Communicating Patient Discharge Readiness: An Implementation Evaluation in an Inpatient Hospital Medicine Setting.

BACKGROUND: The progression of patients through a hospital from admission to discharge can be slowed by delays in patient discharge, increasing pressure on health care staff. We designed and piloted the Discharge Today tool, with the goal of improving the efficiency of patient discharge; however, adoption remained low. PURPOSE: To close this implementation gap, we deployed and evaluated a 4-part implementation strategy bundle. METHODS: We measured the success of implementation by evaluating validated implementation outcomes using both quantitative and qualitative methods, grounded in Normalization Process Theory. RESULTS: The implementation strategies used were effective for increasing use of the Discharge Today tool by hospital medicine physicians and advanced practice providers during both the active and passive implementation periods. CONCLUSIONS: While the implementation strategies used were effective, qualitative findings indicate that limitations in the functionality of the tool, alongside inconsistent use of the tool across clinical staff, continued to inhibit adoption.

Applying Clinical Decision Support Design Best Practices With the Practical Robust Implementation and Sustainability Model Versus Reliance on Commercially Available Clinical Decision Support Tools: Randomized Controlled Trial.

BACKGROUND: Limited consideration of clinical decision support (CDS) design best practices, such as a user-centered design, is often cited as a key barrier to CDS adoption and effectiveness. The application of CDS best practices is resource intensive; thus, institutions often rely on commercially available CDS tools that are created to meet the generalized needs of many institutions and are not user centered. Beyond resource availability, insufficient guidance on how to address key aspects of implementation, such as contextual factors, may also limit the application of CDS best practices. An implementation science (IS) framework could provide needed guidance and increase the reproducibility of CDS implementations. OBJECTIVE: This study aims to compare the effectiveness of an enhanced CDS tool informed by CDS best practices and an IS framework with a generic, commercially available CDS tool. METHODS: We conducted an explanatory sequential mixed methods study. An IS-enhanced and commercial CDS alert were compared in a cluster randomized trial across 28 primary care clinics. Both alerts aimed to improve beta-blocker prescribing for heart failure. The enhanced alert was informed by CDS best practices and the Practical, Robust, Implementation, and Sustainability Model (PRISM) IS framework, whereas the commercial alert followed vendor-supplied specifications. Following PRISM, the enhanced alert was informed by iterative, multilevel stakeholder input and the dynamic interactions of the internal and external environment. Outcomes aligned with PRISM's evaluation measures, including patient reach, clinician adoption, and changes in prescribing behavior. Clinicians exposed to each alert were interviewed to identify design features that might influence adoption. The interviews were analyzed using a thematic approach. RESULTS: Between March 15 and August 23, 2019, the enhanced alert fired for 61 patients (106 alerts, 87 clinicians) and the commercial alert fired for 26 patients (59 alerts, 31 clinicians). The adoption and effectiveness of the enhanced alert were significantly higher than those of the commercial alert (62% vs 29% alerts adopted, P<.001; 14% vs 0% changed prescribing, P=.006). Of the 21 clinicians interviewed, most stated that they preferred the enhanced alert. CONCLUSIONS: The results of this study suggest that applying CDS best practices with an IS framework to create CDS tools improves implementation success compared with a commercially available tool. TRIAL REGISTRATION: ClinicalTrials.gov NCT04028557; http://clinicaltrials.gov/ct2/show/NCT04028557.

Patient Treatment Preferences for Heart Failure Medications: A Mixed Methods Study.

INTRODUCTION: Consideration of patient preferences for guideline-directed medical therapies (GDMT) for heart failure with reduced ejection fraction (HFrEF) may help improve major gaps in prescribing and adherence. This study aimed to identify the range and relative priority of factors influencing patients' decisions to take HFrEF medications. MATERIALS AND METHODS: This was a convergent mixed methods study of patients with HFrEF. Focus groups were conducted to identify a list of factors followed by individuals rating and ranking the influence of each factor on their decision to take a medication. Using thematic analysis, we summarized preferences into categories. RESULTS: Two focus groups with 13 participants reported 22 factors. Of the factors, "keeping you alive" was most commonly ranked in the top three (seven participants), followed by "communication and understanding" (six participants). Factors were summarized into six categories (listed in order of patient-reported influence): 1) demonstrated improvements in quality of life and longevity, 2) decreased risk of hospitalization, 3) opportunity for shared decision-making and trust in provider, 4) absence of adverse events, 5) affordability, and 6) convenience of taking and absence of interference with daily life. CONCLUSION: Patients prioritize treatment benefits and being informed more than risks, cost and inconvenience of taking HFrEF medications.

Integrating the Practical Robust Implementation and Sustainability Model With Best Practices in Clinical Decision Support Design: Implementation Science Approach.

BACKGROUND: Clinical decision support (CDS) design best practices are intended to provide a narrative representation of factors that influence the success of CDS tools. However, they provide incomplete direction on evidence-based implementation principles. OBJECTIVE: This study aims to describe an integrated approach toward applying an existing implementation science (IS) framework with CDS design best practices to improve the effectiveness, sustainability, and reproducibility of CDS implementations. METHODS: We selected the Practical Robust Implementation and Sustainability Model (PRISM) IS framework. We identified areas where PRISM and CDS design best practices complemented each other and defined methods to address each. Lessons learned from applying these methods were then used to further refine the integrated approach. RESULTS: Our integrated approach to applying PRISM with CDS design best practices consists of 5 key phases that iteratively interact and inform each other: multilevel stakeholder engagement, designing the CDS, design and usability testing, thoughtful deployment, and performance evaluation and maintenance. The approach is led by a dedicated implementation team that includes clinical informatics and analyst builder expertise. CONCLUSIONS: Integrating PRISM with CDS design best practices extends user-centered design and accounts for the multilevel, interacting, and dynamic factors that influence CDS implementation in health care. Integrating PRISM with CDS design best practices synthesizes the many known contextual factors that can influence the success of CDS tools, thereby enhancing the reproducibility and sustainability of CDS implementations. Others can adapt this approach to their situation to maximize and sustain CDS implementation success.

For Diabetes Shared Savings Programs, 1 Year of Data Is Not Enough.

Fee-for-service payment models are moving toward pay-for-performance designs, many of which rely on shared savings for financial sustainability. Shared savings programs divide the cost savings between health care purchaser and provider based on provider performance. Often, these programs measure provider performance as the delivery of agreed-upon clinical practice guidelines that usually are represented as evidence-based medicine (EBM). Multiyear studies show a negative relationship between total cost and EBM, indicating that long-term shared savings can be substantial. This study explores expectations for the rewards in the first year of a shared savings program. It also indicates the effectiveness of using 1 year of claims to assess cost savings from evidence-based care, especially in a patient population with high turnover. This study analyzed 1956 adults with diabetes insured through Medicaid. Results of linear regression showed that the relationship between total cost of care and each element of evidence-based medical care during a 1-year period was positive (higher cost) or insignificant. The results indicate that diabetes EBM programs cannot expect to see significant cost savings if the evaluation lasts only 1 year or less. The study concludes that improvements in EBM incentive programs could come from investigating the length of time needed to realize cost savings from each element of diabetes EBM. Investigating other factors that could affect the expected amount of cost savings also would benefit these programs, especially factors derived from sources external to insurance program information such as the medical record and care management data.

Indirect calorimetry: a practical guide for clinicians.

This review provides clinicians with a comprehensive overview of indirect calorimetry including the principles, methodology, technologic advancements, benefits, and challenges. Clinical applications for indirect calorimetry and the potential limitations are specifically addressed for both the inpatient and outpatient setting. Measurement of energy expenditure is the most accurate method to assess energy needs. Indirect calorimetry remains a gold standard in measuring energy expenditure in the clinical settings. The benefits of providing optimal nutrition for recovery from illness and chronic health management are well documented. Indirect calorimetry offers a scientifically-based approach to customize a patient's energy needs and nutrient delivery to maximize the benefits of nutrition therapy. With recent advances in technology, indirect calorimeters are easier to operate, more portable, and affordable. Increased utilization of indirect calorimetry would facilitate individualized patient care and should lead to improved treatment outcomes.

Using telehealth to increase participation in weight maintenance programs.

OBJECTIVE: To compare weight regain, satisfaction, and convenience among three weight maintenance programs: telehealth, traditional classes, and no program. RESEARCH METHODS AND PROCEDURES: This quasi-experimental study compared weight change, satisfaction, and convenience among three program types. The telehealth participants interacted with a registered dietitian (RD) through the web and e-mail, traditional program participants attended a traditional classroom program, and no program participants received no interaction. Eighty-seven subjects (14 men and 73 women) were enrolled in the study: 31 traditional, 31 telehealth, and 25 no program participants. Eligibility included participation in a community-based weight loss program (Colorado Weigh) and minimum 7% weight loss before enrollment. RESULTS: Subject characteristics at baseline were as follows: age, 50 +/- 9.3 (standard deviation) years; height, 1.68 +/- 0.09 m; weight, 80.5 +/- 18.4 kg, with no significant differences between groups. Over 6 months, the traditional group lost 0.5 +/- 4.3 kg, the telehealth group lost 0.6 +/- 2.5 kg, and the no program group gained 1.7 +/- 3.0 kg. Weight change among all three groups was significant (p = 0.02); no program participants gained significantly more weight than the telehealth and traditional groups. There were no differences in overall satisfaction between the telehealth and traditional groups (p = 0.43), but individuals in the telehealth group rated their program as more convenient compared with the traditional group (p = 0.0001). DISCUSSION: These results show the usefulness of telehealth programs in long-term weight loss maintenance. They may be a useful alternative for those who successfully lose weight in a structured behavioral program but do not choose to participate in a formal behavioral weight loss maintenance program.

Variability of measured resting metabolic rate.

BACKGROUND: The necessity of a 12-h fast before resting metabolic rate (RMR) is measured is often a barrier to measuring RMR. OBJECTIVE: We compared RMR measurements obtained in the morning and afternoon and across repeated days to elucidate the magnitude and sources of variability. DESIGN: Healthy men (n = 12) and women (n = 25) aged 21-67 y, with body mass indexes (in kg/m(2)) ranging from 17 to 34 and body fat ranging from 6% to 54%, completed 4 RMR measurements. RMR measurements were made in the morning (after a 12-h fast and 12 h postexercise) and in the afternoon (after a 4-h fast and 12 h postexercise) on 2 separate days with the ventilated-hood technique. Body composition was assessed by dual-energy X-ray absorptiometry. RESULTS: Mean (+/- SE) afternoon RMR was significantly higher than morning RMR on both visit 1 (1593.5 +/- 35.6 compared with 1508.0 +/- 31.5 kcal/d; P = 0.001) and visit 2 (1602 +/- 29.3 compared with 1511.4 +/- 35.9 kcal/d; P = 0.001). The 2 morning measurements (r = 0.93) and the 2 afternoon measurements (r = 0.93) were highly correlated, and no significant differences between measurements were observed. The mean difference between the morning and afternoon measurements was 99.0 +/- 35.8 kcal/d (6%). CONCLUSIONS: Repeated morning and evening measurements of RMR were stable and highly correlated. Day-to-day measurements of RMR were not significantly different. RMR measured in the afternoon after a 4-h fast and exercise was approximately 100 kcal/d higher than RMR measured in the morning.