Making Healthcare Accessible – Role of  Comprehensive Health IT Systems             Arvind Saraf
Problem●   Healthcare costs in India are prohibitively high    ●   Most (76%) of it is Out of pocket    ●   6.3 Crore Indi...
Industry looks upon its own narrowoperational requirements●   IT platforms follow the industrywise vertical perspective (E...
Need to look at Health system in its entirety●   Link up health behavior, outpatient visits,    diagnostics and hosptitali...
IT System design that allows the Complete Systems perspective   Monitoring and Evaluation   Create, Conduct Surveys. Add S...
One such live system – Swasth Live●   Developed by Swasth India, a social business that    aims at ensuring access to heal...
Swasth India as the Service Integrator                                                                                    ...
System Components Module             Data structures                                     Functionality Demographic        ...
Sample Screenshoots
Visit Documentation
Visit Documentation
IPD system
IPD system
Business Analytics on the fly      for Healthcare Enterprises        using the Cloud Model                          ( NCMI...
Health 2.0 India 2012“ Healthcare today is receiving a tsunami  of data .  We are data rich but care poor. The challenge t...
Roadblock to eHealth : Data is    fragmented & changes over time• Data can be turned to intelligence that  can make differ...
“As providers increasingly get information and  more clinical data into their repositories from  the use of new technologi...
Analytics Value across Healthcare               EcosystemHealthcare Providers• Clinical quality initiatives and reporting•...
Business Intelligence (BI )• Business intelligence (BI) tools for hospitals ; such as  those offered by SAS Institute Inc....
What is Business Analytics on SaaS?• A delivery model for business intelligence in  which applications are typically deplo...
Basic BI Architecture on CloudData warehousing                                                   Business Performance     ...
Characteristics of good BI• Structured or Unstructured Data• Data Quality and Integration   – for converting data into a f...
BI on SaaS
Business Intelligence on Demand                         Source : ( Willem 2010)
SaaS model of BI in Healthcare• Hospital Information Systems• ERP•Legacy Systems•Documents                                ...
Benefits of adopting cloud computing             to healthcare• Supply chain Management and Capacity building• Scalable In...
Benefits  VISIBILITY                  Different faces   View the data from various angles, needs and                 of th...
Key DifferentiatorsOn-Demand Self-Serving AnalyticsLarge Data HandlingPerformanceData Load and View Update StrategyEnterpr...
Diabetes Outcome Records
Measuring Performance : NQF-Endorsed® Standards          NQF ( National Quality Forum ) Reports
Billing of different specialty
Billing of different specialty - II
Evidenced Based Benefits ( EBB)            @ NCMI 2012• “ Cloud Benefits : 50 – 70% IT Cost reduction,  30% power saving ,...
Conclusion• Options for Analytics for M&E of health  indicators in MDG , NCD as well as  environmental and climatic studie...
Thanksindrajit@iihmr.org
NCMI-2012 3-5 Feb 12,N DelhiLEVERAGING DATA ANALYTICS   IN HEALTHCARE –SOME      SUCCESS STORIES    Gp Capt ( Dr) Sanjeev ...
Introduction• Breakthroughs in data-capturing technologies,  data    standards,     data     storage,   health  management...
Defining Data Analytics• The science of extensive use of data, statistical and  quantitative analysis, explanatory and pre...
Data Analytics Vs Data Mining• Data analytics is distinguished from data  mining by the scope, purpose and focus  of the a...
• “As a general rule, the most  successful organisation today is the  one with the best information”• We are drowned in da...
Indian scenario-basics first• Most Indian H C O are yet to embark on analytics journey or are still in  early stages of it...
Typical Applications of Data Analytics in                     Healthcare•   Practice of evidence based medicine –    Adher...
Typical Applications of Data        Analytics in Healthcare• Capacity management is among hospitals’  key challenges. When...
NRHM – Gets the IT Edge• Health Statistics Information Portal – a web based  MIS – facilitates speedy & efficient flow of ...
Sir Ganga Ram Hospital• SGRH, a pioneer in health informatics, has  been using data mining with SpeedMiner, a  data mining...
Tracking Infection control data• Each of the hospitals in the Apollo group tracks  infection control parameters month afte...
Comprehensive Unit-Based    Safety Program (CUSP)• . CUSP lets hospital identify safety  concerns,    learn    about     s...
HealthMap- Tracking Emerging Health Threats         Through Online Database• . HealthMap is one such innovation that is  a...
HealthMap• In operation since 06, and created by John  Brownstein, and Clark Freifeld of Childrens  Hospital Boston and Ha...
Decision Analysis Helps Allocate Health            Care Funds in the UK• . In some cases, decision-making  techniques can ...
The Use of Goal Programming for     Tuberculosis Drug Allocation in Manila• The objective function of the model was to mee...
Using Bayes’ theorem to develop         a decision tree• A group of medical professionals is considering the  construction...
Conclusion• Data analytics focuses on inference, the process of  deriving a conclusion based solely on scientific  knowled...
The difficulty lies not so much indeveloping new ideas……………….. as in escaping from theold ones  If you are not riding the ...
Role of IT in Analytics• Having a strong analytical orientation would  seem to be a function of data and information  tech...
Leveraging analytics in Health care• Health information and analytics have been  extensively used in healthcare to measure...
DELTA-            Model for Assessing                     Analytical Capability•   Data: should be discrete, granular, and...
FUNCTION DESCRIPTION EXEMPLARSSupply chain Simulate and optimize supply chain flows; reduceDell,Wal-Mart, Amazoninventory ...
TELE HEALTH CENTRE              FOR          RURAL INDIA                  A bottom to top approach for                    ...
Dr. Shilpa, 96OVERVIEW OF PRESENTATION                              2
Dr. Shilpa, 96   Rural development: A Prerequisite      for National development• 68.84 % of India’s population resides in...
Dr. Shilpa ,96HEALTH CARE PARADOX                              4
Dr. Shilpa ,96                        TELE -MEDICINE         According to World Health Organization (WHO)      Telemedicin...
Dr. Shilpa ,96    TYPES OF TELEMEDICINE                                    TELE                                 MEDICINE  ...
Dr. Shilpa ,96                  Point       • One patient connected to                    to          one doctor          ...
Dr. Shilpa ,96                SWOT ANALYSIS   STRENGTHS                      WEAKNESSES• Improved accessibility   • Limite...
Dr. Shilpa ,96BARRIERS TO IMPLEMENTATION               SOCIO-              CULTURAL    TECHNO-              LEGAL         ...
Dr. Shilpa ,96              Proposed modified model                Primary                Health                CentreOuts...
Dr. Shilpa ,96Super                             Level 3SpecialtyHospitalStateMedical                             Level 2Co...
Data          • Patient’s medical record and related                  preparation       images are transferred from consul...
Dr. Shilpa ,96A way forward                      13
Dr. Shilpa ,96        14
Dr. Shilpa ,96
1Emerging role of Informatics to improve          Population Health Ashish Joshi M.D., M.P.H., PhD Assistant Professor Cen...
Presentation Format2       Defining Informatics and its categories       Role of Informatics in Disease Prevention and M...
Research Map                     Evidence based                      Management     Health    Outcomes        (Clinical tr...
Informatics: Any activity that relates to computing or science   of information where information is defined as data with ...
Bio Informatics                   Imaging(Molecular and cellular           Informatics     processes)                     ...
Public Health Informatics   Systematic application of information and    computer science and technology to public    hea...
Informatics in Disease Prevention                         and ManagementData acquisition          Information Analysis    ...
Multi-dimensional     Human Mind      Health Data       Processing Data                                                 In...
End users •Demographic    •Cultural  •Behavioral  •Contextual    •Clinical  •Technology    •Access      •Cost •Infrastruct...
Technology Mediated Intervention                                                      Framework                           ...
Computer     Psychologists         science                         Doctors     Information                               N...
Manifold needs of individuals            Information about               the illnessesTreatment                          S...
Challenges of using Health                Information Technology               Access to            technology and        ...
Human Centered Informatics Platform •User age, gender,                                          • Set of input attributes ...
Variables                           U.S.A.               Brazil                       India Geographic disparity          ...
Consumer                  Health               Information                 Platform       Cell phone                      ...
Health Education Modalities                                                                                               ...
Interactive Health Information Platform   Allow users to self-pace the program.   Materials targeted or tailored.   Mat...
Information Flow within IHIP                         Content attribute           Technology Platform            Usage  Use...
• Emergency room                                  •   Asthma (6)     • Primary care clinics                            •  ...
Version 2Version 1
Version 3   Version 4
Acceptance of Interactive Health                                                Information Program       97 %            ...
Improvement in Asthma Knowledge                                                                 Scores                    ...
Change in Attitudes towards                                          Influenza Vaccine           67.78%                   ...
28     Ashish Joshi M.D., MPH
29     Ashish Joshi M.D., MPH
30     Ashish Joshi M.D., MPH
EVALUATION         OUTCOMES       IMPROVEMENT                   SUSTAINABILITY                      Existing      TARGETED...
Future Directions   Design and evaluate HC informatics mediated    interventions that are;     Sustainable     Multifac...
Related Publications   A Joshi et al. A Pilot Study to Evaluate SELF INITIATED COMPUTER Patient    Education in Children ...
34     Thanks and Questions!!!                           Ashish Joshi M.D., MPH
Perceived benefits of hospital information system & EMR by          end users             Presented By:Anindam Basu & Dr. ...
Role of ict in healthcare…   Information Systems acts as a Support to the Healthcare    Industry.   Lots and Lots of Dat...
   Studies describes about ICT systems as follows:    ICT implementation is an organization process    Substantial pote...
Classes to determine the success of             ict system User Attitudes and   Perception. Use   of the System itself (...
literature behind the study… Delpierre C et al, 2004: Provided Systematic Review of 26 Papers.   Focusing on User percep...
types of perceived benefits… Direct       Benefits: Reduced Medical Errors; Paper Reduction etc. Indirect Benefits:     ...
objectives behind the study… Studythe Perception of the Hospital Staff towards the ICT system. Study   the kind of probl...
Ict Applications used in the                    hospital…   Open Source EMR & Lab Module   PACS from GE Centricity   Te...
Methodology… Definition of the Sample: The respondent should be a regular  staff of the Hospital & should be using either...
Profile of the respondents        No. of Respondents                        Experience              30                    ...
It importance for the hospital         1        5           Less Important25;17                              Moderate     ...
Finding HIS/EMR         1   14                       18   Very Easy                            Easy                       ...
Average time spend to the                                 application                         More than 3 Hrs             ...
Improvement after the      implementation Neutral                    Improved a little bit Satisfactory Improvement   Trem...
Major issues faced by theM… Technology    Issues:  Computer and Application getting hanged  Application takes longer ti...
Benefits perceivedBenefit Type                Perceived Benefit   Direct      1) More Easy Follow up visits in OPD        ...
Conclusion and discussion                            17
recoMMendations…   Regular Monthly assessment.   Updation of the technology used (thin clients &    server).   Vendor s...
19
“8th National Biennial Conference on Medical Informatics 2012”
“8th National Biennial Conference on Medical Informatics 2012”
“8th National Biennial Conference on Medical Informatics 2012”
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“8th National Biennial Conference on Medical Informatics 2012” at Jawaharlal Nehru Auditorium, AIIMS New Delhi on 5th Feb 2012,
The organizing committee consisting of Mr. S.K. Meher (Organizing Secretary), Major (Dr.) Anil Kuthiala (Jt. Organizing Secretary) and Ashu (Assistant to the Organizing Secretariat) worked hard and toiled to make the conference a grand success.
The scientific committee comprising of Dr. S.B Gogia, Prof. Khalid Moidu, Prof Arindam Basu, Dr. S Bhatia, Dr. Thanga Prabhu, Dr. Karanvir Singh, Tina Malaviya, Dr. Kamal Kishore, Dr. Vivek Sahi, Spriha Gogia, Dr. Supten Sarbhadhikari, Dr.Sanjay Bedi, Mr. Sushil Kumar Meher actively reviewed all papers for the various scientific sessions.

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“8th National Biennial Conference on Medical Informatics 2012”

  1. 1. Making Healthcare Accessible – Role of Comprehensive Health IT Systems Arvind Saraf
  2. 2. Problem● Healthcare costs in India are prohibitively high ● Most (76%) of it is Out of pocket ● 6.3 Crore Indians pushed into poverty (in 2004) due to healthcare costs ● 14% of rural households / 12% of urban households spent >10% of income on healthcare (2004)● Well designed preventive / early diagnosis interventions required to reduce cost ● Intervention choice varies by context ● Lack of effective universe set of interventions ● Government interventions are usually designed in vertical silos, not effectively evaluated
  3. 3. Industry looks upon its own narrowoperational requirements● IT platforms follow the industrywise vertical perspective (Eg Open source platforms - OpenEMR, Clearhealth, Trilonis) Independent Hospitals Clinics Labs / Pharmacies Insurance Companies Government / NGO / Private Awareness / Preventive interventions TPAs Beneficiary
  4. 4. Need to look at Health system in its entirety● Link up health behavior, outpatient visits, diagnostics and hosptitalization history of an individual ● Eg Reduction in illnesses amongst anaemic women diagnosed and educated about it ● Inferring community level causality linkages better● Understanding key local factors to select the right intervention for the area / community. Eg: ● Locations with higher incidence of water-borne diseases may require intervention on chlorine tablets for safe drinking water ● Locations where very high fraction of cases escalate from primary care providers to hospitals may need better primary care providers
  5. 5. IT System design that allows the Complete Systems perspective Monitoring and Evaluation Create, Conduct Surveys. Add Survey data Export data for analysis Insurance CHW Preauthorizations OPD Training Claim line items, review tracking Medical History Activities Visits by Provider Followups or Location Hospitalization Sales Hospitalization details Counsellings (consultations, tests, Medications), Cost items Demographic Administration People and households Organization, staff members, schemes Geography Family / individual Enrollment in the schemes
  6. 6. One such live system – Swasth Live● Developed by Swasth India, a social business that aims at ensuring access to healthcare for the poor● Open-source platforms – LAMP, hosted on Amazon EC2● Used for: ● Insurance claims management for ~10,000 people across ~200 villages of Maharashtra and urban Bangalore ● Used in 7 clinics (and 3 organizations) across Mumbai, Delhi and Tamil Nadu● Why a new system? ● Hard to put together existing systems – different platforms, lack of standards, lack of unifying services or organization
  7. 7. Swasth India as the Service Integrator ● Training institutesWhere applicable - ● Actuarians● Insurance companies ● Medical protocol developers● Social Re-insurers Risk ● Rural Marketeers Technical Management Partners Organisations D es C on ign d ic lise tr & ac a Se eci es tin Sp g ● NGOs rv ● Micro Finance Empanelment Partner Institutions Healthcare Community Co-operatives Swasth India ● Providers & Quality support Aggregators ● Employers Fa ● Hospitals cil Last-mile reach it a s Fe tio ic Doctors ed n& st ● ba gi ck Lo ● Diagnostic labs ● Pharmacies End Drug Suppliers Consumers ● Pharma Companies ● Distributors 7
  8. 8. System Components Module Data structures Functionality Demographic Geography – states, districts, blocks, cities and Add / edit / delete households, families, villages, households, families, person individuals; Update master geography information Admin Ecosystem – organizations, staff members and Add / edit / delete organization, staff members schemes, Enrollment into schemes and schemes; Enroll individuals or families into schemes Hospitalization Hospitals, Hospitalization summaries (diagnosis, Add / edit / delete hospitals, hospitalization proposed procedures and current status), cases, hospital records, bills Hospital records (notes, diagnostic reports, medication administrations), Bills Insurance Preauthorizations, Claims, Claim status Add / edit / review preauthorization, claims Outpatient Patient visit records, Lab reports, Medical Add / edit / delete outpatient clinics and summary, Immunization history doctors, patient visits, lab reports, immunization Community health Community health workers (CHW), Community Add / edit / delete CHWs, community health health projects, Training modules and sessions projects, training modules, projects; Add training sessions, including individual CHW evaluations for the ssesions Monitoring and Surveys, Reports Create and Run surveys; Enter survey data Evaluation point; Create and Generate reports
  9. 9. Sample Screenshoots
  10. 10. Visit Documentation
  11. 11. Visit Documentation
  12. 12. IPD system
  13. 13. IPD system
  14. 14. Business Analytics on the fly for Healthcare Enterprises using the Cloud Model ( NCMI 2012 ) 5th Feb 2012 Indrajit Bhattacharya 1, 2, Anandhi Ramachandran2, B.K.Jha1 1 Birla Institute of Technology,( Noida Campus ), Mesra , Ranchi2 International Institute of Health Management and Research, New Delhi
  15. 15. Health 2.0 India 2012“ Healthcare today is receiving a tsunami of data . We are data rich but care poor. The challenge today is transforming data to actionable care.”
  16. 16. Roadblock to eHealth : Data is fragmented & changes over time• Data can be turned to intelligence that can make difference between effective and timely care versus costly and ineffective or even inappropriate action.” – Hospital and Healthcare Management Nov 2011
  17. 17. “As providers increasingly get information and more clinical data into their repositories from the use of new technologies … coming as a result of the meaningful use requirements, they’re coming up with new applications for analytics.” —Judy Hanover, Research Director, IDC Health Insights
  18. 18. Analytics Value across Healthcare EcosystemHealthcare Providers• Clinical quality initiatives and reporting• Operational efficiencies• Financial performance management• Pay-for-performance initiativesPharmaceutical / Biotechs• Comparative effectiveness• Adaptive trials to support personalized medicine• Consumer and physician engagement and decision supportAcademic Medical Centers• Translational, clinical and comparative effectiveness research• Collaborative and extra-enterprise researchPublic Health• Disease surveillance• Comparative effectiveness and clinical utility studies
  19. 19. Business Intelligence (BI )• Business intelligence (BI) tools for hospitals ; such as those offered by SAS Institute Inc. to develop scorecards to track quality indicators across EHR systems.• Advantages ( not limited to ) : – tune up bed and inventory utilization and staffing – Provide predictive trends for cost effective decision making – access to actionable knowledge that can measurably demonstrate ROI helping in driving operational efficiency and optimizing patient care• Limitation – Cost of procurement and maintenance
  20. 20. What is Business Analytics on SaaS?• A delivery model for business intelligence in which applications are typically deployed outside of a company’s firewall at a hosted location and accessed by an end user with a secure Internet connection.• The vendors provide it either on subscription or on pay - as - you - go model – (http://www.saas-showplace.com)
  21. 21. Basic BI Architecture on CloudData warehousing Business Performance tools OLAP Data Mining Reporting Management Software as a Service - SaaS Data Warehouses ( Platform as a Service - PaaS) Processing Power and Source Data Storage ( Infrastructure as a Service – IaaS ) OLAP : Online Analytical processing Source : Stevan Mrdalj, 2011, “Would Cloud Computing Revolutionize Teaching Business Intelligence Courses”, Issues in Informing Science and Information Technology, Vol. 8
  22. 22. Characteristics of good BI• Structured or Unstructured Data• Data Quality and Integration – for converting data into a format readable by the database• Healthcare Data Warehouse – for storing data used by BI• Healthcare Business Intelligence & Analytics Engine• Healthcare Portal – for display of data for healthcare customers
  23. 23. BI on SaaS
  24. 24. Business Intelligence on Demand Source : ( Willem 2010)
  25. 25. SaaS model of BI in Healthcare• Hospital Information Systems• ERP•Legacy Systems•Documents Source : Ideal Analytics 2012
  26. 26. Benefits of adopting cloud computing to healthcare• Supply chain Management and Capacity building• Scalable Infrastructure• Collaboration with companies offering similar services• Accessing Insurance details• Fast and Easy access of health records• Standard Integration• Report generation using dashboards and KPI• Increased Customer Service Quality
  27. 27. Benefits VISIBILITY Different faces View the data from various angles, needs and of the same data aspectsGRANULARITY Deep dive into Drill down, roll up, slice and dice, group and the data find hidden correlations Accessing any AVAILABILITY data, any time, Data anywhere, anytime to the authorized user any where Can be used Data, information and knowledge at the very well by a SIMPLICITY non-technical disposal of the user instantly without any person special training! FLEXIBILITY Integration, Cut n Slice, ship out chunk, integrate, cube It, externalization and show selectively! WHAT-IF- The change ANALYSIS effect What –happen-when something should occur!PREDICTABILITY Forecast and View the future and view it with little changes Trend Analysis too!
  28. 28. Key DifferentiatorsOn-Demand Self-Serving AnalyticsLarge Data HandlingPerformanceData Load and View Update StrategyEnterprise ScalabilityFlexibility in AnalysisExternalizationImplementation Time and Cost
  29. 29. Diabetes Outcome Records
  30. 30. Measuring Performance : NQF-Endorsed® Standards NQF ( National Quality Forum ) Reports
  31. 31. Billing of different specialty
  32. 32. Billing of different specialty - II
  33. 33. Evidenced Based Benefits ( EBB) @ NCMI 2012• “ Cloud Benefits : 50 – 70% IT Cost reduction, 30% power saving , efficient and effective resource allocation” : Dr. Jack Li, TMU• “ BI Benefits : Demonstrate benefits of HIS / EMR adoption” : Dr. Karanvir Singh , SRGH• Privacy enhanced – change future delivery of HIT delivery
  34. 34. Conclusion• Options for Analytics for M&E of health indicators in MDG , NCD as well as environmental and climatic studies• Implementing BI in Cloud would help in reducing Capital investments and tremendously improve in decision making by Healthcare and Public health organizations – Reduce cost of care – Improve health outcomes
  35. 35. Thanksindrajit@iihmr.org
  36. 36. NCMI-2012 3-5 Feb 12,N DelhiLEVERAGING DATA ANALYTICS IN HEALTHCARE –SOME SUCCESS STORIES Gp Capt ( Dr) Sanjeev Sood MD,Mphil (HHSM) Hosp & Health Systems Administrator
  37. 37. Introduction• Breakthroughs in data-capturing technologies, data standards, data storage, health management information systems (HMIS) and modelling and optimization sciences have created opportunities for large-scale analytics programs.• Several HCOs in the private sector have not only leveraged fact based decision making, but also created sustained competitive advantage from data-based analytics.• They have their business strategies at least in part-around their analytical capabilities.
  38. 38. Defining Data Analytics• The science of extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.• Analytics is a subset of what has come to be called business intelligence: a set of technologies and processes that use data to understand and analyze business performance.• The term “business analytics” now defines technology that uses data analysis to understand business issues in a way that can guide decision-making.• The approach starts with a good quality data. This data is manipulated or processed into information that is valuable, timely, accurate, rational, feasible and reliable for decision making.
  39. 39. Data Analytics Vs Data Mining• Data analytics is distinguished from data mining by the scope, purpose and focus of the analysis.• Data miners sort through huge data sets using sophisticated SW to identify undiscovered patterns and establish hidden relationships.• Data analytics focuses on inference, the process of deriving a conclusion based solely on what is already known by the researcher.
  40. 40. • “As a general rule, the most successful organisation today is the one with the best information”• We are drowned in data,but starved of knowledge -John Gaisnitt
  41. 41. Indian scenario-basics first• Most Indian H C O are yet to embark on analytics journey or are still in early stages of it. They need to generate and compile good quality data by structured and reliable reports and returns from multiple sources. This data needs to be transformed into intelligence to guide decision and policy makers, administrators and health care personnel.• Availability of quality data on morbidity patterns and patient safety are grossly inadequate in India to design innovative health insurance products for population and institutionalize effective patient safety programmes in hospitals.• Currently, most HCOs are data poor, some are data rich, but information poor; very few could be data and information rich.
  42. 42. Typical Applications of Data Analytics in Healthcare• Practice of evidence based medicine – Adhering to online clinical protocols. The Department of Veterans Affairs is currently using this approach extensively.• Early detection of emerging disease vectors, spotting outbreak of epidemic• Prevention of fraudulent health insurance claims.• Data mining is being used by hospitals to predict the ALOS, which helps them better manage the patients, physicians and the
  43. 43. Typical Applications of Data Analytics in Healthcare• Capacity management is among hospitals’ key challenges. When hospitals do not successfully manage capacity assets, they suffer by way of revenue loss, operational inefficiency, delay and patient dissatisfaction.• Advanced Analytics can impact the way hospitals manage their capacity and other processes by enabling forecasting and scheduling for the immediate and longer term.
  44. 44. NRHM – Gets the IT Edge• Health Statistics Information Portal – a web based MIS – facilitates speedy & efficient flow of information from periphery to centre• Tools for advanced data analysis, reporting, monitoring, evaluation & programme management• More efficient public health planning & forecasting for service provisioning, emergency preparedness ,resources mobilization• Objective – data for Action
  45. 45. Sir Ganga Ram Hospital• SGRH, a pioneer in health informatics, has been using data mining with SpeedMiner, a data mining SW product by Hesper. SpeedMiner was installed as an adjunct to HIS at SGRH• An effective business intelligence tool which helps in data analytics and real time monitoring of the KPIs, query handling , and serves as a quality dashboard through the various data collated over a period of time under specific heads.
  46. 46. Tracking Infection control data• Each of the hospitals in the Apollo group tracks infection control parameters month after month and these are benchmarked with standards and variations and values are thoroughly analyzed. Periodically clinical studies on infection control, pathogens and other related areas are also carried out .• All infection control parameters are tracked as part of the ACE 25 CLINICAL EXCELLENCE initiative of Apollo hospitals where key Quality parameters of each hospital in the Apollo group are entered on an Online Dashboard, scored and reviewed by the highest Leadership of the group each month
  47. 47. Comprehensive Unit-Based Safety Program (CUSP)• . CUSP lets hospital identify safety concerns, learn about successful approaches, develop and initiate solutions, and perform regular safety assessments based on data analytics.
  48. 48. HealthMap- Tracking Emerging Health Threats Through Online Database• . HealthMap is one such innovation that is a freely accessible, automated electronic data-mining project for monitoring, organizing, and visualizing reports of global disease outbreaks according to geography, time, and infectious disease agent.
  49. 49. HealthMap• In operation since 06, and created by John Brownstein, and Clark Freifeld of Childrens Hospital Boston and Harvard Medical School, HealthMap acquires data from a variety of freely available electronic media sources (e.g. ProMED- mail, Euro surveillance, Wildlife Disease Information Node to obtain a comprehensive view of the current global state of infectious diseases. Thus, HealthMap is a public website bringing together disparate data sources to achieve a unified view of the current global state of infectious diseases.
  50. 50. Decision Analysis Helps Allocate Health Care Funds in the UK• . In some cases, decision-making techniques can be used to maximize allocatory efficiency – The UK’s National Health Service (NHS) is funded through general tax revenues. The funds are dispersed to about 105 different local health authorities, amounting to annual funding for approximately $35 billion. With such a large sum of national funds going to such an important area, the decision-making process to justly allocate funds can be difficult indeed.
  51. 51. The Use of Goal Programming for Tuberculosis Drug Allocation in Manila• The objective function of the model was to meet the target cure rate of 85% (which is the equivalent of minimizing the underachievement (saticficing) in the allocation of anti-TB drugs to the 45 centres).• Four goal constraints considered the interrelationships among variables in the distribution system. – Goal 1 was to satisfy the medication requirement (a six-month regimen) for each patient. – Goal 2 was to supply each health centre with proper allocation. Goal 3 was to satisfy the cure rate of 85%. – Goal 4 was to satisfy the drug requirement of each health centre.
  52. 52. Using Bayes’ theorem to develop a decision tree• A group of medical professionals is considering the construction of a private clinic.• If the medical demand is high (i.e, there is a favourable market for the clinic), the physicians could realize a net profit of $ 100,000.• If the market is not favourable, they could lose $40,000. Of course, they don’t have to proceed at all, in which case there is no cost. In the absence of any market data, the best the physicians can guess is that there is a 50-50 chance the clinic will be successful. The market research team using the Bayes’ theorem of probability constructed a decision tree to help analyze this problem and take best course of action for the medical professionals.
  53. 53. Conclusion• Data analytics focuses on inference, the process of deriving a conclusion based solely on scientific knowledge and facts.• More recently, the data has been increasingly used by health care organizations as a part of Business Intelligence, to make strategic decisions and choices, and to gain competitive advantage in market.• Today, analytic strategy is viewed as a key engine of a dynamic capability of an organization.• Indian HCOs need to generate quality data first and then analyze this for strategic decisions and research.
  54. 54. The difficulty lies not so much indeveloping new ideas……………….. as in escaping from theold ones If you are not riding the wave of change… …. then you will find yourself beneath it.
  55. 55. Role of IT in Analytics• Having a strong analytical orientation would seem to be a function of data and information technology (IT), and indeed those resources are critical for analytical success.• . Providing data for analytical applications mean that it must be of high quality, separated from transaction systems in a data warehouse or single-purpose “mart” and consistent throughout the organization.
  56. 56. Leveraging analytics in Health care• Health information and analytics have been extensively used in healthcare to measure health status of the population, to assess their health problems, for making comparisons for health status, for planning and administration of quality health services and for carrying out scientific research.• The data has been increasingly used by health care organisations as a part of BI, to make strategic decisions and choices, and to gain competitive advantage in market.• Today, analytic strategy is viewed as a key engine of a dynamic capability of an organization.
  57. 57. DELTA- Model for Assessing Analytical Capability• Data: should be discrete, granular, and clean (with no missing values or outliers) and standardised across the health care organizations. Data quality is no longer a technical matter but rather a vital enterprise discipline with discernible consequences for the organizational productivity and efficiency.• Enterprise: An enterprise approach to analytics implies that organizations work across functions in a unified manner rather than fragmented nature of information held in disparate silos.• Leadership: The leadership should be committed to use analytic tools and techniques to achieve strategic goals. Leadership analytic focus is as important as technological innovations to achieve strategic objectives.• Target: The healthcare organizations must have a long term strategic target with a broad based strategic intent followed by analytics focused strategy. The leadership must commit adequate recourses to achieve strategic targets.• Analysts: The healthcare organizations must have analytic talent, either in house, or consultants to provide continuous high quality advice.
  58. 58. FUNCTION DESCRIPTION EXEMPLARSSupply chain Simulate and optimize supply chain flows; reduceDell,Wal-Mart, Amazoninventory and stock-outs.Customer selection, Identify customers with the greatest profitpotential; Harrah’s, Capital One,loyalty, and service increase likelihood that they will want theproduct or Barclaysservice offering; retain their loyalty.Pricing Identify the price that will maximize yield, or profit.Progressive, MarriottHuman capital Select the best employees for particular tasks orjobs, New England Patriots,at particular compensation levels. Oakland A’s, Boston Red SoxProduct and service Detect quality problems early and minimizethem. Honda, IntelqualityFinancial Better understand the drivers of financial performanceMCI, Verizonperformance and the effects of nonfinancial factors.Research and developmentImprove quality, efficacy, and, whereapplicable, safety Novartis, Amazon, Yahoo
  59. 59. TELE HEALTH CENTRE FOR RURAL INDIA A bottom to top approach for improving health careDr. Shilpa facilities at rural remote areas.Dr. Neha Asija 1ID no.-96
  60. 60. Dr. Shilpa, 96OVERVIEW OF PRESENTATION 2
  61. 61. Dr. Shilpa, 96 Rural development: A Prerequisite for National development• 68.84 % of India’s population resides in rural areas.• Most of Secondary & Tertiary care facilities are in cities and towns.• Low penetration of healthcare services.• Lack of investment in health care.• Problem of retention of doctors in rural areas.• Inadequate medical & diagnostic facilities in rural areas. 3
  62. 62. Dr. Shilpa ,96HEALTH CARE PARADOX 4
  63. 63. Dr. Shilpa ,96 TELE -MEDICINE According to World Health Organization (WHO) Telemedicine is defined as “the delivery of healthcare services,where distance is a critical factor, by all healthcare professionals usinginformation and communication technologies for the exchange of valid information for diagnosis, treatment and prevention of disease and injuries, research and evaluation and for continuing education of healthcare providers, all in the interests of advancing the health of individuals and their communities”. 5
  64. 64. Dr. Shilpa ,96 TYPES OF TELEMEDICINE TELE MEDICINE Store Two-Way & Interactive Forward Television Tele-radiography, Video conferencingNon-emergency a face to face & situations ‘real time’ Tele-dermatolgy consultation 6
  65. 65. Dr. Shilpa ,96 Point • One patient connected to to one doctor • Within same hospital Point Point • One patient end at a time connected to many to specialist doctors VARIOUS WAYS OF Multi Point • Within the same hospitalCOMMUNICATION • Several patient ends connected to several Multipoint different specialist doctors to • At different hospitals, in Multipoint different geographical distances 7
  66. 66. Dr. Shilpa ,96 SWOT ANALYSIS STRENGTHS WEAKNESSES• Improved accessibility • Limited awareness of tele• Continuous medical health and its benefits education • Sustainability of the model OPPORTUNITIES THREATS• Continue technical • Concern associated with development and standardization innovations • Medico legal aspects• Expanding internet literacy and usage 8
  67. 67. Dr. Shilpa ,96BARRIERS TO IMPLEMENTATION SOCIO- CULTURAL TECHNO- LEGAL BARRIERS LOGICAL ISSUES ECONOMIC ISSUES 9
  68. 68. Dr. Shilpa ,96 Proposed modified model Primary Health CentreOutsourcing Source : Indian Space Research Organization(ISRO) 10
  69. 69. Dr. Shilpa ,96Super Level 3SpecialtyHospitalStateMedical Level 2CollegeDistrictHospital Level 1 / MMOBILE CHC PHC 11
  70. 70. Data • Patient’s medical record and related preparation images are transferred from consultancy centre to specialty centre. & P Transfer phase • Tele- consultation date is fixed. H • Depending on the availability of the requested doctor the appointment is A Consultation accepted, rejected or kept pending. phase S • The appointment details are sent to the consultation center. E • After the consultation the doctor S Post gives his opinion on the case and instructions through a post consultation consultation page. phase • Patient’ information is stored.Dr. Shilpa ,96 12
  71. 71. Dr. Shilpa ,96A way forward 13
  72. 72. Dr. Shilpa ,96 14
  73. 73. Dr. Shilpa ,96
  74. 74. 1Emerging role of Informatics to improve Population Health Ashish Joshi M.D., M.P.H., PhD Assistant Professor Center for Global Health and Development and Department of Health Services Research Administration College of Public Health, University of Nebraska Medical Center Email: ashish.joshi@unmc.edu Phone: 402-559-2327
  75. 75. Presentation Format2  Defining Informatics and its categories  Role of Informatics in Disease Prevention and Management  Human Centered Informatics Platform  Case studies  Future work Ashish Joshi M.D., MPH
  76. 76. Research Map Evidence based Management Health Outcomes (Clinical training) Informatics Technology Evaluation Prevention/Population (Public Health Training)3 Ashish Joshi M.D., MPH
  77. 77. Informatics: Any activity that relates to computing or science of information where information is defined as data with meaning.Biomedical Informatics: Science of information applied to or studied in the context of biomedicine. Bernstam et al Journal of Biomedical Informatics, 43 (1):104-110
  78. 78. Bio Informatics Imaging(Molecular and cellular Informatics processes) (Tissue) Biomedical Informatics Public Health Clinical Informatics Informatics (Populations) (Individuals)
  79. 79. Public Health Informatics Systematic application of information and computer science and technology to public health practice, research, and learning. (Yasnoff, 2003)
  80. 80. Informatics in Disease Prevention and ManagementData acquisition Information Analysis InformaticsHealth Outcomes Knowledge Dissemination Representation
  81. 81. Multi-dimensional Human Mind Health Data Processing Data Information lost Time data (When) Information retained Attribute data (Who, What & How) Information Aid overload Place Decision data Human Centered (Where) Making Informatics approaches8 Ashish Joshi M.D., MPH
  82. 82. End users •Demographic •Cultural •Behavioral •Contextual •Clinical •Technology •Access •Cost •Infrastructure•Reimbursement
  83. 83. Technology Mediated Intervention Framework Attribute data “How, why, who, Spatial data Temporal data what” “Where” “When” Population health data Human Centered Informatics methods to support Multidimensional, Multifactorial and Evidence based interventions Prevention Monitoring Referral Management Health Lifestyle Social Clinical Education Modification Support Management Improve healthcare Improve population health Provide cost effective,10 access outcomes sustainable solutions Ashish Joshi M.D., MPH
  84. 84. Computer Psychologists science Doctors Information Nurses INFORMATICS systems Dietitian Public Health Allied healthcare professionals11 Ashish Joshi M.D., MPH
  85. 85. Manifold needs of individuals Information about the illnessesTreatment Social and Options Interactive Health Decision makingAvailable Technologies support Lifestyle and behavior support
  86. 86. Challenges of using Health Information Technology Access to technology and skills Financial Lack of andawareness Challenges technical barriers Privacy and Quality
  87. 87. Human Centered Informatics Platform •User age, gender, • Set of input attributes education • If-then decision rule •User clinical variables algorithm •User Knowledge, Attitudes & Practice (KAP) Data Information Acquisition ProcessingUser interaction Library of Health metrics InformationInformation seeking Disease specific behavior modules Knowledge Evaluation Representation • ↑access to health information • Multiple content layout • ↑ Knowledge and • Multimedia visualization attitude change • Better Health Outcomes 14
  88. 88. Variables U.S.A. Brazil India Geographic disparity X X X Cultural disparity X X X Income disparity X X X Health Education X X X Chronic disease X X X Healthcare access X X X Healthcare cost X X X Internet access XXX XX X Cell Phone use X X X Health reimbursement Insurance Public/Private/out of Out of pocket costs/Public pocket costs Costs of Technology X XX XXX Cell phone Portable enabled Electronic Mobile Health Telehealth disease Medical Record Ambulance Information prevention and Kiosk monitoring Develop a reimbursable and sustainable cost effective population based Innovative HC Technology15 adoption model to reduce health disparities and improve population health outcomes Ashish Joshi M.D., MPH
  89. 89. Consumer Health Information Platform Cell phone Portable enabled Health disease Information prevention and Kiosk monitoring16 Ashish Joshi M.D., MPH
  90. 90. Health Education Modalities Internet Individual Face to Printed Group Video CD/DVD Face material Educator Educator Limited Evaluation e.g. GoogleU U U U E.g. type in “hypertension” Material not Tailored Limited Time 65,100,000 results Information Overload Feb 4 2012
  91. 91. Interactive Health Information Platform Allow users to self-pace the program. Materials targeted or tailored. Material presented in multiple formats including graphics, text and audio. Allows optimization of form, duration and content of the educational modules.
  92. 92. Information Flow within IHIP Content attribute Technology Platform Usage User e.g. cell phone, Outcomes dataFeatures computer Assessment Interface attribute
  93. 93. • Emergency room • Asthma (6) • Primary care clinics • Influenza (7) • Clinic waiting rooms • Multiple Myeloma (8) • Multiple Sclerosis • Metabolic Syndrome • Rural • Breast Feeding Nutrition • Slum (9) • Tribal Settings Medical Conditions Outcomes Target Assessed populations • Knowledge • Children • Attitudes • Adults • Practices • Veterans • CVD Screening • Spanish speaking mothers20 Ashish Joshi M.D., MPH
  94. 94. Version 2Version 1
  95. 95. Version 3 Version 4
  96. 96. Acceptance of Interactive Health Information Program 97 % 94% 91% 89% 75%Easy to use Interesting Enjoyable Easy to Use it in navigate futureA. Joshi et al. A Pilot study to evaluate self initiated computer patient education in children. Technol Health Care. 2007;15(6):433-44
  97. 97. Improvement in Asthma Knowledge Scores 15% 13% 5% Total study subjects Those age ≤ 11 years Those age ≥ 11 yearsA. Joshi et al. A Pilot study to evaluate self initiated computer patient education in children. Technol Health Care. 2007;15(6):433-44
  98. 98. Change in Attitudes towards Influenza Vaccine 67.78% 63.3% 42.2% Before 30% After 14.4% 8.89%The child does not need Worried that child may get Child could get bad flu shot flu once flu shot is given reaction after getting flu shotA. Joshi et al. Evaluation of computer-based Patient Education and Motivation tool on KAP Influenza Vaccination. 2009;12:1-15
  99. 99. 28 Ashish Joshi M.D., MPH
  100. 100. 29 Ashish Joshi M.D., MPH
  101. 101. 30 Ashish Joshi M.D., MPH
  102. 102. EVALUATION OUTCOMES IMPROVEMENT SUSTAINABILITY Existing TARGETED USERS challenges REIMBURSABLE AND SERVICES COST EFFECTIVENESS31 Ashish Joshi M.D., MPH
  103. 103. Future Directions Design and evaluate HC informatics mediated interventions that are;  Sustainable  Multifaceted  Accessible  Reimbursable  Tailored Create practice based informatics solutions through effective collaborations among different stakeholders for improving health outcomes.
  104. 104. Related Publications A Joshi et al. A Pilot Study to Evaluate SELF INITIATED COMPUTER Patient Education in Children with ACUTE Asthma in Pediatric Emergency Department. Technol Health Care. 2007; 15 (6):433-44 A Joshi. A Prototype Evaluation of a Computer-Assisted Physical Therapy System for Osteoarthritis. Journal of Geriatric Physical Therapy: 2008 - Volume 31 - Issue 2 - p 71–78 A Joshi, et al. Prospective tracking of a Pediatric Emergency Department E-kiosk to deliver Asthma Education. Health Informatics Journal. December 2009 vol. 15 (4) 282- 295 A Joshi, et al. Usability of a Patient Education and Motivation tool using Heuristic Evaluation JMIR 2009 Nov 6; 11(4):e47. A Joshi, et al. Evaluation of a Computer-based Patient Education and Motivation Tool on Knowledge, Attitudes and Practice towards Influenza Vaccination. International Electronic Journal of Health Education, 2009; 12:1-15 A Joshi et al. Design and Development of a Computer based Multiple Myeloma Educational Kiosk in VA settings. 2009 International Cancer Education Conference & AACE-CPEN-EACE Joint Annual Meeting. A Joshi et al. Use of Medical Education Computer Kiosks in Different Clinical Settings. Pediatric Academic Societies’ Annual Meeting in Baltimore, Maryland, May 2-5, 2009
  105. 105. 34 Thanks and Questions!!! Ashish Joshi M.D., MPH
  106. 106. Perceived benefits of hospital information system & EMR by end users Presented By:Anindam Basu & Dr. Anandhi Ramachandran8th IAMI Biennial Conference (Improving Health Through IT) 3rd to 5th February 2012. AIIMS, New Delhi 1
  107. 107. Role of ict in healthcare… Information Systems acts as a Support to the Healthcare Industry. Lots and Lots of Data present in the Healthcare Industry. Knowledge Information Data 2
  108. 108.  Studies describes about ICT systems as follows: ICT implementation is an organization process Substantial potential To improve patient safety Increase Organizational Efficiency Increasing Patient Satisfaction Wrong perception ICT overcomes the role of people involved Patient Care is Hindered 3
  109. 109. Classes to determine the success of ict system User Attitudes and Perception. Use of the System itself (80/20 Rule) User Performance with the system. 4
  110. 110. literature behind the study… Delpierre C et al, 2004: Provided Systematic Review of 26 Papers.  Focusing on User perceptions using EHR.  Increases patient as well as user satisfaction.  Qualitative Nature. Hier DB et al, 2004: Physicians Perception across one hospital in Chicago.  80% acceptance rate (out of 191 physicians). O’ Connell RT et al, 2004: Survey done in two specialties (medicine and pediatrics)  Satisfaction level was high.  Others were not satisfied. Kimiafar K, 2006: Hospital Information System  57.7 % of the users were satisfied 5
  111. 111. types of perceived benefits… Direct Benefits: Reduced Medical Errors; Paper Reduction etc. Indirect Benefits: Improve quality of care; Improve access to data; Increased Patient Satisfaction. Strategic Benefits: Improve Patient Safety; Improve Organization Image. 6
  112. 112. objectives behind the study… Studythe Perception of the Hospital Staff towards the ICT system. Study the kind of problems faced by the staff of the Hospital. Government Hospital  Location: Delhi  152 Inpatient Beds  30 Casualty and 26 ICU Beds  9 Departments  Presently has HIS for Administrative Purpose & EMR for Clinical Purpose.  ICT systems working more than 1.5 Years. 7
  113. 113. Ict Applications used in the hospital… Open Source EMR & Lab Module PACS from GE Centricity Telemedicine Centre Access and Biometric Control (for attendance and security) Hospital Information System  Patient Registration  Patient Appointment System for OPD with Queue Management System  Cashiering Module (Billing Module)  Surgery Module  Inventory Management System Computerized MLC Report (From EMR Template). 8
  114. 114. Methodology… Definition of the Sample: The respondent should be a regular staff of the Hospital & should be using either the HIS/EMR application. Sample Size: 52 Questionnaire Based Study (13 Questions) Random Sampling SPSS Version 16.0 used. Study Conducted: May 2011 Limitations:  Less number of Respondents  Open Ended Questions for taking the Holistic Views. 9
  115. 115. Profile of the respondents No. of Respondents Experience 30 No. of Respondents 20 20 18 16 16 14 12 13 10 13 8 6 9 4 3 2 0 Less than 6-12 6 months 1-3 years months More than 3 yearsPhysicians Nurses Other Staff 10
  116. 116. It importance for the hospital 1 5 Less Important25;17 Moderate Important 21;20 Very Important 11
  117. 117. Finding HIS/EMR 1 14 18 Very Easy Easy Moderate Difficult Very 28 Difficult 12
  118. 118. Average time spend to the application More than 3 Hrs 10,2Average Time Spend 1-3 hrs 7,6 30min to 1 Hr 10,3 25,2;3(O) Less than 30 minutes 0 5 10 15 20 25 No. Of Respondents 13
  119. 119. Improvement after the implementation Neutral Improved a little bit Satisfactory Improvement Tremendously Improved 8% 14%40% 38% 14
  120. 120. Major issues faced by theM… Technology Issues: Computer and Application getting hanged Application takes longer time to open Less support from the vendor Lesser GUIs in the application Process Issues: Manual and Electronic Record is to be maintained. Training issues to the new employees. ICT System Rating: 7/10 15
  121. 121. Benefits perceivedBenefit Type Perceived Benefit Direct 1) More Easy Follow up visits in OPD 2) Reduction in Turn Around Time in OPD 3) Reduction in Medical Errors Indirect 1) Easy Accessible data of Patient anytime 2) Increase patient satisfaction 3) Employees more accountable 4) Improved Documentation 5) Increase efficiency and effectiveness of the employees Strategic 1) PACS & EMR: Faster Decisions 2) Increase Patient Safety 3) Faster response to physicians clinical orders 4) Improved Hospital Image 16
  122. 122. Conclusion and discussion 17
  123. 123. recoMMendations… Regular Monthly assessment. Updation of the technology used (thin clients & server). Vendor support is a must Process changes: Electronic Record Staff should be aware of the interfaces GUI interfaces in the application wherever possible. People are important asset for any ICT system, but processes and Technology also plays a significant role for the success. 18
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