia, obstructed labor and acute
anemia are examples. The monthly HMIS reporting forms, however, use the aggregation of
treatments for complications: provision of hypertensive pills, distributing IFA tablets and conducting
blood transfusions. The DQA exercise team further noted confusion among a number of facility staff
10
27. surrounding the units of measure to be reported. Whereas “obstetric complications” calls for the
number of women treated to counted, some facilities were found to be counting, for example, the
number of pills distributed to the women instead. This would essentially invalidate the data being
reported and should be corrected as soon as possible.
Data Collection and Reporting Forms / Tools
The DHIS 2.0 and the monthly HMIS forms used to compile data for entry into the DHIS 2.0 were
found to be consistently used across all the facilities visited.
However, there was no uniformity found among the source registers used at the service delivery
sites visited. Only one of the sites visited was found to have pre-printed forms to use for data
capture of monthly pregnancies and deliveries. All other sites were using either blank registers
modified by hand to record information, or existing registers created for another purpose (e.g.
Medical Store Supplies) that were modified by adding columns and rows as needed. With the hand
printed registers, the relevant data was consistently available for review by the audit team.
In line with the prior finding, recording practices on source documents varies widely across the sites
visited. For example, some weights of newborns were recorded with two decimal places, while
others used only one (i.e., 2.1 versus 2.15). This may be due to the lack of standardized forms
(registers) in use and the absence of written indicator guidelines distributed across facilities.
Data Management Processes
The staff at the facilities generally demonstrated the capacity to compile data, as required. There
were, however, some cases noted of miscounting due in part to the non-standardized registers and
inconsistencies with alignment of reporting periods.
Data confidentiality appears to be effectively maintained; data registers are uniformly maintained in a
locked room after clinical hours. However, a number of staff noted concerns with not having a
defined location for the routine storage of patient records.
There are no unique facility identifiers in use with the reporting system. A cursory review of the
DHIS 2.0 by the DQA auditors did not reveal any obvious duplication of facility names. Given that
there are more than 24,000 primary health clinics in India5, however, there exists a possibility of
duplicating names within the reporting systems at some point, particularly as they either come on
line or are removed from the health system.
Links with National Reporting System
There is a mixed finding with regard to linkages to the national reporting system. There is a clear
and consistent link to national reporting system via the DHIS 2.0 with regard to the data elements
captured and the timelines for reporting. However, there is no system interoperability between the
DHIS 2.0 and the national HMIS web portal, which leads to a complex process of data exports from
the DHIS 2.0 at the state level in order for the national HMIS reporting to be completed.
5 All India Health Status Report, as of 31 December 2013, NRHM website: http://nrhm.gov.in/images/pdf/mis-report/Dec-
2013/1-NRHM.pdf
11
28. In addition, there is significant duplicative data capture for the DHIS 2.0 and the MCTS, which is
burdensome for the staff at the health facility level. While the MCTS appears to capture a significant
portion of the data that is also reported through the DHIS 2.0 (not verified by the DQA team during
this exercise, however), there is no electronic interface between the two systems. Streamlining the
MCTS, the DHIS 2.0, and the national HMIS data capture and transfers would significantly reduce
the duplication of effort across the health system.
The following findings are a result of the implementation of Protocol 2 during the DQA exercise, which
entails validation of reported data versus re-counted data and reviewing the timeliness of data reporting.
The latter component could not be reviewed during the DQA exercise as no logs from the DHIS 2.0
were available to the audit team to review reporting timeliness.
Source Documents
During the site visits by the DQA team, most source documents for the indicators being reviewed
were readily available at the facilities for the audit period in question, in spite of the fact that the
facilities were not using standardized, pre-printed registers.
Although they were not uniform in their structures, the registers reviewed were generally complete
and well-kept by the staff at the facilities. While reviewing the handwritten documents, the DQA
team had only moderate trouble interpreting some of the results and in most cases all of the
required data elements for the indicators under review were captured.
As noted above, the lack of standardized source documents with clearly written indicator definitions
has an impact on the understanding of how and what the staff are responsible for counting for each
indicator, which ultimately impacts the data quality.
Indicator Validations
When reviewing the source documents at facilities and comparing the data counts to the reports
generated by the DHIS 2.0 for the same period, most facility counts were found to match within a
relatively small range of variation (plus/minus 10 percent).
Those errors that were identified were typically based on varying understandings of the indicator
definitions rather than an inability to accurately tally the totals for data elements. For example, in the
summary table provided below (Table 5) for the validation checks conducted of the indicator on
“obstetric complications” reviewed during the DQA exercise, one CHC was found to be counting
the wrong units (“number of pills dispensed” versus “women experiencing complications”).
Provided below are the summary tables of the data validations conducted. The table columns show:
the facility name, the verified counts by the auditors, the reported counts from the DHIS 2.0 and a
verification factor that reflects over-reporting (greater than 1.0), under-reporting (less than 1.0) or
an accurate match (exactly 1.0) between counted and reported.
There were no major validation discrepancies found for the indicator in Table 4, “institutional
deliveries to ANC registrations.”
12
29. Table 4: Trace and Verify: Institutional Deliveries to ANC Registrations
Facility Name Verified Counts at
Audited Sites
Reported Counts at
Audited Sites
Site Verification
Factor
Bhiwani District Hospital 356 356 1.00
CHC Loharu 10 10 1.00
CHC Tosham 28 28 1.00
Narnaul District Hospital 663 670 0.99
CHC Kanina 0 0 -
CHC Nangal Choudhary 53 53 1.00
Mewat District Hospital 154 154 1.00
CHC Ferozpur Zirka 194 197 0.98
CHC Nuh 180 205 0.88
CHC Hathin 223 208 1.07
Table 5 below reflects several major data collection errors on validations of “newborns weighing
less than 2.5 kg to total newborns,” each with a unique set of reasons:
Missing one underweight newborn at CHC Kanina meant a 100 percent reporting discrepancy.
CHC Nangal Choudry reflects that they were using a reporting period from the 29th of one
month to the 28th of the next, rather than the calendar month. Thus, when compared with the
DQA team’s count of the calendar month, there was a discrepancy.
CHC Nuh was stopping their counts before the end of the calendar month in order to review
the monthly data internally with their teams before submitting. This resulted in a discrepancy
when compared to the calendar month tally conducted by the DQA team.
Mewat District Hospital’s discrepancy resulted from a listing in the Admissions-Discharge
register of data ranges for weights (e.g., <1 kg, 2-2.5 kg, 2.5-3.0 kg.) rather than recordings of
the actual weight in kilograms. When staff used the weight ranges, they included those
newborns whose actual weight was exactly 2.5 kg, which, according to the official indicator
definition, should not be included as underweight. This resulted in reporting of the wrong
indicator for this component and should be corrected as soon as possible.
The reason for the discrepancy noted at CHC Tosham could not be readily identified during the
DQA team’s site visit.
13
30. Table 5: Trace and Verify: Newborns Weighing Less than 2.5 kg to Total Newborns
Facility Name
Verified Counts at
Audited Sites
Reported Counts
at Audited Sites
Site Verification
Factor
Bhiwani District Hospital 10 10 1.00
CHC Loharu 2 2 1.00
CHC Tosham 11 17 0.65
Narnaul District Hospital 113 117 0.97
CHC Kanina 1 0 --
CHC Nangal Choudhary 5 13 0.38
Mewat District Hospital 46 86 0.53
CHC Ferozpur Zirka 23 22 1.05
CHC Nuh 8 19 0.42
CHC Hathin 20 20 1.00
For the most part, data for the indicator “Cases of Pregnant Women with Complications and
Attended at Public Facilities to Reported Deliveries” showed only minor discrepancies.
CHC Nuh (noted with a * in Table 6) was found to be counting the wrong units (“number of
pills dispensed” versus “women experiencing complications”) for this indicator. While the Trace
and Verify notes over-reporting of the indicator, in fact, the wrong data was reported.
Table 6: Trace and Verify: Cases of Pregnant Women with Complications and
Attended at Public Facilities to Reported Deliveries
Facility Name
Verified Counts at
Audited Sites
Reported Counts
at Audited Sites
Site Verification
Factor
Bhiwani District Hospital 290 290 1.00
CHC Loharu 10 10 1.00
CHC Tosham 0 0 --
Narnaul District Hospital 45 45 1.00
CHC Kanina 32 32 1.00
CHC Nangal Choudhary 0 0 --
Mewat District Hospital 11 18 0.61
CHC Ferozpur Zirka N/A N/A N/A
CHC Nuh 141 50 2.82*
CHC Hathin 0 0 --
14
31. There were no major validation discrepancies found for the indicator “postpartum sterilizations to
total sterilizations”:
Table 7: Trace and Verify: Postpartum Sterilizations to Total Sterilizations
Facility Name
Verified Counts at
Audited Sites
Reported Counts
at Audited Sites
Site Verification
Factor
Bhiwani District Hospital 73 73 1.00
CHC Loharu 0 0 --
CHC Tosham 18 16 1.13
Narnaul District Hospital 55 58 0.95
CHC Kanina 10 10 1.00
CHC Nangal Choudhary 23 23 1.00
Mewat District Hospital 10 10 1.00
CHC Ferozpur Zirka 0 0 --
CHC Nuh 0 0 --
CHC Hathin 0 0 --
15
32.
33. 3. RECOMMENDATIONS AND NEXT STEPS
There are a number of clear recommendations emanating from the DQA exercise undertaken by HFG
in December 2013. The key findings described above showed both consistent strengths within the
NRHM reporting system, as well as addressable gaps. The following is a set of recommendations and
next steps suggested for Haryana NRHM to continue strengthening the quality of data reported through
the HIS.
M&E Structure, Functions, and Capabilities
Develop training plan for districts and health facilities
As the written guidelines are distributed, a training plan to reinforce the reporting guidelines
should also be developed and implemented. Individuals involved in recording data should receive
an initial training upon assuming their data reporting roles and should also be routinely updated
as indicators, definitions, or timelines are updated.
Part of the training program for health facility staff should focus on the indicator definitions, how
to properly calculate them and how to interpret them. The Service Provider’s Manual developed
by the central NRHM offices provides useful tools and exercises to promote the understanding
and recording of accurate indicators. However, these manuals are not available to health facility
staff as either reference or training tools.
Additionally, the trainings should demonstrate to program staff how to use data at the facility
level. For example, using local population data to define target health impacts, creating simple
charts and graphs to track services and targets over time, and comparing data across health
facilities in order to benchmark performance are all effective ways of promoting the use of
information collected at health facilities.
Provide regular feedback on data submitted into DHIS 2.0
Establishing routine data review mechanisms, such as a quarterly review of data at the district
level with representatives of local health facilities (e.g. Medical Officers in charge or Information
Assistants), will provide an opportunity to highlight data trends (positive, negative, or potential
anomalies), concerns that may exist with data quality/timeliness, and to provide constructive
feedback to the staff compiling and reporting the data.
Developing a log system for recording data changed after submission will help document routine
issues that arise and verify the means by which issues have been addressed.
The Haryana NRHM has recently embarked on an effort to promote the usage of data for
addressing implementation research questions. This effort is believed likely to positively impact
both the reporting of data and the usage side of data for program improvement.
Implement pop-up windows or “help” section within DHIS 2.0 that would allow users to review
the data definitions and reporting guidelines as they are entering data. It could be implemented
as a full online guide or tagged to specific fields of relevance.
17
34. Indicator Definitions and Reporting Guidelines
Provide clearly written indicator definitions and reporting guidelines to all facilities
The written guidelines should include clear due dates for each facility, to whom information
developed by the central NRHM team should be distributed beyond the district levels to ensure
that all health facilities have been trained on them and have them readily available for reference.
A number of indicator definitions reviewed by the DQA team need clarification. Some are not
well matched to the reporting requirements (e.g. obstetric complications), while others are
being misinterpreted by the reporting staff (e.g. newborns weighing less than 2.5 kg).
Distributing a revised set of written indicator definitions will help to standardize the recording
and reporting of data. The following is a detailed summary of the indicators reviewed during the
DQA exercise that would benefit from refinement and clarification to all staff:
Cases of pregnant women with obstetric complications and attended at public facilities to
reported deliveries
[Cases of pregnant women with obstetric complications and attended]
[Reported deliveries]
18
35. Concern(s) with current definition:
The subcomponent “obstetric complications” is vaguely defined. Examples are provided but even
they are sometimes misinterpreted by those recording the indicator. The list should be expanded
and definitions of complications should be more detailed and clear. Reviews of the data registers at
several health facilities indicated inconsistent interpretation of the term “obstetric complications.”
For some examples provided in the manual, such as “eclampsia,” there is no clinical description.
On the reporting forms, the “Number of eclampsia cases managed during delivery” and “Number
having Hb level <11 (tested cases)”’ are shown in section M1, “Ante Natal Care Services.” However,
“Number of Complicated Pregnancies treated with [IV antibiotics], [IV antihypertensive/magsulph
injection], [IV oxytocin], and/or [blood transfusion]” are in section M5, “Complicated pregnancies.”
This shows that the guidelines reflect the definitional diagnosis while the reporting forms
reflect the possible treatments.
Some facilities considered “total number of pregnant women given 100 IFA tablets” to be included
in the “Number of Complicated Pregnancies….” indicator. However, rather than reporting the
number of pregnant women treated, they reported the number of pills distributed to
pregnant women, which would clearly result in the reporting of the wrong indicator.
Recommendations:
Provide a comprehensive checklist of clinical conditions that are classified as meeting the definition
of “obstetric complications” so that labor room teams can actively and rapidly record the data in the
register.
Consolidate within one section of the reporting forms where the various types of “obstetric
complications” are listed so that tallies are more accurate.
Institutional Deliveries to ANC Registration
[Institutional Deliveries]
19
36. [ANC Registration]
M1 Antenatal Care Services (ANC) is the health care a woman receives during pregnancy.
ANC starts with ‘history-taking’ and is followed by examination of the woman, which
includes recording weight and height, doing a blood test for anaemia, measuring blood
pressure, and doing a regular abdominal examination as per the guidelines. The woman is
advised for diet, regular antenatal check-ups, and counseled for family planning. She is also
provided with immunisation for TT and IFA tablets along with proper treatment required in
case of any complication.
Ideally, as per the Reproductive and Child Health Programme schedule, the first ANC
check-up is to be done within 12 weeks, preferably as soon as the pregnancy is suspected,
the second ANC check-up between 14 and 26 weeks, the third between 28 and 34 weeks,
and the fourth between 36 and 40 weeks, but due to unawareness, mobility, distance, and
so forth, the timing for the check-ups may vary.
Concern(s) with current definition:
One challenge with this indicator is that deliveries take place at higher level care facilities with
obstetrical beds, while ANC registrations take place at a much broader range of facilities, including
those without obstetrical services. Because of this, there may or may not be a correlation between
the number of women registered for ANC services and the number of deliveries conducted at any
given facility.
The ANC registration definition indicates that only new pregnant women registering for ANC
services that month should be included in the count. However, most of the registers reviewed
during the DQA exercise used unofficial or adapted registers made by facility staff that did not
distinguish between first, second, or subsequent ANC visits. For the DHIS 2.0 and HMIS web portal
reporting, the staff members use the registers for data consolidation, not the MCTS, which creates a
tracking sheet for the ANC visits.
Recommendation:
Use only standardized, NRHM-issued registers entitled “First ANC visit/registration.”
Newborns Weighing less than 2.5 kg to Newborns Weighed at Birth
[Newborns Weighing less than 2.5kg] / [Newborns Weighed at Birth]
20
37. Concern(s) with current definition:
The definition does not state explicitly whether newborns weighing exactly 2,500 grams (2.5 kg)
should be included in the list of “less than 2,500 grams.” At some of the facilities visited, newborns
weighing exactly 2,500 grams were included while at other facilities they were not.
Recommendation:
Add one line of text to the definition to state: ‘Newborns weighing exactly 2,500 grams’ at birth
should not be included in the totals for ‘less than 2,500 grams.’
Data Collection and Reporting Forms / Tools
Provide proper reporting tools to all district offices and facilities
In accordance with the written guidelines, each facility should be given an adequate number of
the paper registers it needs to report on each service it provides. A comprehensive maternal
and child health register has been developed and distributed to the state-level teams, but these
have not been uniformly distributed across districts and health facilities.
Data Management Processes
Incorporate routine data quality audits as continuous, internal review mechanisms for
facilities
An ongoing, NRHM-driven process to review source-level data across facilities would assist in
identifying and reducing errors in a timely manner. A simple Excel-based Routine Data Quality
Assessment (RDQA) Tool can be used to document structures in place at facilities, review key
indicators for accuracy and develop action plans for improvement where necessary.
The RDQA Tool (or similar approach) can be incorporated into the routine supportive
supervision visit carried out by district-level staff to facilities within their district. This would
allow the NRHM to leverage existing systems and relationships while minimizing the need to
mobilize additional resources.
Links with National Reporting System
Streamline reporting systems
While the electronic data systems used in Haryana eventually feed into the national reporting
system, there are many layers of duplication. The NRHM programs would benefit greatly from
the creation of electronic data interfaces between systems (in the short term) and the
21
38. consolidation of many of the duplicate systems into a single electronic system with patient-level
records (in the long term).
Source Documents
Guidelines on maintain source documents
In all cases during the DQA site visits, the requested source documents reflecting the original
data for the period under review were located and available to the team. However, there do
not appear to be any uniformly followed standards for length of time that source documents are
maintained. NRHM should provide guidelines on timelines for maintaining such records.
Indicator Validations
The Recommendations provided earlier in this section are likely to address the validation issues raised
during the DQA exercise.
Conclusion
Based on the findings from the DQA exercise conducted by HFG, implementing the recommendations
provided here can systematically improve the quality of data being reported and promote the use of that
information for program planning and M&E for the RMNCH+A strategy. Each activity within the
recommendation that is implemented will move NRHM a step closer to helping the RMNCH+A
approach reach its goal of improving maternal and child health outcomes across Haryana.
22
40. M&EUnit
AggregationLevels
ServicePoints
1
There is a documented organizational structure/chart that clearly identifies positions that have data management
responsibilities at the M&E Unit.
P Yes
2 All staff positions dedicated to M&E and data management systems are filled. P -
3 There is a training plan which includes staff involved in data-collection and reporting at all levels in the reporting process. P Yes
4 All relevant staff have received training on the data management processes and tools. P P P -
5
A senior staff member (e.g., the Program Manager) is responsible for reviewing the aggregated numbers prior to the
submission/release of reports from the M&E Unit.
P -
6
There are designated staff responsible for reviewing the quality of data (i.e., accuracy, completeness and timeliness)
received from sub-reporting levels (e.g., regions, districts, service points).
P P -
7
There are designated staff responsible for reviewing aggregated numbers prior to submission to the next level (e.g., to
districts, to regional offices, to the central M&E Unit).
P P -
8 The responsibility for recording the delivery of services on source documents is clearly assigned to the relevant staff. P -
12 … how (e.g., in what specific format) reports are to be submitted. P P P Yes
13 … to whom the reports should be submitted. P P P Yes
14 … when the reports are due. P P P Yes
15 There is a written policy that states for how long source documents and reporting forms need to be retained. P Yes
LIST OF ALL QUESTIONS - For reference only (Protocol 1 - System's Assessment)
Supportingdocumentationrequired?
I - M&E Structure, Functions and Capabilities
Component of the M&E System
Check mark
indicates reporting
system level at
which the question
is asked
II- Indicator Definitions and Reporting Guidelines
24
41. 16
The M&E Unit has identified a standard source document (e.g., medical record, client intake form, register, etc.) to be
used by all service delivery points to record service delivery.
P Yes
17 The M&E Unit has identified standard reporting forms/tools to be used by all reporting levels. P Yes
18 Clear instructions have been provided by the M&E Unit on how to complete the data collection and reporting forms/tools. P P P Yes
19
The source documents and reporting forms/tools specified by the M&E Unit are consistently used by all reporting
levels.
P P -
20
If multiple organizations are implementing activities under the Program/project, they all use the same reporting forms and
report according to the same reporting timelines.
P P P -
21
The data collected by the M&E system has sufficient precision to measure the indicator(s) (i.e., relevant data are
collected by sex, age, etc. if the indicator specifies disaggregation by these characteristics).
P -
22
All source documents and reporting forms relevant for measuring the indicator(s) are available for auditing purposes
(including dated print-outs in case of computerized system).
P P P -
23
The M&E Unit has clearly documented data aggregation, analysis and/or manipulation steps performed at each level of
the reporting system.
P Yes
24
There is a written procedure to address late, incomplete, inaccurate and missing reports; including following-up with sub-
reporting levels on data quality issues.
P P Yes
25
If data discrepancies have been uncovered in reports from sub-reporting levels, the M&E Unit or the Intermediate
Aggregation Levels (e.g., districts or regions) have documented how these inconsistencies have been resolved.
P P -
26
Feedback is systematically provided to all sub-reporting levels on the quality of their reporting (i.e., accuracy,
completeness and timeliness).
P P -
27
There are quality controls in place for when data from paper-based forms are entered into a computer (e.g., double entry,
post-data entry verification, etc).
P P P -
28
For automated (computerized) systems, there is a clearly documented and actively implemented database
administration procedure in place. This includes backup/recovery procedures, security admininstration, and user
administration.
P P P Yes
29 There is a written back-up procedure for when data entry or data processing is computerized. P P P Yes
30
If yes , the latest date of back-up is appropriate given the frequency of update of the computerized system (e.g., back-
ups are weekly or monthly).
P P P -
31 Relevant personal data are maintained according to national or international confidentiality guidelines. P P P -
IV- Data Management Processes
III- Data-collection and Reporting Forms / Tools
25
42. 32
… within each point of service/organization (e.g., a person receiving the same service twice in a reporting period, a
person registered as receiving the same service in two different locations, etc).
P P P -
33
… across service points/organizations (e.g., a person registered as receiving the same service in two different service
points/organizations, etc).
P P P -
34
The reporting system enables the identification and recording of a "drop out", a person "lost to follow-up" and a person
who died.
P P P -
35
The M&E Unit can demonstrate that regular supervisory site visits have taken place and that data quality has been
reviewed.
P Yes
36 When available, the relevant national forms/tools are used for data-collection and reporting. P P P Yes
37 When applicable, data are reported through a single channel of the national information systems. P P P -
38
Reporting deadlines are harmonized with the relevant timelines of the National Program (e.g., cut-off dates for monthly
reporting).
P P P -
39 The service sites are identified using ID numbers that follow a national system. P P P -
IV- Data Management Processes
V- Links with National Reporting System
The reporting system avoids double counting people …
26