Integrating cardiovascular disease (CVD) prevention in routine HIV care remains a challenge. This study aimed to identify factors associated with adherence to guideline-recommended CVD preventive practices among HIV clinicians. Clinicians from eight HIV clinics in Atlanta were invited to complete an online survey. The survey was informed by the Consolidated Framework for Implementation Research and assessed the following: clinician CVD risk screening and advice frequency (never to always), individual characteristics (clinician beliefs, self-efficacy, and motivation), inner setting factors (clinic culture, learning climate, leadership engagement, and resources available), and outer setting factors (peer pressure and patient needs). Bivariate correlations examined associations between these factors and guideline adherence. Thirty-eight clinicians completed the survey (82% women, mean age 42 years, 50% infectious disease physicians). For risk screening, clinicians always check patient blood pressure (median score 7.0/7), while they usually ask about smoking or check their blood glucose (median score 6.0/7). For advice provision, clinicians usually recommend quitting smoking, controlling cholesterol or controlling blood pressure (median score 6.0/7), while they often recommend controlling blood glucose, losing weight, or improving diet/physical activity (median score 5.5/7). Clinician beliefs, motivation and self-efficacy were positively correlated with screening and advice practices (r = .55-.84), while inner setting factors negatively correlated with lifestyle-related screening and advice practices (r = -.51 to -.76). Peer pressure was positively correlated with screening and advice practices (r = .57-.89). Clinician psychosocial characteristics and perceived peer pressure positively influence adherence to guideline-recommended CVD preventive practices. These correlates along with leadership engagement could be targeted with proven implementation strategies.

The collaborative care model is an evidence-based intervention for behavioral and other chronic conditions that has the potential to address the large burden of mental illness globally. Using the World Health Organization Health Systems Framework, the authors present challenges in implementing this model in low- and middle-income countries (LMICs) and discuss strategies to address these challenges based on experiences with three large-scale programs: an implementation research study in a district-level government hospital in rural Nepal, one clinical trial in 50 primary health centers in rural India, and one study in four diabetes clinics in India. Several strategies can be utilized to address implementation challenges and enhance scalability in LMICs, including mobilizing community resources, engaging in advocacy, and strengthening the overall health care delivery system.

Purpose of review

To advance our understanding of the impacts of policies and programs aimed at improving detection, engagement, prevention, and clinical diabetes management in the USA, we synthesized findings from a network of studies that used natural experiments to evaluate diabetes health policies and programs.

Findings

Studies from the Natural EXperiments for Translation in Diabetes (NEXT-D) network used rigorous longitudinal quasi-experimental study designs (e.g., interrupted time series) and analytical methods (e.g., difference-in-differences) to augment causal inference. Investigators partnered with health system stakeholders to evaluate whether glucose testing rates changed from before-to-after clinic interventions (e.g., integrating electronic screening decision prompts in New York City) or employer programs (e.g., targeted messaging and waiving copayments for at-risk employees). Other studies examined participation and behavior change in low- (e.g., wellness coaching) or high-intensity lifestyle modification programs (e.g., diabetes prevention program-like interventions) offered by payers or employers. Lastly, studies assessed how employer health insurance benefits impacted healthcare utilization, adherence, and outcomes among people with diabetes. NEXT-D demonstrated that low-intensity interventions to facilitate glucose testing and enhance engagement in lifestyle modification were associated with small improvements in weight but large improvements in screening and testing when supported by electronic health record-based decision-support. Regarding high-intensity diabetes prevention program-like lifestyle programs offered by payers or employers, enrollment was modest and led to weight loss and marginally lower short-term health expenditures. Health plans that incentivize patient behaviors were associated with increases in medication adherence. Meanwhile, shifting patients to high-deductible health plans was associated with no change in medication use and preventive screenings, but patients with diabetes delayed accessing healthcare for acute complications (e.g., cellulitis). Findings were more pronounced among lower-income patients, who experienced increased rates and acuity of emergency department visits for diabetes complications and other high-severity conditions. Findings from NEXT-D studies provide informative data that can guide programs and policies to facilitate detection, prevention, and treatment of diabetes in practice.

Purpose of review

To advance our understanding of the impacts of policies and programs aimed at improving detection, engagement, prevention, and clinical diabetes management in the USA, we synthesized findings from a network of studies that used natural experiments to evaluate diabetes health policies and programs.

Findings

Studies from the Natural EXperiments for Translation in Diabetes (NEXT-D) network used rigorous longitudinal quasi-experimental study designs (e.g., interrupted time series) and analytical methods (e.g., difference-in-differences) to augment causal inference. Investigators partnered with health system stakeholders to evaluate whether glucose testing rates changed from before-to-after clinic interventions (e.g., integrating electronic screening decision prompts in New York City) or employer programs (e.g., targeted messaging and waiving copayments for at-risk employees). Other studies examined participation and behavior change in low- (e.g., wellness coaching) or high-intensity lifestyle modification programs (e.g., diabetes prevention program-like interventions) offered by payers or employers. Lastly, studies assessed how employer health insurance benefits impacted healthcare utilization, adherence, and outcomes among people with diabetes. NEXT-D demonstrated that low-intensity interventions to facilitate glucose testing and enhance engagement in lifestyle modification were associated with small improvements in weight but large improvements in screening and testing when supported by electronic health record-based decision-support. Regarding high-intensity diabetes prevention program-like lifestyle programs offered by payers or employers, enrollment was modest and led to weight loss and marginally lower short-term health expenditures. Health plans that incentivize patient behaviors were associated with increases in medication adherence. Meanwhile, shifting patients to high-deductible health plans was associated with no change in medication use and preventive screenings, but patients with diabetes delayed accessing healthcare for acute complications (e.g., cellulitis). Findings were more pronounced among lower-income patients, who experienced increased rates and acuity of emergency department visits for diabetes complications and other high-severity conditions. Findings from NEXT-D studies provide informative data that can guide programs and policies to facilitate detection, prevention, and treatment of diabetes in practice.

The high prevalence and costs of type 2 diabetes makes it a rapidly evolving focus of policy action. Health systems, employers, community organizations, and public agencies have increasingly looked to translate the benefits of promising research interventions into innovative policies intended to prevent or control diabetes. Though guided by research, these health policies provide no guarantee of effectiveness and may have opportunity costs or unintended consequences. Natural experiments use pragmatic and available data sources to compare specific policies to other policy alternatives or predictions of what would likely have happened in the absence of any intervention. The Natural Experiments for Translation in Diabetes (NEXT-D) Study is a network of academic, community, industry, and policy partners, collaborating to advance the methods and practice of natural experimental research, with a shared aim of identifying and prioritizing the best policies to prevent and control diabetes. This manuscript describes the NEXT-D Study group's multi-sector natural experiments in areas of diabetes prevention or control as case examples to illustrate the selection, design, analysis, and challenges inherent to natural experimental study approaches to inform development or evaluation of health policies.

Purpose of review

Diabetes incidence is rising among vulnerable population subgroups including minorities and individuals with limited education. Many diabetes-related programs and public policies are unevaluated while others are analyzed with research designs highly susceptible to bias which can result in flawed conclusions. The Natural Experiments for Translation in Diabetes 2.0 (NEXT-D2) Network includes eight research centers and three funding agencies using rigorous methods to evaluate natural experiments in health policy and program delivery.

Recent findings

NEXT-D2 research studies use quasi-experimental methods to assess three major areas as they relate to diabetes: health insurance expansion; healthcare financing and payment models; and innovations in care coordination. The studies will report on preventive processes, achievement of diabetes care goals, and incidence of complications. Some studies assess healthcare utilization while others focus on patient-reported outcomes. NEXT-D2 examines the effect of public and private policies on diabetes care and prevention at a critical time, given ongoing and rapid shifts in the US health policy landscape.

Background

While data from the latter part of the twentieth century consistently showed that immigrants to high-income countries faced higher cardio-metabolic risk than their counterparts in low- and middle-income countries, urbanization and associated lifestyle changes may be changing these patterns, even for conditions considered to be advanced manifestations of cardio-metabolic disease (e.g., chronic kidney disease [CKD]).

Methods and findings

Using cross-sectional data from the Center for cArdiometabolic Risk Reduction in South Asia (CARRS, n = 5294) and Mediators of Atherosclerosis in South Asians Living in America (MASALA, n = 748) studies, we investigated whether prevalence of CKD is similar among Indians living in Indian and U.S. cities. We compared crude, age-, waist-to-height ratio-, and diabetes- adjusted CKD prevalence difference. Among participants identified to have CKD, we compared management of risk factors for its progression. Overall age-adjusted prevalence of CKD was similar in MASALA (14.0% [95% CI 11.8-16.3]) compared with CARRS (10.8% [95% CI 10.0-11.6]). Among men the prevalence difference was low (prevalence difference 1.8 [95% CI -1.6,5.3]) and remained low after adjustment for age, waist-to-height ratio, and diabetes status (-0.4 [-3.2,2.5]). Adjusted prevalence difference was higher among women (prevalence difference 8.9 [4.8,12.9]), but driven entirely by a higher prevalence of albuminuria among women in MASALA. Severity of CKD--i.e., degree of albuminuria and proportion of participants with reduced glomerular filtration fraction--was higher in CARRS for both men and women. Fewer participants with CKD in CARRS were effectively treated. 4% of CARRS versus 51% of MASALA participants with CKD had A1c < 7%; and 7% of CARRS versus 59% of MASALA participants blood pressure < 140/90 mmHg. Our analysis applies only to urban populations. Demographic--particularly educational attainment--differences among participants in the two studies are a potential source of bias.

Conclusions

Prevalence of CKD among Indians living in Indian and U.S. cities is similar. Persons with CKD living in Indian cities face higher likelihood of experiencing end-stage renal disease since they have more severe kidney disease and little evidence of risk factor management.

Cardiovascular, respiratory, and related disorders (CVRDs) are the leading causes of adult death worldwide, and substantial inequalities in care of patients with CVRDs exist between countries of high income and countries of low and middle income. Based on current trends, the UN Sustainable Development Goal to reduce premature mortality due to CVRDs by a third by 2030 will be challenging for many countries of low and middle income. We did systematic literature reviews of effectiveness and cost-effectiveness to identify priority interventions. We summarise the key findings and present a costed essential package of interventions to reduce risk of and manage CVRDs. On a population level, we recommend tobacco taxation, bans on trans fats, and compulsory reduction of salt in manufactured food products. We suggest primary health services be strengthened through the establishment of locally endorsed guidelines and ensured availability of essential medications. The policy interventions and health service delivery package we suggest could serve as the cornerstone for the management of CVRDs, and afford substantial financial risk protection for vulnerable households. We estimate that full implementation of the essential package would cost an additional US$21 per person in the average low-income country and $24 in the average lower-middle-income country. The essential package we describe could be a starting place for low-income and middle-income countries developing universal health coverage packages. Interventions could be rolled out as disease burden demands and budgets allow. Our outlined interventions provide a pathway for countries attempting to convert the UN Sustainable Development Goal commitments into tangible action.