Apples and Oranges: Four Definitions of Multiple Chronic Conditions and their Relationship to 30-Day Hospital Readmission

被引:22
作者
Dattalo, Melissa [1 ,2 ]
DuGoff, Eva [3 ]
Ronk, Katie [3 ]
Kennelty, Korey [1 ,2 ,4 ]
Gilmore-Bykovskyi, Andrea [1 ,5 ]
Kind, Amy J. [1 ,2 ,4 ,5 ]
机构
[1] William S Middleton Mem Vet Affairs Hosp, Dept Vet Affairs, Geriatr Res Educ & Clin Ctr, Madison, WI USA
[2] Univ Wisconsin, Dept Med, Div Geriatr, Sch Med & Publ Hlth, 2870 Univ Ave,Suite 106, Madison, WI 53705 USA
[3] Univ Wisconsin, Sch Med & Publ Hlth, Dept Populat Hlth Sci, Madison, WI USA
[4] Univ Wisconsin, Sch Pharm, 425 N Charter St, Madison, WI 53706 USA
[5] Univ Wisconsin, Sch Nursing, Madison, WI USA
基金
美国国家卫生研究院;
关键词
Medicare; multimorbidity; multiple chronic conditions; readmissions; chronic care management; COMORBIDITY INDEXES; PRIMARY-CARE; EVENTS; REHOSPITALIZATION; EMERGENCY; PROGRAM; COHORT; CLAIMS; TRIAL; RISK;
D O I
10.1111/jgs.14539
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
ObjectivesTo 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. DesignRetrospective cohort study. SettingNational Medicare claims data. ParticipantsRandom sample of Medicare beneficiaries discharged from the hospital from 2005 to 2009 (n = 710,609). MeasurementsBaseline 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. ResultsThe 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. ConclusionMCC 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.
引用
收藏
页码:712 / 720
页数:9
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