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Patterns of multimorbidity in primary care patients at high risk of future hospitalization

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Patterns of multimorbidity in primary care patients at high risk of future hospitalization. / Freund, Tobias; Kunz, Cornelia Ursula; Ose, Dominik et al.
In: Population Health Management, Vol. 15, No. 2, 16.04.2012, p. 119-124.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Freund, T, Kunz, CU, Ose, D, Szecsenyi, J & Peters-Klimm, F 2012, 'Patterns of multimorbidity in primary care patients at high risk of future hospitalization', Population Health Management, vol. 15, no. 2, pp. 119-124. https://doi.org/10.1089/pop.2011.0026

APA

Freund, T., Kunz, C. U., Ose, D., Szecsenyi, J., & Peters-Klimm, F. (2012). Patterns of multimorbidity in primary care patients at high risk of future hospitalization. Population Health Management, 15(2), 119-124. https://doi.org/10.1089/pop.2011.0026

Vancouver

Freund T, Kunz CU, Ose D, Szecsenyi J, Peters-Klimm F. Patterns of multimorbidity in primary care patients at high risk of future hospitalization. Population Health Management. 2012 Apr 16;15(2):119-124. Epub 2012 Feb 7. doi: 10.1089/pop.2011.0026

Author

Freund, Tobias ; Kunz, Cornelia Ursula ; Ose, Dominik et al. / Patterns of multimorbidity in primary care patients at high risk of future hospitalization. In: Population Health Management. 2012 ; Vol. 15, No. 2. pp. 119-124.

Bibtex

@article{52aafa277db745589cbfd2ec0c99456e,
title = "Patterns of multimorbidity in primary care patients at high risk of future hospitalization",
abstract = "Care management is seen as a promising approach to address the complex care needs of patients with multimorbidity. Predictive modeling based on insurance claims data is an emerging concept to identify patients likely to benefit from care management interventions. We aimed to identify and explore patterns of multimorbidity in primary care patients with high predicted risk of future hospitalizations in order to develop a primary care-based care management intervention. We conducted a retrospective cohort study to assess insurance claims data of 6026 patients from 10 primary care practices in Germany. We stratified the population by the predicted likelihood of hospitalization (LOH) using a diagnostic cost group-based case-finding software. Co-occurrence of chronic conditions in multimorbid patients with an upper-quartile LOH score was explored by extraction of mutually exclusive patterns. Predictive modeling identified multimorbid elderly patients with a high number of co-occurring chronic conditions (mean number 7.8 [SD 3.1]). Assessing co-occurrence of highly prevalent chronic conditions in 1407 multimorbid patients with upper-quartile LOH revealed 471 mutually exclusive patterns with low single frequencies. The observed prevalence significantly exceeded expected prevalence for patterns with causal comorbidity. Additionally, chronic pain (related to osteoarthritis) or depression could be identified as discordant co-occurring conditions in 80% (12/15) of the most common multimorbidity patterns. High-risk primary care patients suffer from heterogeneous individual patterns of co-occurring chronic conditions. Care management interventions will have to account for discordant co-occurring conditions such as osteoarthritis and depression.",
keywords = "Aged, Case Management, Chi-Square Distribution, Chronic Disease, Comorbidity, Female, Germany, Hospitalization, Humans, Insurance Claim Review, Male, Middle Aged, Predictive Value of Tests, Prevalence, Primary Health Care, Retrospective Studies, Risk Assessment, Risk Factors, Software",
author = "Tobias Freund and Kunz, {Cornelia Ursula} and Dominik Ose and Joachim Szecsenyi and Frank Peters-Klimm",
note = "{\textcopyright} Mary Ann Liebert, Inc.",
year = "2012",
month = apr,
day = "16",
doi = "10.1089/pop.2011.0026",
language = "English",
volume = "15",
pages = "119--124",
journal = "Population Health Management",
issn = "1942-7905",
publisher = "Mary Ann Liebert Inc.",
number = "2",

}

RIS

TY - JOUR

T1 - Patterns of multimorbidity in primary care patients at high risk of future hospitalization

AU - Freund, Tobias

AU - Kunz, Cornelia Ursula

AU - Ose, Dominik

AU - Szecsenyi, Joachim

AU - Peters-Klimm, Frank

N1 - © Mary Ann Liebert, Inc.

PY - 2012/4/16

Y1 - 2012/4/16

N2 - Care management is seen as a promising approach to address the complex care needs of patients with multimorbidity. Predictive modeling based on insurance claims data is an emerging concept to identify patients likely to benefit from care management interventions. We aimed to identify and explore patterns of multimorbidity in primary care patients with high predicted risk of future hospitalizations in order to develop a primary care-based care management intervention. We conducted a retrospective cohort study to assess insurance claims data of 6026 patients from 10 primary care practices in Germany. We stratified the population by the predicted likelihood of hospitalization (LOH) using a diagnostic cost group-based case-finding software. Co-occurrence of chronic conditions in multimorbid patients with an upper-quartile LOH score was explored by extraction of mutually exclusive patterns. Predictive modeling identified multimorbid elderly patients with a high number of co-occurring chronic conditions (mean number 7.8 [SD 3.1]). Assessing co-occurrence of highly prevalent chronic conditions in 1407 multimorbid patients with upper-quartile LOH revealed 471 mutually exclusive patterns with low single frequencies. The observed prevalence significantly exceeded expected prevalence for patterns with causal comorbidity. Additionally, chronic pain (related to osteoarthritis) or depression could be identified as discordant co-occurring conditions in 80% (12/15) of the most common multimorbidity patterns. High-risk primary care patients suffer from heterogeneous individual patterns of co-occurring chronic conditions. Care management interventions will have to account for discordant co-occurring conditions such as osteoarthritis and depression.

AB - Care management is seen as a promising approach to address the complex care needs of patients with multimorbidity. Predictive modeling based on insurance claims data is an emerging concept to identify patients likely to benefit from care management interventions. We aimed to identify and explore patterns of multimorbidity in primary care patients with high predicted risk of future hospitalizations in order to develop a primary care-based care management intervention. We conducted a retrospective cohort study to assess insurance claims data of 6026 patients from 10 primary care practices in Germany. We stratified the population by the predicted likelihood of hospitalization (LOH) using a diagnostic cost group-based case-finding software. Co-occurrence of chronic conditions in multimorbid patients with an upper-quartile LOH score was explored by extraction of mutually exclusive patterns. Predictive modeling identified multimorbid elderly patients with a high number of co-occurring chronic conditions (mean number 7.8 [SD 3.1]). Assessing co-occurrence of highly prevalent chronic conditions in 1407 multimorbid patients with upper-quartile LOH revealed 471 mutually exclusive patterns with low single frequencies. The observed prevalence significantly exceeded expected prevalence for patterns with causal comorbidity. Additionally, chronic pain (related to osteoarthritis) or depression could be identified as discordant co-occurring conditions in 80% (12/15) of the most common multimorbidity patterns. High-risk primary care patients suffer from heterogeneous individual patterns of co-occurring chronic conditions. Care management interventions will have to account for discordant co-occurring conditions such as osteoarthritis and depression.

KW - Aged

KW - Case Management

KW - Chi-Square Distribution

KW - Chronic Disease

KW - Comorbidity

KW - Female

KW - Germany

KW - Hospitalization

KW - Humans

KW - Insurance Claim Review

KW - Male

KW - Middle Aged

KW - Predictive Value of Tests

KW - Prevalence

KW - Primary Health Care

KW - Retrospective Studies

KW - Risk Assessment

KW - Risk Factors

KW - Software

U2 - 10.1089/pop.2011.0026

DO - 10.1089/pop.2011.0026

M3 - Journal article

C2 - 22313440

VL - 15

SP - 119

EP - 124

JO - Population Health Management

JF - Population Health Management

SN - 1942-7905

IS - 2

ER -