Strategy to Improve Electronic Medical Certification of Cause of Death at Rumah Sakit Persahabatan, Jakarta, Indonesia
Proper death certification has broad medical and public health benefits. Therefore, death certificates should be completed accurately according to the medical certification of cause of death (MCCD) scheme. To improve the data quality of MCCD, Rumah Sakit Persahabatan (RSP) has implemented an electronic form (e-SMPK) since 2023. Although equipped with a user manual and coordination support system, incomplete and inaccurate e-SMPKs are still found. This study aims to identify interventions that can improve the quality (completeness and accuracy) of e-SMPK in RSP using one action research cycle consisting of 4 stages, i.e., diagnosing, planning, taking, and evaluating action. Qualitative data was collected through focused group discussions and field observations. Quantitative data was collected by comparing the completeness and accuracy of e-SMPKs before and after the intervention agreed upon with the participants. Triangulation of the data was carried out to maintain the credibility of the research. This study found that obstacles to e-SMPK consist of system and regulatory factors, skills, practical tools, and processes. Interventions are implemented by adjusting regulations, providing guidance and training, revising electronic forms, improving coordination, and facilitating consultation and verification to overcome obstacles. An increase in the completeness and accuracy of filling in the e-SMPK elements was obtained, most of which were statistically significant.
Authors
- Putri Dianita Ika Meilia (ORCID: https://orcid.org/0000-0003-3699-664X)
- Hanevi Djasri
- Guardian Yoki Sanjaya (ORCID: https://orcid.org/0000-0002-3444-4617)
Institutions
- Universitas Gadjah Mada (ID)
- Ministry of Research, Technology and Higher Education (ID)
Publication Details
- Journal
- JMMR (Jurnal Medicoeticolegal dan Manajemen Rumah Sakit)
- Published
- 2024-08-15
- DOI
- https://doi.org/10.18196/jmmr.v13i2.420
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00