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Measuring the Performance of Health Workers
facilities attracts patients who are sicker and more likely to experience bad outcomes. This means that comparing outcomes across facilities will be misleading. Differences in case mix have several implications for performance measurement. First, the measurement and comparison of quality is made more difficult because the appropriate professional behavior may differ across health workers and health facilities. Thus, even if health workers do the same jobs, their performances might not be equal. If differences in patients are observable to the researcher, it might be possible to adjust for difference in case mix by ensuring that quality is compared for similar patient groups. Unobservable differences may still create problems, though. One way to eliminate this problem is to “create” an artificial patient and investigate how health workers would deal with this patient. As explained later, there are several ways of doing this, but all methods have certain drawbacks. Second, the comparison of productivity is made difficult because some patient groups require more time and other resources. One health facility may have served fewer patients per health worker because the patients were sicker and required more intensive care. Standard productivity measures will not account for such differences unless the patients are registered as different types of patients. Thus, the “solution” is more fine-grained categorization of outputs, reflecting different resources requirements. But there are clearly limits to how far this strategy can be developed.
Impact of Observation It is necessary to measure the quality of the process to properly measure quality overall. This usually requires the observation of health workers while they are providing services. But being in the presence of a health worker while they perform their tasks can alter their behavior. In many cases, this change does not have significant consequences, but in others it means that what is actually being measured is not what is set out to be measured. Being observed is likely to change the behavior of health workers, particularly when there are underlying standards for quality care. Such effects are commonly referred to as Hawthorne effects. When health workers know what they are supposed to do, additional scrutiny can lead them to attempt to meet these standards even when they do not routinely make this attempt. At least four types of changes are possible. First, if health workers know they are being observed at the moment they are performing the task, they can improve their performance. Thus the measured performance will exceed the normal performance. It is also possible that health workers will find out they are being observed after they have performed the activity and will alter their behavior in anticipation of being observed again. In this case, the first observation is an accurate picture of behavior, but the subsequent ones are measures only of the altered behavior. This can happen, for example, with repeated attendance checks; health workers cannot retroactively be present for the first visit, but they can choose to attend more frequently after the first visit in anticipation of future visits. Health Labor Market Analyses in Low- and Middle-Income Countries http://dx.doi.org/10.1596/978-1-4648-0931-6