Multidimensional output, or multitasking, refers to situations in which the responsibilities of an individual encompass multiple activities or outputs that may require different types of skills to accomplish (Holmstrom and Milgrom, 1991). A hospital’s output includes many different components, such as managing a patient’s chronic illness, the timely and efficient diagnosis of a patient’s new symptom, counseling and advice on how to prevent illness, and emotional support.
Multitasking is relevant to P4P programs because the performance measures in these programs typically address only a narrow piece of a hospital’s outputs or the processes that contribute to outputs. For example, a program may measure the provision of aspirin for a patient with AMI but not other processes or outputs that are difficult to measure, such as diagnostic acumen for a patient hospitalized with unclear symptoms. It is hypothesized that if a large incentive is applied to one type of output, other outputs will be neglected, and overall care might worsen (Holmstrom and Milgrom, 1991). This reasoning is used to explain why few private-sector corporations put large fractions of employee pay “at risk,” making them dependent on measures of output for which only a small fraction of what contributes to output can be measured (Asch and Warner, 1996). A large financial incentive based on a narrowly focused set of measures may lead to the unintended consequence of having a hospital “teach to the test,” devoting resources to those things being measured and neglecting other important outputs that are not being measured.
There are several potential ways to overcome or minimize the problem of multitasking. One is to create an incentive program that addresses a broad array of a hospital’s outputs by applying a comprehensive set of performance measures. This approach has been taken by the primary care physician P4P incentive program in the United Kingdom, which has over 146 quality indicators covering clinical care for ten chronic diseases, organization of care, and patient experience (Doran et al., 2006). The challenge with this approach is to avoid creating a program that may be overly complicated and costly—absent efficient measurement tools. Another approach that employers in other industries have used is low-powered incentives (Asch and Warner, 1996). With this approach, the majority of an employee’s income is fixed, and only a small fraction is tied to an incentive. The incentive emphasizes the importance of the measured area but is not large enough to induce undesirable behaviors, such as gaming of the data to win or avoiding caring for sicker patients.