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Supporting Clinical and Public Health Decision Making Through An EMR System In Haiti

Supporting Clinical and Public Health Decision Making Through An EMR System In Haiti. Emmlyne Emmanuel, MD Former EMR Manager. Janet Baseman 1 , Emmlyne Emmanuel 2 , Kurt Jean Charles 3 , Sujata Bijou 1 , Jen Antilla 1 , Jan Flowers 1 , and Bill Lober 1

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Supporting Clinical and Public Health Decision Making Through An EMR System In Haiti

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  1. Supporting Clinical and Public Health Decision Making Through An EMR System In Haiti Emmlyne Emmanuel, MD Former EMR Manager Janet Baseman1, Emmlyne Emmanuel2, Kurt Jean Charles3, Sujata Bijou1, Jen Antilla1, Jan Flowers1, and Bill Lober1 1International Training and Education Center for Health, University of Washington, Seattle; 2Emory University, Atlanta, Georgia; 3Solutions, Inc, Port au Prince, Haiti

  2. Outline • Background on iSanté • Functions of the system • Uses of data • Training and clinical mentoring • Results • Next Steps • Conclusions

  3. Background • As of July 2011: • 70 facilities • ~71k patients iSanté sites as July 2011 Green: currentlyreplicating Red: no replication >2 weeks and< 3months Black: No replication > 3 months

  4. Components

  5. iSante Consolidated Dashboard

  6. iSante Patient Cover Sheet

  7. Patient Lab History

  8. iSantePatient Forms

  9. Reporting • Patient-specific records and summary data • Clinic-level reports to support operations • Data quality reports to support improved… data quality

  10. Data Quality Reports

  11. Use of Data for Population level reporting of PEPFAR, Global Fund indicators • Link to MSPP National Reporting system MESI • Public and restricted views • Developed by Haitian IT firm: Solutions • Uses IXF (WHO format) for indicator transmission • Link to MSPP Care Surveillance system • Uses the CDA standard to report patient level data to NASTAD for case surveillance

  12. MESI – weekly data share “Surveillance”-Online Haiti National HIV/AIDS Surveillance System MESI-offline – weekly data share “Surveillance”-Offline MESI HAITI (clean) HIV/AIDS Case Surveillance Database MESI ITECH National EMR – monthly data share Automated and Manual Intra- and Inter-System Case Deduplication GHESKIO EMR – monthly data share PIH EMR – monthly data share MoH NASTAD, 2010

  13. Training and Clinical Mentoring

  14. IT support POC Vs Forms Entry

  15. Results Percent of active clinics running at least one report

  16. Implementation of facility-level registration system (FPI) Interoperability / Data exchange with other HMIS at the facility-level Facility-level Patient Index (FPI) Patient Demographics Patient Demographics Demographics EDT (Pharm) Lab Results Meds Dispensation OpenELIS iSante Physician Orders Prescription New Deployment Architecture Registration with integrated biometrics • Automated systems management platform for configuration • Virtual machine appliances – virtual machines with pre-configured and ready to run software • Unsupervised installation and upgrades

  17. Conclusion • Use of HIS for tracking the burden of a health problem and health outcomes • Maximizing data quality in EMRs deployed in LDC is important in order to • improve clinical outcomes, • accurately measure and represent burden of disease • and allocate resources appropriately. • Training, Access to population health data, and improvement of IT equipment and software can improve use of the system and quality of data generated.

  18. For more information regarding iSante, please visit www.go2itech.org I-TECH Contacts Bill Lober, Director of Informatics, lober@uw.edu Jan Flowers, Technical Program Manager, jflow2@uw.edu

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