| Summary: | Background: January 1st, 2014 implementation of the SJSN be phased using the INA CBG's software systems in the determination of the cost of health care and process claims. From the 19 diagnosis codes on inpatients medical record RS Mata \"Dr. Yap\" Yogyakarta is known as much accuracy as much as 31,58% and 68,42% inaccuracy. Inaccuracy of the diagnosis codes affecting the cost of claims acquired hospitals. If inaccuracy of diagnosis codes is high then the cost of claims received by the hospital is not in accordance with the cost of service rendered to the patient so the hospital will lose money. The researchers wanted to know coding diagnoses in medical records files and software INA CBG's inpatients of the SJSN implementation in RS Mata \"Dr. Yap\" Yogyakarta.
Goals: To determine the diagnosis coding implementation in the medical record file and software INA CBG's. Knowing the percentage of suitability diagnosis codes in the inpatient medical record file and software INA CBG's. Knowing the percentage of accuracy of diagnosis codes in the inpatient medical record file and software INA CBG's. Knowing the causes of coding inaccuracy of diagnosis in the medical record file and software INA CBG's.
Methods: The research used in this study is a descriptive study with a qualitative approach. The design of the study using cross-sectional design. Subjects were coding clerk, the object is medical record file and software INA CBG's SJSN inpatients in January. Data retrieval technique using simple random sampling technique. Results: Implementation of coding diagnoses in the medical record file and software INA CBG's done by a coder. Coder also duty on assembling and completeness analysis. Encoding patient diagnosis based on ICD-10. The process of finding code patient diagnoses using smart book. The diagnosis code written entry in discharge record. Encoded in the software look INA CBG�s diagnosis in medical resumes in terms claim bill then entered into the software. Percentage suitability diagnosis code as much as 42,39% and 57,61% mismatch. Percentage accuracy of diagnosis codes on medical record file A criterion is 53,13%
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