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Background: A team approach is one of the most effective ways to lower blood pressure (BP) in uncontrolled hypertension, but different models for organizing team-based care have not been compared directly. Methods: A pragmatic, cluster-randomized trial compared 2 interventions in adult patients with moderately severe hypertension (BP≥150/95 mm Hg): (1) clinic-based care using best practices and face-to-face visits with physicians and medical assistants; and (2) telehealth care using best practices and adding home BP telemonitoring with home-based care coordinated by a clinical pharmacist or nurse practitioner. The primary outcome was change in systolic BP over 12 months. Secondary outcomes were change in patient-reported outcomes over 6 months. Results: Participants (N=3071 in 21 primary care clinics) were on average 60 years old, 47% male, and 19% Black. Protocol-specified follow-up within 6 weeks was 32% in clinic-based care and 27% in telehealth care. BP decreased significantly during 12 months of follow-up in both groups, from 157/92 to 139/82 mm Hg in clinic-based care patients (adjusted mean difference −18/−10 mm Hg) and 157/91 to 139/81 mm Hg in telehealth care patients (adjusted mean difference −19/−10 mm Hg), with no significant difference in systolic BP change between groups (−0.8 mm Hg [95% CI, −2.84 to 1.32]). Telehealth care patients were significantly more likely than clinic-based care patients to report frequent home BP measurement, rate their BP care highly, and report that BP care visits were convenient. Conclusions: Telehealth care that includes extended team care is an effective and safe alternative to clinic-based care for improving patient-centered care for hypertension. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02996565.

Background Hypertension control has been decreasing recently. We compared the experience and attitudes toward care between patients with uncontrolled hypertension who are more and less satisfied with that care to identify ways to improve their care. Methods Baseline survey of 3072 patients with diagnosed hypertension and repeated blood pressure measurements at or above 150/95 mmHg during clinic appointments at 21 primary care clinics of a large Midwestern multi-specialty medical group. Survey questions were about previous hypertension care satisfaction, the degree to which that care was patient-centered, their feelings of self-confidence and treatment burden in managing hypertension, and medication side effects. Results A total of 1697 patients completed surveys (response rate = 55%). Of the 1697 patients, the 24% who were most dissatisfied (scored 0 to 5 on a 0 to 10 scale of satisfaction) significantly differed from those most satisfied (scored 9 to 10) on all demographic and clinical characteristics as well as on every measure of care experience and health status. After adjusting for those characteristics, reports of patient-centered care, self-confidence, stopping the medication because of side effects, and the burdensomeness of treatment were all significantly worse (P Conclusions Many patients with uncontrolled hypertension are dissatisfied with their care, but that is associated with different problems for different people. Identifying and attending to these problems may provide opportunities to help them achieve better control.

Background State-of-the-art behavioral weight loss treatment (SBT) can lead to clinically meaningful weight loss, but only 30–60% achieve this goal. Developing adaptive interventions that change based on individual progress could increase the number of people who benefit. Purpose Conduct a Sequential Multiple Assignment Randomized Trial (SMART) to determine the optimal time to identify SBT suboptimal responders and whether it is better to switch to portion-controlled meals (PCM) or acceptance-based treatment (ABT). Method The BestFIT trial enrolled 468 adults with obesity who started SBT and were randomized to treatment response assessment at Session 3 (Early TRA) or 7 (Late TRA). Suboptimal responders were re-randomized to PCM or ABT. Responders continued SBT. Primary outcomes were weight change at 6 and 18 months. Results PCM participants lost more weight at 6 months (−18.4 lbs, 95% CI −20.5, −16.2) than ABT participants (−15.7 lbs, 95% CI: −18.0, −13.4), but this difference was not statistically significant (−2.7 lbs, 95% CI: −5.8, 0.5, p = .09). PCM and ABT participant 18 month weight loss did not differ. Early and Late TRA participants had similar weight losses (p = .96), however, Early TRA PCM participants lost more weight than Late TRA PCM participants (p = .03). Conclusions Results suggest adaptive intervention sequences that warrant further research (e.g., identify suboptimal responders at Session 3, use PCMs as second-stage treatment). Utilizing the SMART methodology to develop an adaptive weight loss intervention that would outperform gold standard SBT in a randomized controlled trial is an important next step, but may require additional optimization work. Clinical Trial information ClinicalTrials.gov identifier; NCT02368002

Objective Most Americans with opioid use disorder (OUD) do not receive indicated medical care. A clinical decision support (CDS) tool for primary care providers (PCPs) could address this treatment gap. Our primary objective was to build OUD-CDS tool and demonstrate its functionality and accuracy. Secondary objectives were to achieve high use and approval rates and improve PCP confidence in diagnosing and treating OUD. Methods A convenience sample of 55 PCPs participated. Buprenorphine-waivered PCPs (n = 8) were assigned to the intervention. Non-waivered PCPs (n = 47) were randomized to intervention (n = 24) or control (n = 23). Intervention PCPs received access to the OUD-CDS, which alerted them to patients at potentially increased risk for OUD or overdose and guided diagnosis and treatment. Control PCPs provided care as usual. Results The OUD-CDS was functional and accurate following extensive multi-phased testing. PCPs used the OUD-CDS in 5% of encounters with at-risk patients, far less than the goal of 60%. OUD screening confidence increased for all intervention PCPs and OUD diagnosis increased for non-waivered intervention PCPs. Most PCPs (65%) would recommend the OUD-CDS and found it helpful with screening for OUD and discussing and prescribing OUD medications. Discussion PCPs generally liked the OUD-CDS, but use rates were low, suggesting the need to modify CDS design, implementation strategies and integration with existing primary care workflows. Conclusion The OUD-CDS tool was functional and accurate, but PCP use rates were low. Despite low use, the OUD-CDS improved confidence in OUD screening, diagnosis and use of buprenorphine. NIH Trial registration NCT03559179. Date of registration: 06/18/2018. URL: https://clinicaltrials.gov/ct2/show/NCT03559179

To prospectively evaluate the relationship between household income, children's cortisol, and body mass index (BMI) trajectories over a 3-year period in early childhood.Household income, child hair cortisol levels, and BMI were measured at baseline, 12-, 24-, and 36-month follow-up visits in the Now Everybody Together for Amazing and Healthful Kids (NET-Works) Study (n = 534, children ages 2-4 years, and household income$65 000/year at baseline). Relationships were examined between very low household income ($25 000/year) at baseline, income status over time (remained$25 000/year or had increasing income), cortisol accumulation from hair samples, and BMI percent of the 95th percentile (BMIp95) trajectories using adjusted linear growth curve modeling. Households with baseline income between $25 000 and $65 000/year were the reference group for all analyses.Children from very low-income households at baseline had annual changes in BMIp95 that were higher (P .001) than children from reference group households (0.40 vs -0.62 percentage units/year). Annual increases in BMIp95 were also greater among children from households that remained very low income (P .01, .34 percentage units/year) and among those with increasing income (P = .01, .51 percentage units/year) compared with the reference group (-0.61 percentage units/year). Children from households that remained very low income had higher hair cortisol accumulations (0.22 pg/mg, P = .02) than reference group children, whereas hair cortisol concentrations of children from households with increasing income (0.03 pg/mg) did not differ significantly from the reference group. Cortisol was not related to BMIp95.The economic circumstances of families may impact children's BMI trajectories and their developing stress systems, but these processes may be independent of one another.

Adults with schizophrenia, schizoaffective disorder, or bipolar disorder, collectively termed serious mental illness (SMI), have shortened life spans compared with people without SMI. The leading cause of death is cardiovascular (CV) disease.To assess whether a clinical decision support (CDS) system aimed at primary care clinicians improves CV health for adult primary care patients with SMI.In this cluster randomized clinical trial conducted from March 2, 2016, to September 19, 2018, restricted randomization assigned 76 primary care clinics in 3 Midwestern health care systems to receive or not receive a CDS system aimed at improving CV health among patients with SMI. Eligible clinics had at least 20 patients with SMI; clinicians and their adult patients with SMI with at least 1 modifiable CV risk factor not at the goal set by the American College of Cardiology/American Heart Association guidelines were included. Statistical analysis was conducted on an intention-to-treat basis from January 10, 2019, to December 29, 2021.The CDS system assessed modifiable CV risk factors and provided personalized treatment recommendations to clinicians and patients.Patient-level change in total modifiable CV risk over 12 months, summed from individual modifiable risk factors (smoking, body mass index, low-density lipoprotein cholesterol level, systolic blood pressure, and hemoglobin A1c level).A total of 80 clinics were randomized; 4 clinics were excluded for having fewer than 20 eligible patients, leaving 42 intervention clinics and 34 control clinics. A total of 8937 patients with SMI (4922 women [55.1%]; mean [SD] age, 48.4 [13.5] years) were enrolled. There was a 4% lower rate of increase in total modifiable CV risk among intervention patients relative to control patients (relative rate ratio [RR], 0.96; 95% CI, 0.94-0.98). The intervention favored patients who were 18 to 29 years of age (RR, 0.89; 95% CI, 0.81-0.98) or 50 to 59 years of age (RR, 0.93; 95% CI, 0.90-0.96), Black (RR, 0.93; 95% CI, 0.88-0.98), or White (RR, 0.96; 95% CI, 0.94-0.98). Men (RR, 0.96; 95% CI, 0.94-0.99) and women (RR, 0.95; 95% CI, 0.92-0.97), as well as patients with any SMI subtype (bipolar disorder: RR, 0.96; 95% CI, 0.94-0.99; schizoaffective disorder: RR, 0.94; 95% CI, 0.90-0.98; schizophrenia: RR, 0.92; 95% CI, 0.85-0.99) also benefited from the intervention. Despite treatment effects favoring the intervention, there were no significant differences in individual modifiable risk factors.This CDS intervention resulted in a rate of change in total modifiable CV risk that was 4% lower among intervention patients compared with control patients. Results were driven by the cumulative effects of incremental and mostly nonsignificant changes in individual modifiable risk factors. These findings emphasize the value of using CDS to prompt early primary care intervention for adults with SMI.ClinicalTrials.gov Identifier: NCT02451670.

Opioid-related deaths continue to rise in the U.S. A shared decision-making (SDM) system to help primary care clinicians (PCCs) identify and treat patients with opioid use disorder (OUD) could help address this crisis.In this cluster-randomized trial, primary care clinics in three healthcare systems were randomized to receive or not receive access to an OUD-SDM system. The OUD-SDM system alerts PCCs and patients to elevated risk of OUD and supports OUD screening and treatment. It includes guidance on OUD screening and diagnosis, treatment selection, starting and maintaining patients on buprenorphine for waivered clinicians, and screening for common comorbid conditions. The primary study outcome is, of patients at high risk for OUD, the percentage receiving an OUD diagnosis within 30 days of index visit. Additional outcomes are, of patients at high risk for or with a diagnosis of OUD, (a) the percentage receiving a naloxone prescription, or (b) the percentage receiving a medication for OUD (MOUD) prescription or referral to specialty care within 30 days of an index visit, and (c) total days covered by a MOUD prescription within 90 days of an index visit.The intervention started in April 2021 and continues through December 2023. PCCs and patients in 90 clinics are included; study results are expected in 2024.This protocol paper describes the design of a multi-site trial to help PCCs recognize and treat OUD. If effective, this OUD-SDM intervention could improve screening of at-risk patients and rates of OUD treatment for people with OUD.

A total of 513 children were included in this secondary analysis of data from the NET-Works trial of low income children at risk for obesity. The purpose of the analysis was to examine HCC longitudinally over 5 assessments from early through middle childhood with the goal of i) determining if there were racial/ethnic differences in HCC, and if so, how early in childhood these differences could be observed; and (ii) whether racial/ethnic differences in HCC reflected structural and family-level indicators of disadvantage. The sample consisted of children from diverse racial/ethnic backgrounds: Black, including Hispanic Black (N = 156), non-Hispanic White (N = 67) and Non-Black Hispanic (N = 290) children. As the largest group, the last group was used as the reference group in analyses. Structural and family-level indicators of disadvantage, including the neighborhood child opportunity index (COI), family income, and parent perceived neighborhood safety, were collected at each assessment. The results showed higher HCC among Black children beginning as early as 2-4 years of age than non-Black Hispanic children who did not differ from non-Hispanic White children. Although family income and COI were lower for children from minoritized racial-ethnic backgrounds, entering these measures as covariates did not reduce the difference in HCC between Black children and the other two groups. The results also showed that HCC initially decreased with age and then plateaued, with no evidence that this pattern differed by race/ethnicity. Because of the potential health risks of chronically elevated cortisol concentrations, these data argue for increased attention to the myriad of factors (oppressive structures, systems, and interpersonal experiences) that likely contribute to elevated cortisol levels among Black children.

Hypertension control is falling in the US yet efficacious interventions exist. Poor patient reach has limited the ability of pragmatic trials to demonstrate effectiveness. This paper uses quantitative and qualitative data to understand factors influencing reach in Hyperlink 3, a pragmatic hypertension trial testing an efficacious pharmacist-led Telehealth Care intervention in comparison to a physician-led Clinic-based Care intervention. Referrals to both interventions were ordered by physicians.A sequential-explanatory mixed methods approach was used to understand barriers and facilitators to reach. Reach was assessed quantitatively using EHR data, defined as the proportion of eligible patients attending intended follow-up hypertension care and qualitatively, via semi-structured interviews with patients who were and were not reached. Quantitative data were analyzed using descriptive and inferential statistics. Qualitative data were analyzed via combined deductive and inductive content analysis.Of those eligible, 27% of Clinic-based (n = 532/1945) and 21% of Telehealth patients (n = 385/1849) were reached. In both arms, the largest drop was between physician-signed orders and patients attending initial intended follow-up care. Qualitative analyses uncovered patient barriers related to motivation, capability, and opportunity to attend follow-up care.Although the proportion of eligible patients with signed orders was high in both arms, the proportion ultimately reached was lower. Patients described barriers related to the influence of one's own personal beliefs or priorities, decision making processes, logistics, and patient perceptions on physician involvement on reach. Addressing these barriers in the design of pragmatic interventions is critical for future effectiveness.NCT02996565.

Purpose: We designed, implemented, and evaluated impact of a prediabetes clinical decision support system on identification of prediabetes and control of major cardiovascular (CV) risk factors in adults with prediabetes receiving care in primary care clinics. Methods: We randomized 34 primary care clinics with 18,229 study-eligible patients age 40-75 years at index encounter with laboratory evidence of prediabetes to usual care (UC) or a prediabetes clinical decision support (PreD-CDS) intervention condition. Study-eligible patients and their primary care clinician (PCC) were given patient-specific treatment suggestions to support diagnosis of PreD and control of systolic BP (SBP), low-density lipoprotein cholesterol (LDL), smoking, and Body Mass Index (BMI, Kg/m2). Electronic medical record (EHR) and other data were analyzed using linear and logistic mixed models to account for nested data structures. Results: At index visit study subjects were 50.7% female, 97.1% white, mean age 60.9 years, 56.7% not diagnosed with PreD, 17.2% current tobacco smokers, and mean age 60.9 years, BMI 33.6 Kg/m2, SBP of 151 mmHg, and LDL 118 mg/dl. Compared to UC clinics, those receiving care at PreD-CDS clinics had no significant change in likelihood of PreD diagnosis, mean SBP, mean LDL, mean BMI, or smoking (all p >.05). Conclusions: This point-of-care EHR-linked web-based clinical decision support system had no statistically significant impact on diagnosis of prediabetes or CV risk factor control. Alternative methods of improving care for these vulnerable patients are needed. Disclosure J. R. Desai: None. H. Ekstrom: None. P. J. O’connor: None. A. Crain: None. D. Saman: None. J. M. Sperl-hillen: None. C. Allen: None. S. Waring: None. K. Ohnsorg: None. D. Appana: None. S. P. Dehmer: None. Funding National Heart, Lung, and Blood Institute (R01HL128201)

Early detection of prediabetes and management of cardiovascular (CV) risk factors to prevent CV disease is essential, but clinicians are often slow to address this risk. Clinical decision support (CDS) systems, with appropriate implementation, can potentially improve prediabetes identification and treatment.34 Midwestern primary care clinics were randomized to receive or not receive access to a prediabetes (PreD) CDS tool. Between October 2016 and December 2019, primary care clinicians (PCPs) received Pre-D CDS alerts during visits with adult patients identified with prediabetes and who met minimal inclusion criteria and had at least one CV risk factor not at goal. The PCP Pre-D CDS included a summary of six modifiable CV risk factors and patient-specific treatment recommendations. Study outcomes included total modifiable CV risk, six modifiable CV risk factors, use of CV medications, and referrals. The Consolidated Framework for Implementation Research was used to examine CDS implementation processes.This cluster-randomized pragmatic trial allowed PCPs the opportunity to improve CV risk in a timely manner for patients with prediabetes. Effectiveness will be assessed using an intent-to-treat analysis. Implementation processes and outcomes will be assessed through interviews, surveys, and electronic health record data harvested by the CDS tool itself. Pre-implementation interviews and activities identified key strategies to incorporate as part of the Pre-D CDS implementation process to ensure acceptability and high use rates. Analyses are ongoing and trial results are expected in mid-2021.

Introduction: Patient ratings of their experience of care are part of the “Triple Aim”. Improvements are highly valued by health care organizations, but are hard to achieve. Hypothesis: We tested the effect of a telehealth intervention on satisfaction with hypertension care. Methods: Hyperlink 3 is an ongoing pragmatic cluster-randomized trial in 3072 patients with uncontrolled hypertension in 21 primary care clinics in HealthPartners, an integrated health system in Minnesota and Wisconsin. Clinics were randomized to Clinic-based Care (CC, 9 clinics, 1648 patients) or Telehealth Care (TC, 12 clinics, 1424 patients). CC patients received guideline-based hypertension care in face-to-face visits. TC patients were additionally offered home blood pressure (BP) telemonitoring with pharmacist care management. Patients were surveyed at baseline and after 6 months of study enrollment and asked to rate their hypertension care in the previous 6 months on a scale of 0-10. We compared change in the proportion of patients rating their care at the highest level (9 or 10). Results: In the TC group, about 37% of patients attended an intake pharmacist visit and 434 (30%) participated in home BP telemonitoring. Baseline surveys were completed by 1719 (56%) of patients at baseline (goal 50% completion) and 1301 (76%) of those completing the baseline survey completed the 6 month survey (goal 75% completion). Baseline survey respondents’ mean age was 62 y (non-respondents 58 y), 46% were men (non-respondents 48%), 19% were black (non-respondents 20%), and mean BP was 164/93 mm Hg (non-respondents 164/95 mm Hg.) Nearly all patients (over 90%) took antihypertensive medications (median 2). Hypertension care ratings of 9 or 10 were 27.9% at baseline and 30.2% at 6 months in CC, compared with 29.0% at baseline and 39.5% at 6 months in TC. The odds ratio (OR) for change over time in 9 or 10 ratings was 1.11 (95% CI 0.87 - 1.42) in CC, and 1.61 (95% CI 1.26 - 2.07) in TC. The OR for change in 9 or 10 ratings over time in TC vs CC was 1.45 (95% CI 1.03 - 2.06). Conclusions: Home BP telemonitoring with pharmacist care management increased the proportion of patients who highly rated their experience of hypertension care, even though only a minority of the TC patients received the intervention.

Introduction: Telehealth and remote monitoring have become critical to patient access to care during the COVID-19 pandemic. We measured the effect of a telehealth care intervention on frequency, sharing methods, and clinical usage of home blood pressure (BP) measurements. Methods: Hyperlink 3 is an ongoing pragmatic cluster-randomized trial in 3072 patients with uncontrolled hypertension in 21 primary care clinics in an integrated health system. Clinics were randomized to Clinic-based Care (CC, 9 clinics, 1648 patients) or Telehealth Care (TC, 12 clinics, 1424 patients). TC patients were offered home BP telemonitoring with pharmacist care management. Patients were surveyed at baseline (Nov 2017 - Apr 2019) and after 6 mo of study enrollment. Results: In the TC group, about 37% of patients attended an intake pharmacist visit and 434 (30%) participated in home BP telemonitoring. Baseline surveys were completed by 1719 (56%) of patients at baseline (goal 50%) and 1301 (76%) of those completing the baseline survey completed the 6 mo survey (goal 75%). Baseline survey respondents' mean age was 62, 46% were men, 19% were black, and mean BP was 164/93 mm Hg. Nearly all patients (>90%) took antihypertensive medications (median 2). The odds ratio (OR) for change in measuring BP > 2 times/week vs. less often was 0.97 (95% CI 0.87 - 1.42) in CC, and 2.01 (95% CI 1.56 - 2.59) in TC. The OR for change in frequent measurement in TC vs CC was 2.08 (95% CI 1.45 - 2.97). Conclusions: A telehealth care intervention markedly increased the frequency of home BP self- monitoring, electronic data sharing, and data-driven BP medication changes, even though only a minority of TC patients received the intervention.

Background: Evidence-based chronic kidney disease (CKD) care can slow progression and avert complications. We evaluated evidence-based care gaps for stage 3 and 4 CKD in patients with and without diabetes (DM). Methods: All patients age 18-75 with a primary care encounter between April and October 2019 in any of 32 clinics in a large Midwestern care system were evaluated for stage 3 or 4 CKD based on laboratory evidence of GFR 15-59 ml/min/1.73 m2 on 2 consecutive tests. Using programmed algorithms they were further assessed for CKD care gaps and classified as DM or no DM. Results: Out of 5,336 patients with stage 3 or 4 CKD, 41% had DM. Patients with DM had a mean A1C of 7.5%, mean systolic BP 134, and 28.6% had A1C ≥8%. Compared to patients without DM, those with DM were slightly older (65.6, 66.2 years, p Conclusion: CKD care for those with DM is better than for those without DM for most care elements, although large care caps remain for both groups. Of note, 28% of patients with DM had an A1C over 8%, and 15.3% of patients with DM had more advanced CKD with no evidence of seeing a nephrologist in the last year. Better care delivery strategies are needed for optimal CKD management including timely nephrology consultation. Disclosure J.M. Sperl-Hillen: None. A. Crain: None. M.B. DeSilva: None. L. Chumba: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R18DK118463)

Background Cardiovascular (CV) disease is the leading cause of death for people with serious mental illness (SMI), but clinicians are often slow to address this risk. Methods/Design 78 Midwestern primary care clinics were randomized to receive or not receive access to a clinical decision support (CDS) tool. Between March 2016 and September 2018, primary care clinicians (PCPs) received CDS alerts during visits with adult patients with SMI who met minimal inclusion criteria and had at least one CV risk factor not at goal. The PCP CDS included a summary of six modifiable CV risk factors and patient-specific treatment recommendations. Psychiatrists received CDS alerts during their next visit with an eligible patient with SMI that alerted them to an elevated body mass index or recent weight gain and the presence of an obesogenic SMI medication. Study outcomes include total modifiable CV risk, six modifiable CV risk factors, and use of obesogenic SMI medications. Discussion This cluster-randomized pragmatic trial allowed PCPs and psychiatrists the opportunity to improve CV risk in a timely manner for patients with SMI. Effectiveness will be assessed using an intent-to-treat analysis, and outcomes will be assessed largely through electronic health record data harvested by the CDS tool itself. In total, 10,347 patients with SMI had an index primary care visit in a randomized clinic, and 8937 patients had at least one follow-up visit. Analyses are ongoing, and trial results are expected in mid-2020. Trial registration ClinicalTrials.gov Identifier: NCT02451670

Background We describe a clinic-randomized trial to improve chronic kidney disease (CKD) care through a CKD-clinical decision support (CKD-CDS) intervention in primary care clinics and the challenges we encountered due to COVID-19 care disruption. Methods/design Primary care clinics (N = 32) were randomized to usual care (UC) or to CKD-CDS. Between April 17, 2019 and March 14, 2020, more than 7000 patients had accrued for analysis by meeting study-eligibility criteria at an index office visit: age 18–75, laboratory criteria for stage 3 or 4 CKD (eGFR 15–59 mL/min/1.73 m2), and one or more opportunities algorithmically identified to improve CKD care such as blood pressure (BP) or glucose control, angiotensin converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB) use, discontinuance of a nonsteroidal anti-inflammatory drug (NSAID), or nephrology referral. At CKD-CDS clinics, CDS provided individualized treatment suggestions that were printed for patients and clinicians at the start of office encounters and were viewable within the electronic health record. By initial design, the impact of the CKD-CDS intervention on care gaps was to be assessed 12 months after the index date, but COVID-19 caused major disruptions to care delivery during the intervention period. In response to disruptions, the intervention was temporarily suspended while we expanded CDS use for telehealth encounters and programmed new criteria for displaying the CKD-CDS to intervention patients due to clinic closures and scheduling changes. Discussion We describe a NIH-funded pragmatic trial of web-based EHR-integrated CKD-CDS and modifications necessary mid-study to complete the study as intended in the face of COVID-19 pandemic challenges.

Objective The spread of evidence-based care is an important challenge in healthcare. We evaluated spread of an evidence-based large-scale multisite collaborative care model for patients with depression and diabetes and/or cardiovascular disease (COMPASS). Methods Primary care patients with depression and comorbid diabetes or cardiovascular disease were recruited. Collaborative care teams used care management tracking systems and systematic case reviews to track and intensify treatment for patients not improving. Targeted outcomes were depression remission and response (assessed with the Patient Health Questionnaire-9) and control of diabetes (assessed by HbA1c) and blood pressure. Patients and clinicians were surveyed about satisfaction with care. Results Eighteen care systems and 172 clinics enrolled 3609 patients across the US. Of those with uncontrolled disease at enrollment, 40% achieved depression remission or response, 23% glucose control and 58% blood pressure control during a mean follow-up of 11 months. There were large variations in outcomes across medical groups. Patients and clinicians were satisfied with COMPASS care. Conclusions COMPASS was successfully spread across diverse care systems and demonstrated improved outcomes for complex patients with previously uncontrolled chronic disease. Future large-scale implementation projects should create robust processes to identify and reduce expected variation in implementation to consistently provide improved care.

To describe primary care clinicians' self-reported satisfaction, burnout and barriers for treating complex patients.We conducted a survey of 1554 primary care clinicians in 172 primary care clinics in 18 health care systems across 8 states prior to the implementation of a collaborative model of care for patients with depression and diabetes and/or cardiovascular disease.Of the clinicians who responded to the survey (n=709; 46%), we found that a substantial minority (31%) were experiencing burnout that was associated with lower career satisfaction (P.0001) and lower satisfaction with resources to treat complex patients (P.0001). Less than 50% of clinicians rated their ability to treat complex patients as very good to excellent with 21% rating their ability as fair to poor. The majority of clinicians (72%) thought that a collaborative model of care would be very helpful for treating complex patients.Burnout remains a problem for primary care clinicians and is associated with low job satisfaction and low satisfaction with resources to treat complex patients. A collaborative care model for patients with mental and physical health problems may provide the resources needed to improve the quality of care for these patients.

Depression is pervasive and costly, and the majority of depression is treated in primary care. The objective of this study was to identify patient characteristics predictive of poor depression outcomes in primary care clinics.This observational study followed 792 patients receiving usual care for depression in 83 clinics across Minnesota for at least six months between 2008 and 2010. The primary outcome was an ordinal outcome of remission or response without remission ("response") six months after the start of treatment. The outcome was assessed via telephone administration of the Patient Health Questionnaire-9. Associations of patient characteristics with the primary outcome were assessed by using ordinal logistic regression.The majority of patients were female, Caucasian, and employed, and most had some college education and good, very good, or excellent self-rated health. At baseline, 32% had mild depression, 40% moderate depression, 20% moderately severe depression, and 8% severe depression. One-third of patients had psychotherapy or psychiatric care in addition to antidepressant medications. At six months, only 47% of patients obtained depression remission or response. Patients were significantly less likely to experience remission or response if they rated their health as poor or fair or if they were unemployed and were more likely to achieve remission or response if they were younger or had mild depression.Patients with poor or fair health or who were unemployed were less likely to respond to usual depression care and may be good candidates for limited, but potentially more effective, intensive treatment resources for depression.

Background Little is known about the reach and impact of collaborative care for depression outside of clinical trials. Objective The objective of this study was to examine the effect of a collaborative care intervention for depression on the rates of depression diagnosis, use of specific depression codes, and treatment intensification. Research design Evaluation of a staggered, multiple baseline implementation initiative. Subjects Patients receiving depression care in primary care clinics throughout Minnesota from February 2008 through March 2011. Measures Data regarding depression diagnosis rates and codes, and measures of antidepressant intensification were provided by health insurers. Results Depression Improvement Across Minnesota: Offering a New Direction (DIAMOND) affected neither rates of depression recognition nor use of depression diagnostic codes, and the overall reach of DIAMOND was disappointingly small. Patients in DIAMOND had more episodes of treatment intensification than non-DIAMOND patients, but we were unable to account for depression severity in our analysis. Conclusions DIAMOND did not affect depression recognition or diagnostic coding, but may have affected treatment intensification. Our results suggest that even strongly evidence-based interventions may have little contamination effects on patients not enrolled in the new care model.

The ability to aggregate clinical data across multiple diverse organizations and to use it for performance measurement, quality improvement, evaluation, and research is rapidly becoming a national necessity, but there are few examples of how to do that. This article uses lessons from a national effort to implement the collaborative care management model for patients with both depression and diabetes or heart disease across 8 partner organizations, 18 medical groups, and more than 170 clinics in 8 states to identify the challenges and provide experience-based recommendations for those tasks. The challenges are divided into those needed for (1) collecting similar data, (2) aggregating those data across care systems, and (3) using the data to both improve and evaluate care. Start with agreement on goals, methods, transparency, and a data system integrated into the electronic medical record while promptly addressing all the legal, regulatory, and human subject requirements.

Background While health systems are striving for patient-centered care, they have little evidence to guide them on how to engage patients in their care, or how this may affect patient experiences and outcomes. Objective To explore which specific patient-centered aspects of care were best associated with depression improvement and care satisfaction. Methods Design: observational. Setting 83 primary care clinics across Minnesota. Subjects Primary care patients with new prescriptions for antidepressants for depression were recruited from 2007 to 2009. Outcome measures Patients completed phone surveys regarding demographics and self-rated health status and depression severity at baseline and 6 months. Patient centeredness was assessed via a modified version of the Patient Assessment of Chronic Illness Care. Differences in rates of remission and satisfaction between positive and negative responses for each care process were evaluated using chi-square tests. Results At 6 months, 37% of 792 patients ages 18-88 achieved depression remission, and 79% rated their care as good-to-excellent. Soliciting patient preferences for care and questions or concerns, providing treatment plans, utilizing depression scales and asking about suicide risk were patient-centered measures that were positively associated with depression remission in the unadjusted model; these associations were mildly weakened after adjustment for depression severity and health status. Nearly all measures of patient centeredness were positively associated with care ratings. Conclusion The patient centeredness of care influences how patients experience and rate their care. This study identified specific actions providers can take to improve patient satisfaction and depression outcomes.

Behavioral weight loss programs help people achieve clinically meaningful weight losses (8–10% of starting body weight). Despite data showing that only half of participants achieve this goal, a “one size fits all” approach is normative. This weight loss intervention science gap calls for adaptive interventions that provide the “right treatment at the right time for the right person.” Sequential Multiple Assignment Randomized Trials (SMART), use experimental design principles to answer questions for building adaptive interventions including whether, how, or when to alter treatment intensity, type, or delivery. This paper describes the rationale and design of the BestFIT study, a SMART designed to evaluate the optimal timing for intervening with sub-optimal responders to weight loss treatment and relative efficacy of two treatments that address self-regulation challenges which impede weight loss: 1) augmenting treatment with portion-controlled meals (PCM) which decrease the need for self-regulation; and 2) switching to acceptance-based behavior treatment (ABT) which boosts capacity for self-regulation. The primary aim is to evaluate the benefit of changing treatment with PCM versus ABT. The secondary aim is to evaluate the best time to intervene with sub-optimal responders. BestFIT results will lead to the empirically-supported construction of an adaptive intervention that will optimize weight loss outcomes and associated health benefits.

Background Uncontrolled hypertension is the largest single contributor to all-cause and cardiovascular mortality in the U.S. population. Nurse- and pharmacist-led team-based care and telehealth care interventions have been shown to result in large and lasting improvements in blood pressure (BP); however, it is unclear how successfully these can be implemented at scale in real-world settings. It is also uncertain how telehealth interventions impact patient experience compared to traditional clinic-based care. Aims/objectives To compare the effects of two evidence-based blood pressure care strategies in the primary care setting: (1) best-practice clinic-based care and (2) telehealth care with home BP telemonitoring and management by a clinical pharmacist. To evaluate implementation using mixed-methods supported by the RE-AIM framework and Consolidated Framework for Implementation Research. Methods The design is a cluster-randomized comparative effectiveness pragmatic trial in 21 primary care clinics (9 clinic-based care, 12 telehealth care). Adult patients (age 18–85) with hypertension are enrolled via automated electronic health record (EHR) tools during primary care encounters if BP is elevated to ≥150/95 mmHg at two consecutive visits. The primary outcome is change in systolic BP over 12 months as extracted from the EHR. Secondary outcomes are change in key patient-reported outcomes over 6 months as measured by surveys. Qualitative data are collected at various time points to investigate implementation barriers and help explain intervention effects. Conclusion This pragmatic trial aims to inform health systems about the benefits, strengths, and limitations of implementing home BP telemonitoring with pharmacist management for uncontrolled hypertension in real-world primary care settings.

SUMMARY: BACKGROUND: Pediatric primary care is an important setting for addressing obesity prevention. OBJECTIVE: The Healthy Homes/Healthy Kids 5‐10 randomized controlled trial evaluated the efficacy of an obesity prevention intervention integrating pediatric primary care provider counseling and parent‐targeted phone coaching. METHODS: Children aged 5 to 10 years with a BMI between the 70th and 95th percentile and their parents were recruited from pediatric primary care clinics. Participants received well‐child visit provider counseling about obesity and safety/injury prevention and were then randomized to a 14‐session phone‐based obesity prevention (OP; n = 212) or safety and injury prevention contact control (CC; n = 209) intervention. The primary outcome was 12 and 24‐month child BMI percentile. RESULTS: There was no overall significant treatment effect on child BMI percentile. Caloric intake was significantly lower among OP compared with CC participants at 12 months (P < .005). In planned subgroup analyses, OP condition girls had significantly lower BMI percentile (P < .05) and BMI z‐score (P < .02) at 12 and 24 months relative to CC girls and were less likely to be overweight (38.0% vs 53.0%, P < .01) or (obese 3.4% vs 8.8%, P < .10) at follow‐up. CONCLUSIONS AND RELEVANCE: An obesity prevention intervention integrating brief provider counseling and parent‐targeted phone counseling did not impact 12 and 24‐month BMI status overall but did have a significant impact on BMI in girls.

Background: Our objective was to assess the impact on primary care of the 2017 ACC/AHA lowering of the threshold for diagnosing HTN to a BP ≥ 130/80 mm Hg, and pharmacologic treatment intensification recommendations for patients with high CV risk and/or DM who have BP levels 130-139/80-89 mm Hg. Discussion: 62% of patients with DM and 57% without DM had a BP ≥ 130/80 mm Hg, and over half of these will require reclassification of HTN due to BP 130-139/80-89 mm Hg.Of patients with Stage 1 HTN, 76.8% of patients with DM and 39.4% without DM are already treated (but above goal). 25% of all DM patients (7755/30,608) and 13% of all non-DM patients (22963/176,555) are currently treated with Stage 1 HTN and will require an increase in BP medication to achieve BP < 130/80 mm Hg.7.7% of all DM patients (2344/30,608) and 2.3% of all non- DM patients with CV risk ≥ 10% (3960/176,555) are currently untreated with Stage 1 HTN and medication initiation will be recommended. If pharmacologic treatment initiation recommendations were limited to those with CV risk ≥ 10% for DM patients, BP medication initiation recommendations would decrease from 7.7% to 2.9% (896/30,608) of the DM population. Conclusion: The 2017 ACC/AHA guideline will result in a significantly increased need for primary care to address BP medication intensification, with a much greater proportional impact on those with DM compared to those without. Disclosure J.M. Sperl-Hillen: None. J.P. Anderson: None. J.R. Desai: None. K.L. Margolis: None. A. Crain: None. P.J. O'Connor: None.

Objectives. To evaluate a multicomponent obesity prevention intervention among diverse, low-income preschoolers. Methods. Parent-child dyads (n = 534) were randomized to the Now Everybody Together for Amazing and Healthful Kids (NET-Works) intervention or usual care in Minneapolis, MN (2012-2017). The intervention consisted of home visits, parenting classes, and telephone check-ins. The primary outcomes were adjusted 24- and 36-month body mass index (BMI). Results. Compared with usual care, the NET-Works intervention showed no significant difference in BMI change at 24 (-0.12 kg/m2; 95% confidence interval [CI] = -0.44, 0.19) or 36 months (-0.19 kg/m2; 95% CI = -0.64, 0.26). Energy intake was significantly lower in the NET-Works group at 24 (-90 kcal/day; 95% CI = -164, -16) and 36 months (-101 kcal/day; 95% CI = -164, -37). Television viewing was significantly lower in the NET-Works group at 24 (rate ratio = 0.84; 95% CI = 0.75, 0.93) and 36 months (rate ratio = 0.88; 95% CI = 0.78, 0.99). Children with baseline overweight or obesity had lower BMI in the NET-Works group than those in usual care at 36 months (-0.71 kg/m2; 95% CI = -1.30, -0.12). Hispanic children had lower BMI in the NET-Works group than those in usual care at 36 months (-0.59 kg/m2; 95% CI = -1.14, -0.04). Conclusions. In secondary analyses, NET-Works significantly reduced BMI over 3 years among Hispanic children and children with baseline overweight or obesity. Trial Registration: ClinicalTrials.gov Identifier: NCT01606891.

Scale-up and spread of evidence-based practices is one of the most important challenges facing health care. We tested whether a statewide initiative, Depression Improvement Across Minnesota-Offering a New Direction (DIAMOND), to implement the collaborative care model for depression in 75 primary care clinics resulted in patient outcome improvements corresponding to those reported in randomized controlled trials.Health plans provided a new monthly payment to participating clinics after a 6-month intensive training program with ongoing data submission, networking, and consultation. Implementation was staggered, with 5 sequences of 10 to 40 clinics every 6 months. Payers provided weekly contact information for members from participating clinics who were filling antidepressant prescriptions, and we conducted baseline and 6-month surveys of 1,578 patients about their care and outcomes.There were 466 patients in DIAMOND clinics who received usual care before implementation (UCB), 559 who received usual care in DIAMOND clinics after implementation (UCA), 245 who received DIAMOND care after implementation (DCA), and 308 who received usual care in comparison clinics (UC). Patients who received DIAMOND care after implementation reported more collaborative care depression services than the 3 comparison groups (10.9 vs 6.4-6.7, on a scale of 0 of 14, where higher numbers indicate more services; P.001) and more satisfaction with their care (4.0 vs 3.4 on a scale 1 to 5, in which higher scores indicate higher satisfaction; P ≤.001). Depression remission rates, however, were not significantly different among the 4 groups (36.4% DCA vs 35.8% UCB, 35.0% UCA, 33.9% UC; P = .94).Despite the incentive of a supporting payment change and intensive training and support for clinics volunteering to participate, no difference in depression outcomes was documented. Specific unmeasured actions present in trials but not present in these clinics may be critical for successful outcome improvement.

Objective This study aims to determine the positive and negative predictive values of self-reported diabetes during the Women's Health Initiative (WHI) clinical trials. Methods All WHI trial participants from four field centers who self-reported diabetes at baseline or during follow-up, as well as a random sample of women who did not self-report diabetes, were identified. Women were surveyed regarding diagnosis and treatment. Medical records were obtained and reviewed for documented treatment with antidiabetes medications or for physician diagnosis of diabetes supported by laboratory measurements of glucose. Results We identified 1,275 eligible participants; 732 consented and provided survey data. Medical records were obtained for 715 women (prevalent diabetes, 207; incident diabetes, 325; no diabetes, 183). Records confirmed 91.8% (95% CI, 87.0-95.0) of self-reported prevalent diabetes cases and 82.2% (95% CI, 77.5-86.1) of incident diabetes cases. Among those who never self-reported diabetes, there was no medical record or laboratory evidence for diabetes in 94.5% (95% CI, 89.9-97.2). Women with higher body mass index were more likely to accurately self-report incident diabetes. In a subgroup of participants enrolled in fee-for-service Medicare, a claims algorithm correctly classified nearly all diabetes cases and noncases. Conclusions Among WHI clinical trial participants, there are high positive predictive values of self-reported prevalent diabetes (91.8%) and incident diabetes (82.2%) and a high negative predictive value (94.5%) when diabetes is not reported. For participants enrolled in fee-for-service Medicare, a claims algorithm has high positive and negative predictive values.

Objective: To examine relationships between parenting styles and practices and child moderate-to-vigorous physical activity (MVPA) and screen time. Methods: Participants were children (6.9 ± 1.8 years) with a body mass index in the 70–95th percentile and their parents (421 dyads). Parent-completed questionnaires assessed parental support for child physical activity (PA), parenting styles and child screen time. Children wore accelerometers to assess MVPA. Results: Parenting style did not predict MVPA, but support for PA did (positive association). The association between support and MVPA, moreover, varied as a function of permissive parenting. For parents high in permissiveness, the association was positive (greater support was related to greater MVPA and therefore protective). For parents low in permissiveness, the association was neutral; support did not matter. Authoritarian and permissive parenting styles were both associated with greater screen time. Conclusions: Parenting practices and styles should be considered jointly, offering implications for tailored interventions.

There is limited information about how to transform primary care practices into medical homes. The research team surveyed leaders of the first 132 primary care practices in Minnesota to achieve medical home certification. These surveys measured priority for transformation, the presence of medical home practice systems, and the presence of various organizational factors and change strategies. Survey response rates were 98% for the Change Process Capability Questionnaire survey and 92% for the Physician Practice Connections survey. They showed that 80% to 100% of these certified clinics had 15 of the 18 organizational factors important for improving care processes and that 60% to 90% had successfully used 16 improvement strategies. Higher priority for this change (P = .001) and use of more strategies (P = .05) were predictive of greater change in systems. Clinics contemplating medical home transformation should consider the factors and strategies identified here and should be sure that such a change is indeed a high priority for them.