Technology for Identifying Willingness to Access Healthcare in Pakistan
The Technology for Identifying Willingness to Access Healthcare in Pakistan experiment is in progress. Please see the initial experiment proposal below:
Proposal: Technology for Identifying Willingness to Access Healthcare
Co-PIs: Musharraf R. Cyan , Dept of Economics, Mark W. Rider, Dept of Economics, and Elisabet Rutstrom, Dept of Economics and DBEL, RCB.
We propose a new technology for overcoming neglected barriers to accessing the formal healthcare system, namely an individual’s “willingness to access” the system. By identifying households with a greater willingness to access modern medical practices for prenatal care, it will be possible to target such households for interventions. As other households witness the benefits of treatment, the chances that they will emulate the early adopters will increase, thereby increasing the expected take-up rate of modern medical practices. This research project will provide an opportunity to understand the role of time preferenc
es, risk attitudes and perceptions of risk as determinants of the willingness to access modern healthcare systems for early adopters.
Our approach is unconventional because it goes beyond analyzing the biological mechanisms of health interventions and instead analyses the psychological, cognitive, and social mechanisms that influence an individual’s willingness to access the healthcare system. In our view, there are two sets of factors that together determine whether an individual accesses the healthcare system. One set consists of the objective factors that influence an individual’s “ability to access” the healthcare system, such as availability, proximity, and affordability of healthcare services (Ensor and Cooper (2004), Goudge et al. (2009), Irfan et al. (2011)). Government policies generally focus on managing these factors in order to increase healthcare take-up rates in a community. However, these policies are often met with limited success, particularly among rural households in developing countries. This study looks instead at the set of subjective factors that influence an individual’s “willingness to access” the healthcare system. In other words, even when modern treatments are affordable and otherwise easily accessible according to objective criteria, many people continue to rely on traditional and mystical practices (Troesken 2010).
The willingness to access new interventions depends on community-wide factors such as religion, culture, and other social norms, including stigma, and on more idiosyncratic factors such as fear, attitudes, and perceptions. We hypothesize that early adopters will be individuals and households who are less averse to risk; who are more patient in terms of the timing of benefits; and who can form accurate perceptions of health benefits and risks based on formal information. We will develop and test these hypotheses in a rural area of Punjab, Pakistan by focusing on one global health priority area, namely maternal and neonatal health. Only 53.5 percent of women in rural Pakistan receive prenatal care from a skilled provider, the rates are even lower in many areas, such as Baluchistan where it is only 30 percent. This has resulted in extremely high maternal mortality rates in Pakistan of 267 per 100,000 live births making it one of the six countries that account for more than half of global maternal deaths. In Punjab, the decision to seek prenatal exams is typically made by the husband (father), other male relatives in the household, and the mother-in-law rather than by only the expectant mother. Therefore, this study will target these key household members.
The scientific basis for this idea rests on identifying the building blocks of successful pathways to fostering more accurate perceptions of modern healthcare solutions. These pathways recognize the importance of demonstrated success in local communities, and they necessarily begin with early adopters of new medical practices. This study will focus on increasing our ability to identify early adopters.
The idea that risk and time preferences are related to demand for medical services has received increased attention lately. Horgby (1998) proposes that the traditional production models of health that originated with Grossman (1972) are deficient in that they neglect to account for risk and uncertainty. He suggests that optimal health seeking choices should be based on portfolio diversification, but does not offer any empirical evidence that they do. Others do offer empirical evidence of correlations between various risky behaviors and measures of risk attitudes, indicating that agents seem to trade off expected payoffs and risk in some way. Using stated preference tasks that rely on hypothetical consequences to measure financial risk attitudes, Barsky, Juster, Kimball and Shapiro (1997) find that risky behaviors such as smoking, drinking, and not owning health insurance are correlated with stated financial risk preferences. Lahiri and Song (2000) find a correlation between stated financial risk preferences and smoking initiation, and Dave and Saffer (2007) with alcohol consumption. Some contrary evidence also exists. Picone, Frank and Taylor (2004) found no relationship with demand for preventive medical tests, nor did Sloan and Norton (1997) with demand for long term care insurance. All of these studies are based on a stated preference approach where the financial risk is hypothetical, however. Holt and Laury (2002) show that there are significant differences in responses to financial risk when the consequences are hypothetical and real. A few studies have since used real consequences when measuring risk attitudes and relating these to risky behaviors. Anderson and Mellor (2008) report a significant negative relationship between risk attitudes and smoking, heavy drinking, obesity, and not using seat belts. Lusk and Coble (2005) find a similar relationship for the consumption of genetically modified foods. Harrison Lau and Rutstrom (2010) elicit both risk attitudes and discount rates using real consequences and relate these to smoking behavior in Denmark. They find that the relationship between smoking and attitudes is heterogeneous and give evidence of variations across gender and age. They report that smoking and non-smoking men do not have significantly different risk attitudes, but they do differ in discount rates. On the other hand, smoking women are more risk averse than non-smoking women, and they do not differ in discount rates. They also report that discount rates are higher for smokers than for non-smokers who are young (< 40) but not old
There is enough evidence of correlations between risky behaviors and risk and time preferences to justify our conjecture that such preferences will be correlated with antenatal care choices, which are also risky. First, there is a high mortality and morbidity risk during pregnancy and birth for the expecting woman, and also for the infant during and immediately after birth. Second, information and understanding of care options are limited, making the choice across such options a risky one. However, none of the empirical studies have tested such relationships on poor households in LDCs. There is, however, a rich literature that reports correlations between risk attitudes and technology adoption decisions in agriculture among poor farmers in LDCs. A review of the earlier literature is given in Feder Just and Zilberman(1985). Later studies seem to confirm these earlier findings. Bardhan, Dabas, Tewari and Kumar (2006) find considerable heterogeneity in risk attitudes among dairy farmers in Uttaranchal, India, and a strong tendency to adopt risk management techniques. Simtowe (2006) finds that risk averse farmers in Malawi are less likely to adopt fertilizer and hybrid maize. Liu (2011) reports that risk averse cotton farmers in China are inclined to delay adoption of new biotechnology.
An important determinant to antenatal and other health care decisions is the subjective beliefs about the efficacy of various methods. We therefore propose to elicit the participants’ subjective beliefs about a selection of care options, including both traditional and modern methods. Delavande, Giné and McKenzie (2011a,b) review the literature and propose a visual, simple method with hypothetical consequences. All the studies reviewed used hypothetical consequences, and we extend these methods to include salient incentives. We are not aware of any previous study that has used actual consequences in belief elicitations among poor households in LDCs.
The final piece of our approach is the reliance on social diffusion to increase the uptake of care in the community, once a critica
l level of early adopters has been reached. The idea that social learning contributes to growth and technology diffusion has played a prominent role in the literature on endogenous growth (Romer (1986), Lucas (1988), Aghion and Howitt (1998), and Acemoglu (2009)). These ideas are also present in the literature on urbanization and growth (Porter (1990), and Glaeser (1992) and in the literature on diffusion of agricultural technologies (Rogers (1995), and Bindlish and Evenson (1997)). Closer to the ideas that inspire us here is the literature that measures the importance of social learning at the individual choice level (Foster and Rosenzweig (1995), Bandiera and Rasul (2006), Munshi (2004), Duflo, Kremer, and Robinson (2006), Kremer and Miguel (2007), Bayer, Pintoff and Pozen (2009), and Conley and Udry (2010)).
We find support in the literature both for the idea that choices over traditional and modern technologies depend on risk and time preferences, and that diffusion of new technologies often depend on social processes. We believe that this is also the case for poor households in LDCs that make choices between traditional and modern health and medical treatments. This study proposes a test of the first part of this hypothesized process: the link between risk and time preferences and the adoption of modern neonatal care over traditional care.
SECTION II: Testing the idea
The experimental plan: We will test whether it is possible to reliably identify early adopters of new health and medical practices based on measures of individually held risk attitudes, perceptions of risk associated with various types of healthcare providers, and patience in valuing future benefits. We will give several choice tasks to volunteer participants in one Union Council in Kasur District of Punjab, where the participants will be the adult members of households that include either an expectant mother or a new-born child. There is a large literature in experimental economics on the design of choice tasks that can identify the attitudes and perceptions that concern us here, and how to analyze these data. This literature includes variations that are proven to work in developing countries with low literacy rates. Some adjustments to these instruments will have to be made to accommodate religious and cultural beliefs that are specific to the region in which this research will be conducted. We will include questionnaires regarding health seeking behavior with an emphasis on choice between formal/modern and informal/traditional providers as well as the extent to which choices are affected by the actions of neighboring households. We will work jointly with a local partner in Pakistan to recruit participants and to conduct the sessions. This institute has a proven track record of successfully working with many international aid agencies to conduct survey based studies in many areas of Pakistan.
Participants will include key decision-makers in each household: the expectant mother, the husband, and the mother-in-law. The budget assumes 100 women in the first trimester of their pregnancy and two other household members in the Union, resulting in a total of 300 participants. We will collect choice data to test whether measured risk attitudes, perception of risk across various types of healthcare providers, and patience in waiting are related to the propensity to adopt modern healthcare. We will also carry out a survey on the same participants that will collect a range of information on their care choices, their income and wealth, and other risky behaviors they may be engaging in. Future research will examine the number of early adopters that is required to generate a large enough demonstration effect to change behavior in a community using longitudinal surveys. It will also be necessary to test how robust these findings are to the specific regions in which the study was conducted. To verify the external validity of the findings of this study, extensions of the test to other parts of Punjab, then Pakistan, and finally other developing countries would be necessary. We plan to use this initial project as a demonstration of the approach and apply for further funding from 3IE and the Gates Foundation, among others.
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