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The novel coronavirus disease (COVID-19) pandemic is the gravest public-health crisis that the United States has seen in more than a century. Healthcare delivery systems are the focal point for interfacing with COVID-19; however, many were and remain unprepared for this or similar outbreaks. In this paper, we describe the Learning Health System (LHS) as an ideal organizing principle to inform an evidence-based response to public-health emergencies like COVID-19. We further describe barriers and challenges to the realization of the LHS and propose a call to action for a substantial investment in the LHS, with a focus on public health. Specifically, we advocate for a Learning Health Network that promotes collaboration between health systems, community-based organizations, and government agencies, especially during public health emergencies. We have approached this commentary through the unique lens of researchers embedded within a large, integrated healthcare delivery system, with direct experience working with clinical and operational units in response to the COVID-19 pandemic.

Objective To characterize patients who utilize services for migraine in a large integrated health care network, and describe patterns of care and utilization. Background Within health care systems, migraine is a common reason for seeking primary and neurology care, but relatively little is documented about who seeks care and the factors that explain variation in utilization. Methods We conducted a retrospective cohort study using electronic health record (EHR) data from Sutter Health primary care (PC) patients who had at least one office visit to a PC clinic between 2013 and 2017. Migraine status was ascertained from diagnosis codes and medication orders. Control status was assigned to those with no evidence of care for any type of headache. We divided the primary care migraine cohort into two groups: those who received all their care for migraine from PC (denoted PC‐M) and those who had ≥1 encounter with a neurologist for migraine (denoted N‐M). Migraine cases were also designated as having preexisting migraine if they had an encounter with a migraine diagnosis within (±) 6 months of their first study period PC visit and, otherwise, designated as first migraine consult. Two levels of contrasts included: patients with migraine and controls; and within the group of patients with migraine, PC‐M and N‐M groups. Comorbid conditions were determined from EHR encounter diagnosis codes. Results We identified 94,149 patients with migraine (including 21,525 N‐M and 72,624 PC‐M) and 1,248,763 controls. Comorbidities: Proportions of psychiatric [29.8% (n = 28,054) vs. 11.8% (n = 147,043)], autoimmune [(4.4% (n = 4162) vs. 2.6% (n = 31,981)], pain [13.2% (n = 12,439) vs. 5.8% (n = 72,049)], respiratory [24.6% (n = 23,186) vs. 12.3% (n = 153,692)], neurologic [2.9% (n = 2688) vs. 0.9% (n = 11,321)], and cerebrovascular [1.0% (n = 945) vs. 0.6% (n = 7500)] conditions were higher in the migraine group compared to controls, all p

Introduction The purpose of this study was to develop and validate a predictive model for the early identification of nonresponders to a 12-month lifestyle change program in clinical practice. Methods Investigators identified lifestyle change program participants in the electronic health records of a large healthcare delivery system between 2010 and 2017. Nonresponse was defined as weight gain or no weight loss at 12 months from the program initiation (baseline). Logistic regression with percentage weight change at 2–12 weeks from baseline was used as an independent predictor of nonresponse. Baseline demographics and clinical characteristics were also tested as potential predictors. The authors performed ten-fold cross-validation for model assessment and examined model performance with the area under the receiver operating characteristic curve, sensitivity, specificity, and positive and negative predictive values. The analyses were conducted in 2019. Results Among 947 program participants, 30% were classified as nonresponders at 12 months. The model with the best discrimination of responders from nonresponders included weight change at 12 weeks from baseline as the sole predictor (area under the receiver operating characteristic curve, 0.789). Sensitivity and positive predictive value were maximized at 0.56 (specificity and negative predictive value, 0.81 each). Conclusions In a cohort of lifestyle change program participants from clinical practice, percentage weight change at 12 weeks from baseline can serve as a single indicator of nonresponse at the completion of the 12-month program. Clinicians can easily apply this algorithm to identify and assess participants in potential need of adjunctive or alternative therapy to maximize treatment outcomes.

Study objective We examine racial and ethnic differences in opioid prescribing and dosing for long bone fractures at emergency department (ED) discharge. Methods We conducted an electronic health records–based cross-sectional study of adults with long bone fractures who presented to the ED across 22 sites from a health care delivery system (2016 to 2017). We examined differences in opioid prescribing at ED discharge and, among patients with a prescription, differences in opioid dosing (measured as morphine milligram equivalents) by race/ethnicity, using regression modeling with statistical adjustment for patient, fracture, and prescriber characteristics. Results A total of 11,576 patients with long bone fractures were included in the study; 64.4% were non-Hispanic white; 16.4%, 7.3%, 5.8%, and 5.1%, respectively, were Hispanic, Asian, black, and of other or unknown race; and 65.6% received an opioid at discharge. After adjusting for other factors, rates of opioid prescribing were not different by race/ethnicity; however, among patients with an opioid prescription, total morphine milligram equivalent units prescribed were 4.3%, 6.0%, and 8.1% less for Hispanics, blacks, and Asians relative to non-Hispanic whites. Conclusion Racial and ethnic minority groups with long bone fractures receive similar frequencies of opioid prescriptions at discharge, with a small potency difference. How this affects pain relief and why it happens is unclear.

Background Urinary tract infection (UTI) accounts for a substantial portion of outpatient visits and antibiotic prescriptions in the United States. Few studies have considered sociodemographic factors including low socioeconomic status (SES)—which may increase residential crowding, inappropriate antibiotic prescribing, or comorbidities—as UTI or multidrug-resistant (MDR) UTI risk factors. Methods We used 2015–2017 electronic health record data from 2 California health care systems to assess whether 3 sociodemographic factors—use of Medicaid, use of an interpreter, and census tract–level deprivation—were associated with overall UTI or MDR UTI. UTIs resistant to ≥3 antibiotic classes were considered MDR. Results Analyses included 601 352 UTI cases, 1 303 455 controls, and 424 977 urinary Escherichia coli isolates from Kaiser Permanente Southern California (KPSC) and Sutter Health in Northern California. The MDR prevalence was 10.4% at KPSC and 12.8% at Sutter Health. All 3 sociodemographic factors (ie, use of Medicaid, using an interpreter, and community deprivation) were associated increased risk of MDR UTI. For example, using an interpreter was associated with a 36% (relative risk [RR], 1.36; 95% CI, 1.31 to 1.40) and 28% (RR, 1.28; 95% CI, 1.22 to 1.34) increased risk of MDR UTI at KPSC and Sutter Health, respectively, adjusted for SES and other potential confounding variables. The 3 sociodemographic factors were only weakly associated with UTI overall. Conclusions We found low SES and use of an interpreter to be novel risk factors for MDR UTI in the United States.

Background Urinary tract infections (UTIs) occur commonly, but recent data on UTI rates are scarce. It is unknown how the growth of virtual healthcare delivery affects outpatient UTI management and trends in the United States. Methods From 1 January 2008 to 31 December 2017, UTIs from outpatient settings (office, emergency, and virtual visits) were identified from electronic health records at Kaiser Permanente Southern California using multiple UTI definitions. Annual rates estimated by Poisson regression were stratified by sex, care setting, age, and race/ethnicity. Annual trends were estimated by linear or piecewise Poisson regression. Results UTIs occurred in 1 065 955 individuals. Rates per 1000 person-years were 53.7 (95% confidence interval [CI], 50.6–57.0) by diagnosis code with antibiotic and 25.8 (95% CI, 24.7–26.9) by positive culture. Compared to office and emergency visits, UTIs were increasingly diagnosed in virtual visits, where rates by diagnosis code with antibiotic increased annually by 21.2% (95% CI, 16.5%–26.2%) in females and 29.3% (95% CI, 23.7%–35.3%) in males. Only 32% of virtual care diagnoses had a culture order. Overall, UTI rates were highest and increased the most in older adults. Rates were also higher in Hispanic and white females and black and white males. Conclusions Outpatient UTI rates increased from 2008 to 2017, especially in virtual care and among older adults. Virtual care is important for expanding access to health services, but strategies are needed in all outpatient care settings to ensure accurate UTI diagnosis and reduce inappropriate antibiotic treatment.

Background Migraine is one of the most common neurological disorders in clinical practice and is a substantial cause of disability worldwide. Current approaches to therapy are primarily based on medication but are often limited by inadequate effectiveness and common side effects. Newer, more effective medications are expensive. Mindfulness-based stress reduction (MBSR), an 8-week classroom-based meditation intervention, is inexpensive, has no known side effects, and has demonstrated clinically meaningful effectiveness for several chronic-pain syndromes. In addition, MBSR has shown promising results for migraine therapy in a few small case studies and pilot studies. We present here the protocol for a two-arm randomized controlled pilot trial of MBSR for moderate-to-severe episodic migraine, which, if successful, will form the basis for a fully powered clinical trial. Methods/design This study, set in Northern California, is a two-arm parallel-comparison single-blinded randomized controlled pilot trial with the goal of recruiting approximately 60 participants with moderate-to-severe episodic migraine. The feasibility outcomes include ability and time required to recruit, adherence to the MBSR treatment, and ability to measure outcomes using 31-day headache diaries and patient-reported questionnaire data. The active treatment arm consists of an 8-week community-based MBSR class plus usual care, and the wait-list control group is usual care. Recruitment is underway and expected to be complete by the end of 2018. Discussion To our knowledge, this is the first pragmatic trial in the U.S. of MBSR for migraine using community-based classes, and if it proves viable, we plan to conduct a fully powered trial to determine the effectiveness of the intervention for reducing headache days for moderate-to-severe episodic migraineurs. Trial registration Clinicaltrials.gov, NCT02824250. Registered on 6 July 2016. Electronic supplementary material The online version of this article (10.1186/s13063-019-3355-y) contains supplementary material, which is available to authorized users.

Introduction Translational lifestyle change programs for community and clinical settings have been available for a decade, yet there are limited data on their comparative effectiveness. This study examines the effectiveness of a Centers for Disease Control and Prevention–aligned lifestyle change program relative to usual care in clinical practice. Methods This was an electronic health record–based retrospective cohort study conducted in a community-based healthcare system. Investigators identified adult program participants and usual-care patients in the electronic health record between 2010 and 2018 and defined their index date (baseline) as the first lifestyle change program encounter or a random encounter date, respectively. Participants were matched 1:2 to usual-care patients on baseline demographics and clinical characteristics using propensity-score methods. Changes in body weight and blood pressure were examined from baseline through 24 months. Results The authors identified 2,833 program participants and 438,432 usual-care patients meeting study eligibility criteria. A total of 2,833 program participants were matched to 4,776 usual-care patients; the average age was 54 years, and 80% of the participants were female. Program participation was associated with a 1.9- and 1.6-fold higher prevalence of clinically meaningful (≥5%) weight loss at 12- and 24-month follow-up than usual care and a higher prevalence of blood pressure control at 12 months but not at 24 months. Patients without type 2 diabetes at baseline had more pronounced outcomes than those with type 2 diabetes. Conclusions This study demonstrates the effectiveness of an evidence-based, Centers for Disease Control and Prevention–aligned lifestyle change program in reducing cardiometabolic risk factors compared with usual care in clinical practice, with long-term reductions in weight and transient reductions in blood pressure.

Graphical abstract, Data quality is essential to the success of the most simple and the most complex analysis. In the context of the COVID-19 pandemic, large-scale data sharing across the US and around the world has played an important role in public health responses to the pandemic and has been crucial to understanding and predicting its likely course. In California, hospitals have been required to report a large volume of daily data related to COVID-19. In order to meet this need, electronic health records (EHRs) have played an important role, but the challenges of reporting high-quality data in real-time from EHR data sources have not been explored. We describe some of the challenges of utilizing EHR data for this purpose from the perspective of a large, integrated, mixed-payer health system in northern California, US. We emphasize some of the inadequacies inherent to EHR data using several specific examples, and explore the clinical-analytic gap that forms the basis for some of these inadequacies. We highlight the need for data and analytics to be incorporated into the early stages of clinical crisis planning in order to utilize EHR data to full advantage. We further propose that lessons learned from the COVID-19 pandemic can result in the formation of collaborative teams joining clinical operations, informatics, data analytics, and research, ultimately resulting in improved data quality to support effective crisis response.

Background: Home-based care coordination and support programs for people with advanced illness work alongside usual care to promote personal care goals, which usually include a preference for home-based end-of-life care. More research is needed to confirm the efficacy of these programs, especially when disseminated on a large scale. Advanced Illness Management is one such program, implemented within a large open health system in northern California, USA. Aim: To evaluate the impact of Advanced Illness Management on end-of-life resource utilization, cost of care, and care quality, as indicators of program success in supporting patient care goals. Design: A retrospective-matched observational study analyzing medical claims in the final 3 months of life. Setting/participants: Medicare fee-for-service 2010–2014 decedents in northern California, USA. Results: Final month total expenditures for Advanced Illness Management enrollees ( N = 1352) were reduced by US$4824 (US$3379, US$6268) and inpatient payments by US$6127 (US$4874, US$7682). Enrollees also experienced 150 fewer hospitalizations/1000 (101, 198) and 1361 fewer hospital days/1000 (998, 1725). The percentage of hospice enrollees increased by 17.9 percentage points (14.7, 21.0), hospital deaths decreased by 8.2 percentage points (5.5, 10.8), and intensive care unit deaths decreased by 7.1 percentage points (5.2, 8.9). End-of-life chemotherapy use and non-inpatient expenditures in months 2 and 3 prior to death did not differ significantly from the control group. Conclusion: Advanced Illness Management has a positive impact on inpatient utilization, cost of care, hospice enrollment, and site of death. This suggests that home-based support programs for people with advanced illness can be successful on a large scale in supporting personal end-of-life care choices.

Context Relatively few patients with gout receive appropriate treatment. Objective To determine whether a pharmacist-staffed gout management program is more effective than usual care in achieving target serum uric acid (sUA) levels in gout patients. Design A parallel-group, randomized controlled trial of a pharmacist-staffed, telephone-based program for managing hyperuricemia vs usual care. Trial duration was 26 weeks. Main outcome measures Primary outcome measure was achieving sUA levels at or below 6 mg/dL at the 26-week visit. Secondary outcome was mean change in sUA levels in the control and intervention groups. Participants were adults with recurrent gout and sUA levels above 6.0 mg/dL. Participants were randomly assigned to management by a clinical pharmacist following protocol or to monitoring of sUA levels but management of their gout by their usual treating physician. Results Of 102 patients who met eligibility criteria, 77 subjects obtained a baseline sUA measurement and were entered into the trial. Among 37 participants in the intervention group, 13 (35%) had sUA levels at or below 6.0 mg/dL at 26 weeks, compared with 5 (13%) of 40 participants in the control group (risk ratio = 2.8, 95% confidence interval [CI] = 1.1 to 7.1, p = 0.03). The mean change in sUA levels among controls was +0.1 mg/dL compared with -1.5 mg/dL in the intervention group (sUA difference = -1.6, 95% CI = -0.9 to -2.4, p Conclusions A structured pharmacist-staffed program was more effective than usual care for achieving target sUA levels. These results suggest a structured program could greatly improve gout management.