One Data: COVID-19, health data connectivity and integration in Indonesia – a case study of Yogyakarta
An effective response to a global crisis such as the COVID-19 pandemic is dependent on health departments and governments having access to information that is up to date and collated through a central system.
The value of reliable data in dealing with the coronavirus has been evident when it comes to forming policy responses and managing community wellbeing.
Integrating health data and information systems is a challenge for a population as large as that of Indonesia with nearly 270 million people spread across 34 provinces and 541 districts. And the pandemic showed just how significant these challenges were in the collection of timely, accurate and complete data about case numbers across the country.
One of the biggest impediments to generating reliable data has been the limited integration between various levels of government and private information systems. This has put a burden on healthcare workers who on a daily basis often have to enter the same data into multiple applications, using systems that do not always work smoothly, which forces the use of informal workarounds to reconcile data from different systems.
Added to the difficulty is the decentralisation of the nation’s governmental structures. The decentralisation of powers from national to sub-national level has allowed districts to make their own policies on the pandemic response, including developing their own applications to collect and analyse data. This has created data duplication, inconsistency and information gaps. Compounding the mismatch are the number of legacy systems – information and communication systems set up by health facilities to support patient services before the COVID-19 pandemic – that do not integrate with the newer COVID-19 applications.
In late 2020, the Indonesian government recognised this problem and launched its Satu Data Indonesia (One Data) project. The One Data project acknowledged the misalignment of COVID-19 data between central and district governments, and the importance of data accuracy. It also identified a pattern of inconsistent, missing or duplicated data, the impact of which creates difficulties in forming appropriate health policy responses.
This report explores the extent of the COVID-19 data connectivity issue. It also proposes ways to improve health information system integration by using enterprise architecture (EA) principles. EA is a management technique that is successfully used in the private sector to bridge the communication gap between business and IT stakeholders. We focused our research on the Special Region of Yogyakarta province, which has four districts and municipalities with several parties involved in creating and using COVID-19 data. An Australia Indonesia Centre team of technology, health informatics and behavioural information researchers used the EA approach to explore the current connectivity landscape.
Ultimately the report makes four key recommendations on government priorities to improve data capture and effectiveness in the health system.
- Adopt the open health information exchange (OpenHIE) framework to build an interoperable data standard across health institutions.
- Use this enterprise architecture to create a national standard for data capture and align governments at all levels.
- Develop data protection policies to protect sensitive information and guarantee individual privacy.
- Develop the system for future needs, such as vaccination records.