Chronic Opioid Prescribing in Primary Care: Factors and Perspectives.

BACKGROUND: Primary care clinicians write 45% of all opioid prescriptions in the United States, but little is known about the characteristics of patients who receive them and the clinicians who prescribe opioids in primary care settings. Our study aimed to describe the patient and clinician characteristics and clinicians' perspectives of chronic opioid prescribing in primary care. METHODS: Using a mixed methods approach, we completed an analysis of 2016 electronic health records from 21 primary care practices to identify patients who had received chronic opioids, which we defined as in receipt of an opioid prescription for at least 3 consecutive months. We compared those receiving chronic opioids with those not in terms of their demographics, prescribing clinician characteristics, and risk factors for opioid-related harms, as identified by the Centers for Disease Control and Prevention Guideline on Opioid Prescribing for Chronic Pain. We then interviewed 16 primary care clinicians about their perspectives on chronic opioid prescribing. RESULTS: Of 84,029 patients, 1.1% (902/84,929) received chronic opioid prescriptions. Characteristics associated with being prescribed chronic opioids include being female, being of black or African American race, and having risks for opioid-related harms, such as mental health diagnoses, substance use disorder, and concurrent benzodiazepine use. Clinicians report multiple difficulties in weaning patients from chronic opioids, including medical contraindications of nonopioid alternatives and difficulty justifying weaning by stable long-term patients. CONCLUSION: Although patients prescribed opioids in primary care have higher risks of opioid-related harms, clinicians report multiple barriers in deprescribing chronic opioids. Future studies should examine strategies to mitigate these harms and engage patients in shared decision making about their chronic opioid use.

Managing the nutritional needs of palliative care patients.

The nutritional needs of patients receiving palliative care should be routinely assessed, taking into account disease trajectory and nutrition-related symptoms. The social and emotional aspects of eating and drinking should also be acknowledged; as should the distress that weight loss and anorexia engenders in patients and their families. Practical strategies to optimise nutritional intake are discussed. Open and sensitive communication of patients' needs and wishes is essential, especially when discussing complementary nutrition approaches. A holistic, multidisciplinary approach is key to meeting nutritional needs, and the goals of nutritional intervention should be regularly reviewed in the light of disease progression.

Methods for Evaluating Respondent Attrition in Web-Based Surveys.

BACKGROUND: Electronic surveys are convenient, cost effective, and increasingly popular tools for collecting information. While the online platform allows researchers to recruit and enroll more participants, there is an increased risk of participant dropout in Web-based research. Often, these dropout trends are simply reported, adjusted for, or ignored altogether. OBJECTIVE: To propose a conceptual framework that analyzes respondent attrition and demonstrates the utility of these methods with existing survey data. METHODS: First, we suggest visualization of attrition trends using bar charts and survival curves. Next, we propose a generalized linear mixed model (GLMM) to detect or confirm significant attrition points. Finally, we suggest applications of existing statistical methods to investigate the effect of internal survey characteristics and patient characteristics on dropout. In order to apply this framework, we conducted a case study; a seventeen-item Informed Decision-Making (IDM) module addressing how and why patients make decisions about cancer screening. RESULTS: Using the framework, we were able to find significant attrition points at Questions 4, 6, 7, and 9, and were also able to identify participant responses and characteristics associated with dropout at these points and overall. CONCLUSIONS: When these methods were applied to survey data, significant attrition trends were revealed, both visually and empirically, that can inspire researchers to investigate the factors associated with survey dropout, address whether survey completion is associated with health outcomes, and compare attrition patterns between groups. The framework can be used to extract information beyond simple responses, can be useful during survey development, and can help determine the external validity of survey results.

Diabetes Engagement and Activation Platform for Implementation and Effectiveness of Automated Virtual Type 2 Diabetes Self-Management Education: Randomized Controlled Trial.

BACKGROUND: Patients with type 2 diabetes require recommendations for self-management education and support. OBJECTIVE: In this study, we aim to design the Diabetes Engagement and Activation Platform (DEAP)-an automated patient education tool integrated into primary care workflow-and examine its implementation and effectiveness. METHODS: We invited patients aged 18-85 years with a hemoglobin A1c (HbA1c) level ≥8 to participate in a randomized controlled trial comparing DEAP with usual care. DEAP modules addressing type 2 diabetes self-management education and support domains were programmed into patient portals, each with self-guided educational readings, videos, and questions. Care teams received patient summaries and were alerted to patients with low confidence or requesting additional help. HbA1c, BMI, and systolic and diastolic blood pressure (DBP) were measured. RESULTS: Out of the 680 patients invited to participate, 337 (49.5%) agreed and were randomized. All of the 189 intervention patients accessed the first module, and 140 patients (74.1%) accessed all 9 modules. Postmodule knowledge and confidence scores were high. Only 18 patients requested additional help from the care team. BMI was lower for intervention patients than controls at 3 months (31.7 kg/m2 vs 32.1 kg/m2; P=.04) and 6 months (32.5 kg/m2 vs 33.0 kg/m2; P=.003); improvements were even greater for intervention patients completing at least one module. There were no differences in 3- or 6-month HbA1c or blood pressure levels in the intent-to-treat analysis. However, intervention patients completing at least one module compared with controls had a better HbA1c level (7.6% vs 8.2%; P=.03) and DBP (72.3 mm Hg vs 75.9 mm Hg; P=.01) at 3 months. CONCLUSIONS: The findings of this study concluded that a significant proportion of patients will participate in an automated virtual diabetes self-management program embedded into patient portals and health systems show promise in helping patients manage their diabetes, weight, and blood pressure. TRIAL REGISTRATION: ClinicalTrials.gov NCT02957721; https://clinicaltrials.gov/ct2/show/NCT02957721.

Practice, clinician, and patient factors associated with the adoption of lung cancer screening.

OBJECTIVES: Lung cancer remains the leading cause of cancer-related deaths in the United States. In 2013, the US Preventive Services Task Force recommended annual screening for lung cancer with low-dose computed tomography in adults meeting certain criteria. This study seeks to assess lung cancer screening uptake in three health systems. SETTING: This study was part of a randomized controlled trial to engage underserved populations in preventive care and includes 45 primary care practices in eight states. METHODS: Practice and clinician characteristics were manually collected. Lung cancer was measured from electronic health record data. A generalized linear mixed model was used to assess characteristics associated with screening. RESULTS: Patient records between 2012 and 2016 were examined. Lung cancer screening uptake overall increased only slightly after the guideline change (2.8-5.6%, p < 0.01). One health system did not show an increase in uptake (0.2-0.1%, p = 0.32), another had a clinically insignificant increase (1.5-2.9%, p < 0.01), and the third nearly doubled its higher baseline screening rate (10.4-19.1%, p < 0.01). Within the third health system, patients more likely to be screened were older, male, had more comorbid conditions, visited the office more frequently, were seen in practices closer to the screening clinic, or were uninsured or covered by Medicare or Medicaid. CONCLUSIONS: Certain patients appeared more likely to be screened. The only health system with increased lung cancer screening explicitly promoted screening rather than relying on clinicians to implement the new guideline. Systems approaches may help increase the low uptake of lung cancer screening.