Antibiotic Prescribing Variability in a Large Urgent Care Network: A New Target for Outpatient Stewardship.

Improving antibiotic prescribing in outpatient settings is a public health priority. In the United States, urgent care (UC) encounters are increasing and have high rates of inappropriate antibiotic prescribing. Our objective was to characterize antibiotic prescribing practices during UC encounters, with a focus on respiratory tract conditions. This was a retrospective cohort study of UC encounters in the Intermountain Healthcare network. Among 1.16 million UC encounters, antibiotics were prescribed during 34% of UC encounters and respiratory conditions accounted for 61% of all antibiotics prescribed. Of respiratory encounters, 50% resulted in antibiotic prescriptions, yet the variability at the level of the provider ranged from 3% to 94%. Similar variability between providers was observed for respiratory conditions where antibiotics were not indicated and in first-line antibiotic selection for sinusitis, otitis media, and pharyngitis. These findings support the importance of developing antibiotic stewardship interventions specifically targeting UC settings.

Practical Tips for Implementing the Diabetes Prevention Program in Clinical Practice.

PURPOSE OF REVIEW: The Diabetes Prevention Program (DPP) is an evidence-based lifestyle change program for prediabetes that is associated with a 58% reduction in 3-year diabetes incidence, and it has been supported by the American Medical Association and the Centers for Disease Control and Prevention. However, 9 in 10 patients are unaware they have the condition. RECENT FINDINGS: With the passage of the Affordable Care Act (ACA) and broadened coverage for preventive services, the DPP has emerged as an accessible intervention in patients at risk. In 2018, Medicare began to cover the DPP, making it widely available for the first time to any patient over the age of 65 meeting eligibility criteria. The DPP is an evidence-based, widely available, frequently covered benefit, for lifestyle change for patients with prediabetes. To take advantage of this intervention, providers need to develop prediabetes screening and DPP referral workflows.

Clinically Feasible Stratification of 3-Year Chronic Disease Risk in Primary Care: The Mental Health Integration Risk Score.

BACKGROUND: Depression is a common illness that imposes a disproportionately large health burden. Depression is generally associated with a higher prevalence of chronic disease risk factors and may contribute to higher chronic disease risk. OBJECTIVE: This study aimed to create and validate sex-specific Mental Health Integration Risk Scores (MHIRS) that predict 3-year chronic disease diagnosis. METHODS: MHIRS was created to predict the first diagnosis of any of the 10 chronic diseases in patients completing a Patient Health Questionnaire-9 Depression Survey who were free at baseline from those 10 chronic disease diagnoses. MHIRS used sex-specific weightings of Patient Health Questionnaire 9 results, age, and components of the complete metabolic profile and complete blood count in randomly chosen derivation (70%) and validation (30%) groups. RESULTS: Among females (N = 10,162, age: 48 ± 16), c-statistics for the composite chronic disease end point were 0.746 (0.725, 0.767) for the derivation group and 0.717 (0.682, 0.753) for the validation group, whereas males (N = 4615, age: 48 ± 15) had 0.755 (0.727, 0.783) and 0.742 (0.702, 0.782). In the validation group, MHIRS strata of low-, moderate-, and high-risk categories had hazard ratios (HR) for any 3-year chronic disease diagnosis among females of HR = 3.42 for moderate vs low and HR = 9.75 for high vs low, whereas males had HR = 4.80 and HR = 10.68, respectively (all p < 0.0001). CONCLUSION: A clinical decision tool comprised by depression severity and common laboratory tests, and MHIRS provides very good stratification of a 3-year chronic disease diagnosis. Designed to be calculated electronically by an electronic health record, MHIRS can be efficiently obtained by clinicians to identify patients at higher chronic disease risk who require further evaluation and more precise clinical management.

A Formative Evaluation of a Diabetes Prevention Program Using the RE-AIM Framework in a Learning Health Care System, Utah, 2013-2015.

INTRODUCTION: Evaluation of interventions can help to close the gap between research and practice but seldom takes place during implementation. Using the RE-AIM framework, we conducted a formative evaluation of the first year of the Intermountain Healthcare Diabetes Prevention Program (DPP). METHODS: Adult patients who met the criteria for prediabetes (HbA1c of 5.70%-6.49% or fasting plasma glucose of 100-125 mg/dL) were attributed to a primary care provider from August 1, 2013, through July 31, 2014. Physicians invited eligible patients to participate in the program during an office visit. We evaluated 1) reach, with data on patient eligibility, participation, and representativeness; 2) effectiveness, with data on attaining a 5% weight loss; 3) adoption, with data on providers and clinics that referred patients to the program; and 4) implementation, with data on patient encounters. We did not measure maintenance. RESULTS: Of the 6,862 prediabetes patients who had an in-person office visit with their provider, 8.4% of eligible patients enrolled. Likelihood of participation was higher among patients who were female, aged 70 years or older, or overweight; had depression and higher weight at study enrollment; or were prescribed metformin. DPP participants were more likely than nonparticipants to achieve a 5% weight loss (odds ratio, 1.70; 95% confidence interval, 1.29-2.25; P < .001). Providers from 7 of 8 regions referred patients to the DPP; 174 providers at 53 clinics enrolled patients. The mean number of DPP counseling encounters per patient was 2.3 (range, 1-16). CONCLUSION: The RE-AIM framework was useful for estimating the formative impact (ie, reach, effectiveness, adoption, and implementation fidelity) of a DPP-based lifestyle intervention deployed in a learning health care system.

The association of antidepressant and statin use with death and incident cardiovascular disease varies by depression severity.

Depression has been reported to be associated with a greater risk of death and cardiovascular disease (CVD); however, the impact of antidepressants (ADM) on CVD risk remains controversial. Statin use is known to decrease CVD risk. Whether the use of these medications together affects CVD risk has not been studied. Patients (N = 26,828) completing the patient health questionnaire (PHQ-9), ≥40 years of age, without prior CVD, and no prior ADM use were studied. Depressive severity was categorized as none-mild (PHQ-9 score ≤14, n = 21,517) and moderate-severe (PHQ-9 score ≥15, n = 5311). Cox hazard regression was used to evaluate the association of no ADM/no statin use (n = 23,104 [86.1%]), ADM/no statin use (n = 877 [3.3%]), no ADM/statin use (n = 2627 [9.8%]), and ADM/statin use (n = 220 [.8%]) with major adverse cardiovascular events (MACE: death, CAD, stroke). Patients averaged 56 ± 12 years; 61% female. There were 1182 (4.4%) 3 year MACE events. The association of ADM and statin use with MACE varied by depressive symptom severity, with statin therapy associated with a decreased risk in the none-mild group (HR = .78, p = .007) and ADM in the moderate-high group (HR = 0.58, p = 0.02). Concomitant use of ADMs and statins did not appear to provide additive benefit.

Association of Integrated Team-Based Care With Health Care Quality, Utilization, and Cost.

IMPORTANCE: The value of integrated team delivery models is not firmly established. OBJECTIVE: To evaluate the association of receiving primary care in integrated team-based care (TBC) practices vs traditional practice management (TPM) practices (usual care) with patient outcomes, health care utilization, and costs. DESIGN: A retrospective, longitudinal, cohort study to assess the association of integrating physical and mental health over time in TBC practices with patient outcomes and costs. SETTING AND PARTICIPANTS: Adult patients (aged ≥18 years) who received primary care at 113 unique Intermountain Healthcare Medical Group primary care practices from 2003 through 2005 and had yearly encounters with Intermountain Healthcare through 2013, including some patients who received care in both TBC and TPM practices. EXPOSURES: Receipt of primary care in TBC practices compared with TPM practices for patients treated in internal medicine, family practice, and geriatrics practices. MAIN OUTCOMES AND MEASURES: Outcomes included 7 quality measures, 6 health care utilization measures, payments to the delivery system, and program investment costs. RESULTS: During the study period (January 2010-December 2013), 113,452 unique patients (mean age, 56.1 years; women, 58.9%) accounted for 163,226 person-years of exposure in 27 TBC practices and 171,915 person-years in 75 TPM practices. Patients treated in TBC practices compared with those treated in TPM practices had higher rates of active depression screening (46.1% for TBC vs 24.1% for TPM; odds ratio [OR], 1.91 [95% CI, 1.75 to 2.08), adherence to a diabetes care bundle (24.6% for TBC vs 19.5% for TPM; OR, 1.26 [95% CI, 1.11 to 1.42]), and documentation of self-care plans (48.4% for TBC vs 8.7% for TPM; OR, 5.59 [95% CI, 4.27 to 7.33]), lower proportion of patients with controlled hypertension (<140/90 mm Hg) (85.0% for TBC vs 97.7% for TPM; OR, 0.87 [95% CI, 0.80 to 0.95]), and no significant differences in documentation of advanced directives (9.6% for TBC vs 9.9% for TPM; OR, 0.97 [95% CI, 0.91 to 1.03]). Per 100 person-years, rates of health care utilization were lower for TBC patients compared with TPM patients for emergency department visits (18.1 for TBC vs 23.5 for TPM; incidence rate ratio [IRR], 0.77 [95% CI, 0.74 to 0.80]), hospital admissions (9.5 for TBC vs 10.6 for TPM; IRR, 0.89 [95% CI, 0.85 to 0.94]), ambulatory care sensitive visits and admissions (3.3 for TBC vs 4.3 for TPM; IRR, 0.77 [95% CI, 0.70 to 0.85]), and primary care physician encounters (232.8 for TBC vs 250.4 for TPM; IRR, 0.93 [95% CI, 0.92 to 0.94]), with no significant difference in visits to urgent care facilities (55.7 for TBC vs 56.2 for TPM; IRR, 0.99 [95% CI, 0.97 to 1.02]) and visits to specialty care physicians (213.5 for TBC vs 217.9 for TPM; IRR, 0.98 [95% CI, 0.97 to 0.99], P > .008). Payments to the delivery system were lower in the TBC group vs the TPM group ($3400.62 for TBC vs $3515.71 for TPM; ß, -$115.09 [95% CI, -$199.64 to -$30.54]) and were less than investment costs of the TBC program. CONCLUSIONS AND RELEVANCE: Among adults enrolled in an integrated health care system, receipt of primary care at TBC practices compared with TPM practices was associated with higher rates of some measures of quality of care, lower rates for some measures of acute care utilization, and lower actual payments received by the delivery system.

Interleukin receptor family member ST2 concentrations in patients following heart transplantation.

OBJECTIVE: To evaluate soluble (s) ST2 as a biomarker of rejection, allograft vasculopathy and mortality after orthotopic heart transplantation (OHT). METHODS: sST2 concentrations were measured in 241 patients following OHT. RESULTS: Elevated sST2 was associated with cellular rejection (CR) ≥ 1R, with highest rates of CR in the 4th sST2 quartile (p = 0.003). No significant association between sST2 and antibody-mediated rejection or allograft vasculopathy was found. sST2 ≥ 30 ng/mL independently predicted death over 7-year follow-up (HR = 2.01; 95% CI 1.15-3.51; p = 0.01). CONCLUSION: Concentrations of sST2 are associated with the presence of CR and predict long-term mortality following OHT.

What do we know about retired physician assistants? A preliminary study.

Retirement generally means the complete end of employment. Retirement is a new phenomenon for physician assistants (PAs), as those trained in the 1970s exit their careers. To better understand retirement patterns of PAs, we undertook a survey in 2011 using a national database. A cadre of 625 respondents met the criteria of being retired and living; the mean age of PA retirement was 61 years (range 47-75 years). Duration of a PA career was 29 years on average (range, 10-40 years). Forty-three percent of respondents retired from family/general medicine and 11% from emergency medicine. Almost all reported receiving Social Security and Medicare; most had some form of a pension. Fewer than one-fifth retired for health reasons. When asked about the timeliness of retiring, 20% wished they had retired later in life; 4% of the men and 7% of the women thought they should have retired earlier; 74% of the men and 73% of the women said they had retired at the right time. Reasons for retiring varied widely. Approximately one-quarter reported volunteering in a medically-related capacity. We suggest that retirement is a concept undergoing evolution in American society and that PAs represent a health profession that reflects the complexity of this evolution.

Implementation of an Antibiotic Stewardship Initiative in a Large Urgent Care Network.

Importance: Urgent Care (UC) encounters result in more inappropriate antibiotic prescriptions than other outpatient setting. Few stewardship interventions have focused on UC. Objective: To evaluate the effectiveness of an antibiotic stewardship initiative to reduce antibiotic prescribing for respiratory conditions in a UC network. Design, Setting, and Participants: This quality improvement study conducted in a UC network with 38 UC clinics and 1 telemedicine clinic included 493 724 total UC encounters. The study compared the antibiotic prescribing rates of all UC clinicians who encountered respiratory conditions for a 12-month baseline period (July 1, 2018, through June 30, 2019) with an intervention period (July 1, 2019, through June 30, 2020). A sustainability period (July 1, 2020, through June 30, 2021) was added post hoc. Interventions: Stewardship interventions included (1) education for clinicians and patients, (2) electronic health record (EHR) tools, (3) a transparent clinician benchmarking dashboard, and (4) media. Occurring independently but concurrent with the interventions, a stewardship measure was introduced by UC leadership into the quality measures, including a financial incentive. Main Outcomes and Measures: The primary outcome was the percentage of UC encounters with an antibiotic prescription for a respiratory condition. Secondary outcomes included antibiotic prescribing when antibiotics were not indicated (tier 3 encounters) and first-line antibiotics for acute otitis media, sinusitis, and pharyngitis. Interrupted time series with binomial generalized estimating equations were used to compare periods. Results: The baseline period included 207 047 UC encounters for respiratory conditions (56.8% female; mean [SD] age, 30.0 [21.4] years; 92.0% White race); the intervention period included 183 893 UC encounters (56.4% female; mean [SD] age, 30.7 [20.8] years; 91.2% White race). Antibiotic prescribing for respiratory conditions decreased from 47.8% (baseline) to 33.3% (intervention). During the initial intervention month, a 22% reduction in antibiotic prescribing occurred (odds ratio [OR], 0.78; 95% CI, 0.71-0.86). Antibiotic prescriptions decreased by 5% monthly during the intervention (OR, 0.95; 95% CI, 0.94-0.96). Antibiotic prescribing for tier 3 encounters decreased by 47% (OR, 0.53; 95% CI, 0.44-63), and first-line antibiotic prescriptions increased by 18% (OR, 1.18; 95% CI, 1.09-1.29) during the initial intervention month. Antibiotic prescriptions for tier 3 encounters decreased by an additional 4% each month (OR, 0.96; 95% CI, 0.94-0.98), whereas first-line antibiotic prescriptions did not change (OR, 1.00; 95% CI, 0.99-1.01). Antibiotic prescribing for respiratory conditions remained stable in the sustainability period. Conclusions and relevance: The findings of this quality improvement study indicated that a UC antibiotic stewardship initiative was associated with decreased antibiotic prescribing for respiratory conditions. This study provides a model for UC antibiotic stewardship.

Implementation of Diabetes Prevention in Health Care Organizations: Best Practice Recommendations.

Approximately 1 in 3 American adults has prediabetes, a condition characterized by blood glucose levels that are above normal, not in the type 2 diabetes ranges, and that increases the risk of developing type 2 diabetes. Evidence-based treatments can be used to prevent or delay type 2 diabetes in adults with prediabetes. The American Medical Association (AMA) has collaborated with health care organizations across the country to build sustainable diabetes prevention strategies. In 2017, the AMA formed the Diabetes Prevention Best Practices Workgroup (DPBP) with representatives from 6 health care organizations actively implementing diabetes prevention. Each organization had a unique strategy, but all included the National Diabetes Prevention Program lifestyle change program as a core evidence-based intervention. DPBP established the goal of disseminating best practices to guide other health care organizations in implementing diabetes prevention and identifying and managing patients with prediabetes. Workgroup members recognized similarities in some of their basic steps and considerations and synthesized their practices to develop best practice recommendations for 3 strategy maturity phases. Recommendations for each maturity phase are classified into 6 categories: (1) organizational support; (2) workforce and funding; (3) promotion and dissemination; (4) clinical integration and support; (5) evaluation and outcomes; (6) and program. As the burden of chronic disease grows, prevention must be prioritized and integrated into health care. These maturity phases and best practice recommendations can be used by any health care organization committed to diabetes prevention. Further research is suggested to assess the impact and adoption of diabetes prevention best practices.

Measuring Adherence to U.S. Preventive Services Task Force Diabetes Prevention Guidelines Within Two Healthcare Systems.

ABSTRACT: Measuring adherence to the 2015 U.S. Preventive Services Task Force (USPSTF) diabetes prevention guidelines can inform implementation efforts to prevent or delay Type 2 diabetes. A retrospective cohort was used to study patients without a diagnosis of diabetes attributed to primary care clinics within two large healthcare systems in our state to study adherence to the following: (1) screening at-risk patients and (2) referring individuals with confirmed prediabetes to participate in an intensive behavioral counseling intervention, defined as a Center for Disease Control and Prevention (CDC)-recognized Diabetes Prevention Program (DPP). Among 461,866 adults attributed to 79 primary care clinics, 45.7% of patients were screened, yet variability at the level of the clinic ranged from 14.5% to 83.2%. Very few patients participated in a CDC-recognized DPP (0.52%; range 0%-3.53%). These findings support the importance of a systematic implementation strategy to specifically target barriers to diabetes prevention screening and referral to treatment.

Leveraging 31 Million Google Street View Images to Characterize Built Environments and Examine County Health Outcomes.

OBJECTIVES: Built environments can affect health, but data in many geographic areas are limited. We used a big data source to create national indicators of neighborhood quality and assess their associations with health. METHODS: We leveraged computer vision and Google Street View images accessed from December 15, 2017, through July 17, 2018, to detect features of the built environment (presence of a crosswalk, non-single-family home, single-lane roads, and visible utility wires) for 2916 US counties. We used multivariate linear regression models to determine associations between features of the built environment and county-level health outcomes (prevalence of adult obesity, prevalence of diabetes, physical inactivity, frequent physical and mental distress, poor or fair self-rated health, and premature death [in years of potential life lost]). RESULTS: Compared with counties with the least number of crosswalks, counties with the most crosswalks were associated with decreases of 1.3%, 2.7%, and 1.3% of adult obesity, physical inactivity, and fair or poor self-rated health, respectively, and 477 fewer years of potential life lost before age 75 (per 100 000 population). The presence of non-single-family homes was associated with lower levels of all health outcomes except for premature death. The presence of single-lane roads was associated with an increase in physical inactivity, frequent physical distress, and fair or poor self-rated health. Visible utility wires were associated with increases in adult obesity, diabetes, physical and mental distress, and fair or poor self-rated health. CONCLUSIONS: The use of computer vision and big data image sources makes possible national studies of the built environment's effects on health, producing data and results that may inform national and local decision-making.

Google Street View Derived Built Environment Indicators and Associations with State-Level Obesity, Physical Activity, and Chronic Disease Mortality in the United States.

Previous studies have demonstrated that there is a high possibility that the presence of certain built environment characteristics can influence health outcomes, especially those related to obesity and physical activity. We examined the associations between select neighborhood built environment indicators (crosswalks, non-single family home buildings, single-lane roads, and visible wires), and health outcomes, including obesity, diabetes, cardiovascular disease, and premature mortality, at the state level. We utilized 31,247,167 images collected from Google Street View to create indicators for neighborhood built environment characteristics using deep learning techniques. Adjusted linear regression models were used to estimate the associations between aggregated built environment indicators and state-level health outcomes. Our results indicated that the presence of a crosswalk was associated with reductions in obesity and premature mortality. Visible wires were associated with increased obesity, decreased physical activity, and increases in premature mortality, diabetes mortality, and cardiovascular mortality (however, these results were not significant). Non-single family homes were associated with decreased diabetes and premature mortality, as well as increased physical activity and park and recreational access. Single-lane roads were associated with increased obesity and decreased park access. The findings of our study demonstrated that built environment features may be associated with a variety of adverse health outcomes.

Rapid Implementation of a Complex, Multimodal Technology Response to COVID-19 at an Integrated Community-Based Health Care System.

BACKGROUND: The rapid spread of severe acute respiratory syndrome coronavirus-2 or SARS-CoV-2 necessitated a scaled treatment response to the novel coronavirus disease 2019 (COVID-19). OBJECTIVE: This study aimed to characterize the design and rapid implementation of a complex, multimodal, technology response to COVID-19 led by the Intermountain Healthcare's (Intermountain's) Care Transformation Information Systems (CTIS) organization to build pandemic surge capacity. METHODS: Intermountain has active community-spread cases of COVID-19 that are increasing. We used the Centers for Disease Control and Prevention Pandemic Intervals Framework (the Framework) to characterize CTIS leadership's multimodal technology response to COVID-19 at Intermountain. We provide results on implementation feasibility and sustainability of health information technology (HIT) interventions as of June 30, 2020, characterize lessons learned and identify persistent barriers to sustained deployment. RESULTS: We characterize the CTIS organization's multimodal technology response to COVID-19 in five relevant areas of the Framework enabling (1) incident management, (2) surveillance, (3) laboratory testing, (4) community mitigation, and (5) medical care and countermeasures. We are seeing increased use of traditionally slow-to-adopt technologies that create additional surge capacity while sustaining patient safety and care quality. CTIS leadership recognized early that a multimodal technology intervention could enable additional surge capacity for health care delivery systems with a broad geographic and service scope. A statewide central tracking system to coordinate capacity planning and management response is needed. Order interoperability between health care systems remains a barrier to an integrated response. CONCLUSION: The rate of future pandemics is estimated to increase. The pandemic response of health care systems, like Intermountain, offers a blueprint for the leadership role that HIT organizations can play in mainstream care delivery, enabling a nimbler, virtual health care delivery system that is more responsive to current and future needs.

Trends in Abstinence and Retention Associated with a Medication-Assisted Treatment Program for People with Opioid Use Disorders.

BACKGROUND: Medication-assisted treatment (MAT) is an evidence-based program for patients with opioid use disorders. Yet, within the state of Utah, MAT had not been widely available, promoted, or adopted within the public sector. Recognizing the potential benefit, a collective impact approach was used to promote social change and increase the use of MAT in the community for treatment of opioid use disorders. OBJECTIVE: Conduct a retrospective, observational case series study to measure the effect of a community-based, collective impact approach implementing the MAT program to improve the rate of abstinence and retention among individuals identified with an opioid use disorder in three Utah counties. METHODS: The study was designed and implemented by the Utah Opioid Community Collaborative (OCC) using a collective impact approach, which included broad sector coordination (public-private collaboration), a common agenda, participation in mutually reinforcing activities, continuous communication, consistent measurement of results, and identification of a backbone organization. The MAT intervention program includes use of medications approved by the U.S. Food and Drug Administration in combination with counseling and behavioral therapies delivered within two community sites. Analysis was performed over time to describe the rate of abstinence and retention associated with participation in the MAT program during 2015 through 2017. RESULTS: Of the 339 identified with risk of an opioid use disorders, 228 enrolled in the MAT Program. At MAT enrollment, average age was 32.6 ± 8.2 years old and 58.0% were female. At 365 days after MAT enrollment, 84% of participants were abstinent from opioid substances and 62% from all illicit substances. CONCLUSIONS: Use of a collective impact approach provides a successful mobilization framework in Utah for increasing community engagement and expanding patient access to underresourced MAT programs while suggesting a high rate of abstinence from illicit substances at 12 months.

Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases.

The spread of COVID-19 is not evenly distributed. Neighborhood environments may structure risks and resources that produce COVID-19 disparities. Neighborhood built environments that allow greater flow of people into an area or impede social distancing practices may increase residents' risk for contracting the virus. We leveraged Google Street View (GSV) images and computer vision to detect built environment features (presence of a crosswalk, non-single family home, single-lane roads, dilapidated building and visible wires). We utilized Poisson regression models to determine associations of built environment characteristics with COVID-19 cases. Indicators of mixed land use (non-single family home), walkability (sidewalks), and physical disorder (dilapidated buildings and visible wires) were connected with higher COVID-19 cases. Indicators of lower urban development (single lane roads and green streets) were connected with fewer COVID-19 cases. Percent black and percent with less than a high school education were associated with more COVID-19 cases. Our findings suggest that built environment characteristics can help characterize community-level COVID-19 risk. Sociodemographic disparities also highlight differential COVID-19 risk across groups of people. Computer vision and big data image sources make national studies of built environment effects on COVID-19 risk possible, to inform local area decision-making.

Using Google Street View to examine associations between built environment characteristics and U.S. health outcomes.

Neighborhood attributes have been shown to influence health, but advances in neighborhood research has been constrained by the lack of neighborhood data for many geographical areas and few neighborhood studies examine features of nonmetropolitan locations. We leveraged a massive source of Google Street View (GSV) images and computer vision to automatically characterize national neighborhood built environments. Using road network data and Google Street View API, from December 15, 2017-May 14, 2018 we retrieved over 16 million GSV images of street intersections across the United States. Computer vision was applied to label each image. We implemented regression models to estimate associations between built environments and county health outcomes, controlling for county-level demographics, economics, and population density. At the county level, greater presence of highways was related to lower chronic diseases and premature mortality. Areas characterized by street view images as 'rural' (having limited infrastructure) had higher obesity, diabetes, fair/poor self-rated health, premature mortality, physical distress, physical inactivity and teen birth rates but lower rates of excessive drinking. Analyses at the census tract level for 500 cities revealed similar adverse associations as was seen at the county level for neighborhood indicators of less urban development. Possible mechanisms include the greater abundance of services and facilities found in more developed areas with roads, enabling access to places and resources for promoting health. GSV images represents an underutilized resource for building national data on neighborhoods and examining the influence of built environments on community health outcomes across the United States.

"Pharming out" support: a promising approach to integrating clinical pharmacists into established primary care medical home practices.

Objective Embedding clinical pharmacists into ambulatory care settings needs to be assessed in the context of established medical home models. Methods A retrospective, observational study examined the effectiveness of the Intermountain Healthcare Collaborative Pharmacist Support Services (CPSS) program from 2012-2015 among adult patients diagnosed with diabetes mellitus (DM) and/or high blood pressure (HBP). Patients who attended this program were considered the intervention (CPSS) cohort. These patients were matched using propensity scores with a reference group (no-CPSS cohort) to determine the effect of achieving disease management goals and time to achievement. Results A total of 17,684 patients had an in-person office visit with their provider and 359 received CPSS (the matched no-CPSS cohort included 999 patients). CPSS patients were 93% more likely to achieve a blood pressure goal < 140/90 mmHg, 57% more likely to achieve HbA1c values < 8%, and 87% more likely to achieve both disease management goals compared with the reference group. Time to goal achievement demonstrated increasing separation between the study cohorts across the entire study period ( P < .001), and specifically, at 180 days post-intervention (HBP: 48% vs 27% P < .001 and DM: 39% vs 30%, P < .05). Conclusions CPSS participation is associated with significant improvement in achievement of disease management goals, time to achievement, and increased ambulatory encounters compared with the matched no-CPSS cohort.

Detecting Risk of Low Health Literacy in Disadvantaged Populations Using Area-based Measures.

INTRODUCTION: Socio-economic status (SES) and low health literacy (LHL) are closely correlated. Both are directly associated with clinical and behavioral risk factors and healthcare outcomes. Learning healthcare systems are introducing small-area measures to address the challenges associated with maintaining patient-reported measures of SES and LHL. This study's purpose was to measure the association between two available census block measures associated with SES and LHL. Understanding the relationship can guide the identification of a multi-purpose area based measure for delivery system use. METHODS: A retrospective observational design was deployed using all US Census block groups in Utah. The principal dependent variable was a nationally-standardized health literacy score (HLS). The primary explanatory variable was a state-standardized area deprivation index (ADI). Statistical methods included linear regression and tests of association. Receiver operating characteristic (ROC) analysis was used to develop LHL criteria using ADI. RESULTS: A significant negative association between the HLS and the ADI score remained after adjusting for area-level risk factors (ß: -0.21 (95% CI: -0.22, -0.19) p < .001). Eighteen block groups (<1%) were identified as having LHL using HLS. A combination of three or more ADI components correlated with LHL predicted 78% of HLS LHL block groups and 35 additional block groups not identified using HLS (c-statistic: 0.64; 95% CI: 0.62, 0.66). CONCLUSIONS: HLS and ADI use differing measurement criteria but are closely correlated. A state-based ADI detected additional neighborhoods with risk of LHL compared to use of a national HLS. An ADI represents a multi-purpose area measure of social determinants useful for learning health systems tailoring care.

Twitter-derived neighborhood characteristics associated with obesity and diabetes.

Neighborhood characteristics are increasingly connected with health outcomes. Social processes affect health through the maintenance of social norms, stimulation of new interests, and dispersal of knowledge. We created zip code level indicators of happiness, food, and physical activity culture from geolocated Twitter data to examine the relationship between these neighborhood characteristics and obesity and diabetes diagnoses (Type 1 and Type 2). We collected 422,094 tweets sent from Utah between April 2015 and March 2016. We leveraged administrative and clinical records on 1.86 million individuals aged 20 years and older in Utah in 2015. Individuals living in zip codes with the greatest percentage of happy and physically-active tweets had lower obesity prevalence-accounting for individual age, sex, nonwhite race, Hispanic ethnicity, education, and marital status, as well as zip code population characteristics. More happy tweets and lower caloric density of food tweets in a zip code were associated with lower individual prevalence of diabetes. Results were robust in sibling random effects models that account for family background characteristics shared between siblings. Findings suggest the possible influence of sociocultural factors on individual health. The study demonstrates the utility and cost-effectiveness of utilizing existing big data sources to conduct population health studies.