Analisis Beban Kerja dan Kebutuhan Petugas Unit Rekam Medis di RSUP Dr. Sitanala

Hospitals, as healthcare service providers, are required to improve the quality and efficiency of their services, one of which is through the implementation of Electronic Medical Records (EMR). This transformation impacts the workload of staff, particularly in the Medical Records Unit. This study aims to analyze the workload and staffing needs of the Medical Records Unit at Dr. Sitanala Central General Hospital using a descriptive quantitative approach with the Health Workload Analysis (ABK-Kes) method. Data were collected through observation and interviews with six staff members using observation sheets, interview guidelines, and informed consent forms. The results show that the Available Working Time (AWT) is 72,000 minutes per year, exceeding the national standard. There are 11 core tasks and 3 supporting tasks, with the highest Standard Workload (SWL) found in the recording and filing activity (72,000), and the Standard Supporting Task (SST) value is 1.2. Based on achievements, SWL, and SST, a total of four staff members are needed to balance the workload. Currently, only one staff member remains due to staff rotation, resulting in a shortage of three personnel. Therefore, Dr. Sitanala Hospital needs to recruit three additional medical record officers with a minimum qualification of a D3 in Medical Records to maintain optimal service and manageable workloads.

Authors

Institutions

Publication Details

Journal
Jurnal Ilmu Kedokteran dan Kesehatan Indonesia
Published
2025-06-24
DOI
https://doi.org/10.55606/jikki.v5i2.6865
Primary Topic
Management and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analisis Beban Kerja dan Kebutuhan Petugas Unit Rekam Medis di RSUP Dr. Sitanala

Nora Ramadan, Deasy Rosmala Dewi, Puteri Fannya, Daniel Happy Putra
Jurnal Ilmu Kedokteran dan Kesehatan Indonesia
Management and Optimization Techniques
article

Analisis Beban Kerja dan Kebutuhan Petugas Unit Rekam Medis di RSUP Dr. Sitanala

Nora Ramadan, Deasy Rosmala Dewi, Puteri Fannya, Daniel Happy Putra
article en

Abstract

Hospitals, as healthcare service providers, are required to improve the quality and efficiency of their services, one of which is through the implementation of Electronic Medical Records (EMR). This transformation impacts the workload of staff, particularly in the Medical Records Unit. This study aims to analyze the workload and staffing needs of the Medical Records Unit at Dr. Sitanala Central General Hospital using a descriptive quantitative approach with the Health Workload Analysis (ABK-Kes) method. Data were collected through observation and interviews with six staff members using observation sheets, interview guidelines, and informed consent forms. The results show that the Available Working Time (AWT) is 72,000 minutes per year, exceeding the national standard. There are 11 core tasks and 3 supporting tasks, with the highest Standard Workload (SWL) found in the recording and filing activity (72,000), and the Standard Supporting Task (SST) value is 1.2. Based on achievements, SWL, and SST, a total of four staff members are needed to balance the workload. Currently, only one staff member remains due to staff rotation, resulting in a shortage of three personnel. Therefore, Dr. Sitanala Hospital needs to recruit three additional medical record officers with a minimum qualification of a D3 in Medical Records to maintain optimal service and manageable workloads.

Jurnal Ilmu Kedokteran dan Kesehatan IndonesiaVol. 5(2)
Universitas Esa Unggul (ID)
Openalex Percentile: Top 78%
Management and Optimization Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.