Understanding the Information Needs of Pharmacy Staff Using CancelRx: A Qualitative Study of the Use of Prescription E-cancellation.

Background: Although electronic prescription cancellation such as via CancelRx can facilitate critical communication between prescribers and pharmacy staff about discontinued medications, there is little work that explores whether CancelRx meets the needs of pharmacy staff users. Objective: This study leverages qualitative interviews with pharmacy staff to address the following question: When medication changes are made by a prescriber using CancelRx, what information is needed by pharmacy staff to make correct and effective decisions in their roles in medication management? Methods: We conducted an inductive thematic analysis of interviews with 11 pharmacy staff members (pharmacists and pharmacy technicians) across three outpatient community pharmacy sites within an academic health care system. Results: Three information needs themes were consistently identified by both pharmacists and pharmacy technicians: prescriber intent when initiating the CancelRx, clinical rationale for the medication change, and intended medication regimen. Notably, both pharmacists and pharmacy technicians often reported seeking multiple information needs not fully addressed by CancelRx in the electronic health record (EHR) to achieve the shared goals of correct dispensing of medications and supporting patient self-management. Conclusions: Our qualitative analysis reveals that outpatient community pharmacy staff in an academic health care system often seek additional information from the (EHR) following medication changes communicated by CancelRx to meet their information needs. Ideally, the prescriber would provide sufficient information through CancelRx to automatically identify all discontinued prescriptions. These limitations highlight the need for design features that support routine communication of needed information at the time of a medication change, such as structured data elements.

Prevalence of lifestyle-related behavioral information in claims data in the U.S.

OBJECTIVE: Given their association with varying health risks, lifestyle-related behaviors are essential to consider in population-level disease prevention. Health insurance claims are a key source of information for population health analytics, but the availability of lifestyle information within claims data is unknown. Our goal was to assess the availability and prevalence of data items that describe lifestyle behaviors across several domains within a large U.S. claims database. METHODS: We conducted a retrospective, descriptive analysis to determine the availability of the following claims-derived lifestyle domains: nutrition, eating habits, physical activity, weight status, emotional wellness, sleep, tobacco use, and substance use. To define these domains, we applied a serial review process with three physicians to identify relevant diagnosis and procedure codes within claims for each domain. We used enrollment files and medical claims from a large national U.S. health plan to identify lifestyle relevant codes filed between 2016 and 2020. We calculated the annual prevalence of each claims-derived lifestyle domain and the proportion of patients by count within each domain. RESULTS: Approximately half of all members within the sample had claims information that identified at least one lifestyle domain (2016 = 41.9%; 2017 = 46.1%; 2018 = 49.6%; 2019 = 52.5%; 2020 = 50.6% of patients). Most commonly identified domains were weight status (19.9-30.7% across years), nutrition (13.3-17.8%), and tobacco use (7.9-9.8%). CONCLUSION: Our study demonstrates the feasibility of using claims data to identify key lifestyle behaviors. Additional research is needed to confirm the accuracy and validity of our approach and determine its use in population-level disease prevention.

Obesity Management in Adults: A Review.

Importance: Obesity affects approximately 42% of US adults and is associated with increased rates of type 2 diabetes, hypertension, cardiovascular disease, sleep disorders, osteoarthritis, and premature death. Observations: A body mass index (BMI) of 25 or greater is commonly used to define overweight, and a BMI of 30 or greater to define obesity, with lower thresholds for Asian populations (BMI ≥25-27.5), although use of BMI alone is not recommended to determine individual risk. Individuals with obesity have higher rates of incident cardiovascular disease. In men with a BMI of 30 to 39, cardiovascular event rates are 20.21 per 1000 person-years compared with 13.72 per 1000 person-years in men with a normal BMI. In women with a BMI of 30 to 39.9, cardiovascular event rates are 9.97 per 1000 person-years compared with 6.37 per 1000 person-years in women with a normal BMI. Among people with obesity, 5% to 10% weight loss improves systolic blood pressure by about 3 mm Hg for those with hypertension, and may decrease hemoglobin A1c by 0.6% to 1% for those with type 2 diabetes. Evidence-based obesity treatment includes interventions addressing 5 major categories: behavioral interventions, nutrition, physical activity, pharmacotherapy, and metabolic/bariatric procedures. Comprehensive obesity care plans combine appropriate interventions for individual patients. Multicomponent behavioral interventions, ideally consisting of at least 14 sessions in 6 months to promote lifestyle changes, including components such as weight self-monitoring, dietary and physical activity counseling, and problem solving, often produce 5% to 10% weight loss, although weight regain occurs in 25% or more of participants at 2-year follow-up. Effective nutritional approaches focus on reducing total caloric intake and dietary strategies based on patient preferences. Physical activity without calorie reduction typically causes less weight loss (2-3 kg) but is important for weight-loss maintenance. Commonly prescribed medications such as antidepressants (eg, mirtazapine, amitriptyline) and antihyperglycemics such as glyburide or insulin cause weight gain, and clinicians should review and consider alternatives. Antiobesity medications are recommended for nonpregnant patients with obesity or overweight and weight-related comorbidities in conjunction with lifestyle modifications. Six medications are currently approved by the US Food and Drug Administration for long-term use: glucagon-like peptide receptor 1 (GLP-1) agonists (semaglutide and liraglutide only), tirzepatide (a glucose-dependent insulinotropic polypeptide/GLP-1 agonist), phentermine-topiramate, naltrexone-bupropion, and orlistat. Of these, tirzepatide has the greatest effect, with mean weight loss of 21% at 72 weeks. Endoscopic procedures (ie, intragastric balloon and endoscopic sleeve gastroplasty) can attain 10% to 13% weight loss at 6 months. Weight loss from metabolic and bariatric surgeries (ie, laparoscopic sleeve gastrectomy and Roux-en-Y gastric bypass) ranges from 25% to 30% at 12 months. Maintaining long-term weight loss is difficult, and clinical guidelines support the use of long-term antiobesity medications when weight maintenance is inadequate with lifestyle interventions alone. Conclusion and Relevance: Obesity affects approximately 42% of adults in the US. Behavioral interventions can attain approximately 5% to 10% weight loss, GLP-1 agonists and glucose-dependent insulinotropic polypeptide/GLP-1 receptor agonists can attain approximately 8% to 21% weight loss, and bariatric surgery can attain approximately 25% to 30% weight loss. Comprehensive, evidence-based obesity treatment combines behavioral interventions, nutrition, physical activity, pharmacotherapy, and metabolic/bariatric procedures as appropriate for individual patients.

Use of medications associated with weight change among participants in the All of Us research programme.

Our objective was to describe the use of medications associated with weight change among US adults with overweight/obesity, including anti-obesity medications (AOMs), weight-loss-promoting and weight-gain-promoting medications. We performed a cross-sectional analysis of data from the nationwide All of Us Research Programme. We included adults with measured body mass index (BMI) ≥ 27 kg/m2 enrolled between 2018 and 2022 across the United States. We used linked electronic health record data to determine medication use ±12 months of BMI measure. Our 132 057 participants had mean age 54 years and mean BMI 34 kg/m2 ; 60% of participants were women, 62% White, and 32% Black. Only 1% used any AOM, and 14% used at least one weight-loss-promoting medication. We found that 36% used at least one weight-gain-promoting medication, and approximately 20% used multiple weight-gain-promoting medications. While AOMs are underutilized by participants with overweight/obesity, weight-gain-promoting medication use is common. Our results raise concern about potential iatrogenic weight gain from medications. Future research is needed to estimate the long-term effect of weight-gain-promoting medications on weight status and determine whether weight-loss benefits occur with their discontinuation. Clinician education on AOMs and weight-loss-promoting medications may be needed to increase their use.

Utility of an Electronic Health Record Report to Identify Patients with Delays in Testing for Poorly Controlled Diabetes.

BACKGROUND: Reducing hemoglobin A1c (HbA1c) is essential for patients with poorly controlled diabetes. However, delays in HbA1c testing are common, and incomplete electronic health record (EHR) reports hinder identification of patients who are overdue. This study sought to quantify how often an EHR report correctly identifies patients with HbA1c testing delays and to describe potential contributing factors. METHODS: Using an EHR report, the researchers identified adult patients who had an HbA1c > 9.0% between October 2017 and March 2018 and a suspected delay (for example, another HbA1c had not resulted within six months). A retrospective chart review of 200 randomly selected records was performed to confirm delays in testing. Secondary measures were collected from 93 charts to evaluate associated factors. RESULTS: A total of 685 patients with suspected delays were identified. On chart review (N = 200), 82.0% were confirmed. Nine percent of patients had a timely repeat result, but the result was not in a discrete field within the EHR. Another 8.5% were never expected to return. Among a subset of confirmed delays, patients often received lifestyle counseling, but less than half had documented discussions about repeat glycemic testing. Also, 74.2% had a timely follow-up appointment scheduled but the majority (85.5%) were missed. CONCLUSION: Most suspected delays in HbA1c testing were confirmed; however, a substantial minority were misclassified due to missing data or follow-up care outside the health system. Current solutions to improve data quality for HbA1c are labor intensive and highlight the need for better integration of health care data. Missed appointments were commonly noted among patients with delays in care and are a potential target for improvement.

Identification of Prediabetes Discussions in Unstructured Clinical Documentation: Validation of a Natural Language Processing Algorithm.

BACKGROUND: Prediabetes affects 1 in 3 US adults. Most are not receiving evidence-based interventions, so understanding how providers discuss prediabetes with patients will inform how to improve their care. OBJECTIVE: This study aimed to develop a natural language processing (NLP) algorithm using machine learning techniques to identify discussions of prediabetes in narrative documentation. METHODS: We developed and applied a keyword search strategy to identify discussions of prediabetes in clinical documentation for patients with prediabetes. We manually reviewed matching notes to determine which represented actual prediabetes discussions. We applied 7 machine learning models against our manual annotation. RESULTS: Machine learning classifiers were able to achieve classification results that were close to human performance with up to 98% precision and recall to identify prediabetes discussions in clinical documentation. CONCLUSIONS: We demonstrated that prediabetes discussions can be accurately identified using an NLP algorithm. This approach can be used to understand and identify prediabetes management practices in primary care, thereby informing interventions to improve guideline-concordant care.

Hypoglycemia Communication in Primary Care Visits for Patients with Diabetes.

BACKGROUND: Hypoglycemia is a common and serious adverse effect of diabetes treatment, especially for patients using insulin or insulin secretagogues. Guidelines recommend that these patients be assessed for interval hypoglycemic events at each clinical encounter and be provided anticipatory guidance for hypoglycemia prevention. OBJECTIVE: To determine the frequency and content of hypoglycemia communication in primary care visits. DESIGN: Qualitative study PARTICIPANTS: We examined 83 primary care visits from one urban health practice representing 8 clinicians and 33 patients using insulin or insulin secretagogues. APPROACH: Using a directed content analysis approach, we analyzed audio-recorded primary care visits collected as part of the Achieving Blood Pressure Control Together study, a randomized trial of behavioral interventions for hypertension. The coding framework included communication about interval hypoglycemia, defined as discussion of hypoglycemic events or symptoms; the components of hypoglycemia anticipatory guidance in diabetes guidelines; and hypoglycemia unawareness. Hypoglycemia documentation in visit notes was compared to visit transcripts. KEY RESULTS: Communication about interval hypoglycemia occurred in 24% of visits, and hypoglycemic events were reported in 16%. Despite patients voicing fear of hypoglycemia, clinicians rarely assessed hypoglycemia frequency, severity, or its impact on quality of life. Hypoglycemia anticipatory guidance was provided in 21% of visits which focused on diet and behavior change; clinicians rarely counseled on hypoglycemia treatment or avoidance of driving. Limited discussions of hypoglycemia unawareness occurred in 8% of visits. Documentation in visit notes had low sensitivity but high specificity for ascertaining interval hypoglycemia communication or hypoglycemic events, compared to visit transcripts. CONCLUSIONS: In this high hypoglycemia risk population, communication about interval hypoglycemia and counseling for hypoglycemia prevention occurred in a minority of visits. There is a need to support clinicians to more regularly assess their patients' hypoglycemia burden and enhance counseling practices in order to optimize hypoglycemia prevention in primary care.

Endoplasmic reticulum stress, the unfolded protein response, autophagy, and the integrated regulation of breast cancer cell fate.

How breast cancer cells respond to the stress of endocrine therapies determines whether they will acquire a resistant phenotype or execute a cell-death pathway. After a survival signal is successfully executed, a cell must decide whether it should replicate. How these cell-fate decisions are regulated is unclear, but evidence suggests that the signals that determine these outcomes are highly integrated. Central to the final cell-fate decision is signaling from the unfolded protein response, which can be activated following the sensing of stress within the endoplasmic reticulum. The duration of the response to stress is partly mediated by the duration of inositol-requiring enzyme-1 activation following its release from heat shock protein A5. The resulting signals appear to use several B-cell lymphoma-2 family members to both suppress apoptosis and activate autophagy. Changes in metabolism induced by cellular stress are key components of this regulatory system, and further adaptation of the metabolome is affected in response to stress. Here we describe the unfolded protein response, autophagy, and apoptosis, and how the regulation of these processes is integrated. Central topologic features of the signaling network that integrate cell-fate regulation and decision execution are discussed.

Interaction of dietary polyphenols with molecular signaling pathways of antiestrogen resistance: possible role in breast cancer recurrence.

Abstract Breast cancer is the most common cancer diagnosed in women and its global incidence is rising rapidly. Adjuvant hormonal therapy, with antiestrogens (AE) such as tamoxifen and fulvestrant, is highly effective in the treatment of estrogen receptor-positive (ER+) breast cancers and is largely responsible for the increase in survival rates seen in the past four decades. However, nearly 50% of women with ER+ cancer display de novo or acquired resistance to AE therapies. Potential molecular mechanisms driving the resistance phenotype are beginning to be elucidated, allowing further development of more effective therapeutic and preventive strategies to reduce the overall mortality due to breast cancer. Over 70% of breast cancer survivors surveyed report increasing their comsumption of fruits, vegetables, and natural product supplements upon diagnosis. These are rich sources of dietary polyphenols (PPs) that can interact with cell-signaling pathways involved in the development of AE resistance. However, research on mechanisms by which these agents may affect AE resistance and whether PP intake can significantly change breast cancer recurrence is limited. We summarize the available data on the effects of PPs on breast cancer recurrence and the interactions of these compounds with some of the signaling pathways hypothesized to drive cell death and survival involved in the development of AE resistance in breast cancer.

Darier's disease misdiagnosed as severe seborrheic dermatitis.

Darier's disease is a rare autosomal disorder resulting in characteristic findings of the skin, nails, and mucous membranes. Darier's disease is commonly misdiagnosed as seborrheic dermatitis or eczema. We present the case of a young adult active duty Air Force member with 5 years of skin complaints. The 23-year-old patient had been treated for seborrheic dermatitis and eczema with a variety of oral and topical treatments, which did not result in improvement of his symptoms. Upon referral to dermatology, the dermatologist noted skin, nail, and mucous membrane findings consistent with Darier's disease. A skin biopsy histologically confirmed the presence of Darier's disease and treatment was started. Although the course of the disease cannot be stopped, the patient's symptoms did reduce with the appropriate treatment. This case highlights the importance of revisiting the original diagnosis when conventional treatment fails to improve the disease course.