| Title |
The Impact of Disability and Social Determinants of Health on Condition-Specific Readmissions beyond Medicare Risk Adjustments: A Cohort Study
|
|---|---|
| Published in |
Journal of General Internal Medicine, November 2016
|
| DOI | 10.1007/s11606-016-3869-x |
| Pubmed ID | |
| Authors |
Jennifer Meddings, Heidi Reichert, Shawna N. Smith, Theodore J. Iwashyna, Kenneth M. Langa, Timothy P. Hofer, Laurence F. McMahon |
| Abstract |
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. |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 40% |
| Spain | 2 | 20% |
| Unknown | 4 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 80% |
| Scientists | 1 | 10% |
| Science communicators (journalists, bloggers, editors) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 193 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Unknown | 192 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 13% |
| Researcher | 25 | 13% |
| Student > Master | 24 | 12% |
| Student > Bachelor | 20 | 10% |
| Student > Doctoral Student | 16 | 8% |
| Other | 34 | 18% |
| Unknown | 49 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 45 | 23% |
| Nursing and Health Professions | 38 | 20% |
| Social Sciences | 13 | 7% |
| Psychology | 9 | 5% |
| Computer Science | 4 | 2% |
| Other | 22 | 11% |
| Unknown | 62 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 48. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 March 2021.
All research outputs
#802,209
of 23,911,072 outputs
Outputs from Journal of General Internal Medicine
#677
of 7,806 outputs
Outputs of similar age
#15,598
of 309,882 outputs
Outputs of similar age from Journal of General Internal Medicine
#7
of 84 outputs
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