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ECONOMY OF GHANA NETWORK UNIVERSITY OF GHANA

ECONOMY OF GHANA NETWORK UNIVERSITY OF GHANA. TOPIC : DISCRETE CHOICE EXPERIMENT APPROACH TO THE ANALYSIS OF UPTAKE OF THE NATIONAL HEALTH INSURANCE SCHEME AND INSURANCE AWARENESS IN THE TAMALE METROPOLIS BY WILLIAM KOFI NKEGBE Date: 3 RD OCTOBER, 2014. PRESENTATION. BACKGROUND

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ECONOMY OF GHANA NETWORK UNIVERSITY OF GHANA

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  1. ECONOMY OF GHANA NETWORKUNIVERSITY OF GHANA TOPIC: DISCRETE CHOICE EXPERIMENT APPROACH TO THE ANALYSIS OF UPTAKE OF THE NATIONAL HEALTH INSURANCE SCHEME AND INSURANCE AWARENESS IN THE TAMALE METROPOLIS BY WILLIAM KOFI NKEGBE Date: 3RD OCTOBER, 2014

  2. PRESENTATION • BACKGROUND • PROBLEM STATEMENT • OBJECTIVES • RELEVANCE OF THE STUDY • SCOPE • METHODOLOGY • RESULTS • CONCLUSION AND RECOMMENDATIONS • APPRECIATION

  3. BACKGROUND In 2004, Government estimated that in five(5) years every resident of Ghana shall belong to a health insurance scheme that adequately covers him/her against the need to pay out of pocket at the point of use(cash and carry) to a defined package of acceptable quality health service (GoG 2004). • But as at June 2009, about 67.46% of the population of Ghana was on the NHIS (NHIA,2010). And active enrolment in the Tamale metropolis stood at 30% as at June 2013 (TMHIS, 2013)

  4. In considering the problem of non-achievement of the complete coverage objective of government; we take cognizance of Lancaster(1966), who stated that the utility associated with a good or service is made up of the utilities of its composing characteristics or attributes, and individuals valuations depend on those characteristics.

  5. Again, a recent study on assessing knowledge and attitude toward insurance in Ghana identified lack of awareness as a major challenge for insurance providers in Ghana (Ackah & Owusu, 2011). Knowledge and attitude of individuals towards insurance in general could have an important influence on their decision to either or not take up health insurance

  6. It is on this basis that performing a discrete choice experiment on uptake on the National Health Insurance Scheme and assessing the impact of insurance awareness on choice decision is necessary

  7. PROBLEM STATEMENT Since the inception of the NHIS, many successes have been chocked. • NHIS covers the entire country • Decoupling of children under 18 from parents enrollment • Free antenatal and postnatal health services • Expansion of facility providers on the scheme

  8. Expansion of health facilities • Commendations from the international communities, Etc . But we still have the problem of not able to achieve complete coverage as targeted.

  9. Some studies have been conducted on the NHIS in some districts of the Northern Region and other parts of the country. But these did not take into consideration the utility theory as stated by Lancaster (1966) and knowledge on insurance.

  10. That is to say: individuals have preferences with regards to their health insurance needs, which is determined, both consciously and sub-conscious, by a range of influencing factors. Also for the available range of health insurance alternatives, an individual will seek to obtain his/her most preferred alternative

  11. Again, the observation that knowledge, attitude and behavior of individuals toward insurance, are major challenges of insurance providers could have some significant influence on uptake on health insurance. These observations make the current study worthwhile

  12. Research Questions The foregoing discussion gave rise to the following questions: • What attributes of health insurance may influence respondents’ decision to take up health insurance and their individual contribution on choice? • Will exposure to insurance awareness education influence choice?

  13. OBJECTIVE • The study aimed at using the discrete choice experiment approach to evaluate the impact of the features of health insurance, and insurance awareness on ones choice to take up health insurance.

  14. RELEVANCE OF THE STUDY • The study will provide valuable insight into the health insurance preference of health service consumers. • Besides, it will help the National Health Insurance Authority (NHIA), and other private health insurance providers in their policy formulation towards the implementation of their mandate. • Also, it will provide basis for the application of Statistical techniques and other tools in eliciting preferences in health insurance and the impact of insurance awareness education has on it. • It will also be relevant in determining a way to predict uptake on health insurance schemes by fitting an appropriate model. • Through this we can identify polity interventions appropriate in addressing health financing and non-enrollment on insurance issues. • It will also add up to the available literature in the area of the study.

  15. Review of Related Literature • The techniques of estimating individual preferences have primarily emerged from a desire to understand consumer preferences for different goods and services and are founded on utility theory (Ryan et al, 2001) • Lancaster (1966) observed that the utility associated with a good or service is made up of the utility of its composing characteristics or attributes, and that individuals’ valuations depend on those characteristics.

  16. The preferences of the consumer are the fundamental description useful for analyzing choice, and utility is simply a way of describing preference (Varian, 2010). • According to Ryan et al (2012), DCE is a quantitative method for evaluating different factors that influence job choices. That DCE has recently emerged as a very attractive method for researchers and policy makers alike, since it provides qualitative information on the relative importance of various job characteristics that influence the job choices of health workers, as well as the trade-offs between these factors and the probability of take-up of defined jobs.

  17. In discrete choice experiments, respondents are asked to choose between hypothetical alternatives, where each alternative is described by a bundle of attributes. The theoretical foundation for discrete choice experiments is the random utility theory. Individuals are asked to state their preferences between hypothetical alternatives and are assumed to choose the alternative that provides the highest indirect utility. The utility yielded by an alternative is assumed to depend on its choice–specific attributes (Mangham, 2007).

  18. Discrete choice experimentation has been used successfully in a variety of disciplines to help solve different problems. Some of these disciplines include agriculture (Aizaki, 2012), environment and resource economics (Hoyos, 2010), transportation (Ben-Akiva & Lerman, 1985; Horne et al., 2005), health (Lancsar et al., 2013; Yi et al., 2011; Arana et al., 2006), welfare (Swait et al., 2004; Ryan et al., 2006) and employment preference (Mangham & Hanson, 2008). The application of discrete choice experimentation in this study will help determine if discrete choice experiments will be successful in policy formulation in the area of health insurance choices and the effect of insurance awareness on the choices made

  19. METHODOLOGY Study Area In the Tamale Metropolis • Capital of the Northern Region • Population of 371,351 (PHC, 2010) • It has about 53 electoral areas and over 150 communities, with over 100 been peri-urban or rural, most of which are far from the Tamale township • It has about 46 health facilities spread within the Metropolis. • Besides Agriculture, most indigenes engage in commerce or other indigenous traditional industry.

  20. The DCE Design Stages in conducting the DCE • Identification of attributes and assignment of levels • Experimental design • Development and administration of the survey (data collection) • Data input • Analysis and interpretation (Ryan et al, 2012)

  21. “Conjoint and choice experiments are popular research techniques that are used to study how consumers make preference evaluations and choice decisions. An experimental design provides the plan for running the experiment” (Kuhfeld, 2010). • A design is optimal if it is both balanced and orthogonal • A fractional-factorial design that is both balanced and orthogonal is called orthogonal array

  22. Attributes and levels • The attributes and levels were therefore chosen to fit a known orthogonal array to ensure that the design is optimal. .The study developed seven(7) attributes, each with two(2) levels, (ie. 27) to ensure optimal design The orthogonal array chosen for our seven-two level factors has eight runs (8 27) (Kuhfeld, 2005). This is both balanced and orthogonal, or at least nearly so (Kuhfeld, 2010).

  23. Attributes and attribute levels for health insurance benefit packages (HIP)

  24. Eight Choice Sets Generated from Orthogonal Design Facility in SPSS Conjoint Source: Study design output, 2013

  25. Choice set

  26. Sampling • Purposive sampling For choosing category of respondents • Respondent who were interviewed under the control group were randomly interviewed

  27. Sample size determination Literature on discrete choice experiment offer limited guidance on what forms an appropriate sample size, and reveals considerable variation in the number of individuals to be interviewed (Hanson et al, 2005). Hensher et al (2005) advised that there is no magic number, but one suspects that a total sample of fifty(50) individuals each with 16 choice sets and fully generic parameter specification for design attributes and noncontextual or covariate effects might just be acceptable. The study assumed simple random sampling with a normally distributed population (p). A total of 240 respondents (error bound of 0.05)

  28. Field Survey/ Data Collection Data was collected from two groups of respondents: • Control group • Treatment group The main instrument used was the questionnaire were administered face-to-face

  29. Data Entry and Analysis • Cspro 5.0 was used for data entry • Main-effect estimator in STATA version 12.0 was used to generate the probit model for choice analysis • Propensity scores for insurance awareness index.

  30. The Probit Model The probit model is based on the cumulative distribution function (CDF) of the normal distribution. • This then yields the model to be estimated as follows: where; • = choice, the dependent variable which equals 1 if package 1 is chosen, and 0 if package two is chosen; • = the alternative specific constant; • = premium (10-25); • = premium (26-50); • = insurance card in a week; • = insurance card in a month;

  31. = out-patient services which cover all facilities and services; • = out-patient services which cover specified services; • = in-patient services that include specialist services; • = in-patient services with some specialist services; • = maternity care that covers babies for three months; • = maternity care that covers babies for one month; • = emergency services that cover cost of ambulance/transportation; • = emergency services that do not cover cost of ambulance/transportation; • = insurance cover (covers children below eighteen years); • = insurance cover (individual cover); and • = error term.

  32. RESULTS

  33. Probit model on respondents’ choice of health insurance benefit packages Number of obs = 6720 LR chi2(9) = 3243.54 Prob > chi2 = 0.0000 Source: Survey data

  34. Impact of Insurance Awareness on Choice Number of obs = 6720 LR chi2(10) = 3304.39 Prob > chi2 = 0.0000

  35. All attributes have shown to have some influence in respondents’ choice decisions. However; • Higher premium will impede uptake • Increases/improvement in out-patient, in-patient, emergency services, and insurance cover will increase clients’ utility and hence increase uptake. • Out-patient services has the highest impact on the model, indicating their willingness to trade-off other benefits for it.

  36. Hence, respondents will prefer an insurance package with • Lower premium • Out-patient services at specified facilities • In-patient services that cover specialist services • Maternity care • Emergency services that includes transportation • Insurance package that covers children below 18 years. • It is also revealed that insurance awareness has significant impact on the choice probability of individuals.

  37. Conclusion • It can be concluded that DCEs are effective methods of assessing health insurance uptake as have been applied in other areas. • And that the individual attributes of health insurance packages available have influence on the choice decisions of prospective beneficiaries. • Also, insurance awareness education will effectively and positively influence decisions of clients or potential clients in choosing insurance packages.

  38. Recommendation • DCEs are robust and can be applied in many areas, especially in the study of preference for non-market goods and services. • The attributes and their impact revealed in the study should be considered in designing health insurance packages. • Besides, insurance awareness education should be promoted and vigorously embarked on to help enhance insurance awareness and uptake in Ghana, especially among the low-income population. • Also, in designing health insurance packages, the economic status of beneficiaries should be taken into consideration in fixing premium, since premium at a certain level will reduce uptake considerably. • Finally, it is recommended that further studies be conducted in this area using different designs of experiment, to assess the willingness to take-up insurance and the type of insurance package preferred among low-income population in the area.

  39. DEFINITION OF TERMS Health Insurance : insurance against the risk of incurring medical expenses among individuals. Discrete choice experiment: a quantitative technique for eliciting preference Attributes: benefits and cost of an alternative Decision-maker : the individual whose choice is under study. Insurance Awareness: a person’s behaviour, skills, knowledge and attitude.

  40. Some References • Ryan, M., Bate, A. et al. (2001), Use of Discrete Choice Experiments to Elicit Preferences’ Quality in Health 10(Supplement I): i55-i60 Ryan, M., Kolstad, R. J., Rockers, C. P., Dolea, C., (2012), How to Conduct a Discrete Choice • Experiment for Health Workforce Recruitment and Retention in Remote and Rural Areas: User Guide with Case Studies, WHO • Kuhfeld, W. F. (2005b), Orthogonal Arrays. http://support.sas.com/techsup/technote/ts723.html • Hensher, D. A., Rose, J. M., and Greene, H. W. (2005), Applied Choice Analysis, A Primer, Cambridge university Press, Cambirdge • Cochran , G. W. (1977). Sampling Techniques, 3rd Edition, Wiley Publications. 75-76 • Lancaster, K. (1966), A New Approach to Consumer Theory. Journal of Political Economy 74(2):132-57 • Lindsay J.M & Kara H (2008). Employment preference of public sector nurses in Malawi: results from a discrete choice experiment: Tropical medicine and International Health 13, 1433 – 1441

  41. APPRECIATION • Dr Isaac K. Baidoo • GIZ for funding my field survey • The GETFund • Economy of Ghana Network T o all of you God Bless You

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