Effect of a multicomponent intervention on achievement and improvements in quality-of-care indices among people with Type 2 diabetes in South Asia: the CARRS trial

Technology-supported shared decision-making in chronic conditions: A systematic review of randomized controlled trials

OBJECTIVES

To describe the role of patients with a chronic disease, healthcare professionals (HCPs) and technology in shared decision making (SDM) and the use of clinical decision support systems (CDSSs), and to evaluate the effectiveness of SDM and CDSSs interventions.

METHODS

Randomized controlled studies published between 2011 and 2021 were identified and screened independently by two reviewers, followed by data extraction and analysis. SDM elements and interactive styles were identified to shape the roles of patients, HCPs and technology.

RESULTS

Forty-three articles were identified and reported on 21 SDM-studies, 15 CDSS-studies, 2 studies containing both an SDM-tool and a CDSS, and 5 studies with other decision support components. SDM elements were mostly identified in SDM-tools and interactions styles were least common in the other decision support components.

CONCLUSIONS

Patients within the included RCTs mainly received information from SDM-tools and occasionally CDSSs when it concerns treatment strategies. HCPs provide and clarify information using SDM-tools and CDSSs. Technology provides interactions, which can support more active SDM. SDM-tools mostly showed evidence for positive effects on SDM outcomes, while CDSSs mostly demonstrated positive effects on clinical outcomes.

PRACTICE IMPLICATIONS

Technology-supported SDM has potential to optimize SDM when patients, HCPs and technology collaborate well together.

Know-do gaps for cardiovascular disease care in Cambodia: Evidence on clinician knowledge and delivery of evidence-based prevention actions

Cardiovascular diseases (CVD) are the leading cause of death in Cambodia. However, it is unknown whether clinicians in Cambodia provide evidence-based CVD preventive care actions. We address this important gap and provide one of the first assessments of clinical care for CVD prevention in an LMIC context. We determined the proportion of primary care visits by adult patients that resulted in evidence-based CVD preventive care actions, identified which care actions were most frequently missed, and estimated the know-do gap for each clinical action. We used data on 190 direct clinician-patient observations and 337 clinician responses to patient vignettes from 114 public primary care health facilities. Our main outcomes were the proportion of patient consultations and responses to care vignettes where clinicians measured blood pressure, blood glucose, body mass index, and asked questions regarding alcohol, tobacco, physical activity, and diet. There were very large clinical care shortfalls for all CVD care actions. Just 6.4% (95% CI: 3.0%, 13.0%) of patients had their BMI measured, 8.0% (4.6%, 13.6%) their blood pressure measured at least twice, only 4.7% (1.9%, 11.2%) their blood glucose measured. Less than 21% of patients were asked about their physical activity (11.7% [7.0%, 18.9%]), smoking (18.0% [11.8%, 26.5%]), and alcohol-related behaviors (20.2% [13.7%, 28.9%]). We observed the largest know-do gaps for blood glucose and BMI measurements with smaller but important know-do gaps for the other clinical actions. CVD care did not vary across clinician cadre or by years of experience. We find large CVD care delivery gaps in primary-care facilities across Cambodia. Our results suggest that diabetes is being substantially underdiagnosed and that clinicians are losing CVD prevention potential by not identifying individuals who would benefit from behavioral changes. The large overall and know-do gaps suggest that interventions for improving preventive care need to target both clinical knowledge and the bottlenecks between knowledge and care behavior.