Variations in Receipt of Contraceptives by Insurance Status and Race/Ethnicity.

BACKGROUND Although use of contraceptives has increased among young women in the United States, more than half of pregnancies remain unplanned. The goal of this study was to examine the association between insurance status and receipt of contraceptives among young women receiving care within a large integrated health care system in the Southeastern United States to better inform strategies for increasing access to contraception.METHODS This retrospective study used electronic medical record data from an integrated health care system based in Charlotte, North Carolina. Data were analyzed for 51,900 women aged 18-29 who lived in Mecklenburg County and had at least 1 primary care visit between 2014 and 2016. Contraceptive orders were identified by service and procedure codes and grouped into long-acting reversible contraceptives (LARC) and non-LARC categories. Adjusted multinomial logistic regression models were used to assess the association between receipt of contraceptives and insurance status.RESULTS Compared to non-Hispanic White women with commercial insurance, non-Hispanic Black (OR = 1.25; 95% CI, 1.13-1.38) and Hispanic (OR = 2.25; 95% CI, 1.93-2.61) women with Medicaid had higher odds of receiving LARC. Similar variations by insurance and race/ethnicity were observed for the non-LARC group.LIMITATIONS Data were limited to a single health care system and did not capture contraceptive orders by unaffiliated providers. Analyses used the most frequent payor and did not account for changes in insurance status.CONCLUSION Findings indicate an important role of race/ethnicity and insurance coverage in contraceptive care. Higher receipt of LARC among Black and Hispanic women also suggests that implicit biases may influence contraception counseling and promotion practices. Future study is warranted to further delineate these relationships.

Leveraging Data Analytics to Advance Personal, Population, and System Health: Moving Beyond Merely Capturing Services Provided.

The health care industry collects ever-increasing volumes of patient data. Currently, this largely untapped "big data" primarily documents encounters and facilitates billing. This issue of the North Carolina Medical Journal explores the promise and the perils of big data as we seek to transform our health care system into one that is more proactive, equitable, and value based.

Shared decision making and time to exacerbation in children with asthma.

Objective: Although shared decision making (SDM) is a promising approach for improving outcomes for patients with chronic diseases, no evidence currently supports the use of SDM to delay asthma exacerbations. We evaluated the impact of an SDM intervention implemented by providers in a real-world setting on time to exacerbation in children with asthma. Methods: This study used a prospective cohort observed between 2011 and 2013 at five primary care practices that serve vulnerable populations (e.g., Medicaid and uninsured patients) in Charlotte, NC. Patients aged 2 to 17 receiving SDM were matched to those receiving usual care using propensity scores. Time to asthma exacerbation (asthma hospitalization, emergency department visit or oral steroid prescription in the outpatient setting) was compared between groups using Kaplan-Meier curves and conditional Cox proportional hazards models. Results: The cohort included 746 children, 60.5% male and 54.2% African American, with a mean age of 8.6 years. Of these, 625 received usual care and 121 received SDM. The final analysis included 100 matched pairs of children. Kaplan-Meier curves showed longer exacerbation-free time for patients in the SDM intervention compared to those in usual care (p = 0.005). The difference in risk of experiencing an exacerbation was marginally significant between the two groups (HR = 0.56, 95% C.I. = 0.29-1.08, p = 0.08). Conclusions: SDM was found to delay exacerbations among children with asthma. Clinicians should consider incorporating patient preferences in treatment decisions through SDM as a means for longer exacerbation-free time among children with poor asthma control.

Impact of shared decision making on asthma quality of life and asthma control among children.

OBJECTIVE: Few studies have examined the effectiveness of shared decision making (SDM) in clinical practice. This study evaluated the impact of SDM on quality of life and symptom control in children with asthma. METHODS: We conducted a prospective 3-year study in six community-based practices serving a low-income patient population. Practices received training on SDM using an evidence-based toolkit. Patients aged 2-17 with a diagnosis of asthma were identified from scheduling and billing data. At approximate 6-month intervals, patients completed a survey consisting of the Mini Pediatric Asthma Quality of Life Questionnaire (range 1-7) and the control domain of the Pediatric Asthma Therapy Assessment Questionnaire (range 0-7). We used propensity scores to match 46 children receiving SDM to 46 children receiving usual care with decision support. Included children had completed a baseline survey and at least one follow-up survey. Random coefficient models incorporated repeated measures to assess the effect of SDM on asthma quality of life and asthma control. RESULTS: The sample was primarily of non-White patients (94.6%) with Medicaid insurance (92.4%). Receipt of SDM using an evidence-based toolkit was associated with higher asthma quality of life [mean difference 0.9; 95% confidence interval (CI) 0.4-1.4] and fewer asthma control problems (mean difference -0.9; 95% CI -1.6--0.2) compared to usual care with decision support. CONCLUSIONS: Implementation of SDM within clinical practices using a standardized toolkit is associated with improved asthma quality of life and asthma control for low-income children with asthma when compared to usual care with decision support.

Using Community-Based Participatory Research to Develop Geospatial Models Toward Improving Community Health for Disadvantaged Hispanic Populations in Charlotte, NC.

Hispanic immigrant communities across the U.S. experience persistent health disparities and barriers to primary care. We examined whether community-based participatory research (CBPR) and geospatial modeling could systematically and reproducibly pinpoint neighborhoods in Charlotte, North Carolina with large proportions of Hispanic immigrants who were at-risk for poor health outcomes and health disparities. Using a CBPR framework, we identified 21 social determinants of health measures and developed a geospatial model from a subset of those measures to identify neighborhoods with large proportions of Hispanic immigrant populations at risk for poor health outcomes. The geospatial model included four measures-poverty, English ability, acculturation and violent crime-which comprised our Hispanic Health Risk Index (HHRI). We developed a Primary Care Barrier Index (PCBI) to determine (1) how well the HHRI correlated with a statistically derived composite measure incorporating all 21 measures identified through the CBPR process as being associated with access to primary care; (2) whether the HHRI predicted primary care access as well as the statistically-derived composite measure in a statistical model; and (3) whether the HHRI identified similar neighborhoods as the statistically derived composite measure. We collapsed 17 of the 21 social determinants using principal components analysis to develop the PCBI. We determined the correlation of each index with inappropriate emergency department (ED) visits, a proxy for primary care access, using logistic generalized estimating equations. Results from logistic regression models showed positive associations of both the HHRI and the PCBI with the use of the ED for primary care treatable conditions. Enhanced by the knowledge of the local community, the CBPR process with geospatial modeling can guide the multi-tiered validation of social determinants of health and identify neighborhoods that are at-risk for poor health outcomes and health disparities.

Results from a pragmatic prospective cohort study: Shared decision making improves outcomes for children with asthma.

OBJECTIVE: Patient/provider shared decision making (SDM) improves asthma control in a pragmatic clinical trial setting. This study evaluated the impact of an evidence-based SDM toolkit on outcomes for patients with asthma implemented by providers in a real world setting. We hypothesized that these patients with asthma would demonstrate improved outcomes such as reduced emergency department (ED) visits, hospitalizations, and oral steroid use in the 12 months following a SDM visit compared to those who did not receive the intervention. METHODS: Patients with asthma were identified within six primary care practices that serve vulnerable populations in Charlotte, NC (746 children; 718 adult patients). Propensity scores were used to match 200 children and 206 adults for analysis. The primary outcome variable was asthma exacerbation defined as an ED visit or hospitalization for asthma or outpatient prescription of an oral steroid. Patients were monitored at 3, 6, and 12 months after the intervention date. The outcome variables of ED visits, hospitalizations, and oral steroids were compared between intervention and matched control patients. RESULTS: The proportion of pediatric patients with one or more exacerbations was significantly lower in the SDM intervention group compared to controls during 12 months after exposure to the intervention (33% vs. 47%, p = 0.023). For adults, there was not a strong association between use of the SDM intervention and outcomes improvement. CONCLUSIONS: The evidence-based SDM intervention implemented in this study was associated with improved asthma outcomes for pediatric patients but not adult patients in a real world clinical setting.

Bringing Big Data to the Forefront of Healthcare Delivery: The Experience of Carolinas HealthCare System.

The use of big data to transform care delivery is rapidly becoming a reality. To deliver on the promise of value-based care, providers must know the key drivers of wellness at the patient and community levels, as well as understand resource constraints and opportunities to improve efficiency in the health-care system itself. Data are the linchpin. By gathering the right data and finding innovative ways to glean knowledge, we can improve clinical care, advance the health of our communities, improve the lives of our patients, and operate more efficiently. At Carolinas HealthCare System-one of the nation's largest health-care systems, with nearly 12 million patient encounters annually at more than 900 care locations-we have made substantial investments to establish a centralized data and analytics infrastructure that is transforming the way we deliver care across the continuum. Although the impetus and vision for our program have evolved over the past decade, our efforts coalesced into a strategic, centralized initiative with the launch of the Dickson Advanced Analytics (DA) group in 2012. DA has yielded significant gains in our ability to use data, not only for reporting purposes and understanding our business but also for predicting outcomes and informing action.While these efforts have been successful, the path has not been easy. Effectively harnessing big data requires navigating myriad technological, cultural, operational, and other hurdles. Building a program that is feasible, effective, and sustainable takes concerted effort and a rigorous process of continuous self-evaluation and strategic adaptation.

Bringing Big Data to the Forefront of Healthcare Delivery: The Experience of Carolinas HealthCare System.

The use of big data to transform care delivery is rapidly becoming a reality. To deliver on the promise of value-based care, providers must know the key drivers of wellness at the patient and community levels, as well as understand resource constraints and opportunities to improve efficiency in the healthcare system itself. Data are the linchpin. By gathering the right data and finding innovative ways to glean knowledge, we can improve clinical care, advance the health of our communities, improve the lives of our patients, and operate more efficiently. At Carolinas HealthCare System-one of the nation's largest healthcare systems, with nearly 12 million patient encounters annually at more than 900 care locations-we have made substantial investments to establish a centralized data and analytics infrastructure that is transforming the way we deliver care across the continuum. Although the impetus and vision for our program have evolved over the past decade, our efforts coalesced into a strategic, centralized initiative with the launch of the Dickson Advanced Analytics (DA2) group in 2012. DA2 has yielded significant gains in our ability to use data, not only for reporting purposes and understanding our business but also for predicting outcomes and informing action.While these efforts have been successful, the path has not been easy. Effectively harnessing big data requires navigating myriad technological, cultural, operational, and other hurdles. Building a program that is feasible, effective, and sustainable takes concerted effort and a rigorous process of continuous self-evaluation and strategic adaptation.

Adapting community based participatory research (CBPR) methods to the implementation of an asthma shared decision making intervention in ambulatory practices.

OBJECTIVE: Translating research findings into clinical practice is a major challenge to improve the quality of healthcare delivery. Shared decision making (SDM) has been shown to be effective and has not yet been widely adopted by health providers. This paper describes the participatory approach used to adapt and implement an evidence-based asthma SDM intervention into primary care practices. METHODS: A participatory research approach was initiated through partnership development between practice staff and researchers. The collaborative team worked together to adapt and implement a SDM toolkit. Using the RE-AIM framework and qualitative analysis, we evaluated both the implementation of the intervention into clinical practice, and the level of partnership that was established. Analysis included the number of adopting clinics and providers, the patients' perception of the SDM approach, and the number of clinics willing to sustain the intervention delivery after 1 year. RESULTS: All six clinics and physician champions implemented the intervention using half-day dedicated asthma clinics while 16% of all providers within the practices have participated in the intervention. Themes from the focus groups included the importance of being part the development process, belief that the intervention would benefit patients, and concerns around sustainability and productivity. One year after initiation, 100% of clinics have sustained the intervention, and 90% of participating patients reported a shared decision experience. CONCLUSIONS: Use of a participatory research process was central to the successful implementation of a SDM intervention in multiple practices with diverse patient populations.

A trans-disciplinary approach to the evaluation of social determinants of health in a Hispanic population.

BACKGROUND: Individual and community health are adversely impacted by disparities in health outcomes among disadvantaged and vulnerable populations. Understanding the underlying causes for variations in health outcomes is an essential step towards developing effective interventions to ameliorate inequalities and subsequently improve overall community health. Working at the neighborhood scale, this study examines multiple social determinates that can cause health disparities including low neighborhood wealth, weak social networks, inadequate public infrastructure, the presence of hazardous materials in or near a neighborhood, and the lack of access to primary care services. The goal of this research is to develop innovative and replicable strategies to improve community health in disadvantaged communities such as newly arrived Hispanic immigrants. METHODS/DESIGN: This project is taking place within a primary care practice-based research network (PBRN) using key principles of community-based participatory research (CBPR). Associations between social determinants and rates of hospitalizations, emergency department (ED) use, and ED use for primary care treatable or preventable conditions are being examined. Geospatial models are in development using both hospital and community level data to identify local areas where interventions to improve disparities would have the greatest impact. The developed associations between social determinants and health outcomes as well as the geospatial models will be validated using community surveys and qualitative methods. A rapidly growing and underserved Hispanic immigrant population will be the target of an intervention informed by the research process to impact utilization of primary care services and designed, deployed, and evaluated using the geospatial tools and qualitative research findings. The purpose of this intervention will be to reduce health disparities by improving access to, and utilization of, primary care and preventative services. DISCUSSION: The results of this study will demonstrate the importance of several novel approaches to ameliorating health disparities, including the use of CBPR, the effectiveness of community-based interventions to influence health outcomes by leveraging social networks, and the importance of primary care access in ameliorating health disparities.

Communities matter: the relationship between neighborhoods and health.

Understanding the link between neighborhood conditions (both physical and social) and health outcomes is an essential step toward ameliorating health disparities in low-income and high-risk minority populations. This commentary discusses the evidence that the neighborhood is a key social determinant of health and describes tools that can be used to help overcome disparities in community health.

A Population Health Approach to Transitional Care Management for High-Risk Patients with Diabetes: Outcomes at a Rural Hospital.

Patient transitions from inpatient to home care are an important area of focus for reducing costly unplanned hospital readmissions. In rural settings, the challenge of reducing unplanned readmissions is amplified by limited access to both ambulatory and acute care as well as high levels of social disadvantage. In addition, there is a scarcity of evidence regarding strategies that have been proven to improve care transitions and related patient outcomes in this setting. This paper describes the process for implementation and results of a telephone-based transitional care management (TCM) program designed to reduce readmissions for patients with diabetes in a rural hospital in Scotland County, North Carolina. Data were collected from July 2016 to January 2019 using billing records to identify adult patients with high or very high risk of readmission based on length of stay, acuity, comorbidity, and emergency department visits (LACE) scores. Care managers contacted eligible patients by phone after discharge to review discharge instructions, assess need for home health services and transportation assistance, and schedule primary care follow-up visits. Overall, 13.8% of 15,271 discharges were targeted for TCM; 68.2% of these involved a patient with diabetes. The post-intervention 30-day readmission rate was 18.0% among patients identified as high or very high risk versus 8.8% among the overall population and did not differ significantly between TCM participants with diabetes and those without (22.9% vs.18.8%; P = 0.525). Findings highlight challenges with implementing transition of care interventions in rural settings, which include staffing, patient volume, and accessing data from out-of-network providers.

Patient and Family Engagement in the Design of a Mobile Health Solution for Pediatric Asthma: Development and Feasibility Study.

BACKGROUND: Asthma is a highly prevalent, chronic disease with significant morbidity, cost, and disparities in health outcomes. While adherence to asthma treatment guidelines can improve symptoms and decrease exacerbations, most patients receive care that is not guideline-based. New approaches that incorporate shared decision-making (SDM) and health information technology (IT) are needed to positively impact asthma management. Despite the promise of health IT to improve efficiency and outcomes in health care, new IT solutions frequently suffer from a lack of widespread adoption and do not achieve desired results, as a consequence of not involving end-users in design. OBJECTIVE: To describe a case study of a pediatric asthma SDM health IT solution's development and demonstrate a methodology for engaging actual patients and families in IT development. Perspectives are shared from the vantage point of the research team and a parent of a child with asthma, who participated on the development team. METHODS: We adapted user-centric design principles to engage actual users across three main development phases: project initiation, ideation, and usability testing. To facilitate the necessary level of user engagement, our approach included: (1) a Development Workgroup consisting of patients, caregivers, and providers who met regularly with the research team; and (2) "real-world users" consisting of patients, caregivers, and providers recruited from a variety of care locations, including safety-net clinics. RESULTS: Using this methodology, we successful partnered with asthma patients and families to create an interactive, digital solution called Carolinas Asthma Coach. Carolinas Asthma Coach incorporates SDM principles to elicit patient information, including goals and preferences, and provides health-literate, tailored education with specific guideline-based recommendations for patients and their providers. Of the patients, caregivers, and providers surveyed, 100% (n=60) said they would recommend Carolinas Asthma Coach to a friend or colleague. Qualitative feedback from users provided support for the usability and engaging nature of the app. CONCLUSIONS: This project demonstrates the feasibility and benefits of deploying user-centric design methods that engage real patients and caregivers throughout the health IT design process.

BMI at birth and overweight at age four.

BACKGROUND: Extensive investigation has established that an elevated weight at birth is associated with subsequent obesity and obesity related negative health outcomes. The significance of overweight at birth, however, remains ill-defined. Historically, it has been difficult to approximate adiposity in infancy in a way that is both simple and meaningful. Body-mass-index (BMI) growth charts for children younger than two years of age only became available in 2006 when published by the WHO. METHODS: This retrospective cohort analysis utilised anthropometric data extracted from the electronic medical record of a large integrated healthcare system in North Carolina. BMI and weight-for-age (WFA) >85% of WHO growth charts measured newborn overweight and macrosomia respectively. Logistic regression models assessed the associations between newborn macrosomia and overweight and overweight at 4 years of age, as well as associations with maternal BMI. Models included demographic data, gestational age, and maternal diabetes status as covariates. RESULTS: Both BMI and WFA >85% at birth were significantly associated with overweight at age 4 years. However, the greater odds of overweight was associated with newborn BMI >85%, with an adjusted odds ratio (AOR) of 2.08 (95% confidence interval [CI]: 1.4-3.08) versus 1.57 (95% CI: 1.08-2.27). Maternal obesity was also more robustly correlated with newborn BMI >85%, AOR of 4.14 (95% CI: 1.6-10.7), than with newborn WFA >85%, AOR of 3.09 (95% CI: 1.41-6.77). CONCLUSIONS: BMI >85% at birth is independently associated with overweight at 4 years. Newborn overweight is perhaps superior to newborn macrosomia in predicting overweight at age 4.

Nutrition education for cardiovascular disease prevention in individuals with spinal cord injuries: study protocol for a randomized controlled trial.

BACKGROUND: Individuals with chronic spinal cord injuries (SCIs) have an increased prevalence of cardiovascular disease (CVD) and associated risk factors compared with age-matched control subjects. Exercise has been shown to improve selected CVD risk factors in individuals with SCI, but using nutrition education as an intervention has not been evaluated in this population. This paper describes our research plan for evaluating the effect of nutrition education on individuals with SCI. In the present study, called Eat Smart, Live Better, we are using a randomized controlled design to test an intervention adapted from an existing evidence-based program that showed a positive effect on nutrition knowledge and behavior of older adults from the general population. There will be an inpatient group (n = 100) and a community group (n = 100). The aims of our study are to compare the intervention and control groups for (1) changes in nutritional behavior, nutritional knowledge, and dietary quality by participants in the program; (2) levels of adiposity and metabolic CVD risk factors at 12-month follow-up; and (3) differential effects among individuals with SCI in the acute rehabilitation setting and those living in the community. METHODS/DESIGN: This is a randomized controlled trial of nutrition education. The treatment groups receive six nutrition education sessions. The control groups receive the one "standard of care" nutrition lecture that is required by the Commission on Accreditation of Rehabilitation Facilities. Treatment groups include both an inpatient group, comprising patients who have been admitted to an acute rehabilitation facility because of their recent SCI, and an outpatient group, consisting of community-dwelling adults who are at least 1 year after their SCI. A total of 200 participants will be randomized 1:1 to the intervention or control group, stratified by location (acute rehabilitation facility or community dwelling). DISCUSSION: To our knowledge, this will be the first reported study of nutrition education in individuals with SCI. The low cost and feasibility of the intervention, if shown to improve nutritional behavior, suggests that it could be implemented in rehabilitation facilities across the country. This has the potential of lowering the burden of CVD and CVD risk factors in this high-risk population. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02368405 . Registered on February 10, 2015.

Policosanol is ineffective in the treatment of hypercholesterolemia: a randomized controlled trial.

BACKGROUND: Policosanol is one of the fastest growing over-the-counter supplements sold in the United States. The use of policosanol to treat elevated cholesterol is based on clinical trials conducted in Cuba, which showed sugar cane-derived policosanol to be similar in efficacy to statins. Recent studies have challenged these findings, but there have been no trials conducted in North America that have examined the ability of sugar cane-derived policosanol to lower cholesterol. OBJECTIVES: This study investigated the efficacy of sugar cane-derived policosanol in healthy adults with mild hypercholesterolemia. The primary outcome was the percentage change in LDL cholesterol after 8 wk of therapy. Secondary outcome measures included changes in total cholesterol, HDL cholesterol, triacylglycerols, C-reactive protein, and nuclear magnetic resonance-determined lipoprotein profile. Dietary habits, weight, and blood pressure were also monitored. DESIGN: Ambulatory, community-dwelling healthy adults with mild hypercholesterolemia (n = 40) were assigned to receive oral policosanol (20 mg) or placebo once daily for 8 wk. This was a double-blind, randomized controlled trial conducted from January through August 2005. RESULTS: No significant differences in the change in LDL cholesterol were observed between the placebo (n = 20) and policosanol (n = 20) groups. Also, no significant changes in secondary outcome measures, including total cholesterol, HDL cholesterol, triacylglycerol, C-reactive protein, and nuclear magnetic resonance spectroscopy-determined profiles were observed. Policosanol was well tolerated, and no significant adverse events were noted. CONCLUSION: Policosanol does not alter the serum lipid profile over an 8-wk period in adults with mild hypercholesterolemia.

Psychometric Properties of the Mini Pediatric Asthma Quality of Life Questionnaire in a US Sample.

The 13-item Mini Pediatric Asthma Quality of Life Questionnaire (MiniPAQLQ) was developed to measure asthma-specific quality of life in children. However, no validation studies have been conducted in the United States. This study aimed at determining the psychometric properties of the MiniPAQLQ in a US sample. Children aged 7-17 years and with an asthma diagnosis (n = 193) were identified from primary care clinics within an integrated healthcare system in the Southeastern United States. Participants completed surveys consisting of the MiniPAQLQ and the control module of the Asthma Therapy Assessment Questionnaire (ATAQ). Convergent validity was determined based on association between the MiniPAQLQ and ATAQ scores. Internal consistency reliability was determined from Cronbach's alpha coefficients for the MiniPAQLQ subscales (symptoms, emotions, and activities). Item-convergent validity was examined based on corrected item-total correlations. Item-discriminant validity was determined by comparing corrected item-total correlations and item-to-other-scale correlations. Floor and ceiling effects were examined based on the percentage of respondents having the lowest and highest scores on the MiniPAQLQ. A negative association was observed between quality of life scores from the MiniPAQLQ and asthma control as determined from the ATAQ, providing evidence of convergent validity. Internal consistency reliability was good with Cronbach's alpha values of above 0.8 for the MiniPAQLQ subscales. Item-convergent validity was confirmed, whereas item-discriminant validity was not confirmed. Floor effects were absent, whereas ceiling effects were present. The MiniPAQLQ possesses moderately good psychometric properties among children and adolescents in the United States and could be a useful tool for asthma management in clinical practice.

A Family Medicine Health Technology Strategy for Achieving the Triple Aim for US Health Care.

BACKGROUND AND OBJECTIVES: Health information technology (health IT) and health technology, more broadly, offer tremendous promise for connecting, synthesizing, and sharing information critical to improving health care delivery, reducing health system costs, and achieving personal and community health. While efforts to spur adoption of electronic health records (EHRs) among US practices and hospitals have been highly successful, aspirations for effective data exchanges and translation of data into measureable improvements in health outcomes remain largely unrealized. There are shining examples of health enhancement through new technologies, and the discipline of family medicine is well poised to take advantage of these innovations to improve patient and population health. The Future of Family Medicine led to important family medicine health IT initiatives over the past decade. For example, the American Academy of Family Physicians (AAFP) Center for Health Information Technology and the Robert Graham Center provided important leadership for informing health IT policy and standard-setting, such as the Centers for Medicare and Medicaid Services EHR incentives programs (often referred to as "meaningful use."). As we move forward, there is a need for a new and more comprehensive family medicine strategy for technology. To inform the Family Medicine for America's Health (FMAHealth) initiative, this paper explores strategies and tactics that family medicine could pursue to improve the utility of technology for primary care and to help primary care become a leader in rapid development, testing, and implementation of new technologies. These strategies were also designed with a broader stakeholder audience in mind, intending to reach beyond the work being done by FMAHealth. Specific suggestions include: a shared primary care health IT center, meaningful primary care quality measures and capacity to assess/report them, increased primary care technology research, a national family medicine registry, enhancement of family physicians' technology leadership, and championing patient-centered technology functionality.

Systolic Blood Pressure Control Among Individuals With Type 2 Diabetes: A Comparative Effectiveness Analysis of Three Interventions.

BACKGROUND: The relative effectiveness of 3 approaches to blood pressure control-(i) an intensive lifestyle intervention (ILI) focused on weight loss, (ii) frequent goal-based monitoring of blood pressure with pharmacological management, and (iii) education and support-has not been established among overweight and obese adults with type 2 diabetes who are appropriate for each intervention. METHODS: Participants from the Action for Health in Diabetes (Look AHEAD) and the Action to Control Cardiovascular Risk in Diabetes (ACCORD) cohorts who met criteria for both clinical trials were identified. The proportions of these individuals with systolic blood pressure (SBP) <140 mm Hg from annual standardized assessments over time were compared with generalized estimating equations. RESULTS: Across 4 years among 480 Look AHEAD and 1,129 ACCORD participants with baseline SBPs between 130 and 159 mm Hg, ILI (OR = 1.46; 95% CI = [1.18-1.81]) and frequent goal-based monitoring with pharmacotherapy (OR = 1.51; 95% CI = [1.16-1.97]) yielded higher rates of blood pressure control compared to education and support. The intensive behavioral-based intervention may have been more effective among individuals with body mass index >30 kg/m2, while frequent goal-based monitoring with medication management may be more effective among individuals with lower body mass index (interaction P = 0.047). CONCLUSIONS: Among overweight and obese adults with type 2 diabetes, both ILI and frequent goal-based monitoring with pharmacological management can be successful strategies for blood pressure control. CLINICAL TRIALS REGISTRY: clinicaltrials.gov identifiers NCT00017953 (Look AHEAD) and NCT00000620 (ACCORD).