Hospital Use of Observation Stays: Cross-sectional Study of the Impact on Readmission Rates.
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SUBMITTER: Venkatesh AK
PROVIDER: S-EPMC5850934 | biostudies-literature | 2016 Dec
REPOSITORIES: biostudies-literature
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Hospital Use of Observation Stays: Cross-sectional Study of the Impact on Readmission Rates.
Venkatesh Arjun K AK Wang Changqin C Ross Joseph S JS Altaf Faseeha K FK Suter Lisa G LG Vellanky Smitha S Grady Jacqueline N JN Bernheim Susannah M SM
Medical care 20161201 12
<h4>Background</h4>The Centers for Medicare and Medicaid Services publicly reports hospital risk-standardized readmission rates (RSRRs) as a measure of quality and performance; mischaracterizations may occur because observation stays are not captured by current measures.<h4>Objectives</h4>To describe variation in hospital use of observation stays, the relationship between hospitals observation stay use and RSRRs.<h4>Materials and methods</h4>Cross-sectional analysis of Medicare fee-for-service b ...[more]
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Project description:ObjectiveTo examine the association of hospital volume (a marker of quality of care) with hospital readmission rates.DesignRetrospective cross-sectional study.Setting4651 US acute care hospitals.Study data6,916,644 adult discharges, excluding patients receiving psychiatric or medical cancer treatment.Main outcome measuresWe used Medicare fee-for-service data from 1 July 2011 to 30 June 2012 to calculate observed-to-expected, unplanned, 30 day, standardized readmission rates for hospitals and for specialty cohorts medicine, surgery/gynecology, cardiorespiratory, cardiovascular, and neurology. We assessed the association of hospital volume by quintiles with 30 day, standardized readmission rates, with and without adjustment for hospital characteristics (safety net status, teaching status, geographic region, urban/rural status, nurse to bed ratio, ownership, and cardiac procedure capability. We also examined associations with the composite outcome of 30 day, standardized readmission or mortality rates.ResultsMean 30 day, standardized readmission rate among the fifth of hospitals with the lowest volume was 14.7 (standard deviation 5.3) compared with 15.9 (1.7) among the fifth of hospitals with the highest volume (P<0.001). We observed the same pattern of lower readmission rates in the lowest versus highest volume hospitals in the specialty cohorts for medicine (16.6 v 17.4, P<0.001), cardiorespiratory (18.5 v 20.5, P<0.001), and neurology (13.2 v 14.0, p=0.01) cohorts; the cardiovascular cohort, however, had an inverse association (14.6 v 13.7, P<0.001). These associations remained after adjustment for hospital characteristics except in the cardiovascular cohort, which became non-significant, and the surgery/gynecology cohort, in which the lowest volume fifth of hospitals had significantly higher standardized readmission rates than the highest volume fifth (difference 0.63 percentage points (95% confidence interval 0.10 to 1.17), P=0.02). Mean 30 day, standardized mortality or readmission rate was not significantly different between highest and lowest volume fifths (20.4 v 20.2, P=0.19) and was highest in the middle fifth of hospitals (range 20.6-20.8).ConclusionsStandardized readmission rates are lowest in the lowest volume hospitals-opposite from the typical association of greater hospital volume with better outcomes. This association was independent of hospital characteristics and was only partially attenuated by examining mortality and readmission together. Our findings suggest that readmissions are associated with different aspects of care than mortality or complications.
| S-EPMC4353286 | biostudies-literature
Project description:Background/objectivesObservation stays are increasingly common for older adults, yet little is known about the extent to which they are being used as the Centers for Medicare and Medicaid Services (CMS) originally intended for unscheduled or acute problems and whether different types of services are reflected in current billing practices.DesignObservational cohort study.Setting/participantsA total of 867,165 qualifying observation stays identified from 451,408 patients using Medicare fee-for-service claims data from a nationally representative 20% beneficiary sample between January 1, 2014, and November 30, 2014.MeasurementsUsing descriptive and multivariable logistic model analytic approaches, we evaluated the patient, stay, and hospital characteristics associated with the most common billing practice for observation stays (charge revenue center 0761 exclusively) vs all other practices.ResultsSixty-three percent of observation stays were billed exclusively under the 0761 revenue center and were more likely to be for preplanned chronic conditions consisting of short-term treatments (eg, chemotherapy, radiation therapy, wound care, paracentesis, epidural spinal injection). These stays appeared to be used for recurrent single-day visits, given their strong association with prior visits and a high rate of reobservation (41.4%), with frequent return stays appearing in a 7-day pattern.ConclusionNearly two-thirds of observation stays are billed using only the 0761 revenue code and appear to be for prescheduled, repeated treatments-differing substantially from CMS' explicitly stated purpose as a form of care used while a healthcare provider determines whether a patient presenting for unscheduled or acute conditions requires inpatient hospital admission or can be safely discharged. Guidance is needed from CMS to clarify the appropriate role of observation stays, with discussion as to whether episodic single-day, planned treatment for chronic conditions not originating in the emergency department should be billed as observation stays or placed under another mechanism. Subsequent research is needed to understand how the current use of observation stays impact patient out-of-pocket costs. J Am Geriatr Soc 68:1568-1572, 2020.
| S-EPMC7363536 | biostudies-literature
Project description:BACKGROUND:Short hospital stays may represent opportunities to avert unnecessary admissions or expedite inpatient care. To inform the design of interventions that target patients with potentially avoidable hospital admissions or brief stays, we examined the patient, physician and situational characteristics associated with short stays among patients admitted to general internal medicine wards and describe the use of hospital resources by these patients. METHODS:This was a multicentre cross-sectional study conducted between Apr. 1, 2012, and Mar. 31, 2015, at 5 teaching hospitals in Toronto. We included all general internal medicine admissions through the emergency department. We examined patient, physician and situational predictors of a short hospital stay, which was defined as the patient's being discharged home alive in 2 possible time windows: less than 24 hours, or 72 hours or less. RESULTS:The final study sample included 56 055 admissions and 37 700 unique patients. Patients discharged in less than 24 hours and in 72 hours or less accounted for 4245 (7.6%) and 13 442 (31.6%) admissions, respectively. After we controlled for patient factors, patients of female physicians were less likely than those of male physicians to have stays lasting less than 24 hours (adjusted odds ratio [OR] 0.80, 95% confidence interval [CI] 0.74-0.86) or 72 hours or less (adjusted OR 0.82, 95% CI 0.79-0.86). Patients admitted at night or on a weekday were significantly more likely than those admitted at other times to have stays lasting less than 24 hours (night: adjusted OR 2.73, 95% CI 2.44-3.06; weekday: adjusted OR 1.26, 95% CI 1.17-1.36) or 72 hours or less (night: adjusted OR 1.29, 95% CI 1.22-1.37, weekday: adjusted OR 1.05, 95% CI 1.01-1.10). Among stays lasting less than 24 hours and 24-72 hours, intravenously administered medications were ordered for 2788 (65.7%) and 10 722 (79.8%) patients, respectively, and computed tomography scans were performed for 1561 (36.8%) and 5354 (39.1%) patients, respectively. INTERPRETATION:Short general internal medicine hospital stays were common and were associated with patient, physician and situational factors. Interventions to avert hospital admission or reduce length of stay may be more effective if they are accessible outside typical working hours and provide access to intravenous therapy and radiological investigations.
| S-EPMC6349563 | biostudies-literature
Project description:BackgroundPatients are treated using observation services (OS) when their care needs exceed standard outpatient care (i.e., clinic or emergency department) but do not qualify for admission. Medicare and other private payers seek to limit this care setting to 48 hours.Data source/study settingHealthcare Cost and Utilization Project data from 10 states and data collected from two additional states for 2009.Study designBivariate analyses and hierarchical linear modeling were used to examine patient- and hospital-level predictors of OS stays exceeding 48 (and 72) hours (prolonged OS). Hierarchical models were used to examine the additional cost associated with longer OS stays.Principal findingsOf the 696,732 patient OS stays, 8.8 percent were for visits exceeding 48 hours. Having Medicaid or no insurance, a condition associated with no OS treatment protocol, and being discharged to skilled nursing were associated with having a prolonged OS stay. Among Medicare patients, the mean charge for OS stays was $10,373. OS visits of 48-72 hours were associated with a 42 percent increase in costs; visits exceeding 72 hours were associated with a 61 percent increase in costs.ConclusionPatient cost sharing for most OS stays of less than 24 hours is lower than the Medicare inpatient deductible. However, prolonged OS stays potentially increase this cost sharing.
| S-EPMC4231577 | biostudies-literature
Project description:ObjectiveTo examine the relationship between community factors and hospital readmission rates.Data sources/study settingWe examined all hospitals with publicly reported 30-day readmission rates for patients discharged during July 1, 2007, to June 30, 2010, with acute myocardial infarction (AMI), heart failure (HF), or pneumonia (PN). We linked these to publicly available county data from the Area Resource File, the Census, Nursing Home Compare, and the Neilsen PopFacts datasets.Study designWe used hierarchical linear models to assess the effect of county demographic, access to care, and nursing home quality characteristics on the pooled 30-day risk-standardized readmission rate.Data collection/extraction methodsNot applicable.Principal findingsThe study sample included 4,073 hospitals. Fifty-eight percent of national variation in hospital readmission rates was explained by the county in which the hospital was located. In multivariable analysis, a number of county characteristics were found to be independently associated with higher readmission rates, the strongest associations being for measures of access to care. These county characteristics explained almost half of the total variation across counties.ConclusionsCommunity factors, as measured by county characteristics, explain a substantial amount of variation in hospital readmission rates.
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Project description:ImportanceThe Affordable Care Act has led to US national reductions in hospital 30-day readmission rates for heart failure (HF), acute myocardial infarction (AMI), and pneumonia. Whether readmission reductions have had the unintended consequence of increasing mortality after hospitalization is unknown.ObjectiveTo examine the correlation of paired trends in hospital 30-day readmission rates and hospital 30-day mortality rates after discharge.Design, setting, and participantsRetrospective study of Medicare fee-for-service beneficiaries aged 65 years or older hospitalized with HF, AMI, or pneumonia from January 1, 2008, through December 31, 2014.ExposureThirty-day risk-adjusted readmission rate (RARR).Main outcomes and measuresThirty-day RARRs and 30-day risk-adjusted mortality rates (RAMRs) after discharge were calculated for each condition in each month at each hospital in 2008 through 2014. Monthly trends in each hospital's 30-day RARRs and 30-day RAMRs after discharge were examined for each condition. The weighted Pearson correlation coefficient was calculated for hospitals' paired monthly trends in 30-day RARRs and 30-day RAMRs after discharge for each condition.ResultsIn 2008 through 2014, 2 962 554 hospitalizations for HF, 1 229 939 for AMI, and 2 544 530 for pneumonia were identified at 5016, 4772, and 5057 hospitals, respectively. In January 2008, mean hospital 30-day RARRs and 30-day RAMRs after discharge were 24.6% and 8.4% for HF, 19.3% and 7.6% for AMI, and 18.3% and 8.5% for pneumonia. Hospital 30-day RARRs declined in the aggregate across hospitals from 2008 through 2014; monthly changes in RARRs were -0.053% (95% CI, -0.055% to -0.051%) for HF, -0.044% (95% CI, -0.047% to -0.041%) for AMI, and -0.033% (95% CI, -0.035% to -0.031%) for pneumonia. In contrast, monthly aggregate changes across hospitals in hospital 30-day RAMRs after discharge varied by condition: HF, 0.008% (95% CI, 0.007% to 0.010%); AMI, -0.003% (95% CI, -0.005% to -0.001%); and pneumonia, 0.001% (95% CI, -0.001% to 0.003%). However, correlation coefficients in hospitals' paired monthly changes in 30-day RARRs and 30-day RAMRs after discharge were weakly positive: HF, 0.066 (95% CI, 0.036 to 0.096); AMI, 0.067 (95% CI, 0.027 to 0.106); and pneumonia, 0.108 (95% CI, 0.079 to 0.137). Findings were similar in secondary analyses, including with alternate definitions of hospital mortality.Conclusions and relevanceAmong Medicare fee-for-service beneficiaries hospitalized for heart failure, acute myocardial infarction, or pneumonia, reductions in hospital 30-day readmission rates were weakly but significantly correlated with reductions in hospital 30-day mortality rates after discharge. These findings do not support increasing postdischarge mortality related to reducing hospital readmissions.
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Project description:BACKGROUND:Whether types of hospitals with high readmission rates also have high overall postdischarge acute care utilization (including emergency department and observation care) is unknown. DESIGN:Cross-sectional analysis. SUBJECTS:Nonfederal United States acute care hospitals. MEASURES:Using methodology established by the Centers for Medicare & Medicaid Services, we calculated each hospital's "excess days in acute care" for fee-for-service (FFS) Medicare beneficiaries aged over 65 years discharged after hospitalization for acute myocardial infarction, heart failure (HF), or pneumonia, representing the mean difference between predicted and expected total days of acute care utilization in the 30 days following hospital discharge, per 100 discharges. We assessed the multivariable association of 8 hospital characteristics with excess days in acute care and the proportion of hospitals with each characteristic that were statistical outliers (95% credible interval estimate does not include 0). RESULTS:We included 2184 hospitals for acute myocardial infarction [228 (10.4%) better than expected, 549 (25.1%) worse than expected], 3720 hospitals for HF [484 (13.0%) better and 840 (22.6%) worse], and 4195 hospitals for pneumonia [673 (16.0%) better, 1005 (24.0%) worse]. Results for all conditions were similar. Worse than expected outliers for pneumonia included: 18.8% of safety net hospitals versus 26.1% of nonsafety net hospitals; 16.7% of public hospitals versus 33.1% of for-profit hospitals; 19.5% of nonteaching hospitals versus 52.2% of major teaching hospitals; 7.9% of rural hospitals versus 42.1% of large urban hospitals; 5.9% of hospitals with 24-<50 beds versus 58% of hospitals with >500 beds; and 29.0% of hospitals with nurse-to-bed ratios >1.0-1.5 versus 21.7% of hospitals with ratios >2.0. CONCLUSIONS:Including emergency department and observation stays in measures of postdischarge utilization produces similar results as measuring only readmissions in that major teaching, urban and for-profit hospitals still perform disproportionately poorly versus nonteaching or public hospitals. However, it enables identification of more outliers and a more granular assessment of the association of hospital factors and outcomes.
| S-EPMC6170884 | 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:Medicare penalizes hospitals with higher than expected readmission rates by up to 3% of annual inpatient payments. Expected rates are adjusted only for patients' age, sex, discharge diagnosis, and recent diagnoses.To assess the extent to which a comprehensive set of patient characteristics accounts for differences in hospital readmission rates.Using survey data from the nationally representative Health and Retirement Study (HRS) and linked Medicare claims for HRS participants enrolled in Medicare who were hospitalized from 2009 to 2012 (n = 8067 admissions), we assessed 29 patient characteristics from survey data and claims as potential predictors of 30-day readmission when added to standard Medicare adjustments of hospital readmission rates. We then compared the distribution of these characteristics between participants admitted to hospitals with higher vs lower hospital-wide readmission rates reported by Medicare. Finally, we estimated differences in the probability of readmission between these groups of participants before vs after adjusting for the additional patient characteristics.All-cause readmission within 30 days of discharge.Of the additional 29 patient characteristics assessed, 22 significantly predicted readmission beyond standard adjustments, and 17 of these were distributed differently between hospitals in the highest vs lowest quintiles of publicly reported hospital-wide readmission rates (P ? .04 for all comparisons). Almost all of these differences (16 of 17) indicated that participants admitted to hospitals in the highest quintile of readmission rates were more likely to have characteristics that were associated with a higher probability of readmission. The difference in the probability of readmission between participants admitted to hospitals in the highest vs lowest quintile of hospital-wide readmission rates was reduced by 48% from 4.41 percentage points with standard adjustments used by Medicare to 2.29 percentage points after adjustment for all patient characteristics assessed (reduction in difference: -2.12; 95% CI, -3.33 to -0.67; P =?.003).Patient characteristics not included in Medicare's current risk-adjustment methods explained much of the difference in readmission risk between patients admitted to hospitals with higher vs lower readmission rates. Hospitals with high readmission rates may be penalized to a large extent based on the patients they serve.
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Project description:Addressing social determinants of health may help hospitals improve population health and outcomes that are tied to financial incentives, such as readmission rates. Whether this strategy is effective remains unknown. The authors measure the association between nonprofit hospital spending on their community's social needs and Medicare readmission rates. This is a retrospective cohort study (July 2013 to June 2014) that combines Internal Revenue Service tax reports of community benefit spending by private, acute care, nonprofit hospitals with Medicare readmissions data for residents of their surrounding community, the hospital's zip code. Total community benefit spending and 2 of the largest subsets of spending-health care-related and community-directed spending-were measured and normalized as the proportion of each hospital's total expenditure. Associations between quintiles of community benefit spending and Medicare readmission rates were measured using discharge-level multivariate linear regression, adjusting for patient, hospital, community characteristics, and local public health department spending. The sample consisted of 1405 nonprofit hospitals with 341,913 discharges. Associations between readmission rates and total community benefit spending and the health care-related subset were not statistically significant. Discharges from hospitals in the upper quintiles of community-directed spending were associated with lower readmission rates by 0.82 to 1.21 absolute percentage points (P?=?0.01 to <0.001) compared to the lowest quintile. The magnitude of associations between community-directed spending and readmissions was larger for preventable readmissions and smaller when including beneficiaries beyond the hospital's zip code. These associations suggest that community-directed spending may be associated with better health care outcomes.
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