Post-hospitalization dialysis facility processes of care and hospital readmissions among hemodialysis patients: a retrospective cohort study.
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ABSTRACT: Background
Both dialysis facilities and hospitals are accountable for 30-day hospital readmissions among U.S. hemodialysis patients. We examined the association of post-hospitalization processes of care at hemodialysis facilities with pulmonary edema-related and other readmissions.Methods
In a retrospective cohort comprised of electronic medical record (EMR) data linked with national registry data, we identified unique patient index admissions (n = 1056; 2/1/10-7/31/15) that were followed by ≥3 in-center hemodialysis sessions within 10 days, among patients treated at 19 Southeastern dialysis facilities. Indicators of processes of care were defined as present vs. absent in the dialysis facility EMR. Readmissions were defined as admissions within 30 days of the index discharge; pulmonary edema-related vs. other readmissions defined by discharge codes for pulmonary edema, fluid overload, and/or congestive heart failure. Multinomial logistic regression to estimate odds ratios (ORs) for pulmonary edema-related and other vs. no readmissions.Results
Overall, 17.7% of patients were readmitted, and 8.0% had pulmonary edema-related readmissions (44.9% of all readmissions). Documentation of the index admission (OR = 2.03, 95% CI 1.07-3.85), congestive heart failure (OR = 1.87, 95% CI 1.07-3.27), and home medications stopped (OR = 1.81, 95% CI 1.08-3.05) or changed (OR = 1.69, 95% CI 1.06-2.70) in the EMR post-hospitalization were all associated with higher risk of pulmonary edema-related vs. no readmission; lower post-dialysis weight (by ≥0.5 kg) after vs. before hospitalization was associated with 40% lower risk (OR = 0.60, 95% CI 0.37-0.96).Conclusions
Our results suggest that some interventions performed at the dialysis facility in the post-hospitalization period may be associated with reduced readmission risk, while others may provide a potential existing means of identifying patients at higher risk for readmissions, to whom such interventions could be efficiently targeted.
SUBMITTER: Plantinga LC
PROVIDER: S-EPMC6069998 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Hospitalization for cardiovascular disease (CVD) is common among patients receiving maintenance dialysis, but patterns of readmissions following cardiovascular events are underexplored. METHODS AND RESULTS:In this retrospective analysis of prevalent, Medicare-eligible patients receiving dialysis in 2012-2013, all live-discharge hospitalizations attributed to CVD were ascertained. Rates of all-cause, CVD-related, and non-CVD-related readmissions and death in the ensuing 10 and 30 days were calculated. Multinomial logistic modeling was used to assess the relationship between potential explanatory factors and outcomes of interest. Among 142 210 analyzed hospitalizations, mean age at time of index CVD hospitalization was 64.9±14.1 years; 50.4% of index hospitalizations were for women, and 41.4% were for white patients. Fully 15.6% and 34.2% of CVD hospitalizations resulted in readmission within 10 and 30 days, respectively; less than half of readmissions were CVD related (42.5%, 10 days; 43.1%, 30 days). Death within 30 days, regardless of readmission, occurred after 4.5% of index hospitalizations; 51.2% were attributed to CVD. Compared with ages 65 to 69 years, younger age tended to be associated with increased readmission risk (adjusted relative risk for ages 18-44 years: 1.55; 95% confidence interval, 1.48-1.63). Readmission risk did not differ between white and black patients, but risk of death without readmission was markedly lower for black patients (relative risk: 0.60; 95% confidence interval, 0.55-0.67). CONCLUSIONS:Roughly 1 in 3 CVD hospitalizations resulted in 30-day readmission; nearly 1 in 20 was followed by death within 30 days. Risk of death without readmission was higher for white than black patients, despite no difference in risk of readmission.
| S-EPMC5850182 | biostudies-literature
Project description:ImportanceMergers and acquisitions among health care institutions are increasingly common, and dialysis markets have undergone several decades of mergers and acquisitions.ObjectiveTo examine the outcomes of hemodialysis facility acquisitions independent of associated changes in market competition resulting from acquisitions.Design, setting, and participantsCohort study using difference-in-differences (DID) analyses to compare changes in health outcomes over time among in-center US dialysis facilities that were acquired by a hemodialysis chain with facilities located nearby but not acquired. Multivariable Cox proportional hazards regression models and negative binomial models with predicted marginal effects were developed to examine health outcomes, controlling for patient, facility, and geographic characteristics. All facility ownership types were examined together and stratified analyses were conducted of facilities that were independently owned and chain owned prior to acquisitions. The study was conducted from January 2001 to September 2015; 174 905 patients starting in-center dialysis in the 3 years before and following dialysis facility acquisitions were included. Data were analyzed from March 2017 to December 2018.ExposuresAcquisition by a hemodialysis chain.Main outcomes and measuresTwelve-month hazard of death and hospital days per patient-year were the primary outcomes.ResultsOf the 174 905 patients included in the study, 79 705 were women (45.6%), 24 409 (14.0%) were of Hispanic ethnicity, 61 815 (35.3%) were black, 105 272 (60.2%) were white, and 1247 (0.7%) were Native American. Mean (SD) age was 65 (15) years. Before acquisitions, adjusted mortality and hospitalization rates were 10% (95% CI, -16% to -5%) and 2.9 days per patient-year (95% CI, -3.8 to -2.0) lower, respectively, at independently owned facilities that were acquired compared with those that were not acquired, while hospitalization rates were 0.7 days (95% CI, -1.2 to -2.0) lower at chain-owned facilities that were acquired compared with those that were not acquired. In stratified analyses of independently owned facilities, mortality decreases were smaller at acquired (-8.4%; 95% CI, -14% to -25%) vs nonacquired (-20.3%; 95% CI, -25.8% to -14.3%) facilities (DID P < .001). Similarly, hospitalization rates did not change at acquired facilities and decreased by 2.6 days per patient-year (95% CI, -3.6 to -1.7 days) at nonacquired facilities (DID P < .001). Acquisitions were not associated with changes in health outcomes at chain-owned facilities. Slower reductions in mortality and hospitalization rates at independently owned facilities contributed to significant differences in hospitalizations (-2.0 days; 95% CI, -2.5 to -1.6, at nonacquired vs 0.9 days; 95% CI, -1.3 to -0.5, at acquired facilities; DID, P < .001) across all ownership types but not mortality (DID, P = .28) with regard to acquisitions.Conclusions and relevanceAcquisition of independently owned dialysis facilities by larger dialysis organizations was associated with slower decreases in mortality and hospitalization rates, as nonacquired facilities appeared to experience more rapid improvements in outcomes over time.
| S-EPMC6537810 | biostudies-literature
Project description:BackgroundTo assure and improve the quality and safety of care provided by dialysis facilities, federal oversight has been conducted through periodic survey assessment. However, with the growing number of individuals living with ESRD and dialysis facilities, state survey agencies have faced challenges in time and resources to complete survey activities. Therefore, the survey process ('Basic Survey' used prior to 2013) was redesigned in order to develop a more efficient process ('Core Survey' newly implemented since 2013). The purpose of this analysis was to evaluate and compare dialysis facility survey outcomes between the Core and Basic Survey processes, using a causal inference technique. The survey outcomes included condition-level citations, total citations (condition- and standard-level), and citation rate per survey-hour.MethodsFor comparisons of non-randomly assigned survey types, propensity score matching was used. Data were drawn from CMS' Quality Improvement Evaluation System (QIES) database from January 1, 2013 through July 31, 2014. Covariates available included survey type, facility characteristics (state, urban, practices catheter reuse, dialysis modalities offered, number of patients, mortality, hospitalization, infection) and survey-related characteristics (number of surveyors, time since last survey).ResultsCompared to the Basic Survey, the Core Survey identified 10% more total citations (P = 0.001) and identified condition-level citations more frequently, although the latter finding did not reach statistical significance. These findings suggest an increase of 10% in citation rate (i.e. ratio between citations and survey time) with the Core survey process (P = 0.002).ConclusionsGreater efficiency has implications for attenuating the time-intensive burden of the state survey process, and improving the safety and quality of care provided by dialysis facilities.
| S-EPMC6485704 | biostudies-literature
Project description:BackgroundThirty-day readmissions are common in patients receiving hemodialysis and costly to Medicare. Because patients on hemodialysis have a high background hospitalization rate, 30-day readmissions might be less likely related to the index hospitalization than in patients with other conditions.MethodsIn adults with Medicare receiving hemodialysis in the United States, we used multinomial logistic regression to evaluate whether prior hospitalization burden was associated with increased 30-day readmissions unrelated to index hospitalizations with a discharge date from January 1, 2013 to December 31, 2014. We categorized a hospitalization, 30-day readmission pair as "related" if the principal diagnoses came from the same organ system.ResultsThe adjusted probability of unrelated 30-day readmission after any index hospitalization was 19.1% (95% confidence interval [95% CI] 18.9% to 19.3%), 22.6% (95% CI, 22.4% to 22.8%), and 31.2% (95% CI, 30.8% to 31.5%) in patients with 0-1, 2-4, and ?5 hospitalizations, respectively. Cardiovascular index hospitalizations had the highest adjusted probability of related 30-day readmission: 10.4% (95% CI, 10.2% to 10.7%), 13.6% (95% CI, 13.4% to 13.9%), and 20.8% (95% CI, 20.2% to 21.4%), respectively. Renal index hospitalizations had the lowest adjusted probability of related 30-day readmission: 2.0% (95% CI, 1.8% to 2.3%), 3.9% (95% CI, 3.4% to 4.4%), and 5.1% (95% CI, 4.3% to 5.9%), respectively.ConclusionsHigh prior hospitalization burden increases the likelihood that patients receiving hemodialysis experience a 30-day readmission unrelated to the index hospitalization. Health care payers such as Medicare should consider incorporating clinical relatedness into 30-day readmission quality measures.
| S-EPMC6362625 | biostudies-literature
Project description:A focus of health care reform has been on reducing 30-day hospital readmissions. Patients with ESRD are at high risk for hospital readmission. It is unknown whether more monitoring by outpatient providers can reduce hospital readmissions in patients receiving hemodialysis. In nationally representative cohorts of patients in the United States receiving in-center hemodialysis between 2004 and 2009, we used a quasi-experimental (instrumental variable) approach to assess the relationship between frequency of visits to patients receiving hemodialysis following hospital discharge and the probability of rehospitalization. We then used a multivariable regression model and published hospitalization data to estimate the cost savings and number of hospitalizations that could be prevented annually with additional provider visits to patients in the month following hospitalization. In the main cohort (n=26,613), one additional provider visit in the month following hospital discharge was estimated to reduce the absolute probability of 30-day hospital readmission by 3.5% (95% confidence interval, 1.6% to 5.3%). The reduction in 30-day hospital readmission ranged from 0.5% to 4.9% in an additional four cohorts tested, depending on population density around facilities, facility profit status, and patient Medicaid eligibility. At current Medicare reimbursement rates, the effort to visit patients one additional time in the month following hospital discharge could lead to 31,370 fewer hospitalizations per year, and $240 million per year saved. In conclusion, more frequent physician visits following hospital discharge are estimated to reduce rehospitalizations in patients undergoing hemodialysis. Incentives for closer outpatient monitoring following hospital discharge could lead to substantial cost savings.
| S-EPMC4147977 | biostudies-literature
Project description:Rationale & objectiveCompared to the original nursing home status (any nursing home stay in the previous calendar year), new nursing home status variables were developed to improve the risk adjustment of Standardized Mortality/Hospitalization Ratio (SMR/SHR) models used in public reporting of dialysis quality of care, such as the Annual Dialysis Facility Report.Study designRetrospective observational study.Setting & participants625,040 US maintenance dialysis patients with >90 kidney failure days in 2019.PredictorsNursing home status variables; patient characteristics; comorbid conditions.OutcomesMortality/hospitalization.Analytical approachWe assigned patients and patient times (SMR/SHR model) to one of 3 mutually exclusive categories: long-term care (≥90 days), short-term care (1-89 days), or non-nursing home, based on nursing home stay during the previous 365 days from the first day of the time period at risk. Nursing home status was derived from the Nursing Home Minimum Data Set. Comparisons of hazard ratios from adjusted models, facility SMR/SHR performance, and model C-statistics between the original/new models were performed.ResultsSMR's hazard ratio of original nursing home status (2.09) was lower than both ratios of short-term care (2.38) and long-term care (2.43), whereas SHR's hazard ratio of original nursing home status (1.10) was between the ratios of long-term care (1.01) and short-term care (1.20). There was a difference in hazard ratios between short-term care and long-term care for both measures. Small percentages of facilities changed performance categories: 0.7% for SMR and 0.4% for SHR. The SMR C-statistic improved whereas the SHR C-statistic was relatively unchanged.LimitationsLimited capture of subacute rehabilitation stays in the nursing home by using a 90-day cutoff for short-term care and long-term care; unable to draw causal inference about nursing home care.ConclusionsUse of a nursing home metric that effectively separates short-term from long-term nursing home utilization results in more meaningful risk adjustment that generally comports with Medicare payment policy, potentially resulting in more interpretable results for dialysis stakeholders.
| S-EPMC9879984 | biostudies-literature
Project description:BackgroundThe extension of the interdialytic interval due to due to dialysis session non-attendance varies according to which session of the week the patient misses. The impact of this on subsequent hospitalization and mortality is unknown.MethodsThe ARO cohort study prospectively collected data from hemodialysis patients across 15 European countries on demography, comorbidity, laboratory, hospitalisation, mortality and individual hemodialysis sessions from 2007 to 2014. Event rates for death and hospitalisation according to dialysis day of the week were calculated for patients who attended the three previous scheduled hemodialysis sessions, who then on the next scheduled dialysis day either attended or did not attend. The hazard ratio for these events following non-attendance for the first compared to the second dialysis session of the week was estimated using Cox proportional hazards model adjusted for patient demographics.Results3.8 million hemodialysis sessions in 9397 patients were analysed. The non-attendance rates for Monday/Wednesday/Friday sessions were 0.8, 0.9% & 1.4% respectively, and for Tuesday/Thursday/Saturday sessions were 0.6, 1.0% & 1.2% respectively. Compared to those who attended, for the 48-72 h between non-attendance and the next scheduled haemodialysis session, mortality significantly increased from 4.86 to 51.9/100 pt-yrs and hospitalisation increased from 0.58 to 2.1/yr. As time from the two-day break increased, the risk associated with non-attendance lessened: compared to missing the second hemodialysis session, missing the first session had a hazard ratio for mortality of 2.04 (95% CI 1.27-3.29), and for hospitalisation 1.78 (95% CI 1.29-2.47). In patients who attended their scheduled dialysis session and the three preceding, after the two-day break there were absolute increases in mortality (8.3 vs. 4.9/100 pt-yrs) and hospitalisation (1.0 vs. 0.6/yr for the rest of the week) comparable to previous studies.ConclusionsIn addition to hospitalisation and mortality increases seen after the two-day break, additional harm may be manifested in the greater increases in mortality and hospitalisation observed after non-attendance for the first hemodialysis session after the two-day break compared to missing other sessions.
| S-EPMC7285433 | biostudies-literature
Project description:Rationale & objectiveThe coronavirus disease 2019 (COVID-19) pandemic has had a profound impact on hospitalizations in general and on dialysis patients in particular. This study modeled the impact of COVID-19 on hospitalizations of dialysis patients in 2020.Study designRetrospective cohort study.Setting & participantsMedicare patients on dialysis in calendar year 2020.PredictorsCOVID-19 status was divided into 4 stages: COVID1 (first 10 days after initial diagnosis), COVID2 (extends until the Post-COVID stage), Post-COVID (after 21 days with no COVID-19 diagnosis), and Late-COVID (begins after a hospitalization with a COVID-19 diagnosis); demographic and clinical characteristics; and dialysis facilities.OutcomeThe sequence of hospitalization events.Analytical approachA proportional rate model with a nonparametric baseline rate function of calendar time on the study population.ResultsA total of 509,609 patients were included in the study, 63,521 were observed to have a SARS-CoV-2 infection, 34,375 became Post-COVID, and 1,900 became Late-COVID. Compared with No-COVID, all 4 stages had significantly greater adjusted risks of hospitalizations with relative rates of 18.50 (95% CI, 18.19-18.81) for COVID1, 2.03 (95% CI, 1.99-2.08) for COVID2, 1.37 (95% CI, 1.35-1.40) for Post-COVID, and 2.00 (95% CI, 1.89-2.11) for Late-COVID.LimitationsFor Medicare Advantage patients, we only had inpatient claim information. The analysis was based on data from the year 2020, and the effects may have changed due to vaccinations, new treatments, and new variants. The COVID-19 effects may be somewhat overestimated due to missing information on patients with few or no symptoms and possible delay in COVID-19 diagnosis.ConclusionsWe discovered a marked time dependence in the effect of COVID-19 on hospitalization of dialysis patients, beginning with an extremely high risk for a relatively short period, with more moderate but continuing elevated risks later, and never returning to the No-COVID level.
| S-EPMC9398821 | biostudies-literature
Project description:Background and objectivesAssisted peritoneal dialysis is a treatment option for individuals with barriers to self-care who wish to receive home dialysis, but previous research suggests that this treatment modality is associated with a higher rate of hospitalization. The objective of our study was to determine whether assisted peritoneal dialysis has a different rate of hospital days compared to in-center hemodialysis.Design, setting, participants, & measurementsWe conducted a multicenter, retrospective cohort study by linking a quality assurance dataset to administrative health data in Ontario, Canada. Subjects were accrued between January 1, 2004 and July 9, 2013. Individuals were grouped into assisted peritoneal dialysis (family or home care assisted) or in-center hemodialysis on the basis of their first outpatient dialysis modality. Inverse probability of treatment weighting using a propensity score was used to create a sample in which the baseline covariates were well balanced.ResultsThe study included 872 patients in the in-center hemodialysis group and 203 patients in the assisted peritoneal dialysis group. Using an intention to treat approach, patients on assisted peritoneal dialysis had a similar hospitalization rate of 11.1 d/yr (95% confidence interval, 9.4 to 13.0) compared with 12.9 d/yr (95% confidence interval, 10.3 to 16.1) in the hemodialysis group (P=0.19). Patients on assisted peritoneal dialysis were more likely to be hospitalized for dialysis-related reasons (admitted for 2.4 d/yr [95% confidence interval, 1.8 to 3.2] compared with 1.6 d/yr [95% confidence interval, 1.1 to 2.3] in the hemodialysis group; P=0.04). This difference was partly explained by more hospital days because of peritonitis. Modality switching was associated with high rates of hospital days per year.ConclusionsAssisted peritoneal dialysis was associated with similar rates of all-cause hospitalization compared with in-center hemodialysis. Patients on assisted peritoneal dialysis who experienced peritonitis and technique failure had high rates of hospitalization.
| S-EPMC5012487 | biostudies-literature
Project description:Rationale & objectiveSuboptimal care coordination between dialysis facilities and hospitals is an important driver of 30-day hospital readmissions among patients receiving dialysis. We examined whether the introduction of web-based communications platform ("DialysisConnect") was associated with reduced hospital readmissions.Study designPilot pre-post study.Setting & participantsA total of 4,994 index admissions at a single hospital (representing 2,419 patients receiving dialysis) during the study period (January 1, 2019-May 31, 2021).InterventionDialysisConnect was available to providers at the hospital and 4 affiliated dialysis facilities (=intervention facilities) during the pilot period (November 1, 2020-May 31, 2021).OutcomesThe primary outcome was 30-day readmission; secondary outcomes included 30-day emergency department visits and observation stays. Interrupted time series and linear models with generalized estimating equations were used to assess pilot versus prepilot differences in outcomes; difference-in-difference analyses were performed to compare these differences between intervention versus control facilities. Sensitivity analyses included a third, prepilot/COVID-19 period (March 1, 2020-October 31, 2020).ResultsThere was no statistically significant difference in the monthly trends in the 30-day readmissions pilot versus prepilot periods (-0.60 vs -0.13, P = 0.85) for intervention facility admissions; the difference-in-difference estimate was also not statistically significant (0.54 percentage points, P = 0.83). Similar analyses including the prepilot/COVID-19 period showed that, despite a substantial drop in admissions at the start of the pandemic, there were no statistically significant differences across the 3 periods. The age-, sex-, race-, and comorbid condition-adjusted, absolute pilot versus prepilot difference in readmissions rate was 1.8% (-3.7% to 7.3%); similar results were found for other outcomes.LimitationsPotential loss to follow-up and pandemic effects.ConclusionsIn this pilot, the introduction of DialysisConnect was not associated with reduced hospital readmissions. Tailored care coordination solutions should be further explored in future, multisite studies to improve the communications gap between dialysis facilities and hospitals.
| S-EPMC9372774 | biostudies-literature