For many developing countries, public health clinics constitute an important source of primary health care. However, in much of the developing world, doctor absenteeism significantly impedes public healthcare provision. Workers’ intrinsic incentive to perform may substitute for weak or deficient extrinsic incentives. There is much evidence that policies targeting extrinsic motivation, such as financial incentives, can increase health worker performance, but not for all workers or in all settings. For example, if a worker is more intrinsically motivated, extrinsic motivation may not be necessary. And, though intrinsic measures such as personality have been shown to predict performance in many domains, very limited evidence exists that these non-cognitive traits affect performance of public sector employees in developing countries. If this relationship between personality and job performance exists in healthcare service provision, understanding workers' distribution of personality traits may allow for better ex-ante predictions of the effects of a potential policy change, such as increased monitoring or increased information sharing through bureaucratic channels. Furthermore, establishing this relationship is one possible avenue for identifying new, effective policy options to combat absenteeism. And, these policies may be specifically useful in cases when extrinsic motivations are weak.
In the Punjab Province in Pakistan, small clinics are the primary source of healthcare available to rural populations. Led by doctors who manage subordinate staff, clinics provide out-patient services, neo-natal and reproductive care, as well as vaccinations. To monitor clinic quality, district health officials dispatch inspectors who, among other items, report whether or not doctors and associated staff are present at the time of an unannounced checkup. At district headquarters, an Executive District Officer (EDO) receives the reports of inspectors and is expected to make administrative decisions accordingly.
Researchers investigated which personality traits were strongest predictors of health worker performance. Using well-established personality tests (Big 5* and Public Sector Motivation, see table below) validated for the Pakistani context, 389 doctors, 101 health inspectors, and 33 senior health officials (Executive District Officers or EDOs) were surveyed from Punjab Province.
The study also sought to identify collusion between inspectors and clinics, in the form of health inspectors informing doctors ahead of inspections to guarantee attendance when reports were filed. If a doctor was absent during an independent assessment conducted by the experiment team yet reported as present during every official inspector checkup, collusion between the inspector and doctor was considered likely.
Finally, the experiment tested how administrators respond to information about clinic quality. All health inspection data collected via smartphones were aggregated for each clinic and presented to senior health officials on an online dashboard. To manipulate the salience of the information provided to these officials, clinics with three or more absentee staff were highlighted in red on the dashboard. Because this cutoff (i.e. three or more absences and two or fewer absences) was arbitrary and never communicated to officials, it can be used to understand the impact of information salience on decision maker performance. The responsiveness of officials to under-performing clinics was measured by assessing clinic staff attendance in a follow-up 15-45 days after a high-absentee clinic was ‘flagged’ in the online dashboard.
Results and Policy Implications
First, Big 5 characteristics and Public Sector Motivation positively predict doctor attendance and negatively predict whether doctors collude with inspectors to falsify reports. Personality traits are less strong predictors of inspector performance.
Second, smartphone monitoring has the largest impact on health inspectors with high Big 5 characteristics—a one standard deviation increase in the Big 5 index is associated with a 27 percentage point differential increase in inspections in response to increase monitoring.
Last, senior officials (EDOs) with high Big 5 characteristics are most likely to respond to a report of an underperforming clinic as measured by improved subsequent performance at the facility—one standard devision higher EDO Big 5 index is associated with an additional 40 percentage point reduction in doctor absence following an underperforming facility flag in treatment districts.
There are four central implications of these results. First, the degree of correlation between personality measures, doctor attendance, and the responsiveness of senior officials to actionable data on absence suggest that psychometric measures such as the Big 5 index could potentially provide useful diagnostics in public sector hiring, training, and promotion decisions. Second, this project’s experimental settings imply that improvements in performance may be achievable even in a system where everyone has the same weak incentives to work. Third, personalities are a major predictor of which officials will use actionable evidence in making policy decisions. Last, these results suggest that this heterogeneity in intrinsic motivation has material implications for service delivery, allowing for better selection and targeting of new policy interventions.
November, 2011 – December, 2012
|*Big 5||Perry Public Sector Motivation|
|Openness||Attraction to policymaking|
|Conscientiousness||Commitment to policymaking|
Callen, M., Gulzar, S., Hasanain, A., Khan, Y., Rezaee, A., (2013) Personalities and Public Sector Performance: Experimental Evidence from Pakistan. Working paper.
Photo Credit: Department for International Development. Mobile health clinic in Pakistan.