Optimal surgeon and hospital volume thresholds to reduce mortality and length of stay for CABG.
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ABSTRACT: Objective
We used nationwide population-based data to identify optimal hospital and surgeon volume thresholds and to discover the effects of these volume thresholds on operative mortality and length of stay (LOS) for coronary artery bypass surgery (CABG).Design
Retrospective cohort study.Setting
General acute care hospitals throughout Taiwan.Participants
A total of 12,892 CABG patients admitted between 2011 and 2015 were extracted from Taiwan National Health Insurance claims data.Main outcome measures
Operative mortality and LOS. Restricted cubic splines were applied to discover the optimal hospital and surgeon volume thresholds needed to reduce operative mortality. Generalized estimating equation regression modeling, Cox proportional-hazards modeling and instrumental variables analysis were employed to examine the effects of hospital and surgeon volume thresholds on the operative mortality and LOS.Results
The volume thresholds for hospitals and surgeons were 55 cases and 5 cases per year, respectively. Patients who underwent CABG from hospitals that did not reach the volume threshold had higher operative mortality than those who received CABG from hospitals that did reach the volume threshold. Patients who underwent CABG with surgeons who did not reach the volume threshold had higher operative mortality and LOS than those who underwent CABG with surgeons who did reach the volume threshold.Conclusions
This is the first study to identify the optimal hospital and surgeon volume thresholds for reducing operative mortality and LOS. This supports policies regionalizing CABG at high-volume hospitals. Identifying volume thresholds could help patients, providers, and policymakers provide optimal care.
SUBMITTER: Chou YY
PROVIDER: S-EPMC8046183 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo investigate whether provider volume has an impact on the hazard of mortality for coronary artery bypass grafting (CABG) patients in Taiwan.Data sources/study settingMultiple sources of linked data from the National Health Insurance Program in Taiwan.Study designThe linked data were used to identify 27,463 patients who underwent CABG without concomitant angioplasty or valve procedures and the surgeon and hospital volumes. Generalized estimating equations and hazard models were estimated to assess the impact of volume on mortality. The hazard modeling technique used accounts for bias stemming from unobserved heterogeneity.Principal findingsBoth surgeon and hospital volume quartiles are inversely related to the hazard of mortality after CABG. Patients whose surgeon is in the three higher volume quartiles have lower 1-, 3-, 6-, and 12-month mortality after CABG, while only those having their procedure performed at the highest quartile of volume hospitals have lower mortality outcomes.ConclusionsMortality outcomes are related to provider CABG volume in Taiwan. Unobserved heterogeneity is a concern in the volume-outcome relationship; after accounting for it, surgeon volume effects on short-term mortality are large. Using models controlling for unobserved heterogeneity and examining longer term mortality may still differentiate provider quality by volume.
| S-EPMC2965499 | biostudies-literature
Project description:BackgroundThe length of a patient's stay (LOS) in a hospital is one metric used to compare the quality of care, as a longer LOS may flag higher complication rates or less efficient processes. A meaningful comparison of LOS can only occur if the expected average length of stay (ALOS) is defined first. This study aimed to define the expected ALOS of primary and conversion bariatric surgery in Australia and to quantify the effect of patient, procedure, system, and surgeon factors on ALOS.MethodsThis was a retrospective observational study of prospectively maintained data from the Bariatric Surgery Registry of 63 604 bariatric procedures performed in Australia. The primary outcome measure was the expected ALOS for primary and conversion bariatric procedures. The secondary outcome measures quantified the change in ALOS for bariatric surgery resulting from patient, procedure, hospital, and surgeon factors.ResultsUncomplicated primary bariatric surgery had an ALOS (SD) of 2.30 (1.31) days, whereas conversion procedures had an ALOS (SD) of 2.71 (2.75) days yielding a mean difference (SEM) in ALOS of 0.41 (0.05) days, P < 0.001. The occurrence of any defined adverse event extended the ALOS of primary and conversion procedures by 1.14 days (CI 95% 1.04-1.25), P < 0.001 and 2.33 days (CI 95% 1.54-3.11), P < 0.001, respectively. Older age, diabetes, rural home address, surgeon operating volume and hospital case volume increased the ALOS following bariatric surgery.ConclusionsOur findings have defined Australia's expected ALOS following bariatric surgery. Increased patient age, diabetes, rural living, procedural complications and surgeon and hospital case volume exerted a small but significant increase in ALOS.Study typeRetrospective observational study of prospectively collected data.
| S-EPMC10952963 | biostudies-literature
Project description:ImportanceMany strategies to reduce hospital length of stay (LOS) have been implemented, but few studies have evaluated hospital-led interventions focused on high-risk populations. The Agency for Healthcare Research and Quality (AHRQ) Learning Health System panel commissioned this study to further evaluate system-level interventions for LOS reduction.ObjectiveTo identify and synthesize evidence regarding potential systems-level strategies to reduce LOS for patients at high risk for prolonged LOS.Evidence reviewMultiple databases, including MEDLINE and Embase, were searched for English-language systematic reviews from January 1, 2010, through September 30, 2020, with updated searches through January 19, 2021. The scope of the protocol was determined with input from AHRQ Key Informants. Systematic reviews were included if they reported on hospital-led interventions intended to decrease LOS for high-risk populations, defined as those with high-risk medical conditions or socioeconomically vulnerable populations (eg, patients with high levels of socioeconomic risk, who are medically uninsured or underinsured, with limited English proficiency, or who are hospitalized at a safety-net, tertiary, or quaternary care institution). Exclusion criteria included interventions that were conducted outside of the hospital setting, including community health programs. Data extraction was conducted independently, with extraction of strength of evidence (SOE) ratings provided by systematic reviews; if unavailable, SOE was assessed using the AHRQ Evidence-Based Practice Center methods guide.FindingsOur searches yielded 4432 potential studies. We included 19 systematic reviews reported in 20 articles. The reviews described 8 strategies for reducing LOS in high-risk populations: discharge planning, geriatric assessment, medication management, clinical pathways, interdisciplinary or multidisciplinary care, case management, hospitalist services, and telehealth. Interventions were most frequently designed for older patients, often those who were frail (9 studies), or patients with heart failure. There were notable evidence gaps, as there were no systematic reviews studying interventions for patients with socioeconomic risk. For patients with medically complex conditions, discharge planning, medication management, and interdisciplinary care teams were associated with inconsistent outcomes (LOS, readmissions, mortality) across populations. For patients with heart failure, clinical pathways and case management were associated with reduced length of stay (clinical pathways: mean difference reduction, 1.89 [95% CI, 1.33 to 2.44] days; case management: mean difference reduction, 1.28 [95% CI, 0.52 to 2.04] days).Conclusions and relevanceThis systematic review found inconsistent results across all high-risk populations on the effectiveness associated with interventions, such as discharge planning, that are often widely used by health systems. This systematic review highlights important evidence gaps, such as the lack of existing systematic reviews focused on patients with socioeconomic risk factors, and the need for further research.
| S-EPMC8453321 | biostudies-literature
Project description:Clostridium difficile is a health care-associated infection of increasing importance. The purpose of this study was to estimate the time until death from any cause and time until release among patients with C. difficile, comparing the burden of those in the intensive care unit (ICU) with those in the general hospital population.A parametric mixture model was used to estimate event times, as well as the case-fatality ratio in ICU and non-ICU patients within a cohort of 609 adult incident cases of C. difficile in the Southeastern United States between 1 July 2009 and 31 December 2010.ICU patients had twice the median time to death (relative time = 1.97 [95% confidence interval (CI) = 0.96-4.01]) and nearly twice the median time to release (1.88 [1.40-2.51]) compared with non-ICU patients. ICU patients also experienced 3.4 times the odds of mortality (95% CI = 1.8-6.2). Cause-specific competing risks analysis underestimated the relative survival time until death (0.65 [0.36-1.17]) compared with the mixture model.Patients with C. difficile in the ICU experienced higher mortality and longer lengths of stay within the hospital. ICU patients with C. difficile infection represent a population in need of particular attention, both to prevent adverse patient outcomes and to minimize transmission of C. difficile to other hospitalized patients.
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Project description:ObjectiveAn aging population and increasing use of percutaneous therapies have resulted in older patients with more co-morbidity being referred for cardiac surgery. Objective measurements of physiological reserve and severity of co-morbid disease are required to improve risk stratification. We hypothesised that FEV1 would predict mortality and length of stay following cardiac surgery.MethodsWe assessed clinical outcomes in 2,241 consecutive patients undergoing coronary artery bypass grafting and/or valve surgery from 2001 to 2007 in a regional cardiac centre. Generalized linear models of the association between FEV1 and length of hospital stay and mortality were adjusted for age, sex, height, body mass index, socioeconomic status, smoking, cardiovascular risk factors, long-term use of bronchodilators or steroids for lung disease, and type and urgency of surgery. FEV1 was compared to an established risk prediction model, the EuroSCORE.ResultsSpirometry was performed in 2,082 patients (93%) whose mean (SD) age was 67 (10) years. Median hospital stay was 3 days longer in patients in the lowest compared to the highest quintile for FEV1, 1.35-fold higher (95% CI 1.20-1.52; p<0.001). The adjusted odds ratio for mortality was increased 2.11-fold (95% CI 1.45-3.08; p<0.001) per standard deviation decrement in FEV1 (800 ml). FEV1 improved discrimination of the EuroSCORE for mortality. Similar associations were found after excluding people with known pulmonary disease and/or airflow limitation on spirometry.ConclusionsReduced FEV1 strongly predicted increased length of stay and in-hospital mortality following cardiac surgery. FEV1 is a widely available measure of physiological health that may improve risk stratification of complex patients undergoing cardiac surgery and should be evaluated for inclusion in new prediction tools.
| S-EPMC3665784 | biostudies-literature
Project description:ObjectivesTo assess the relationship between surgeon (SV) and hospital volume (HV) on mortality after radical cystectomy (RC).Patients and methodsWe queried the National Cancer Database (NCDB) for adult patients undergoing RC between 2010 and 2013. We calculated average volume for each surgeon and hospital. Using propensity-scored weights for combined volume groups with a proportional hazards regression model, we compared the associations between HV and SV with 90-day survival after RC.ResultsA total of 19 346 RCs were performed at 927 hospitals by 2 927 surgeons in the period 2010-2013. The median (interquartile range) HV and SV were 12.3 (5.0-35.5) and 4.3 (1.3-12.3) cases, respectively. For HV, 90-day unadjusted mortality was 8.5% in centres with <5 cases/year (95% confidence interval [CI] 7.7-9.3) and 5.6% in those with >30 cases/year (95% CI 5.0-6.2). For SV, 90-day mortality was 8.1% for surgeons with <5 cases/year (95% CI 7.6-8.6) and 4.0% for those with >30 cases/year (95% CI 2.8-5.2; all P < 0.05). The 30-day mortality rate was lowest for the combined HV-SV groups with HV >30, ranging from 1.6% to 2.1%.ConclusionsIn hospitals reporting to the NCDB, volume was associated with improved mortality after RC. These associations appear to be driven by hospital- rather than surgeon-level effects. An elevated SV had a beneficial effect on mortality at the highest-volume hospitals. These findings inform efforts to regionalize complex surgical care and improve quality at community and safety net hospitals.
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Project description:ObjectiveThe interdependence of hospitals is underappreciated in patient outcomes studies. We used a network science approach to foreground this interdependence. Specifically, within two large state-based interhospital networks, we examined the relationship of a hospital's network position with in-hospital mortality and length of stay.MethodsWe constructed interhospital network graphs using data from the Healthcare Cost and Utilization Project and the American Hospital Association Annual Survey for Florida (2014) and California (2011). The exposure of interest was hospital centrality, defined as weighted degree (sum of all ties to a given hospital from other hospitals). The outcomes were in-hospital mortality and length of stay with sub-analyses for four acute medical conditions: pneumonia, heart failure, ischemic stroke, myocardial infarction. We compared outcomes for each quartile of hospital centrality relative to the most central quartile (Q4), independent of patient- and hospital-level characteristics, in this retrospective cross-sectional study.ResultsThe inpatient cohorts had 1,246,169 patients in Florida and 1,415,728 in California. Compared to Florida's central hospitals which had an overall mortality 1.60%, peripheral hospitals had higher in-hospital mortality (1.97%, adjusted OR (95%CI): Q1 1.61 (1.37, 1.89), p<0.001). Hospitals in the middle quartiles had lower in-hospital mortality compared to central hospitals (%, adjusted OR (95% CI): Q2 1.39%, 0.79 (0.70, 0.89), p<0.001; Q3 1.33%, 0.78 (0.70, 0.87), p<0.001). Peripheral hospitals had longer lengths of stay (adjusted incidence rate ratio (95% CI): Q1 2.47 (2.44, 2.50), p<0.001). These findings were replicated in California, and in patients with heart failure and pneumonia in Florida. These results show a u-shaped distribution of outcomes based on hospital network centrality quartile.ConclusionsThe position of hospitals within an inter-hospital network is associated with patient outcomes. Specifically, hospitals located in the peripheral or central positions may be most vulnerable to diminished quality outcomes due to the network. Results should be replicated with deeper clinical data.
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Project description:Hospital length of stay (LOS) and time for a patient to reach clinical stability (TCS) have increasingly become important outcomes when investigating ways in which to combat Community Acquired Pneumonia (CAP). Difficulties arise when deciding how to handle in-hospital mortality. Ad-hoc approaches that are commonly used to handle time to event outcomes with mortality can give disparate results and provide conflicting conclusions based on the same data. To ensure compatibility among studies investigating these outcomes, this type of data should be handled in a consistent and appropriate fashion.Using both simulated data and data from the international Community Acquired Pneumonia Organization (CAPO) database, we evaluate two ad-hoc approaches for handling mortality when estimating the probability of hospital discharge and clinical stability: 1) restricting analysis to those patients who lived, and 2) assigning individuals who die the "worst" outcome (right-censoring them at the longest recorded LOS or TCS). Estimated probability distributions based on these approaches are compared with right-censoring the individuals who died at time of death (the complement of the Kaplan-Meier (KM) estimator), and treating death as a competing risk (the cumulative incidence estimator). Tests for differences in probability distributions based on the four methods are also contrasted.The two ad-hoc approaches give different estimates of the probability of discharge and clinical stability. Analysis restricted to patients who survived is conceptually problematic, as estimation is conditioned on events that happen at a future time. Estimation based on assigning those patients who died the worst outcome (longest LOS and TCS) coincides with the complement of the KM estimator based on the subdistribution hazard, which has been previously shown to be equivalent to the cumulative incidence estimator. However, in either case the time to in-hospital mortality is ignored, preventing simultaneous assessment of patient mortality in addition to LOS and/or TCS. The power to detect differences in underlying hazards of discharge between patient populations differs for test statistics based on the four approaches, and depends on the underlying hazard ratio of mortality between the patient groups.Treating death as a competing risk gives estimators which address the clinical questions of interest, and allows for simultaneous modelling of both in-hospital mortality and TCS / LOS. This article advocates treating mortality as a competing risk when investigating other time related outcomes.
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Project description:Language barriers between patients and providers may influence the process and quality of care.To examine the association of language preference with length of stay (LOS) and in-hospital mortality for patients admitted for acute myocardial infarction (AMI).Electronic administrative hospital discharge data for all non-disabled Medicaid beneficiaries age 35 years and older admitted to all acute care California hospitals with a diagnosis of AMI between 1994 and 1998.We used multivariate regression to explore whether observed differences in the hospital LOS and in-hospital mortality between non-English preference (NEP) and English preference (EP) individuals could be explained by individual and/or hospital level factors. We adjusted for patient level characteristics using 24 covariates from a previously validated prediction model of mortality after hospitalization for AMI.Of 12,609 Medicaid patients across 401 California hospitals, 2,757 (22%) had NEP. NEP was associated with a 3.9% increased LOS (95% CI 0.7, 7.1; p = 0.02) in unadjusted analysis and a 3.8% increased LOS (95% CI 0.3, 7.3; p = 0.03) after controlling for patient level characteristics. Differences in LOS were no longer significant after adjusting receipt of cardiac procedure/ surgery (2.8%; 95% CI -0.6, 6.2; p = 0.1) or after adjusting for hospital (0.9%; 95% CI -2.5, 4.3; p = 0.6). Non-English language preference was associated with lower in-hospital mortality in unadjusted analysis (odds ratio [OR] = 0.80; 95% CI 0.69, 0.94; p = 0.005), but was not significant after adjusting for patient level characteristics (adjusted OR [AOR] 0.95; 95% CI 0.78, 1.27; p = 0.6). Adjusting for receipt of cardiac procedure/ surgery (AOR 0.97; 95% CI 0.79, 1.18; p = 0.7) and hospital (AOR 0.97; 95% CI 0.78; 1.21; p = 0.8) did not alter this finding.Language preference is not associated with AMI mortality, and the small increase in length of stay associated with non-English preference is accounted for by hospital level factors. Our results suggest that system level differences are important to consider in studies of the effect of language barriers in the health care setting.
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Project description:Interventions: Group 1: Patients assigned to the intervention group will receive a pedometer preoperatively with a defined step goal of 7500 steps daily. Postoperatively, the patients receive a predefined target of daily steps to be achieved in the first days after surgery. On the first postoperative day these are at least 500 steps, on the 2nd postoperative day 1000 steps, on the 3rd postoperative day 2000 steps, on the 4th postoperative day 3000 steps and on the 5th postoperative day and 4000 steps. The actual steps taken are documented regardless of whether the goal is reached.
Group 2: The control group receives a pedometer preoperatively with the request to document the daily steps taken without a defined step target. The pedometer continues to be used postoperatively and the number of steps is documented during the inpatient stay.
Primary outcome(s): Length of hospital stay
Study Design: Allocation: Randomized controlled study; Masking: Blinded (masking used); Control: active; Assignment: parallel; Study design purpose: treatment
| 72433 | ecrin-mdr-crc