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Caution Ahead: Research Challenges of a Randomized Controlled Trial Implemented to Improve Breast Cancer Treatment at Safety-Net Hospitals.

ABSTRACT: PURPOSE:To implement and test a Web-based tracking and feedback (T&F) tool to close referral loops and reduce adjuvant breast cancer treatment underuse in safety-net hospitals (SNHs). PATIENT AND METHODS:We randomly assigned 10 SNHs, identified patients with new stage 1 to stage 3 breast cancer, assessed their connection with the oncologist, and relayed this information to surgeons for follow-up. We interviewed key informants about the tool's usefulness. We conducted intention-to-treat and pre- and poststudy analyses to assess the T&F tool and implementation effectiveness, respectively. RESULTS:Between the study start and intervention implementation, several hospitals reorganized care delivery and 49% of patients scheduled to undergo breast cancer surgery were ineligible because they already were in contact with an oncologist. One high-volume hospital closed. Despite randomization of hospitals, intervention (INT) hospitals had fewer white patients (5% v 16%; P = .0005), and more underuse (28% v 15%; P = .002) compared with usual care (UC) hospitals. Over time, INT hospitals with poorer follow-up significantly reduced underuse compared with UC hospitals (INT hospitals, from 33% to 9%, P = .001 v UC hospitals, from 15% to 11%, P = .5). There was no difference in underuse (9% at INT hospitals, 11% at UC hospitals; P = .8). Hospitals with better follow-up (odds ratio, 0.85; 95% CI, 0.73 to 0.98) had less underuse. In settings with poor follow-up and tracking approaches, key informants found the tool useful. The rapidly changing delivery landscape posed significant challenges to this implementation research. CONCLUSION:A T&F tool did not significantly reduce adjuvant underuse but may help reduce underuse in SNHs with poor follow-up capabilities. Inability to discern T&F effectiveness is likely due to encountered challenges that inform lessons for future implementation research.

SUBMITTER: Bickell NA

PROVIDER: S-EPMC6550054 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Caution Ahead: Research Challenges of a Randomized Controlled Trial Implemented to Improve Breast Cancer Treatment at Safety-Net Hospitals.

Bickell Nina A NA Shah Ajay A Castaldi Maria M Lewis Theophilus T Sickles Alan A Arora Shalini S Clarke Kevin K Kemeny Margaret M Srinivasan Anitha A Fei Kezhen K Franco Rebeca R Parides Michael M Pappas Peter P McAlearney Ann Scheck AS

Journal of oncology practice 20180103 3

<h4>Purpose</h4>To implement and test a Web-based tracking and feedback (T&F) tool to close referral loops and reduce adjuvant breast cancer treatment underuse in safety-net hospitals (SNHs).<h4>Patient and methods</h4>We randomly assigned 10 SNHs, identified patients with new stage 1 to stage 3 breast cancer, assessed their connection with the oncologist, and relayed this information to surgeons for follow-up. We interviewed key informants about the tool's usefulness. We conducted intention-to- ...[more]

PMID: 29298115

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Project description:Purpose of Review:Patient engagement in research is increasingly recognized as an important component of the research process and may facilitate translation of research findings. To heighten awareness on this important topic, this review presents opportunities and challenges of patient engagement in research, drawing on specific examples from 4 areas of Canadian kidney research conducted by New Investigators in the Kidney Research Scientist Core Education and National Training (KRESCENT) Program. Sources of Information:Research expertise, published reports, peer-reviewed articles, and research funding body websites. Methods:In this review, the definition, purpose, and potential benefits of patient engagement in research are discussed. Approaches toward patient engagement that may help with translation and uptake of research findings into clinical practice are highlighted. Opportunities and challenges of patient engagement are presented in both basic science and clinical research with the following examples of kidney research: (1) precision care in focal and segmental glomerulosclerosis, (2) systems biology approaches to improve management of chronic kidney disease and enhance kidney graft survival, (3) reducing the incidence of suboptimal dialysis initiation, and (4) use of patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) in kidney practice. Key Findings:Clinical research affords more obvious opportunities for patient engagement. The most obvious step at which to engage patients is in the setting of research priorities. Engagement at all stages of the research cycle may prove to be more challenging, and requires a detailed plan, along with funds and infrastructure to ensure that it is not merely tokenistic. Basic science research is several steps removed from the clinical application and involves complex scientific concepts, which makes patient engagement inherently more difficult. Limitations:This is a narrative review of the literature that has been partly influenced by the perspectives and experiences of the authors and focuses on research conducted by the authors. The evidence base to support the suggested benefits of patient engagement in research is currently limited. Implications:The formal incorporation of patients' priorities, perspectives, and experiences is now recognized as a key component of the research process. If patients and researchers are able to effectively work together, this could enhance research quality and efficiency. To effectively engage patients, proper infrastructure and dedicated funding are needed. Going forward, a rigorous evaluation of patient engagement strategies and their effectiveness will be needed.

Project description:ImportanceMedical patients discharged from safety-net hospitals (SNHs) experience higher readmission rates compared with those discharged from non-SNHs. However, little is known about whether this association persists for surgical patients.ObjectivesTo examine differences in readmission rates between SNHs and non-SNHs among surgical patients after discharge and determine whether hospital characteristics might account for some of the variation.Design, setting, and participantsThis observational retrospective study linked the Healthcare Cost and Utilization Project State Inpatient Databases of the Agency for Healthcare Research and Quality from January 1, 2011, through December 31, 2014, for 4 states (New York, Florida, Iowa, and Washington) with data from the 2014 American Hospital Association annual survey. After identifying surgical discharges, SNHs were defined as those with the top quartile of inpatient stays paid by Medicaid or self-paid. Hospital-level risk-standardized readmission rates (RSRRs) for surgical discharges were calculated. The association between hospital RSRRs and hospital characteristics was evaluated with bivariate analyses. An estimated multivariable hierarchical linear regression model was used to examine variation in hospital RSRRs, adjusting for hospital characteristics, state, year, and SNH status. Data were analyzed from June 1, 2017, through March 1, 2018.ExposuresSurgical care at an SNH.Main outcomes and measuresReadmission after an index surgical admission.ResultsA total of 1 252 505 patients across all 4 years and states were included in the analysis (51.7% women; mean [SD] age, 52.7 [18.1] years). Bivariate analyses found that SNHs had higher mean (SD) surgical RSRRs compared with non-SNHs; significant differences were found for New York (9.6 [0.1] vs 10.9 [0.1]; P < .001) and Florida (11.6 [0.1] vs 12.1 [0.1]; P = .001). The SNHs also had higher RSRRs in these 2 states when stratified by hospital funding (nonfederal government SNHs in New York, 11.9 [0.2]; for-profit, private SNHs in Florida, 13.1 [0.2]; P < .001 for both); however, bed size was a significant factor for higher mean (SD) RSRRs only for New York (200 to 399 beds, 12.0 [0.4]; P = .006). Similar results were found for multivariable linear regression models; RSRRs were 1.02% higher for SNHs compared with non-SNHs (95% CI, 0.75%-1.29%; P < .001). Increased RSRRs were observed for hospitals in New York and Florida, teaching hospitals, and investor-owned hospitals. Factors associated with reduced RSRRs included presence of an ambulatory surgery center, cardiac catheterization capabilities, and high surgical volume.Conclusions and relevanceAccording to results of this study, surgical patients treated at SNHs experienced slightly higher RSRRs compared with those treated at non-SNHs. This association persisted after adjusting for year, state, and hospital factors, including teaching status, hospital bed size, and hospital volume.

Project description:ObjectiveTo systematically review how safety-net hospitals' status is identified and defined, discuss current definitions' limitations, and provide recommendations for a new classification and evaluation framework.Data sourcesSafety-net hospital-related studies in the MEDLINE database published before May 16, 2019.Study designSystematic review of the literature that adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.Data collection/extraction methodsWe followed standard selection protocol, whereby studies went through an abstract review followed by a full-text screening for eligibility. For each included study, we extracted information about the identification method itself, including the operational definition, the dimension(s) of disadvantage reflected, study objective, and how safety-net status was evaluated.Principal findingsOur review identified 132 studies investigating safety-net hospitals. Analysis of identification methodologies revealed substantial heterogeneity in the ways disadvantage is defined, measured, and summarized at the hospital level, despite a 4.5-fold increase in studies investigating safety-net hospitals for the past decade. Definitions often exclusively used low-income proxies captured within existing health system data, rarely incorporated external social risk factor measures, and were commonly separated into distinct safety-net status categories when analyzed.ConclusionsConsistency in research and improvement in policy both require a standard definition for identifying safety-net hospitals. Yet no standardized definition of safety-net hospitals is endorsed and existing definitions have key limitations. Moving forward, approaches rooted in health equity theory can provide a more holistic framework for evaluating disadvantage at the hospital level. Furthermore, advancements in precision public health technologies make it easier to incorporate detailed neighborhood-level social determinants of health metrics into multidimensional definitions. Other countries, including the United Kingdom and New Zealand, have used similar methods of identifying social need to determine more accurate assessments of hospital performance and the development of policies and targeted programs for improving outcomes.

Dataset Information

Caution Ahead: Research Challenges of a Randomized Controlled Trial Implemented to Improve Breast Cancer Treatment at Safety-Net Hospitals.

Publications

Caution Ahead: Research Challenges of a Randomized Controlled Trial Implemented to Improve Breast Cancer Treatment at Safety-Net Hospitals.

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