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Dwi widyawati
Sekolah Tinggi Ilmu Kesehatan Sapta Bakti
Public Health

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Accuracy of Writing Diagnosis and Accuracy of Gastroenteritis Codes Dwi widyawati; Nofri Heltiani; Andriansyah -
Jurnal Manajemen Informasi Kesehatan (Health Information Management) Vol. 9 No. 1 (2024): Health Information and Management
Publisher : Sekolah Tinggi Ilmu Kesehatan Sapta Bakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51851/jmis.v9i1.506

Abstract

Accurate diagnosis coding according to ICD-10 to assign accurate diagnosis codes for inpatients also requires additional information such as laboratory results to be taken into account. The results of initial observations made on 10 medical resume sheets for gastroenteritis cases showed that 3 (30%) had accurate diagnosis codes and 7 (70%) had inaccurate diagnosis codes. This can affect the quality of data, information and reports as well as the accuracy of rates for general patients and INA-CBG'S rates which are used as a payment method for BPJS patients so that it can have an impact on reducing the quality of hospital services. This research aims to determine the accuracy of writing diagnoses and the accuracy of gastroenteritis codes for inpatients at Rafflesia Hospital in 2023. The type of research used is descriptive research with a cross sectional method. The population in this study was 214 medical record files for inpatient gastroenteritis cases in 2022 with a sample of 140 files using a simple random sampling technique. The research data used is secondary data which was processed univariately. The results of this study were that from 140 inpatient gastroenteritis medical record files, 100(100%) had the results of supporting examinations but they did not match the diagnosis written on the patient's medical resume because in writing the diagnosis it was not stated whether the gastroenteritis was infected or non-infected, 29(21% ) writing the diagnosis correctly, 43(31%) wrote the diagnosis incorrectly because they used Indonesian and 68(48%) wrote the diagnosis incorrectly because they used non-standard abbreviations and 69(49%) had an accurate diagnosis code and 71(51%) Inaccurate diagnosis code because there is no 4th character.
Accuracy of Dengue Hemorrhagic Fever (DHF) Diagnosis Codes in Terms of Completeness and Accuracy of Medical Information Dwi Widyawati; Nofri Heltiani; Nova Oktavia
Jurnal Manajemen Informasi Kesehatan (Health Information Management) Vol. 9 No. 2 (2024): Health Information and Management
Publisher : Sekolah Tinggi Ilmu Kesehatan Sapta Bakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51851/jmis.v9i2.599

Abstract

The completeness of the physical examination and the accuracy of laboratory results are crucial in supporting the accuracy of diagnostic codes. A preliminary survey of 10 Dengue Hemorrhagic Fever (DHF) medical records revealed that 4 (40%) were accurate and 6 (60%) were inaccurate. This was due to incomplete and inaccurate physical examination and laboratory results, which affected diagnosis and coding. This resulted in decreased data, information, and reporting quality, as well as the accuracy of INA-CBG rates, which could negatively impact the quality of hospital services. This study aimed to determine the accuracy of DHF diagnostic codes in terms of the completeness of medical information. This study used an observational, quantitative descriptive design, with 86 DHF medical records as the population and sample. The data used were secondary data obtained through observation using a checklist. The data were then processed and analyzed univariately using a frequency distribution. The results of this study are that from 86 DHF medical record files, 33 (38%) were found to have complete physical examinations, 12 (10%) were accurate laboratory test results, 8 (9%) were accurate diagnoses, and 8 (9%) were accurate diagnosis codes. It is expected that medical record officers, especially in the assembling section, will conduct medical record audits through qualitative analysis and improve coder skills through coding classification training.
Co-Authors Andriansyah - Nofri Heltiani Nofri Heltiani Nova Oktavia