Chronic Obstructive Pulmonary Disease is inflammation of the lungs that develops over a long period of time. This study determine the level of accuracy of the diagnosis code for Chronic Obstructive Pulmonary Disease. This research is a descriptive study, with a retrospective approach. Saturated samples were 100 cases of Chronic Obstructive Pulmonary Disease using nonprobability sampling technique. The research instruments were ICD-10, checklist, observation guide, interview guide, calculator and voice recorder. Data processing by editing, coding, data entry, tabulating, and presenting data. The analysis was carried out descriptively. The percentage of diagnosis code accuracy of Chronic Obstructive Pulmonary Disease is 60% and code inaccuracy is 40%. The code inaccuracy is 40 medical records of 100 documents. Factors that affect the accuracy of the diagnosis code are medical personnel (doctors), medical record officers as coders, and other health workers.
The author suggests that more emphasis should be placed on doctors to clarify the writing of a diagnosis and use medical terminology for disease diagnosis in order to make it easier for coding officers to provide disease codes and affect the accuracy of patient disease codes, the officers should be more careful and careful during the disease coding process. So that there are no more medical record files that are not coded so that the resulting code is accurate, and coding officers should be more careful during the process of giving the diagnosis code so that there are no more inaccurate medical record files due to incorrect coding.
World Health Organization, “International Satistical Classification of Diseases and Related Health Problems Tenth Revision volume 1, 1 dan 3”, Geneva, 2016.
Centers for Medicare and Medicaid Services (CMS) and the National Center for Health Statistics (NCHS). ICD-10. 2016.
Bowman, E, & Abdelhak, Mervat. (2001). Coding, classification, and reimbursement systems. Health information: management of a strategic resource. 2nd edition. Philadelphia: WB Saunders Company, 229-258.
Nurmala R.I. 2017. Analisis Keakuratan Kode Diagnosis PPOK Eksaserbasi Akut Berdasarkan ICD-10 Pada Dokumen Rekam Medis Pasien Rawat Inap di RSUD Sragen Triwulan II Tahun 2011.
Psychiatric Association. Diagnostic and Statistical Pulmonarry Obstructive Cronic. 5th edition. Washington: American Psychiatric Association; 2000
Robert S., Hankes M. A., dan Jacobs E. B. 2001. Health Information of A Strategic Resource 2nd Edition. Philadelphia: Sunders Company
Iezzoni LI, Foley SM, Daley J, et al. Comorbidities, complications, and coding bias: does the number of diagnosis codes matter in predicting in-hospital mortality? JAMA 1992;267:2197–203.
Jonshon. “The Accuracy of Medicare's Hospital Claims Data: Progress Has Been Made, but Problems Remain.” American Journal of Public Health. 2016;82:243–8
Jerremi, Appel GL. “InacBGS Hospital Case Records: Implications for Medicare Casemix Accuracy.” Inquiry. 2015;21:128–34
Christanto, dkk. 2014. Kapita Selekta Kedokteran Jilid II Edisi IV. Jakarta: Medika Aesculapius
Departemen Kesehatan 2006. Pedoman Penyelenggaraan dan Prosedur Rekam Medis Rumah Sakit di Indonesia Revisi II. Dirjen Yanmed Departemen Kesehatan RI. Jakarta
Keputusan Menteri Kesehatan Republik Indonesia No. 1022/MENKES/SK/XI/2008 tentang Pedoman Pengendalian penyakit Paru Obstruktif Kronik
Michenzi EM. “Data Quality: An Illustration of Its Potential Impact upon Diagnosis-Related Group's Case Mix Index and Reimbursement.” Medical Care. 2017;21:1001–1
Bros, Fardon D. “Quality of Data Regarding Diagnoses. A Multicenter Study.” Journal of Bone Joint Surgery America. 2015;79:1481–9