Opportunities for mhealth in the Developing World: OpenMRS

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1 Opportunities for mhealth in the Developing World: OpenMRS Hamish SF Fraser MBChB, MSc, FACMI Assistant Professor, Division of Global Health Equity, Brigham and Womens Hospital and Harvard Medical School Senior advisor for medical informatics, Partners In Health

2 What do we use EMR data for? Clinical care and quality improvement Reporting to clinicians, managers, funders Logistics and supply chain management Clinical research

3 OpenMRS: a modular, open source, EMR platform Uses concept dictionary for data storage Modular design simplifies adding new functions and linking to other systems Released with open source license (April 2007) Core of paid programmers with growing community support Clinical use in over 50 developing countries Secure logins and auditing of data access and changes Developed as a collaboration of PIH, the Regenstrief Institute and the South African MRC Partners In Health Regenstrief Ins1tute Medical Reseach Council South Africa

4 OpenMRS spread: > 50 countries, (more not yet mapped

5 Physician looking up ARV patients Photo Rockefeller Foundation

6 Clinical consults Lara Kellet, funding CDC

7 La Colline, Haiti Patient visits & diagnoses

8 Using patient registration data Image, Jitka Hiscox

9 Standards and Interoperability Standardized concept dictionary with mapping to ICD10, SNOMED and others (CEIL) Maternal Concept Lab (MCL) Interoperability with mhealth software Modular architecture SMART Apps

10 mhealth Platforms linked to OpenMRS Sana MIT Open Data Kit: U. Washington ComCare: DiMagi, Cambridge OpenXdata: Bergen

11 Support for SMART Apps Childrens Hospital Informatics Program

12 Open Development Sharing source code Sharing modules Sharing concept dictionary Comparing outcomes Sharing de-identified data Sharing decision support tools Analysis of system performance with sharing of data on adverse events a problem with HIPAA

13 Evaluation: RCT of Alerts for HIV care Printed reminders from OpenMRS for pediatric HIV care in Kenya: overdue 6-week HIV DNA polymerase chain reaction tests 18-month (ELISA) antibody tests CD4 tests routine laboratory studies chest radiographs initiating Anti-Retroviral Therapy referring malnourished children for nutritional evaluation and assistance Were MC, et al. Pediatrics Mar;131(3):e789-96

14 Evaluation They randomized 1611 patients, (30 providers) They studied completion of overdue clinical tasks over the five months of the study Showed improvement in task completion when the providers had the reminders: (68% intervention vs 18% control, P<.001). Tasks occurred earlier in the intervention group (77 days, SD 2.4 days) control group (104 days, SD 1.2 days) (P<.001).

15 Call to Action on Global ehealth Evaluation Consensus Statement of the WHO Global ehealth Evaluation Meeting, Bellagio, September 2011 To improve health and reduce health inequalities, rigorous evaluation of ehealth is necessary to generate evidence and promote the appropriate integration and use of technologies.

16 University hospital of Mirebalais, Haiti OpenMRS 2.0 point of care EMR PIH, OpenMRS, Thoughworks Inc.

17 Collaborators and Funders Partners In Health Regenstrief institute World Health Organization US Centers for Disease Control Brigham and Women hospital Harvard Medical School Millennium Villages Project International Development Research Centre, Ottawa Rockefeller Foundation Thoughtworks inc. Google Inc

18

19 OpenMRS is growing fast Wide deployment to more than 50 LMICs Large scale rollouts in Rwanda, Kenya, the Philippines Wider range of diseases: Oncology, Heart Disease, Diabetes, Primary Care, Surgery More direct point of care use Wider use as part of mhealth projects Linking to broader ehealth architecture projects

20 You need bottom up and top down Bottom up Address clinical needs and problems Ensure data quality Local ownership and priorities Top down Plan for wide use Horizontal approach to disease healthcare Core data set and use of open standards Evaluation and evidence based decision making

21 Problems and Challenges Entry level solutions can be hard Easy configuration for non-programmers Getting data out of OpenMRS and simplifying reporting Making it more user friendly Infrastructure, infrastructure

22 Levels of development of OpenMRS 1. Site specific implementation/customization 2. Distribution/implementation package: specific clinical requirements and organization 3. Develop application tools/components forms, reports, summaries, data visualization, flow sheets, data import and export tools etc. 4. Interoperability with related applications Labs, pharmacy, mhealth, MOH reporting etc. 5. Modify the OpenMRS Platform and API

23 The PIH OpenMRS timeline and creation of new components. Synchronization HTML forms Reporting framework Patient registration New UI

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