Therese Bittermann

Association of Distance From a Transplant Center With Access to Waitlist Placement, Receipt of Liver Transplantation, and Survival Among US Veterans

IMPORTANCE Centralization of specialized health care services such as organ transplantation and bariatric surgery is advocated to improve quality, increase efficiency, and reduce cost. The effect of increased travel on access and outcomes from these services is not fully understood. OBJECTIVE To evaluate the association between distance from a Veterans Affairs (VA) transplant center (VATC) and access to being waitlisted for liver transplantation, actually having a liver transplant, and mortality. DESIGN, SETTING, AND PARTICIPANTS Retrospective study of veterans meeting liver transplantation eligibility criteria from January 1, 2003, until December 31, 2010, using data from the Veterans Health Administrations integrated, national, electronic medical record linked to Organ Procurement and Transplantation Network data. MAIN OUTCOMES AND MEASURES The primary outcome was being waitlisted for transplantation at a VATC. Secondary outcomes included being waitlisted at any transplant center, undergoing a transplantation, and survival. RESULTS From 2003-2010, 50,637 veterans were classified as potentially eligible for transplant; 2895 (6%) were waitlisted and 1418 of those were waitlisted (49%) at 1 of the 5 VATCs. Of 3417 veterans receiving care at a VA hospital located within 100 miles from a VATC, 244 (7.1%) were waitlisted at a VATC and 372 (10.9%) at any transplant center (VATC and non-VATCs). Of 47,219 veterans receiving care at a VA hospital located more than 100 miles from a VATC, 1174 (2.5%) were waitlisted at a VATC and 2523 (5.3%) at any transplant center (VATC and non-VATCs). In multivariable models, increasing distance to closest VATC was associated with significantly lower odds of being waitlisted at a VATC (odds ratio [OR], 0.91 [95% CI, 0.89-0.93] for each doubling in distance) or any transplant center (OR, 0.94 [95% CI, 0.92-0.96] for each doubling in distance). For example, a veteran living 25 miles from a VATC would have a 7.4% (95% CI, 6.6%-8.1%) adjusted probability of being waitlisted, whereas a veteran 100 miles from a VATC would have a 6.2% (95% CI, 5.7%-6.6%) adjusted probability. In adjusted models, increasing distance from a VATC was associated with significantly lower transplantation rates (subhazard ratio, 0.97; 95% CI, 0.95-0.98 for each doubling in distance). There was significantly increased mortality among waitlisted veterans from the time of first hepatic decompensation event in multivariable survival models (hazard ratio, 1.03; 95% CI, 1.01-1.04 for each doubling in distance). For example, a waitlisted veteran living 25 miles from a VATC would have a 62.9% (95% CI, 59.1%-66.1%) 5-year adjusted probability of survival from first hepatic decompensation event compared with a 59.8% (95% CI, 56.3%-63.1%) 5-year adjusted probability of survival for a veteran living 100 miles from a VATC. CONCLUSIONS AND RELEVANCE Among VA patients meeting eligibility criteria for liver transplantation, greater distance from a VATC or any transplant center was associated with lower likelihood of being waitlisted, receiving a liver transplant, and greater likelihood of death. The relationship between these findings and centralizing specialized care deserves further investigation.

Lack of Standardization in Exception Points for Patients with Primary Sclerosing Cholangitis and Bacterial Cholangitis

For conditions that the Model for End‐Stage Liver Disease (MELD) score does not accurately predict waitlist mortality, transplant centers may apply to regional review boards for exception points. For patients with primary sclerosing cholangitis (PSC) suffering from bacterial cholangitis, consensus recommendations published in December 2006 are to grant exception points for recurrent cholangitis with ≥2 episodes of bacteremia or ≥1 episode septic complications. Using data provided by the United Network for Organ Sharing, we evaluated PSC patients who applied for exception points due to bacterial cholangitis from February 27, 2002 to March 14, 2011. Before publication of the recommendations, 66.0% of applications were accepted, compared with 80.1% after (p < 0.001). Focusing on applications after publication of the recommendations, 311 (74.6%) did not meet the recommended criteria, and 250 (80.4%) of these were approved. Of patients with approved applications, those not meeting consensus criteria were more likely to be transplanted, (77.4% vs. 62.8%, p = 0.043), whereas those with denied applications for approved indications were more liked to die/be removed (44.4% vs. 9.5%, p = 0.49). Although data are needed to properly identify those patients at highest risk for waitlist mortality, standardized criteria or a centralized review board should be adopted to ensure consistency in the granting of exception points.

Center variation in the use of nonstandardized model for end‐stage liver disease exception points

The Model for End‐Stage Liver Disease (MELD) score is an imperfect prognosticator of waitlist dropout, so transplant centers may apply for exception points to increase a waitlist candidates priority on the waitlist. Exception applications are categorized as recognized exceptional diagnoses (REDs; eg, hepatocellular carcinoma) and non‐REDs (eg, cholangitis). Although prior work has demonstrated regional variation in the use of exceptions, no work has examined the between‐center variability. We analyzed all new waitlist candidates from February 27, 2002 to June 3, 2011 to explore variations in the use of non‐REDs, for which no strict exception criteria exist. There were 58,641 new waitlist candidates, and 4356 (7.4%) applied for a non‐RED exception. The number of applications increased steadily over time, as did the approval rates for such applications: from <50% in 2002 to nearly 75% in 2010. When we adjusted for patient factors, there was significant variability (P < 0.001) in the use of non‐RED exceptions in 8 of 11 United Network for Organ Sharing (UNOS) regions and in the approval of these exceptions in 6 of 11 UNOS regions. The variability in the use and approval of non‐REDs was clinically significant: waitlist candidates with approved exceptions were significantly more likely to undergo transplantation (68.3% versus 53.4%, P < 0.001) and were less likely to be removed for death or clinical deterioration (10.4% versus 16.2%, P < 0.001). Increased median MELD score at transplantation within a donor service area was the only center factor associated with increased odds of applying for exceptions, while no center factors were associated with having non‐RED exceptions approved. Further work is needed to identify other sources of variation to ensure the appropriate and equitable use of non‐RED exceptions. Liver Transpl 19:1330–1342, 2013.

Waitlist priority for hepatocellular carcinoma beyond milan criteria: a potentially appropriate decision without a structured approach.

Due to the risk of waitlist dropout from tumor progression, liver transplant candidates with hepatocellular carcinoma (HCC) within Milan criteria (MC) receive standardized exception points. An expansion of this process to candidates with HCC beyond MC has been proposed, though it remains controversial. This study sought to better define the utilization of exception points in candidates with HCC beyond MC and the associated outcomes. We reviewed all nonstandardized HCC applications that underwent formal regional review board evaluation between January 1, 2005 and March 2, 2011; 2184 initial HCC exception point applications were submitted. Of these, 41.9% fulfilled MC, 26.6% fulfilled University of California‐San Francisco (UCSF) criteria and 17.6% exceeded UCSF criteria. The majority of applications were accepted: 89.8% within UCSF and 71.2% beyond UCSF. There was a significantly (p < 0.001) higher risk of death on the waitlist or within 90 days of waitlist removal for candidates within UCSF (12.4%) or beyond UCSF (13.0%) criteria, compared to candidates with HCC within MC (6.0%). However, posttransplant outcomes were similar. While these results suggest increasing access to candidates with HCC beyond MC, comprehensive documentation of tumor characteristics and of successful downstaging is needed to ensure priority is restricted to those with the highest likelihood of favorable posttransplant outcome.

Early post-transplant survival: Interaction of MELD score and hospitalization status

BACKGROUND & AIMS Urgency-based allocation that relies on the MELD score prioritizes patients at the highest risk of waitlist mortality. However, identifying patients at greatest risk for short-term post-transplant mortality is needed in order to optimize the potential gains in overall survival obtained through improved long-term management of transplant recipients. There are limited data on the predictive ability of MELD score for early post-transplant mortality, and no data assessing the interaction between MELD score and hospitalization status. METHODS We analyzed UNOS data from 2002 to 2013 on 50,838 non-status 1 single-organ liver transplant recipients and fit multivariable logistic models to evaluate the association and interaction between MELD score and pre-transplant hospitalization status on short-term post-transplant mortality. RESULTS There was a significant interaction (p<0.01) between laboratory MELD score and hospitalization status on three-, six-, and 12-month post-transplant mortality in multivariable logistic models. This interaction was most pronounced in patients with a laboratory MELD score <25 transplanted from an ICU, whose adjusted predicted three-, six-, and 12-month post-transplant mortality approximated those of patients with a MELD score ⩾30. Compared to hospitalized patients with a MELD score of 30-34, those with a MELD score ⩾35 in an ICU had significantly increased risk of three-month (OR: 1.54, 95% CI: 1.21-1.97), 6-month (OR: 1.35, 95% CI: 1.09-1.67), and 12-month (OR: 1.25, 95% CI: 1.03-1.52) post-transplant mortality. DISCUSSION Pre-transplant ICU status modifies the risk of early post-transplant mortality, independent of MELD score. This should be considered when determining candidacy for transplantation in order to optimize efficient use of a scarce resource.

Exception point applications for 15 points: An unintended consequence of the Share 15 policy†

In 2005, the United Network for Organ Sharing (UNOS) adopted the Share 15 policy to improve organ allocation by facilitating transplantation for local and regional patients with Model for End‐Stage Liver Disease (MELD) scores of 15 or higher. There has been concern that the lack of standardization in the use of exception points is potentially diminishing the benefits of this policy. We reviewed all applications for 15 exception points submitted through UNOS from January 1, 2005 through March 14, 2011 (notably, there were only 5 applications for 15 MELD exception points submitted before the initiation of the Share 15 policy). Four hundred fifty‐two applications were submitted for 301 patients. There was significant regional variability, with regions 3 and 10 submitting 72.1% of all applications. More than one‐quarter of the applications (32.7%) specifically requested exception points to make a patient eligible for a local, regional, or higher risk organ. All applications were accepted for 74.1% of the patients, and 72.2% of these patients ultimately underwent transplantation; however, when all applications were denied, only 54.0% underwent transplantation (P = 0.006). Overall, 197 applicants (65.4%) underwent transplantation with a deceased donor organ, and 80.2% of these patients had a native MELD score at transplantation less than 15. In conclusion, these analyses demonstrate several important changes in practice that have occurred as a result of the implementation of the Share 15 policy. Since 2005, there has been a marked increase in the number of applications for 15 exception points, with significant regional variability in their use and a lack of standardization in their approval. Liver Transpl, 2012.

The Kidney Allocation System Does Not Appropriately Stratify Risk of Pediatric Donor Kidneys: Implications for Pediatric Recipients

Kidney Allocation System (KAS) was enacted in 2014 to improve graft utility, while facilitating transplantation of highly‐sensitized patients and preserving pediatric access to high‐quality kidneys. Central to this system is the Kidney Donor Profile Index (KDPI), a metric intended to predict transplant outcomes based on donor characteristics but derived using only adult donors. We posited that KAS had inadvertently altered the profile and quantity of kidneys made available to pediatric recipients. This question arose from our observation that most pediatric donors carry a KDPI over 35 and have therefore been rendered relatively inaccessible to pediatric recipients under KAS. Here we explore early trends in pediatric transplantation following KAS, including: (i) use of pediatric donors, (ii) use of Public Health System (PHS) high infectious risk donors, (iii) wait time, and (iv) living donor transplantation. We note some concerning preliminary changes following KAS implementation, including the allocation of fewer deceased donor pediatric kidneys to children and stagnation in pediatric wait times. Moreover, the poor predictive power of the KDPI for adult donors appears to be even worse when applied to pediatric donors. These early trends warrant further observation and consideration of changes in pediatric kidney allocation if they persist.

A Medical Resident–Pharmacist Collaboration Improves the Rate of Medication Reconciliation Verification at Discharge

BACKGROUND At the Hospital of the University of Pennsylvania (Philadelphia), it is standard practice to perform medication reconciliation at patient discharge. Although pharmacists historically were available to assist resident physicians in the discharge medication reconciliation process, the process was never standardized. An internal review showed a 60%-70% rate of pharmacist review of discharge medication lists, potentially enabling medication errors to go unnoticed during transitions of care. In response, a medical resident- and pharmacist-led collaboration was designed, and a pre-post-intervention study was conducted to assess its effectiveness. METHODS A new work flow was established in which house staff notified pharmacists when a preliminary discharge medication list was ready for reconciliation and provided access for pharmacists to correct medication errors in the electronic discharge document with physician approval. Length of stay, average time of day of patient discharge, and readmission data were compared in the pre- and post-intervention periods. RESULTS There were 981 discharges in the preintervention period and 1,207 in the postintervention period. The rate of pharmacist reconciliation increased from 64.0% to 82.4% after the intervention (p<.0001). The average number of errors identified and corrected by pharmacists decreased from 0.979 to 0.862 per discharge (p<.0001). There was no significant change in readmission rates or time of discharge after the intervention. CONCLUSIONS Redesigning the discharge medication reconciliation process in a teaching hospital to include a review of medical resident discharge medication lists by pharmacists provided more opportunities for discharge medication error identification and correction.

Healthcare utilization after liver transplantation is highly variable among both centers and recipients

The relationship between healthcare utilization before and after liver transplantation (LT), and its association with center characteristics, is incompletely understood. This was a retrospective cohort study of 34 402 adult LTs between 2002 and 2013 using Vizient inpatient claims data linked to the United Network for Organ Sharing (UNOS) database. Multivariable mixed‐effects linear regression models evaluated the association between hospitalization 90 days pre‐LT and the number of days alive and out of the hospital (DAOH) 1 year post‐LT. Of those patients alive at LT discharge, 24.7% spent ≥30 days hospitalized during the first year. Hospitalization in the 90 days pre‐LT was inversely associated with DAOH (β = −3.4 DAOH/week hospitalized pre‐LT; P = .002). Centers with >30% of their liver transplant recipients hospitalized ≥30 days in the first LT year were typically smaller volume and/or transplanting higher risk recipients (Model for End‐Stage Liver Disease [MELD] score ≥35, inpatient or ventilated pre‐LT). In conclusion, pre‐LT hospitalization predicts 1‐year post‐LT hospitalization independent of MELD score at the patient‐level, whereas center‐specific post‐LT healthcare utilization is associated with certain center behaviors and selection practices.

Functional status, healthcare utilization, and the costs of liver transplantation

The Model for End‐Stage Liver Disease (MELD) score predicts higher transplant healthcare utilization and costs; however, the independent contribution of functional status towards costs is understudied. The study objective was to evaluate the association between functional status, as measured by Karnofsky Performance Status (KPS), and liver transplant (LT) costs in the first posttransplant year. In a cohort of 598 LT recipients from July 1, 2009 to November 30, 2014, multivariable models assessed associations between KPS and outcomes. LT recipients needing full assistance (KPS 10%‐40%) vs being independent (KPS 80%‐100%) were more likely to be discharged to a rehabilitation facility after LT (22% vs 3%) and be rehospitalized within the first posttransplant year (78% vs 57%), all P < .001. In adjusted generalized linear models, in addition to MELD (P < .001), factors independently associated with higher 1‐year post‐LT transplant costs were older age, poor functional status (KPS 10%‐40%), living donor LT, pre‐LT hemodialysis, and the donor risk index (all P < .001). One‐year survival for patients in the top cost decile was 83% vs 93% for the rest of the cohort (log rank P < .001). Functional status is an important determinant of posttransplant resource utilization; therefore, standardized measurements of functional status should be considered to optimize candidate selection and outcomes.