Journal of Preventive Medicine and Public Health

Original Article

Reliability and Validity of the Appropriateness Evaluation Protocol for Public Hospitals in Korea: Clara Lee, Stella Jung-Hyun Kim, Changwoo Lee, Euichul Shin; J Prev Med Public Health. 2019;52(5):316-322. Published online September 12, 2019; DOI: https://doi.org/10.3961/jpmph.19.125

5,103 View
184 Download
4 Crossref

Objectives
This study was conducted to assess the applicability of the Appropriateness Evaluation Protocol (AEP) for public hospitals in Korea.
Methods
In May 2016, 1500 admission claims were collected from Korean public district hospitals using stratified random sampling. Of these claims, 560 admissions to 37 hospitals were retrieved for analysis. Medical records administrators determined the appropriateness of admission using the criteria detailed in the AEP, and a physician separately assessed the appropriateness of admission based on her clinical judgment. To examine the applicability of the AEP, the concordance of the decisions made between a pair of AEP reviewers and between an AEP reviewer and a physician reviewer was compared.
Results
The results showed an almost perfect inter-rater agreement between the AEP reviewers and a moderate agreement between the AEP reviewers and the physician. The sensitivity and specificity of the AEP were calculated as 0.86 and 0.56, respectively.
Conclusions
Our findings suggest that the AEP could potentially be applied to Korean public hospitals as a reliable and valid instrument for assessing the appropriateness of admissions.

Summary

Korean summary
이 연구는 우리나라 공공병원을 대상으로 Appropriateness Evaluation Protocol(AEP) 도구를 적용가능성을 검토하기 위해 실시되었다. 우리나라의 지역공공병원 입원자료(2016년 5월 기준)를 층화무작위추출을 통해 1,500건을 추출하였으며, 이중 37개 병원의 560건에 대해 입원적정성을 분석하였다. 의무기록사 2인은 AEP 도구를 이용하여 입원적정성을 각각 검토하였고, 의사 1인은 전문가적 판단을 기준으로 검토하였다. AEP 도구의 적용가능성을 판단하기 위해 의무기록사간 그리고 의무기록사-의사간 일치율을 산출하였다. 의무기록사간 일치율은 거의 완벽한 수준으로 나타났고, 의무기록사-의사간은 중등도의 일치율을 보였다. 민감도, 특이도는 각각 0.86 그리고 0.56이었다. 이러한 결과는 AEP 도구가 우리나라 공공병원의 입원적정성을 평가하기 위한 일관적이고 정확한 도구임을 제시한다.

Citations

Citations to this article as recorded by

Inappropriate hospital admission as a risk factor for the subsequent development of adverse events: a cross-sectional study
Diego San Jose-Saras, Jorge Vicente-Guijarro, Paulo Sousa, Paloma Moreno-Nunez, Jesús María Aranaz-Andres, Cristina Díaz-Agero Pérez, Miguel Ignacio Cuchi Alfaro, Juan Manuel Ramos López, Mercedes García Haro, Abelardo Claudio Fernández Chávez, Cornelia B
BMC Medicine.2023;[Epub] CrossRef
Inappropriate Hospital Admission According to Patient Intrinsic Risk Factors: an Epidemiological Approach
D. San Jose-Saras, J. Vicente-Guijarro, P. Sousa, P. Moreno-Nunez, M. Espejo-Mambié, J. M. Aranaz-Andres
Journal of General Internal Medicine.2023; 38(7): 1655. CrossRef
Strategies to improve the flow of admissions and hospital stays: a Delphi study of an adaptation of the Appropriateness Evaluation Protocol (AEP)
A. Morillo-Rodríguez, S. Alonso-Fernández, J.M. Mòdol Deltell, B. Soldevila Madorell, Ll. Benito-Aracil, D. Parés
Revista Clínica Española (English Edition).2023; 223(5): 270. CrossRef
Estrategias para mejorar el flujo de ingresos y estancias hospitalarias: adaptación del cuestionario Appropriateness Evaluation Protocol (AEP): estudio Delphi
A. Morillo-Rodríguez, S. Alonso-Fernández, J.M. Mòdol Deltell, B. Soldevila Madorell, Ll. Benito-Aracil, D. Parés
Revista Clínica Española.2023; 223(5): 270. CrossRef

Validation Studies

Construction and Validation of Hospital-Based Cancer Registry Using Various Health Records to Detect Patients with Newly Diagnosed Cancer: Experience at Asan Medical Center.: Hwa Jung Kim, Jin Hee Cho, Yongman Lyu, Sun Hye Lee, Kyeong Ha Hwang, Moo Song Lee; J Prev Med Public Health. 2010;43(3):257-264.; DOI: https://doi.org/10.3961/jpmph.2010.43.3.257

3,785 View
61 Download
3 Crossref

Abstract PDF

OBJECTIVES
An accurate estimation of cancer patients is the basis of epidemiological studies and health services. However in Korea, cancer patients visiting out-patient clinics are usually ruled out of such studies and so these studies are suspected of underestimating the cancer patient population. The purpose of this study is to construct a more complete, hospital-based cancer patient registry using multiple sources of medical information. METHODS: We constructed a cancer patient detection algorithm using records from various sources that were obtained from both the in-patients and out-patients seen at Asan Medical Center (AMC) for any reason. The medical data from the potentially incident cancer patients was reviewed four months after first being detected by the algorithm to determine whether these patients actually did or did not have cancer. RESULTS: Besides the traditional practice of reviewing the charts of in-patients upon their discharge, five more sources of information were added for this algorithm, i.e., pathology reports, the national severe disease registry, the reason for treatment, prescriptions of chemotherapeutic agents and radiation therapy reports. The constructed algorithm was observed to have a PPV of 87.04%. Compared to the results of traditional practice, 36.8% of registry failures were avoided using the AMC algorithm. CONCLUSIONS: To minimize loss in the cancer registry, various data sources should be utilized, and the AMC algorithm can be a successful model for this. Further research will be required in order to apply novel and innovative technology to the electronic medical records system in order to generate new signals from data that has not been previously used.

Summary

Citations

Citations to this article as recorded by

The role of Hospital-Based Cancer Registries (HBCRs) as information systems in the delivery of evidence-based integrated cancer care: a scoping review
Sheela Tripathee, Sara Jane MacLennan, Amudha Poobalan, Muhammad Imran Omar, Aravinda Meera Guntupalli
Health Systems.2023; : 1. CrossRef
The clinical behavior and survival of patients with hepatocellular carcinoma and a family history of the disease
Jihyun An, Seheon Chang, Ha Il Kim, Gi‐Won Song, Ju Hyun Shim
Cancer Medicine.2019; 8(15): 6624. CrossRef
Chronic hepatitis B infection and non-hepatocellular cancers: A hospital registry-based, case-control study
Jihyun An, Jong Woo Kim, Ju Hyun Shim, Seungbong Han, Chang Sik Yu, Jaewon Choe, Danbi Lee, Kang Mo Kim, Young-Suk Lim, Young-Hwa Chung, Yung Sang Lee, Dong Jin Suh, Jin Hyoung Kim, Han Chu Lee, Yury E Khudyakov
PLOS ONE.2018; 13(3): e0193232. CrossRef

English Abstract

Prognostic Impact of Charlson Comorbidity Index Obtained from Medical Records and Claims Data on 1-year Mortality and Length of Stay in Gastric Cancer Patients.: Min Ho Kyung, Seok Jun Yoon, Hyeong Sik Ahn, Se min Hwang, Hyun Ju Seo, Kyoung Hoon Kim, Hyeung Keun Park; J Prev Med Public Health. 2009;42(2):117-122.; DOI: https://doi.org/10.3961/jpmph.2009.42.2.117

5,548 View
112 Download
12 Crossref

Abstract PDF

OBJECTIVES
We tried to evaluate the agreement of the Charlson comorbidity index values (CCI) obtained from different sources (medical records and National Health Insurance claims data) for gastric cancer patients. We also attempted to assess the prognostic value of these data for predicting 1-year mortality and length of the hospital stay (length of stay). METHODS: Medical records of 284 gastric cancer patients were reviewed, and their National Health Insurance claims data and death certificates were also investigated. To evaluate agreement, the kappa coefficient was tested. Multiple logistic regression analysis and multiple linear regression analysis were performed to evaluate and compare the prognostic power for predicting 1 year mortality and length of stay. RESULTS: The CCI values for each comorbid condition obtained from 2 different data sources appeared to poorly agree (kappa: 0.00-0.59). It was appeared that the CCI values based on both sources were not valid prognostic indicators of 1-year mortality. Only medical record-based CCI was a valid prognostic indicator of length of stay, even after adjustment of covariables (beta = 0.112, 95% CI = [0.017-1.267]). CONCLUSIONS: There was a discrepancy between the data sources with regard to the value of CCI both for the prognostic power and its direction. Therefore, assuming that medical records are the gold standard for the source for CCI measurement, claims data is not an appropriate source for determining the CCI, at least for gastric cancer.

Summary

Citations

Citations to this article as recorded by

Factors Associated with Hospital Length of Stay among Women’s Cancer Patients: Based on the In-depth Injury Patient Surveillance System Data
Yoonjung Kang, Hyewon Lee
Journal of Health Informatics and Statistics.2022; 47(2): 148. CrossRef
The impact of global budgeting in Taiwan on inpatients with unexplained fever
Keh-Sen Liu, Tsung-Fu Yu, Hsing-Ju Wu, Chun-Yi Lin
Medicine.2019; 98(37): e17131. CrossRef
What happened to health service utilization, health care expenditures, and quality of care in patients with acute pancreatitis after implementation of global budgeting in Taiwan?
Ya-Lin Ko, Jyun-Wei Wang, Hui-Mei Hsu, Chia-Hung Kao, Chun-Yi Lin
Medicine.2018; 97(41): e12620. CrossRef
The impact of global budgeting on health service utilization, health care expenditures, and quality of care among patients with pneumonia in Taiwan
C.-Y. Lin, T. Ma, C.-C. Lin, C.-H. Kao
European Journal of Clinical Microbiology & Infectious Diseases.2016; 35(2): 219. CrossRef
Comparison of Hospital Standardized Mortality Ratio Using National Hospital Discharge Injury Data
Jong-Ho Park, Yoo-Mi Kim, Sung-Soo Kim, Won-Joong Kim, Sung-Hong Kang
Journal of the Korea Academia-Industrial cooperation Society.2012; 13(4): 1739. CrossRef
Predictive Ability of Charlson Comorbidity Index on Outcomes From Lung Cancer
Apar Kishor Ganti, Emily Siedlik, Alissa S. Marr, Fausto R. Loberiza, Anne Kessinger
American Journal of Clinical Oncology.2011; 34(6): 593. CrossRef
Comparative Study on Three Algorithms of the ICD-10 Charlson Comorbidity Index with Myocardial Infarction Patients
Kyoung Hoon Kim
Journal of Preventive Medicine and Public Health.2010; 43(1): 42. CrossRef
The Impact of Medicaid Expansion to include population with low income on the preventable hospitalizations
Hyun-Chul Shin, Se-Ra Kim
Korean Journal of Health Policy and Administration.2010; 20(1): 87. CrossRef
Charlson Comorbidity Index as a Predictor of Long-Term Survival after Surgery for Breast Cancer: A Nationwide Retrospective Cohort Study in South Korea
Hye Kyung Woo, Jong Hyock Park, Han Sung Kang, So Young Kim, Sang Il Lee, Hyung Ho Nam
Journal of Breast Cancer.2010; 13(4): 409. CrossRef
A comparison of the Charlson comorbidity index derived from medical records and claims data from patients undergoing lung cancer surgery in Korea: a population-based investigation
Hyun-Ju Seo, Seok-Jun Yoon, Sang-Il Lee, Kun Sei Lee, Young Ho Yun, Eun-Jung Kim, In-Hwan Oh
BMC Health Services Research.2010;[Epub] CrossRef
Health Outcome Prediction Using the Charlson Comorbidity Index In Lung Cancer Patients
Se-Won Kim, Seok-Jun Yoon, Min-Ho Kyung, Young-Ho Yun, Young-Ae Kim, Eun-Jung Kim
Korean Journal of Health Policy and Administration.2009; 19(4): 18. CrossRef
Factors Affecting Health of the Rural Residents
Dong-Koog Son, Kyu-Sik Lee, Jong-Ku Park, Sang-Baek Koh, Ki-Nam Jin, Eun-Woo Nam, Hae-Jong Lee
Korean Journal of Health Policy and Administration.2009; 19(4): 1. CrossRef

First
Prev
Page of 1
Next
Last

Search