The document describes the development of metadata and data standards for the health domain in India by the Health MDDS Domain Committee. The committee was formed to promote interoperability across health IT systems. It identified over 1000 common data elements across 39 health entities. It defined the data elements and established 111 code directories derived from global clinical coding standards. The standards are intended to enable integration and information exchange between existing fragmented health IT systems in India.
The application of big data in health care is a fast-growing field, with many discoveries and methodologies published in the last five years. Big data refers to datasets that are not only big but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Moreover, medical data is one of the most growing data, as it is obtained from Electronic Health Records (EHRs) or patients themselves. Due to the rapid growth of such medical data, we need to provide suitable tools and techniques in order to handle and extract value and knowledge from these datasets to improve the quality of patient care and reduces healthcare costs. Furthermore, such value can be provided using big data analytics, which is the application of advanced analytics techniques on big data. This paper presents an overview of big data content, sources, technologies, tools, and challenges in health care. It also intends to identify the strategies to overcome the challenges.
In this presentation, Shaheen Gauher talks about two things: (1) How data science and machine learning can be used to manage and control escalating healthcare costs, and (2) How to create a Population Health Management Solution using state of the art Azure Data Lake Analytics and Population Health Report with real time visualization capability using Power BI. The solution presented can be deployed on Azure through a one-click deployment option in https://gallery.cortanaintelligence.com/
Big data is generating a lot of hype in every industry including healthcare. As my colleagues and I talk to leaders at health systems, we’ve learned that they’re looking for answers about big data. They’ve heard that it’s something important and that they need to be thinking about it. But they don’t really know what they’re supposed to do with it.
The application of big data in health care is a fast-growing field, with many discoveries and methodologies published in the last five years. Big data refers to datasets that are not only big but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Moreover, medical data is one of the most growing data, as it is obtained from Electronic Health Records (EHRs) or patients themselves. Due to the rapid growth of such medical data, we need to provide suitable tools and techniques in order to handle and extract value and knowledge from these datasets to improve the quality of patient care and reduces healthcare costs. Furthermore, such value can be provided using big data analytics, which is the application of advanced analytics techniques on big data. This paper presents an overview of big data content, sources, technologies, tools, and challenges in health care. It also intends to identify the strategies to overcome the challenges.
In this presentation, Shaheen Gauher talks about two things: (1) How data science and machine learning can be used to manage and control escalating healthcare costs, and (2) How to create a Population Health Management Solution using state of the art Azure Data Lake Analytics and Population Health Report with real time visualization capability using Power BI. The solution presented can be deployed on Azure through a one-click deployment option in https://gallery.cortanaintelligence.com/
Big data is generating a lot of hype in every industry including healthcare. As my colleagues and I talk to leaders at health systems, we’ve learned that they’re looking for answers about big data. They’ve heard that it’s something important and that they need to be thinking about it. But they don’t really know what they’re supposed to do with it.
Healthcare is changing rapidly. It is clear that humans need mechanisms to automate some parts of data processing and help humans in decision making. This talk will concentrate on how to improve the machine understanding of unstructured data.
Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.
This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.
The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.
Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.
Benefits of Big Data in Health Care A Revolutionijtsrd
Lifespan of a normal human is increasing with the world population and it produces new challenge in health care. big data change the method of data management ,leverage data and analyzing data.with the help of big data we can reduces the costs of treatment, reducing medication and provide better treatment with predictive analytics. Health related data collected from various sources like electronic health record EHR ,medical imaging system, genomic sequencing, pay of records, pharmaceutical research , and medical devices, etc. are refers to as big data in healthcare. Dr. Ritushree Narayan ""Benefits of Big Data in Health Care: A Revolution"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd22974.pdf
Paper URL: https://www.ijtsrd.com/computer-science/data-miining/22974/benefits-of-big-data-in-health-care-a-revolution/dr-ritushree-narayan
This informative webinar features Brian Babineau, Senior Analyst from ESG, who discusses the data management challenges facing healthcare IT professionals. Jamie Clifton from BridgeHead Software concludes with a brief discussion of BridgeHead's healthcare data management solutions, including HEAT, an archiving appliance built with Sun Microsystems.
Clinical Narrative And Structured Data In The Ehr Venus And Mars Live In Harm...Nick van Terheyden
For nearly two decades healthcare technology has attempted to impose new documentation methods that are more suited to database management but do not meet the needs of the busy practicing physician. Conventional wisdom is that documents are bad and discrete data is good but historically clinicians have resisted efforts to establish structured data entry methodologies trying to replace the clinician preferred method of data capture – dictation. Clinical Document Architecture for Common Document Types (CDA4CDT) offers a bridge between the two opposing worlds of clinical documentation creating semantically interoperable data while retaining the precise clinical content contained in free flowing narrative
Data Governance Talking Points: Simple Lessons From the TrenchesHealth Catalyst
About 7 months ago, one of Health Catalyst's clients asked for a 90-minute cram course on data governance, including time for questions and answers. They were struggling, like so many other healthcare organizations, caught in the swing of extremes from too much to too little, while equilibrium eluded them. With a last-minute rush, Dale Sanders (President of Technology, Health Catalyst) fell back on his time in the Air Force and threw together a talking points paper to facilitate the conversation. At the end of the meeting, the client was effusive with their appreciation, using words like “incredibly insightful,” “brilliant,” and “hugely valuable.” Dale didn’t think it was that good, but their data governance function was “dramatically better,” and they were happy, so something worked.
Since then, Dale has used the same talking points in two other similar meetings, with similar feedback and results. It still doesn’t feel that great or insightful to him, but he's glad to flow with the feedback and share the same style in this webinar in the hope that it’s useful.
After viewing this webinar, Dale hopes that you will have some tactical ideas to assess your organization’s data governance strategy. Are you leveraging the data you have? What could improve?
Understanding the Need of Data Integration in E Healthcareijtsrd
This paper discusses the current scenario of e healthcare and different dimensions of Big data in healthcare and the importance of data integration in e health care and the challenges associated with data integration and associated uses of data integration with respect to different use cases which might be helpful to physician's decision making because the data driven decision making involves combination of heterogeneous data which includes Electronic Health Record containing different types of data and connected healthcare organization in order to provide value based connected healthcare which would be useful to primary healthcare center located at different location because patients suddenly expect their healthcare experiences to be as exceptional and as transparent as those of retail or banking, and physician's have to scramble to adjust to these new expectations due to lack of data integrity. Mrs. Shashi Rekha. H. | Dr. Chethana Prakash. M | Dr. K. Thippeswamy "Understanding the Need of Data Integration in E- Healthcare" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31007.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31007/understanding-the-need-of-data-integration-in-e-healthcare/mrs-shashi-rekha-h
The Scope of Health Information Technology: Progress and ChallengesAndrew Oram
Presents an overview of health IT technologies, such as devices, telehealth, electronic health records, analytics, coordinated care, and health information exchange. The goal is not just to list trends but to show their relationships and dependencies, suggest ways they can contribute to improvement in health care, and provide frameworks for understanding their strengths, weaknesses, and impacts.
Interoperability in health care information systemsAlexander Ask
A slide show from our bachelor thesis presentation. Its main focus is interoperability in health care and how interoperability issues can be addressed by open standardization.
THE TECHNOLOGY OF USING A DATA WAREHOUSE TO SUPPORT DECISION-MAKING IN HEALTH...ijdms
This paper describes the technology of data warehouse in healthcare decision-making and tools for support
of these technologies, which is used to cancer diseases. The healthcare executive managers and doctors
needs information about and insight into the existing health data, so as to make decision more efficiently
without interrupting the daily work of an On-Line Transaction Processing (OLTP) system. This is a
complex problem during the healthcare decision-making process. To solve this problem, the building a
healthcare data warehouse seems to be efficient. First in this paper we explain the concepts of the data
warehouse, On-Line Analysis Processing (OLAP). Changing the data in the data warehouse into a
multidimensional data cube is then shown. Finally, an application example is given to illustrate the use of
the healthcare data warehouse specific to cancer diseases developed in this study. The executive managers
and doctors can view data from more than one perspective with reduced query time, thus making decisions
faster and more comprehensive
Digital Tools and Solutions for Healthcare and Pharma from Healtho5Digital MedCom
How can pharma use Digtal Tools for Physican Outreach in India. We at Healtho5 Solutions come up with specific solutions for pharma's digital needs. Mail us at drneelesh@digmed.in or neelesh@healtho5.com
Health Data Exchange:. Still a Pipe Dream? A Presentation from 2009David Lee Scher, MD
This presentation discussing interoperability was given at the European Society of Cardiology in 2009.This remains an important topic for healthcare worldwide. Addendum: All names shown are fictitious and not real patients.
Healthcare is changing rapidly. It is clear that humans need mechanisms to automate some parts of data processing and help humans in decision making. This talk will concentrate on how to improve the machine understanding of unstructured data.
Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.
This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.
The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.
Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.
Benefits of Big Data in Health Care A Revolutionijtsrd
Lifespan of a normal human is increasing with the world population and it produces new challenge in health care. big data change the method of data management ,leverage data and analyzing data.with the help of big data we can reduces the costs of treatment, reducing medication and provide better treatment with predictive analytics. Health related data collected from various sources like electronic health record EHR ,medical imaging system, genomic sequencing, pay of records, pharmaceutical research , and medical devices, etc. are refers to as big data in healthcare. Dr. Ritushree Narayan ""Benefits of Big Data in Health Care: A Revolution"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd22974.pdf
Paper URL: https://www.ijtsrd.com/computer-science/data-miining/22974/benefits-of-big-data-in-health-care-a-revolution/dr-ritushree-narayan
This informative webinar features Brian Babineau, Senior Analyst from ESG, who discusses the data management challenges facing healthcare IT professionals. Jamie Clifton from BridgeHead Software concludes with a brief discussion of BridgeHead's healthcare data management solutions, including HEAT, an archiving appliance built with Sun Microsystems.
Clinical Narrative And Structured Data In The Ehr Venus And Mars Live In Harm...Nick van Terheyden
For nearly two decades healthcare technology has attempted to impose new documentation methods that are more suited to database management but do not meet the needs of the busy practicing physician. Conventional wisdom is that documents are bad and discrete data is good but historically clinicians have resisted efforts to establish structured data entry methodologies trying to replace the clinician preferred method of data capture – dictation. Clinical Document Architecture for Common Document Types (CDA4CDT) offers a bridge between the two opposing worlds of clinical documentation creating semantically interoperable data while retaining the precise clinical content contained in free flowing narrative
Data Governance Talking Points: Simple Lessons From the TrenchesHealth Catalyst
About 7 months ago, one of Health Catalyst's clients asked for a 90-minute cram course on data governance, including time for questions and answers. They were struggling, like so many other healthcare organizations, caught in the swing of extremes from too much to too little, while equilibrium eluded them. With a last-minute rush, Dale Sanders (President of Technology, Health Catalyst) fell back on his time in the Air Force and threw together a talking points paper to facilitate the conversation. At the end of the meeting, the client was effusive with their appreciation, using words like “incredibly insightful,” “brilliant,” and “hugely valuable.” Dale didn’t think it was that good, but their data governance function was “dramatically better,” and they were happy, so something worked.
Since then, Dale has used the same talking points in two other similar meetings, with similar feedback and results. It still doesn’t feel that great or insightful to him, but he's glad to flow with the feedback and share the same style in this webinar in the hope that it’s useful.
After viewing this webinar, Dale hopes that you will have some tactical ideas to assess your organization’s data governance strategy. Are you leveraging the data you have? What could improve?
Understanding the Need of Data Integration in E Healthcareijtsrd
This paper discusses the current scenario of e healthcare and different dimensions of Big data in healthcare and the importance of data integration in e health care and the challenges associated with data integration and associated uses of data integration with respect to different use cases which might be helpful to physician's decision making because the data driven decision making involves combination of heterogeneous data which includes Electronic Health Record containing different types of data and connected healthcare organization in order to provide value based connected healthcare which would be useful to primary healthcare center located at different location because patients suddenly expect their healthcare experiences to be as exceptional and as transparent as those of retail or banking, and physician's have to scramble to adjust to these new expectations due to lack of data integrity. Mrs. Shashi Rekha. H. | Dr. Chethana Prakash. M | Dr. K. Thippeswamy "Understanding the Need of Data Integration in E- Healthcare" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31007.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31007/understanding-the-need-of-data-integration-in-e-healthcare/mrs-shashi-rekha-h
The Scope of Health Information Technology: Progress and ChallengesAndrew Oram
Presents an overview of health IT technologies, such as devices, telehealth, electronic health records, analytics, coordinated care, and health information exchange. The goal is not just to list trends but to show their relationships and dependencies, suggest ways they can contribute to improvement in health care, and provide frameworks for understanding their strengths, weaknesses, and impacts.
Interoperability in health care information systemsAlexander Ask
A slide show from our bachelor thesis presentation. Its main focus is interoperability in health care and how interoperability issues can be addressed by open standardization.
THE TECHNOLOGY OF USING A DATA WAREHOUSE TO SUPPORT DECISION-MAKING IN HEALTH...ijdms
This paper describes the technology of data warehouse in healthcare decision-making and tools for support
of these technologies, which is used to cancer diseases. The healthcare executive managers and doctors
needs information about and insight into the existing health data, so as to make decision more efficiently
without interrupting the daily work of an On-Line Transaction Processing (OLTP) system. This is a
complex problem during the healthcare decision-making process. To solve this problem, the building a
healthcare data warehouse seems to be efficient. First in this paper we explain the concepts of the data
warehouse, On-Line Analysis Processing (OLAP). Changing the data in the data warehouse into a
multidimensional data cube is then shown. Finally, an application example is given to illustrate the use of
the healthcare data warehouse specific to cancer diseases developed in this study. The executive managers
and doctors can view data from more than one perspective with reduced query time, thus making decisions
faster and more comprehensive
Digital Tools and Solutions for Healthcare and Pharma from Healtho5Digital MedCom
How can pharma use Digtal Tools for Physican Outreach in India. We at Healtho5 Solutions come up with specific solutions for pharma's digital needs. Mail us at drneelesh@digmed.in or neelesh@healtho5.com
Health Data Exchange:. Still a Pipe Dream? A Presentation from 2009David Lee Scher, MD
This presentation discussing interoperability was given at the European Society of Cardiology in 2009.This remains an important topic for healthcare worldwide. Addendum: All names shown are fictitious and not real patients.
In this full-day tutorial, you will learn basic overview of electronic medical records systems, health data management and how you can use the OpenMRS system for data and information management. We will cover basics of installation, user management, location management, patient dashboards and some interesting features that are provided by different modules. You can see how OpenMRS can be customized with different modules that are suitable for different contexts. This tutorial is helpful for new users and developers who would like to know the features of OpenMRS. Individuals who would like to evaluate and try to see if OpenMRS fits their healthcare needs will also benefit from this tutorial.
Leveraging emerging standards for patient engagement pchamHealth2015
Patients are playing an increasingly important role in creating relevant healthcare data about themselves using mobile devices and applications. It is important this data can move with them securely throughout a healthcare ecosystem. The increased use of medical devices and mobile applications opens the dialogue around open source and non-proprietary standards with complementing policies.
Introduction to Routine Health Information System SlidesSaide OER Africa
Introduction to Routine Health Information System was created for undergraduate and postgraduate health science students to introduce them to the concepts and methods of routine health information systems.
The learning objectives are to help users explain the roles of routine health information systems (RHIS) in health service management; examine strategies used to improve routine health information systems; acquaint with skills to carry out the process of improving RHIS performance; discuss three categories of determinants that influence RHIS.
A hybrid approach to data management is emerging in healthcare as organizations recognize the value of an enterprise data warehouse in combination with a data lake.
In this SlideShare, we discuss data lakes in healthcare and we:
Provide an overview of a Hadoop-based data lake architecture and integration platform, and its application in machine learning, predictive modeling, and data discovery
Discuss several key use cases driving the adoption of data lakes for both providers and health plans
Discuss available data storage forms and the required tools for a data lake environment
Detail best practices for conducting data lake assessments and review key implementation considerations for healthcare
Browne Jacobson, Deloitte and DoctorLink are pleased to invite you to our first joint health tech seminar with leading industry thought leaders. This will be a practical session, sharing experience from across the NHS and beyond to inform options on how to improve services, break down silos and focus on population health outcomes.
This event is exclusively for Commissioners, GPs, and Policymakers keen to understand how new integrated care systems and models of care can meet the needs of their local population and can be implemented pragmatically and affordably to drive improvement goals and achieve better health, better care and better value.
White paper: Functional Requirements for Enterprise Clinical Data Management:...Carestream
As healthcare organizations plan for the future growth and integration of clinical
data into their IT ecosystems, it’s crucial to clearly define the functional requirements spanning the needs of users across the enterprise. This white paper provides an overview of the key functional requirements. To learn more visit carestream.com/clinical-collaboration
Microsoft: A Waking Giant in Healthcare Analytics and Big DataDale Sanders
Ten years ago, critics didn’t believe that Microsoft could scale in the second generation of relational data warehouses, but they did. More recently, many of these same pundits have criticized Microsoft for missing the technology wave du jour in cloud offerings, mobile technology, and big data. But, once again, Microsoft has been quietly reengineering its culture and products, and as a result, they now offer the best value and most visionary platform for cloud services, big data, and analytics in healthcare.
Nachiket Mor IT for primary healthcare in indiaPankaj Gupta
An Approach Towards Health Systems Design in India,
Information technology for Primary Healthcare in India,
Johns Hopkins University,
March 2020,
13 citations - [Streveler and Gupta, 2019] - Health Systems for New India - Niti Aayog Book published in Nov 2019,
eObjects - eClaims, eDischarge, ePrescription, eEncounter, eReferral,
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
263778731218 Abortion Clinic /Pills In Harare ,sisternakatoto
263778731218 Abortion Clinic /Pills In Harare ,ABORTION WOMEN’S CLINIC +27730423979 IN women clinic we believe that every woman should be able to make choices in her pregnancy. Our job is to provide compassionate care, safety,affordable and confidential services. That’s why we have won the trust from all generations of women all over the world. we use non surgical method(Abortion pills) to terminate…Dr.LISA +27730423979women Clinic is committed to providing the highest quality of obstetrical and gynecological care to women of all ages. Our dedicated staff aim to treat each patient and her health concerns with compassion and respect.Our dedicated group ABORTION WOMEN’S CLINIC +27730423979 IN women clinic we believe that every woman should be able to make choices in her pregnancy. Our job is to provide compassionate care, safety,affordable and confidential services. That’s why we have won the trust from all generations of women all over the world. we use non surgical method(Abortion pills) to terminate…Dr.LISA +27730423979women Clinic is committed to providing the highest quality of obstetrical and gynecological care to women of all ages. Our dedicated staff aim to treat each patient and her health concerns with compassion and respect.Our dedicated group of receptionists, nurses, and physicians have worked together as a teamof receptionists, nurses, and physicians have worked together as a team wwww.lisywomensclinic.co.za/
New Drug Discovery and Development .....NEHA GUPTA
The "New Drug Discovery and Development" process involves the identification, design, testing, and manufacturing of novel pharmaceutical compounds with the aim of introducing new and improved treatments for various medical conditions. This comprehensive endeavor encompasses various stages, including target identification, preclinical studies, clinical trials, regulatory approval, and post-market surveillance. It involves multidisciplinary collaboration among scientists, researchers, clinicians, regulatory experts, and pharmaceutical companies to bring innovative therapies to market and address unmet medical needs.
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
Couples presenting to the infertility clinic- Do they really have infertility...Sujoy Dasgupta
Dr Sujoy Dasgupta presented the study on "Couples presenting to the infertility clinic- Do they really have infertility? – The unexplored stories of non-consummation" in the 13th Congress of the Asia Pacific Initiative on Reproduction (ASPIRE 2024) at Manila on 24 May, 2024.
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Maxilla, Mandible & Hyoid Bone & Clinical Correlations by Dr. RIG.pptx
Mdds sundararaman 12th meeting
1. Meta Data & Data Standards for Health
Domain
Dissemination Workshop
12th December 2013
2. • Initiated under National e-Governance Plan (NeGP) by DeitY.
• Aims to promote- e-Governance by making systems speak to
each other.
• Domain specific committees constituted –Health MDDS
Domain committee constituted on Sept. 2012.
– Chairperson - Joint Secretary (Policy), Sr. Technical Officer (NIC) as
member-secretary.
– Secretariat- National Health System Resource Centre (NHSRC).
– Tasks of Secretariat- Stakeholder Consultations, selecting appropriate
technical agencies to support this work and Domain Expertise.
– Members from public health programme divisions, industry, IT domain
experts, NIC,
Meta Data & Data Standards- The Initiative
3. Terms of Reference:
1. To identify Generic Data Elements in the health domain,
which are common across e-Governance applications within
the domain as well as other domains involved in providing
sectoral services delivery under e-governance.
2. To study the Global Standards for standardising the
metadata of identified generic data elements for adoption as
Indian standards.
3. To develop own standards / extension of global standards in
Indian context, wherever required, around policy on Open
Standards,
(and in synergy with other domain committees by following
Institutional Mechanism for formulation of Domain specific MDDS
formulation published by DietY).
MDDS Health Domain Project - Mandate
4. Mandate of MDDS Committee….
4. Create and maintain repository of metadata of
standardised generic standards, and include the same
in central repository by having liaison with e-Gov
standards Div, NIC.
5. Ensure enforcement of standards in the applications
being developed in health domain at central/ state
Government level.
6. To advise for identification of suitable test suits for
conformance testing of the implementation.
5. • Malaria Control
• State Health Management Information
Systems- In seven States with Hospital
Information Systems.
• Routine Immunization Management Program
• Sporadic use in Medical College Hospitals
The first generation IT systems are characterized
by low expectations, effectiveness and
complexity..
The 1st
Generation
Systems
(1993–2005)
6. • The National Health Management
Information System- common Web- Portal
with entry-
States develop a large number of systems-
1.Human Resource Management Information System.
2.Hospital Information Systems
3.Disease Surveillance Systems
4.Drug Logistics and Inventory Systems
5.E- Tendering and Procurement Systems
6.Clinical Establishments Licensing and Regulation
7.Emergency Call Centre and Ambulance Services
8.Mother and Child Tracking Systems- over 6 crore
records.
9.Financial Transaction Recording Systems
10.Major initiatives in Tele-medicine.
11.Mobile Health , Insurance etc etc.
2nd
Generation
Systems
National Rural
Health Mission
Catalyzed
7. Main Positives of the Second Phase
• IT is now seen as mandatory in all aspects of
health systems management.
• High degrees of complexity and sophistication in
systems.
• Rapidly accelerating expectations.
• For example : From 600 district reports (2008), to
5000 block block reports ( 2011) to 2 lakh facilities(
2012), to 6 crore mothers and children, below 2
!!!!!
• AND NOW to every health encounter ???
8. BUT the problem : All Public Health IT Systems in silos
Nutrition
Block
Facility
MCTS –
Reprod.
& Child
Health
System
at
National
Level
NACO
National
Disease
Program
Hospital
Informati
on
Systems,
EMR
State
Health
Program
s e.g.
EMRI,
eMamta,
HMIS,
DHIS
Birth &
Deaths
Private
Sector
MOHFW
District
Admin
State HQ
Directorates e.g.
Malaria, IDSP, NACO
IDSP
National
Disease
Program
Malaria
National
Disease
Program
RNTCP
National
Disease
Program
Web
portal –
Reprod.
& Child
Health
System
at
National
Level
o Every program/ state develops own IT solutions. States have 10 to 30
systems
o No help to integrated decision making for Public Health management.
o State to central exchange very poor- and even at the same level.
o Systems a struggling with poor design and falling short of objectives.
o Private Providers not participating in information exchange.
9. Importance of Inter-operability
realized.
• In Public Systems:
– To reduce work load in data recording and
entry.
– To support decentralized , horizontally
integrated decision making.
– To improve quality and use of information.
– To allow rapid growth of new systems and
uses of IT.
• For Providers AND Patients
– to improve quality of care
– To enable continuity of care
• For Insurance Payers
– access to patient records for claims
settlements:
3rd Phase-
(2012
onwards):
From IT
Systems to IT
Architecture…
.
10. Three Levels of Interoperability:
MDDS Builds Semantic Operability
Institutional
Interoperability
Syntactic
Interoperability
Semantic
Interoperability
11. The Process
Consultation with key stakeholders- MoHFW, NIC, C-DAC, MMP,
HISP, International Domain Experts, health care IT industry,
Program Managers, EHR Committee etc.
Review of Documents –EHR Standards, MMP, 12th Five Year Plan,
Public Health IT Systems Study, System Manuals, Program
Guidelines, MDDS Standard Document
Refer Global Data Standards- ICD-10, CPT, SNOMED, CCI, ICHI,
ICF, WHO Morbidity & Mortality Codes, LOINC
Refer Globally recognized Interoperability Standards –HL7 V2.X,
V3, CCD, SDMX.
Study of public IT Systems- HMIS Web Portal, MCTS, DHIS 2.0,
IDSP, Nikshay- RNTCP, iHRIS, e-Aushadhi
12. The Output
MDDS
Report
Name Description
Part I Overview Report •Design Principles - Semantic Theory & its
application in Health Domain
•Roll-out mechanism, Institutional framework.
•Integration Solutions.
Part II Data Element Quick
Reference
List of 1077 Data Elements with their
definitions and Values
Part III Code Directories •Code Directory List,
•Sample Values
•Meta Data for Code Directory
Part IV Data Element Meta Data Meta Data for Each Data Element. Including
Data Element Type, Format, Size, Validation,
Values, Default Value, Owner etc.
Annexure •Data Sets- Inventory, Blood
Bank etc.
•Some examples of data sets created form the
common data elements.
•Interim Measures
Integration & Upgrade as
per MDDS
•Integration Solutions for existing system-
HMIS-MCTS, DHIS-iHRIS
•MDDS Mapping with HMIS. IDSP & RNTCP
Systems
•Part II, III & IV and Annexure are in soft copy in CD.
•For online access visit- http://mohfw.nic.in, www.nhsrcindia.org
13. MDDS Health Domain Standards
Building Blocks of MDDS Health Domain
o The health domain landscape are broadly
divided into 39 Entities.
o These entities are described and qualified
with the help of 1077 Data Elements.
o Values of Data Elements are categorized
under Data Elements (735), Values List
(201) & Code Directories (141)
o Meta Data are constructed to define each
Data Element and Code Directory to
establish Interoperability Standards
o Interoperability Standards
o Reference Architecture for Interoperability
14. MDDS The Conceptual Design
Example-I
CONCEPTUAL DOMAIN
ENTITY (E.G. PHARMACY ORDER)
LIST OF VALUES
(BID, TID, QID,HS, STAT)
OBJECT CLASS
MEDICATION ORDERS
ATTRIBUTE
FREQUENCY
DATA ELEMENT
MEDICATION FREQUENCY
CONCEPT
FREQUENCY OF MEDICATION
VALUE DOMAIN
MEDICATION FREQUENCY
CODE DIRECTORY
15. MDDS The Conceptual Design
Example-II
Concept
Operational Status
of Facility
Value Domain
Operational Status
Value List
Conceptual Domain
Entity (e.g. Facility)
Object Class
Facility
Attribute
Operational Status
List of Values
Functional, Non-
Functional, Under
Repair , Closed,
Data Element
Facility Operational
Status
16. MDDS The Conceptual Design
Example-III
Concept
Health Condition
Code
Value Domain
ICD-10 Code
Directory
Conceptual Domain
Entity (e.g. Diagnosis)
Object Class
Health Condition
Attribute
Code
List of Values
ICD-10 Disease Codes
Pulmonary
Tuberculosis - Lab
Confirmed
Values: A15
Data Element
Health Condition
Code
17. MDDS The Conceptual Design
Example-IV
Concept
Scheduled
Ambulance Trip
Reasons
Value Domain
Medical Reason for
Scheduled Trip Code
Directory
Conceptual Domain
Entity (e.g.
Ambulance)
Object Class
Ambulance
Attribute
Scheduled Trip
Reasons
List of Values
Delivery, RTA, chest
pain, -drawn from
ICD and WHO
Data Element
Reasons for
Scheduled
Ambulance Trip
18. Common Data Elements
• Defining Minimum Data Elements as standards is
difficult in Health Domain.
• Minimum Data needs of the Primary Care Setting would
be different from the Secondary and Tertiary Care
Settings.
• Health Domain has come-up with the Common Data
Elements which will act as superset from which program
specific data sets can be created.
• Data Set design is better left to the users.
19. Common Data Element - ENTITIES
Description of Entities
Entity
No. of Data
Elements
Entity
No. of Data
Elements
Generic 35 Lab 39
Person 32 Radiology 10
Patient 21 Pharmacy 32
Employee 155 Immunisation Order 10
Provider 16 Clinical Order 19
Source of Payment 38 Procedure 8
Bill 39 Blood Bank 36
Facility 32 Nursing 21
Episode 2 OT 33
Encounter 9 CSSD 20
Advance Directives 6 Inventory 179
ADT 56 Remission 5
Emergency 19 Complications 5
Outreach 11 Relapse 5
Disaster Response 31 Morbidity 6
Examination 5 Disability 7
Vital Signs 16 Mortality 6
Allergy 13 Ambulance 66
Clinical Notes 15 Indicator 5
Diagnosis 14 Total 1077
20. Common Data Elements: Snapshot
Entity- Diagnosis
Number Name of Data Element Data Format Maximum Size
05.020.0001 Health Condition Type Integer 2
05.020.0002 Health Condition name Varchar 99
05.020.0003 Health Condition Code Varchar 10
05.020.0004 Health Condition Free text Varchar 254
05.020.0005 Health Condition Category Char 1
05.020.0006 Diagnosis Priority Char 1
05.020.0007 Health condition status Integer 2
05.020.0008 Co-morbidity Flag Integer 1
05.020.0009 Co-morbidity Health Condition
Code
Varchar 10
05.020.0010 Present Health Condition Onset
Date
Custom
05.020.0011 Prognosis Integer 2
21. Complexities Pushed to Code Directories
Code Directory Facts:
Total Code Directory- 141
Code Directory Populated-111 (79%)
Code Directory Derived from established sources- 42%
7 Code Directories - Facility Master.
Ref No Name of Code Directory Ownership & Source
CD05.001 Facility Master MDDS Committee
CD05.019 ICD - 10 Codes WHO
CD05.024 LOINC LOINC
CD05.030 System of Medicine MDDS Committee
CD05.036 Immunization Product WHO
CD05.043 Procedure Code
Canadian Classification of Health
Intervention (CCI)
CD05.056 WHO List for General Mortality WHO
CD05.059
WHO International Classification of Functioning,
Disability and Health (ICF)
WHO
CD05.104 Generic Drug National Formulary of India
CD05.109 Pharmaceutical Unit of Measurement Food and Drug Administration
CD05.118 Third Party Administrator IRDA
CD05.130 Medical Reasons for Scheduled Ambulance Trip LOINC & WHO
22. Identity Management in Indian Health System
• Health information exchange between
systems through Identifiers
– Facility Identifiers (Unique Facility
Identification Number/Global
Unique Identifier)
– Provider Identifiers – Unique
Individual Health Care Provider
Number
– Patient Identifiers– UID/ Alternate
Unique Identification Number
– Disease Identifiers– ICD-10 Codes
– Service Identifiers– CCI Codes
– Document Identifiers– Document ID
23. Facility Identity Management
Unique Facility Identification
I. Facility Signature Domain:
– Unique Facility Identification
Number
– Global Unique Identifier
– Type of Facility
– Address
– Geocode
– Difficulty status- Easy/Difficult
– Rural/Urban Area
– Population covered
– Administrative linked parent
facility Type
– Operational Status
– Referral facility
– Ownership Authority & Type
II. Facility Services Domain:
– Facility System of Medicine
Type
– Facility Services Master
III. Facility Human Resource
Domain
IV. Facility Infrastructure
Domain:
– Facility Bed Master
– Facility Bed Type Master
Suggested Model – Central Model
24. Further gains of this effort…
• Gone far beyond just clinical terminology standardization: Set
standards - administrative and operational parameters
• MDDS provides platform to dramatically accelerate use of
EHR standards/HL7/DICOM communication standards.
• Now in a position to be a global leader in healthcare IT useage
and implementations. Global Governments could also use
MDDS as a base and modify it for their local healthcare
industry .
• Allows greater democracy – in choose their own systems and
software applications, vendors and technical infrastructure :
within a ‘standards’ framework that ensure national
consistency in the reporting and management of healthcare
outcomes.
25. The Second Level of Interoperability:
Appropriate Integration Solutions will ensure Syntactic
Interoperability
Institutional
Interoperability
Syntactic
Interoperability
Semantic
Interoperability
26. Point-to-point Integration
Pros
• Useful for all historical applications without much disruptive
changes.
• One eligible application can receive message from a source
application message channel.
Cons
• Extra effort, time and cost to write Transformation logic for each
application.
• Semantic interoperability difficult to implement across different
applications.
<?xml version=“1.0” ?>
<Group group_id=1>
<dataelement>
<HMIS_dataelement>id=” M1|1.1” name=” Total Number of Pregnant Woman Registered for ANC”
Value”</HMIS_dataelement>
<MCTS_dataelement> id=“1” value=“100” isChild=”F”</MCTS_dataelement>
</dataelement>
<dataelement>
<HMIS_dataelement>id=” M1|1.1.1” name=” Of which Number Registered with in First
Trimester”</HMIS_dataelement>
<MCTS_dataelement> id=“2” value=“30” isChild=”T” Parentdataelement=”M1|1.1”</MCTS_dataelement>
</dataelement>
<FacilityCode> 00000000023</FacilityCode>
<FacilityType>”SC”</FacilityType>
<REPORTING_PERIOD> <TYPE>”Monthly”</TYPE> <FROM_VALUE>=”July 2013”</FROM_VALUE>
<TO_VALUE>=”July 2013”</TO_VALUE></REPORTING_PERIOD>
</Group>
Spaghetti framework
27. Broker-Based Integration
Pros
• Message broker can be
used to receive messages,
transform and route to
recipient application (Hub
and spoke architecture.)
• Data from finite set of
disparate applications can
be integrated using this.
Cons
• Data discovery at run
time based on a service
request is difficult.
• May lead to a highly
complex architecture-
difficult to maintain.
28. Intelligent Gateway
(Health Information Exchange)
• Better suited to
current context.
• Based on Registry
architecture
pattern.
• Allows to
dynamically
locate the data
records and the
application
locations.
• Integration with
other domain
applications is
quite easy.
29. Choosing Integration Options
If within range of Tower in
Mumbai Circle, it has a registry
lookup to connect the 2
o Condition - II
o Broker
Integration
• Condition - I
• Point to Point
Integration
√ Condition - III
√ Exchange
Integration
• Any No. of Apps.
• Need to know where the book
is located in the Library. Else it
is like trying to find any book
without library catalogue
• Limited No. of Historical
apps.
• If Time & Effort not a
constraint
• Scalable to any number of
systems.
• Historical apps cant be retired.
• MDDS implementation with
deviations- Real world
• Intelligent broker is like -
Searching a book in electronic
catalogue – E.g. Amazon Books.
HOT Line
Roaming
Mobile from
Bangalore
Circle
Roaming
Mobile from
Delhi Circle
Trunk Dialing – Operator needs to
know where to route the call
30. Third Level of Interoperability
Set of rules, guidelines on the way we collect and report
data- and of course the desire to dialogue and share:
Institutional
Interoperability
Syntactic
Interoperability
Semantic
Interoperability
31. Institutional Interoperability
Guidelines, norms for data collection and
reporting, patterns of flow, aggregation and
context of usage.
Different levels of digital capacity, different
granularities of reporting,
Choice of standard, Indicators for data exchange.
Most importantly a dialogue between
organizations, to understand information needs,
as well as barriers to better quality and use of
information.
National Authority should be able to facilitate
this role.
32. Key Principles: Follow-up and Roll-out
1. Data standards are seen as dynamic- provision to be made
for constant upgradation and corrections.
2. Even the starting standards as released now, will need
clarifications, corrections, additions, deletions- standing
committee to help to this.
3. In private sector, the adoption would be voluntary- driven by
the advantages and ease of doing so.
4. In public sector it would be driven by financing
conditionality and needs for sharing information.
5. Once standards prove themselves, and ecosystems to test
and certify measure a mix of financial incentives and
disincentives for private sector could be considered.
33. Standards Roll-out and Adoption–The Steps
a. All centrally financed applications and software should
comply with these standards. This will be part of the
sanction of funds.
b. Specific proposals received to reengineer available public
health IT products to confirm to standards can be taken-up
on Case to case basis. Same would not be applicable to new
applications.
c. Adherence to standards- The MDDS committee may
consider accreditation and rate contracting suitable testing
agencies and only these may be allowed.
d. Creating Awareness- All major health IT symposia and
seminars to be covered to explain and popularise standards
so that industry voluntarily adopts the standards even solely
for private purposes.
34. Standards Roll-out contd..
e. Standards Updation- Suggestions, complaints, technical
snags should be conveyed to secretary of the MDDS
committee (mdds-mohfw@nic.in). (Reply to each of these
queries within a one month time standard).
f. Any modification would be notified on the website of
MoHFW, NHSRC and the main portal of the standards.
g. MoHFW would facilitate integration where requested.
h. Exchange between state financed and central financed
systems desirable- not mandatory.
35. Institutional Framework
National Health Information Authority
The Mandate
• Testing &
Certification
• Accreditation
• Compliance
• Update
• Upgrade
• Identify gaps
• Collect
Feedback
• Advocacy
• Capacity
Building
• Incentive
• Legislation
• Publish
• Disseminate
• FAQs
• Help lines
MAINTAIN FACILITATE
CERTIFYMANAGE
MDDS
Health Domain
Standard
36. The Structure & Function
The Mandate
Policy Formulation
Technical
Group
(4-5 Technical
Architect)
Functional
Group (4-5
Health IT
Professionals)
Management
Group
(4-5 Health
Mgmt
Professionals
Certification
Group
Core Groups
National Health
Information Authority
Core Functions
Health IT Forum
Academic &
Research
Institutions
37. Concluding Remark
• Solving the semantic barriers brings inter-
operability much closer, but there would be still
challenges to face.
• EHR standards and MDDS publication is thus
the first step of a long journey
….. not its final destination.
38. Thank You
• We- in the MDDS committee- gratefully acknowledge the
contributions of all our technical partners especially the work
of
UNITED HEALTH GROUP & TAURUS GLOCAL
• We also acknowledge the contributions of technical experts in
NIC and NHSRC who co-ordinated and contributed to this
process.
• And of many many others- with apologies for not naming
them individually…..