Raymond Kang

A comprehensive risk assessment of mortality following donation after cardiac death liver transplant – An analysis of the national registry

BACKGROUND & AIMS Organ scarcity has resulted in increased utilization of donation after cardiac death (DCD) donors. Prior analysis of patient survival following DCD liver transplantation has been restricted to single institution cohorts and a limited national experience. We compared the current national experience with DCD and DBD livers to better understand survival after transplantation. METHODS We compared 1113 DCD and 42,254 DBD recipients from the Scientific Registry of Transplant Recipients database between 1996 and 2007. Patient survival was analyzed using the Kaplan-Meier methodology and Cox regression. RESULTS DCD recipients experienced worse patient survival compared to DBD recipients (p<0.001). One and 3 year survival was 82% and 71% for DCD compared to 86% and 77% for DBD recipients. Moreover, DCD recipients required re-transplantation more frequently (DCD 14.7% vs. DBD 6.8%, p<0.001), and re-transplantation survival was markedly inferior to survival after primary transplant irrespective of graft type. Amplification of mortality risk was observed when DCD was combined with cold ischemia time >12h (HR = 1.81), shared organs (HR = 1.69), recipient hepatocellular carcinoma (HR=1.80), recipient age >60 years (HR = 1.92), and recipient renal insufficiency (HR = 1.82). CONCLUSIONS DCD recipients experience significantly worse patient survival after transplantation. This increased risk of mortality is comparable in magnitude to, but often exacerbated by other well-established risk predictors. Utilization decisions should carefully consider DCD graft risks in combination with these other factors.

The increased costs of donation after cardiac death liver transplantation: caveat emptor.

Objective:To determine the effect of donation after cardiac death (DCD) livers on post-transplantation costs. Background:DCD livers are increasingly being used to expand the donor pool despite higher complication rates. Although complications after liver transplantation have profound financial implications, the effect of DCD livers on post-transplantation costs has not been studied. Methods:We estimated direct medical care costs based on inpatient and outpatient hospital costs for 28 DCD and 198 donation after brain death (DBD) liver recipients. Organ acquisition and physician costs were excluded. Results:Donor and recipient demographics were comparable for DCD and DBD transplants. One-year, post-transplantation costs were higher for DCD recipients (124.9% of DBD costs, P = 0.04). DCD costs remained higher (125.2% of DBD costs, P = 0.009) after adjusting for recipient characteristics. Furthermore, DCD post-transplantation costs were 30% higher than DBD costs after adjusting for pre-transplantation costs (P = 0.02). Biliary complications (DCD 58% vs. DBD 21%; P < 0.001) and, specifically, ischemic cholangiopathy (DCD 44% vs. DBD 1.6%; P < 0.001) occurred more frequently after DCD transplantation. Moreover, DCD recipients underwent retransplantation more often (DCD 21% vs. DBD 7.1%, P = 0.02). One-year costs were increased for recipients with ischemic cholangiopathy or retransplantation by 53% (P = 0.01) and 107% (P < 0.001), respectively. However, DCD costs continued to be higher when retransplanted patients were excluded (120% of DBD costs, P = 0.02). Conclusions:Higher rates of graft failure and biliary complications translate into markedly increased direct medical care costs for DCD recipients. These important financial implications should be considered in decisions regarding the use of DCD livers.

Understanding the Safety Net: Inpatient Quality of Care Varies Based on How One Defines Safety-Net Hospitals

A challenge to investigating quality of care at safety-net hospitals is the absence of a standard method for identifying these hospitals. The authors identified three different, commonly used approaches for classifying hospitals as safety-net providers. Analyzing national data on hospital demographics and quality of care, they found little overlap among these three sets of hospitals. Under two definitions, safety-net providers clearly underperformed on quality compared with non-safety-net providers; under a third definition, results were mixed. How one defines safety-net providers can affect health services research outcomes and policy recommendations.

Racial and Ethnic Disparities within and between Hospitals for Inpatient Quality of Care: An Examination of Patient-Level Hospital Quality Alliance Measures

Background. Little is known about whether disparities occur within or between hospitals for national Hospital Quality Alliance (HQA) measures. Methods. We examined patient-level data from 4,450 non-federal hospitals in the U.S. for over 2.3 million Black, Hispanic, Asian, American Indian/Alaska Native, and Native Hawaiian/Pacific Islander patients who received care for acute myocardial infarction, heart failure, or pneumonia in 2005. Results. There were 37 out of 95 findings of disparities after adjusting for patient characteristics. Eleven of the disparities were explained entirely by where minorities received care and the magnitude for 25 of the others was substantially reduced after adjusting for site of care. Discussion. Adjusting for between-hospital quality differences accounted for a large proportion of the disparities. Where disparities exist, the primary cause may be that minorities are more likely to receive care in lower-performing hospitals. Policies to reduce disparities should include targeting resources to facilities serving a high percentage of minority patients.

The extent and predictors of waiting time geographic disparity in kidney transplantation in the United States

Background Waiting time to deceased donor kidney transplant varies greatly across the United States. This variation violates the final rule, a federal mandate, which demands geographic equity in organ allocation for transplantation. Methods Retrospective analysis of the United States Renal Data System and United Network for Organ Sharing database from 2000 to 2009. Median waiting time was calculated for each of the 58 donor service areas (DSA) in the United States. Multivariate regression was performed to identify DSA predictors for long waiting times to kidney transplantation. Results The median waiting time varied between the 58 DSAs from 0.61 to 4.57 years, ranging from 0.59 to 5.17 years for standard criteria donor kidneys and 0.41 to 4.69 years for expanded criteria donor kidneys. The disparity in waiting time between the DSAs grew from 3.26 years (range, 0.41–3.67) in 2000 to 4.72 years (range, 0.50–5.22) in 2009. In DSAs with longer waiting times, there were significantly more patients suffering from end-stage renal disease and more patients listed for kidney transplant, lower kidney procurement rates, and higher transplant center competition. Patients were more likely black, sensitized, with lower educational attainment and less likely to waitlist outside of their DSA of residence. Donor organs used in DSAs with long waiting times were more likely hepatitis C positive and had a higher kidney donor profile index. Graft and patient survival at 5 years was worse for deceased donor kidney transplant, but rates for living donor kidney transplant were higher. Conclusion Our analysis demonstrates significant and worsening geographic disparity in waiting time for kidney transplant across the DSAs. Increase in living donor kidney transplant and use of marginal organs has not mitigated the disparity. Changes to the kidney allocation system might be required to resolve this extensive geographic disparity in kidney allocation.

How well can we identify the high-performing hospital?

Sharing lessons from high-performing hospitals facilitates quality improvement. High-performing hospitals have usually been identified using a small number of performance measures. The objective was to analyze how well 1,006 hospitals performed across a broader range of measures. Five measures were developed from publicly available data: adherence to processes of care, 30-day readmission rates, in-hospital mortality, efficiency, and patient satisfaction. For a subset of hospitals, the authors included two survey-based assessments of patient care quality, one by chief quality officers and one by frontline clinicians. In general, there was little correlation among the publicly available measures (r ≤ .10), though there was notable correlation between objective measures and survey-based measures (r = .23). Hospitals that performed well on a composite measure calculated from the publicly available measures were often not in the top quintile on most individual measures. This highlights the challenge in identifying high-performing hospitals to learn organizational-level best practices.

Pay-For-Performance Programs to Reduce Racial/Ethnic Disparities: What Might Different Designs Achieve?

Pay-for-performance (P4P) programs may have unintended effects on racial/ethnic disparities. We used patient-level quality scores from the Hospital Quality Alliance and ranked hospitals by overall quality and by racial/ethnic disparities. We then modeled the effects of different P4P designs on national disparity scores. The models using overall quality to rank hospitals resulted in modest reductions in national disparity scores, although these were smaller than the reductions that were found from programs using disparities to rank hospitals. These results suggest that many hospitals treat Whites and minorities equitably. Nevertheless, in order to maximize both improvements in quality and reductions in national disparities, P4P programs should consider an approach that considers both overall quality and reductions in disparities when setting incentives.

Quality of care provided to individual patients in US hospitals: results from an analysis of national Hospital Quality Alliance data.

Background:There is little national data on the characteristics of patients who receive high quality inpatient care defined as either the receipt of all appliable processes (all-or-none performance) or the proportion of applicable processes received during thier hospitalization. Objectives:To assess the quality of care provided to patients hospitalized for acute myocardial infarction (AMI), heart failure or pneumonia, to describe variations in quality by patient and hospital characteristics, and the sensitivity of all-or-none performance to the number and type of processes. Design and Subjects:Retrospective analysis of previously unavailable Hospital Quality Alliance patient-level data on 2.3 million individuals receiving care in non-federal US hospitals in 2005. Measures:The proportion of patients who received all applicable care processes, and the mean proportion of applicable processes received by hospitalized patients. Results:82.8% of AMI patients, 57.3% of HF patients, and 41.7% of PN patients received all applicable care processes during their hospitalizations. Within each condition, all-or-none performance varied by patient age, race/ethnicity, and admission source, and characteristics of the hospital in which they received care. In addition, patients who were eligible for more processes were less likely to receive all of them, and certain individual processes had large impacts on all-or-none performance. Conclusions:Large numbers of U.S. hospital patients fail to receive all recommended care. All-or-none composites are intriguing indicators of quality; however designers of such systems should address the sensitivity of these composites to both the number and type of individual processes included.

Hospital commitment to community orientation and its association with quality of care and patient experience.

EXECUTIVE SUMMARY We examine the association between hospital community orientation and qualityofcare measures, which include process measures for patients admitted for acute myocardial infarction, heart failure, and pneumonia as well as measures of patient experience. The community orientation measure is obtained from the 2009 American Hospital Associations Annual Survey Database. Information on hospital quality of care and patient experience comes from 2009 Hospital Quality Alliance data and results from the 2009 Hospital Consumer Assessment of Healthcare Providers and Systems (Medicare.gov, 2009). To evaluate the relationship between community orientation and measures of quality and patient experience, we used multivariate linear regressions. Organizational and market control variables included bed size, ownership, teaching status, safety net status, number of nurses per patient day, multihospital system status, network status, extent of reliance on managed care, market competition, and location within an Aligning Forces for Quality community (these communities have multistakeholder alliances and focus on improving quality of care at the community level). After controlling for organizational factors, we found that hospitals with a stronger commitment to community orientation perform better on process measures for all three conditions, and they report higher patient experience of care scores for one measure, than do those demonstrating weaker commitment. Hospital commitment to community orientation is significantly related to the provision of highquality care and to one measure of patient experience of care.

Smoking Cessation Advice Rates in US Hospitals

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