BACKGROUND: Due to low care utilization, a complex intervention was done for two years to optimize the Ethiopian Health Extension Program. Improved quality of the integrated community case management services was an intermediate outcome of this intervention through community education and mobilization, capacity building of health workers, and strengthening of district ownership and accountability of sick child services. We evaluated the association between the intervention and the health extension workers' ability to correctly classify common childhood illnesses in four regions of Ethiopia. METHODS: Baseline and endline assessments were done in 2016 and 2018 in intervention and comparison areas in four regions of Ethiopia. Ill children aged 2 to 59 months were mobilized to visit health posts for an assessment that was followed by re-examination. We analyzed sensitivity, specificity, and difference-in-difference of correct classification with multilevel mixed logistic regression in intervention and comparison areas at baseline and endline. RESULTS: Health extensions workers' consultations with ill children were observed in intervention (n = 710) and comparison areas (n = 615). At baseline, re-examination of the children showed that in intervention areas, health extension workers' sensitivity for fever or malaria was 54%, 68% for respiratory infections, 90% for diarrheal diseases, and 34% for malnutrition. At endline, it was 40% for fever or malaria, 49% for respiratory infections, 85% for diarrheal diseases, and 48% for malnutrition. Specificity was higher (89-100%) for all childhood illnesses. Difference-in-differences was 6% for correct classification of fever or malaria [aOR = 1.45 95% CI: 0.81-2.60], 4% for respiratory tract infection [aOR = 1.49 95% CI: 0.81-2.74], and 5% for diarrheal diseases [aOR = 1.74 95% CI: 0.77-3.92]. CONCLUSION: This study revealed that the Optimization of Health Extension Program intervention, which included training, supportive supervision, and performance reviews of health extension workers, was not associated with an improved classification of childhood illnesses by these Ethiopian primary health care workers. TRIAL REGISTRATION: ISRCTN12040912, http://www.isrctn.com/ISRCTN12040912.
The Covid-19 and other recent pandemics has highlighted existing weakness in health systems across the Latin-America and the Caribbean (LAC) region to effectively prepare for and respond to Public Health Emergencies. It has been stated that quality of care will be among the most influential factors on Covid 19 mortality rates and low systems performance is the common case in these countries. More comprehensive and system level strategies are required to address the challenges. These must focus on redesigning and strengthening health systems to make them more resilient to the changing needs of populations and based on quality improvement methods that have shown rigorously evaluated positive effects in previous local and regional experiences. A call to action is being made by the Latin American Consortium for Quality, Patient Safety and Innovation (CLICSS) and they provide specific recommendations for decision makers.
The COVID-19 pandemic has made vivid the need for resilient, high-quality health systems and presents an opportunity to reconsider how to build such systems. Although even well resourced, well performing health systems have struggled at various points to cope with surges of COVID-19, experience suggests that establishing health system foundations based on clear aims, adequate resources, and effective constraints and incentives is crucial for consistent provision of high-quality care, and that these cannot be replaced by piecemeal quality improvement interventions. We identify four mutually reinforcing structural investments that could transform health system performance in resource-constrained countries: revamping health provider education, redesigning platforms for care delivery, instituting strategic purchasing and management strategies, and developing patient-level data systems. Countries should seize the political and moral energy provided by the COVID-19 pandemic to build health systems fit for the future.
BACKGROUND: The use of appropriate and relevant nurse-sensitive indicators provides an opportunity to demonstrate the unique contributions of nurses to patient outcomes. The aim of this work was to develop relevant metrics to assess the quality of nursing care in low- and middle-income countries (LMICs) where they are scarce. MAIN BODY: We conducted a scoping review using EMBASE, CINAHL and MEDLINE databases of studies published in English focused on quality nursing care and with identified measurement methods. Indicators identified were reviewed by a diverse panel of nursing stakeholders in Kenya to develop a contextually appropriate set of nurse-sensitive indicators for Kenyan hospitals specific to the five major inpatient disciplines. We extracted data on study characteristics, nursing indicators reported, location and the tools used. A total of 23 articles quantifying the quality of nursing care services met the inclusion criteria. All studies identified were from high-income countries. Pooled together, 159 indicators were reported in the reviewed studies with 25 identified as the most commonly reported. Through the stakeholder consultative process, 52 nurse-sensitive indicators were recommended for Kenyan hospitals. CONCLUSIONS: Although nurse-sensitive indicators are increasingly used in high-income countries to improve quality of care, there is a wide heterogeneity in the way indicators are defined and interpreted. Whilst some indicators were regarded as useful by a Kenyan expert panel, contextual differences prompted them to recommend additional new indicators to improve the evaluations of nursing care provision in Kenyan hospitals and potentially similar LMIC settings. Taken forward through implementation, refinement and adaptation, the proposed indicators could be more standardised and may provide a common base to establish national or regional professional learning networks with the common goal of achieving high-quality care through quality improvement and learning.
BACKGROUND: As more countries progress towards malaria elimination, a better understanding of the most critical health system features for enabling and supporting malaria control and elimination is needed. METHODS: All available health systems data relevant for malaria control were collated from 23 online data repositories. Principal component analysis was used to create domain specific health system performance measures. Multiple regression model selection approaches were used to identify key health systems predictors of progress in malaria control in the 2000-2016 period among 105 countries. Additional analysis was performed within malaria burden groups. RESULTS: There was large heterogeneity in progress in malaria control in the 2000-2016 period. In univariate analysis, several health systems factors displayed a strong positive correlation with reductions in malaria burden between 2000 and 2016. In multivariable models, delivery of routine services and hospital capacity were strongly predictive of reductions in malaria cases, especially in high burden countries. In low-burden countries approaching elimination, primary health center density appeared negatively associated with progress while hospital capacity was positively correlated with eliminating malaria. CONCLUSIONS: The findings presented in this manuscript suggest that strengthening health systems can be an effective strategy for reducing malaria cases, especially in countries with high malaria burden. Potential returns appear particularly high in the area of service delivery.
BACKGROUND: Evidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects of CQI on quality of antenatal HIV care in primary care clinics in rural South Africa. METHODS AND FINDINGS: We conducted a stepped-wedge cluster-randomised controlled trial (RCT) comparing CQI to usual standard of antenatal care (ANC) in 7 nurse-led, public-sector primary care clinics-combined into 6 clusters-over 8 steps and 19 months. Clusters randomly switched from comparator to intervention on pre-specified dates until all had rolled over to the CQI intervention. Investigators and clusters were blinded to randomisation until 2 weeks prior to each step. The intervention was delivered by trained CQI mentors and included standard CQI tools (process maps, fishbone diagrams, run charts, Plan-Do-Study-Act [PDSA] cycles, and action learning sessions). CQI mentors worked with health workers, including nurses and HIV lay counsellors. The mentors used the standard CQI tools flexibly, tailored to local clinic needs. Health workers were the direct recipients of the intervention, whereas the ultimate beneficiaries were pregnant women attending ANC. Our 2 registered primary endpoints were viral load (VL) monitoring (which is critical for elimination of mother-to-child transmission of HIV [eMTCT] and the health of pregnant women living with HIV) and repeat HIV testing (which is necessary to identify and treat women who seroconvert during pregnancy). All pregnant women who attended their first antenatal visit at one of the 7 study clinics and were ≥18 years old at delivery were eligible for endpoint assessment. We performed intention-to-treat (ITT) analyses using modified Poisson generalised linear mixed effects models. We estimated effect sizes with time-step fixed effects and clinic random effects (Model 1). In separate models, we added a nested random clinic-time step interaction term (Model 2) or individual random effects (Model 3). Between 15 July 2015 and 30 January 2017, 2,160 participants with 13,212 ANC visits (intervention n = 6,877, control n = 6,335) were eligible for ITT analysis. No adverse events were reported. Median age at first booking was 25 years (interquartile range [IQR] 21 to 30), and median parity was 1 (IQR 0 to 2). HIV prevalence was 47% (95% CI 42% to 53%). In Model 1, CQI significantly increased VL monitoring (relative risk [RR] 1.38, 95% CI 1.21 to 1.57, p < 0.001) but did not improve repeat HIV testing (RR 1.00, 95% CI 0.88 to 1.13, p = 0.958). These results remained essentially the same in both Model 2 and Model 3. Limitations of our study include that we did not establish impact beyond the duration of the relatively short study period of 19 months, and that transition steps may have been too short to achieve the full potential impact of the CQI intervention. CONCLUSIONS: We found that CQI can be effective at increasing quality of primary care in rural Africa. Policy makers should consider CQI as a routine intervention to boost quality of primary care in rural African communities. Implementation research should accompany future CQI use to elucidate mechanisms of action and to identify factors supporting long-term success. TRIAL REGISTRATION: This trial is registered at ClinicalTrials.gov under registration number NCT02626351.
BACKGROUND: Healthcare is amongst the most complex of human systems. Coordinating activities and integrating newer with older ways of treating patients while delivering high-quality, safe care, is challenging. Three landmark reports in 2018 led by (1) the Lancet Global Health Commission, (2) a coalition of the World Health Organization, the Organisation for Economic Co-operation and Development and the World Bank, and (3) the National Academies of Sciences, Engineering and Medicine of the United States propose that health systems need to tackle care quality, create less harm and provide universal health coverage in all nations, but especially low- and middle-income countries. The objective of this study is to review these reports with the aim of advancing the discussion beyond a conceptual diagnosis of quality gaps into identification of practical opportunities for transforming health systems by 2030. MAIN BODY: We analysed the reports via text-mining techniques and content analyses to derive their key themes and concepts. Initiatives to make progress include better measurement, using the capacities of information and communications technologies, taking a systems view of change, supporting systems to be constantly improving, creating learning health systems and undergirding progress with effective research and evaluation. Our analysis suggests that the world needs to move from 2018, the year of reports, to the 2020s, the decade of action. We propose three initiatives to support this move: first, developing a blueprint for change, modifiable to each country's circumstances, to give effect to the reports' recommendations; second, to make tangible steps to reduce inequities within and across health systems, including redistributing resources to areas of greatest need; and third, learning from what goes right to complement current efforts focused on reducing things going wrong. We provide examples of targeted funding which would have major benefits, reduce inequalities, promote universality and be better at learning from successes as well as failures. CONCLUSION: The reports contain many recommendations, but lack an integrated, implementable, 10-year action plan for the next decade to give effect to their aims to improve care to the most vulnerable, save lives by providing high-quality healthcare and shift to measuring and ensuring better systems- and patient-level outcomes. This article signals what needs to be done to achieve these aims.
OBJECTIVES: Recent studies have identified large and systematic deficits in clinical care in low-income countries that are likely to limit health gains. This has focused attention on effectiveness of pre-service education. One approach to assessing this is observation of clinical performance among recent graduates providing care. However, no studies have assessed performance in a standard manner across countries. We analysed clinical performance among recently graduated providers in nine low- or middle-income countries. METHODS: Service Provision Assessments from Haiti, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Tanzania, and Uganda were used. We constructed a Good Medical Practice Index that assesses completion of essential clinical actions using direct observations of care (range 0-1), calculated index scores by country and clinical cadre, and assessed the role of facility and clinical characteristics using regression analysis. RESULTS: Our sample consisted of 2223 clinicians with at least one observation of care. The Good Medical Practice score for the sample was 0.50 (SD = 0.20). Nurses and midwives had the highest score at 0.57 (SD = 0.20), followed by associate clinicians at 0.43 (SD = 0.18), and physicians at 0.42 (SD = 0.16). The average national performance varied from 0.63 (SD = 0.18) in Uganda to 0.39 (SD = 0.17) in Nepal, persisting after adjustment for facility and clinician characteristics. CONCLUSIONS: These results show substantial gaps in clinical performance among recently graduated clinicians, raising concerns about models of clinical education. Competency-based education should be considered to improve quality of care in LMICs. Observations of care offer important insight into the quality of clinical education.
BACKGROUND: Quality improvement collaboratives (QICs) have been used to improve health care for decades. Evidence on QIC effectiveness has been reported, but systematic reviews to date have little information from low- and middle-income countries (LMICs). OBJECTIVE: To assess the effectiveness of QICs in LMICs. METHODS: We conducted a systematic review following Cochrane methods, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach for quality of evidence grading, and the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement for reporting. We searched published and unpublished studies between 1969 and March 2019 from LMICs. We included papers that compared usual practice with QICs alone or combined with other interventions. Pairs of reviewers independently selected and assessed the risk of bias and extracted data of included studies. To estimate strategy effectiveness from a single study comparison, we used the median effect size (MES) in the comparison for outcomes in the same outcome group. The primary analysis evaluated each strategy group with a weighted median and interquartile range (IQR) of MES values. In secondary analyses, standard random-effects meta-analysis was used to estimate the weighted mean MES and 95% confidence interval (CI) of the mean MES of each strategy group. This review is registered with PROSPERO (International Prospective Register of Systematic Reviews): CRD42017078108. RESULTS: Twenty-nine studies were included; most (21/29, 72.4%) were interrupted time series studies. Evidence quality was generally low to very low. Among studies involving health facility-based health care providers (HCPs), for "QIC only", effectiveness varied widely across outcome groups and tended to have little effect for patient health outcomes (median MES less than 2 percentage points for percentage and continuous outcomes). For "QIC plus training", effectiveness might be very high for patient health outcomes (for continuous outcomes, median MES 111.6 percentage points, range: 96.0 to 127.1) and HCP practice outcomes (median MES 52.4 to 63.4 percentage points for continuous and percentage outcomes, respectively). The only study of lay HCPs, which used "QIC plus training", showed no effect on patient care-seeking behaviors (MES -0.9 percentage points), moderate effects on non-care-seeking patient behaviors (MES 18.7 percentage points), and very large effects on HCP practice outcomes (MES 50.4 percentage points). CONCLUSIONS: The effectiveness of QICs varied considerably in LMICs. QICs combined with other invention components, such as training, tended to be more effective than QICs alone. The low evidence quality and large effect sizes for QIC plus training justify additional high-quality studies assessing this approach in LMICs.
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.
PURPOSE: The purpose of this paper is to explore the way "hybrid" clinical managers in Kenyan public hospitals interpret and enact hybrid clinical managerial roles in complex healthcare settings affected by professional, managerial and practical norms. DESIGN/METHODOLOGY/APPROACH: The authors conducted a case study of two Kenyan district hospitals, involving repeated interviews with eight mid-level clinical managers complemented by interviews with 51 frontline workers and 6 senior managers, and 480 h of ethnographic field observations. The authors analysed and theorised data by combining inductive and deductive approaches in an iterative cycle. FINDINGS: Kenyan hybrid clinical managers were unprepared for managerial roles and mostly reluctant to do them. Therefore, hybrids' understandings and enactment of their roles was determined by strong professional norms, official hospital management norms (perceived to be dysfunctional and unsupportive) and local practical norms developed in response to this context. To navigate the tensions between managerial and clinical roles in the absence of management skills and effective structures, hybrids drew meaning from clinical roles, navigating tensions using prevailing routines and unofficial practical norms. PRACTICAL IMPLICATIONS: Understanding hybrids' interpretation and enactment of their roles is shaped by context and social norms and this is vital in determining the future development of health system's leadership and governance. Thus, healthcare reforms or efforts aimed towards increasing compliance of public servants have little influence on behaviour of key actors because they fail to address or acknowledge the norms affecting behaviours in practice. The authors suggest that a key skill for clinical managers in managers in low- and middle-income country (LMIC) is learning how to read, navigate and when opportune use local practical norms to improve service delivery when possible and to help them operate in these new roles. ORIGINALITY/VALUE: The authors believe that this paper is the first to empirically examine and discuss hybrid clinical healthcare in the LMICs context. The authors make a novel theoretical contribution by describing the important role of practical norms in LMIC healthcare contexts, alongside managerial and professional norms, and ways in which these provide hybrids with considerable agency which has not been previously discussed in the relevant literature.
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.
This study aimed to describe the foundations for quality of care (QoC) in the Mexican public health sector and identify barriers to quality evaluation and improvement from the perspective of the QoC leaders of the main public health sector institutions: Ministry of Health (MoH), the Mexican Institute of Social Security (IMSS) and the Institute of Social Security of State Workers (ISSSTE). We administered a semi-structured online questionnaire that gathered information on foundations (governance, health workforce, platforms, tools and population), evaluation and improvement activities for QoC; 320 leaders from MoH, IMSS and ISSSTE participated. We used thematic content and descriptive analyses to analyse the data. We found that QoC foundations, evaluation and improvement activities pose essential challenges for the Mexican health sector. Governance for QoC is weakly aligned across MoH, IMSS and ISSSTE. Each institution follows its own agenda of evaluation and improvement programmes and has distinct QoC indicators and information systems. The institutions share similar barriers to strengthening QoC: poor organizational structure at a facility level, scarcity of financial resources, lack of training in QoC for executive/managerial staff and health professionals and limited public participation. In conclusion, a stronger legal framework and policy dialogue is needed to foster governance by the MoH, to define and align health sector-wide QoC policies, and to set common goals and articulate QoC improvement actions among institutions. Robust QoC organizational structure with designated staff and clarity on their responsibilities should be established at all levels of healthcare. Investment is necessary to fund formal and in-service QoC training programmes for health professionals and to reinforce quality evaluation and improvement activities and quality information systems. QoC evaluation results should be available to healthcare providers and the population. Active public participation in the design and implementation of improvement initiatives should be strengthened.
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.