Cindy Bryce

Hypoglycemia is the most common serious adverse effect of diabetes treatment and a major cause of medication-related hospitalization. This study aimed to identify trends and predictors of hospital utilization for hypoglycemia among adults with type 2 diabetes. Using electronic health record data from six academic health systems, we performed a retrospective open cohort study including 532,323 patients aged ≥18 years with type 2 diabetes receiving regular care between 2009 and 2019. The primary outcome was the yearly event rate for hypoglycemia hospital utilization: emergency department visits, observation visits, or inpatient admissions for hypoglycemia identified using a validated ICD-9 algorithm. After the transition to ICD-10 in 2015, we used two ICD-10 code sets for hypoglycemia (limited and expanded) that were used in prior studies. We identified independent predictors of hypoglycemia hospital utilization using multivariable logistic regression analysis with data from 2014. We found that yearly rates of hypoglycemia hospital utilization decreased non-significantly from 3.4 to 2.6 events per 1,000 patients from 2009 to 2014. From 2016 to 2019, yearly event rates ranged from 15.5 to 16.5, or 21.1 to 21.8, using the limited and expanded ICD-10 code sets, respectively. The strongest independent risk factors for hypoglycemia hospital utilization were chronic kidney disease (OR 3.13, 95% CI 2.63-3.70), age 18-39 years (OR 3.00 vs. age 40-64 years, 95% CI 2.42-3.73), and insulin use (OR 2.61 vs. no diabetes medications, 95% CI 2.16-3.15). In this multicenter open cohort study, we found that rates of hypoglycemia hospital utilization were stable from 2009 to 2014 and varied considerably by clinical risk factors such that younger adults, insulin users, and those with chronic kidney disease were at especially high risk. There is a need to validate hypoglycemia ascertainment using ICD-10 codes, which detect a substantially higher number of events compared to ICD-9. Disclosure S. J. Pilla: None. J. L. Kraschnewski: None. E. Lehman: None. L. Kong: None. E. Francis: None. J. M. Poger: None. C. L. Bryce: None. N. M. Maruthur: Other Relationship; Self; Johns Hopkins HealthCare Solutions. H. Yeh: None. Funding National Institutes of Health (KL2TR003099); Patient-Centered Outcomes Research Institute (1306-04912)

Obesity is associated with many chronic medical conditions (1, 2). Most persons who lose weight through lifestyle interventions eventually regain it (3). Sustained lifestyle support (1, 46) and consistent self-monitoring of behaviors and weight (7, 8) are key strategies for promoting maintenance of weight loss. Interventions that support self-monitoring by leveraging the long-term relationship between patients and their primary care health team could address this problem. Few randomized clinical trials to date have focused on weight maintenance, and most did not recruit patients with weight-related comorbidities, such as diabetes (911). Others that recruited from primary care did not coordinate the intervention with routine care and the ongoing patientprovider relationship (12, 13). Weight maintenance interventions can be integrated into routine primary care by using the electronic health record (EHR) to identify potentially eligible patients, establish ongoing contact with patients during the intervention, and engage the primary care provider (PCP). This randomized clinical trial tested the hypothesis that there would be incremental benefit of personalized coaching and PCP support in an EHR-based intervention designed to help primary care patients maintain recent intentional weight loss of at least 5%. Methods Study Overview MAINTAIN-pc (Maintaining Activity and Nutrition through Technology-Assisted Innovation in Primary Care) was a randomized trial conducted in coordination with practices affiliated with the University of Pittsburgh Medical Center (UPMC). Participants were recruited between October 2013 and February 2015, and follow-up was completed in March 2017. The University of Pittsburgh Institutional Review Board approved the study, and all participants provided written informed consent. The trial was initially designed to be a 36-month intervention, with the primary outcome defined as weight change at 36 months. Delays in EHR build and recruitment resulted in a decision after enrollment was completed to shorten the intervention to 24 months, with 24-month weight change as the revised primary outcome. In addition, we added an exploratory 30-month weight outcome to assess the duration of effect after the intervention ended. An updated institutional review board protocol (with revised consent) was approved on 25 September 2015. These changes were made before any data were analyzed. The study protocol is available in the Supplement. Supplement. Study Protocol Participants Practice-based recruitment tools in 9 primary care practices and 1 specialty practice (endocrinology) included an EHR alert that identified potentially eligible patients and allowed for creation of a study referral order, visits to practice meetings to familiarize physicians and staff with the trial, and flyers and brochures. Secondary recruitment efforts included letters to research registry participants, electronic campus newsletter postings, and outreach to local weight loss studies. Participants with PCPs in UPMC primary care practices without practice-based recruitment tools (nontargeted practices) were also enrolled. Interested participants contacted study staff and completed a telephone screening, which included a review of EHR data to confirm a minimum prior weight loss of 5%. An in-person baseline assessment conducted by study staff was scheduled for those who were eligible, interested, and approved for participation by their PCP. During the baseline assessment, participants provided informed consent and then completed baseline measurements and surveys. Eligibility criteria included age 18 to 75 years, intentional weight loss of at least 5% in the previous 2 years, access to an Internet-connected computer, and receipt of care from a UPMC PCP. Exclusion criteria included a medical explanation for recent weight loss (for example, cancer), active preparation for bariatric surgery, bariatric surgery in the previous 5 years, or pregnancy. Randomization Eligible participants were assigned in a 1:1 ratio to the coaching group or the tracking group using computer-generated permuted block randomization with block sizes of 4 and 6 persons and stratification by sex and site of primary care. The study statistician (D.T.) generated the allocation sequence, and study staff obtained assignments from the data center Web site. Assignments were given to participants after baseline assessment by study staff. Intervention All participants received a 1-hour orientation on the EHR-based tracking tools (weight, diet, and physical activity tracking flow sheets) and basic information about healthy eating and safe physical activity. Participants were encouraged to log in daily and enter data on weight, diet, and physical activity. Those in the coaching group also received an introduction to the role of the coaches. Both groups received weekly reminders to enter information into the EHR-based tracking tools. Participants in the coaching group received…

Purpose The purpose of this qualitative study was to explore perceptions of people with diabetes about their experience of living with and managing their diabetes. Methods This study was part of a larger study of patients with diabetes who used a novel computer portal system for access to information about diabetes and to their health care providers for enhanced communication. The research method used for this portion of the study was grounded theory methodology, a particular kind of qualitative research method. Results A central theme generated from the data was “normalizing an identity as a person with diabetes.” The participants described themselves as diabetic; they took on an identity in which having diabetes was central. They struggled with how to become “a person with diabetes” rather than a “diabetic person.” Conclusions For people who are diagnosed with diabetes, there is a struggle to become a person with diabetes rather than a diabetic person and to manage the lifestyle changes that are mandated by this role/identity. One way of dealing or coping with this new identity is to begin to “normalize” these lifestyle changes—to view them as healthy living for all people, those with and without diabetes. This will then have implications for interventions—encouraging healthy lifestyles among people with diabetes rather than emphasizing that people with diabetes are “different from” the general population.

Introduction: Primary care physicians are uniquely positioned to provide counselling for weight loss, yet lifestyle habits of primary care patients with recent, intentional weight loss are unclear. Our objective was to characterize diet and exercise habits in primary care patients with recent, intentional weight loss, comparing those with greater (≥10%) to those with lesser (5 to <10%) weight loss. Methods: This cross-sectional analysis of baseline data from a weight loss maintenance clinical trial in a primary care setting included patients,18-75 years old, with ≥5% intentional weight loss via lifestyle change in the past 2 years. Recent weight loss was confirmed with medical records. Dietary habits were measured by the Connor Diet Habits Survey. Results: Participants (n=192, 74% female, 87% white) had mean (SD) age 53 (12) years, body mass index 30.4 (5.9) kg/m 2 , and recent weight loss of 11 (8) %. Participants had a high burden of comorbidities: high blood pressure (50%), dyslipidemia (43%), diabetes (14%), and cardiovascular disease (10%). Participants reported high median intake of fruits and vegetables (5 servings/day), and low intake of fried foods (1 servings/wk), desserts (1 serving/wk) and sugar-sweetened beverages (0 serving/wk) (see Table) . Participants ate at restaurants on average twice/wk and most drank skim milk. Those with greater weight loss had higher intakes of fruits and vegetables (p=0.04) and low fat foods/recipes (p=0.02); other dietary habits were not related to amount of recent weight loss (see Table ). Conclusions: Despite the plethora of studies that support and refute a variety of dietary recommendations to promote weight loss, dietary habits in primary care patients with a high burden of comorbidities and recent, intentional weight loss were consistent with conventional wisdom including: more fruits and vegetables, limited added sugars, and more low fat foods and recipes. Future research should test the effects of this eating pattern in a primary care setting for weight loss and maintenance.

Introduction: Though weight loss can improve health, weight regain is common. Primary care physicians are uniquely positioned to provide counseling for weight loss maintenance given their longitudinal care of patients, yet evidence of simple lifestyle recommendations for maintaining weight loss in primary care patients is lacking. Our objective was to characterize longitudinal associations between diet habits and weight change among primary care patients with recent, intentional weight loss of at least 5%. Methods: This was a secondary analysis of data from a weight loss maintenance clinical trial in a primary care setting that compared two interventions delivered through the electronic health record: continued coaching vs. tracking only. Dietary habits [fried foods, desserts, fruits and vegetables (F&V), and sugar-sweetened beverages (SSB)] were measured by the Connor Diet Habits Survey. Linear regression models were used to evaluate associations (overall and by randomized group) between changes in dietary habits and weight separately at 6- and 24-month follow-up, adjusted for baseline diet habit, age, gender and clinic location. Results: Participants (n=192) were 74% female, 87% white and had baseline mean (SD) age of 53 (12) years, body mass index of 30.4 (5.9) kg/m 2 , and recent weight loss of 11 (8) percent. Overall, participants had mean (SD) weight loss of 0.18 (5.04) kg at 6 months (n=169) and weight gain of 3.26 (7.60) kg at 24 months (n=140). At 6 months, a 1 serving per week increase in dessert intake was associated with 0.53 kg (p=0.030) greater weight gain. Fried foods, F&V, and SSB were not associated with 6-month weight changes. However, by 24 months, an increase of 1 serving per week was associated with greater weight gain of 0.54 kg (p=0.043) for fried foods, 0.80 kg (p=0.031) for desserts, and 2.01 kg (p=0.002) for SSB. A decrease of 1 F&V serving per day was associated with a 0.82 kg (p=0.008) greater weight gain at 24 months. When stratified by randomized group, associations were stronger in the continued coaching vs. tracking only arm. Conclusions: Increased consumption of desserts was associated with weight regain at 6 and 24 months, while increased fried foods and SSB, and decreased F&V were associated with weight regain at 24 months. These data suggest that simple strategies such as improving or at least maintaining dietary intake of fried foods, desserts, F&V, and SSB could help facilitate long-term weight loss maintenance in primary care patients.

BACKGROUND The Society for Surgical Oncology's Choosing Wisely guidelines recommend against sentinel lymph node biopsy (SLNB) in favor of observation in this population. Recent analyses reveal that this has not been widely adopted. The purpose of this cost-effectiveness analysis is to compare the costs and benefits associated with observation or SLNB in women >70 years old with hormone receptor-positive, clinically node-negative, operable breast cancer. METHODS A decision tree with Markov modeling was created to compare treatment strategies using long-term follow-up data from clinical trials in this population. Costs were estimated from published literature and publicly available databases. Breast cancer-specific health-state utilities were derived from the literature and expert opinion. One-way, 2-way, and probabilistic sensitivity analyses were conducted. A structural sensitivity analysis was performed to assess the effect of functional status and anxiety from nonevaluation of the axilla on cost-effectiveness. Costs and benefits, measured in life-years (LYs) and quality-adjusted life-years (QALYs), were tabulated across 10, 15, and 20 years and compared using incremental cost-effectiveness ratios (ICERs). RESULTS SLNB is not cost-effective from the payer or societal perspectives with ICERs of $138,374/LY and $131,900/LY, respectively. When QALYs were considered, SLNB provided fewer QALYs (SLNB, 10.33 QALYs; observation, 10.53 QALYs) at a higher cost (SLNB, $15,845; observation, $4020). Structural sensitivity analysis revealed that SLNB was cost-effective in certain patients with significant anxiety related to axillary observation (ICER, $39,417/QALY). CONCLUSIONS Routine SLNB in this population is not cost-effective. The cost-effectiveness of SLNB, however, is dependent on individual patient factors, including functional status as well as patient preference.

(See the article by McKinnell et al, on pages 2–13.) Methicillin-resistant Staphylococcus aureus (MRSA) has been a dominant healthcare-associated pathogen worldwide— except in some European countries in which a “search and destroy” policy has been implemented that includes active surveillance testing (AST), pre-emptive isolation, and contact precautions (CP). Although AST has reduced MRSA healthcare-associated infections (HAI) in various observational studies, the necessity of universal MRSA AST upon hospital admission in the United States remains controversial among experts. Economic analysis has been adopted to assess the effectiveness and viability of MRSA AST. In this issue of ICHE, McKinnell et al examined the economic impact of universal MRSA AST by comparing the costs of AST/CP with the benefits of preventing consecutive MRSA HAI. Their study design is unique in terms of the additional comparison elements of screening sites (ie, nares only vs nares and oropharynx vs multiple sites) and AST methods (ie, chromogenic agar vs polymerase chain reaction [PCR]). However, we must be cautious when interpreting their results for the following reasons. The authors suggest that their results can be used to estimate the cost-benefits of universal AST for a hospital with any number of admissions using a simple calculation comprising estimated costs per 10,000 hospital admissions. This is an ambitious generalization. Without defining a specific hospital setting, this analysis cannot represent all hospital types due to variations in hospital characteristics such as MRSA incidence, CP compliance, patient population (eg, severity of illness), and services provided (eg, tertiary care). Although model input parameters were extracted from systematic reviews and parameter uncertainties were handled by sensitivity analysis, the generalizability of results from their model is restricted to hospitals with similar input parameters within the ranges of this study. Model-based economic analysis is well suited to assist the decision-making process among alternative options given limited resources. However, it can lead us astray if bias affects any part of the modeling structure or its assumptions. In fact, the economic analysis method can be complex, and its results are often presented in a modeler-oriented way that nonexpert audiences may find difficult to follow. Even economic analysis studies on the same intervention (eg, MRSA AST) can yield significantly different results depending on the modeler’s choices of (1) decision model structure and (2) weighted value of and method for combining selected costs and outcomes. In fact, one coauthor of this study (Lee) has reported contrary findings. Even more troubling, if modelers had prior beliefs in the positive or negative results of a specific intervention, they might be able to manipulate or may be at risk of unconsciously affecting the economic analysis to support a particular conclusion. Additionally, because of the shortage of high-quality data available for input parameters (eg, costs, probabilities), modelers often use published data or make assumptions based on expert opinions. Therefore, when making decisions based on published economic evaluations, we need to carefully assess the modelers’ choice of decision model structure and input parameters before considering any results. In McKinnell et al, several necessary assumptions implicit in the modeling analysis remain unstated and could benefit from clarification. First, the authors do not specify how their model treated the impact of turnaround time differences in the two featured AST methods (ie, chromogenic agar vs PCR). Although both methods provide rapid turnaround times compared to a conventional microbiological culture with a diagnostic delay of 3–5 days, a Dutch multicenter study reports that a chromogenic-based method is cost-saving compared to two PCR-based methods, resulting in lower costs per test (€2.08 vs €56.22/€69.62) and increased pre-emptive isolation hours (30 vs 19.7/16.1 h). In a pilot study at our hospital,

The determinants of experiencing menopausal symptoms are complex, representing biological, psychological, and social factors. We report the impact of one such factor, fertility, on the experience of menopausal symptoms. We hypothesize that nulliparous women will have more dissatisfaction with childbearing choices and more negative attitudes toward menopause but will experience fewer menopausal symptoms. Women aged 40 to 65 years were recruited from a single internal medicine practice to participate in a 5-year longitudinal study of the impact of menopause on health-related quality of life. Women completed questionnaires including the RAND-36, attitudes toward menopause, menopausal symptoms, and fertility and childbearing. Based on self-reported pregnancy and birth history, we categorized women as parous (one or more live births), nulligravida (no pregnancies or births), and nulliparous (one or more pregnancies and no live births). Categorical variables were analyzed using univariable and multivariable ordered logistic and logistic regression. Continuous variables were analyzed using Student's t test and multivariable linear regression techniques. The 728 participants were, on average, 50.8 years old with 2.4 pregnancies and 1.7 live births. Compared with parous women, nulligravida and nulliparous women were more likely to report being very dissatisfied with childbearing choices (odds ratio [OR] [95% CI]: 3.3 [2.3-4.6] and 4.0 [2.5-6.4], respectively). Nulliparous, but not nulligravida, women expressed more negative attitudes toward menopause compared with parous women (P<0.001). Nulligravida and nulliparous women were half as likely to report hot flashes as parous women (OR [95% CI]: 0.6 [0.4-0.9] and 0.5 [0.3-0.9], respectively). Compared with parous women, nulligravida women were less likely to report vaginal dryness (OR [95% CI]: 0.5 [0.3-0.7]). Our study examined the impact of pregnancy and birth history on menopausal symptoms, and the findings support the hypothesis that women who experience infertility may find menopause to be a time of normalcy and experience fewer hot flashes. Both physiologic and psychosocial mechanisms deserve further study.

<sec> <title>BACKGROUND</title> <p>Online tools are a convenient and effective method of delivering lifestyle interventions to obese adult primary care patients. A referral model allows physicians to efficiently direct their patients to the intervention during a primary care visit. However, little is known of physicians' perspectives and utilization of the referral model for an online lifestyle modification intervention.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The aim was to evaluate the response of primary care providers (PCPs) to a referral model for implementing a year-long online intervention for weight loss to obese adult patients.</p> </sec> <sec> <title>METHODS</title> <p>The PCPs at six primary care clinics were asked to refer adult obese patients to a year-long online lifestyle intervention providing self-management support for weight loss. Following the 1-year intervention, all providers at the participating practices were surveyed regarding their views of the program. Respondents completed survey items assessing their attitudes regarding the 1-year intensive weight loss intervention and identifying resources they would find helpful for assisting patients with weight loss. Referring physicians were asked about their level of satisfaction with implementing the counseling services using standard electronic health record referral processes. Attitudes toward obesity counseling among referring and nonreferring providers were compared. Impressions of how smoothly the referral model of obesity treatment integrated with the clinical workflow were also quantified.</p> </sec> <sec> <title>RESULTS</title> <p>Of the 67 providers who completed the surveys, nonreferring providers (n=17) were more likely to prefer counseling themselves (P=.04) and to report having sufficient time to do so (P=.03) than referring providers (n=50) were. Nonreferring providers were more likely to report that their patients lacked computer skills (76%, 13/17 vs 34%, 17/50) or had less access to the Internet (65%, 11/17 vs 32%, 16/50).</p> </sec> <sec> <title>CONCLUSIONS</title> <p>Understanding providers' views and barriers regarding the integration of online tools will facilitate widespread implementation of an online lifestyle modification intervention.</p> </sec>

ABSTRACT The presence of HIV infection, alone or in combination with other infections and diseases, can have a serious impact on a patient’s health and quality of life (QOL). According to the World Health Organization (WHO) Constitution of 1948, “Health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity” [1]. Like the definition of health, the definition of QOL is broad and multidimensional, “[An] individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns” [2].

Introduction: Allosensitized children listed with a requirement for a negative prospective crossmatch (XM) have a high risk of death awaiting heart transplantation (HTx). Previously we found that acceptance of the first suitable organ offer for these patients, regardless of the possibility of a +XM, results in a survival benefit at all times after listing, including post-HTx. The cost-effectiveness of this strategy is unknown. Methods: We used a Markov-state transition model with a 10 yr time horizon to compare survival, costs, and utility (i.e. quality of life) for 2 waitlist strategies for sensitized candidates: requiring a negative prospective XM (WAIT) vs. accepting the first suitable organ offer (TAKE). Model data were derived from OPTN status 1A pediatric HTx listings from 1999-2009, the PHTS and HCUP KIDS databases, and other published sources. We assumed no possibility of a +XM in the wait strategy and that the probability of a +XM in the take strategy was equal to the pre-t...