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Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary (2015)

Chapter: 5 Synthesizing Evidence, Identifying Gaps

« Previous: 4 Reviewing the Evidence for Different Quality Improvement Methods
Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
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5

Synthesizing Evidence, Identifying Gaps

Key Points Made by Individual Speakers

  • Outstanding clinicians are often tapped for executive positions in hospitals and provider networks, though little in their formal training qualifies them for management. Training health executives in management might make for leaders who are more receptive to quality improvement in health. (Ruelas)
  • There is a pronounced gap between what providers know and how they practice. Closing this gap probably depends on training and on involving the private sector. (Das)
  • The vast majority of strategies in the systematic review were tested only once or twice, often in studies with high risk of bias. Without more consistent attention to research questions, it will not be possible to build a convincing body of evidence on any strategy. (Rowe)
  • In the absence of clear treatment guidelines, market forces and patient demand will have a strong influence on provider behavior. Therefore, emphasis on the frontline health worker to improve quality might be misplaced. (Das, Heiby, Laxminarayan, Mor, Ruelas, audience member) • Discussions about quality would be eased by a common vocabulary of terms used to describe different strategies. (Rowe)

The second day of the workshop opened with brief welcoming comments from Sheila Leatherman. Then Enrique Ruelas of the Monterrey Institute of Technology and Higher Education gave the opening address. His comments broadened the scope of the discussion beyond the six methods,

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

setting the topic squarely within current policy debates about health equity and human rights. He stressed the importance of treating patients with dignity as a fundamental human right. Respectful treatment builds trust between patients and providers. Over time, this translates into wider use of services and better health.

The concept of health as a human right has been central to the recent discussion about universal coverage, and improving quality protects that right. Ruelas took issue with a point in the universal coverage discussion: the policy documents, particularly the ones released by the WHO and the Pan American Health Organization, do not reference quality beyond a cursory mention of “quality services.” While considerable attention is paid to questions of access, funding, professional training, and infrastructure, quality of care is neglected.

Ruelas also cautioned the audience against lumping low- and middle-income countries together, describing the differences among low-, lower-middle-, and upper-middle-income countries (see Table 5-1). Given the variability in the baseline health indicators and available funding, it seems wise to consider quality improvement strategies differently for each category.

In reflecting on the previous day’s discussion, Ruelas shared some of his experiences from working in quality improvement in Mexico. When he started in the mid-1980s, the country was in a financial crisis. There was some resistance to the idea of investing in quality when so many people had no access to services. Ruelas argued that the need for quality was greater precisely because so few people had access to services. He understood the concern that accreditation standards, for example, may seem unrealistically high in poor countries; he had felt the same way when responsible for oversight of accreditation in Mexico. Nevertheless, he saw a vicious cycle in lowering the standards or removing the items that seem too difficult to attain. Once a standard is taken out of consideration, the health workers

TABLE 5-1 Variability in Key Health Indicators by World Bank Income Group in 2013

Health indicator World Bank income group
Low Lower-middle Upper-middle
Life expectancy at birth (years)   62   66   74
Child mortality rate (per 1,000 live births)   76   59   20
Per capita spending on health (current US$)   36   88 479

SOURCE: World Bank, 2015.

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

will never reach it. He counseled the workshop audience to keep this in mind as they try to strike the difficult balance between setting achievable goals and encouraging progress.

Making progress at a large scale—moving beyond a single clinic or village to an entire district or hospital system—often requires the cooperation of the central bureaucracy, and good programs can help ensure this by empowering staff to work with the government. Ruelas acknowledged that sometimes this process is beyond the control of health staff. In government, central ministry staff may change with the administration, and the new political appointees might not share an interest in quality improvement. Even the best quality of care program can fail because of the larger political context.

Ruelas concluded with comments on the current gaps in quality of care programming. He discussed how to create an environment conducive to triggering change. Building such an environment takes years, he cautioned; it is not a matter of a few conversations with political leaders. In Mexico, they learned from a 1994 survey that people were unhappy with the quality of health services, but it was not for another few years that the national quality assessment data were available to substantiate these concerns. The national quality strategy came into place in 2000, in part because President Vicente Fox, the former Coca-Cola chairman for Latin America, understood the importance of quality control.

Data and political will are important for expanding quality programs, but Ruelas advised that these are not the only factors driving sustainability and scale. One interpretation of Rowe’s analysis is that combining certain strategies is more effective than using the same tools singly. This was consistent with Ruelas’s experience in Mexico, where the national quality strategy used 10 interventions. Using only one, he felt, would have been far less successful.

Along the same lines, Ruelas saw a gap between improving quality for the individual patient and improving the quality and efficiency of the overall system. Improving the systems means working with more than 10 clinics or 20 hospitals; the units of the intervention are an order of magnitude larger. Quality improvement at large scale requires clarity on the central message and a consistent incentive system. Scale also means involving the different networks. Diabetes patients, for example, are treated in primary care and occasionally hospitalized. Integrating quality work in hospital and primary care systems protects these patients from falling into gaps in the system.

Quality improvement, Ruelas explained, is ultimately about management, and a final gap he discussed was the training of managers. He observed that, in low- and middle-income countries, outstanding clinicians are often made chief executives of hospitals or put in charge of provider networks. The training and skills that qualify a clinician are different,

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

however, from those that make a good manager. It is not reasonable to expect that a retired clinician will have the same understanding of quality improvement and how to make changes as someone trained in management. Ruelas encouraged the audience to think more about how to provide essential management training to health executives.

The next session built on Ruelas’s comments, as the speakers continued discussing the evidence and gaps in it. Jishnu Das of the World Bank gave the first presentation. He described the overwhelming similarities among the six strategies being discussed: all are based around health services, depend greatly on context, and are labor-intensive. There is no randomized controlled trial establishing the effectiveness of any one of them, and the analysis of these methods raises questions about what constitutes quality of care.

Das encouraged the group to first clarify if quality of care is a policy or a product and, if policy is the question of interest, whether or not the policy is explicitly a health policy. The World Bank research suggests that changes outside of health—improving roads, for example—can drive more improvement in infant mortality than health interventions. Das then shared some research on improving the quality of primary care in India, summarizing work his group has been doing for the past decade.1

On average, India has about 4.4 health providers in each village. The vast majority (77 percent) have no formal medical training. Although unlicensed practice is illegal in India, 2011 estimates indicate that it accounted for 70 percent of the first contact with primary care in the country.

Research using standardized patients found that about 4 percent of patients get the correct treatment and no incorrect treatment; 40 percent of the time patients get the correct treatment plus another treatment, and 75 percent of the time patients receive at least one incorrect treatment (Das et al., 2012). Other research indicates that ignorance of proper treatment protocol is not the problem. Das described this tension as “the know-do gap,” a problem that has been documented in Canada, the Netherlands, Rwanda, and Tanzania, as well as India. When providers are presented with vignettes describing common problems such as diarrhea, unstable angina, and asthma, they respond with the correct treatment more than 80 percent of the time (see Figure 5-1). This is true regardless of whether they work in the public or private sectors, or even hold a qualifying medical degree. But when actual standardized patients present in their clinics with identical problems, 50 to 70 percent of survey providers give some other, incorrect treatment. The know-do gap shown in Figure 5-1 is most pronounced for the treatment of diarrhea: although on average 88 percent of providers

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1 Das presented ongoing work that he is doing in collaboration with Karthik Muralidharan and others.

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

image

FIGURE 5-1 The know-do gap in correct treatment by case among different types of providers in India.

NOTE: MBBS = Bachelor of Medicine, Bachelor of Surgery; SP = standardized patient.

SOURCE: © 2015 Das, Hammer, and Mohpal (unpublished), as presented in Das, 2015.

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

image

FIGURE 5-2 A review of clinic records 6 months after the standardized patient (SP) visits raised concerns about missing and erroneous information.

SOURCE: Analysis of MAQARI data by Aakash Mohpal and Jishnu Das (unpublished), as presented in Das, 2015.

know how to treat the condition properly, only 16 percent actually do.2 Beyond knowing that the prescribed treatment is incorrect, it is not clear in what way it is incorrect—that is, if the provider’s course of action would be properly classified as over- or under-treatment.

Auditing clinic records after presentation by standardized patients raises more concerns. Six months after the patient actors visited clinics, the investigators searched clinic records for the date of their visits using the patient’s reported name (see Figure 5-2). While 71 percent of the standardized patients were listed in the clinic records, only 32 percent had any symptoms recorded, and of those only 25 percent of the records showed the symptoms the patient actually reported. In one case, a patient with chest pains and symptoms of angina was recorded as having a headache. Das concluded that the records are, for practical purposes, erroneous and not a valid data source for managers.

It is difficult to know how to fix a problem of such scope. Das outlined some solutions, starting with involving the private sector. In India, private sector clinicians provide 80 to 90 percent of care; some of these providers have long experience and apprenticeship-style training, despite having no

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2 These figures come from ongoing work by Das, Jeffrey Hammer, and Aakash Mohpal.

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

recognized degree. Others he described as “orphans of government and donor projects,” often attempts at task-shifting programs. Targeting these providers is necessary, he said, but must be done for a reasonable cost. In Kenya, the government asked the World Bank to come up with a product that would cost $100–$125 per facility. In India, Das and his colleagues worked with a budget of $150 per provider.

Within this budget, the researchers randomly assigned 304 providers to receive an intensive training or to be in a control group (Das et al., 2015). The training, designed and implemented by the Liver Foundation of West Bengal, lasted 2 days per week, 4 hours per day, for 9 months; used multiple trainers and a variety of teaching methods; and covered multiple topics. Six months after the training ended, standardized patients were sent to all 304 providers to test the intervention’s effectiveness. They found that the training increased the likelihood of correctly treating a standardized patient by 7–8 percentage points over a baseline of 52 percent. Trained providers improved adherence to a treatment checklist by 4–7 percentage points over the baseline adherence of 27 percent. At the same time, there was no difference between trained and untrained provider groups on measures of over-treatment (e.g., over-use of antibiotics, polypharmacy,3 or injections). Das and his colleagues found that the improved services increased demand for care by two patients per day. At that rate, providers can recoup the cost of training in about 6 months.

The researchers also compared the trained private-sector providers to the public-sector, degree-holding providers in the same villages on various measures of quality (see Table 5-2). All informal private-sector providers spent more time with their patients, were less likely to prescribe antibiotics for asthma or myocardial infarctions, and were less likely to give unnecessary treatments or polypharmacy. However, trained public-sector providers were more likely to correctly diagnose and manage the patient’s condition; training the private-sector providers reduced that difference by half.

Das concluded that randomized controlled trials of quality programs can yield a wealth of information for policy makers. He also emphasized the value of involving the private sector, given that private providers are responsible for more than 80 percent of medical care in India. He argued that the costs of such programs, between $100 and $150 per provider, are sufficiently modest to allow for large-scale, sustainable implementation.

Nynke van den Broek of the Liverpool School of Tropical Medicine then gave a presentation on the quality gaps in maternal and newborn health. Indicators of neonatal and maternal health are the most disparate in the world, making maternal and neonatal health a litmus test for the strength of the health system. Despite having ample information about

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3 The use of four or more medications by a patient.

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

TABLE 5-2 Proportion of Providers Adhering to Various Treatment Guidelines in the Public Sector (PHC), Private Sector Non-Intervention (control), and Private Sector Intervention (treatment) Groups

  PHC Control Treatment
Checklist – all 0.202 0.273 0.313
Correct treatment 0.667 0.520 0.594
Average quality treatment 0.182 0.114 0.174
Correct diagnosis 0.182 0.136 0.188
Consultation length (minutes) 1.735 3.252 3.495
Gave antibiotics 0.667 0.477 0.480
Antibiotics (asthma and myocardial infarction) 0.636 0.331 0.332
Offered injection 0.045 0.011 0.019
Treatment – polypharmacy 2.758 2.162 2.208

SOURCE: © 2015 Das, Chowdhury, Hussam, and Banerjee (unpublished), as presented in Das, 2015.

what works to protect mothers and newborns, there is little information about how interventions could be effectively bundled together to improve quality.

Effectively combining essential interventions for pregnancy and delivery is one goal of the Liverpool School of Tropical Medicine’s Making It Happen program. The program aims to improve both the availability and the quality of obstetric and neonatal care. Quality improvement is supported using the audit method, which, though different from the six methods described at the workshop, has significant overlap with all of them. Van den Broek described audit as a way of asking questions. For example, it might ask, “why do mothers in this clinic die?” The audit method has a long history: a 1935 BMJ paper used the technique to estimate maternal mortality in Rochdale, near Liverpool, United Kingdom (Oxley et al., 1935). Audit has much in common with plan-do-study-act cycles; in audit, health workers gather information, review it, and make decisions based on it (see Figure 5-3).

Making It Happen makes use of audit and implementation research in the program’s 11 target countries. Researchers answer questions such as whether emergency obstetric training is more effective when given alone or in combination with other quality improvement methods. Project staff first defined quality and came to the conclusion that, “Quality of care is the degree to which maternal health services for individuals and populations increase the likelihood of timely and appropriate treatment for the purpose of achieving

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

image

FIGURE 5-3 The audit cycle.

SOURCE: van den Broek, 2015.

desired outcomes that are both consistent with current professional knowledge and uphold basic reproductive rights” (Hulton et al., 2000).

Edward Kelley4 of the WHO gave the last presentation of the session, joining via videoconference from Geneva. He echoed van den Broek’s point about the challenges of measuring the effectiveness of bundles of interventions, as well as Ruelas’s idea that the momentum for universal coverage will make quality questions even more important. Kelley emphasized the challenge of looking at quality in the context of health systems strengthening. Much as malaria and HIV programming has often taken too narrow a view of improving services, so has health systems research sometimes been too insular. He observed that health systems experts need to work closely with ministers of finance, a lesson that his work on Ebola has made imminently clear.

In the subsequent discussion, participants considered gaps in the research environment that might be holding back the field. Rowe pointed out that much of the information on quality improvement is hard to find,

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4 Much of Kelley’s presentation was not comprehensible to the Washington audience because of a bad videoconferencing connection.

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

a problem that could be corrected with a public data clearinghouse. Such a clearinghouse would allow researchers to know if and when certain strategies have been tried. It could be made more useful by setting out a taxonomy of different strategies to improve provider performance or quality of care. Currently, there is no universal classification for these methods. Even at the workshop, the method that some participants described as audit and feedback others called the plan-do-study-act cycle. A common vocabulary could do much to simplify the discussion and facilitate comparisons of similar methods.

Another major challenge facing implementation researchers is the need for repetition. Rowe explained that his group had combed through almost 500 studies and found more than 80 distinct strategies to improve provider performance. The vast majority of the strategies were tested only once or twice. Without more consistent attention to a research question, it is difficult to build a convincing body of evidence on the effectiveness of any strategy. But correcting this problem may require explicit incentives to repeat and replicate other groups’ work.

The relationship between frontline quality improvement and policy change is something many of the meeting guests had experience with. James Heiby explained that USAID’s primary interest is improving care on the front lines, often focusing on providers’ practices. Guests from the implementing organizations saw themselves as working both at the provider level (in clinics or hospitals, for example) and at the district and national levels, feeding policy makers with the information they need to change national guidelines.

In the absence of clear treatment guidelines, market forces and patient demand can have a strong influence on provider behavior. A few participants suggested that sometimes the provider tendency to give injections and prescribe unnecessary medicines is driven by the patient’s expectations; financial incentives may also play a role. Research from China has used the audit method to make a compelling point about financial incentives to over-prescribe antibiotics (Currie et al., 2014). Given the important influence that contextual factors, such as prescribing regulations, have on quality, some participants questioned USAID’s emphasis on the frontline health worker. Quality of care may depend on policy changes at a higher level.

Developing countries provide interesting examples of unregulated markets for health care. Das observed that the private, unregulated health market in India rewards perceived quality: providers who complete more of the clinical checklist charge significantly more than providers who do not. One problem is that, in many countries, there is no link between quality and wages in the public sector. The majority of public-sector health workers in India earn six times more than their counterparts in the private sector, a fact that is often obscured by high salaries at the top private hospitals.

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

Das mentioned an explosion in private medical schools in India, some of which are very poor quality and have instructors who rarely come to class. He described meeting students from these schools and asking them about their plans for the future. Many intend to open a private practice in a slum, then apply and re-apply for a government job. Working in an undesirable location makes them competitive for government work and, because the government cannot discriminate in wages, they would be guaranteed a good salary.

Some participants saw this as an example of how governments and donors need to look beyond the proximal good when setting policy. The initial effect of reimbursing public providers equally, without regard to the quality of their education, might have been positive, but over time, it has warped the market. Similarly, a quality improvement strategy put into place now, based on good proximal evidence, can change the equilibrium of a health system. Over years, after the system comes back to equilibrium, the changes may have different consequences than those immediately apparent. It might be beneficial for policy makers to try to anticipate these changes and consider how stress in one part of a system can affect other parts.

Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×

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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Suggested Citation:"5 Synthesizing Evidence, Identifying Gaps." National Academies of Sciences, Engineering, and Medicine. 2015. Improving Quality of Care in Low- and Middle-Income Countries: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/21736.
×
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Quality of care is a priority for U.S. Agency for International Development (USAID). The agency's missions abroad and their host country partners work in quality improvement, but a lack of evidence about the best ways to facilitate such improvements has constrained their informed selection of interventions. Six different methods - accreditation, COPE, improvement collaborative, standards-based management and recognitions (SBM-R), supervision, and clinical in-service training - currently make up the majority of this investment for USAID missions. As their already substantial investment in quality grows, there is demand for more scientific evidence on how to reliably improve quality of care in poor countries. USAID missions, and many other organizations spending on quality improvement, would welcome more information about how different strategies work to improve quality, when and where certain tools are most effective, and the best ways to measure success and shortcomings.

To gain a better understanding of the evidence supporting different quality improvement tools and clarity on how they would help advance the global quality improvement agenda, the Institute of Medicine convened a 2-day workshop in January 2015. The workshop's goal was to illuminate these different methods, discussing their pros and cons. This workshop summary is a description of the presentations and discussions.

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