Three reasons why COVID-19 data in Indonesia is unreliable and how to fix it
More than a year after the start of the pandemic, Indonesia has Southeast Asia’s highest number of COVID-19 cases and death rate and is still struggling with disorganized COVID-19 data management.
The latest media report shows that COVID-19 cases in Indonesia are more common than official figures. The report says 15% of Indonesians had previously been infected with the coronavirus, far more than the estimated 0.4% shown in government data.
At the start of the pandemic, Indonesian President Joko “Jokowi” Widodo admitted his administration had decided not to reveal all the data to avoid causing panic. Its coordinating minister for maritime affairs and investment, Luhut Binsar Pandjaitan, also recognized the inadequacy of health data between central government and local governments.
The teachings of Yogyakarta
In October and November 2020, our team investigated how healthcare facilities record and organize reporting of COVID-19 data in Yogyakarta. It is a province of about 4 million inhabitants located 500 kilometers east of the capital Jakarta.
We chose Yogyakarta because it is a small province with four districts and a municipality whose COVID-19 data management involves various health information systems, similar to other provinces in Indonesia. By analyzing the functioning of the data collection system in Yogyakarta, we hope to be able to apply the results in other provinces of Indonesia.
We spoke to officials of various institutions in Yogyakarta, such as the health offices and the communication and information office, at the provincial and district levels. We also gathered the views of healthcare facilities, as well as community and app developers.
Based on these interviews, our research captures three issues contributing to the complexity of COVID-19 data management in the province.
1. Fragmented application systems
In DI Yogyakarta, we found several systems used for COVID-19 related data management at district, provincial and national levels.
This is the result of the decentralization policy which allows each region to create local mechanisms for monitoring cases in the field.
This decentralized mechanism is intended to speed up responses from local authorities. Decentralization allows local government to act quickly in relation to the expectations of central government policies.
However, this makes the flow of data and information from local government to central government cumbersome, as the data is not fully integrated.
2. Date entry duplication
The lack of an integrated system covering both local and national levels has prevented regions from provide only one valid data set.
We found nine examples of COVID-19 data collection and analysis applications between district, provincial and central authorities and health facilities. These cover case detection, contact tracing, laboratory confirmation, self-testing, logistics, and data collection on healthcare resources.
In general, the health establishments of DI Yogyakarta have an internal information system in each local hospital or primary health center. The main goal is to collect patient care data for all cases.
During the pandemic, the district health office and local government created a local COVID-19 app. The provincial COVID-19 working group has also developed an application to integrate data between districts called COVID-19 Monitoring Systems (CMS).
Nationally, the data collection system focuses on two main tasks: collecting confirmed cases of COVID-19 and providing updated data on human resources, logistics and bed availability.
Unfortunately, at local and national level, these different applications are not integrated. This means that healthcare staff at the healthcare facility level have to enter the same data multiple times in different applications, which increases the workload and the likelihood of making mistakes.
3. Lack of human resources
Carrying out all COVID-19 control activities places a heavy burden on health facilities. Health workers should provide services to patients, trace contacts and monitor cases. They also suffer from a lack of human resources when it comes to entering data into different applications.
It is common for health workers to enter COVID-19 data after hours of service, resulting in incomplete data and delayed data submission. This results in discrepancies between system data and manual reports.
For example, labs provide data, such as COVID-19 test results, to healthcare facilities in different formats and methods, such as PDFs, Excel files, email, and Google Drive.
Health workers then need to combine this data into a single format at the district health office before sending it to the provincial and central governments.
Additionally, due to accessibility issues with apps and the pressure to report data quickly, we found that health workers and managers were using informal communication channels such as WhatsApp to deliver updates on the number of tests, new cases and deaths each day.
This further increases the likelihood of making mistakes. It also raises data privacy concerns for patients’ medical information.
So what is the solution?
The Indonesian government has released a presidential decree integrate multiple data sources to improve policy and decision-making.
But the regulations are still poorly applied.
In the face of a pandemic, the government should put in place a clear and concise system to regulate the flow of data from the local level to the central level. The government should also revamp the large number of information systems and data management applications to make them more efficient.
All local government data entry must comply with national COVID-19 data and metadata standards. This means that the data from the regions can be sent directly from the local application currently in use to the central application via data integration. It also means that the system must facilitate communication between the various existing systems and services.
This allows central and regional agencies to easily access and share data.
We recommend that the Indonesian government use the enterprise architecture principles of The open group architecture framework to implement a conceptual plan that defines the structure and functioning of organizations to align with different measures in response to COVID-19.
The plan should focus on challenges such as the immunization process and reducing restrictions on social activities.
Based on these considerations and several references, we adopt the OpenHIE framework, a free, adaptable and open framework for improving health information systems.
OpenHIE is suitable for a bottom-up community approach to building a health information system. It is also effective in helping alleviate problems associated with COVID-19 data collection.