지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
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Objectives: This study aimed at revising the Korean Out-patient Groups for Korean Medicine (KOPG-OM, version 1.0) based on clinical similarity and resource use, by using the accumulated claims data, and evaluating the validity of the revised classification system.
Methods: A clinical specialist panel involving 19 specialists from 8 Korean medicine (KM) specialty areas reviewed the classification tree, diagnosis groups and procedure groups in terms of clinical similarity. Several models of outpatient grouping were formulated, with the validity of each tested based on the R2 coefficient of determination for the treatment costs of all visits. To add age splits, the variances of treatment costs by age groups were also analyzed. These statistical analyses were performed using KM claims data of National Health Insurance from 2010 to 2012.
Results: The classification tree designed via panel discussions was used to allocate outpatient cases to 26 diagnosis groups, with cases involving procedures such as acupuncture, moxibustion and cupping, then allocated to 9 procedure groups in each diagnosis group. The cases without procedures were categorized into the visit index ? medication group. This process resulted in 298 outpatient groups. The R2 values for treatment costs of all visits ranged from 0.38 to 0.69 depending on the providers" types.
Conclusions: The revised model of KOPG-KM has a higher validity for outpatient classification than the current system and can provide better management of the costs of outpatient care in KM.
Methods: A clinical specialist panel involving 19 specialists from 8 Korean medicine (KM) specialty areas reviewed the classification tree, diagnosis groups and procedure groups in terms of clinical similarity. Several models of outpatient grouping were formulated, with the validity of each tested based on the R2 coefficient of determination for the treatment costs of all visits. To add age splits, the variances of treatment costs by age groups were also analyzed. These statistical analyses were performed using KM claims data of National Health Insurance from 2010 to 2012.
Results: The classification tree designed via panel discussions was used to allocate outpatient cases to 26 diagnosis groups, with cases involving procedures such as acupuncture, moxibustion and cupping, then allocated to 9 procedure groups in each diagnosis group. The cases without procedures were categorized into the visit index ? medication group. This process resulted in 298 outpatient groups. The R2 values for treatment costs of all visits ranged from 0.38 to 0.69 depending on the providers" types.
Conclusions: The revised model of KOPG-KM has a higher validity for outpatient classification than the current system and can provide better management of the costs of outpatient care in KM.
목차
서론
연구대상 및 방법
연구결과
고찰
결론
참고문헌
참고문헌 (14)
참고문헌 신청
1. [기타자료] - Health Insurance Review & Assessment Service / 2011 / / KOPG-OM Classification : 1 ~ 2
2. [기타자료] - Health Insurance Review & Assessment Service / 2011 / KOPG Classification. Version 1.1 : 1 ~ 2
3. [기타자료] - Health Insurance Review & Assessment Service / 2006 / T/F Operating Result for Development of KOPG-OM and Computerized Classification Program : 14 ~ 46
4. [학술지(정기간행물)] - Averill RF / 1993 / Design of Prospective Payment Patient Classification System for Ambulatory Care / Healthcare Financing Review 15 (1) : 71 ~ 100
5. [기타자료] - Averill RF / 1999 / The Evolution of Casemix Measurement Using Diagnosis Related Groups / 3M Health Information System, Wallingford, Connecticut : 5 ~ 98
2. [기타자료] - Health Insurance Review & Assessment Service / 2011 / KOPG Classification. Version 1.1 : 1 ~ 2
3. [기타자료] - Health Insurance Review & Assessment Service / 2006 / T/F Operating Result for Development of KOPG-OM and Computerized Classification Program : 14 ~ 46
4. [학술지(정기간행물)] - Averill RF / 1993 / Design of Prospective Payment Patient Classification System for Ambulatory Care / Healthcare Financing Review 15 (1) : 71 ~ 100
5. [기타자료] - Averill RF / 1999 / The Evolution of Casemix Measurement Using Diagnosis Related Groups / 3M Health Information System, Wallingford, Connecticut : 5 ~ 98
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UCI(KEPA) : I410-ECN-0101-2015-510-002656164