Low-performing Centers Research Articles

A multidimensional approach to identifying high-performing trauma centers across the United States.

The differentiators of centers performing at the highest level of quality and patient safety are likely both structural and cultural. We aimed to combine five indicators representing established domains of trauma quality and to identify and describe the structural characteristics of consistently performing centers. Using American College of Surgeons Trauma Quality Improvement Program data from 2017 to 2020, we evaluated five quality measures across several care domains for adult patients in levels I and II trauma centers: (1) time to operating room for patients with abdominal gunshot wounds and shock, (2) proportion of patients receiving timely venous thromboembolism prophylaxis, (3) failure to rescue (death following a complication), (4) major hospital complications, and (5) mortality. Overall performance was summarized as a composite score incorporating all measures. Centers were ranked from highest to lowest performer. Principal component analysis showed the influence of each indicator on overall performance and supported the composite score approach. We identified 272 levels I and II centers, with 28 and 27 centers in the top and bottom 10%, respectively. Patients treated in high-performing centers had significant lower rates of death major complications and failure to rescue, compared with low-performing centers ( p < 0.001). The median time to operating room for gunshot wound was almost half that in high compared with low-performing centers, and rates of timely venous thromboembolism prophylaxis were over twofold greater ( p < 0.001). Top performing centers were more likely to be level I centers and cared for a higher number of severely injured patients per annum. Each indicator contributed meaningfully to the variation in scores and centers tended to perform consistently across most indicators. The combination of multiple indicators across dimensions of quality sets a higher standard for performance evaluation and allows the discrimination of centers based on structural elements, specifically level 1 status, and trauma center volume. Therapeutic /Care Management; Level IV.

Failure to rescue in trauma: Early and late mortality in low- and high-performing trauma centers.

Failure to rescue (FTR) is defined as mortality following a complication. Failure to rescue has come under scrutiny as a quality metric to compare trauma centers. In contrast to elective surgery, trauma has an early period of high expected mortality because of injury sequelae rather than a complication. Here, we report FTR in early and late mortality using an externally validated trauma patient database, hypothesizing that centers with higher risk-adjusted mortality rates have higher risk-adjusted FTR rates. The study included 114,220 patients at 34 Levels I and II trauma centers in a statewide quality collaborative (2016-2020) with Injury Severity Score of ≥5. Emergency department deaths were excluded. Multivariate regression models were used to produce center-level adjusted rates for mortality and major complications. Centers were ranked on adjusted mortality rate and divided into quintiles. Early deaths (within 48 hours of presentation) and late deaths (after 48 hours) were analyzed. Overall, 6.7% of patients had a major complication and 3.1% died. There was no difference in the mean risk-adjusted complication rate among the centers. Failure to rescue was significantly different across the quintiles (13.8% at the very low-mortality centers vs. 23.4% at the very-high-mortality centers, p < 0.001). For early deaths, there was no difference in FTR rates among the highest and lowest mortality quintiles. For late deaths, there was a twofold increase in the FTR rate between the lowest and highest mortality centers (9.7% vs. 19.3%, p < 0.001), despite no difference in the rates of major complications (5.9% vs. 6.0%, p = 0.42). Low-performing trauma centers have higher mortality rates and lower rates of rescue following major complications. These differences are most evident in patients who survive the first 48 hours after injury. A better understanding of the complications and their role in mortality after 48 hours is an area of interest for quality improvement efforts. Prognostic and Epidemiologic; Level III.

The Dark Side of Chasing the Perfect Donor. Is it Time for Us to Change Cardiac Transplant Program Performance Metrics?

The Dark Side of Chasing the Perfect Donor. Is it Time for Us to Change Cardiac Transplant Program Performance Metrics?

Characteristics Associated With High-Performing Pediatric Heart Transplant Centers in the United States From 2006 to 2015

Differences among pediatric transplant centers in long-term survival of pediatric recipients of heart transplants can be mostly explained by differences in 90-day mortality. To understand characteristics associated with high-performing pediatric HT centers by comparing key outcomes among centers stratified by 90-day risk-adjusted mortality. This retrospective cohort study included recipients of HT aged younger than 18 years in the US. Analyses included 44 US centers during 2006 to 2015 using the Organ Procurement and Transplant Network database. A risk model for 90-day mortality was developed using data from all recipients to estimate expected 90-day mortality and 90-day standardized mortality ratio (SMR; calculated as observed mortality divided by expected mortality) for each center. Centers were stratified into tertiles by SMR and compared for key outcomes. Data were analyzed from January to March 2020. High-, medium-, and low-performing centers (SMR tertile). Posttransplant 90-day mortality across recipient risk spectrum and incidence of and mortality following early posttransplant complications. Of 3211 children analyzed, 1016 (31.6%) were infants younger than 1 year and 1459 (45.4%) were girls. The median (interquartile range) age was 4 (0-12) years. Centers were stratified by SMR tertile, and SMR was 0 to 0.71 among 15 high-performing centers, 0.79 to 1.12 among 14 medium-performing centers, and 1.19 to 3.33 among 15 low-performing centers. High-performing centers had 90-day mortality of 0.8% (95% CI, 0.3%-1.8%) in children with low risk and expected mortality of 2.0%, 2.3% (95% CI, 0.6%-5.7%) in children with intermediate risk and expected mortality of 6.5%, and 16.7% (95% CI, 7.9%-29.3%) in children with high risk and expected mortality of 30.8%. Incidence of acute rejection during transplant hospitalization was 10.3% at high-performing centers, 10.3% at medium-performing centers, and 9.7% at low-performing centers (P for trend = .68), and incidence of post-HT kidney failure requiring dialysis was 4.1% at high-performing centers, 5.2% at medium-performing centers, and 8.5% at low-performing centers (P for trend = .001). Ninety-day mortality was significantly lower at high-performing centers among children treated for rejection (high-performing: 2.0%; medium-performing: 6.9%; low-performing: 11.7%; P for trend = .006) and among recipients receiving dialysis for post-HT kidney failure (high-performing: 17.5%; medium-performing: 39.4%; low-performing: 47.6%; P for trend < .001). This cohort study found that high-performing pediatric HT centers had lower 90-day mortality across the recipient risk spectrum and lower mortality among recipients who develop rejection or post-HT kidney failure during transplant hospitalization. These findings suggest presence of superior processes and systems of care at high-performing pediatric HT centers.

Pulmonary complications in trauma: Another bellwether for failure to rescue?

BackgroundPulmonary complications are the most common adverse event after injury and second greatest cause of failure to rescue (death after pulmonary complications). It is not known whether readily accessible trauma center data can be used to stratify center-level performance for various complications. Performance variation between trauma centers would allow sharing of best practices among otherwise similar hospitals. We hypothesized that high-, average-, and low-performing centers for pulmonary complication and failure to rescue could be identified and that hospital factors associated with success and failure could be discovered. MethodsPennsylvania state trauma registry data (2007–2015) were abstracted for pulmonary complications. Burns and age <17 were excluded. Multivariable logistic regression models were developed for pulmonary complication and failure to rescue, using demographics, comorbidities, and injuries/physiology. Expected event rates were compared with observed rates to identify outliers. Center-level variables associated with outcomes of interest were taken from the American Hospital Association Annual Survey Database and assessed for inclusion. ResultsIncluded in the study were 283,121 patients (male [60%] blunt trauma [92%]). Of these patients, 3% (8,381 of 283,121) developed pulmonary complications (center-level range 0.18%–5.8%). The percentage of failure-to-rescue patients was 13.4% (1,120/8,381, center-level range 0.0%-22.6%). For pulmonary complications, 13 out of 27 centers were high performers (95% CI for O:E ratio <1) and 7 out of 27 were low (95% CI for an O:E ratio >1). For failure-to-rescue patients, 2 out of 27 centers were low performers and the remainder average. There was little concordance between performance for pulmonary complications and failure to rescue. Research programs, large non-teaching hospitals, those with advanced practice providers, and those with health maintenance organizations had reduced failure-to-rescue patients. ConclusionFactors associated with complications were distinct from those affecting failure to rescue and center-level success in reducing complications often did not translate into success in preventing death once they occurred. Our data demonstrate that high- and low-performing centers and the factors driving success or failure are identifiable. This work serves as a guide for comparing practices and improving outcomes with readily available data.

High-Performance Trauma Centers in a Single-State Trauma System

Trauma centers with low observed:expected (O:E) mortality ratios are considered high performers; however, it is unknown whether improvements in this ratio are due to a small number of unexpected survivors with high mortality risk (big saves) or a larger number of unexpected survivors with moderate mortality risk (marginal gains). We hypothesized that the highest-performing centers achieve that status via larger numbers of unexpected survivors with moderate mortality risk. We calculated O:E ratios for trauma centers in Pennsylvania for 2016 using a risk-adjusted mortality model. We identified high and low performers as centers whose 95% CIs did not cross 1. We visualized differences between these centers by plotting patient-level observed and expected mortality; we then examined differences in a subset of patients with a predicted mortality of ≥10% using the chi-squared test. One high performer and 1 low performer were identified. The high performer managed a population with more blunt injuries (97.2% vs 93.6%, P < .001) and a higher median Injury Severity Score (14 vs 11, P < .001). There was no difference in survival between these centers in patients with an expected mortality of <10% (98.0% vs 96.7%, P = .11) or ≥70% (23.5% vs 10.8%, P = .22), but there was a difference in the subset with an expected mortality of ≥10% (77.5% vs 43.1%, P < .001). Though patients with very low predicted mortality do equally well in high-performing and low-performing centers, the fact that performance seems determined by outcomes of patients with moderate predicted mortality favors a "marginal gains" theory.

Understanding and Addressing Variation in Health Care-Associated Infections After Durable Ventricular Assist Device Therapy: Protocol for a Mixed Methods Study.

BackgroundDurable ventricular assist device (VAD) therapy is reserved for patients with advanced heart failure who have a poor estimated 1-year survival. However, despite highly protocolized management processes, patients are at a unique risk for developing a health care–associated infection (HAI). Few studies have examined optimal strategies for HAI prevention after durable VAD implantation, despite variability in rates across centers and their impact on short- and long-term outcomes.ObjectiveThe objective of this study is to develop recommendations for preventing the most significant HAIs after durable VAD implantation. The study has 3 specific aims: (1) identify determinants of center-level variability in HAI rates, (2) develop comprehensive understanding of barriers and facilitators for achieving low center-level HAI rates, and (3) develop and disseminate a best practices toolkit for preventing HAIs that accommodates various center contexts.MethodsThis is a sequential mixed methods study starting with a cross-sectional assessment of current practices. To address aim 1, we will conduct (1) a systematic review of HAI prevention studies and (2) in-depth quantitative analyses using administrative claims, in-depth clinical data, and organizational surveys of VAD centers. For aim 2, we will apply a mixed methods patient tracer assessment framework to conduct semistructured interviews, field observations, and document analysis informed by findings from aim 1 at 5 high-performing (ie, low HAIs) and 5 low-performing (ie, high HAI) centers, which will be examined using a mixed methods case series analysis. For aim 3, we will build upon the findings from the previous aims to develop and field test an HAI preventive toolkit, acquire stakeholder input at an annual cardiac surgical conference, disseminate the final version to VAD centers nationwide, and conduct follow-up surveys to assess the toolkit’s adoption.ResultsThe project was funded by the Agency for Healthcare Research and Quality in 2018 and enrollment for the overall project is ongoing. Data analysis is currently under way and the first results are expected to be submitted for publication in 2019.ConclusionsThis mixed methods study seeks to quantitatively assess the determinants of HAIs across clinical centers and qualitatively identify the context-specific facilitators and barriers for attaining low HAI rates. The mixed data findings will be used to develop and disseminate a stakeholder-acceptable toolkit of evidence-based HAI prevention recommendations that will accommodate the specific contexts and needs of VAD centers.International Registered Report Identifier (IRRID)PRR1-10.2196/14701

Variability in functional outcome and treatment practices by treatment center after out-of-hospital cardiac arrest: analysis of International Cardiac Arrest Registry.

Functional outcomes vary between centers after out-of-hospital cardiac arrest (OHCA) and are partially explained by pre-existing health status and arrest characteristics, while the effects of in-hospital treatments on functional outcome are less understood. We examined variation in functional outcomes by center after adjusting for patient- and arrest-specific characteristics and evaluated how in-hospital management differs between high- and low-performing centers. Analysis of observational registry data within the International Cardiac Arrest Registry was used to perform a hierarchical model of center-specific risk standardized rates for good outcome, adjusted for demographics, pre-existing functional status, and arrest-related factors with treatment center as a random effect variable. We described the variability in treatments and diagnostic tests that may influence outcome at centers with adjusted rates significantly above and below registry average. A total of 3855 patients were admitted to an ICU following cardiac arrest with return of spontaneous circulation. The overall prevalence of good outcome was 11-63% among centers. After adjustment, center-specific risk standardized rates for good functional outcome ranged from 0.47 (0.37-0.58) to 0.20 (0.12-0.26). High-performing centers had faster time to goal temperature, were more likely to have goal temperature of 33°C, more likely to perform unconscious cardiac catheterization and percutaneous coronary intervention, and had differing prognostication practices than low-performing centers. Center-specific differences in outcomes after OHCA after adjusting for patient-specific factors exist. This variation could partially be explained by in-hospital management differences. Future research should address the contribution of these factors to the differences in outcomes after resuscitation.

Quality-based ratings in Medicare and trends in kidney transplantation.

To assess the relationship between the 2007 Medicare regulation enforcing quality standards for transplant centers and trends in kidney transplantation. Transplant centers' biannual reports and the national registry for kidney transplantation from 2003 to 2010. Non-compliant (low-performing) centers were compared with centers in compliance with quality standards according to: number of transplants, waiting-list registrations, and rates of graft failures, transfers, and deaths. Multivariate regressions were estimated to evaluate the association between the regulation and transplantation outcomes. Patient characteristics and outcomes were aggregated to six-month periods and linked to centers' reports. Relative to average-performing centers, 12 percent of transplants shifted away from low-performing centers and high-performing centers captured 6 percent of this decline. Low-performing centers experienced a 2-percentage point per period decline in 1-year graft failure rates and a 15-percent decrease in registrations post-regulation, whereas high-performing centers incurred a 5-percent decrease in registrations relative to average-performing centers. Government oversight in kidney transplantation was associated with a small downward shift in overall kidney transplants. Reductions in graft failure rates at low-performing centers may imply an increase in quality or a decline in transplantation of either marginal organs or riskier patients; whereas reductions in registrations may indicate risk aversion toward high-risk patients. Policy makers should consider making less punitive requirements for programs, which employ new transplantation techniques to expand access.

Regional Variation in Performance for Commission on Cancer Breast Quality Measures and Impact on Overall Survival.

Adherence to quality measures has become an important indicator of cancer center performance for high-quality cancer care. We examined regional variation in performance for Commission on Cancer breast quality measures and its impact on overall survival (OS) for those measures that have been shown to impact OS. Six breast quality measures were analyzed using the National Cancer DataBase from 2014 to 2015, and a multivariable model was used to assess performance for each measure by region. Kaplan-Meier and Cox proportional hazard models were used to examine OS between high- and low-performing centers from 2007 to 2012. Overall, 305,391 women had surgery at 1322 institutions in nine US regions; 90.8% underwent needle biopsy (range 86.0-92.6% between regions, p < 0.01), 69.8% had breast-conserving surgery (BCS) for stage 0-II cancer (60.9-79.3%, p < 0.01), 85.2% aged < 70years had radiation therapy (RT) after BCS (79.6-90.8%, p < 0.01), 78.3% of women with four or more positive nodes had post-mastectomy RT (70.9-84.5%, p < 0.01), 90.9% with hormone receptor (HR)-positive stage IB-III cancer had hormone therapy (83.7-95.1%, p < 0.01), and 89.4% aged < 70years with HR-negative stage IB-III cancer had chemotherapy (87.6-91.4%, p < 0.01). Multivariate analyses adjusted for patient and facility factors found that region was the only consistent predictor of non-compliance across measures. With median 65-month follow-up, there was no difference in OS between high- and low-performing centers for the three measures that have been shown to impact OS. There is significant regional variation in performance on the breast quality measures but this variation did not impact OS. Targeted efforts in certain areas of the country may help improve performance on these measures.

Factors Influencing Patients’ Perspectives of Radiology Imaging Centers: Evaluation Using an Online Social Media Ratings Website

PurposeThe goal of this study was to use patient reviews posted on Yelp.com, an online ratings website, to identify factors most commonly associated with positive versus negative patient perceptions of radiology imaging centers across the United States. MethodsA total of 126 outpatient radiology centers from the 46 largest US cities were identified using Yelp.com; 1,009 patient reviews comprising 2,582 individual comments were evaluated. Comments were coded as pertaining to either the radiologist or other service items, and as expressing either a positive or negative opinion. Distribution of comments was compared with center ratings using Fisher’s exact test. ResultsOverall, 14% of comments were radiologist related; 86% pertained to other aspects of service quality. Radiologist-related negative comments more frequent in low-performing centers (mean rating ≤2 on 1-5 scale) than high-performing centers (rating ≥4) pertained to imaging equipment (25% versus 7%), report content (25% versus 2%), and radiologist professionalism (25% versus 2%) (P < .010). Other service-related negative comments more frequent in low-performing centers pertained to receptionist professionalism (70% versus 21%), billing (65% versus 10%), wait times (60% versus 26%), technologist professionalism (55% versus 12%), scheduling (50% versus 17%), and physical office conditions (50% versus 5%) (P < .020). Positive comments more frequent in high-performing centers included technologist professionalism (98% versus 55%), receptionist professionalism (79% versus 50%), wait times (72% versus 40%), and physical office conditions (64% versus 25%) (P < .020). ConclusionsPatients’ perception of radiology imaging centers is largely shaped by aspects of service quality. Schedulers, receptionists, technologists, and billers heavily influence patient satisfaction in radiology. Thus, radiologists must promote a service-oriented culture throughout their practice.

Association between Kidney Transplant Center Performance and the Survival Benefit of Transplantation Versus Dialysis

Despite the benefits of kidney transplantation, the total number of transplants performed in the United States has stagnated since 2006. Transplant center quality metrics have been associated with a decline in transplant volume among low-performing centers. There are concerns that regulatory oversight may lead to risk aversion and lack of transplantation growth. A retrospective cohort study of adults (age≥18 years) wait-listed for kidney transplantation in the United States from 2003 to 2010 using the Scientific Registry of Transplant Recipients was conducted. The primary aim was to investigate whether measured center performance modifies the survival benefit of transplantation versus dialysis. Center performance was on the basis of the most recent Scientific Registry of Transplant Recipients evaluation at the time that patients were placed on the waiting list. The primary outcome was the time-dependent adjusted hazard ratio of death compared with remaining on the transplant waiting list. Among 223,808 waitlisted patients, 59,199 and 32,764 patients received a deceased or living donor transplant, respectively. Median follow-up from listing was 43 months (25th percentile=25 months, 75th percentile=67 months), and there were 43,951 total patient deaths. Deceased donor transplantation was independently associated with lower mortality at each center performance level compared with remaining on the waiting list; adjusted hazard ratio was 0.24 (95% confidence interval, 0.21 to 0.27) among 11,972 patients listed at high-performing centers, adjusted hazard ratio was 0.32 (95% confidence interval, 0.31 to 0.33) among 203,797 patients listed at centers performing as expected, and adjusted hazard ratio was 0.40 (95% confidence interval, 0.35 to 0.45) among 8039 patients listed at low-performing centers. The survival benefit was significantly different by center performance (P value for interaction <0.001). Findings indicate that measured center performance modifies the survival benefit of kidney transplantation, but the benefit of transplantation remains highly significant even at centers with low measured quality. Policies that concurrently emphasize improved center performance with access to transplantation should be prioritized to improve ESRD population outcomes.

Abstract 203: Emergent Brain Imaging for Acute Ischemic Stroke in Veterans Health Administration Hospitals

Objective: Tissue plasminogen activator (tPA) is under-utilized in Veterans Health Administration medical centers (VAMCs); delays in brain imaging may be a significant barrier. Our primary objective was to describe door-to-imaging time (DIT) patterns among veterans with acute ischemic stroke (IS). We identified patient-level predictors of faster imaging times and decomposed variation in DIT attributable to hospital and patient-level factors. Methods: Detailed medical record reviews were done on 5,000 acute IS patients admitted to any VAMC in 2007; this analysis included those with emergent brain imaging (CT/MRI within 6 hours). We used descriptive statistics to report DIT patterns and a series of random-intercept hierarchical linear regression models to identify predictors of DIT and to decompose variation in DIT. Results: Among the 2,681 acute IS patients emergently imaged in a VAMC, median DIT was 67.7 minutes (min) (IQR, 37.1-115.8 min). Among the 83 patients who were eligible for tPA, the median DIT was 45.9 min (IQR, 28.4-72.1 min) and 22% met the DIT&lt;25 min guideline. Arrival from clinic and increased onset-to-arrival time were independently associated with slower DIT, whereas blood pressure on arrival &gt;185/110 mm Hg was associated with faster DIT (Table). In the model without patient-level factors, 7.2% of variation in DIT was attributable to hospital. Adding patient-level predictors to the model explained 18.8% of the variation in DIT, but 6.4% of the variation remained attributable to case-mix-adjusted hospital variation. Despite this clinical substantial hospital variation, the low IS caseload at most hospitals made it impossible to reliably identify high- and low-performing facilities. Conclusion: There remains room for improvement in DIT for VAMC acute IS patients. Variation is attributable to patient and hospital factors, however, low case IS loads at most hospitals prevented reliable discrimination between high and low-performing centers.

Cost-effectiveness of Treatment Strategies for Pancreatic Head Adenocarcinoma and Potential Opportunities for Improvement

Generally dismal outcomes have led to a nihilistic attitude toward treating pancreatic cancer, while fiscal constraints have increased scrutiny of treatments costs. Our objective was to compare the cost-effectiveness of various treatment strategies for resectable pancreatic head adenocarcinoma, and to identify opportunities for improved cost effectiveness. A decision model compared 6 strategies: no treatment, radiotherapy only, chemotherapy only, chemotherapy plus radiotherapy, surgery alone, and surgery plus adjuvant therapy. Outcomes and probabilities were identified using the National Cancer Data Base, the American Cancer Society National Surgical Quality Improvement Program, and the literature. Costs were estimated using Medicare payment. Incremental cost-effectiveness ratios (ICERs) were calculated, and sensitivity analyses were performed by varying potentially modifiable parameters of the model. Survival was reported in quality-adjusted life-months (QALMs). Surgery plus adjuvant therapy, chemotherapy alone, and no treatment were the only viable strategies in terms of cost effectiveness. Surgery plus adjuvant therapy versus no treatment demonstrated an incremental cost-effectiveness ratio (ICER) of $7,663/QALM. Theoretically increasing survival in node-negative, margin-negative patients from 14 to 22 QALMs produced the largest reduction in the ICER for surgery plus adjuvant therapy compared to no treatment ($6,386/QALM), whereas reducing the perioperative mortality from 3 to 1% had only a marginal effect. The ICER was significantly lower for high-performing centers ($5,991/QALM) than for low-performing centers ($9,144/QALM). Surgery plus adjuvant therapy for resectable pancreatic head adenocarcinoma extends survival, but at considerable expense. Significant cost reductions could be realized by improving treatment outcomes to levels of high-performing centers and development of increasingly effective adjuvant therapies.

Hidden Selection Bias Deriving From Donor Organ Characteristics Does Not Affect Performance Evaluations of Kidney Transplant Centers

Transplant center performance evaluations have garnered substantial attention in recent years. Among sources of bias that may affect measured performance are underlying characteristics of donor organs. An unresolved question is whether centers accepting higher-risk donations are placed in jeopardy for lower evaluations independent of actual quality of care. The primary aim was to assess whether unmeasured characteristics of donor organs impact risk-adjusted outcomes used for center performance evaluations. The study included adult kidney transplant recipients (n = 53,791) from 1994 to 2008 from a national registry. We compared adjusted graft survival with use of paired-donor kidneys (allocated to high- and low-performing centers) and unpaired donor kidneys to investigate whether measured center performance was consistent with organs derived from the same donor (minimizing the influence of noncodified risk factors). The primary finding was that differences between centers were unaffected by use of paired or unpaired donations (hazard ratio for patients transplanted at high performing centers with paired kidneys = 0.63 [95% CI, 0.53-0.74] and with unpaired kidneys = 0.66 [95% CI, 0.62-0.70], P value for interaction = 0.52). This finding was consistent over 5 consecutive cohorts, based on either concurrent or prospective outcomes and by altering the threshold criteria for identification of performance outliers. Results indicate that underlying selection bias from donor characteristics does not impact transplant center evaluations. This is important evidence that donor selection is not a primary driver for evaluated quality of care among transplant centers and acceptance of higher-risk kidneys should not be perceived as a primary threat to measured performance.

Significant Alterations in Reported Clinical Practice Associated with Increased Oversight of Organ Transplant Center Performance

In the past several years, emphasis on quality metrics in the field of organ transplantation has increased significantly, largely because of the new conditions of participation issued by the Centers for Medicare and Medicaid Services. These regulations directly associate patients' outcomes and measured performance of centers with the distribution of public funding to institutions. Moreover, insurers and marketing ventures have used publicly available outcomes data from transplant centers for business decision making and advertisement purposes. We gave a 10-question survey to attendees of the Transplant Management Forum at the 2009 meeting of the United Network for Organ Sharing to ascertain how centers have responded to the increased oversight of performance. Of 63 responses, 55% indicated a low or near low performance rating at their center in the past 3 years. Respondents from low-performing centers were significantly more likely to indicate increased selection criteria for candidates (81% vs 38%, P = .001) and donors (77% vs 31%, P < .001) as well as alterations in clinical protocols (84% vs 52%, P = .007). Among respondents indicating lost insurance contracts (31%), these differences were also highly significant. Based on respondents' perceptions, outcomes of performance evaluations are associated with significant changes in clinical practice at transplant centers. The transplant community and policy makers should practice vigilance that performance evaluations and regulatory oversight do not inadvertently lead to diminished access to care among viable candidates or decreased transplant volume.

Significant alterations in reported clinical practice associated with increased oversight of organ transplant center performance

In the past several years, emphasis on quality metrics in the field of organ transplantation has increased significantly, largely because of the new conditions of participation issued by the Centers for Medicare and Medicaid Services. These regulations directly associate patients' outcomes and measured performance of centers with the distribution of public funding to institutions. Moreover, insurers and marketing ventures have used publicly available outcomes data from transplant centers for business decision making and advertisement purposes. We gave a 10-question survey to attendees of the Transplant Management Forum at the 2009 meeting of the United Network for Organ Sharing to ascertain how centers have responded to the increased oversight of performance. Of 63 responses, 55% indicated a low or near low performance rating at their center in the past 3 years. Respondents from low-performing centers were significantly more likely to indicate increased selection criteria for candidates (81% vs 38%, P = .001) and donors (77% vs 31%, P < .001) as well as alterations in clinical protocols (84% vs 52%, P = .007). Among respondents indicating lost insurance contracts (31%), these differences were also highly significant. Based on respondents' perceptions, outcomes of performance evaluations are associated with significant changes in clinical practice at transplant centers. The transplant community and policy makers should practice vigilance that performance evaluations and regulatory oversight do not inadvertently lead to diminished access to care among viable candidates or decreased transplant volume.