As an example, let’s assume that a non-government organization (NGO) manages public health programs in Chin State, Myanmar. This remote, conflict-affected region has no government health infrastructure except for the NGO. The normal data flow of health information is done by taking pictures of paper records and compiling them into different spreadsheet files, an unsustainable solution.
Now, let’s say that they are planning to launch the initiative of implementing a health information management system (HMIS), specifically, District Health Information System v2 (DHIS2). It would enable data centralization and improve disease surveillance. It provides a stable and sustainable digital solution for both under-resourced and developed communities. This avoids the need for future transitions to other health systems and ensures interoperability with various standards. This could strengthen the information and governance building blocks of the health system, enabling responsiveness and improved efficiency as its outcomes.
However, this initiative could face numerous barriers. The two major problems are financing and resources. To keep the digital system running, they must rely on either on-premises or cloud computing but also maintain the chosen infrastructure. The NGO relies on grants, creating a risk if funding ends. Resource challenges, particularly high staff turnover and the time required to recruit qualified personnel pose significant problems. Each new staff member can lead to delays in data reporting, increased data entry errors, higher training costs, and longer onboarding times.
In terms of allocative efficiency, I would only support this initiative if the inefficiencies of the current spreadsheet-based system are not an evitable problem, significantly impeding the health system’s goals.