The results demonstrate the feasibility and potential of using EHRs and claims for collecting new types of geriatric risk information that could augment the more commonly collected disease information to identify and move upstream the management of high-risk cases among older patients.
Objectives
To examine characteristics and locations of high‐ and low‐quality skilled nursing facilities (SNFs) and whether certain vulnerable individuals were differentially discharged to facilities with lower quality ratings.
Design
Retrospective observational study.
Setting
Medicare‐certified SNFs providing postacute care.
Participants
SNF stays (N=1,195,166) of Medicare beneficiaries aged 65 and older admitted to 14,033 SNFs within 2 days of hospital discharge.
Measurements
We used Medicare claims from October 2013 to September 2014 and SNF 5‐star ratings published on Nursing Home Compare. We describe the characteristics and populations of facilities according to quality, and the location of low (1 star) and high (5 stars) quality facilities. We used logistic regression models to estimate odds of admission to a low‐quality facility after hospital discharge according to race, ethnicity, dual Medicare–Medicaid enrollment, functional status, discharge from a safety‐net or low‐quality hospital, and residence in a county with more low‐quality SNFs.
Results
More than one‐fifth (22.2%) of the facilities had a 5‐star (high quality) rating, and 15.9% had a one‐star (low quality) rating. Low‐quality facilities were more likely to be in the south (44%), for profit (85%), and larger (>70 beds (86%)). Dual enrollment was the strongest predictor of admission to a 1‐star facility (odds ratio (OR) = 1.53, 95% confidence interval (CI) = 1.51–1.55), although racial or ethnic minority status (black: OR = 1.25, 95% CI = 1.22–1.28; Hispanic: OR = 1.10, 95% CI = 1.06–1.14) and geographic prevalence of facilities (for a 10% increase in 1‐star beds located in the county of individual's residence: OR = 1.27, 95% CI = 1.26–1.27) were also significant predictors.
Conclusion
Vulnerable groups are more likely to be discharged to lower‐quality facilities for postacute care. Policy‐makers should monitor disparities in SNF quality. J Am Geriatr Soc 67:108–114, 2019.
Objectives: To assess two models for the prediction of health utilization and functions using standardized in-person assessments of frailty and administrative claims-based geriatric risk measures among Medicare fee-for-service beneficiaries aged 65 years and above. Methods: Outcomes of hospitalizations, death, and functional help were investigated for participants in the 2011 National Health and Aging Trends Study. For each outcome, multivariable logistic regression model was used to investigate claims-based geriatric risk and survey-based frailty. Results: Both claims-based and survey-based models showed moderate discrimination. The c-statistic of the standardized frailty models ranged from 0.67 (for any hospitalization) to 0.84 (for any IADL [instrumental activities of daily living] help). Models using administrative data ranged from 0.71 (for any hospitalization) to 0.81 (for any IADL help). Discussion: Models based on existing administrative data appear to be as discriminate as survey-based models. Health care providers and insurance plans can effectively apply existing data resources to help identify high-risk individuals for potential care management interventions.
Within the existing fee-for-service healthcare model, ACOs are a mechanism for decreasing costs by improving quality of care. Higher quality organizations incorporate greater levels of coordination of care, which is associated with greater cost savings. Pioneer ACOs have the highest level of integration of services; hence, they save the most money.
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