Publications

    Nana Mensah Abrampah, Shamsuzzoha Babar Syed, Lisa R Hirschhorn, Bejoy Nambiar, Usman Iqbal, Ezequiel Garcia-Elorrio, Vijay Kumar Chattu, Mahesh Devnani, and Edward Kelley. 2018. “Quality improvement and emerging global health priorities.” Int J Qual Health Care, 30, suppl_1, Pp. 5-9.Abstract
    Quality improvement approaches can strengthen action on a range of global health priorities. Quality improvement efforts are uniquely placed to reorient care delivery systems towards integrated people-centred health services and strengthen health systems to achieve Universal Health Coverage (UHC). This article makes the case for addressing shortfalls of previous agendas by articulating the critical role of quality improvement in the Sustainable Development Goal era. Quality improvement can stimulate convergence between health security and health systems; address global health security priorities through participatory quality improvement approaches; and improve health outcomes at all levels of the health system. Entry points for action include the linkage with antimicrobial resistance and the contentious issue of the health of migrants. The work required includes focussed attention on the continuum of national quality policy formulation, implementation and learning; alongside strengthening the measurement-improvement linkage. Quality improvement plays a key role in strengthening health systems to achieve UHC.
    Svetlana V Doubova, Sebastián García-Saisó, Ricardo Pérez-Cuevas, Odet Sarabia-González, Paulina Pacheco-Estrello, Hannah H Leslie, Carmen Santamaría, Laura Del Pilar Torres-Arreola, and Claudia Infante-Castañeda. 2018. “Barriers and opportunities to improve the foundations for high-quality healthcare in the Mexican Health System.” Health Policy Plan, 33, 10, Pp. 1073-1082.Abstract
    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.
    Rohit Ramaswamy, Julie Reed, Nigel Livesley, Victor Boguslavsky, Ezequiel Garcia-Elorrio, Sylvia Sax, Diarra Houleymata, Leighann Kimble, and Gareth Parry. 2018. “Unpacking the black box of improvement.” Int J Qual Health Care, 30, suppl_1, Pp. 15-19.Abstract
    During the Salzburg Global Seminar Session 565-'Better Health Care: How do we learn about improvement?', participants discussed the need to unpack the 'black box' of improvement. The 'black box' refers to the fact that when quality improvement interventions are described or evaluated, there is a tendency to assume a simple, linear path between the intervention and the outcomes it yields. It is also assumed that it is enough to evaluate the results without understanding the process of by which the improvement took place. However, quality improvement interventions are complex, nonlinear and evolve in response to local settings. To accurately assess the effectiveness of quality improvement and disseminate the learning, there must be a greater understanding of the complexity of quality improvement work. To remain consistent with the language used in Salzburg, we refer to this as 'unpacking the black box' of improvement. To illustrate the complexity of improvement, this article introduces four quality improvement case studies. In unpacking the black box, we present and demonstrate how Cynefin framework from complexity theory can be used to categorize and evaluate quality improvement interventions. Many quality improvement projects are implemented in complex contexts, necessitating an approach defined as 'probe-sense-respond'. In this approach, teams experiment, learn and adapt their changes to their local setting. Quality improvement professionals intuitively use the probe-sense-respond approach in their work but document and evaluate their projects using language for 'simple' or 'complicated' contexts, rather than the 'complex' contexts in which they work. As a result, evaluations tend to ask 'How can we attribute outcomes to the intervention?', rather than 'What were the adaptations that took place?'. By unpacking the black box of improvement, improvers can more accurately document and describe their interventions, allowing evaluators to ask the right questions and more adequately evaluate quality improvement interventions.
    Anna D Gage, Margaret E Kruk, Tsinuel Girma, and Ephrem T Lemango. 2018. “The know-do gap in sick child care in Ethiopia.” PLoS One, 13, 12, Pp. e0208898.Abstract
    BACKGROUND: While health care provider knowledge is a commonly used measure for process quality of care, evidence demonstrates that providers don't always perform as much as they know. We describe this know-do gap for malaria care for sick children among providers in Ethiopia and examine what may predict this gap. METHODS: We use a 2014 nationally-representative survey of Ethiopian providers that includes clinical knowledge vignettes of malaria care and observations of care provided to children in facilities. We compare knowledge and performance of assessment, treatment and counseling items and overall. We subtract performance scores from knowledge and use regression analysis to examine what facility and provider characteristics predict the gap. 512 providers that completed the malaria vignette and were observed providing care to sick children were included in the analysis. RESULTS: Vignette and observed performance were both low, with providers on average scoring 39% and 34% respectively. The know-do gap for assessment was only 1%, while the gap for treatment and counseling items was 39%. Doctors had the largest gap between knowledge and performance. Only provider type and availability of key equipment significantly predicted the know-do gap. CONCLUSIONS: While both provider knowledge and performance in sick child care are poor, there is a gap between knowledge and performance particularly with regard to treatment and counseling. Interventions to improve quality of care must address not only deficiencies in provider knowledge, but also the gap between knowledge and action.
    Mark D Huffman, Padinhare P Mohanan, Raji Devarajan, Abigail S Baldridge, Dimple Kondal, Lihui Zhao, Mumtaj Ali, Mangalath N Krishnan, Syam Natesan, Rajesh Gopinath, Sunitha Viswanathan, Joseph Stigi, Johny Joseph, Somanathan Chozhakkat, Donald M Lloyd-Jones, Dorairaj Prabhakaran, and Acute Coronary Syndrome Quality Improvement Kerala (ACS QUIK) in Investigators. 2018. “Effect of a Quality Improvement Intervention on Clinical Outcomes in Patients in India With Acute Myocardial Infarction: The ACS QUIK Randomized Clinical Trial.” JAMA, 319, 6, Pp. 567-578.Abstract
    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.
    Lisa R Hirschhorn, Rohit Ramaswamy, Mahesh Devnani, Abraham Wandersman, Lisa A Simpson, and Ezequiel Garcia-Elorrio. 2018. “Research versus practice in quality improvement? Understanding how we can bridge the gap.” Int J Qual Health Care, 30, suppl_1, Pp. 24-28.Abstract
    The gap between implementers and researchers of quality improvement (QI) has hampered the degree and speed of change needed to reduce avoidable suffering and harm in health care. Underlying causes of this gap include differences in goals and incentives, preferred methodologies, level and types of evidence prioritized and targeted audiences. The Salzburg Global Seminar on 'Better Health Care: How do we learn about improvement?' brought together researchers, policy makers, funders, implementers, evaluators from low-, middle- and high-income countries to explore how to increase the impact of QI. In this paper, we describe some of the reasons for this gap and offer suggestions to better bridge the chasm between researchers and implementers. Effectively bridging this gap can increase the generalizability of QI interventions, accelerate the spread of effective approaches while also strengthening the local work of implementers. Increasing the effectiveness of research and work in the field will support the knowledge translation needed to achieve quality Universal Health Coverage and the Sustainable Development Goals.
    Tsion Assefa, Damen Haile Mariam, Wubegzier Mekonnen, and Miliard Derbew. 2017. “Health system's response for physician workforce shortages and the upcoming crisis in Ethiopia: a grounded theory research.” Hum Resour Health, 15, 1, Pp. 86.Abstract
    BACKGROUND: A rapid transition from severe physician workforce shortage to massive production to ensure the physician workforce demand puts the Ethiopian health care system in a variety of challenges. Therefore, this study discovered how the health system response for physician workforce shortage using the so-called flooding strategy was viewed by different stakeholders. METHODS: The study adopted the grounded theory research approach to explore the causes, contexts, and consequences (at the present, in the short and long term) of massive medical student admission to the medical schools on patient care, medical education workforce, and medical students. Forty-three purposively selected individuals were involved in a semi-structured interview from different settings: academics, government health care system, and non-governmental organizations (NGOs). Data coding, classification, and categorization were assisted using ATLAs.ti qualitative data analysis scientific software. RESULTS: In relation to the health system response, eight main categories were emerged: (1) reasons for rapid medical education expansion; (2) preparation for medical education expansion; (3) the consequences of rapid medical education expansion; (4) massive production/flooding as human resources for health (HRH) development strategy; (5) cooperation on HRH development; (6) HRH strategies and planning; (7) capacity of system for HRH development; and (8) institutional continuity for HRH development. The demand for physician workforce and gaining political acceptance were cited as main reasons which motivated the government to scale up the medical education rapidly. However, the rapid expansion was beyond the capacity of medical schools' human resources, patient flow, and size of teaching hospitals. As a result, there were potential adverse consequences in clinical service delivery, and teaching learning process at the present: "the number should consider the available resources such as number of classrooms, patient flows, medical teachers, library…". In the future, it was anticipated to end in surplus in physician workforce, unemployment, inefficiency, and pressure on the system: "…flooding may seem a good strategy superficially but it is a dangerous strategy. It may put the country into crisis, even if good physicians are being produced; they may not get a place where to go…". CONCLUSION: Massive physician workforce production which is not closely aligned with the training capacity of the medical schools and the absorption of graduates in to the health system will end up in unanticipated adverse consequences.
    Hannah H Leslie, Donna Spiegelman, Xin Zhou, and Margaret E Kruk. 2017. “Service readiness of health facilities in Bangladesh, Haiti, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Uganda and the United Republic of Tanzania.” Bull World Health Organ, 95, 11, Pp. 738-748.Abstract
    Objective: To evaluate the service readiness of health facilities in Bangladesh, Haiti, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Uganda and the United Republic of Tanzania. Methods: Using existing data from service provision assessments of the health systems of the 10 study countries, we calculated a service readiness index for each of 8443 health facilities. This index represents the percentage availability of 50 items that the World Health Organization considers essential for providing health care. For our analysis we used 37-49 of the items on the list. We used linear regression to assess the independent explanatory power of four national and four facility-level characteristics on reported service readiness. Findings: The mean values for the service readiness index were 77% for the 636 hospitals and 52% for the 7807 health centres/clinics. Deficiencies in medications and diagnostic capacity were particularly common. The readiness index varied more between hospitals and health centres/clinics in the same country than between them. There was weak correlation between national factors related to health financing and the readiness index. Conclusion: Most health facilities in our study countries were insufficiently equipped to provide basic clinical care. If countries are to bolster health-system capacity towards achieving universal coverage, more attention needs to be given to within-country inequities.
    Tsion Assefa, Damen Haile Mariam, Wubegzier Mekonnen, Miliard Derbew, and Wendimagegn Enbiale. 2016. “Physician distribution and attrition in the public health sector of Ethiopia.” Risk Manag Healthc Policy, 9, Pp. 285-295.Abstract
    BACKGROUND: Shortages and imbalances in physician workforce distribution between urban and rural and among the different regions in Ethiopia are enormous. However, with the recent rapid expansion in medical education training, it is expected that the country can make progress in physician workforce supply. Therefore, the aim of this study was to examine the distribution of physician workforce in Ethiopia and assess the role of retention mechanisms in the reduction of physician migration from the public health sector of Ethiopia. METHODS: This organizational survey examined physician workforce data from 119 hospitals from 5 regions (Amhara, Oromia, Southern Nations Nationalities and Peoples Region [SNNPR], Tigray, and Harari) and 2 city administrations (Addis Ababa and Dire Dawa City). Training opportunity, distribution, and turnover between September 2009 and July 2015 were analyzed descriptively. Poisson regression model was used to find the association of different covariates with physician turnover. RESULTS: There were 2,300 medical doctors in 5 regions and 2 city administrations in ~6 years of observations. Of these, 553 (24.04%) medical doctors moved out of their duty stations and the remaining 1,747 (75.96%) were working actively. Of the actively working, the majority of the medical doctors, 1,407 (80.5%), were males, in which 889 (50.9%) were born after the year 1985, 997 (57%) had work experience of <3 years, and most, 1,471 (84.2%), were general practitioners. Within the observation period, physician turnover among specialists ranged from 21.4% in Dire Dawa to 43.3% in Amhara region. The capital, Addis Ababa, was the place of destination for 32 (82%) of the physicians who moved out to other regions from elsewhere in the country. The Poisson regression model revealed a decreased incidence of turnover among physicians born between the years 1975 and 1985 (incident rate ratio [IRR]: 0.63; 95% confidence interval [CI]: 0.51, 0.79) and among those who were born prior to 1975 (IRR: 0.24; 95% CI: 0.17, 0.34) compared to those who were born after 1985. Female physicians were 1.4 times (IRR: 1.44; 95% CI: 1.14, 1.81) more likely to move out from their duty stations compared to males. In addition, physicians working in district hospitals were 2 times (IRR: 2.14; 95% CI: 1.59, 2.89) more likely to move out and those working in general hospitals had 1.39 times (IRR: 1.39; 95% CI: 1.08, 1.78) increased rate of turnover in comparison with those who were working in referral hospitals. Physicians working in the Amhara region had 2 times (IRR: 2.01; 95% CI: 1.49, 2.73) increased risk of turnover in comparison with those who were working in the capital, Addis Ababa. The probability of migration did not show a statistically significant difference in all other regions (>0.05). CONCLUSION: The public health sector physician workforce largely constituted of male physicians, young and less experienced. High turnover rate among females, the young and less experienced physicians, and those working in distant places (district hospitals) indicate the need for special attention in devising human resources management and retention strategies.
    Mohammed K Ali, Kavita Singh, Dimple Kondal, Raji Devarajan, Shivani A Patel, Roopa Shivashankar, Vamadevan S Ajay, AG Unnikrishnan, Usha V Menon, Premlata K Varthakavi, Vijay Viswanathan, Mala Dharmalingam, Ganapati Bantwal, Rakesh Kumar Sahay, Muhammad Qamar Masood, Rajesh Khadgawat, Ankush Desai, Bipin Sethi, Dorairaj Prabhakaran, Venkat KM Narayan, Nikhil Tandon, and Nikhil Tandon. 2016. “Effectiveness of a Multicomponent Quality Improvement Strategy to Improve Achievement of Diabetes Care Goals: A Randomized, Controlled Trial.” Ann Intern Med, 165, 6, Pp. 399-408.Abstract
    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.

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