Introduction

The performance of health systems is a fundamental determinant of population health. Many countries pay particular attention to achieving equity in the health care delivery system. To monitor equity in health services, a body of research used conventional utilization-based indicators; however, the indicators were criticized in that medical utilization may occur independent of need [1], [2]. As an alternative approach, direct measurement of unmet needs for health care has been used to complement the limitation of the utilization-based indicators. Stenvens et al. (1998) defined health care need as “the capacity to benefit from healthcare”; unmet needs occur where patients/individuals remain “non­recipients of beneficial healthcare interventions” [3].

In the last decade, measuring unmet needs for healthcare has been widely used to assess horizontal equity at both local and national levels [4], [5], [6], [7], [8], [9]. Studies have primarily focused on individual-level characteristics as influential factors on the unmet needs for health care [10], [11], [12], [13], [14], [15], [16], [17]. Whereas, there have been a few studies of unmet health needs focused on community-level variations, these studies were largely ecological and did not control for individual-level characteristics. The findings of the studies thus may be a reflection of the composition of communities, rather than an indication that the characteristics of the community themselves influence health care utilization. Examining the effects at the individual- and community-level simultaneously is enabled by multilevel analysis which is a statistically proper method to analyze hierarchically nested data structure.

Several studies have examined the relationship between individuals’ unmet needs for health care and community-level factors with the multilevel method. The studies suggested that regional low socio-economic status (SES) such as high rates of poverty and unemployment [18], [19], low levels of educational attainment within communities [18], [19], [20], social disruption [21], social capital [21], and the degree of urbanization [18], [21] may influence health status and hence the need for health care. In contrast to studies which focused on consumers’ utilization, some studies have examined supply-side factors (e.g. primary care physicians, dentists, psychiatrists) [18] or hospital beds [19], [21] and showed that they do not necessarily correlate with the level of unmet needs.

In South Korea, as in other countries, there are persistent indications of unmet needs in spite of the achievement of universal health care coverage in 1989. The studies in Korea have identified high levels of out-of-pocket payments in health care expenditure as a major cause of unmet needs in universal health care coverage [22], [23] and suggested improving limited benefit coverage to enable easier access to health care [7], [23], [24], [25]. On the other side, there was no ecological research to elucidate the effect of contextual level factors on regional unmet needs for health care in Korea. To our knowledge, there also has been no study to identify the individual- and contextual-level predictors of unmet needs for South Korean health care via multilevel analysis.

We sought to conduct a study to examine individual- and contextual-level predictors of unmet needs for health care in Korea by multilevel analysis. We hypothesize that contextual-level predictors may enable or impede the ability of individuals to meet their health care needs.

Methods

Results

Table 1 shows the prevalence of unmet needs for health care and distributions of health care resources per 1,000 residents across 16 regions. Overall, the private health care resources outweighed the public parts. Health care resources in private sectors took at least 75% out of the total national health care resources (regional range of beds: 74.9- 99.6%; physicians: 76.2%–97.7%). A preliminary analysis showed that there is a trend toward increasing beds in the private sectors as the prevalence of unmet needs rise (r = 0.117, p<0.0001); however, there is no statistical significance in correlations between the unmet needs and the public sectors.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 1. Prevalence of unmet needs for health care and distributions of health care resources in 1,000 residents across regions.

https://doi.org/10.1371/journal.pone.0051004.t001

Table 2 shows the distributions of predictors related to unmet needs for health care. Out of a total 7,200 individuals, 1,796 adults (24.9%) experienced unmet needs for health care. Females reported unmet needs at a higher rate than males. Adults who were either young or economically poor experienced more unmet need for health care. The prevalence of unmet need increased with lower levels of educational attainment. Married adults reported the lowest level of unmet needs.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 2. Prevalence of unmet needs for health care and characteristics of Korean adults.

https://doi.org/10.1371/journal.pone.0051004.t002

Table 3 shows the results of the two-level binomial logit models used to predict the probability of unmet need for health care. The results from the individual characteristics were consistent with the unadjusted results of Table 2. The lower value of -2log(likelihood), the better model; the model 3 is better than others. Of the contextual factors (model 3), the regions that had the highest number of hospital beds in the private sectors were associated with a higher prevalence of unmet needs (Figure 1). There was no statistically significant association between regional distribution of physicians and unmet needs for health care (model 2).

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Figure 1. Probability of unmet needs for health care across number of hospital beds in private sectors per 1,000 residents.

https://doi.org/10.1371/journal.pone.0051004.g001

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 3. Multilevel logistic regression estimates (along with their SE) based on two-level binomial logit models for unmet health care need of Korean adults.

https://doi.org/10.1371/journal.pone.0051004.t003

Discussion

The current study showed an inverse relationship between the number of regional hospital beds per 1,000 residents in private sectors and unmet needs for health care in Korea. Our most notable finding is that–net of individual-level characteristics–the experience of unmet needs was higher in regions with the highest level of private hospital beds per 1,000 residents. This contradicts previous studies, which reported a lack of association between supply of health care resources and unmet health care needs [18], [21] or a significant positive association, if any, with health care supply [19].

This is the first study to report the association between unmet needs and regional resources with regard to health care services in South Korea. The strength of our investigation is the simultaneous consideration of individual characteristics and area-level characteristics within a multi-level analytical framework [27]. Our findings prompt careful consideration of the unique history and evolution of policies which determine the supply of medical resources within the Korean health system. The government, at the introductory stage of health supply policies in 1970–80s, instead of investing in public health care sectors, stimulated the private sectors by providing financial subsidies and administrative supports to meet the people’s health care needs rapidly (at the same time increasing the numbers of medical schools and the entrance quota among private universities) [28], [29], [30]. Spurred utilization of medical services by the national health insurance program introduced in 1977, enabled many physician clinics to have inpatient facilities and hospitals which relied on out-patient services for profit by entrepreneurial physicians [28], [29]. In part due to government policies, the number of acute-care hospital beds per 1,000 capita grew to nearly double the OECD average; however, the number declined in all other OECD countries over time except Turkey [31]. In the 2000s, the private sector dominates the health care system in Korea while the role of the public sector is very limited–96% of hospitals and clinics are privately-owned and they account for 90% of beds while the proportion of public hospital beds are about 10% [32].

Moreover, due to ineffective regulations on private hospitals, the Korean health care delivery system has no mechanism for functional differentiation and referral arrangement across levels of the system [28], [29]. Under the supply overflow and the disorganized health delivery system, competition among private hospitals has intensified [28], [29]. As the revenue of most private hospitals is made up almost exclusively of patient care without philanthropic donations or government subsidy [29], they behave as for-profit entities notwithstanding their not-for-profit status in legal terms [29], [31], [32]. They compete through quality of medical services rather than price under the fee-for-service reimbursement scheme [29], [31], [32]. Competition based on quality translates to expansion of specialists, high-tech equipment, and reduced waiting times. The widening gap of quality medical services among hospitals spurred the excessive expansion of private hospital beds. In short, to win the “medical arms race”, private hospitals have competed to have more beds for more financing. They could easily induce the demand of uninsured services and charge higher prices for them than their public sector counterparts. As a result, the average length of stay is one and a half times longer than the OECD average [31]. Precedent studies from other countries and Korea were consistent with our claim that increased competition leads to high hospital costs [33], [34], [35], [36], [37]. In addition, these inefficient behaviors by the hospitals and the high level of out-of-pocket payment caused by low level of national health care coverage in Korea–amounting to 4.6% of household final consumption in 2007, the third highest in the OECD area [31]–has hindered an individual’s ability to meet their medical needs. Consequently, high competition in the regions where hospital beds in private sectors were overflowed has raised medical costs; thus, it might lead to more unmet needs reports by residents under the low level of national health care coverage.

Private hospitals’ creating needs might be another potential mechanism of the paradoxical result. In regions with higher private sector involvement, there might be more advertising and “want creation”, resulting in increased demand and a perceived need of health services. It might be implied that at least some part of the “unmet” need is actually “unnecessary” need (i.e. excessive and unwarranted demand). As some of the medical services were not affordable to some people in the community, perceptions of unmet need might be higher in communities where more private hospital beds exist. This dynamic has certainly been documented when there is an over-supply of physicians, i.e. lots of unnecessary procedures being carried out under a fee-for-service scheme [29], [31], [32], [33], [38].

Thirdly, the lower quality of medical services of public hospital physicians in regions where there is high competition among private hospitals might enhance unmet needs of the residents. The public hospital physicians who work in these regions may be frustrated, lowering their motivation and think about their job ad hoc or work without full activation [39], [40]. Experiencing relative deprivation from lower salary, insufficient medical resources, and poor circumstances compared to a private hospital, physicians might contribute to public hospital physicians’ lower quality of care, which leads to more unmet needs [39], [40], [41]. This potential strategy may enhance unmet needs which might have been covered via physicians in public hospitals, especially for poor individuals.

Reversely, private hospitals tend to be located and provide more beds where the unmet needs are greatest to respond to commercial opportunities. To exclude this possibility of reverse causality, we intentionally used healthcare provision dataset of one year prior to the KNHANES survey to model a one-year time lag. However, the additional beds provision to meet the unmet needs could be private hospitals’ a reasonable commercial response if the unmet needs in a region have persisted not to decreased.

We found no association between the contextual variables of hospital beds and physicians in public sectors and unmet needs. This may be a result of the exceptional lack of physicians in public sectors, which constitute less than 0.3 physicians per 1,000 populations, one of the lowest in the OECD countries [31]. With regard to individual characteristics, similar to previous work, we found that individuals who reported unmet needs were more socioeconomically disadvantaged than the general population. We confirmed that low income and education, and a marital status of either widowed or divorced were associated with a greater likelihood of reporting an unmet need for health care.

Limitations to this study should be noted. Firstly, the density of hospital beds might not be a representative variable considering growing non-hospital services such as ambulatory care services or same-day surgery. However, there has been no incentive such as global budgeting, diagnosis related group (DRG), which could encourage more same-day surgery in Korea, or to induce adequate medical utilization under the context that high proportion of uncovered treatment and majority of private hospitals behave for-profit. Secondly, the number of hospital beds and physicians per population has been used as representative variables for overall medical resources to correspond to the perceived unmet needs in Korea’s unique medical context [18], [21], [31], [42]. Moreover, we cannot estimate associations between health care provisions in regions and the unmet needs of specific health care services (e.g. in-patient services, out-patient services, mental health services, childcare services, and ambulatory care services) because the KNHANES survey does not ask about the kinds of unmet needs for medical services. Lastly, the technology status, another factor of medical resources, was not included in the analytic models due to the limitations of available data.

Despite the limitations discussed above, multilevel analyses on unmet needs for health care among South Koreans reveal several important insights. The policy for the allocation of health care resources in public sectors should execute specifically to the regions reporting high level of unmet needs in spite of a plethora of health care resources by the private sector in the regions. Policies such as purchasing private hospitals by regional governments and regional regulations for the quota of hospital beds could also be effective. In the long term, efforts to reduce the level of out-of-pocket payment and raise the coverage level of national health care insurance are needed for regional equity for health care access in Korea.