Firnalia Ellen Novana, Eka Wilda Faida, Alfina Aisatus Saadah, Faiqatul Hikmah

ANALISIS TINGKAT PENGETAHUAN DAN MOTIVASI PETUGAS REKAM MEDIS DALAM IMPLEMENTASI REKAM MEDIS ELEKTRONIK

Introduction

Analisis tingkat pengetahuan dan motivasi petugas rekam medis dalam implementasi rekam medis elektronik. Analisis pengetahuan dan motivasi petugas rekam medis dalam implementasi Rekam Medis Elektronik (RME). Temukan hasil tingkat pengetahuan & motivasi serta rekomendasi peningkatannya.

Abstract

Dalam implementasi RME seluruh petugas rekam medis di unit pendaftaran sudah mampu mengoperasionalkan sistem informasi tersebut, akan tetapi dalam pelaksanaanya masih belum sepenuhnya berjalan secara optimal. Hal ini disebabkan oleh pengisian identitas dan data sosial pasien masih banyak yang kosong. Ketidaklengkapan data registrasi pasien tersebut ditinjau dari aspek pengetahuan. Pengetahuan petugas bisa ditingkatkan menjadi lebih baik lagi dengan adanya dukungan atau motivasi yang tinggi dari diri sendiri maupun rekan kerja. Tujuan penelitian ini yaitu untuk menganalisis tingkat pengetahuan dan motivasi petugas rekam medis dalam implementasi RME. Jenis penelitian ini menggunakan deskriptif kuantitatif. Pengambilan sampel menggunakan teknik non probability sampling dengan jumlah sampel 6 petugas rekam medis. Metode pengumpulan data yang digunakan yaitu kuesioner untuk memperoleh jawaban dari petugas rekam medis dan dianalisis menggunakan tabel distribusi frekuensi dan narasi. Hasil penelitian didapatkan bahwa tingkat pengetahuan dengan hasil 100 % sudah berkategori baik maka perlu dipertahankan agar pengetahuan yang dimiliki tidak menurun sedangkan tingkat motivasi dengan hasil 66,7% berkategori sedang maka perlu Menetapkan SOP atau pedoman yang jelas tentang implementasi RME agar petugas termotivasi menjalankan tugasnya sesuai dengan prosedur.

Review

This study, titled "ANALYSIS OF THE LEVEL OF KNOWLEDGE AND MOTIVATION OF MEDICAL RECORD OFFICERS IN THE IMPLEMENTATION OF ELECTRONIC MEDICAL RECORDS," addresses a pertinent issue within health information management: the suboptimal implementation of Electronic Medical Records (EMR) despite officers' reported ability to operate the system. The identified problem of incomplete patient registration data (identity and social information) is a common challenge in EMR adoption globally, impacting data quality, patient care, and administrative efficiency. By focusing on the human factors of knowledge and motivation among medical record officers, the research aims to uncover underlying causes for these operational deficiencies, making it relevant for healthcare institutions striving for effective digital transformation. Utilizing a descriptive quantitative approach, the study aimed to analyze the levels of knowledge and motivation among medical record officers regarding EMR implementation. Data were collected via questionnaires from a small sample of six officers using non-probability sampling, and subsequently analyzed using frequency distribution tables and narrative descriptions. The findings indicate a robust level of knowledge, with 100% of officers categorized as having "good" knowledge, suggesting this area is well-established and needs maintenance. However, motivation emerged as a potential barrier, with 66.7% of officers categorized as having "moderate" motivation. Consequently, the research recommends establishing clear Standard Operating Procedures (SOPs) or guidelines to enhance motivation and ensure tasks are performed in accordance with established procedures. A key strength of this research lies in its practical focus, directly addressing a tangible operational issue within EMR implementation and offering a concrete recommendation for improvement. The distinction between high knowledge and moderate motivation is an insightful finding, suggesting that merely knowing *how* to use a system does not automatically translate to optimal performance without adequate motivational structures. However, the study's primary limitation is its extremely small sample size (n=6), which severely restricts the generalizability and statistical robustness of the findings. While the descriptive approach is suitable for exploring initial trends, such a small sample makes it challenging to draw definitive conclusions applicable beyond the specific context studied. Future research would significantly benefit from expanding the sample size to allow for more generalizable quantitative analysis and potentially incorporating qualitative methods (e.g., in-depth interviews) to explore the nuanced reasons behind moderate motivation and incomplete data, particularly when knowledge levels are already high. This would provide a deeper understanding of the complex interplay of human, procedural, and systemic factors influencing optimal EMR implementation.

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