Success factors for implementing and sustaining a mature electronic medical record in a low-resource setting: a case study of iSanté in Haiti.

Electronic health information systems, including electronic medical records (EMRs), have the potential to improve access to information and quality of care, among other things. Success factors and challenges for novel EMR implementations in low-resource settings have increasingly been studied, although less is known about maturing systems and sustainability. One systematic review identified seven categories of implementation success factors: ethical, financial, functionality, organizational, political, technical and training. This case study applies this framework to iSanté, Haiti's national EMR in use in more than 100 sites and housing records for more than 750 000 patients. The author group, consisting of representatives of different agencies within the Haitian Ministry of Health (MSPP), funding partner the Centers for Disease Control and Prevention (CDC) Haiti, and implementing partner the International Training and Education Center for Health (I-TECH), identify successes and lessons learned according to the seven identified categories, and propose an additional cross-cutting category, sustainability. Factors important for long-term implementation success of complex information systems are balancing investments in hardware and software infrastructure upkeep, user capacity and data quality control; designing and building a system within the context of the greater eHealth ecosystem with a plan for interoperability and data exchange; establishing system governance and strong leadership to support local system ownership and planning for system financing to ensure sustainability. Lessons learned from 10 years of implementation of the iSanté EMR system are relevant to sustainability of a full range of increasingly interrelated information systems (e.g. for laboratory, supply chain, pharmacy and human resources) in the health sector in low-resource settings.

An assessment of data quality in a multi-site electronic medical record system in Haiti.

OBJECTIVES: Strong data quality (DQ) is a precursor to strong data use. In resource limited settings, routine DQ assessment (DQA) within electronic medical record (EMR) systems can be resource-intensive using manual methods such as audit and chart review; automated queries offer an efficient alternative. This DQA focused on Haiti's national EMR - iSanté - and included longitudinal data for over 100,000 persons living with HIV (PLHIV) enrolled in HIV care and treatment services at 95 health care facilities (HCF). METHODS: This mixed-methods evaluation used a qualitative Delphi process to identify DQ priorities among local stakeholders, followed by a quantitative DQA on these priority areas. The quantitative DQA examined 13 indicators of completeness, accuracy, and timeliness of retrospective data collected from 2005 to 2013. We described levels of DQ for each indicator over time, and examined the consistency of within-HCF performance and associations between DQ and HCF and EMR system characteristics. RESULTS: Over all iSanté data, age was incomplete in <1% of cases, while height, pregnancy status, TB status, and ART eligibility were more incomplete (approximately 20-40%). Suspicious data flags were present for <3% of cases of male sex, ART dispenses, CD4 values, and visit dates, but for 26% of cases of age. Discontinuation forms were available for about half of all patients without visits for 180 or more days, and >60% of encounter forms were entered late. For most indicators, DQ tended to improve over time. DQ was highly variable across HCF, and within HCFs DQ was variable across indicators. In adjusted analyses, HCF and system factors with generally favorable and statistically significant associations with DQ were University hospital category, private sector governance, presence of local iSante server, greater HCF experience with the EMR, greater maturity of the EMR itself, and having more system users but fewer new users. In qualitative feedback, local stakeholders emphasized lack of stable power supply as a key challenge to data quality and use of the iSanté EMR. CONCLUSIONS: Variable performance on key DQ indicators across HCF suggests that excellent DQ is achievable in Haiti, but further effort is needed to systematize and routinize DQ approaches within HCFs. A dynamic, interactive "DQ dashboard" within iSanté could bring transparency and motivate improvement. While the results of the study are specific to Haiti's iSanté data system, the study's methods and thematic lessons learned holdgeneralized relevance for other large-scale EMR systems in resource-limited countries.