Publications

BACKGROUND: The ACS QUIK trial showed that a multicomponent quality improvement toolkit intervention resulted in improvements in processes of care for patients with acute myocardial infarction in Kerala but did not improve clinical outcomes in the context of background improvements in care. We describe the development of the ACS QUIK intervention and evaluate its implementation, acceptability, and sustainability. METHODS: We performed a mixed methods process evaluation alongside a cluster randomized, stepped-wedge trial in Kerala, India. The ACS QUIK intervention aimed to reduce the rate of major adverse cardiovascular events at 30 days compared with usual care across 63 hospitals (n = 21,374 patients). The ACS QUIK toolkit intervention, consisting of audit and feedback report, admission and discharge checklists, patient education materials, and guidelines for the development of code and rapid response teams, was developed based on formative qualitative research in Kerala and from systematic reviews. After four or more months of the center's participation in the toolkit intervention phase of the trial, an online survey and physician interviews were administered. Physician interviews focused on evaluating the implementation and acceptability of the toolkit intervention. A framework analysis of transcripts incorporated context and intervening mechanisms. RESULTS: Among 63 participating hospitals, 22 physicians (35%) completed online surveys. Of these, 17 (77%) respondents reported that their hospital had a cardiovascular quality improvement team, 18 (82%) respondents reported having read an audit report, admission checklist, or discharge checklist, and 19 (86%) respondents reported using patient education materials. Among the 28 interviewees (44%), facilitators of toolkit intervention implementation were physicians' support and leadership, hospital administrators' support, ease-of-use of checklists and patient education materials, and availability of training opportunities for staff. Barriers that influenced the implementation or acceptability of the toolkit intervention for physicians included time and staff constraints, Internet access, patient volume, and inadequate understanding of the quality improvement toolkit intervention. CONCLUSIONS: Implementation and acceptability of the ACS QUIK toolkit intervention were enhanced by hospital-level management support, physician and team support, and usefulness of checklists and patient education materials. Wider and longer-term use of the toolkit intervention and its expansion to potentially other cardiovascular conditions or other locations where the quality of care is not as high as in the ACS QUIK trial may be useful for improving acute cardiovascular care in Kerala and beyond. TRIAL REGISTRATION: NCT02256657.

Background: Economic dimensions of implementing quality improvement for diabetes care are understudied worldwide. We describe the economic evaluation protocol within a randomised controlled trial that tested a multi-component quality improvement (QI) strategy for individuals with poorly-controlled type 2 diabetes in South Asia. Methods/design: This economic evaluation of the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) randomised trial involved 1146 people with poorly-controlled type 2 diabetes receiving care at 10 diverse diabetes clinics across India and Pakistan. The economic evaluation comprises both a within-trial cost-effectiveness analysis (mean 2.5 years follow up) and a microsimulation model-based cost-utility analysis (life-time horizon). Effectiveness measures include multiple risk factor control (achieving HbA1c < 7% and blood pressure < 130/80 mmHg and/or LDL-cholesterol< 100 mg/dl), and patient reported outcomes including quality adjusted life years (QALYs) measured by EQ-5D-3 L, hospitalizations, and diabetes related complications at the trial end. Cost measures include direct medical and non-medical costs relevant to outpatient care (consultation fee, medicines, laboratory tests, supplies, food, and escort/accompanying person costs, transport) and inpatient care (hospitalization, transport, and accompanying person costs) of the intervention compared to usual diabetes care. Patient, healthcare system, and societal perspectives will be applied for costing. Both cost and health effects will be discounted at 3% per year for within trial cost-effectiveness analysis over 2.5 years and decision modelling analysis over a lifetime horizon. Outcomes will be reported as the incremental cost-effectiveness ratios (ICER) to achieve multiple risk factor control, avoid diabetes-related complications, or QALYs gained against varying levels of willingness to pay threshold values. Sensitivity analyses will be performed to assess uncertainties around ICER estimates by varying costs (95% CIs) across public vs. private settings and using conservative estimates of effect size (95% CIs) for multiple risk factor control. Costs will be reported in US$ 2018. Discussion: We hypothesize that the additional upfront costs of delivering the intervention will be counterbalanced by improvements in clinical outcomes and patient-reported outcomes, thereby rendering this multi-component QI intervention cost-effective in resource constrained South Asian settings. Trial registration: ClinicalTrials.gov: NCT01212328.

OBJECTIVE: To estimate the direction and magnitude of effect and quality of evidence for hospital-based heart failure (HF) quality improvement interventions on process of care measures and clinical outcomes among patients with acute HF. REVIEW METHODS: We performed a structured search to identify relevant randomised trials evaluating the effect of in-hospital quality improvement interventions for patients hospitalised with HF through February 2017. Studies were independently reviewed in duplicate for key characteristics, outcomes were summarised and a qualitative synthesis was performed due to substantial heterogeneity. RESULTS: From 3615 records, 14 randomised controlled trials were identified for inclusion with multifaceted interventions. There was a trend towards higher in-hospital use of ACE inhibitors (ACE-I; 57.9%vs40.0%) and beta-blockers (BBs; 46.7%vs10.2%) in the intervention than the comparator in one trial (n=429 participants). Five trials (n=78 727 participants) demonstrated no effect of the intervention on use of ACE-I or angiotensin receptor blocker at discharge. Three trials (n=89 660 participants) reported no effect on use of BB at discharge. Two trials (n=419 participants) demonstrated a trend towards lower hospital readmission up to 90 days after discharge. There was no consistent effect of the quality improvement intervention on 30-day all-cause mortality, hospital length of stay and patient-level health-related quality of life. CONCLUSIONS: Randomised trials of hospital-based HF quality improvement interventions do not show a consistent effect on most process of care measures and clinical outcomes. The overall quality of evidence for the prespecified primary and key secondary outcomes was very low to moderate, suggesting that future research will likely influence these estimates. TRIAL REGISTRATION NUMBER: CRD42016049545.

Importance: Wide heterogeneity exists in acute myocardial infarction treatment and outcomes in India. Objective: To evaluate the effect of a locally adapted quality improvement tool kit on clinical outcomes and process measures in Kerala, a southern Indian state. Design, Setting, and Participants: Cluster randomized, stepped-wedge clinical trial conducted between November 10, 2014, and November 9, 2016, in 63 hospitals in Kerala, India, with a last date of follow-up of December 31, 2016. During 5 predefined steps over the study period, hospitals were randomly selected to move in a 1-way crossover from the control group to the intervention group. Consecutively presenting patients with acute myocardial infarction were offered participation. Interventions: Hospitals provided either usual care (control group; n = 10 066 participants [step 0: n = 2915; step 1: n = 2649; step 2: n = 2251; step 3: n = 1422; step 4; n = 829; step 5: n = 0]) or care using a quality improvement tool kit (intervention group; n = 11 308 participants [step 0: n = 0; step 1: n = 662; step 2: n = 1265; step 3: n = 2432; step 4: n = 3214; step 5: n = 3735]) that consisted of audit and feedback, checklists, patient education materials, and linkage to emergency cardiovascular care and quality improvement training. Main Outcomes and Measures: The primary outcome was the composite of all-cause death, reinfarction, stroke, or major bleeding using standardized definitions at 30 days. Secondary outcomes included the primary outcome's individual components, 30-day cardiovascular death, medication use, and tobacco cessation counseling. Mixed-effects logistic regression models were used to account for clustering and temporal trends. Results: Among 21 374 eligible randomized participants (mean age, 60.6 [SD, 12.0] years; n = 16 183 men [76%] ; n = 13 689 [64%] with ST-segment elevation myocardial infarction), 21 079 (99%) completed the trial. The primary composite outcome was observed in 5.3% of the intervention participants and 6.4% of the control participants. The observed difference in 30-day major adverse cardiovascular event rates between the groups was not statistically significant after adjustment (adjusted risk difference, -0.09% [95% CI, -1.32% to 1.14%]; adjusted odds ratio, 0.98 [95% CI, 0.80-1.21]). The intervention group had a higher rate of medication use including reperfusion but no effect on tobacco cessation counseling. There were no unexpected adverse events reported. Conclusions and Relevance: Among patients with acute myocardial infarction in Kerala, India, use of a quality improvement intervention compared with usual care did not decrease a composite of 30-day major adverse cardiovascular events. Further research is needed to understand the lack of efficacy. Trial Registration: clinicaltrials.gov Identifier: NCT02256657.

BACKGROUND: Achievement of diabetes care goals is suboptimal globally. Diabetes-focused quality improvement (QI) is effective but remains untested in South Asia. OBJECTIVE: To compare the effect of a multicomponent QI strategy versus usual care on cardiometabolic profiles in patients with poorly controlled diabetes. DESIGN: Parallel, open-label, pragmatic randomized, controlled trial. (ClinicalTrials.gov: NCT01212328). SETTING: Diabetes clinics in India and Pakistan. PATIENTS: 1146 patients (575 in the intervention group and 571 in the usual care group) with type 2 diabetes and poor cardiometabolic profiles (glycated hemoglobin [HbA1c] level ≥8% plus systolic blood pressure [BP] ≥140 mm Hg and/or low-density lipoprotein cholesterol [LDLc] level ≥130 mg/dL). INTERVENTION: Multicomponent QI strategy comprising nonphysician care coordinators and decision-support electronic health records. MEASUREMENTS: Proportions achieving HbA1c level less than 7% plus BP less than 130/80 mm Hg and/or LDLc level less than 100 mg/dL (primary outcome); mean risk factor reductions, health-related quality of life (HRQL), and treatment satisfaction (secondary outcomes). RESULTS: Baseline characteristics were similar between groups. Median diabetes duration was 7.0 years; 6.8% and 39.4% of participants had preexisting cardiovascular and microvascular disease, respectively; mean HbA1c level was 9.9%; mean BP was 143.3/81.7 mm Hg; and mean LDLc level was 122.4 mg/dL. Over a median of 28 months, a greater percentage of intervention participants achieved the primary outcome (18.2% vs. 8.1%; relative risk, 2.24 [95% CI, 1.71 to 2.92]). Compared with usual care, intervention participants achieved larger reductions in HbA1c level (-0.50% [CI, -0.69% to -0.32%]), systolic BP (-4.04 mm Hg [CI, -5.85 to -2.22 mm Hg]), diastolic BP (-2.03 mm Hg [CI, -3.00 to -1.05 mm Hg]), and LDLc level (-7.86 mg/dL [CI, -10.90 to -4.81 mg/dL]) and reported higher HRQL and treatment satisfaction. LIMITATION: Findings were confined to urban specialist diabetes clinics. CONCLUSION: Multicomponent QI improves achievement of diabetes care goals, even in resource-challenged clinics. PRIMARY FUNDING SOURCE: National Heart, Lung, and Blood Institute and UnitedHealth Group.