An Advanced Practice Practitioner–Based Program to Reduce 30‐ and 90‐Day Readmissions After Liver Transplantation

Mahmud, Nadim; Halpern, Samantha; Farrell, Rebecca Trantowski; Ventura, Kate; Thomasson, Arwin; Lewis, Heather; Olthoff, Kim M.; Levine, Matthew H.; Nazarian, Susanna M.; Khungar, Vandana

doi:10.1002/lt.25466

Cited by 21 publications

(25 citation statements)

References 19 publications

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“…Further, patients with cognitive impairment were necessarily excluded due to their lack of consenting capacity, so our results may not apply as directly to that population. While our response rate of 57% for the patient survey compares favorably with similarly designed surveys—e.g., H-CAHPS surveys of patient experience typically average approximately 30% response rate [ 52 ]--the possibility remains that participants were systematically different than non-participants in ways that we were unable to measure. Because patients were initially recruited by hospitals, and not formally consented until contacted for the survey, we were unable to collect demographic information about those who did not consent.…”

Section: Discussionmentioning

confidence: 99%

Improving evidence-based grouping of transitional care strategies in hospital implementation using statistical tools and expert review

Clouser

et al. 2021

BMC Health Serv Res

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Background As health systems transition to value-based care, improving transitional care (TC) remains a priority. Hospitals implementing evidence-based TC models often adapt them to local contexts. However, limited research has evaluated which groups of TC strategies, or transitional care activities, commonly implemented by hospitals correspond with improved patient outcomes. In order to identify TC strategy groups for evaluation, we applied a data-driven approach informed by literature review and expert opinion. Methods Based on a review of evidence-based TC models and the literature, focus groups with patients and family caregivers identifying what matters most to them during care transitions, and expert review, the Project ACHIEVE team identified 22 TC strategies to evaluate. Patient exposure to TC strategies was measured through a hospital survey (N = 42) and prospective survey of patients discharged from those hospitals (N = 8080). To define groups of TC strategies for evaluation, we performed a multistep process including: using ACHIEVE’S prior retrospective analysis; performing exploratory factor analysis, latent class analysis, and finite mixture model analysis on hospital and patient survey data; and confirming results through expert review. Machine learning (e.g., random forest) was performed using patient claims data to explore the predictive influence of individual strategies, strategy groups, and key covariates on 30-day hospital readmissions. Results The methodological approach identified five groups of TC strategies that were commonly delivered as a bundle by hospitals: 1) Patient Communication and Care Management, 2) Hospital-Based Trust, Plain Language, and Coordination, 3) Home-Based Trust, Plain language, and Coordination, 4) Patient/Family Caregiver Assessment and Information Exchange Among Providers, and 5) Assessment and Teach Back. Each TC strategy group comprises three to six, non-mutually exclusive TC strategies (i.e., some strategies are in multiple TC strategy groups). Results from random forest analyses revealed that TC strategies patients reported receiving were more important in predicting readmissions than TC strategies that hospitals reported delivering, and that other key co-variates, such as patient comorbidities, were the most important variables. Conclusion Sophisticated statistical tools can help identify underlying patterns of hospitals’ TC efforts. Using such tools, this study identified five groups of TC strategies that have potential to improve patient outcomes.

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Section: Discussionmentioning

confidence: 99%

Improving evidence-based grouping of transitional care strategies in hospital implementation using statistical tools and expert review

Clouser

et al. 2021

BMC Health Serv Res

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“…As a sensitivity analysis, the endpoint of interest additionally included deaths attributed to recurrent HCC in those without documented recurrent HCC. 23 These subjects were censored at date of death.…”

Section: Methodsmentioning

confidence: 99%

T2 Hepatocellular Carcinoma Exception Policies That Prolong Waiting Time Improve the Use of Evidence-based Treatment Practices

Durkin

Kaplan

Bittermann

2020

Transplantation Direct

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Background. A United Network for Organ Sharing policy change in 2015 created a 6-mo delay in the receipt of T2 hepatocellular carcinoma exception points. It was hypothesized that the policy changed locoregional therapy (LRT) practices and explant findings because of longer expected waiting time. Methods. Patients transplanted with a first T2 hepatocellular carcinoma exception application between January 1, 2010 and December 31, 2014 (prepolicy; N = 6562), and those between August 10, 2015 and December 2, 2019 (postpolicy; N = 2345), were descriptively compared using data from United Network for Organ Sharing. Results. Median time from first application to transplantation was more homogenous across the US postpolicy, due to greater absolute increases in Regions 3, 6, 10, and 11 (>120 d). During waitlisting, postpolicy candidates received more LRT overall (P < 0.001), with more notable increases in previously short-wait regions. Postpolicy explants were overall more likely to have ≥1 tumor with complete necrosis (23.9 versus 18.4%; P < 0.001) and less likely have ≥1 tumor with no necrosis (32.6% versus 38.5%; P < 0.001). Significant geographic variability in explant treatment response was observed prepolicy with recipients in previously short-wait regions having more frequent tumor viability at transplant. Postpolicy, there were no differences in the prevalence of recipients with ≥1 tumor with 100% or 0% necrosis across regions (P = 0.9 and 0.2, respectively). Conclusions. The 2015 T2 exception policy has led to reduced geographic variability in the use of pretransplant LRT and in less frequent tumor viability on explant for recipients in previously short-waiting times.

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“…APPs ability to adhere to pathway driven practices helps ensure care is evidence based. The Centers for Medicare and Medicaid Conditions of Participation require transplant centers provide multidisciplinary care to transplant recipients and an APP helps ensure these discussions occur daily and no discipline is excluded 11 …”

Section: Utilization Of Apps In Transplantmentioning

confidence: 99%

“…As outpatient providers, APPs manage patients as part of a multidisciplinary team and serve as the primary provider typically in a clinic setting 6,7,9,11 . Early in the post‐transplant course, the focus is on acute recovery from surgery with careful monitoring for organ specific complications.…”

Section: Utilization Of Apps In Transplantmentioning

confidence: 99%

“…They found that there was no significance in demographics of the patients; however, they significantly decreased readmission rates in the post‐exposure group at 30 days (hazard ratio 0.60, 95% confidence interval, 0.39–0.90; p = .02) and 90 days (hazard ratio 0.49, 95% confidence interval, 0.34–0.71; p ≤ .001). They felt that these results were mediated through increased NP outpatient clinics and phone calls to patients 11 …”

Section: Utilization Of Apps In Transplantmentioning

confidence: 99%

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Examining the critical role of advanced practice providers on a multidisciplinary transplant team

Chambers

Reinschmidt

Agudelo³

et al. 2021

American Journal of Transplantation

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It is well documented that Physician Assistants (PAs) and Nurse Practitioners (NPs), collectively known as Advanced Practice Providers (APPs), have a beneficial role beyond the field of primary care. APPs broad spectrum of knowledge make them particularly well suited for specializing in complex fields such as transplant. Variations in practice across transplant centers lead to questions regarding optimal use of APPs. Using job descriptions from transplant centers currently employing APPs, we sought to examine the critical role of transplant APPs beyond clinical care alone. In this review, we explore not only the general training of APPs and current utilization of APPs in transplant, but also safety, cost effectiveness, and comparison of APPs to other transplant providers. We aimed to highlight the importance of recruitment and retention of transplant specific trained APPs to provide continuity in transplant programs. Additionally, APPs expansion into transplant research, quality improvement, leadership, and management must be considered. We challenge transplant centers utilizing APPs to consider these important aspects when seeking ways to expand and optimize the critical role APPs provide on the transplant team.

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An Advanced Practice Practitioner–Based Program to Reduce 30‐ and 90‐Day Readmissions After Liver Transplantation

Cited by 21 publications

References 19 publications

Improving evidence-based grouping of transitional care strategies in hospital implementation using statistical tools and expert review

Improving evidence-based grouping of transitional care strategies in hospital implementation using statistical tools and expert review

T2 Hepatocellular Carcinoma Exception Policies That Prolong Waiting Time Improve the Use of Evidence-based Treatment Practices

Examining the critical role of advanced practice providers on a multidisciplinary transplant team

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