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Setting: Four in-patient health facilities in western Uganda. Objective: To determine the impact of an innovative multi-modal quality improvement program on human immunodeficiency virus (HIV) status assessment and the impact of HIV status on severe illness conditions and mortality. Design: This was a staggered, pre-post quasi-experimental study designed to assess a multi-modal intervention (collaborative improvement meetings, audit and feedback, clinical mentoring) for improving quality of care following formal training in the management of severe illness in low-income settings. Results: From August 2014 to May 2015, 5759 patients were hospitalized, of whom 2451 (42.6%) had their HIV status assessed; 395 (16.1%) were HIV-infected. HIV-infected patients were significantly more likely to meet criteria for shock (27.5% vs. 15.1%, risk ratio [RR] 1.8, 95% confidence interval [CI] 1.7-1.9, P < 0.001) and severe respiratory distress (6.7% vs. 4.3%, RR 1.5, 95%CI 1.2-2.0, P < 0.001), and were significantly more likely to die in hospital (12.0% vs. 2.9%, RR 4.1, 95%CI 3.2-5.4, P < 0.001). There was no evidence of improved HIV status assessment during the intervention period (36.5% vs. 44.8%, +8.3%, 95%CI -8.3 to 24.8, P = 0.33). Conclusions: Hospitalized HIV-infected patients in western Uganda are at high risk for severe illness and death. Novel quality improvement strategies are needed to enhance hospital-based HIV testing in high-burden settings.

Background To improve management of severely ill hospitalized patients in low-income settings, the World Health Organization (WHO) established a triage tool called “Quick Check” to provide clinicians with a rapid, standardized approach to identify patients with severe illness based on recognition of abnormal vital signs. Despite the availability of these guidelines, recognition of severe illness remains challenged in low-income settings, largely as a result of infrequent vital sign monitoring. Methods We conducted a staggered, pre-post quasi-experimental study at four inpatient health facilities in western Uganda to assess the impact of a multi-modal intervention for improving quality of care following formal training on WHO “Quick Check” guidelines for diagnosis of severe illness in low-income settings. Intervention components were developed using the COM-B (“capability,” “opportunity,” and “motivation” determine “behavior”) model and included clinical mentoring by an expert in severe illness care, collaborative improvement meetings with external support supervision, and continuous audits of clinical performance with structured feedback. Results There were 5759 patients hospitalized from August 2014 to May 2015: 1633 were admitted before and 4126 during the intervention period. Designed to occur twice monthly, collaborative improvement meetings occurred every 2–4 weeks at each site. Clinical mentoring sessions, designed to occur monthly, occurred every 4–6 months at each site. Audit and feedback reports were implemented weekly as designed. During the intervention period, there were significant increases in the site-adjusted likelihood of initial assessment of temperature, heart rate, blood pressure, respiratory rate, mental status, and pulse oximetry. Patients admitted during the intervention period were significantly more likely to be diagnosed with sepsis (4.3 vs. 0.4%, risk ratio 10.1, 95% CI 3.0–31.0, p

Pre-training facility assessment tool. Appendix S2. Quick Check + hospital assessment report of existing severe illness practices. Table S1. Characteristics of inpatient health facilities participating in SIMS intervention. Table S2. Diagnostic criteria for severe illness conditions covered in Quick Check + training program, as defined by the World Health Organization District Clinician Manual. Table S3a. Barriers to executing target behaviors*, as documented by hospital staff while formulating implementation plans and placed into COM-B domains. Table S3b. Intervention functions targeting identified barriers and facilitators as defined in the Behavioral Change Wheel framework. Table S4a Between-site variation in vital sign collection before and after SIMS introduction, by site. Table S4b. Between-site variation in impact of SIMS on vital sign collection, by vital sign. Figure S1. Diagram illustrating the conceptual model based on components of the COM-B model that was utilized to develop the SIMS intervention. Figure S2. Staggered, pre-post quasi-experimental study design utilized for implementation of SIMS intervention. Baseline period indicates time period following Quick Check + training and before SIMS intervention. Intervention period indicates time period during which SIMS intervention was implemented. Figure S3. Flow diagram for patients included in study (DOCX 607Â kb)

A1 Introduction to the 8th Annual Conference on the Science of Dissemination and Implementation: Optimizing Personal and Population Health David Chambers1, Lisa Simpson2 1Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Rockville, MD, 20850, USA; 2AcademyHealth, Washington, DC, 20036, USA For the second year in a row, we are pleased to be able to share the proceedings of the Annual Conference on the Science of Dissemination and Implementation in Health, a large meeting reflecting the expanding and evolving research field that seeks to optimize the use of evidence, interventions, and tools from health research within the myriad of settings where people receive health care, make health-related decisions, and increase knowledge of influences on the health of the population. We once again benefitted from a strong partnership, co-led by AcademyHealth and the National Institutes of Health (NIH), with co-sponsorship from the Agency for Healthcare Research and Quality (AHRQ), the Patient Centered Outcomes Research Institute (PCORI), the Robert Wood Johnson Foundation (RWJF), the US Department of Veterans Affairs (VA), and the WT Grant Foundation. In addition, we benefitted from the collaboration of staff from the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO). NIH and AcademyHealth again co-led the program planning committee, which focused on the development of the plenary sessions, and convened a scientific advisory panel to suggest speakers and advise on the overall conference development. The planning committee identified four key areas around which to focus the plenary panels and keynote address. Dr. America Bracho, M.D., M.P.H., Executive Director of Latino Health Access in Orange County, California, spoke about the opportunities for implementation science to inform efforts to improve community health and engage underserved populations. The three plenary panels each focused on a significant future direction for dissemination and implementation (D & I) research: the interface between D&I science and population health, emerging opportunities for global implementation science, and the challenges around implementation of precision medicine. The plenary sessions were complemented by facilitated lunchtime discussions on the same three topics, which offered participants an opportunity to identify key research questions for each and brainstorm next steps. Synopses of the lunchtime discussions are included in this supplement. Given the overwhelming success of the 2014 conference and the large number of abstracts received in 2014 (660), the program planning committee identified eight program tracks for abstract submitters to respond to, and through which the concurrent sessions of the conference would be organized. These tracks—Behavioral Health, Big Data and Technology for Dissemination and Implementation Research, Clinical Care Settings, Global Dissemination and Implementation, Promoting Health Equity and Eliminating Disparities, Health Policy Dissemination and Implementation, Prevention and Public Health, and Models, Measures and Methods— were designed to enable conference participants to follow a consistent theme across the multiple sessions of the conference and form the structure of this supplement. The call for abstracts, including individual paper presentations, individual posters and panel presentations, resulted in 515 submissions, spread across the eight thematic tracks. Over one hundred reviewers devoted their time to ensuring a comprehensive and expert review, and reviews were conducted within each track and coordinated by the track leads. For the final program, 64 oral presentations, 12 panels, and 263 posters were presented over the two-day meeting. Slides for the oral presentations and panels (with the agreement of the authors) were posted on the conference website (http://diconference.academyhealth.org/archives/2015archives) and all abstracts were included on the conference webapp (https://academyhealth.confex.com/academyhealth/2015di/meetingapp.cgi). This supplement has compiled the abstracts for presented papers, panel sessions, and lunchtime discussions from the 8th Annual Meeting on the Science of Dissemination and Implementation in Health: Optimizing Personal and Population Health. We are pleased to have the abstracts from the conference together in one volume once again, and look forward to the 9th Annual meeting, scheduled for December in Washington, D.C.

Pre-training facility assessment tool. Appendix S2. Quick Check + hospital assessment report of existing severe illness practices. Table S1. Characteristics of inpatient health facilities participating in SIMS intervention. Table S2. Diagnostic criteria for severe illness conditions covered in Quick Check + training program, as defined by the World Health Organization District Clinician Manual. Table S3a. Barriers to executing target behaviors*, as documented by hospital staff while formulating implementation plans and placed into COM-B domains. Table S3b. Intervention functions targeting identified barriers and facilitators as defined in the Behavioral Change Wheel framework. Table S4a Between-site variation in vital sign collection before and after SIMS introduction, by site. Table S4b. Between-site variation in impact of SIMS on vital sign collection, by vital sign. Figure S1. Diagram illustrating the conceptual model based on components of the COM-B model that was utilized to develop the SIMS intervention. Figure S2. Staggered, pre-post quasi-experimental study design utilized for implementation of SIMS intervention. Baseline period indicates time period following Quick Check + training and before SIMS intervention. Intervention period indicates time period during which SIMS intervention was implemented. Figure S3. Flow diagram for patients included in study (DOCX 607Â kb)