Introduction

CHAPTER 3

Quality of Care: A Framework for Measurement

Introduction

Effective coverage has two components: the first is the coverage rate for a given service, and the second is the quality of care provided as part of the provision of that service. This chapter delves into the second component, quality of care, and the role that it plays in driving health outcomes in low- and middle-income countries (LMICs). Specific to the effective coverage framework introduced in the previous chapter, this chapter unpacks the relationship between the correct treatment rate and the quality of care. Increasing access to health services may not translate into better health outcomes if the quality of the services delivered is poor. Indeed, despite gains in coverage, health outcomes remain strikingly poor in most LMICs (Kruk et al. 2018; Benova et al. 2018; Das, Hammer, and Leonard 2008). A study of maternal deaths in 137 LMICs found that of an estimated 207,000 excess deaths in 2016, 57,000 were likely due to the receipt of poor quality of care, whereas an estimated 47,000 deaths were attributed to lack of access to care (Kruk et al. 2018).

Poor quality of care is often related to poor adherence to protocol by health workers (Das, Hammer, and Leonard 2008), but as this chapter discusses, low health worker effort is only one reason for poor quality. Disentangling the contribution of the various constraints to quality is important for understanding why quality is poor and whether an intervention, say performance pay for health workers, would have the scope to make a significant improvement in clinical quality and thus effective coverage. If poor effort only constitutes a minor constraint to quality and most such constraints are outside the locus of control of the health worker, then performance pay–type interventions may have limited impact on effective coverage.

This chapter discusses how poor clinical quality may arise for at least three reasons. First, structural constraints may continue to be a limiting factor, preventing health workers from providing adequate care. Second, inadequate training may result in health workers not knowing what they should do when presented with a patient. Third, health workers may not put their knowledge to use in their clinical practice; that is, they may not apply sufficient effort. Ibnat et al. (2019) cast these three constraints into a three-gap framework, where poor health outcomes can be the consequence of a can-do gap, a know-do gap, and a know-can-do gap or idle capacity. Although there may be other barriers to the provision of highquality care, including absenteeism, the decomposition of these three constraints is important because it helps in understanding the need for financial incentives as a policy lever. For instance, pay for performance might motivate health workers, but if the constraints are primarily structural, then infrastructure investments might be the more effective instrument. Similarly, if inadequate medical training leads to poor provider knowledge, performance-based incentives may have a limited impact on outcomes. Chapter 4 further illustrates this point by providing an empirical example, using data on antenatal care consultations in five Sub-Saharan African countries.

Given the importance of a systematic assessment of clinical quality for both research and policy, this chapter summarizes various approaches to measuring quality of care that are used in academic research. Collecting health care quality data in a comprehensive, cost-effective, and unbiased manner is a well-documented and persistent challenge. The chapter highlights measurement methods that can distinguish provider effort from provider knowledge or competence. For instance, the purpose of the financial incentives on which this report focuses is to increase provider effort, whereas knowledge gaps may be best addressed with training. The report also argues for collecting basic cost measures as a complement. Chapter 7 returns to the question of quality measurement and discusses how to integrate quality metrics into health system reform and the design of effective performance incentives.

While many of the examples in this report focus on the provision of high-quality antenatal care, the patterns discussed here are not unique to antenatal care provision. A study that evaluated the quality of care in 25 LMICs found that 58 percent of febrile children under age five who were seen as patients received poor quality of care for suspected malaria (Macarayan, Papanicolas, and Jha 2020). Similarly, a cross-sectional