The Impact of Disability and Social Determinants of Health on Condition-Specific Readmissions beyond Medicare Risk Adjustments: A Cohort Study

被引:106
作者
Meddings, Jennifer [1 ,2 ,3 ,6 ]
Reichert, Heidi [1 ,6 ]
Smith, Shawna N. [1 ,4 ,6 ]
Iwashyna, Theodore J. [1 ,3 ,4 ,6 ]
Langa, Kenneth M. [1 ,3 ,4 ,5 ,6 ]
Hofer, Timothy P. [1 ,3 ,6 ]
McMahon, Laurence F., Jr. [1 ,5 ,6 ]
机构
[1] Univ Michigan, Sch Med, Dept Internal Med, Div Gen Med, 2800 Plymouth Rd,Bldg 16,430W, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Sch Med, Div Gen Pediat, Dept Pediat & Communicable Dis, Ann Arbor, MI USA
[3] Ann Arbor VA Med Ctr, Ann Arbor, MI USA
[4] Univ Michigan, Inst Social Res, Ann Arbor, MI USA
[5] Univ Michigan, Sch Publ Hlth, Ann Arbor, MI 48109 USA
[6] Univ Michigan, Inst Healthcare Policy & Innovat, Ann Arbor, MI 48109 USA
基金
美国医疗保健研究与质量局;
关键词
readmission; risk adjustment; Medicare; pneumonia; heart failure; HOSPITAL READMISSION; COGNITIVE IMPAIRMENT; 30-DAY READMISSION; HEART-FAILURE; UNITED-STATES; CARE; COMPLICATIONS; PREDICTION; MORTALITY; PATTERNS;
D O I
10.1007/s11606-016-3869-x
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Readmission rates after pneumonia, heart failure, and acute myocardial infarction hospitalizations are risk-adjusted for age, gender, and medical comorbidities and used to penalize hospitals. To assess the impact of disability and social determinants of health on condition-specific readmissions beyond current risk adjustment. Retrospective cohort study of Medicare patients using 1) linked Health and Retirement Study-Medicare claims data (HRS-CMS) and 2) Healthcare Cost and Utilization Project State Inpatient Databases (Florida, Washington) linked with ZIP Code-level measures from the Census American Community Survey (ACS-HCUP). Multilevel logistic regression models assessed the impact of disability and selected social determinants of health on readmission beyond current risk adjustment. Outcomes measured were readmissions 30 days after hospitalizations for pneumonia, heart failure, or acute myocardial infarction. HRS-CMS models included disability measures (activities of daily living [ADL] limitations, cognitive impairment, nursing home residence, home healthcare use) and social determinants of health (spouse, children, wealth, Medicaid, race). ACS-HCUP model measures were ZIP Code-percentage of residents 65 years of age with ADL difficulty, spouse, income, Medicaid, and patient-level and hospital-level race. For pneumonia, 3 ADL difficulties (OR 1.61, CI 1.079-2.391) and prior home healthcare needs (OR 1.68, CI 1.204-2.355) increased readmission in HRS-CMS models (N = 1631); ADL difficulties (OR 1.20, CI 1.063-1.352) and 'other' race (OR 1.14, CI 1.001-1.301) increased readmission in ACS-HCUP models (N = 27,297). For heart failure, children (OR 0.66, CI 0.437-0.984) and wealth (OR 0.53, CI 0.349-0.787) lowered readmission in HRS-CMS models (N = 2068), while black (OR 1.17, CI 1.056-1.292) and 'other' race (OR 1.14, CI 1.036-1.260) increased readmission in ACS-HCUP models (N = 37,612). For acute myocardial infarction, nursing home status (OR 4.04, CI 1.212-13.440) increased readmission in HRS-CMS models (N = 833); 'other' patient-level race (OR 1.18, CI 1.012-1.385) and hospital-level race (OR 1.06, CI 1.001-1.125) increased readmission in ACS-HCUP models (N = 17,496). Disability and social determinants of health influence readmission risk when added to the current Medicare risk adjustment models, but the effect varies by condition.
引用
收藏
页码:71 / 80
页数:10
相关论文
共 44 条
[1]   PRESSURE ULCER RISK-FACTORS AMONG HOSPITALIZED-PATIENTS WITH ACTIVITY LIMITATION [J].
ALLMAN, RM ;
GOODE, PS ;
PATRICK, MM ;
BURST, N ;
BARTOLUCCI, AA .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 1995, 273 (11) :865-870
[2]  
Andrews R, 2008, THE QUALITY OF REPOR
[3]  
[Anonymous], 2013, READMISSIONAMI HF PN
[4]  
[Anonymous], 2016, HEALTH AND RETIREMEN
[5]  
[Anonymous], 2016, ACCOUNTING FOR SOCIA
[6]  
[Anonymous], 2014, RISK ADJUSTMENT FOR
[7]  
[Anonymous], 2014, DEFINING CATEGORIZAT
[8]   Patient Characteristics and Differences in Hospital Readmission Rates [J].
Barnett, Michael L. ;
Hsu, John ;
McWilliams, J. Michael .
JAMA INTERNAL MEDICINE, 2015, 175 (11) :1803-1812
[9]  
Berenson J., 2012, Higher readmissions at safety-net hospitals and potential policy solutions (Issue Brief)
[10]  
Bergquist S, 1999, Adv Wound Care, V12, P339