The role of outpatient facilities in explaining variations in risk-adjusted readmission rates between hospitals.
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ABSTRACT:
SUBMITTER: Lorch SA
PROVIDER: S-EPMC2813435 | biostudies-other | 2010 Feb
REPOSITORIES: biostudies-other
Publications
The role of outpatient facilities in explaining variations in risk-adjusted readmission rates between hospitals.
Lorch Scott A SA Baiocchi Michael M Silber Jeffrey H JH Even-Shoshan Orit O Escobar Gabriel J GJ Small Dylan S DS
Health services research 20090924 1
<h4>Objective</h4>Validate risk-adjusted readmission rates as a measure of inpatient quality of care after accounting for outpatient facilities, using premature infants as a test case.<h4>Study setting</h4>Surviving infants born between January 1, 1998 and December 12, 2001 at five Northern California Kaiser Permanente neonatal intensive care units (NICU) with 1-year follow-up at 32 outpatient facilities.<h4>Study design</h4>Using a retrospective cohort of premature infants (N=898), Poisson's re ...[more]
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Project description:ObjectiveTo examine the relative influence of hospital and skilled nursing facilities (SNFs) on 30-day rehospitalization.Data sources/settingsElderly Medicare beneficiaries newly admitted to a SNF following hospitalization.Study designWe ranked hospitals and SNFs into quartiles based on previous years' adjusted rehospitalization rates (ARRs) and examined how rehospitalizations from a given hospital vary depending upon the admitting SNF ARR quartile. We examined whether the availability of SNFs with low rehospitalization rates influenced hospitals' SNF readmission rates and whether changes in a hospital's ARR over 3 years is associated with changes in the SNFs to which they discharge.Principal findingsHospital readmission rates from SNFs varied 5 percentage points between patients discharged to SNFs in the lowest and the highest rehospitalization quartiles. Low rehospitalization rate hospitals sent a larger fraction of their patients to the lowest rehospitalization SNFs available in the area. A 10 percent increase in hospital's share of discharges to the lowest rehospitalization quartile SNFs is associated with a 1 percentage point reduction in hospital's ARR.ConclusionsThe SNF rehospitalization rate has greater influence on patients' risk of rehospitalization than the discharging hospital. Identifying high-performing SNFs may be a powerful strategy for hospitals to reduce rehospitalizations.
| S-EPMC5346496 | biostudies-literature
Project description:AbstractHealth information technology (IT) is often proposed as a solution to fragmentation of care, and has been hypothesized to reduce readmission risk through better information flow. However, there are numerous distinct health IT capabilities, and it is unclear which, if any, are associated with lower readmission risk.To identify the specific health IT capabilities adopted by hospitals that are associated with hospital-level risk-standardized readmission rates (RSRRs) through path analyses using structural equation modeling.This STROBE-compliant retrospective cross-sectional study included non-federal U.S. acute care hospitals, based on their adoption of specific types of health IT capabilities self-reported in a 2013 American Hospital Association IT survey as independent variables. The outcome measure included the 2014 RSRRs reported on Hospital Compare website.A 54-indicator 7-factor structure of hospital health IT capabilities was identified by exploratory factor analysis, and corroborated by confirmatory factor analysis. Subsequent path analysis using Structural equation modeling revealed that a one-point increase in the hospital adoption of patient engagement capability latent scores (median path coefficient ß = -0.086; 95% Confidence Interval, -0.162 to -0.008), including functionalities like direct access to the electronic health records, would generally lead to a decrease in RSRRs by 0.086%. However, computerized hospital discharge and information exchange capabilities with other inpatient and outpatient providers were not associated with readmission rates.These findings suggest that improving patient access to and use of their electronic health records may be helpful in improving hospital performance on readmission; however, computerized hospital discharge and information exchange among clinicians did not seem as beneficial - perhaps because of the quality or timeliness of information transmitted. Future research should use more recent data to study, not just adoption of health IT capabilities, but also whether their usage is associated with lower readmission risk. Understanding which capabilities impact readmission risk can help policymakers and clinical stakeholders better focus their scarce resources as they invest in health IT to improve care delivery.
| S-EPMC7909153 | biostudies-literature
Project description:BackgroundThere has been a relentless increase in emergency medical admissions in the UK over recent years. Many of these patients suffer with chronic conditions requiring continuing medical attention. We wished to determine whether conventional outpatient clinic follow up after discharge has any impact on the rate of readmission to hospital.MethodsTwo consultant general physicians with the same patient case-mix but markedly different outpatient follow-up practice were chosen. Of 1203 patients discharged, one consultant saw twice as many patients in the follow-up clinic than the other (Dr A 9.8% v Dr B 19.6%). The readmission rate in the twelve months following discharge was compared in a retrospective analysis of hospital activity data. Due to the specialisation of the admitting system, patients mainly had cardiovascular or cerebrovascular disease or had taken an overdose. Few had respiratory or infectious diseases. Outpatient follow-up was focussed on patients with cardiac disease.ResultsRisk of readmission increased significantly with age and length of stay of the original episode and was less for digestive system and musculo-skeletal disorders. 28.7% of patients discharged by Dr A and 31.5 % of those discharged by Dr B were readmitted at least once. Relative readmission risk was not significantly different between the consultants and there was no difference in the length of stay of readmissions.ConclusionsIncreasing the proportion of patients with this age- and case-mix who are followed up in a hospital general medical outpatient clinic is unlikely to reduce the demand for acute hospital beds.
| S-EPMC117439 | biostudies-literature
Project description:OBJECTIVES:To identify modifiable factors leading to unplanned readmission and characterize differences in adjusted unplanned readmission rates across hospitals. DESIGN:Retrospective cohort study using prospectively collected clinical registry data SETTING:: Pediatric Cardiac Critical Care Consortium clinical registry. PATIENTS:Patients admitted to a pediatric cardiac ICU at Pediatric Cardiac Critical Care Consortium hospitals. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:We examined pediatric cardiac ICU encounters in the Pediatric Cardiac Critical Care Consortium registry from October 2013 to March 2016. The primary outcomes were early (< 48?hr from pediatric cardiac ICU transfer) and late (2-7 d) unplanned readmission. Generalized logit models identified independent predictors of unplanned readmission. We then calculated observed-to-expected ratios of unplanned readmission and identified higher-than or lower-than-expected unplanned readmission rates for those with an observed-to-expected ratios greater than or less than 1, respectively, and a 95% CI that did not cross 1. Of 11,301 pediatric cardiac ICU encounters (16 hospitals), 62% were surgical, and 18% were neonates. There were 175 (1.6%) early unplanned readmission, and 300 (2.7%) late unplanned readmission, most commonly for respiratory (31%), or cardiac (28%) indications. In multivariable analysis, unique modifiable factors were associated with unplanned readmission. Although shorter time between discontinuation of vasoactive infusions and pediatric cardiac ICU transfer was associated with early unplanned readmission, nighttime discharge was independently associated with a greater likelihood of late unplanned readmission. Two hospitals had lower-than-expected unplanned readmission in both the early and late categories, whereas two other hospitals were higher-than-expected in both. CONCLUSIONS:This analysis demonstrated time from discontinuation of critical care therapies to pediatric cardiac ICU transfer as a significant, modifiable predictor of unplanned readmission. We identified two hospitals with lower-than-expected adjusted rates of both early and late unplanned readmission, suggesting that their systems are well designed to prevent unplanned readmission. This offers the possibility of disseminating best practices to other hospitals through collaborative learning.
| S-EPMC6239958 | biostudies-literature
Project description:ObjectiveTo compare hospital-community partnerships among safety-net hospitals relative to non-safety-net hospitals, and explore whether hospital-community partnerships are associated with reductions in readmission rates.Data sourcesData from four nationwide hospital-level datasets for 2015-2016, including American Hospital Association (AHA) annual survey, Hospital Inpatient Prospective Payment System (IPPS) data, CMS Hospital Compare, and County Health Rankings National (CHRN) data.Study designWe first examined how safety-net hospitals partner with nine different community providers, and how the overall and individual partnership patterns differ from those in non-safety-net hospitals. We then explored their association with 30-day readmission rates by diagnosis and hospital wide.Data collection/extraction methodsWe included 1979 hospitals across 50 US states.Principal findingsSafety-net hospitals were more engaged in hospital-community partnerships, especially with local public health, local governments, social services, nonprofits, and insurance companies, relative to their non-safety-net peers. However, we found that such partnerships were not significantly related to reductions in readmission rates. The findings indicated that merely partnering with various community organizations may not be associated with readmission rate reduction.ConclusionsBefore promoting partnerships with various community organizations for its own sake, further prospective, longitudinal, and evidence-based guidance derived from the study of hospital-community partnerships is needed to make meaningful recommendations aimed at readmission rate reduction in safety-net hospitals.
| S-EPMC7376002 | biostudies-literature
Project description:OBJECTIVES:Prior studies have reported mixed findings about the existence of racial disparities in readmission rates among Medicare Advantage beneficiaries, but these studies used data from one state, focused on black-white disparities, and did not focus on patients discharged to skilled nursing facilities (SNFs). The objective of the study was to characterize racial and ethnic disparities in rates of 30-day rehospitalization directly from SNFs among fee-for-service and Medicare Advantage patients. DESIGN:A cross-sectional study of admissions to SNFs in 2015 was conducted. SETTING:SNFs across the United States. PARTICIPANTS:The sample included 1 500 334 white, 213 848 African American, and 99 781 Hispanic Medicare patients who were admitted to 13 375 SNFs. MEASUREMENTS:The main outcome of interest was readmission, identified as patients sent back to any hospital directly from the SNF within 30?days of admission, as indicated on the Minimum Data Set discharge assessment. RESULTS:Overall readmission rates for fee-for-service patients were 16.7% (95% confidence interval [CI] = 16.7%-16.8%) for whites, 18.8% (95% CI =?18.7%-19.0%) for African Americans, and 17.4% (95% CI =?17.1%-17.7%) for Hispanics. Readmission rates in Medicare Advantage were 14.7% (95% CI =?14.5%-14.8%) for whites, 16.8% (95% CI =?16.6%-17.1%) for African Americans, and 15.3% (95% CI =?14.9%-15.6%) for Hispanics. We also found that African Americans had about 1% higher readmission rates than whites, even when they received care within the same SNF. No statistically significant differences were found in the magnitude of within-SNF racial disparities in Medicare Advantage compared with Medicare fee-for-service. CONCLUSION:We found racial disparities in readmission rates even within the same facility for both Medicare Advantage and fee-for-service beneficiaries. Intervention to reduce disparities in readmission rates, as well as more comprehensive quality measures that incorporate outcomes for Medicare Advantage enrollees, are needed. J Am Geriatr Soc 67:1672-1679, 2019.
| S-EPMC6684399 | biostudies-literature
Project description:ImportanceThe Hospital Readmissions Reduction Program publicly reports and financially penalizes hospitals according to 30-day risk-standardized readmission rates (RSRRs) exclusively among traditional Medicare (TM) beneficiaries but not persons with Medicare Advantage (MA) coverage. Exclusively reporting readmission rates for the TM population may not accurately reflect hospitals' readmission rates for older adults.ObjectiveTo examine how inclusion of MA patients in hospitals' performance is associated with readmission measures and eligibility for financial penalties.Design, setting, and participantsThis is a retrospective cohort study linking the Medicare Provider Analysis and Review file with the Healthcare Effectiveness Data and Information Set at 4070 US acute care hospitals admitting both TM and MA patients. Participants included patients admitted and discharged alive with a diagnosis of acute myocardial infarction (AMI), congestive heart failure (CHF), or pneumonia between 2011 and 2015. Data analyses were conducted between April 1, 2018, and November 20, 2020.ExposuresAdmission to an acute care hospital.Main outcomes and measuresThe outcome was readmission for any reason occurring within 30 days after discharge. Each hospital's 30-day RSRR was computed on the basis of TM, MA, and all patients and estimated changes in hospitals' performance and eligibility for financial penalties after including MA beneficiaries for calculating 30-day RSRRs.ResultsThere were 748 033 TM patients (mean [SD] age, 76.8 [83] years; 360 692 [48.2%] women) and 295 928 MA patients (mean [SD] age, 77.5 [7.9] years; 137 422 [46.4%] women) hospitalized and discharged alive for AMI; 1 327 551 TM patients (mean [SD] age, 81 [8.3] years; 735 855 [55.4%] women) and 457 341 MA patients (mean [SD] age, 79.8 [8.1] years; 243 503 [53.2%] women) for CHF; and 2 017 020 TM patients (mean [SD] age, 80.7 [8.5] years; 1 097 151 [54.4%] women) and 610 790 MA patients (mean [SD] age, 79.6 [8.2] years; 321 350 [52.6%] women) for pneumonia. The 30-day RSRRs for TM and MA patients were correlated (correlation coefficients, 0.31 for AMI, 0.40 for CHF, and 0.41 for pneumonia) and the TM-based RSRR systematically underestimated the RSRR for all Medicare patients for each condition. Of the 2820 hospitals with 25 or more admissions for at least 1 of the outcomes of AMI, CHF, and pneumonia, 635 (23%) had a change in their penalty status for at least 1 of these conditions after including MA data. Changes in hospital performance and penalty status with the inclusion of MA patients were greater for hospitals in the highest quartile of MA admissions.Conclusions and relevanceIn this cohort study, the inclusion of data from MA patients changed the penalty status of a substantial fraction of US hospitals for at least 1 of 3 reported conditions. This suggests that policy makers should consider including all hospital patients, regardless of insurance status, when assessing hospital quality measures.
| S-EPMC7890527 | biostudies-literature
Project description:Safety-net and teaching hospitals are somewhat more likely to be penalized for excess readmissions, but the association of other hospital characteristics with readmission rates is uncertain and may have relevance for hospital-centered interventions.To examine the independent association of 8 hospital characteristics with hospital-wide 30-day risk-standardized readmission rate (RSRR).This is a retrospective cross-sectional multivariable analysis.US hospitals.Centers for Medicare and Medicaid Services specification of hospital-wide RSRR from July 1, 2013 through June 30, 2014 with race and Medicaid dual-eligibility added.We included 6,789,839 admissions to 4474 hospitals of Medicare fee-for-service beneficiaries aged over 64 years. In multivariable analyses, there was regional variation: hospitals in the mid-Atlantic region had the highest RSRRs [0.98 percentage points higher than hospitals in the Mountain region; 95% confidence interval (CI), 0.84-1.12]. For-profit hospitals had an average RSRR 0.38 percentage points (95% CI, 0.24-0.53) higher than public hospitals. Both urban and rural hospitals had higher RSRRs than those in medium metropolitan areas. Hospitals without advanced cardiac surgery capability had an average RSRR 0.27 percentage points (95% CI, 0.18-0.36) higher than those with. The ratio of registered nurses per hospital bed was not associated with RSRR. Variability in RSRRs among hospitals of similar type was much larger than aggregate differences between types of hospitals.Overall, larger, urban, academic facilities had modestly higher RSRRs than smaller, suburban, community hospitals, although there was a wide range of performance. The strong regional effect suggests that local practice patterns are an important influence. Disproportionately high readmission rates at for-profit hospitals may highlight the role of financial incentives favoring utilization.
| S-EPMC5426655 | biostudies-literature
Project description:BackgroundInpatient falls in hospitals are an acknowledged indicator of quality of care. International comparisons could highlight quality improvement potential and enable cross-national learning. Key to fair cross-national comparison is the availability of a risk adjustment model validated in an international context. This study aimed to 1) ascertain that the variables of the inpatient fall risk adjustment model do not interact with country and thus can be used for risk adjustment, 2) compare the risk of falling in hospitals between Switzerland and Austria after risk adjustment.MethodsThe data on inpatient falls from Swiss and Austrian acute care hospitals were collected on a single measurement day in 2017, 2018 and 2019 as part of an international multicentre cross-sectional study. Multilevel logistic regression models were used to screen for interaction effects between the patient-related fall risk factors and the countries. The risks of falling in hospital in Switzerland and in Austria were compared after applying the risk-adjustment model.ResultsData from 176 hospitals and 43,984 patients revealed an inpatient fall rate of 3.4% in Switzerland and 3.9% in Austria. Two of 15 patient-related fall risk variables showed an interaction effect with country: Patients who had fallen in the last 12 months (OR 1.49, 95% CI 1.10-2.01, p = 0.009) or had taken sedatives/psychotropic medication (OR 1.40, 95% CI 1.05-1.87, p = 0.022) had higher odds of falling in Austrian hospitals. Significantly higher odds of falling were observed in Austrian (OR 1.38, 95% CI 1.13-1.68, p = 0.002) compared to Swiss hospitals after applying the risk-adjustment model.ConclusionsAlmost all patient-related fall risk factors in the model are suitable for a risk-adjusted cross-country comparison, as they do not interact with the countries. Further model validation with additional countries is warranted, particularly to assess the interaction of risk factors "fall in the last 12 months" and "sedatives/psychotropic medication intake" with country variable. The study underscores the crucial role of an appropriate risk-adjustment model in ensuring fair international comparisons of inpatient falls, as the risk-adjusted, as opposed to the non-risk-adjusted country comparison, indicated significantly higher odds of falling in Austrian compared to Swiss hospitals.
| S-EPMC10935870 | biostudies-literature
Project description:ObjectivesHospital discharges to post-acute care (PAC) facilities have increased rapidly. This increase may lead to more hospital readmissions from PAC facilities, which are common and poorly understood. We sought to determine the risk factors and timing for hospital readmission from PAC facilities and evaluate the impact of readmission on patient outcomes.DesignRetrospective analysis of Medicare Current Beneficiary Survey (MCBS) from 2003-2009.SettingThe MCBS is a nationally representative survey of beneficiaries matched with claims data.ParticipantsCommunity-dwelling beneficiaries who were hospitalized and discharged to a PAC facility for rehabilitation.Intervention/exposurePotential readmission risk factors included patient demographics, health utilization, active medical conditions at time of PAC admission, and PAC characteristics.MeasurementsHospital readmission during the PAC stay, return to community residence, and all-cause mortality.ResultsOf 3246 acute hospitalizations followed by PAC facility stays, 739 (22.8%) included at least 1 hospital readmission. The strongest risk factors for readmission included impaired functional status (HR 4.78, 95% CI 3.21-7.10), markers of increased acuity such as need for intravenous medications in PAC (1.63, 1.39-1.92), and for-profit PAC ownership (1.43, 1.21-1.69). Readmitted patients had a higher mortality rate at both 30 days (18.9% vs 8.6%, P < .001) and 100 days (39.9% vs 14.5%, P < .001) even after adjusting for age, comorbidities, and prior health care utilization (30 days: OR 2.01, 95% CI 1.60-2.54; 100 days: OR 3.79, 95% CI 3.13-4.59).ConclusionsHospital readmission from PAC facilities is common and associated with a high mortality rate. Readmission risk factors may signify inadequate transitional care processes or a mismatch between patient needs and PAC resources.
| S-EPMC4847128 | biostudies-literature