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Longitudinal care continuity and avoidable hospitalization: the application of claims-based measures
BACKGROUND: Longitudinal continuity between a patient and his/her primary care physician is an important aspect in measuring continuity of care (COC). The majority of previous studies employed questionnaire surveys to patients to measure the continual relationship between patients and their physicia...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224272/ https://www.ncbi.nlm.nih.gov/pubmed/37244982 http://dx.doi.org/10.1186/s12913-023-09457-w |
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author | Cheng, Shou-Hsia Chen, Chi-Chen Lin, Yueh-Yun |
author_facet | Cheng, Shou-Hsia Chen, Chi-Chen Lin, Yueh-Yun |
author_sort | Cheng, Shou-Hsia |
collection | PubMed |
description | BACKGROUND: Longitudinal continuity between a patient and his/her primary care physician is an important aspect in measuring continuity of care (COC). The majority of previous studies employed questionnaire surveys to patients to measure the continual relationship between patients and their physicians. This study aimed to construct a provider duration continuity index (PDCI) by using longitudinal claims data and to examine its agreement with commonly used COC measures. Then, this study investigated the effects of the various types of COC measure on the likelihood of avoidable hospitalization while considering the level of comorbidity. METHODS: This study constructed a 4-year panel (from 2014 to 2017) of the nationwide health insurance claims data in Taiwan. In total, 328,044 randomly selected patients with 3 or more physician visits per year were analyzed. Two PDCIs were constructed to measure the duration of interaction between a patient and his/her physicians over time. The agreement between the PDCIs and three commonly used COC indicators, the Usual Provider of Care index, the Continuity of Care Index, and the Sequential Continuity Index, were examined. Generalized estimating equations were conducted to examine the association between COC and avoidable hospitalization by the level of comorbidity. RESULTS: The results showed that the correlations among the three commonly used COC indicators were high (γ = 0.787 ~ 0.958) and the correlation between the two longitudinal continuity measures was moderate (γ = 0.577 ~ 0.579), but the correlations between the commonly used COC indicators and the two PDCIs were low (γ = 0.001 ~ 0.257). All COC measures, both the PDCIs and the three commonly used COC indicators, showed independent protective effects on the likelihood of avoidable hospitalization in three comorbidity groups. CONCLUSION: The duration of interaction between patients and physicians is an independent domain in measuring COC and has a significant effect on health care outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-09457-w. |
format | Online Article Text |
id | pubmed-10224272 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102242722023-05-28 Longitudinal care continuity and avoidable hospitalization: the application of claims-based measures Cheng, Shou-Hsia Chen, Chi-Chen Lin, Yueh-Yun BMC Health Serv Res Research BACKGROUND: Longitudinal continuity between a patient and his/her primary care physician is an important aspect in measuring continuity of care (COC). The majority of previous studies employed questionnaire surveys to patients to measure the continual relationship between patients and their physicians. This study aimed to construct a provider duration continuity index (PDCI) by using longitudinal claims data and to examine its agreement with commonly used COC measures. Then, this study investigated the effects of the various types of COC measure on the likelihood of avoidable hospitalization while considering the level of comorbidity. METHODS: This study constructed a 4-year panel (from 2014 to 2017) of the nationwide health insurance claims data in Taiwan. In total, 328,044 randomly selected patients with 3 or more physician visits per year were analyzed. Two PDCIs were constructed to measure the duration of interaction between a patient and his/her physicians over time. The agreement between the PDCIs and three commonly used COC indicators, the Usual Provider of Care index, the Continuity of Care Index, and the Sequential Continuity Index, were examined. Generalized estimating equations were conducted to examine the association between COC and avoidable hospitalization by the level of comorbidity. RESULTS: The results showed that the correlations among the three commonly used COC indicators were high (γ = 0.787 ~ 0.958) and the correlation between the two longitudinal continuity measures was moderate (γ = 0.577 ~ 0.579), but the correlations between the commonly used COC indicators and the two PDCIs were low (γ = 0.001 ~ 0.257). All COC measures, both the PDCIs and the three commonly used COC indicators, showed independent protective effects on the likelihood of avoidable hospitalization in three comorbidity groups. CONCLUSION: The duration of interaction between patients and physicians is an independent domain in measuring COC and has a significant effect on health care outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-09457-w. BioMed Central 2023-05-27 /pmc/articles/PMC10224272/ /pubmed/37244982 http://dx.doi.org/10.1186/s12913-023-09457-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Cheng, Shou-Hsia Chen, Chi-Chen Lin, Yueh-Yun Longitudinal care continuity and avoidable hospitalization: the application of claims-based measures |
title | Longitudinal care continuity and avoidable hospitalization: the application of claims-based measures |
title_full | Longitudinal care continuity and avoidable hospitalization: the application of claims-based measures |
title_fullStr | Longitudinal care continuity and avoidable hospitalization: the application of claims-based measures |
title_full_unstemmed | Longitudinal care continuity and avoidable hospitalization: the application of claims-based measures |
title_short | Longitudinal care continuity and avoidable hospitalization: the application of claims-based measures |
title_sort | longitudinal care continuity and avoidable hospitalization: the application of claims-based measures |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224272/ https://www.ncbi.nlm.nih.gov/pubmed/37244982 http://dx.doi.org/10.1186/s12913-023-09457-w |
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