We evaluated the efficacy of a peer-educator network intervention as a strategy to reduce HIV acquisition among injection drug users (IDUs) and their drug and/or sexual networks. A randomized controlled trial was conducted in St. Petersburg, Russia among IDU index participants and their risk network participants. Network units were randomized to the control or experimental intervention. Only the experimental index participants received training sessions to communicate risk reduction techniques to their network members. Analysis includes 76 index and 84 network participants who were HIV uninfected. The main outcome measure was HIV sero-conversion. The incidence rates in the control and experimental groups were 19.57 (95 % CI 10.74–35.65) and 7.76 (95 % CI 3.51–17.19) cases per 100 p/y, respectively. The IRR was 0.41 (95 % CI 0.15–1.08) without a statistically significant difference between the two groups (log rank test statistic X2 = 2.73, permutation p value = 0.16). Retention rate was 67 % with a third of the loss due to incarceration or death. The results show a promising trend that this strategy would be successful in reducing the acquisition of HIV among IDUs.

BACKGROUND Inappropriate laboratory testing is a contributor to waste in healthcare. OBJECTIVE To evaluate the impact of a multifaceted laboratory reduction intervention on laboratory costs. DESIGN A retrospective, controlled, interrupted time series (ITS) study. SETTING University of Utah Health Care, a 500‐bed academic medical center in Salt Lake City, Utah. POPULATION All patients 18 years or older admitted to the hospital to a service other than obstetrics, rehabilitation, or psychiatry. INTERVENTION Multifaceted quality‐improvement initiative in a hospitalist service including education, process change, cost feedback, and financial incentive. MEASUREMENTS Primary outcomes of lab cost per day and per visit. Secondary outcomes of number of basic metabolic panel (BMP), comprehensive metabolic panel (CMP), complete blood count (CBC), and prothrombin time/international normalized ratio tests per day; length of stay (LOS); and 30‐day readmissions. RESULTS A total of 6310 hospitalist patient visits (intervention group) were compared to 25,586 nonhospitalist visits (control group). Among the intervention group, the unadjusted mean cost per day was reduced from $138 before the intervention to $123 after the intervention (P < 0.001), and the unadjusted mean cost per visit decreased from $618 to $558 (P = 0.005). The ITS analysis showed significant reductions in cost per day, cost per visit, and the number of BMP, CMP, and CBC tests per day (P = 0.034, 0.02, <0.001, 0.004, and <0.001). LOS was unchanged and 30‐day readmissions decreased in the intervention group. CONCLUSION A multifaceted approach to laboratory reduction demonstrated a significant reduction in laboratory cost per day and per visit, as well as common tests per day at a major academic medical center. Journal of Hospital Medicine 2016;11:348–354. © 2016 Society of Hospital Medicine

Objective The objective of this study was to assess the clinical and financial impact of a quality improvement project that utilized a modified Early Warning Score (mEWS)-based clinical decision support intervention targeting early recognition of sepsis decompensation. Materials and Methods We conducted a retrospective, interrupted time series study on all adult patients who received a diagnosis of sepsis and were exposed to an acute care floor with the intervention. Primary outcomes (total direct cost, length of stay [LOS], and mortality) were aggregated for each study month for the post-intervention period (March 1, 2016–February 28, 2017, n = 2118 visits) and compared to the pre-intervention period (November 1, 2014–October 31, 2015, n = 1546 visits). Results The intervention was associated with a decrease in median total direct cost and hospital LOS by 23% (P = .047) and .63 days (P = .059), respectively. There was no significant change in mortality. Discussion The implementation of an mEWS-based clinical decision support system in eight acute care floors at an academic medical center was associated with reduced total direct cost and LOS for patients hospitalized with sepsis. This was seen without an associated increase in intensive care unit utilization or broad-spectrum antibiotic use. Conclusion An automated sepsis decompensation detection system has the potential to improve clinical and financial outcomes such as LOS and total direct cost. Further evaluation is needed to validate generalizability and to understand the relative importance of individual elements of the intervention.

This study evaluates the performance of the Project EX tobacco use cessation program in Russian summer recreational camps. An eight-session clinic-based tobacco use cessation program for adolescents was tested during the summer of 2011 in an experimental pilot trial that involved different youth that rotated through camps. Conditions were nested within camps. Two rotations of unique subject groups of smokers (program and standard care control) through each of five camps provided the means of controlling for campsite by condition. Assignment of condition by rotation was random (by a flip of a coin), achieving reasonable baseline comparability (total n=164 smokers at baseline, 76 program group, 88 standard care control group). Evaluation involved an immediate pretest and posttest and a six-month telephone follow-up. At immediate posttest, Project EX was moderately well-received, significantly reduced future smoking expectation (46% reduction in EX Program Condition versus 8% in Control, p<.0001), decreased intention to not quit smoking (−5.2% in EX versus +1.4% in Control, p<.05), and increased motivation to quit smoking (0.72 versus −0.04, p<.0001). At the six-month follow-up, program subjects reported a higher intent-to-treat quit rate during the last 30 days (7.5% versus 0.1%, p<.05). For the subjects who remained monthly smokers at the six-month follow-up, Project EX reduced subjects’ level of nicotine dependence (−0.53 versus +0.15, p<.001). The results were quite promising for this program, which included motivation enhancement, coping skill, and alternative medicine material. However, further research on teen tobacco use cessation programming in Russia with larger sample sizes, involving other locations of the country, and with stronger research designs is needed.

BACKGROUND Cellulitis is a common infection with wide variation of clinical care. OBJECTIVE To implement an evidence‐based care pathway and evaluate changes in process metrics, clinical outcomes, and cost for cellulitis. DESIGN A retrospective observational pre‐/postintervention study was performed. SETTING University of Utah Health Care, a 500‐bed academic medical center in Salt Lake City, Utah. PATIENTS All patients 18 years or older admitted to the emergency department observation unit or hospital with a primary diagnosis of cellulitis. INTERVENTION Development of an evidence‐based care pathway for cellulitis embedded into the electronic medical record with education for all emergency and internal medicine physicians. MEASUREMENTS Primary outcome of broad‐spectrum antibiotic use. Secondary outcomes of computed tomography/magnetic resonance imaging orders, length of stay (LOS), 30‐day readmission, and pharmacy, lab, imaging, and total facility costs. RESULTS A total of 677 visits occurred, including 370 visits where order sets were used. Among all patients, there was a 59% decrease in the odds of ordering broad‐spectrum antibiotics (P < 0.001), 23% decrease in pharmacy cost (P = 0.002), and 13% decrease in total facility cost (P = 0.006). Compared to patients for whom order sets were not used, patients for whom order sets were used had a 75%, 13%, and 25% greater decrease in the odds of ordering broad‐spectrum antibiotics (P < 0.001), clinical LOS (P = 0.041), and pharmacy costs (P = 0.074), respectively. CONCLUSION The evidence‐based care pathway for cellulitis improved care at an academic medical center by reducing broad‐spectrum antibiotic use, pharmacy costs, and total facility costs without an adverse change in LOS or 30‐day readmissions. Journal of Hospital Medicine 2015;10:780–786. © 2015 Society of Hospital Medicine

Although electronic telemetry ordering changes can produce decreases in hospital-wide telemetry monitoring, a multifaceted intervention may lead to an even larger decline in utilization rates. Whether these changes are durable cannot be ascertained from our study.

Objective The study sought to evaluate a novel electronic health record (EHR) add-on application for chronic disease management that uses an integrated display to decrease user cognitive load, improve efficiency, and support clinical decision making. Materials and Methods We designed a chronic disease management application using the technology framework known as SMART on FHIR (Substitutable Medical Applications and Reusable Technologies on Fast Healthcare Interoperability Resources). We used mixed methods to obtain user feedback on a prototype to support ambulatory providers managing chronic obstructive pulmonary disease. Each participant managed 2 patient scenarios using the regular EHR with and without access to our prototype in block-randomized order. The primary outcome was the percentage of expert-recommended ideal care tasks completed. Timing, keyboard and mouse use, and participant surveys were also collected. User experiences were captured using a retrospective think-aloud interview analyzed by concept coding. Results With our prototype, the 13 participants completed more recommended care (81% vs 48%; P &lt; .001) and recommended tasks per minute (0.8 vs 0.6; P = .03) over longer sessions (7.0 minutes vs 5.4 minutes; P = .006). Keystrokes per task were lower with the prototype (6 vs 18; P &lt; .001). Qualitative themes elicited included the desire for reliable presentation of information which matches participants’ mental models of disease and for intuitive navigation in order to decrease cognitive load. Discussion Participants completed more recommended care by taking more time when using our prototype. Interviews identified a tension between using the inefficient but familiar EHR vs learning to use our novel prototype. Concept coding of user feedback generated actionable insights. Conclusions Mixed methods can support the design and evaluation of SMART on FHIR EHR add-on applications by enhancing understanding of the user experience.

Objectives Artificial intelligence (AI), including predictive analytics, has great potential to improve the care of common chronic conditions with high morbidity and mortality. However, there are still many challenges to achieving this vision. The goal of this project was to develop and apply methods for enhancing chronic disease care using AI. Methods Using a dataset of 27,904 patients with diabetes, an analytical method was developed and validated for generating a treatment pathway graph which consists of models that predict the likelihood of alternate treatment strategies achieving care goals. An AI-driven clinical decision support system (CDSS) integrated with the electronic health record (EHR) was developed by encapsulating the prediction models in an OpenCDS Web service module and delivering the model outputs through a SMART on FHIR (Substitutable Medical Applications and Reusable Technologies on Fast Healthcare Interoperability Resources) web-based dashboard. This CDSS enables clinicians and patients to review relevant patient parameters, select treatment goals, and review alternate treatment strategies based on prediction results. Results The proposed analytical method outperformed previous machine-learning algorithms on prediction accuracy. The CDSS was successfully integrated with the Epic EHR at the University of Utah. Conclusion A predictive analytics-based CDSS was developed and successfully integrated with the EHR through standards-based interoperability frameworks. The approach used could potentially be applied to many other chronic conditions to bring AI-driven CDSS to the point of care.