Patient Perceptions of Prenatal Cannabis Use and Implications for Clinicians.

OBJECTIVE: To understand pregnant patients' reasons for prenatal cannabis use and perceptions of safety, desired and undesirable health care experiences, and desired information about prenatal cannabis use and secondarily to understand racial differences in these perceptions and preferences. METHODS: We conducted a qualitative study including 18 semi-structured, race-concordant virtual focus groups with pregnant individuals who self-reported cannabis use at prenatal care entry in a large integrated health care system in Northern California from November 2021 to December 2021. The focus groups included semi-structured questions that were recorded, transcribed, and coded by the research team. Thematic analysis was used to analyze the data. RESULTS: Overall, 53 participants were included; 30 self-identified, as White and 23 self-identified as Black. Participants averaged 30.3 years of age (SD 5.2 years) and were on average at 20.9 weeks of gestation at study enrollment; 69.8% reported daily cannabis use, 24.5% reported weekly cannabis use, and 5.7% reported monthly or less cannabis use at entrance to prenatal care. Although some participants quit cannabis use in early pregnancy because of concerns about potential health risks, many perceived a lack of scientific evidence or believed that prenatal cannabis use was safe. Many preferred cannabis to over-the-counter or prescription medications for treating mood, morning sickness, pain, and sleep. Participants valued open interactions with obstetricians that acknowledged their motivations for use, and they desired information about potential risks through conversations and educational materials. White and Black participants' perspectives were generally similar, but a few Black participants uniquely described concerns about racial bias related to their prenatal cannabis use. CONCLUSION: Pregnant patients used cannabis to manage mood and medical symptoms, and many believed that prenatal cannabis use was safer than the use of prescription medications. Obstetrician-initiated, patient-centered conversations around prenatal cannabis use, advice to discontinue cannabis use during pregnancy, and exploration of willingness to switch to medically recommended interventions for pregnancy-related symptoms may benefit patients.

Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder.

BACKGROUND: Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD. OBJECTIVE: The aim is to examine patient engagement with multiple digital phenotyping methods among patients receiving buprenorphine medication for OUD. METHODS: The study enrolled 65 patients receiving buprenorphine for OUD between June 2020 and January 2021 from 4 addiction medicine programs in an integrated health care delivery system in Northern California. Ecological momentary assessment (EMA), sensor data, and social media data were collected by smartphone, smartwatch, and social media platforms over a 12-week period. Primary engagement outcomes were meeting measures of minimum phone carry (≥8 hours per day) and watch wear (≥18 hours per day) criteria, EMA response rates, social media consent rate, and data sparsity. Descriptive analyses, bivariate, and trend tests were performed. RESULTS: The participants' average age was 37 years, 47% of them were female, and 71% of them were White. On average, participants met phone carrying criteria on 94% of study days, met watch wearing criteria on 74% of days, and wore the watch to sleep on 77% of days. The mean EMA response rate was 70%, declining from 83% to 56% from week 1 to week 12. Among participants with social media accounts, 88% of them consented to providing data; of them, 55% of Facebook, 54% of Instagram, and 57% of Twitter participants provided data. The amount of social media data available varied widely across participants. No differences by age, sex, race, or ethnicity were observed for any outcomes. CONCLUSIONS: To our knowledge, this is the first study to capture these 3 digital data sources in this clinical population. Our findings demonstrate that patients receiving buprenorphine treatment for OUD had generally high engagement with multiple digital phenotyping data sources, but this was more limited for the social media data. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.3389/fpsyt.2022.871916.

Effectiveness of a pharmacist-delivered primary care telemedicine intervention to increase access to pharmacotherapy and specialty treatment for alcohol use problems: Protocol for the alcohol telemedicine consult cluster-randomized pragmatic trial.

BACKGROUND: Alcohol use problems are associated with serious medical, mental health and socio-economic consequences. Yet even when patients are identified in healthcare settings, most do not receive treatment, and use of pharmacotherapy is rare. This study will test the effectiveness of the Alcohol Telemedicine Consult (ATC) Service, a novel, personalized telehealth intervention approach for primary care patients with alcohol use problems. METHODS: This cluster-randomized pragmatic trial, supplemented by qualitative interviews, will include adults with a primary care visit between 9/10/21-3/10/23 from 16 primary care clinics at two large urban medical centers within Kaiser Permanente Northern California, a large, integrated healthcare system. Clinics are randomized to the ATC Service (intervention), including alcohol pharmacotherapy and SBIRT (screening, MI (Motivational Interviewing)-based brief intervention and referral to addiction treatment) delivered by clinical pharmacists, or the Usual Care (UC) arm that provides systematic alcohol SBIRT. Primary outcomes include a comparison of the ATC and UC arms on 1) implementation outcomes (alcohol pharmacotherapy prescription rates, specialty addiction treatment referrals); and 2) patient outcomes (medication fills, addiction treatment initiation, alcohol use, healthcare services utilization) over 1.5 years. A general modeling approach will consider clustering of patients/providers, and a random effects model will account for intra-class correlations across patients within providers and across clinics. Qualitative interviews with providers will examine barriers and facilitators to implementation. DISCUSSION: The ATC study examines the effectiveness of a pharmacist-provided telehealth intervention that combines pharmacotherapy and MI-based consultation. If effective, the ATC study could affect treatment models across the spectrum of alcohol use problems. CLINICAL TRIALS REGISTRATION: This study has been registered on ClinicalTrials.gov (NCT05252221).

Physical, Mental Health and Developmental Conditions, and Sociodemographic Characteristics Associated With Adverse Childhood Experiences Among Young Children in Pediatric Primary Care.

INTRODUCTION: To examine associations between patient characteristics and adverse childhood experiences (ACEs) in a population-based sample of pediatric primary care patients, using electronic health records and clinical, administrative data. METHOD: An observational study was conducted in an integrated health care delivery system. Children ages 1-5 years (N = 13,370) were screened for ACEs at routine well-child visits between September 1, 2018 and May 31, 2019 in three pediatrics clinics. Multivariate models examined associations between patient characteristics (age, gender, race/ethnicity, insurance type, neighborhood income and education level, physical, mental health and developmental diagnoses, weight status) and any ACEs, and ≥ 3 ACEs exposure. RESULTS: Prevalence and severity of ACE exposure varied by race/ethnicity. Older age, Medicaid insurance, epilepsy/seizure disorder, sleeping disorders, adjustment disorders, and feeding disorders were associated with higher odds of ACEs exposure, higher-income with lower odds. DISCUSSION: Understanding relationships between ACEs and patient features can provide information to clinicians for early detection and appropriate interventions.