Determinants of Health Insurance Choices

Determinants of wellness indemnity ChoicesCHAPTER ONEINTRODUCTIONBackground to the Problem health rush financing in ontogenesis countries remain a policy issue with few countries able to spend the $34 per capita recommended by the World health Organisation as minimum extremity for basic swellness worry. Lack of financial resources to adequately meet the increasing drive for health divvy up fates of the African population remain a persistent line of work, and is becoming more critical in the context of increasing incidences of non- communicable diseases.Consequently, there pitch been attempts by African judicatures to explore different methods of health c atomic number 18 financing. The 2005 World health Assembly encouraged its member states to move towards achieving commonplace bilkage. Universal coverage does not only relate to generation of health care notes but implies law in access and guaranteed financial gamble protection. As it is the desire of entirely countries to move towards a formation of universal coverage,6 it is argued that irrespective of the source of financing for the health system selected, pre wages and pooling of resources and risks arbasic principles in financial-risk protection. Further recognition of the importance of universal coverage for countries led to the WHO proposing the 2010 World Health writing to address financing for universal health coverage (UHC).Since independence, one of the overall clinicals of the government of Kenya has been to promote and improve the health status of Kenyans. This objective is motivated by the evidence that investing in health produces positive outcomes in human capital that live long term impacts in the overall socio-economic development of a country (World Bank 1993 Mwabu 1998). In a number of government policy documents and in successive National Development Plans, the government has set forth that the planning of health services should be available, accessible and affo rdable to those in most need of healthcare (sessional paper No. 10 of 1965 KHPFP, various Development Plans). divergent health financing policy initiatives have been on a lower floor(a)taken in Kenya, all aimed largely at addressing affordability and access to health care services. Universalist free health for all policy saw a rapid blowup of the healthcare infrastructure, particularly in the 1970s and 1980s, and advances in health and loving indicators. During this period, health financing system was supported primarily via general tax revenue. With the growing population and worsening socio-economic and political factors, a severe crisis of health and kindly development unraveled in the nineties (UNDP 2002). As a result of the crisis, the governments objectives and commitments to free healthcare provision for all eroded dramati bodey forcing it to implement a cost-sharing turning away in 1989. User fees were abolished for outpatient care in 1990, inspired by concerns about social justice, but re-introduced in 1992 because of budgetary constraints. Today, these fees have remained, with their impact on access to health care the landing field of several empirical studies. The user fee system was significantly altered in June 2004, when the Ministry of Health stipulated that health care at dispensary and health centre take aim be free for all citizens, except for a minimal registration fee in government health facilities.Health financing in Kenya is characterized by a high out of pocket expenditure. The Annual Health Sector Statistics Report (2008), indicate that the out of pocket expenditure as a remainder of total expenditure stands at 36% while creation expenditure as a remainder of total health expenditure is 29% per cent. 31 per cent of the total health expenditure comes from the development partners while the private companies contribute 3%. This kind of scenario distinguishs access to health a big problem for the majority of the mint below t he poverty line that constitute about 45.9 per cent of the population. According to the 2007 Kenya Household Expenditure regard, 37.7% of Kenyans who were ill and did not seek care were hindered by cost. Health indemnity is emerging as the most preferred form of health financing mechanism in situations where private out-of-pocket expenditures on health are significantly high and cost recovery strategies affect the access to healthcare. The need for health redress in Kenya has been recognized by policymakers for sort of some time now, as exemplified by the establishment of NHIF in 1966 through with(predicate) an Act of Parliament. The most significant event in the recent past has been the governments chase in social health policy as a health financing method and its potential implementation in Kenya. The aim is to ensure equity and access to healthcare services by all Kenyans.Despite the recognition of the importance of health damages by the government, the number of people in Kenya enrolled in health indemnity policy schemes is low (KNBS, 2009). In view of this, there is need to carry out a study on factors determining choice of health policy.Overview of Health Insurance in KenyaKimani et al (2004) put forward that health insurance in Kenya has been provided by both private and public systems. The main objective of the health systems has been to insure Kenyans over against health risks that they may encounter in future.The broad categories of health insurance in Kenya are as discussed belowPrivate healthcare InsuranceHealth insurance is considered private when the third party (insurer) is a profit organisation (Republic of Kenya, 2003a). In private insurance, people pay premiums related to the evaluate cost of providing services to them, that is, people who are in high health risk groups pay more, and those at low risk pay less. Cross-subsidy betwixt people with different risks of ill health is limited. Membership of a private insurance scheme is usually voluntary.Private health insurance has been offered by general insurance firms, which offer healthcare insurance as one of their portfolio of products. Therefore, their intention may be driven by the profit motive as business enterprises sooner that the pursuit to promote the general health of Kenyans.Wangombe et al (1994) identify two categories of private health insurance in Kenya direct private health insurance and, employment based insurance. Nderitu (2002) notes that direct private health insurance is very expensive and only the middle and high-income groups afford it In the employment-based plans, the employer provides care directly through employer-owned on site health facility, or through employer contracts with health facilities or healthcare organisations. These are both voluntary health schemes and are not legislated by the government.According to Techlink International Report (1999), few firms provide healthcare insurance in the strict sense of insurance in priv ate healthcare insurance in Kenya. The general insurance firms offering healthcare insurance as one of their portfolio of products include American Life Insurance Company (ALICO), Apollo Insurance, GMD Kenya, Kenya Alliance Insurance Company Ltd, and UAP Provincial Insurance. Other firms run checkup schemes and they are in two categories the starting signal category provides healthcare through own clinics and hospitals (these include AAR Health Services, Avenue Healthcare Ltd, Comprehensive Medical Services, Health Plan Services), while the other category provides healthcare through third party facilities (examples are Bupa International, Health Management Services and Health First International). These medical schemes are also known as Health Management Organisations (HMOs). HMOs are registered as companies under the Companies Act. The ideal originated in the US, where HMOs also help the government to disseminate preventive messages to the public. They were introduced in Kenya a decade ago in response to a 1994 Government call on the private sector to assist in medical care. HMOs are filling a vacuum left by the public health insurance scheme. In HMOs, the patient pays a fixed annual fee, called a capitation fee, to cover the medical cost. Members of a HMO must go to the doctors of that HMO. In addition, to see a specialist, their HMO family doctor must refer them. HMOs have grown rapidly especially in the last few years, especially among those who are cover by employer-provided health plans, mainly because they have helped contain cost increases.National Hospital Insurance neckcloth (NHIF)The NHIF was established by an Act of Parliament in 1966 as a department in the Ministry of Health, which oversaw its operations, but responsible to the government Treasury for fiscal matters. The Fund was set up to provide for a national contributing(prenominal) hospital insurance scheme for all residents in Kenya. The Act establishing the NHIF provided for the enrolm ent in the NHIF of all Kenyans between the ages of 18 and 65 and mandates employers to deduct premium from reward and salaries. Contributions and membership are compulsory for all salaried employees earning a net salary of Kshs. 1000 per month and above. The level of contribution is graduated according to income, ranging from Ksh 30 to Ksh 320 per month.The Fund covers up to 180 con hospital days per member and his/her beneficiaries per year. Besides being self-financing and self-administering, the Fund monitors its own collections and distributes benefits to providers. The NHIF Act also provides for the Fund to make loans from its reserves to hospitals for service improvement.Over the years, the original Act of Parliament has been reviewed to accommodate the changing healthcare needs of the Kenyan population, employment and restructuring in the health sector. The government restructured the NHIF Act in 1998 to make the Fund an autonomous parastatal. The apex of NHIF is no longer the Ministry but a Board of Directors. The Fund was given the task of alter as many Kenyans as possible to have access to quality and affordable healthcare against a background of rising medical costs and a dwindling share of resources.According to the amended NHIF Act, beneficiaries are both in-patients and outpatients ( member 22 of NHIF Act, 1998), but outpatient services are not yet operational. NHIF Management Board pays benefits to stated hospitals for expenses incurred at those hospitals by any contributor, his/her named spouse, child or other named dependant. According to the NHIF Act, the benefits payable from the Fund are limited to expenses incurred in respect of drugs, laboratory tests and diagnostic services, surgical, dental, or medical procedures or equipment, physiotherapy care and doctors fees, food and boarding costs (Republic of Kenya, 1999).Though the NHIF is meant to be a health insurance scheme subsequently the amendment of the NHIF Act in 1998, it is still a hospital insurance scheme since it only pays for inpatient services only. Currently, NHIF pays more than half of a typical inpatient bill in private-for-profit sector in urban areas. Although benefit rates have been increased since the onset of the cost-sharing programme, the Funds reimbursement levels remain a small proportion of the total costs of care in many for-profit facilitiesThe relevance of NHIF has been questioned in the light of access and affordability of healthcare for the poor, together with its coverage. It is for this reason that the Kenyan Government has proposed a scheme that is supposed to address fundamental concerns regarding equity, access, affordability and quality in the provision of health services in Kenya.National Social Health Insurance FundThe proposed mandatory social health insurance scheme, seeks to transform the NHIF into a National Social Health Insurance Fund (NSHIF) to provide health insurance cover to both outpatients and inpatients. The main o bjective of the Fund is to facilitate the provision of accessible, affordable and quality healthcare services to all its members irrespective of their age, economic or social status (Republic of Kenya, 2003b).It allow be compulsory for every Kenyan and every permanent resident to become a member through enrolment and payment of a subscription either monthly or annually, or as may be deemed convenient to different socio-economic groups. Subscriptions for the poor will be paid for with funds from the government and other sources.The current cost sharing fees will be replaced by pre-paid contribution into the new scheme. Some of the services that the members will enjoy under the new outpatient cover include general consultation with general practitioners prescribed laboratory tests/investigations drugs/medicines prescribed X-rays and ultra sound diagnosis treatment of Sexually genetical Infections (STIs) Treatment, dressing or diagnostic testing family planning ante-natal and post-na tal care clinical counseling services health and wellness education (Ministry of Health, 2004a)Statement of the ProblemHealth insurance is an institutional and financial mechanism which is seen as one option of obtaining additional resources for the financing of health care without deterring the poor and the vulnerable group from seeking care when they need it. It has the potential of generating secure funds for equitable health care. Governments funds so saved could then be diverted to the development and expansion of primary health care services and other infrastructure. It is a way of improving quality and access to health care as well as managing resources more efficiently.Health insurance helps dwellings and private individuals to set aside financial resources to meet costs of medical care in event of illness. It is based on the principle of pooling funds and entrusting management of such funds to a third party (government, employer or insurance company or a provider) that p ays for healthcare costs of members who contribute to the pool.Lack of health insurance promotes deferment in seeking care, non-compliance of the treatment regime and results in an overall poor health outcome (Hadley, 2002). equatorial diseases, especially malaria and tuberculosis have long been a public problem in Kenya. However, Beyond grappling with a persistent high burden of infective disease, including malaria, HIV/AIDS, and tuberculosis, Kenya faces an emerging chronic diseases problem characterized by increasing rates of cardiovascular disease, cancers, and diabetes. Since the 1990s some of Kenyas early achievements in health have begun to wrick Over the past two decades life expectancy has declined to 53 years, and mortality among children under the age of five has risen slightly.In Kenya, only about 10% of the population has some form of health insurance (KNBS, 2010 Republic of Kenya, 2009 Kinuthia, 2002). Coverage has remained the same since 2003. This implies that a hug e segment of Kenyans are still not covered hence the burden of paying bills lies with themselves or through fund raising. In addition, most of the insurance firms are located in urban areas where a square number of population can afford as compared to rural areas.With the current debate on the introduction of National Social Health insurance, there is need to examine the factors which affect individuals decisions of enrolling in health insurance scheme.Purpose of the StudyThe purpose of this study is to identify the factors that influence choice of health insurance among Kenyans. specialised ObjectivesTo evaluate socio-economic factors influencing choice of health insurance in Kenya.To determine the role of information on the choice factors of health insurance in Kenya.To determine how repair factor influences the choice of health insurance in Kenya.Make policy recommendationsChapter twoLITERATURE REVIEWTheoretical frameworkThe theory of demand for health insurance is based on exp ected utility theory ofThe standard economic theory of behavior under uncertainty is well known riskaverse individuals will pay to avoid severe financial consequences of the unfortunatestate of the world. In some markets, that willingness to pay to avoid risk leads to theexistence of dependant upon(p) contracts, or insurance markets. In the health insurance context,the unfortunate state of the world can be described as the event of illness or fear ofillness serious enough to require an individual or family to pay the full cost of necessaryand efficacious medical care solely out of current income or wealthiness. Risk averseindividuals facing actuarially fair prices will fully insure, but with unavoidable loadingcosts in the concrete world, individuals prefer incomplete insurance. The optimal degree ofcoverage in the face of loading costs is increasing in the degree of risk aversion.Ones degree or intensity of risk aversion to not having health insurance can bereasonably posited t o depend upon wealth (W), because the potential financial loss from ruinous illness is increasing in wealth, although after a very high threshold level ofwealth is r each(prenominal)ed, risk aversion may decline again education (ED), because moreeducated people know the consequences of not having insurance, they know thelikelihood of appropriate health care being efficacious, and they also may have moreconfidence that they can obtain efficacious care within any insurance and deliverysystem income (Y), because financial protection both of wealth and of current income or consumption streams is a normal good family status (FS), since parents andmarried partners may be more likely to seek coverage for family members whom theycare about and/or for whom they feel responsible other access to insurance(OTHER_ESI, ELIG), since the value placed on any particular insurance option may bedifferent if one is married to a worker whose employer offers coverage, or if some familymember(s) is(are) eligible for public insurance health status (HS) of everyone in thefamily sensed risk (RISK) to health status, increasing in age and other sometimesobservable clinical factors which we summarize with _, so that RISK = RISK(age,_)gender (SEX), since men and women have different health use profiles and then,contingent on a health shock that requires an intervention, ones aversion to the risk ofillness also depends upon expected expenditures (EX) and the variance of possibleexpenditures (_EX). These expenditure functions depend upon the quantity (C) andquality (q) of medical care that may be necessary (and efficacious) as well as theexpected price of each unit of that medical care (PC). Note, when it comes to riskaversion and demand for health insurance, the expected value of necessary medical careis not more classical than the variance of that potential demand or need for medical care,i.e., the upper bound of potentially required medical care affects demand. In other words,the first two moments of the health services utilization and expenditure distributionmatter, a priori, to insurance demand.We find it useful to think about an individuals demand for health insurancehaving two classes of arguments those that reflect influences on the subjective value ofinsurance coverage per se, and those that determine the net price to the consumer. Fromthe above, one may summarize the value of a particular package of health benefits, V(Bi),ERIU Working Paper 36asV(Bi) = V(W, ED, Y, FS, OTHER_ESI, ELIG, HS, RISK, SEX, EX(C,q,PC), _EX).Let the price of health insurance (to the individual) be P*. Health insurance demand for aparticular package of benefits is thenHId = 0 if V(Bi) HId 0 if V(Bi) _ P*.Thus we have the truism, people will be uninsurable if the value to them of the insurancebenefit package they can buy is less than the price they have to pay. We also note theobvious that those which value health insurance the most are likely to buy the most of it,conditional on a given price. This concept of V(B) is similar to Pauly and Herringsnotion of reservation price for health insurance (Pauly and Herring, 2002, forthcoming),and V(B) P* is similar to consumer surplus.An interesting feature of health insurance markets is that some of those with thehighest V(B) are also those most likely to make choices such as seeking jobs fromemployers that offer health insurance that lead them to find the lowest prices of healthinsurance (P*). Thus purchasers of insurance are likely to obtain substantial consumersurplus. Other people with high demand say those who expect to be very sick areunable to work. They often either qualify for public programs or end up facing very highprices in the private non-group insurance market, and sometimes can find no one willingto sell insurance to them at any actuarially fair price.3 Therefore, it is difficult to sustainthe interpretation that observed prices paid in health insurance markets reflect equipoise marginal subjectiv e values of having health insurance.my argument is that3Pollitz K, R Sorian, and K Thomas, How Accessible is Individual Health Insurance for Consumers inLess-Than-Perfect Health? Report to the hydrogen J. Kaiser Family Foundation, June 2001.buyers have CS, so nobodys marginal utility is revealed in these markets. I inserted anew CS sentence above.The arguments in our expressions of health insurance demand are useful forgeneral expressions of demand, but we also need to make clear that some eligible peopledo not enroll in insurance even though the monetary cost is zero . This would not seempossible from our characterization of health insurance demand. The important point isthat P* in our framework represents more than just monetary cost. P* includes time costand any disutility from an enrollment process that is perceived as burdensome orembarrassing (e.g. some say a kind of stigma is associated with Medicaid since it was forso long associated with people on cash assistance). We expl ain more in section 4 what isknown about the ways P* exceeds zero for various public insurance programs with zeronominal fees.2.2 SociallyEmpirical LiteratureKirigia et al (2005), using data from the 1994 South African Health Inequalities Survey (SANHIS) examined the family relationship between health insurance ownership and the demographic, economic and educational characteristics of South African women. Applying binary logistic regression technique, they found out that environmental rating, residence, smoking and marital status variables determined health insurance coverage.The 2002 Jamaican Survey of brio Conditions was used to flummox the determinants of private health insurance coverage. Bourne and Kerr-Campbell (2010), using logistic regression to estimate the determinants of health insurance coverage, found out that social standing, durable goods, income, marital status, area of residence, education, social support, crowding, psychological conditions, retirement benefits, living arrangements, the number of males in the household and good health determined health insurance coverage.Nketiah-Amponsah (2009) investigated the determinants of public health insurance among women aged 15-49 in gold coast using primary data collected in three districts in Ghana in 2008. Using the logit model the paper concludes that marital status, income, age, religion and access to television and newspapers are the most significant determinants of womens insurance coverage. In addition, health inputs like medical personnel and health infrastructure increase demand for health insurance and health care. Another study using primary data was conducted in Ghana by Sarpong et al (2010) to explore the association between socio-economic status and subscription to the Ghanaian National Health Insurance Scheme (NHIS). Applying logistic regression, they concluded that economic well being and distance to the closest health facility were important determinants of National health insuran ce coverage.Gius (2010), using data from the 2008 National Health Interview Survey (NHIS) estimated the logistic model for determinants of health insurance coverage for young adults. They posit that socioeconomic factors among them, age, sex, race, employment, area of residence, cost of insurance and beliefs held about health insurance are important in determining the health insurance coverage.In Malawi, Makoka et al (2007), based on a logistic regression found income and education as significant determinants of private health care where public health services are free. This study used primary data collected from Blantyre and Zomba cities in 2003.A working paper study by Bhat and Jain (2006) examined factors affecting the demand for health insurance in a micro health insurance scheme setting. EstimatingTakeuchi et al (1998) estimating the logistic model for factors associated with health insurance coverage among Chinese Americans in Los Angeles county found out that marital status, length of stay in the unify States, education, employment and household income were important factors determining health insurance coverage.Hopkins and Kidd (1992), utilizing data from the 1989-90 National Health Survey examined the socio-economic variables which influence the demand for health insurance under medicare in Australia using the binary logit model. They conclude that age, income, health status, material wellbeing and geographical location are important determinants of decision to purchase insurance.Owando (2006) carried out a study on factors influencing the demand for health insurance in Kenya. Using the probit model, they found out that age, self evaluated health status, marital status, income, level of educational attainment, household size, risk behavior and employment status were important determinants of health insurance ownership in Kenya.CHAPTER 3METHODOLOGYTheoretical FrameworkThis study borrows heavy from the demand theory. Health Insurance is treated just l ike any other good. Hence, demand for health insurance should be affected by variables such as price of the commodity, price of related commodities, income, tastes and preferences among others.The demand equation for health insurance is modeled as followsModel SpecificationThe decision to buy health insurance will be formulated in two interrelated choices. First, the choice is related to the decision to buy or not the health insurance. Since the unfree variable takes two forms, will use binary logit model to study this choice. Theory and previous empirical work (Kirigia et al ,2005 Bourne and Kerr-Campbell, 2010) suggest that the prospect that an individual owns a health insurance is conditional on several socio economic variables including age, education, area of residence, household size, occupation, marital status, health status among others.In this study, the relationship between the binary status variable and its determinants is specified as followsWhere are the following in helpless variables age, sex, marital status, area of residence, level of education, proxy measures for economic well-being (land ownership availability of electricity, characteristics of dwelling place), knowledge (access to radio, television and newspaper), household size, occupation, health status (HIV and Tuberclosis), cigarette smoking.The second step, if the decision to buy insurance is positive is to reduce attention to the types of health insurance, that is, community based health insurance, health insurance trough employer, social security and private health insurance. This can be handled by applying a polychotomous model, more in particular a multinomial logit model. This approach is justifiable because the categories refer to choices being made that are mutually exclusive.The regression model is expressed as followsData Sources and VariablesThe study will utilize survey methodology in which secondary data relating to the issue under investigation will be obtained from th e 2008-09 Kenya Demographic Health Survey (KDHS). This is a nationally representative sample survey of 8,444 women aged between 18-44 years and 3465 men aged between 15 and 54 years of age selected from 400 sample points (clusters) throughout Kenya. Data collection was done from the month of November, 2008 and February, 2009.Dependent and Independent variableThe dependent variable will be health insurance ownership. For purposes of coding the health insurance ownership outcome