Cold Ischemia Time and Delayed Graft Function in Kidney Transplantation: A Paired Kidney Analysis.

BACKGROUND: We aimed to understand the association between cold ischemia time (CIT) and delayed graft function (DGF) after kidney transplantation and the impact of organ pumping on that association. METHODS: Retrospective cohort study using US registry data. We identified kidney pairs from the same donor where both kidneys were transplanted but had a CIT difference >0 and ≤20 h. We determined the frequency of concordant (both kidneys with/without DGF) or discordant (only 1 kidney DGF) DGF outcomes. Among discordant pairs, we computed unadjusted and adjusted relative risk of DGF associated with longer-CIT status, when then repeated this analysis restricted to pairs where only the longer-CIT kidney was pumped. RESULTS: Among 25 831 kidney pairs included, 71% had concordant DGF outcomes, 16% had only the longer-CIT kidney with DGF, and 13% had only the shorter-CIT kidney with DGF. Among discordant pairs, longer-CIT status was associated with a higher risk of DGF in unadjusted and adjusted models. Among pairs where only the longer-CIT kidney was pumped, longer-CIT kidneys that were pumped had a lower risk of DGF than their contralateral shorter-CIT kidneys that were not pumped regardless of the size of the CIT difference. CONCLUSIONS: Most kidney pairs have concordant DGF outcomes regardless of CIT difference, but even small increases in CIT raise the risk of DGF. Organ pumping may mitigate and even overcome the adverse consequences of prolonged CIT on the risk of DGF, but prospective studies are needed to better understand this relationship.

Association between donor kidney cysts and donor and recipient outcomes after living donor kidney transplantation.

INTRODUCTION: Incidental kidneys cysts are typically considered benign, but the presence of cysts is more frequent in individuals with other early markers of kidney disease. We studied the association of donor kidney cysts with donor and recipient outcomes after living donor kidney transplantation. METHODS: We retrospective identified 860 living donor transplants at our center (1/1/2011-7/31/2022) without missing data. Donor cysts were identified by review of pre-donation CT scan reports. We used linear regression to study the association between donor cysts and 6-month single-kidney estimated glomerular filtration rate (eGFR) increase, and time-to-event analyses to study the association between donor cysts and recipient death-censored graft failure. RESULTS: Among donors, 77% donors had no kidney cysts, 13% had ≥1 cyst on the kidney not donated, and 11% only had cysts on the donated kidney. In adjusted linear regression, cysts on the donated kidney and kidney not donated were not significantly associated with 6-month single-kidney eGFR increase. Among transplants, 17% used a transplanted kidney with a cyst and 6% were from donors with cysts only on the kidney not transplanted. There was no association between donor cyst group and post-transplant death-censored graft survival. Results were similar in sensitivity analyses comparing transplants using kidneys with no cysts versus 1-2 cysts versus ≥3 cysts. CONCLUSIONS: Kidney cysts in living kidney donors were not associated with donor kidney recovery or recipient allograft longevity, suggesting incidental kidney cysts need not be taken into account when determining living donor candidate suitability or the laterality of planned donor nephrectomy.

Impact of Median MELD at Transplant Minus 3 National Policy on Quality of Transplanted Livers for Patients With and Without Hepatocellular Carcinoma.

BACKGROUND: Patients with hepatocellular carcinoma (HCC) have been overprioritized in the deceased donor liver allocation system. The United Network for Organ Sharing adopted a policy in May 2019 that limited HCC exception points to the median Model for End-Stage Liver Disease at transplant in the listing region minus 3. We hypothesized this policy change would increase the likelihood to transplant marginal quality livers into HCC patients. METHODS: This was a retrospective cohort study of a national transplant registry, including adult deceased donor liver transplant recipients with and without HCC from May 18, 2017, to May 18, 2019 (prepolicy) to May 19, 2019, to March 1, 2021 (postpolicy). Transplanted livers were considered of marginal quality if they met ≥1 of the following: (1) donation after circulatory death, (2) donor age ≥70, (3) macrosteatosis ≥30% and (4) donor risk index ≥95th percentile. We compared characteristics across policy periods and by HCC status. RESULTS: A total of 23 164 patients were included (11 339 prepolicy and 11 825 postpolicy), 22.7% of whom received HCC exception points (prepolicy versus postpolicy: 26.1% versus 19.4%; P = 0.03). The percentage of transplanted donor livers meeting marginal quality criteria decreased for non-HCC (17.3% versus 16.0%; P < 0.001) but increased for HCC (17.7% versus 19.4%; P < 0.001) prepolicy versus postpolicy. After adjusting for recipient characteristics, HCC recipients had 28% higher odds of being transplanted with marginal quality liver independent of policy period (odds ratio: 1.28; confidence interval, 1.09-1.50; P < 0.01). CONCLUSIONS: The median Model for End-Stage Liver Disease at transplant in the listing region minus 3 policy limited exception points and decreased the quality of livers received by HCC patients.

Sex-based Disparities in Access to Liver Transplantation for Waitlisted Patients With Model for End-stage Liver Disease Score of 40.

OBJECTIVE: To determine the association of sex with access to liver transplantation among candidates with the highest possible model for end-stage liver disease score (MELD 40). BACKGROUND: Women with end-stage liver disease are less likely than men to receive liver transplantation due in part to MELD's underestimation of renal dysfunction in women. The extent of the sex-based disparity among patients with high disease severity and equally high MELD scores is unclear. METHODS: Using national transplant registry data, we compared liver offer acceptance (offers received at match MELD 40) and waitlist outcomes (transplant vs death/delisting) by sex for 7654 waitlisted liver transplant candidates from 2009 to 2019 who reached MELD 40. Multivariable logistic and competing-risks regression was used to estimate the association of sex with the outcome and adjust for the candidate and donor factors. RESULTS: Women (N = 3019, 39.4%) spent equal time active at MELD 40 (median: 5 vs 5 days, P = 0.28) but had lower offer acceptance (9.2% vs 11.0%, P < 0.01) compared with men (N = 4635, 60.6%). Adjusting for candidate/donor factors, offers to women were less likely accepted (odds ratio = 0.87, P < 0.01). Adjusting for candidate factors, once they reached MELD 40, women were less likely to be transplanted (subdistribution hazard ratio = 0.90, P < 0.01) and more likely to die or be delisted (subdistribution hazard ratio = 1.14, P = 0.02). CONCLUSIONS: Even among candidates with high disease severity and equally high MELD scores, women have reduced access to liver transplantation and worse outcomes compared with men. Policies addressing this disparity should consider factors beyond MELD score adjustments alone.

The Association of Dialysis Facility Payer Mix With Access to Kidney Transplantation.

Importance: Insurance coverage for patients with end-stage kidney disease has shifted toward more commercially insured patients at dialysis facilities. The associations among insurance status, facility-level payer mix, and access to kidney transplantation are unclear. Objective: To determine the association of dialysis facility commercial payer mix and 1-year incidence of wait-listing for kidney transplantation, and to delineate the association of commercial insurance at the patient vs facility level. Design, Setting, and Participants: This retrospective population-based cohort study used data from the United States Renal Data System from 2013 to 2018. Participants included patients aged 18 to 75 years initiating chronic dialysis between 2013 and 2017, excluding patients with a prior kidney transplant or with major contraindications to kidney transplant. Data were analyzed from August 2021 and May 2023. Exposure: Dialysis facility commercial payer mix, calculated as the proportion of patients with commercial insurance per facility. Main Outcomes and Measures: The primary outcome was patients added to a waiting list for kidney transplant within 1 year of dialysis initiation. Multivariable Cox regression, censoring for death, was used to adjust for patient-level (demographic, socioeconomic, and medical) and facility-level factors. Results: A total of 233 003 patients (97 617 [41.9%] female patients; mean [SD] age, 58.0 [12.1] years) across 6565 facilities met inclusion criteria. Participants included 70 062 Black patients (30.1%), 42 820 Hispanic patients (18.4%), 105 368 White patients (45.2%), and 14 753 patients (6.3%) who identified as another race or ethnicity (eg, American Indian or Alaskan Native, Asian, Native Hawaiian or Pacific Islander, and multiracial). Of 6565 dialysis facilities, the mean (SD) commercial payer mix was 21.2% (15.6 percentage points). Patient-level commercial insurance was associated with increased incidence of wait-listing (adjusted hazard ratio [aHR], 1.86; 95% CI, 1.80-1.93; P < .001). At the facility-level and before covariate adjustment, higher commercial payer mix was associated with increased wait-listing (fourth vs first payer mix quartile [Q]: HR, 1.79; 95% CI, 1.67-1.91; P < .001). However, after covariate-adjustment, including adjusting for patient-level insurance status, commercial payer mix was not significantly associated with outcome (Q4 vs Q1: aHR, 1.02; 95% CI, 0.95-1.09; P = .60). Conclusions and Relevance: In this national cohort study of patients newly initiated on chronic dialysis, although patient-level commercial insurance was associated with higher access to the kidney transplant waiting lists, there was no independent association of facility-level commercial payer mix with patients being added to waiting lists for transplant. As the landscape of insurance coverage for dialysis evolves, the potential downstream impact on access to kidney transplant should be monitored.

Increased volume of organ offers and decreased efficiency of kidney placement under circle-based kidney allocation.

The newest kidney allocation policy kidney allocation system 250 (KAS250) broadened geographic distribution while increasing allocation system complexity. We studied the volume of kidney offers received by transplant centers and the efficiency of kidney placement since KAS250. We identified deceased-donor kidney offers (N = 907,848; N = 36,226 donors) to 185 US transplant centers from January 1, 2019, to December 31, 2021 (policy implemented March 15, 2021). Each unique donor offered to a center was considered a single offer. We compared the monthly volume of offers received by centers and the number of centers offered before the first acceptance using an interrupted time series approach (pre-/post-KAS250). Post-KAS250, transplant centers received more kidney offers (level change: 32.5 offers/center/mo, P < .001; slope change: 3.9 offers/center/mo, P = .003). The median monthly offer volume post-/pre-KAS250 was 195 (interquartile range 137-253) vs. 115 (76-151). There was no significant increase in deceased-donor transplant volume at the center level after KAS250, and center-specific changes in offer volume did not correlate with changes in transplant volume (r = -0.001). Post-KAS250, the number of centers to whom a kidney was offered before acceptance increased significantly (level change: 1.7 centers/donor, P < .001; slope change: 0.1 centers/donor/mo, P = .014). These findings demonstrate the logistical burden of broader organ sharing, and future allocation policy changes will need to balance equity in transplant access with the operational efficiency of the allocation system.

Organ Donation and Transplants During Major US Motorcycle Rallies.

Importance: Large-scale motorcycle rallies attract thousands of attendees and are associated with increased trauma-related morbidity and mortality. Objective: To examine the association of major US motorcycle rallies with the incidence of organ donation and transplants. Design, Setting, and Participants: This population-based, retrospective cross-sectional study used data from the Scientific Registry of Transplant Recipients for deceased organ donors aged 16 years or older involved in a motor vehicle crash and recipients of organs from these donors from March 2005 to September 2021. Exposure: Dates of 7 large US motorcycle rallies and regions near these events. Main Outcomes and Measures: The main outcomes were incidence of motor vehicle crash-related organ donation and number of patients receiving a solid organ transplant from these donors. An event study design was used to estimate adjusted rates of organ donation during the dates of 7 major US motorcycle rallies compared with the 4 weeks before and after the rallies in rally-affected and rally-unaffected (control) regions. Donor and recipient characteristics and metrics of organ quality were compared between rally and nonrally dates. Results: The study included 10 798 organ donors (70.9% male; mean [SD] age, 32.5 [13.7] years) and 35 329 recipients of these organs (64.0% male; 49.3 [15.5] years). During the rally dates, there were 406 organ donors and 1400 transplant recipients. During the 4 weeks before and after the rallies, there were 2332 organ donors and 7714 transplant recipients. Donors and recipients during rally and nonrally dates were similar in demographic and clinical characteristics, measures of organ quality, measures of recipient disease severity, and recipient waiting time. During rallies, there were 21% more organ donors per day (incidence rate ratio [IRR], 1.21; 95% CI, 1.09-1.35; P = .001) and 26% more transplant recipients per day (IRR, 1.26; 95% CI, 1.12-1.42; P < .001) compared with the 4 weeks before and after the rallies in the regions where they were held. Conclusions and Relevance: In this cross-sectional study, major motorcycle rallies in the US were associated with increased incidence of organ donation and transplants. While safety measures to minimize morbidity and mortality during motorcycle rallies should be prioritized, this study showed the downstream association of these events with organ donation and transplants.

The New Distance-Based Kidney Allocation System: Implications for Patients, Transplant Centers, and Organ Procurement Organizations.

Purpose of Review: The goal of deceased donor kidney allocation policy is to provide objective prioritization for donated kidneys, and policy has undergone a series of revisions in the past decade in attempt to achieve equity and utility in access to kidney transplantation. Most recently, to address geographic disparities in access to kidney transplantation, the Kidney Allocation System changed to a distance-based allocation system-colloquially termed "KAS 250"-moving away from donor service areas as the geographic basis of allocation. We review the early impact of this policy change on access to transplant for patients, and on complexity of organ allocation and transplantation for transplant centers and organ procurement organizations. Recent Findings: Broader sharing of kidneys has increased complexity of the allocation system, as transplant centers and OPOs now interact in larger networks. The increased competition resulting from this system, and the increased operational burden on centers and OPOs resulting from greater numbers of organ offers, may adversely affect organ utilization. Preliminary results suggest an increase in transplant rate overall but a trend toward higher kidney discard and increased cold ischemia time. Summary: The KAS 250 allocation policy changed the geographic basis of deceased donor kidney distribution in a manner that is intended to reduce geographic disparities in access to kidney transplantation. Close monitoring of this policy's impact on patients, transplant center behavior, and process measures is critical to the aim of maximizing access to transplant while achieving transplant equity.

Influence of organ quality on the observed association between deceased donor kidney procurement biopsy findings and graft survival.

Deceased donor kidney procurement biopsies findings are the most common reason for kidney discard. Retrospective studies have found inconsistent associations with post-transplant outcomes but may have been limited by selection bias because kidneys with advanced nephrosclerosis from high-risk donors are typically discarded. We conducted a retrospective cohort study of kidneys transplanted in the United States from 2015 to 2019 with complete biopsy data available, defining "suboptimal histology" as glomerulosclerosis ≥11%, IFTA ≥mild, and/or vascular disease ≥mild. We used time-to-event analyses to determine the association between suboptimal histology and death-censored graft failure after stratification by kidney donor profile index (KDPI) (≤35%, 36%-84%, ≥85%) and final creatinine (<1 mg/dl, 1-2 mg/dl, >2 mg/dl). Among 30 469 kidneys included, 36% had suboptimal histology. In adjusted analyses, suboptimal histology was associated with death-censored graft failure among kidneys with KDPI 36-84% (HR 1.22, 95% CI 1.09-1.36), but not KDPI≤35% (HR 1.24, 0.94-1.64) or ≥ 85% (HR 0.99, 0.81-1.22). Similarly, suboptimal histology was associated with death-censored graft failure among kidneys from donors with creatinine 1-2 mg/dl (HR 1.39, 95% CI 1.20-1.60) but not <1 mg/dl (HR 1.07, 0.93-1.23) or >2 mg/dl (HR 0.95, 0.75-1.20). The association of procurement histology with graft longevity among intermediate-quality kidneys that were likely to be both biopsied and transplanted suggests biopsies provide independent organ quality assessments.

Anastomosis Time and Outcomes after Donation after Circulatory Death Kidney Transplantation.

BACKGROUND: At every stage in the transplantation process for a deceased-donor kidney, time means ischemia. Donation after circulatory death (DCD) kidneys are already subject to warm ischemia in the donor, but another underappreciated component of warm ischemia time is the time required for anastomosis prior to reperfusion. We studied the effect of anastomosis time (AT) on outcomes after DCD kidney transplantation. STUDY DESIGN: This is a retrospective study of the Scientific Registry of Transplant Recipients, including all US adult DCD kidney transplantation recipients from 2009 to 2015 (N = 6,397). Our exposure was AT (time out of cold storage until reperfusion, quartiles). Outcomes included delayed graft function (DGF), death-censored graft survival, and overall patient survival. Multivariable logistic and Cox regression quantified the association of AT with outcomes, adjusting for donor and recipient factors (including donor warm ischemia time). RESULTS: AT accounted for 67% of total warm ischemia time on average, with a median AT of 38 minutes (median total warm ischemia 56 minutes). Longer AT (fourth [≥48min] vs first quartile [≤30min]) was associated with increased DGF (odds ratio = 1.19, p = 0.024) and increased graft failure (hazard ratio = 1.21, p = 0.043) but was not associated with patient survival. Comparing patients with the longest vs shortest AT, adjusted DGF incidence was 44.0% vs 36.7% (p = 0.024), and 5-year graft survival was 84.8% vs 88.2% (p = 0.004). CONCLUSION: Prolonged AT is associated with worse graft outcomes in DCD kidney transplant recipients. Efforts to minimize rewarming during implantation and optimize AT may improve graft outcomes.

Association of transplant center market concentration and local organ availability with deceased donor kidney utilization.

Although there is a shortage of kidneys available for transplantation, many transplantable kidneys are not procured or are discarded after procurement. We investigated whether local market competition and/or organ availability impact kidney procurement/utilization. We calculated the Herfindahl-Hirschman Index (HHI) for deceased donor kidney transplants (2015-2019) for 58 US donation service areas (DSAs) and defined 4 groups: HHI ≤ 0.32 (high competition), HHI = 0.33-0.51 (medium), HHI = 0.53-0.99 (low), and HHI = 1 (monopoly). We calculated organ availability for each DSA as the number kidneys procured per incident waitlisted candidate, grouped as: <0.42, 0.42-0.69, >0.69. Characteristics of procured organs were similar across groups. In adjusted logistic regression, the HHI group was inconsistently associated with composite export/discard (reference: high competition; medium: OR 1.16, 95% CI 1.11-1.20; low 1.01, 0.96-1.06; monopoly 1.19, 1.13-1.26) and increasing organ availability was associated with export/discard (reference: availability <0.42; 0.42-0.69: OR 1.35, 95% CI 1.30-1.40; >0.69: OR 1.83, 95% CI 1.73-1.93). When analyzing each endpoint separately, lower competition was associated with higher export and only market monopoly was weakly associated with lower discard, whereas higher organ availability was associated with export and discard. These results indicate that local organ utilization is more strongly influenced by the relative intensity of the organ shortage than by market competition between centers.

Association of balanced abdominal organ transplant center volumes with patient outcomes.

BACKGROUND: The volume-outcome relationship for organ-specific transplantation is well-described; it is unknown if the relative balance of kidney compared with liver volumes within an institution relates to organ-specific outcomes. We assessed the association between relative balance within a transplant center and outcomes. METHODS: National retrospective analysis of isolated kidney and liver transplants in United States 2005-2014 followed through 2019. Latent class analysis defined transplant center phenotypes. Multivariate Cox models estimated death-censored graft loss and mortality. RESULTS: Latent class analysis identified four phenotypes: kidney only (n = 117), kidney dominant (n = 36), mixed/balanced (n = 90), and liver dominant (n = 13). Compared to mixed centers, the risk of kidney graft loss was higher at kidney-dominant (HR 1.07, p < .001) and liver-dominant (HR 1.10, p < .001) centers, while kidney-only (HR 1.06, p = .01) centers had higher mortality. Liver graft loss was not associated with phenotype, but risk of patient death was lower (HR 0.93, p = .02) at liver dominant and higher (HR 1.06, p = .02) at kidney-dominant centers. CONCLUSIONS: A mixed phenotype was associated with improved kidney transplant outcomes, whereas liver transplant outcomes were best at liver-dominant centers. While these findings need to be verified with center-level resources, optimization of shared resources could improve patient and organ outcomes.

Prevalence and Patterns of Opioid Use Before and After Liver Transplantation.

BACKGROUND: Opioid use in liver transplantation is poorly understood and has potential associated morbidity. METHODS: Using a national data set of employer-based insurance claims, we identified 1257 adults who underwent liver transplantation between December 2009 and February 2015. We categorized patients based on their duration of opioid fills over the year before and after transplant admission as opioid-naive/no fills, chronic opioid use (≥120 d supply), and intermittent use (all other use). We calculated risk-adjusted prevalence of peritransplant opioid fills, assessed changes in opioid use after transplant, and identified correlates of persistent or increased opioid use posttransplant. RESULTS: Overall, 45% of patients filled ≥1 opioid prescription in the year before transplant (35% intermittent use, 10% chronic). Posttransplant, 61% of patients filled an opioid prescription 0-2 months after discharge, and 21% filled an opioid between 10-12 months after discharge. Among previously opioid-naive patients, 4% developed chronic use posttransplant. Among patients with pretransplant opioid use, 84% remained intermittent or increased to chronic use, and 73% of chronic users remained chronic users after transplant. Pretransplant opioid use (risk factor) and hepatobiliary malignancy (protective) were the only factors independently associated with risk of persistent or increased posttransplant opioid use. CONCLUSIONS: Prescription opioid use is common before and after liver transplant, with intermittent and chronic use largely persisting, and a small development of new chronic use posttransplant. To minimize the morbidity of long-term opioid use, it is critical to improve pain management and optimize opioid use before and after liver transplant.

The Association Between Preoperative Opioid Exposure and Prolonged Postoperative Use.

OBJECTIVE: To determine the effect of nonchronic, periodic preoperative opioid use on prolonged opioid fills after surgery. BACKGROUND: Nonchronic, periodic opioid use is common, but its effect on prolonged postoperative opioid fills is not well understood. We hypothesize greater periodic opioid use before surgery is correlated with persistent postoperative use. METHODS: We used a national private insurance claims database, Optum's de-identifed Clinformatics Data Mart Database, to identify adults undergoing general, gynecologic, and urologic surgical procedures between 2008 and 2015 (N = 191,043). We described patterns of opioid fills based on dose, recency, duration, and continuity to categorize preoperative opioid exposure. Patients with chronic use were excluded. Our primary outcome was persistent postoperative use, defined as filling an opioid prescription between 91- and 180-days post-discharge. The association between preoperative opioid use and persistent use was determined using multivariable logistic regression, controlling for clinical covariates. RESULTS: In the year before surgery, 41% of patients had nonchronic, periodic opioid fills. Compared with other risk factors, patterns of preoperative fills were most strongly correlated with persistent postoperative opioid use. Patients with recent intermittent use were significantly more likely to have prolonged fills after surgery compared with opioid-naïve patients [minimal use: odds ratio (OR): 2.0, 95% confidence interval (CI) 1.89-2.03; remote intermittent: OR 4.7, 95% CI 4.46-4.93; recent intermittent: OR 12.2, 95% CI 11.49-12.90]. CONCLUSIONS: Patients with nonchronic, periodic opioid use before surgery are vulnerable to persistent postoperative opioid use. Identifying opioid use before surgery is a critical opportunity to optimize care after surgery.

Classifying Preoperative Opioid Use for Surgical Care.

OBJECTIVE: We characterized patterns of preoperative opioid use in patients undergoing elective surgery to identify the relationship between preoperative use and subsequent opioid fill after surgery. BACKGROUND: Preoperative opioid use is common, and varies by dose, recency, duration, and continuity of fills. To date, there is little evidence to guide postoperative prescribing need based on prior opioid use. METHODS: We analyzed claims data from Clinformatics DataMart Database for patients aged 18 to 64 years undergoing major and minor surgery between 2008 and 2015. Preoperative use was defined as any opioid prescription filled in the year before surgery. We used cluster analysis to group patients by the dose, recency, duration, and continuity of use. Our primary outcome was second postoperative fill within 30 postoperative days. Our primary explanatory variable was opioid use group. We used logistic regression to examine likelihood of second fill by opioid use group. RESULTS: Out of 267,252 patients, 102,748 (38%) filled an opioid prescription in the 12 months before surgery. Cluster analysis yielded 6 groups of preoperative opioid use, ranging from minimal (27.6%) to intermittent (7.7%) to chronic use (2.7%). Preoperative opioid use was the most influential predictor of second fill, with larger effect sizes than other factors even for patients with minimal or intermittent opioid use. Increasing preoperative use was associated with risk-adjusted likelihood of requiring a second opioid fill compared with naive patients [minimal use: odds ratio (OR) 1.49, 95% confidence interval (95% CI) 1.45-1.53; recent intermittent use: OR 6.51, 95% CI 6.16-6.88; high chronic use: OR 60.79, 95% CI 27.81-132.92, all P values <0.001). CONCLUSION: Preoperative opioid use is common among patients who undergo elective surgery. Although the majority of patients infrequently fill opioids before surgery, even minimal use increases the probability of needing additional postoperative prescriptions in the 30 days after surgery when compared with opioid-naive patients. Going forward, identifying preoperative opioid use can inform surgeon prescribing and care coordination for pain management after surgery.

Provider Characteristics Associated With Outpatient Opioid Prescribing After Surgery.

OBJECTIVE: To characterize differences in postoperative opioid prescribing across surgical, nonsurgical, and advanced practice providers. BACKGROUND: There is a critical need to identify best practices around perioperative opioid prescribing. To date, differences in postoperative prescribing among providers are poorly understood. METHODS: This is a retrospective multicenter analysis of commercial insurance claims from a statewide quality collaborative. We identified 15,657 opioid-naïve patients who underwent a range of surgical procedures between January 2012 and October 2015 and filled an opioid prescription within 30 days postoperatively. Our primary outcome was total amount of opioid filled per prescription within 30 days postoperatively [in oral morphine equivalents (OME)]. Hierarchical linear regression was used to determine the association between provider characteristics [specialty, advanced practice providers (nurse practitioners and physician assistants) vs. physician, and gender] and outcome while adjusting for patient factors. RESULTS: Average postoperative opioid prescription amount was 326 ± 285 OME (equivalent: 65 tablets of 5 mg hydrocodone). Advanced practice providers accounted for 19% of all prescriptions, and amount per prescription was 18% larger in this group compared with physicians (315 vs. 268, P < 0.001). Primary care providers accounted for 13% of all prescriptions and prescribed on average 279 OME per prescription. The amount of opioid prescribed varied by surgical specialty and ranged from 178 OME (urology) to 454 OME (neurosurgery). CONCLUSIONS: Advanced practice providers account for 1-in-5 postoperative opioid prescriptions and prescribe larger amounts per prescription relative to surgeons. Engaging all providers involved in postoperative care is necessary to understand prescribing practices, identify barriers to reducing prescribing, and tailor interventions accordingly.

A statewide comparison of opioid prescribing in teaching versus nonteaching hospitals.

BACKGROUND: Postoperative opioid prescribing is often excessive, but the differences in opioid prescribing between teaching hospitals and nonteaching hospitals is not well understood. Given the workload of surgical training and frequent turnover of prescribers on surgical services, we hypothesized that postoperative opioid prescribing would be higher among teaching compared with nonteaching hospitals. STUDY DESIGN: We used insurance claims from a statewide quality collaborative in Michigan to identify 17,075 opioid-naïve patients who underwent 22 surgical procedures across 76 hospitals from 2012 to 2016. Our outcomes included the following: (1) the amount of opioid prescribed for the initial postoperative prescription in oral morphine equivalents and (2) high-risk prescribing in the 30 days after surgery (high daily dose [≥ 100 oral morphine equivalents], new long-acting/extended-release opioid, overlapping prescriptions, or concurrent benzodiazepine prescription). Teaching hospital status was obtained from the 2014 American Hospital Association survey. Multilevel regression was used to adjust for patient and procedural factors and to perform reliability adjustment. RESULTS: The amount of opioid prescribed per initial opioid prescription varied 4.7-fold across all hospitals from 130 oral morphine equivalents to 616 oral morphine equivalents. Patients discharged from teaching hospitals filled larger initial opioid prescriptions overall compared with nonteaching hospitals (251 oral morphine equivalents versus 232 oral morphine equivalents; P = .026). Teaching hospitals had higher risk-adjusted rates of high-risk prescribing compared with nonteaching hospitals (13.7% vs 10.3%; P = .034). CONCLUSION: In Michigan, surgical patients discharged from teaching hospitals received significantly larger postoperative opioid prescriptions and had higher rates of high-risk prescribing compared with nonteaching hospitals. All hospitals, and particularly teaching institutions, should ensure that adequate resources are devoted to facilitating safe postoperative opioid prescribing.