Randomized controlled trial of once-per-week intermittent fasting for health improvement: the WONDERFUL trial.

Aims: Low-density lipoprotein cholesterol (LDL-C) predicts heart disease onset and may be reduced by intermittent fasting. Some studies, though, reported that fasting increased LDL-C; however, no study evaluated LDL-C as the primary endpoint. This randomized controlled trial evaluated the effect of low-frequency intermittent fasting on LDL-C and other biomarkers. Methods and results: Adults aged 21-70 years were enrolled who were not taking a statin, had modestly elevated LDL-C, had ≥1 metabolic syndrome feature or type 2 diabetes, and were not taking anti-diabetic medication (N = 103). Water-only 24-h fasting was performed twice weekly for 4 weeks and then once weekly for 22 weeks; controls ate ad libitum. The primary outcome was 26-week LDL-C change score. Secondary outcomes (requiring P ≤ 0.01) were 26-week changes in homeostatic model assessment of insulin resistance (HOMA-IR), Metabolic Syndrome Score (MSS), brain-derived neurotrophic factor (BDNF), and MicroCog general cognitive proficiency index (GCPi). Intermittent fasting (n = 50) and control (n = 53) subjects were, respectively, aged 49.3 ± 12.0 and 47.0 ± 9.8 years, predominantly female (66.0% and 67.9%), and overweight (103 ± 24 and 100 ± 21 kg) and had modest LDL-C elevation (124 ± 19 and 128 ± 20 mg/dL). Drop-outs (n = 12 fasting, n = 20 control) provided an evaluable sample of n = 71 (n = 38 fasting, n = 33 control). Intermittent fasting did not change LDL-C (0.2 ± 16.7 mg/dL) vs. control (2.5 ± 19.4 mg/dL; P = 0.59), but it improved HOMA-IR (-0.75 ± 0.79 vs. -0.10 ± 1.06; P = 0.004) and MSS (-0.34 ± 4.72 vs. 0.31 ± 1.98, P = 0.006). BDNF (P = 0.58), GCPi (P = 0.17), and weight (-1.7 ± 4.7 kg vs. 0.2 ± 3.5 kg, P = 0.06) were unchanged. Conclusions: A low-frequency intermittent fasting regimen did not reduce LDL-C or improve cognitive function but significantly reduced both HOMA-IR and MSS. Trial registration: clinicaltrials.gov, NCT02770313.

A role for the MEGF6 gene in predisposition to osteoporosis.

Osteoporosis is a common skeletal disorder characterized by deterioration of bone tissue. The set of genetic factors contributing to osteoporosis is not completely specified. High-risk osteoporosis pedigrees were analyzed to identify genes that may confer susceptibility to disease. Candidate predisposition variants were identified initially by whole exome sequencing of affected-relative pairs, approximately cousins, from 10 pedigrees. Variants were filtered on the basis of population frequency, concordance between pairs of cousins, affecting a gene associated with osteoporosis, and likelihood to have functionally damaging, pathogenic consequences. Subsequently, variants were tested for segregation in 68 additional relatives of the index carriers. A rare variant in MEGF6 (rs755467862) showed strong evidence of segregation with the disease phenotype. Predicted protein folding indicated the variant (Cys200Tyr) may disrupt structure of an EGF-like calcium-binding domain of MEGF6. Functional analyses demonstrated that complete loss of the paralogous genes megf6a and megf6b in zebrafish resulted in significant delay of cartilage and bone formation. Segregation analyses, in silico protein structure modeling, and functional assays support a role for MEGF6 in predisposition to osteoporosis.

Implementation of Care Management: An Analysis of Recent AHRQ Research.

Care management (CM) is a promising team-based, patient-centered approach "designed to assist patients and their support systems in managing medical conditions more effectively." As little is known about its implementation, this article describes CM implementation and associated lessons from 12 Agency for Healthcare Research and Quality-sponsored projects. Two rounds of data collection resulted in project-specific narratives that were analyzed using an iterative approach analogous to framework analysis. Informants also participated as coauthors. Variation emerged across practices and over time regarding CM services provided, personnel delivering these services, target populations, and setting(s). Successful implementation was characterized by resource availability (both monetary and nonmonetary), identifying as well as training employees with the right technical expertise and interpersonal skills, and embedding CM within practices. Our findings facilitate future context-specific implementation of CM within medical homes. They also inform the development of medical home recognition programs that anticipate and allow for contextual variation.

Individual versus interprofessional team performance in formulating care transition plans: A randomised study of trainees from five professional groups.

Health professions trainees' performance in teams is rarely evaluated, but increasingly important as the healthcare delivery systems in which they will practice move towards team-based care. Effective management of care transitions is an important aspect of interprofessional teamwork. This mixed-methods study used a crossover design to randomise health professions trainees to work as individuals and as teams to formulate written care transition plans. Experienced external raters assessed the quality of the written care transition plans as well as both the quality of team process and overall team performance. Written care transition plan quality did not vary between individuals and teams (21.8 vs. 24.4, respectively, p = 0.42). The quality of team process did not correlate with the quality of the team-generated written care transition plans (r = -0.172, p = 0.659). However, there was a significant correlation between the quality of team process and overall team performance (r = 0.692, p = 0.039). Teams with highly engaged recorders, performing an internal team debrief, had higher-quality care transition plans. These results suggest that high-quality interprofessional care transition plans may require advance instruction as well as teamwork in finalising the plan.

Making cognitive decision support work: Facilitating adoption, knowledge and behavior change through QI.

This paper evaluates the role of facilitation in the successful implementation of Computerized Decision Support (CDS). Facilitation processes include education, specialized computerized decision support, and work process reengineering. These techniques, as well as modeling and feedback enhance self-efficacy, which we propose is one of the factors that mediate the effectiveness of any CDS. In this study, outpatient clinics implemented quality improvement (QI) projects focused on improving geriatric care. Quality Improvement is the systematic process of improving quality through continuous measurement and targeted actions. The program, entitled "Advancing Geriatric Education through Quality Improvement" (AGE QI), consisted of a 6-month, QI based, intervention: (1) 2h didactic session, (2) 1h QI planning session, (3) computerized decision support design and implementation, (4) QI facilitation activities, (5) outcome feedback, and (6) 20h of CME. Specifically, we examined the impact of the QI based program on clinician's perceived self-efficacy in caring for older adults and the relationship of implementation support and facilitation on perceived success. The intervention was implemented at 3 institutions, 27 community healthcare system clinics, and 134 providers. This study reports the results of pre/post surveys for the forty-nine clinicians who completed the full CME program. Self-efficacy ratings for specific clinical behaviors related to care of older adults were assessed using a Likert based instrument. Self-ratings of efficacy improved across the following domains (depression, falls, end-of-life, functional status and medication management) and specifically in QI targeted domains and were associated with overall clinic improvements.

Factors that influence physical function and emotional well-being among Medicare-Medicaid enrollees.

Dually enrolled Medicare-Medicaid older adults are a vulnerable population. We tested House's Conceptual Framework for Understanding Social Inequalities in Health and Aging in Medicare-Medicaid enrollees by examining the extent to which disparities indicators, which included race, age, gender, neighborhood poverty, education, income, exercise (e.g., walking), and physical activity (e.g., housework) influence physical function and emotional well-being. This secondary analysis included 337 Black (31%) and White (69%) older Medicare-Medicaid enrollees. Using path analysis, we determined that race, neighborhood poverty, education, and income did not influence physical function or emotional well-being. However, physical activity (e.g., housework) was associated with an increased self-report of physical function and emotional well-being of ß = .23, p < .001; ß = .17, p < .01, respectively. Future studies of factors that influence physical function and emotional well-being in this population should take into account health status indicators such as allostatic load, comorbidity, and perceived racism/discrimination.

Clinical questions raised by providers in the care of older adults: a prospective observational study.

OBJECTIVE: To characterise clinical questions raised by providers in the care of complex older adults in order to guide the design of interventions that can help providers answer these questions. MATERIALS AND METHODS: To elicit clinical questions, we observed and audio recorded outpatient visits at three healthcare organisations. At the end of each appointment, providers were asked to identify clinical questions raised in the visit. Providers rated their questions based on their urgency, importance to the patient's care and difficulty in finding a useful answer to. Transcripts of the audio recordings were analysed to identify ageing-specific factors that may have contributed to the nature of the questions. RESULTS: We observed 36 patient visits with 10 providers at the three study sites. Providers raised 70 clinical questions (median of 2 clinical questions per patient seen; range 0-12), pursued 50 (71%) and successfully answered 34 (68%) of the questions they pursued. Overall, 36 (51%) of providers' questions were not answered. Over one-third of the questions were about treatment alternatives and adverse effects. All but two clinical questions were motivated either directly or indirectly by issues related to ageing, such as the normal physiological changes of ageing and diseases with higher prevalence in the elderly. CONCLUSIONS: The frequency of clinical questions was higher than in previous studies conducted in general primary care patient populations. Clinical questions were predominantly influenced by ageing-related issues. We propose a series of recommendations that may be used to guide the design of solutions to help providers answer their clinical questions in the care of older adults.

Electronic end-of-life care registry: the Utah ePOLST initiative.

As a patient's end-of-life approaches, it is typical for the disease to be the focus of treatment instead of the dying patient. There is limited congruence between the care preferred by patients and the treatment actually delivered to patients during their end-of-life. The Physician Orders for Life-Sustaining Treatment Paradigm has been endorsed or is in development in all but three states and the District of Columbia in an effort to ensure that patients are provided with adequate opportunities to specify their end-of-life care preferences. However, most states are using paper forms to document these preferences which may be inaccessible when needed. We have developed an electronic end-of-life care registry that allows authorized users to store and retrieve information pertaining to patients' end-of-life care preferences. In this paper, we describe (a) the requirements identified for the registry from the users' perspective and (b) the design and development of the electronic registry.

The role of information technology in translating educational interventions into practice: an analysis using the PRECEDE/PROCEED model.

OBJECTIVE: The evidence base for information technology (IT) has been criticized, especially with the current emphasis on translational science. The purpose of this paper is to present an analysis of the role of IT in the implementation of a geriatric education and quality improvement (QI) intervention. DESIGN: A mixed-method three-group comparative design was used. The PRECEDE/PROCEED implementation model was used to qualitatively identify key factors in the implementation process. These results were further explored in a quantitative analysis. METHOD: Thirty-three primary care clinics at three institutions (Intermountain Healthcare, VA Salt Lake City Health Care System, and University of Utah) participated. The program consisted of an onsite, didactic session, QI planning and 6 months of intense implementation support. RESULTS: Completion rate was 82% with an average improvement rate of 21%. Important predisposing factors for success included an established electronic record and a culture of quality. The reinforcing and enabling factors included free continuing medical education credits, feedback, IT access, and flexible support. The relationship between IT and QI emerged as a central factor. Quantitative analysis found significant differences between institutions for pre-post changes even after the number and category of implementation strategies had been controlled for. CONCLUSIONS: The analysis illustrates the complex dependence between IT interventions, institutional characteristics, and implementation practices. Access to IT tools and data by individual clinicians may be a key factor for the success of QI projects. Institutions vary widely in the degree of access to IT tools and support. This article suggests that more attention be paid to the QI and IT department relationship.

Potentially inappropriate medication prescribing in outpatient practices: prevalence and patient characteristics based on electronic health records.

BACKGROUND: Some older adults receive potentially inappropriate medications (PIMs), increasing their risk for adverse events. A literature search did not find any US multicenter studies that measured the prevalence of PIMs in outpatient practices based on data from electronic health records (EHRs), using both the Beers and Zhan criteria. OBJECTIVES: The aims of the present study were to compare the prevalence of PIMs using standard drug terminologies at 2 disparate institutions using EHRs and to identify characteristics of elderly patients who have a PIM on their active-medication lists. METHODS: This cross-sectional study of outpatients' active-medication lists from April 1, 2006, was conducted using data from 2 outpatient primary care settings: Intermountain Healthcare, Salt Lake City, Utah (center 1), and the Cleveland Clinic, Cleveland, Ohio (center 2). Data were included from patients who were aged > or =65 years at the time of the last office visit and had > or =2 documented clinic visits within the previous 2 years. The primary end point was prevalence of PIMs, measured according to the 2002 Beers criteria or the 2001 Zhan criteria. RESULTS: Data from 61,251 patients were included (36,663 women, 24,588 men; center 1: 37,247 patients; center 2: 24,004). A total of 8693 (23.3%) and 5528 (23.0%) patients at centers 1 and 2, respectively, were documented as receiving a PIM as per the Beers criteria; this difference was not statistically significant. Per the Zhan criteria (P < 0.001), these values were 6036 (16.2%) and 4160 (17.3%). Eight of the most common PIMs were the same at both institutions, with propoxyphene and fluoxetine (once daily) being the most prescribed. Female sex, polypharmacy (> or =6 medications), and multiple primary care visits were significantly associated with PIM prescribing. CONCLUSIONS: In this analysis of data from elderly patients at 2 outpatient centers, a small set of 8 medications accounted for the majority of PIMs at both centers, irrespective of geographic and demographic variations. Female sex, polypharmacy, and number of primary care visits were significantly associated with PIM prescribing. In this analysis of data from elderly patients at 2 outpatient centers, a small set of 8 medications accounted for the majority of PIMs at both centers, irrespective of geographic and demographic variations.

The effect of technology-supported, multidisease care management on the mortality and hospitalization of seniors.

OBJECTIVES: To explore changes in mortality and hospital usage for chronically ill seniors enrolled in a multidisease care management program, Care Management Plus (CMP). DESIGN: Controlled clinical trial with seven intervention and six control clinics with additional patient-level matching. SETTING: Intermountain Health Care, a large health system in Utah; seven intervention and six control clinics. PARTICIPANTS: Three thousand four hundred thirty-two senior patients (>or=65) enrolled in Medicare. INTERVENTION: The intervention employed nurse care managers supported by specialized information technology in primary care to manage chronically ill patients (2002-2005). MEASUREMENTS: Mortality and hospitalization data were collected from clinical records and Medicare billing. RESULTS: One thousand one hundred forty-four intervention patients were matched to 2,288 controls. Average age was 76.2; average comorbidity score was 2.3+/-1.1; 75% of patients had two or more chronic diseases. Survival analyses showed lower mortality and slightly more emergency department visits for care managed patients than for controls. In patients with diabetes mellitus, the intervention resulted in significantly lower mortality at 1 year (6.2%, vs 10.6% for controls) and at 2 years (12.9% vs 18.2%). Hospitalization rate was lower (21.0%, vs. 24.2% for controls) at 1 year and substantially more so at the 2-year follow-up. CONCLUSION: CMP was successful in reducing death for all patients. For complex patients with diabetes mellitus in the intervention group, death and hospital usage were lower. Per clinic, hypothesized savings from decreased hospitalizations was $17,384 to $70,349.

Care management dosage.

BACKGROUND: The care of patients with complex illnesses requires careful management, but systems of care management (CM) vary in their structure and effectiveness. OBJECTIVE: To create a framework identifying components of broad-based CM interventions and validate the framework, including using this framework to evaluate the contribution of varying components on outcomes of patients with chronic illness. DESIGN: We create the framework using retrospective information about CM activities and services over 12 months and categorize it using cluster and factor analysis. We then validate this framework through content and criterion techniques. Content validity is assessed through a Delphi study and criterion validity through relationship of the dosage measures and patterns of care to process and outcomes measures. PARTICIPANTS: Patients with diabetes and/or cardiovascular disease receiving CM services in a model known as Care Management Plus implemented in primary care. RESULTS: Six factors of CM activity were identified, including a single dosage summary measure and 5 separate patterns of care. Of these, the overall dosage summary measure, face-to-face time, duration of follow-up, and breadth of services were all related to improved processes for hemoglobin A1c and LDL testing and control. Brief intense patterns of care and high face-to-face care manager time were also related to improved outcomes. CONCLUSIONS: Using this framework, we isolate components of a CM intervention directly related to improved process of care or patient outcomes. Current efforts to structure CM to include face-to-face time and multiple diseases are discussed.

Productivity enhancement for primary care providers using multicondition care management.

OBJECTIVE: To assess the impact of a multicondition care management system on primary care physician efficiency and productivity. STUDY DESIGN: Retrospective controlled repeated-measures design comparing physician productivity with the proportion of patients in the care management system. METHODS: The setting was primary care clinics in Intermountain Healthcare, a large integrated delivery network. The care management system consisted of a trained team with nurses as care managers and specialized information technology. We defined the use of the care management system as a proportion of referrals by the physician to the care manager. Clinic, physician, and patient panel demographics were used to adjust expected visit productivity and were included in a multivariate mixed model with repeated measures comprising work relative value units and system use. RESULTS: The productivity of 120 physicians in 7 intervention clinics and 14 control clinics was compared during 24 months. Clinic, physician, and patient panel characteristics exhibited similar characteristics, although patients in intervention clinics were less likely to be married. Adjusted work relative value units were 8% (range, 5%-12%) higher for intervention clinics vs control clinics. Additional annual revenue was estimated at 99,986 dollars per clinic. These additional revenues outweighed the estimated cost of the program of 92,077 dollars. CONCLUSIONS: Physician productivity increased when more than 2% of patients were seen by a care management team; the increased revenue in our market exceeded the cost of the program. Implications for the creation, structure, and reimbursement of such teams are discussed.

Use of health-related, quality-of-life metrics to predict mortality and hospitalizations in community-dwelling seniors.

OBJECTIVES: To investigate whether health-related quality-of-life (HRQoL) scores in a primary care population can be used as a predictor of future hospital utilization and mortality. DESIGN: Prospective cohort study measuring Short Form 12 (SF-12) scores obtained using a mailed survey. SF-12 scores, age, and a comorbidity score were used to predict hospitalization and mortality rate using multivariable logistic regression and Cox proportional hazards during the ensuing 28-month period for elderly patients. SETTING: Intermountain Health Care, a large integrated-delivery network serving a population of more than 150,000 seniors. PARTICIPANTS: Participants were senior patients who had one or more chronic diseases, were community dwelling, and were initially treated in primary care clinics. MEASUREMENTS: SF-12 survey Version 1. RESULTS: Seven thousand seventy-six surveys were sent to eligible participants; 3,042 (43%) were returned. Of the returned surveys, 2,166 (71%) were complete and scoreable. For the respondent group, a multivariable analysis demonstrated that older age, male sex, higher comorbidity score, and lower mental and physical summary measures of SF-12 predicted higher mortality and hospitalization. On average, nonresponders were older and had higher comorbidity scores and mortality rates than responders. CONCLUSION: The SF-12 survey provided additional predictive ability for future hospitalizations and mortality. Such predictive ability might facilitate preemptive interventions that would change the course of disease in this segment of the population. However, nonresponder bias may limit the utility of mailed SF-12 surveys in certain populations.

Implementing a multidisease chronic care model in primary care using people and technology.

Management of chronic disease is performed inadequately in the United States in spite of the availability of beneficial, effective therapies. Successful programs to manage patients with these diseases must overcome multiple challenges, including the recognized fragmentation and complexity of the healthcare system, misaligned incentives, a focus on acute problems, and a lack of team-based care. In many successful programs, care is provided in settings or episodes that focus on a single disease. While these programs may allow for streamlined, focused provision of care, comprehensive care for multiple diseases may be more difficult. At Intermountain Healthcare (Intermountain), a generalist model of chronic disease management was formulated to overcome the limitations associated with specialization. In the Intermountain approach, which reflects elements of the Chronic Care Model (CCM), care managers located within multipayer primary care clinics collaborate with physicians, patients, and other members of a primary care team to improve patient outcomes for a variety of conditions. An important part of the intervention is widespread use of an electronic health record (EHR). This EHR provides flexible access to clinical data, individualized decision support designed to encourage best practice for patients with a variety of diseases (including co-occurring ones), and convenient communication between providers. This generalized model is used to treat diverse patients with disparate and coexisting chronic conditions. Early results from the application of this model show improved patient outcomes and improved physician productivity. Success factors, challenges, and obstacles in implementing the model are discussed.

Use and impact of a computer-generated patient summary worksheet for primary care.

Advanced clinical information systems have been proposed to improve patient care in terms of safety, effectiveness, and efficiency. In order to be effective, such systems require detailed patient-specific clinical information in a form easily reviewed by clinicians. We have developed a patient summary worksheet for use in outpatient clinics, which presents a structured overview of patient health information. The worksheet provides patient demographic information, specific problems and conditions, the patient's current medication profile, laboratory test results pertinent to patient problems, and disease-specific or preventive care actionable advisories. Usage has grown from a few hundred to over 25,000 unique patients per month during a two-year period. Diabetic patients for whom the worksheet is accessed are significantly more likely to be in compliance with accepted testing regimens for glycosolated hemoglobin (OR 1.47, 95% CI 1.28, 1.61).

Drug-age alerting for outpatient geriatric prescriptions: a joint study using interoperable drug standards.

For more than a decade, the Beers criteria have identified specific medications that should generally be avoided in the geriatric population. Studies that have shown high prevalence rates of these potentially inappropriate medications have used disparate methodologies to identify these medications and hence are difficult to replicate and generalize. In an effort to improve prescribing behavior, we are building a drug-age alerting system utilizing standard drug coding systems for use in our Electronic Health Record (EHR) systems.