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ImportanceThere is a dearth of population-level data on major disruptive life events (defined here as arrests by a legal authority, address changes, bankruptcy, lien, and judgment filings) for patients with bipolar I disorder (BPI) or schizophrenia, which has limited studies on mental health and treatment outcomes.ObjectiveTo conduct a population-level study on disruptive life events by using publicly available data on disruptive life events, aggregated by a consumer credit reporting agency in conjunction with electronic health record (EHR) data.Design, Setting, and ParticipantsThis study used EHR data from 2 large, integrated health care systems, Kaiser Permanente Southern California and Henry Ford Health. Cohorts of patients diagnosed from 2007 to 2019 with BPI or schizophrenia were matched 1:1 by age at analysis, age at diagnosis (if applicable), sex, race and ethnicity, and Medicaid status to (1) an active comparison group with diagnoses of major depressive disorder (MDD) and (2) a general health (GH) cohort without diagnoses of BPI, schizophrenia, or MDD. Patients with diagnoses of BPI or schizophrenia and their respective comparison cohorts were matched to public records data aggregated by a consumer credit reporting agency (98% match rate). Analysis took place between November 2020 and December 2022.Main Outcomes and MeasuresThe differences in the occurrence of disruptive life events among patients with BPI or schizophrenia and their comparison groups.ResultsOf 46 167 patients, 30 008 (65%) had BPI (mean [SD] age, 42.6 [14.2] years) and 16 159 (35%) had schizophrenia (mean [SD], 41.4 [15.1] years). The majoriy of patients were White (30 167 [65%]). In addition, 18 500 patients with BPI (62%) and 6552 patients with schizophrenia (41%) were female. Patients with BPI were more likely to change addresses than patients in either comparison cohort (with the incidence ratio being as high as 1.25 [95% CI, 1.23-1.28]) when compared with GH cohort. Patients with BPI were also more likely to experience any of the financial disruptive life events with odds ratio ranging from 1.15 [95% CI, 1.07-1.24] to 1.50 [95% CI, 1.42-1.58]). The largest differences in disruptive life events were seen in arrests of patients with either BPI or schizophrenia compared with GH peers (3.27 [95% CI, 2.84-3.78] and 3.04 [95% CI, 2.57-3.59], respectively). Patients with schizophrenia had fewer address changes and were less likely to experience a financial event than their matched comparison cohorts.Conclusions and RelevanceThis study demonstrated that data aggregated by a consumer credit reporting agency can support population-level studies on disruptive life events among patients with BPI or schizophrenia.

Introduction: Produce prescriptions are one of several approaches that have been receiving national attention to increase food security while also improving diet for patients with diet-related health challenges. Implementation of produce prescriptions vary widely, from food vouchers to tailored, pre-arranged weekly home deliveries. Our study focuses on sending weekly curated produce boxes, scaled by family size up to 5 members. We curated 5 different culturally themed boxes for participants to choose from with the ability to change theme at any time throughout the study period. It was our hypothesis that pre-curated, culturally varied boxes would allow to address patient food preferences to assure continued retention. Methods: This produce prescriptions pre-randomized clinical trial is being conducted at Kaiser Permanente Southern California, an integrated health care system with over 4.5M members. Adult members with uncontrolled diabetes with recent Hemoglobin A1c >7.5% or 8% (if >65 years or certain comorbid conditions) were pre-randomized into a high or low-dose (intervention) versus usual care group. Surveys are conducted at 4 different time points (2 and 8-week, 3 and 6 months) for participants pre-randomized to the intervention group. The eight week and 3 months survey that are now completed provide participant feedback on utility and satisfaction of both the food and recipes provided. Results: Recruitment has closed to enrollment; the intervention is slated to end January 2023. There were 150 participants enrolled in each arm for a total 450 participants. The average age at enrollment was 59 years. Over 62% reported currently being unemployed, retired or disabled. Just over half (51%), reported Spanish as their preferred language. Although diabetes was the main eligibility for this study, participants on average had 2-3 additional comorbidities, with 65% also being diagnosed with hypertension and 8.5% having congestive heart failure. Generally, respondents (N=187) considered the foods culturally appropriate with 69% indicating being familiar with the foods delivered and 70% knew how to prepare the foods. Recipes were moderately useful familiarizing participants with new foods (26%). Only 41% reported that of the foods new to them, they would use again in the future. Deliveries could be improved for future with participants overwhelmingly asking for more fruit, vegetables, legumes (98%, 94%, 71%), while also stating diary would be important to add to the deliveries (94%). Overall, 72% of participants reporting being very satisfied with the weekly produce deliveries and 81% stated the food helped them eat healthier throughout the week. Conclusions: Weekly produce deliveries are a promising approach to promote healthier eating providing more variety and autonomy in choices will likely increase use of produce and overall satisfaction in such programs.

INTRODUCTION: Coronavirus disease 2019 rapidly shifted health care toward telehealth. We assessed satisfaction with and preferences for telehealth among patients with irritable bowel syndrome (IBS). METHODS: We conducted a cross-sectional survey in an integrated healthcare system in Southern California with members aged 18-90 years with an International Classification of Diseases 9 and 10 codes for IBS from office-based encounters between June 1, 2018, and June 1, 2020. Eligible patients were emailed a survey assessing telehealth satisfaction overall and by patient-related factors, IBS characteristics, health and technologic literacy, utilization, and coronavirus disease 2019 perceptions. We identified perceived telehealth benefits and challenges. Multivariable logistic regression identified predictors of telehealth dissatisfaction. RESULTS: Of 44,789 surveys sent, 5,832 (13.0%) patients responded and 1,632 (3.6%) had Rome IV IBS. Among 1,314 (22.5%) patients with IBS and prior telehealth use (mean age 52.6 years [17.4]; 84.9% female; and 59.4% non-Hispanic White, 29.0% Hispanic, and 5.6% non-Hispanic Black), 898 (68.3%) were satisfied, 130 (9.9%) were dissatisfied, and 286 (21.8%) felt neutral. In addition, 78.6% would use telehealth again. Independent predictors of telehealth dissatisfaction include social media use of once a week or less (adjusted odds ratio [OR] = 2.1; 1.3-3.5), duration of IBS for

In April 2020, the Mayo Clinic helped establish the US Food and Drug Administration Expanded Access Protocol for COVID-19 (coronavirus disease 2019) convalescent plasma (CCP). The effectiveness of CCP in the published literature is contradictory because some retrospective studies showed benefit in reducing mortality and severe illness, whereas prospective randomized controlled trials demonstrated no benefit of CCP.To discuss (1) the implementation of CCP across Kaiser Permanente Southern California between April 2020 and April 2021, (2) retrospective multivariable analysis of 2,831 patients with COVID-19 who were transfused with CCP compared with 18,475 patients with COVID-19 who did not receive CCP, (3) how to reconcile contradictory published data regarding the efficacy of CCP, and (4) guidance regarding the future use of convalescent plasma in a large community hospital setting.Multivariable analysis was controlled for demographic characteristics, level of oxygen delivery, intensive care unit stay, selected laboratory findings, and other concurrent treatment-related variables. Tubing segments from 151 CCP units transfused between October 2020 and April 2021 were retrospectively tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) anti-spike protein receptor-binding domain IgG. Multivariable analysis showed that CCP transfusion did not affect mortality rates at 30 days and 5 months (odds ratio, 1.04, 95% CI, 0.87-1.25, and hazard ratio, 1.05, 95% CI, 0.93-1.19).If convalescent plasma is offered as a therapeutic in a future viral pandemic, we recommend (1) transfusing only those patients who are negative for neutralizing antibodies, (2) transfusing very early during the disease course, (3) only using convalescent plasma with known levels of neutralizing antibodies, or (4) alternatively providing fractionated hyperimmune globulin.

Objective To evaluate whether a natural language processing (NLP) algorithm could be adapted to extract, with acceptable validity, markers of residential instability (ie, homelessness and housing insecurity) from electronic health records (EHRs) of 3 healthcare systems. Materials and methods We included patients 18 years and older who received care at 1 of 3 healthcare systems from 2016 through 2020 and had at least 1 free-text note in the EHR during this period. We conducted the study independently; the NLP algorithm logic and method of validity assessment were identical across sites. The approach to the development of the gold standard for assessment of validity differed across sites. Using the EntityRuler module of spaCy 2.3 Python toolkit, we created a rule-based NLP system made up of expert-developed patterns indicating residential instability at the lead site and enriched the NLP system using insight gained from its application at the other 2 sites. We adapted the algorithm at each site then validated the algorithm using a split-sample approach. We assessed the performance of the algorithm by measures of positive predictive value (precision), sensitivity (recall), and specificity. Results The NLP algorithm performed with moderate precision (0.45, 0.73, and 1.0) at 3 sites. The sensitivity and specificity of the NLP algorithm varied across 3 sites (sensitivity: 0.68, 0.85, and 0.96; specificity: 0.69, 0.89, and 1.0). Discussion The performance of this NLP algorithm to identify residential instability in 3 different healthcare systems suggests the algorithm is generally valid and applicable in other healthcare systems with similar EHRs. Conclusion The NLP approach developed in this project is adaptable and can be modified to extract types of social needs other than residential instability from EHRs across different healthcare systems.