Knowledge, Attitude and Perception on Casemix System Among the Hospital Staff in Malaysia and Indonesia

Objective: The aim of this study is to assess the Knowledge, Attitude, and Perception (KAP) of hospital staff regarding the Casemix System in Developing countries. Methods: A cross-sectional study was carried among the hospital staffs in Indonesia and Malaysia. The study hospitals and respondents were selected via random and purposive sampling, respectively. Data was collected via self-administered questionnaires. Results: Total 350 hospital staffs participated, out of this 58.6% of participants were from Indonesia. Most of the respondents (58.0%) had a moderate level of knowledge score, medium level of perception score (84.9%) and negative attitude (90.0%) on Casemix. The study found that years of working experience, type of occupation, hospital type, country, and those with training in Casemix were significantly related to knowledge score. No independent variable except for country was related to perception score. It was also found that majority (66.7%) of the participating hospitals (N=36) completely captured the demographic data in their HIS, 47.2% completely implementing the coding module as per Casemix requirement and 27.8% of the hospitals recorded the Activity Daily Living (ADL) score in their system. Conclusion: Among the participants, only 2.3% demonstrated a high level of knowledge about Casemix. When it comes to attitudes, majority of respondents expressed a negative view towards Casemix. Regarding perceptions, only 11.4% of respondents had a high perception of Casemix, while the majority, 84.9%, had a medium perception.

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Publication Details

Journal
Journal of Health Policy & Outcomes Research
Published
2024-10-28
DOI
https://doi.org/10.7365/jhpor.2024.2.2
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.53
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article

Knowledge, Attitude and Perception on Casemix System Among the Hospital Staff in Malaysia and Indonesia

Syed Mohamed Aljunid, Nimetcan Mehmet Orhun, S. A. Aljunid
1 citations
Journal of Health Policy & Outcomes Research
Big Data and Business Intelligence
0.53
article

Knowledge, Attitude and Perception on Casemix System Among the Hospital Staff in Malaysia and Indonesia

Syed Mohamed Aljunid, Nimetcan Mehmet Orhun, S. A. Aljunid
article en
1 citations

Abstract

Objective: The aim of this study is to assess the Knowledge, Attitude, and Perception (KAP) of hospital staff regarding the Casemix System in Developing countries. Methods: A cross-sectional study was carried among the hospital staffs in Indonesia and Malaysia. The study hospitals and respondents were selected via random and purposive sampling, respectively. Data was collected via self-administered questionnaires. Results: Total 350 hospital staffs participated, out of this 58.6% of participants were from Indonesia. Most of the respondents (58.0%) had a moderate level of knowledge score, medium level of perception score (84.9%) and negative attitude (90.0%) on Casemix. The study found that years of working experience, type of occupation, hospital type, country, and those with training in Casemix were significantly related to knowledge score. No independent variable except for country was related to perception score. It was also found that majority (66.7%) of the participating hospitals (N=36) completely captured the demographic data in their HIS, 47.2% completely implementing the coding module as per Casemix requirement and 27.8% of the hospitals recorded the Activity Daily Living (ADL) score in their system. Conclusion: Among the participants, only 2.3% demonstrated a high level of knowledge about Casemix. When it comes to attitudes, majority of respondents expressed a negative view towards Casemix. Regarding perceptions, only 11.4% of respondents had a high perception of Casemix, while the majority, 84.9%, had a medium perception.

Journal of Health Policy & Outcomes ResearchVol. 2/2024
Ankara Yıldırım Beyazıt University (TR), IMU University (MY)
Openalex Percentile: Top 21%
Big Data and Business Intelligence
0.53
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