Patterns of Multimorbidity and Differences in Healthcare Utilization and Complexity Among Acutely Hospitalized Medical Patients (≥65 Years) – A Latent Class Approach
The majority of acutely admitted older medical patients are multimorbid, receive multiple drugs, and experience a complex treatment regime. To be able to optimize treatment and care, we need more knowledge of the association between different patterns of multimorbidity and healthcare utilization and...
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| Published in | Clinical epidemiology Vol. 12; pp. 245 - 259 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
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New Zealand
Taylor & Francis Ltd
01.01.2020
Dove Dove Medical Press |
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| Online Access | Get full text |
| ISSN | 1179-1349 1179-1349 |
| DOI | 10.2147/CLEP.S226586 |
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| Abstract | The majority of acutely admitted older medical patients are multimorbid, receive multiple drugs, and experience a complex treatment regime. To be able to optimize treatment and care, we need more knowledge of the association between different patterns of multimorbidity and healthcare utilization and the complexity thereof. The purpose was therefore to investigate patterns of multimorbidity in a Danish national cohort of acutely hospitalized medical patients aged 65 and older and to determine the association between these multimorbid patterns with the healthcare utilization and complexity.
Longitudinal cohort study of 129,900 (53% women) patients. Latent class analysis (LCA) was used to develop patterns of multimorbidity based on 22 chronic conditions ascertained from Danish national registers. A latent class regression was used to test for differences in healthcare utilization and healthcare complexity among the patterns measured in the year leading up to the index admission.
LCA identified eight distinct multimorbid patterns. Patients belonging to multimorbid patterns including the major chronic conditions; diabetes and chronic obstructive pulmonary disease was associated with higher odds of healthcare utilization and complexity than the reference pattern ("Minimal chronic conditions"). The pattern with the highest number of chronic conditions did not show the highest healthcare utilization nor complexity.
Our study showed that chronic conditions cluster together and that these patterns differ in healthcare utilization and complexity. Patterns of multimorbidity have the potential to be used in epidemiological studies of healthcare planning but should be confirmed in other population-based studies. |
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| AbstractList | The majority of acutely admitted older medical patients are multimorbid, receive multiple drugs, and experience a complex treatment regime. To be able to optimize treatment and care, we need more knowledge of the association between different patterns of multimorbidity and healthcare utilization and the complexity thereof. The purpose was therefore to investigate patterns of multimorbidity in a Danish national cohort of acutely hospitalized medical patients aged 65 and older and to determine the association between these multimorbid patterns with the healthcare utilization and complexity.
Longitudinal cohort study of 129,900 (53% women) patients. Latent class analysis (LCA) was used to develop patterns of multimorbidity based on 22 chronic conditions ascertained from Danish national registers. A latent class regression was used to test for differences in healthcare utilization and healthcare complexity among the patterns measured in the year leading up to the index admission.
LCA identified eight distinct multimorbid patterns. Patients belonging to multimorbid patterns including the major chronic conditions; diabetes and chronic obstructive pulmonary disease was associated with higher odds of healthcare utilization and complexity than the reference pattern ("Minimal chronic conditions"). The pattern with the highest number of chronic conditions did not show the highest healthcare utilization nor complexity.
Our study showed that chronic conditions cluster together and that these patterns differ in healthcare utilization and complexity. Patterns of multimorbidity have the potential to be used in epidemiological studies of healthcare planning but should be confirmed in other population-based studies. The majority of acutely admitted older medical patients are multimorbid, receive multiple drugs, and experience a complex treatment regime. To be able to optimize treatment and care, we need more knowledge of the association between different patterns of multimorbidity and healthcare utilization and the complexity thereof. The purpose was therefore to investigate patterns of multimorbidity in a Danish national cohort of acutely hospitalized medical patients aged 65 and older and to determine the association between these multimorbid patterns with the healthcare utilization and complexity.PURPOSEThe majority of acutely admitted older medical patients are multimorbid, receive multiple drugs, and experience a complex treatment regime. To be able to optimize treatment and care, we need more knowledge of the association between different patterns of multimorbidity and healthcare utilization and the complexity thereof. The purpose was therefore to investigate patterns of multimorbidity in a Danish national cohort of acutely hospitalized medical patients aged 65 and older and to determine the association between these multimorbid patterns with the healthcare utilization and complexity.Longitudinal cohort study of 129,900 (53% women) patients. Latent class analysis (LCA) was used to develop patterns of multimorbidity based on 22 chronic conditions ascertained from Danish national registers. A latent class regression was used to test for differences in healthcare utilization and healthcare complexity among the patterns measured in the year leading up to the index admission.PATIENTS AND METHODSLongitudinal cohort study of 129,900 (53% women) patients. Latent class analysis (LCA) was used to develop patterns of multimorbidity based on 22 chronic conditions ascertained from Danish national registers. A latent class regression was used to test for differences in healthcare utilization and healthcare complexity among the patterns measured in the year leading up to the index admission.LCA identified eight distinct multimorbid patterns. Patients belonging to multimorbid patterns including the major chronic conditions; diabetes and chronic obstructive pulmonary disease was associated with higher odds of healthcare utilization and complexity than the reference pattern ("Minimal chronic conditions"). The pattern with the highest number of chronic conditions did not show the highest healthcare utilization nor complexity.RESULTSLCA identified eight distinct multimorbid patterns. Patients belonging to multimorbid patterns including the major chronic conditions; diabetes and chronic obstructive pulmonary disease was associated with higher odds of healthcare utilization and complexity than the reference pattern ("Minimal chronic conditions"). The pattern with the highest number of chronic conditions did not show the highest healthcare utilization nor complexity.Our study showed that chronic conditions cluster together and that these patterns differ in healthcare utilization and complexity. Patterns of multimorbidity have the potential to be used in epidemiological studies of healthcare planning but should be confirmed in other population-based studies.CONCLUSIONOur study showed that chronic conditions cluster together and that these patterns differ in healthcare utilization and complexity. Patterns of multimorbidity have the potential to be used in epidemiological studies of healthcare planning but should be confirmed in other population-based studies. Purpose: The majority of acutely admitted older medical patients are multimorbid, receive multiple drugs, and experience a complex treatment regime. To be able to optimize treatment and care, we need more knowledge of the association between different patterns of multimorbidity and healthcare utilization and the complexity thereof. The purpose was therefore to investigate patterns of multimorbidity in a Danish national cohort of acutely hospitalized medical patients aged 65 and older and to determine the association between these multimorbid patterns with the healthcare utilization and complexity. Patients and Methods: Longitudinal cohort study of 129,900 (53% women) patients. Latent class analysis (LCA) was used to develop patterns of multimorbidity based on 22 chronic conditions ascertained from Danish national registers. A latent class regression was used to test for differences in healthcare utilization and healthcare complexity among the patterns measured in the year leading up to the index admission. Results: LCA identified eight distinct multimorbid patterns. Patients belonging to multimorbid patterns including the major chronic conditions; diabetes and chronic obstructive pulmonary disease was associated with higher odds of healthcare utilization and complexity than the reference pattern (“Minimal chronic conditions”). The pattern with the highest number of chronic conditions did not show the highest healthcare utilization nor complexity. Conclusion: Our study showed that chronic conditions cluster together and that these patterns differ in healthcare utilization and complexity. Patterns of multimorbidity have the potential to be used in epidemiological studies of healthcare planning but should be confirmed in other population-based studies. Helle Gybel Juul-Larsen, 1-3 Line Due Christensen, 1, 4 Thomas Bandholm, 1-3, 5Ove Andersen, 1, 2, 6Thomas Kallemose, 1 Lillian Mørch Jørgensen, 1, 6 Janne Petersen 1, 7, 8 1Clinical Research Centre, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; 2Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; 3Department of Physical and Occupational Therapy, Physical Medicine & Rehabilitation Research - Copenhagen (PMR-C), Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; 4Research Unit for General Practice, Aarhus, Denmark; 5Department of Orthopedic Surgery, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; 6Emergency Department, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; 7Centre for Clinical Research and Prevention, Copenhagen University Hospital Bispebjerg and Frederiksberg, Copenhagen, Denmark; 8Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, DenmarkCorrespondence: Helle Gybel Juul-LarsenClinical Research Centre, Section 056, Copenhagen University, Amager and Hvidovre Hospitals, Kettegård Allé 30, Hvidovre DK-2650, DenmarkTel +45 38626077Email helle.juul-larsen@regionh.dkPurpose: The majority of acutely admitted older medical patients are multimorbid, receive multiple drugs, and experience a complex treatment regime. To be able to optimize treatment and care, we need more knowledge of the association between different patterns of multimorbidity and healthcare utilization and the complexity thereof. The purpose was therefore to investigate patterns of multimorbidity in a Danish national cohort of acutely hospitalized medical patients aged 65 and older and to determine the association between these multimorbid patterns with the healthcare utilization and complexity.Patients and Methods: Longitudinal cohort study of 129,900 (53% women) patients. Latent class analysis (LCA) was used to develop patterns of multimorbidity based on 22 chronic conditions ascertained from Danish national registers. A latent class regression was used to test for differences in healthcare utilization and healthcare complexity among the patterns measured in the year leading up to the index admission.Results: LCA identified eight distinct multimorbid patterns. Patients belonging to multimorbid patterns including the major chronic conditions; diabetes and chronic obstructive pulmonary disease was associated with higher odds of healthcare utilization and complexity than the reference pattern ("Minimal chronic conditions"). The pattern with the highest number of chronic conditions did not show the highest healthcare utilization nor complexity.Conclusion: Our study showed that chronic conditions cluster together and that these patterns differ in healthcare utilization and complexity. Patterns of multimorbidity have the potential to be used in epidemiological studies of healthcare planning but should be confirmed in other population-based studies.Keywords: chronic conditions, multimorbidity, older medical patients, acute hospitalization, latent class analysis |
| Author | Juul-Larsen, Helle Gybel Petersen, Janne Andersen, Ove Christensen, Line Due Jørgensen, Lillian Mørch Bandholm, Thomas Kallemose, Thomas |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32184671$$D View this record in MEDLINE/PubMed |
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| Title | Patterns of Multimorbidity and Differences in Healthcare Utilization and Complexity Among Acutely Hospitalized Medical Patients (≥65 Years) – A Latent Class Approach |
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