More research is needed to document both the value of eHealth for strengthening resource-limited health systems and the challenges involved in their implementation and adoption, so that insights from such research may be used to inform future initiatives. While many studies of eHealth for patient care in low- and middle-income countries (LMIC) are taking place, evidence of its role in improving administrative processes such as financial management is lacking, despite the importance of ‘good governance’ (transparency and accountability) for ensuring strong and resilient health systems.
The overall objective of this PhD was to elucidate the enablers, inhibitors and outcomes characterising the implementation and adoption of a modular eHealth system in a group of healthcare facilities in rural Malawi. The system included both clinical and billing modules. The specific objectives were (i) to understand the socio-technical, organisational and change management factors facilitating or hindering the implementation and adoption of the eHealth system, (ii) to assess the quality of data captured by the eHealth system compared with conventional paper-based records, and (iii) to understand how information within the eHealth system was used for service delivery, reporting and financial management. A further aim was to contribute to the corpus of mixed-methods case studies exploring eHealth system implementation processes and outcomes (including data quality) in LMIC. As described in the following chapters, the research also gave rise to unanticipated and serendipitous findings, which led to new lines of enquiry and influenced the theoretical perspectives from which the analysis drew.
For the hospital case study (Case Study 1), a retrospective single-case embedded design was employed, with outpatient and inpatient departments being the two units of analysis. Qualitative data included document review and in-depth key informant interviews, while quantitative data was obtained from the web-based District Health Information System (DHIS2), patient files and the hospital’s finance records. For the study of primary health centres (Case Study 2), a single-case embedded design was also used, with the rollout project as the case and the three units of analysis being 3 Early Adopter Facilities, 4 Late Majority facilities and 2 Laggard facilities. This case study used a prospective design, with data being collected 7 months and 24 months after implementation of the eHealth system due to a mismatch between the independent eHealth implementation project and the PhD research. Data sources included documentation screened against the criteria listed in the Performance of Routine Information System Management (PRISM) tools, information extracted from the eHealth system, health indicators drawn from DHIS2 and qualitative data from focus group discussions. In both case studies, framework analysis was used for qualitative data with the aid of NVivo, while quantitative data was analysed by calculating data completeness, accuracy and agreement. Descriptive statistics and the Mann-Whitney U-test were used for analysing finance data in Case Study 1. Content analysis was also used to gain insights from Case Study 2 aided by SPSS.
Converging the results of these two case studies illustrates the potential of eHealth to strengthen LMIC health systems through developing human resource capacity (skills, staff roles), facilitating service delivery, and improving financial management and governance. However, realising such improvements is dependent upon understanding the socio-technical interactions mediating the integration of new systems into organisational processes and work practices, and implementing appropriate change management interventions. The results of this study suggest that, for effective implementation and adoption of eHealth systems, healthcare leaders should (1) recruit data entry clerks to relieve clinical staff, improve workflow and avoid data fraud, (2) facilitate appropriate data use among system users and an information culture at the facilities, and (3) strengthen knowledge and skills transfer from eHealth system developers to local implementers and system champions, to optimise responsiveness and ensure sustainability. Further interdisciplinary research is needed to obtain additional insights into factors affecting the quality of eHealth data and its use in the management of LMIC health systems, including the role of social, professional and technological influences on financial good-governance.