Literature Collection

BACKGROUND: Syringe exchange programs are uniquely positioned to offer treatment services to interested clients. Prevention Point Philadelphia recently expanded to offer buprenorphine maintenance treatment through its Stabilization, Treatment, and Engagement Program (STEP). OBJECTIVE: To describe the STEP model of care and report treatment outcomes. METHODS: Retrospective chart review of patients enrolled in STEP (October 2011 to August 2014). The main outcome measure was time retained in treatment, defined as time from treatment initiation to treatment failure. Secondary outcome measures were buprenorphine and opiate use, from urine toxicology screens. Retention in treatment was analyzed using Kaplan-Meier survival estimates; patients who remained in treatment at the end of the study period were censored on that day. The percentage of patients who were positive for buprenorphine and opiates in each month of treatment was calculated. RESULTS: Of the 124 patients enrolled in STEP, the median age was 41 (range: 21-63) and 80% reported injection heroin use. Comorbidities were common: 33% had human immunodeficiency virus (HIV) infection, most reported anxiety (78%) or depression (71%), and 20% were homeless. The most common program outcomes were unplanned self-discharge (n = 29; 23%), incarceration (n = 20; 16%), and administrative discharge (n = 19; 15%). The percentages of patients retained in treatment at 3, 6, 9, and 12 months were 77%, 65%, 59%, and 56%, respectively. Among those retained, the percentages with a positive buprenorphine screen at 3, 6, 9, and 12 months were 88%, 100%, 96%, and 95%, respectively. The percentages with a positive opiates screen were 19%, 13%, 17%, and 16%, respectively. CONCLUSIONS: With a program that blended organizational and community resources, retention in buprenorphine maintenance treatment was comparable to retention rates reported from other settings. Further research should directly compare treatment outcomes in syringe exchange program-based settings versus primary care and specialty settings.

BACKGROUND: Integrating advanced machine-learning (ML) algorithms into clinical practice is challenging and requires interdisciplinary collaboration to develop transparent, interpretable, and ethically sound clinical decision support (CDS) tools. We aimed to design a ML-driven CDS tool to predict opioid overdose risk and gather feedback for its integration into the University of Florida Health (UFHealth) electronic health record (EHR) system. METHODS: We used user-centered design methods to integrate the ML algorithm into the EHR system. The backend and UI design sub-teams collaborated closely, both informed by user feedback sessions. We conducted seven user feedback sessions with five UF Health primary care physicians (PCPs) to explore aspects of CDS tools, including workflow, risk display, and risk mitigation strategies. After customizing the tool based on PCPs' feedback, we held two rounds of one-on-one usability testing sessions with 8 additional PCPs to gather feedback on prototype alerts. These sessions informed iterative UI design and backend processes, including alert frequency and reappearance circumstances. RESULTS: The backend process development identified needs and requirements from our team, information technology, UFHealth, and PCPs. Thirteen PCPs (male = 62%, White = 85%) participated across 7 user feedback sessions and 8 usability testing sessions. During the user feedback sessions, PCPs (n = 5) identified flaws such as the term "high risk" of overdose potentially leading to unintended consequences (e.g., immediate addiction services referrals), offered suggestions, and expressed trust in the tool. In the first usability testing session, PCPs (n = 4) emphasized the need for natural risk presentation (e.g., 1 in 200) and suggested displaying the alert multiple times yearly for at-risk patients. Another 4 PCPs in the second usability testing session valued the UFHealth-specific alert for managing new or unfamiliar patients, expressed concerns about PCPs' workload when prescribing to high-risk patients, and recommended incorporating the details page into training sessions to enhance usability. CONCLUSIONS: The final backend process for our CDS alert aligns with PCP needs and UFHealth standards. Integrating feedback from PCPs in the early development phase of our ML-driven CDS tool helped identify barriers and facilitators in the CDS integration process. This collaborative approach yielded a refined prototype aimed at minimizing unintended consequences and enhancing usability.

INTRODUCTION: Interprofessional teamwork is the key issue of delivering integrated hospital care; however, measuring interprofessional collaboration for auditing is fragmented. In this study, a questionnaire to measure InterProfessional collaborative Practice for Integrated Hospital care (IPPIH) has been developed and validated. METHODS: A four-step iterative process was conducted: (1) literature search to find suitable questionnaires; (2) semistructured stakeholder interviews (individual and in focus groups) to discuss the topics and questions (face validity), (3) pretesting the prototype of the questionnaire in two different integrated care pathways for feasibility, usability, and internal consistency, and (4) testing (content and construct validity and responsiveness) of the revised questionnaire in eight integrated care pathways; the validation and responsiveness was tested by means of exploratory factor analysis, calculation of Cronbach alpha, item analysis, and linear mixed model analysis. RESULTS: Based on six questionnaires and the opinion of direct stakeholders, the questionnaire IPPIH comprised 27 items. Five different domains could be distinguished: own skills, culture, coordination and collaboration, practical support, and appreciation with the Cronbach alpha varied from 0.91 to 0.48. The self-reported intensity of the collaboration within a specific care pathway significantly influenced the outcome ( P = .000). DISCUSSION: The product is a questionnaire, IPPIH, which can measure the degree of interprofessional collaborative practice in integrated hospital care pathways. The IPPIH was initially developed for quality assurance. However, the IPPIH also seems to be suitable as a self-assessment tool for directors to monitor and improve the interprofessional collaboration and the quality of their integrated care pathway.

BACKGROUND: This study explores the facilitating and inhibiting factors in the design/development, implementation, and applicability/evaluation of value-based payment models of integrated care. The Delphi technique was used to reach consensus among a panel of (inter)national experts on these factors. METHODS: An expert panel of 15 members participated in a three-round Delphi study. Factors from experts and literature were used to compile a list of 40 facilitators and 40 inhibitors. Afterwards, experts were asked to rate the importance of these factors using a 5-point Likert scale. RESULTS: Eight facilitating (e.g., transparency, communication, and trust among involved stakeholders) and seven inhibiting factors (e.g., lack of motivation and engagement among involved stakeholders) achieved full consensus. Timely availability of data and an integrated information technology system for data registration (a facilitator) were the only factors achieving full consensus through a very high agreement. CONCLUSIONS: Adequate outcome measures, targets, benchmarks, and incentives are important in value-based payment models. The less quantifiable items, such as strong leadership, transparency, communication and trust, and motivation and engagement of the involved stakeholders, are also important for successful adoption of these models and promote high-quality care at lower or equal costs.