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Apples and Oranges: Four Definitions of Multiple Chronic Conditions and their Relationship to 30-Day Hospital Readmission.
Dattalo, Melissa; DuGoff, Eva; Ronk, Katie; Kennelty, Korey; Gilmore-Bykovskyi, Andrea; Kind, Amy J.
Affiliation
  • Dattalo M; Geriatric Research, Education, and Clinical Center, Department of Veterans Affairs, William S. Middleton Memorial Veterans Affairs Hospital, Madison, Wisconsin.
  • DuGoff E; Division of Geriatrics, Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin.
  • Ronk K; Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin.
  • Kennelty K; Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin.
  • Gilmore-Bykovskyi A; Geriatric Research, Education, and Clinical Center, Department of Veterans Affairs, William S. Middleton Memorial Veterans Affairs Hospital, Madison, Wisconsin.
  • Kind AJ; Division of Geriatrics, Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin.
J Am Geriatr Soc ; 65(4): 712-720, 2017 Apr.
Article in En | MEDLINE | ID: mdl-28205206
ABSTRACT

OBJECTIVES:

To determine the extent of agreement between four commonly used definitions of multiple chronic conditions (MCCs) and compare each definition's ability to predict 30-day hospital readmissions.

DESIGN:

Retrospective cohort study.

SETTING:

National Medicare claims data.

PARTICIPANTS:

Random sample of Medicare beneficiaries discharged from the hospital from 2005 to 2009 (n = 710,609). MEASUREMENTS Baseline chronic conditions were determined for each participant using four definitions of MCC. The primary outcome was all-cause 30-day hospital readmission. Agreement between MCC definitions was measured, and sensitivities and specificities for each definition's ability to identify patients experiencing a future readmission were calculated. Logistic regression was used to assess the ability of each MCC definition to predict 30-day hospital readmission.

RESULTS:

The sample prevalence of hospitalized Medicare beneficiaries with two or more chronic conditions ranged from 18.6% (Johns Hopkins Adjusted Clinical Groups (ACG) Case-Mix System software) to 92.9% (Medicare Chronic Condition Warehouse (CCW)). There was slight to moderate agreement (kappa = 0.03-0.44) between pair-wise combinations of MCC definitions. CCW-defined MCC was the most sensitive (sensitivity 95.4%, specificity 7.4%), and ACG-defined MCC was the most specific (sensitivity 32.7%, specificity 83.2%) predictor of being readmitted. In the fully adjusted model, the risk of readmission was higher for those with chronic condition Special Needs Plan (c-SNP)-defined MCCs (odds ratio (OR) = 1.50, 95% confidence interval (CI) = 1.47-1.52), Charlson Comorbidity Index-defined MCCs (OR = 1.45, 95% CI = 1.42-1.47), ACG-defined MCCs (OR = 1.22, 95% CI = 1.19-1.25), and CCW-defined MCCs (OR = 1.15, 95% CI = 1.11-1.19) than for those without MCCs.

CONCLUSION:

MCC definitions demonstrate poor agreement and should not be used interchangeably. The two definitions with the greatest agreement (CCI, c-SNP) were also the best predictors of 30-day hospital readmissions.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Patient Readmission / Multiple Chronic Conditions Type of study: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limits: Aged / Female / Humans / Male Country/Region as subject: America do norte Language: En Journal: J Am Geriatr Soc Year: 2017 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Patient Readmission / Multiple Chronic Conditions Type of study: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limits: Aged / Female / Humans / Male Country/Region as subject: America do norte Language: En Journal: J Am Geriatr Soc Year: 2017 Document type: Article