Dataset Information

Influence of hospital and nursing home quality on hospital readmissions.

ABSTRACT: OBJECTIVES:To determine whether the quality of the hospital and of the nursing home (NH) to which a patient was discharged were related to the likelihood of rehospitalization. STUDY DESIGN:Retrospective cohort study of 1,382,477 individual hospitalizations discharged to 15,356 NHs from 3683 hospitals between 2006 and 2008. METHODS:Data come from Medicare claims and enrollment records, Minimum Data Set, Online Survey Certification and Reporting Dataset, Hospital Compare, and the American Hospital Association Database. Cross-classified random effects models were used to test the association of hospital and NH quality measures and the likelihood of 30-day rehospitalization. RESULTS:Patients discharged from higher-quality hospitals (as indicated by higher scores on their accountability process measures and high nurse staffing levels) and patients who received care in higher-quality NHs (as indicated by high nurse staffing levels and lower deficiency scores) were less likely to be rehospitalized within 30 days. CONCLUSIONS:The passage of the Affordable Care Act changed the accountability of hospitals for patients' outcomes after discharge. This study highlights the joint accountability of hospitals and NHs for rehospitalization of patients.

SUBMITTER: Thomas KS

PROVIDER: S-EPMC4692800 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Influence of hospital and nursing home quality on hospital readmissions.

Thomas Kali S KS Rahman Momotazur M Mor Vincent V Intrator Orna O

The American journal of managed care 20141101 11

<h4>Objectives</h4>To determine whether the quality of the hospital and of the nursing home (NH) to which a patient was discharged were related to the likelihood of rehospitalization.<h4>Study design</h4>Retrospective cohort study of 1,382,477 individual hospitalizations discharged to 15,356 NHs from 3683 hospitals between 2006 and 2008.<h4>Methods</h4>Data come from Medicare claims and enrollment records, Minimum Data Set, Online Survey Certification and Reporting Dataset, Hospital Compare, and ...[more]

PMID: 25730351

Similar Datasets

Project description:BackgroundRisk factors common to nursing home (NH) residents are potentially not fully captured by the Hospital Readmissions Reduction Program (HRRP). The unique challenges faced by hospitals that disproportionately serve NH residents who are at greater risk of readmissions have not been studied.MethodsUsing 100% Medicare Provider Analysis and Review File and the Minimum Data Set from 2010-2013, we constructed a measure of hospital share of NH-originating hospitalizations (NOHs). We defined hospital share of NOHs as the proportion of inpatient stays by patients aged 65 or older who were directly admitted from NHs. To evaluate the impact of the share of NOHs on readmission penalties, we categorized hospitals into quartiles according to their share of NOHs and estimated the differences in the adjusted penalties across hospital quartiles after accounting for hospital characteristics, market characteristics and state fixed effects. We repeated the analyses for the penalties incurred in each year between 2015 and 2019.ResultsHospitals varied substantially in the share of NOHs (median [interquartile range], 11.3% [8.2%-15.1%]), with limited variation over time. In 2015, hospitals in the highest quartile of NOH received on average 0.58% Medicare payment reduction compared to 0.44% reduction among those in the lowest quartile (32.9% higher penalties, p < 0.001). The increase in penalties continued to grow in 2017 and 2018 when the HRRP expanded to include additional target conditions (47.3% and 66.7%, respectively, p < 0.001 for both). Although the effect diminished in 2019 following the additional adjustment for hospital's dual-eligible share, hospitals in the highest quartile of NOH still incurred 43.0% (p < 0.001) higher penalties than those in the lowest quartile.ConclusionsHospitals varied considerably in their share of NOHs. Hospitals having a higher share of NOHs were disproportionately penalized for excess readmissions, even under the revised policy that adjusts for the share of dual-eligible admissions.

Project description:OBJECTIVE:To use patient-level clinical variables to develop and validate a parsimonious model to predict hospital readmissions from home healthcare (HHC) in Medicare fee-for-service beneficiaries. DESIGN:Retrospective analysis using multivariable logistic regression and gradient boosting machine (GBM) learning to develop and validate a predictive model. SETTING/PARTICIPANTS/MEAUREMENTS:A 5% national sample of patients, aged 65?years or older, with Medicare fee-for-service who received skilled HHC services within 5 days of hospital discharge in 2012 (n = 43 407). Multiple data sets were merged, including Medicare Outcome and Assessment Information Set, Home Health Claims, Medicare Provider Analysis and Review, and Master Beneficiary Summary Files, to extract patient-level variables from the first HHC visit after discharge and measure 30-day readmission outcomes. RESULTS:Among 43 407 patients with inpatient hospitalizations followed by HHC, 14.7% were readmitted within 30?days. Of the 53 candidate variables, seven remained in the final model as individually predictive of outcome: Elixhauser comorbidity index, index hospital length of stay, urinary catheter presence, patient status (ie, fragile health with high risk of complications or serious progressive condition), two or more hospitalizations in prior year, pressure injury risk or presence, and surgical wound presence. Of interest, surgical wounds, either from a total hip or total knee arthroplasty procedure or another surgical procedure, were associated with fewer readmissions. The optimism-corrected c-statistics for the full model and parsimonious model were 0.67 and 0.66, respectively, indicating fair discrimination. The Brier score for both models was 0.120, indicating good calibration. The GBM model identified similar predictive variables. CONCLUSION:Variables available to HHC clinicians at the first postdischarge HHC visit can predict readmission risk and inform care plans in HHC. Future analyses incorporating measures of social determinants of health, such as housing instability or social support, have the potential to enhance prediction of this outcome. J Am Geriatr Soc 67:2505-2510, 2019.

Project description:BackgroundThirty-day hospital readmissions represent an international challenge leading to increased prevalence of adverse events, reduced quality of care and pressure on healthcare service's resources and finances. There is a need for a broader understanding of hospital readmissions, how they manifest, and how resources in the primary healthcare service may affect hospital readmissions. The aim of the study was to examine how nurses and nursing home leaders experienced the resource situation, staffing and competence level in municipal healthcare services, and if and how they experienced these factors to influence hospital readmissions.MethodThe study was conducted as a comparative case study of two municipalities affiliated with the same hospital, chosen for historical differences in readmission rates. Nurses and leaders from four nursing homes participated in focus groups and interviews. Data were analyzed within and across cases.ResultsThe analysis resulted in four common themes, with some variation in each municipality, describing nurses' and leaders' experience of the nursing home resource situation, staffing level and competence and their perception of factors affecting hospital readmissions. The nursing home patients were described as becoming increasingly complex with a subsequent need for increased nurse competence. There was variation in competence and staffing between nursing homes, but capacity building was an overall focus. Economic limitations and attempts at saving through cost-cutting were present, but not perceived as affecting patient care and the availability of medical equipment. Several factors such as nurse competence and staffing, physician coverage, and adequate communication and documentation, were recognized as factors affecting hospital readmissions across the municipalities.ConclusionSeveral factors related to nurses' and leaders' experience of the resource situation, staffing and competence level were suggested to affect hospital readmissions and the municipalities were similar in their answers regarding these factors. Patients were perceived as more complex with higher patient mortality forcing long-term nursing homes to shift towards an acute care or palliative function, and short-term nursing homes to function as "small hospitals", requiring higher nurse competence. Staffing, competence and physician coverage did not seem to have adjusted to the new patient group in some nursing homes.

Project description:ImportanceWhile the number of prescribing clinicians (physicians and nurse practitioners) who provide any nursing home care remained stable over the past decade, the number of clinicians who focus their practice exclusively on nursing home care has increased by over 30%.ObjectivesTo measure the association between regional trends in clinician specialization in nursing home care and nursing home quality.DesignRetrospective cross-sectional study.Setting and participantsPatients treated in 15,636 nursing homes in 305 US hospital referral regions between 2013 and 2016.MeasuresClinician specialization in nursing home care for 2012-2015 was measured using Medicare fee-for-service billings. Nursing home specialists were defined as generalist physicians (internal medicine, family medicine, geriatrics, and general practice) or advanced practitioners (nurse practitioners and physician assistants) with at least 90% of their billings for care in nursing homes. The number of clinicians was aggregated at the hospital referral region level and divided by the number of occupied Medicare-certified nursing home beds. Nursing Home Compare quality measure scores for 2013-2016 were aggregated at the HHR level, weighted by occupied beds in each nursing home in the hospital referral region. We measured the association between the number of nursing home specialists per 1000 beds and the clinical quality measure scores in the subsequent year using linear regression.ResultsAn increase in nursing home specialists per 1000 occupied beds in a region was associated with lower use of long-stay antipsychotic medications and indwelling bladder catheters, higher prevalence of depressive symptoms, and was not associated with urinary tract infections, use of restraints, or short-stay antipsychotic use.Conclusions and implicationsHigher prevalence of nursing home specialists was associated with regional improvements in 2 of 6 quality measures. Future studies should evaluate whether concentrating patient care among clinicians who specialize in nursing home practice improves outcomes for individual patients. The current findings suggest that prescribing clinicians play an important role in nursing home care quality.

Dataset Information

Influence of hospital and nursing home quality on hospital readmissions.

Publications

Influence of hospital and nursing home quality on hospital readmissions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets