Mixed Method Approach to Examine Prediabetes Screening, Follow-up Care & Guideline Implementation

Introduction: Nationally, prediabetes remains alarmingly underdiagnosed and untreated. A 2015 revision to national clinical guidelines more strongly recommending screening and more clearly recommending follow-up care could improve screening rates for prediabetes and clinician response to abnormal values. I conducted a mixed-methods study to assess and contextualize abnormal blood glucose screening and prediabetes follow-up care within a large, academic health system. Methods: For Aim 1, the dissertation evaluated abnormal blood glucose screening and clinician response to prediabetes through two retrospective cohort studies that: 1) utilized an interrupted time series design & segmented linear regression to assess implementation of the 2015 USPSTF abnormal blood glucose clinical guideline (Sub Aim A) and 2): utilized GEE to assess race and gender differences in abnormal blood screening and clinician response to prediabetes (Sub Aim B). For Aim 2, the dissertation assessed barriers to and facilitators of prediabetes screening and follow-up care through in-depth interviews to explore clinicians’ perceptions of prediabetes, EHR systems, and USPSTF clinical guidelines (Sub Aim C). Results: The results from Sub Aim A showed that: 1) only 16% of patients eligible for screening were screened for diabetes; 2) there was no statistically significant change in trend in diabetes screening rates from pre- to post-guideline; 3) only 2.5% of patients with prediabetes were referred to behavioral interventions; and 4) there was a statistically significant slight decrease in referral to behavioral interventions from pre- to post-guideline release. The findings from Sub Aim B demonstrated that: 1) a higher proportion of non-white patients had screening than white patients and 2) a higher proportion of male patients had screening than female patients. Sub Aim C found that: 1) providers did not have a systematic approach to screening; 2) physicians felt that the 2015 USPSTF abnormal blood glucose screening recommendation was reasonable and agreed with it but the treatment portion of the recommendation was hard to implement in practice; and 3) physician-provided counseling on lifestyle modifications was clinicians’ preferred and initial treatment for prediabetes. Conclusion: Our findings indicated that the 2015 USPSTF abnormal blood glucose guideline had little to no effect on prediabetes screening and treatment rates.Doctor of Philosoph

A Feasibility Study of Supply and Demand for Diabetes Prevention Programs in North Carolina

Diabetes Prevention Programs (DPPs) have shown that healthy eating and moderate physical activity are effective ways of delaying and preventing type 2 diabetes in people with impaired glucose tolerance. We assessed willingness to pay for DPPs from the perspective of potential recipients and the cost of providing these programs from the perspective of community health centers and local health departments in North Carolina

Implicit Racial/Ethnic Bias Among Health Care Professionals and Its Influence on Health Care Outcomes: A Systematic Review

Background. In the United States, people of color face disparities in access to health care, the quality of care received, and health outcomes. The attitudes and behaviors of health care providers have been identified as one of many factors that contribute to health disparities. Implicit attitudes are thoughts and feelings that often exist outside of conscious awareness, and thus are difficult to consciously acknowledge and control. These attitudes are often automatically activated and can influence human behavior without conscious volition. Objectives.We investigated the extent towhich implicit racial/ethnic bias exists among health care professionals and examined the relationships between health care professionals’ implicit attitudes about racial/ethnic groups and health care outcomes. Search Methods. To identify relevant studies, we searched 10 computerized bibliographic databases and used a reference harvesting technique. Selection Criteria. We assessed eligibility using double independent screening based on a priori inclusion criteria. We included studies if they sampled existing health care providers or those in training to become health care providers, measured and reported results on implicit racial/ethnic bias, and were written in English. Data Collection and Analysis. We included a total of 15 studies for review and then subjected them to double independent data extraction. Information extracted included the citation, purpose of the study, use of theory, study design, study site and location, sampling strategy, response rate, sample size and characteristics, measurement of relevant variables, analyses performed, and results and findings.We summarized study design characteristics, and categorized and then synthesized substantive findings. Main Results. Almost all studies used cross-sectional designs, convenience sampling, USparticipants, and the Implicit Association Test to assess implicit bias. Low to moderate levels of implicit racial/ethnic bias were found among health care professionals in all but 1 study. These implicit bias scores are similar to those in the general population. Levels of implicit bias against Black, Hispanic/Latino/Latina, and dark-skinned people were relatively similar across these groups. Although some associations between implicit bias and health care outcomes were nonsignificant, results also showed that implicit bias was significantly related to patient–provider interactions, treatment decisions, treatment adherence, and patient health outcomes. Implicit attitudesweremore often significantly related to patient–provider interactions and health outcomes than treatment processes. Conclusions. Most health care providers appear to have implicit bias in terms of positive attitudes toward Whites and negative attitudes toward people of color. Future studies need to employ more rigorous methods to examine the relationships between implicit bias and health care outcomes. Interventions targeting implicit attitudes among health care professionals are needed because implicit bias may contribute to health disparities for people of color

Effects of COVID-19 shelter-in-place confinement on diabetes prevention health behaviors among US adults with prediabetes: A cross-sectional survey

The coronavirus disease 2019 (COVID-19) pandemic has resulted in significant lifestyle changes due to shelter-in-place confinement orders. The study’s purpose was to assess if the COVID-19 pandemic affected self-reported diabetes prevention behaviors among American adults with prediabetes. As part of a randomized clinical trial among adults with prediabetes and overweight/obesity, questions were added to existing study surveys to assess the effect of the COVID-19 pandemic on diabetes prevention behaviors and stress. Survey responses were summarized using frequencies. 259 study participants completed seven COVID-19 survey questions from June 2020 to June 2021. Participants were 62.9% female, 42.5% White, 31.3% Black, 11.6% Asian, 8.1% Hispanic, and 6.6% Other. Over 75% of participants reported that the COVID-19 pandemic affected physical activity levels, with 82.1% of those affected reporting decreased physical activity; 70.3% reported that the pandemic affected their eating habits, with 61.7% of those affected reporting their eating habits became less healthy; 73.7% reported that the pandemic affected their level of stress, with 97.4% of those affected reporting that their level of stress had increased; 60% reported that the pandemic affected their motivation to adopt/maintain healthy habits, with 72.9% of those affected reporting their motivation decreased. A high percentage of study participants with prediabetes reported decreases in health promotion behaviors and increases in stress due to the COVID-19 pandemic. Consequently, the pandemic could lead to increased diabetes incidence. Strategies to improve diabetes prevention behaviors and address mental health concerns among those at-risk for diabetes are critical during and after the COVID-19 pandemic

A Web-Based mHealth Intervention With Telephone Support to Increase Physical Activity Among Pregnant Patients With Overweight or Obesity: Feasibility Randomized Controlled Trial.

BackgroundPregnant patients with overweight or obesity are at high risk for perinatal complications. Excess gestational weight gain (GWG) further exacerbates this risk. Mobile health (mHealth) lifestyle interventions that leverage technology to facilitate self-monitoring and provide just-in-time feedback may motivate behavior change to reduce excess GWG, reduce intervention costs, and increase scalability by improving access.ObjectiveThis study aimed to test the acceptability and feasibility of a pilot mHealth lifestyle intervention for pregnant patients with overweight or obesity to promote moderate intensity physical activity (PA), encourage guideline-concordant GWG, and inform the design of a larger pragmatic cluster randomized controlled trial.MethodsWe conducted a mixed methods acceptability and feasibility randomized controlled trial among pregnant patients with a prepregnancy BMI of 25 to 40 kg/m2. Patients with singletons at 8 to 15 weeks of gestation who were aged ≥21 years and had Wi-Fi access were recruited via email from 2 clinics within Kaiser Permanente Northern California and randomized to receive usual prenatal care or an mHealth lifestyle intervention. Participants in the intervention arm received wireless scales, access to an intervention website, activity trackers to receive automated feedback on weight gain and activity goals, and monthly calls from a lifestyle coach. Surveys and focus groups with intervention participants assessed intervention satisfaction and ways to improve the intervention. PA outcomes were self-assessed using the Pregnancy Physical Activity Questionnaire, and GWG was assessed using electronic health record data for both arms.ResultsOverall, 33 patients were randomly assigned to the intervention arm, and 35 patients were randomly assigned to the usual care arm. All participants in the intervention arm weighed themselves at least once a week, compared with 20% (7/35) of the participants in the usual care arm. Participants in the intervention arm wore the activity tracker 6.4 days per week and weighed themselves 5.3 times per week, and 88% (29/33) of them rated the program "good to excellent." Focus groups found that participants desired more nutrition-related support to help them manage GWG and would have preferred an app instead of a website. Participants in the intervention arm had a 23.46 metabolic equivalent of task hours greater change in total PA per week and a 247.2-minute greater change in moderate intensity PA per week in unadjusted models, but these effects were attenuated in adjusted models (change in total PA: 15.55 metabolic equivalent of task hours per week; change in moderate intensity PA: 199.6 minutes per week). We found no difference in total GWG (mean difference 1.14 kg) compared with usual care.ConclusionsThe pilot mHealth lifestyle intervention was feasible, highly acceptable, and promoted self-monitoring. Refined interventions are needed to effectively affect PA and GWG among pregnant patients with overweight or obesity.Trial registrationClinicalTrials.gov NCT03936283; https://clinicaltrials.gov/ct2/show/NCT03936283

Race and ethnicity and pharmacy dispensing of SGLT2 inhibitors and GLP-1 receptor agonists in type 2 diabetesResearch in context

Summary: Background: Sodium-Glucose Cotransporter 2 Inhibitors (SGLT2i) and Glucagon-Like Peptide-1 Receptor Agonists (GLP-1 RA) improve cardiorenal outcomes in patients with type 2 diabetes. Equitable use of SGLT2i and GLP-1 RA has the potential to reduce racial and ethnic health disparities. We evaluated trends in pharmacy dispensing of SGLT2i and GLP-1 RA by race and ethnicity. Methods: Retrospective cohort study of patients (≥18 years) with type 2 diabetes using 2014–2022 electronic health record data from six US care delivery systems. Entry was at earliest pharmacy dispensing of any type 2 diabetes medication. We used multivariable logistic regression to evaluate the association between pharmacy dispensing of SGLT2i and GLP1-RA and race and ethnicity. Findings: Our cohort included 687,165 patients (median 6 years of dispensing data; median 60 years; 0.3% American Indian/Alaska Native (AI/AN), 16.6% Asian, 10.5% Black, 1.4% Hawaiian or Pacific Islander (HPI), 31.1% Hispanic, 3.8% Other, and 36.3% White). SGLT2i was lower for AI/AN (OR 0.80, 95% confidence interval 0.68–0.94), Black (0.89, 0.86–0.92) and Hispanic (0.87, 0.85–0.89) compared to White patients. GLP-1 RA was lower for AI/AN (0.78, 0.63–0.97), Asian (0.50, 0.48–0.53), Black (0.86, 0.83–0.90), HPI (0.52, 0.46–0.57), Hispanic (0.69, 0.66–0.71), and Other (0.78, 0.73–0.83) compared to White patients. Interpretation: Dispensing of SGLT2is, and GLP-1 RAs was lower in minority group patients. There is a need to evaluate approaches to increase use of these cardiorenal protective drugs in patients from racial and ethnic minority groups with type 2 diabetes to reduce adverse cardiorenal outcomes and improve health equity. Funding: Patient-Centered Outcomes Research Institute and National Institutes of Health

Methods and initial findings from the Durham Diabetes Coalition: Integrating geospatial health technology and community interventions to reduce death and disability

Objective: The Durham Diabetes Coalition (DDC) was established in response to escalating rates of disability and death related to type 2 diabetes mellitus, particularly among racial/ethnic minorities and persons of low socioeconomic status in Durham County, North Carolina. We describe a community-based demonstration project, informed by a geographic health information system (GHIS), that aims to improve health and healthcare delivery for Durham County residents with diabetes. Materials and Methods: A prospective, population-based study is assessing a community intervention that leverages a GHIS to inform community-based diabetes care programs. The GHIS integrates clinical, social, and environmental data to identify, stratify by risk, and assist selection of interventions at the individual, neighborhood, and population levels. Results: The DDC is using a multifaceted approach facilitated by GHIS to identify the specific risk profiles of patients and neighborhoods across Durham County. A total of 22,982 patients with diabetes in Durham County were identified using a computable phenotype. These patients tended to be older, female, African American, and not covered by private health insurance, compared with the 166,041 persons without diabetes. Predictive models inform decision-making to facilitate care and track outcomes. Interventions include: 1) neighborhood interventions to improve the context of care; 2) intensive team-based care for persons in the top decile of risk for death or hospitalization within the coming year; 3) low-intensity telephone coaching to improve adherence to evidence-based treatments; 4) county-wide communication strategies; and 5) systematic quality improvement in clinical care. Conclusions: To improve health outcomes and reduce costs associated with type 2 diabetes, the DDC is matching resources with the specific needs of individuals and communities based on their risk characteristics

Implicit Racial/Ethnic Bias Among Health Care Professionals and Its Influence on Health Care Outcomes: A Systematic Review

Background. In the United States, people of color face disparities in access to health care, the quality of care received, and health outcomes. The attitudes and behaviors of health care providers have been identified as one of many factors that contribute to health disparities. Implicit attitudes are thoughts and feelings that often exist outside of conscious awareness, and thus are difficult to consciously acknowledge and control. These attitudes are often automatically activated and can influence human behavior without conscious volition. Objectives. We investigated the extent to which implicit racial/ethnic bias exists among health care professionals and examined the relationships between health care professionals’ implicit attitudes about racial/ethnic groups and health care outcomes. Search Methods. To identify relevant studies, we searched 10 computerized bibliographic databases and used a reference harvesting technique. Selection Criteria. We assessed eligibility using double independent screening based on a priori inclusion criteria. We included studies if they sampled existing health care providers or those in training to become health care providers, measured and reported results on implicit racial/ethnic bias, and were written in English. Data Collection and Analysis. We included a total of 15 studies for review and then subjected them to double independent data extraction. Information extracted included the citation, purpose of the study, use of theory, study design, study site and location, sampling strategy, response rate, sample size and characteristics, measurement of relevant variables, analyses performed, and results and findings. We summarized study design characteristics, and categorized and then synthesized substantive findings. Main Results. Almost all studies used cross-sectional designs, convenience sampling, US participants, and the Implicit Association Test to assess implicit bias. Low to moderate levels of implicit racial/ethnic bias were found among health care professionals in all but 1 study. These implicit bias scores are similar to those in the general population. Levels of implicit bias against Black, Hispanic/Latino/Latina, and dark-skinned people were relatively similar across these groups. Although some associations between implicit bias and health care outcomes were nonsignificant, results also showed that implicit bias was significantly related to patient–provider interactions, treatment decisions, treatment adherence, and patient health outcomes. Implicit attitudes were more often significantly related to patient–provider interactions and health outcomes than treatment processes. Conclusions. Most health care providers appear to have implicit bias in terms of positive attitudes toward Whites and negative attitudes toward people of color. Future studies need to employ more rigorous methods to examine the relationships between implicit bias and health care outcomes. Interventions targeting implicit attitudes among health care professionals are needed because implicit bias may contribute to health disparities for people of color