ESRI Discussion Paper Series No.18

The Quality and Efficiency of At-Home Long-Term Care in Japan:

Evidence from Micro-level Data

By

Satoshi Shimizutani and Wataru Suzuki

December 2002

Economic and Social Research Institute Cabinet Office

Tokyo, Japan

The Quality and Efficiency of At-Home Long-term Care in Japan:

Evidence from Micro-level Data1

By

Satoshi Shimizutani and Wataru Suzuki

December 2002

Please address correspondence to:

Satoshi Shimizutani, Cabinet Office, Tokyo, Japan

Email: satoshi.shimizutani@esri.cao.go.jp

Wataru Suzuki, Osaka University, Osaka, Japan

Email: suzuki@osipp.osaka-u.ac.jp

1 This research originated in a study on Japan’s long-term care conducted by the Price Policy Division of the Cabinet Office. We thank to Koichi Hamada, Reiko Kanda, Koichi Kawabuchi, Shuzo Nishimura, Haruko Noguchi and Takashi Oshio for their comments. We also thank to Kaigo Roudou Antei Center for providing us valuable data. The views expressed in this paper do not necessarily represent those of the Economic and Social Research Institute or of the Japanese government.

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Abstract This paper evaluates the quality and efficiency of the at-home long-term care market in Japan, a market in which for-profit enterprises were allowed to enter after the introduction of the long-term care insurance in Spring of 2000. We take advantage of data from a unique self-conducted survey to compare the quality of services and efficiency of various types of providers with different ownerships, including for-profits, nonprofits and public-owned providers, and different lengths of operation. We present two major findings. First, contrary to the prevailing perception, there are no statistically significant differentials in the quality of services between for-profit and nonprofit providers. Although the non-profits have the advantages in qualification and experience of staff and provision of professional training, the quality of services provided by nonprofits is worse than that of the for-profit counterparts from a couple of perspectives. Second, our estimates on the cost function after controlling for quality of services demonstrate that the management of newer providers is more efficient than that of the older providers. We find that public-owned providers could not necessarily be more advantageous in efficiency than other providers under an “equal fitting” market and that there is no reason to believe that the for-profit providers were behaving opportunistically. In other words, our results indicate that the competition mechanism works effectively in the at-home long term care market and that free market policy contributes significantly toward improving the quality and the efficiency of the at-home long term care market in Japan.

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1. Introduction The long-term care service system for the elderly dramatically changed in Japan after the public long-term care insurance was enforced in Spring of 2000. Under the new insurance system, the long-term market was transformed to be more market-oriented. On the demand side, not only households in lower income classes but all insured eligible people are now entitled to receive necessary care services. Users are free to contract care services with any providers under the “contract system,” as opposed to the old “distribution system,” which provided no choice other than the care services determined by local governments. On the supply side, the most notable change in the market structure is that private providers, including for-profits, are now allowed to operate in the market. This drastic reform aims to stimulate the supply care services to satisfy the rapidly increasing long-term care services demanded by the expanding number of elderly in Japan. At the same time, this reform was also designed to improve the quality of services by introducing competition and to optimize the efficiency of the overall market by the participation of new or for-profit providers2. According to the Ministry of Health, Labor and Welfare (MHLW), the supply of care services obviously expanded after the reform3, which supports the assertion that the first target was accomplished. Nevertheless, few studies have examined the improvements in the quality and efficiency of Japan’s long-term care market, with the exception of Suzuki (2002), who insists that that the remaining two targets were not attained. One criticism of his study, however, is the timing of the survey. He uses a survey conducted in October 2000, soon after the public long-term insurance was implemented. His findings thus need to be tested again by a new data set collected after the market chaos instilled by the changes ends, and the system stabilizes. This paper takes advantage of new survey data to compare the efficiency and quality of services by different providers in the at-home long-term care market and to address a policy evaluation on the reforms after two years of operation. In the United States, dozens of studies have been done that compare the quality and efficiency of long term care services between nonprofit and for-profit providers. Japan, however, has few empirical studies on these topics because for-profit providers had not been permitted to participate in the long-term care markets for the elderly until two years ago. This paper makes the first effort to compare quantitatively the quality of services and efficiency between nonprofit and for-profit care providers in Japan, using data from a unique, self-conducted survey4.

2 See detailed discussions in Iguchi (2000). 3 For example, providers registered in WAM-NET have increased from 9,185 in April 2000 to 14,691 (60% percent up) in February 2002. 4 Suzuki (2002) performed the first comparative study of quality of services between nonprofit and for-profit providers.

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This paper is organized as follows. Section 2 provides a literature review on the quality and efficiency studies of the long term care services for the elderly. Section 3 describes the survey data used in this study. Section 4 compares the quality of services between nonprofit and for-profit providers after proposing a set of indexes to measure the quality of services. Section 5 discloses the gap in efficiency between newer and older, nonprofit and for-profit providers by estimating cost functions after adjusting for quality of services. Section 6 concludes. 2. Literature Review In this section, we provide a literature review on related studies to examine the quality of services and efficiency both theoretically and empirically. First, we review some theoretical studies. As regards the quality of services, Hansmann (1980) made a noticeable theoretical contribution to the study on equality of services in for-profit and nonprofit providers, which is well known as the “contract failure model.” This model suggests that for-profit providers in the medical care or long-term care market are very likely to behave opportunistically due to an information asymmetry between users and providers5. A solution to prevent this type of opportunistic behavior is to discourage participation of for-profit companies in the medical and long-term care market. This was the strategy that was actually adopted until 20006. On the other hand, the “non-distribution constraint,” a legal requirement for nonprofit providers that prohibit s them from distributing earned revenue, serves to mitigate opportunistic behavior7. It should be noted, however, that this is not the case when care service users could make an ex-ante evaluation about the quality of services. Some recent studies (Chillemi & Gui (1991), Aoki (1995)) argue that opportunistic behaviors could be prevented when purchases are made repeatedly and the market is sufficiently competitive (Hirth (1999)). Meanwhile, theoretical studies concerning the differentials in efficiency between nonprofits and for-profits have reached relatively broad agreement. Due to “attenuated property rights,” the managers of nonprofit enterprises and public organizations are not constrained to cut costs like the for-profits are (James & Rose-Ackerman (1986)). It should

5 To see the nature of the problem, suppose that consumers are unable to judge the quality of care until after they purchase it; they make the purchase only one time. Further, assume that there exists a continuum preference for different quality care among consumers, and that their willingness to pay exceeds the cost of providing the care. Then, to the extent that consumers cannot assure the quality of service, the incentive of profit-maximizing firms will be to provide only low-quality care to each type of customer, and to charge high prices (Holtman and Idson (1991)). Therefore, the contract failure model proposes that due to an information asymmetry, rational consumers will choose care services provided by nonprofit enterprises as a signal of quality. 6 See Yashiro (2000) for details. 7 Hansmann (1980) terms a “non-distributional constraint” on nonprofits, which prohibits the distribution of any earned profits to owners.

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be emphasized that the efficiency of nonprofits is not necessarily worse than that of the for-profits because the market conditions of the long-term care are different from that of a typical competitive market. In the United States, Tuckman & Chang (1988) observe the cost coverage of nonprofit and for-profit Medicare providers, since the payment method has been transformed into flat-rate reimbursement. In Japan, however, Nanbu (2000) argues that under the officially fixed service prices, providers of long-term care do not have sufficient motivation to minimize costs. Next, we turn to review some empirical works on the quality of services and efficiency in for-profit and nonprofit providers. Although many recent studies have examined the quality of services in the nursing home market for the elderly, they do not reach agreement on whether the quality of services provided by nonprofits would be better than that of their for-profit counterparts. Some studies, namely Weisbrod (1988), Ullmann & Holtmann (1985), Cohen & Spector (1996), Holtmann & Idson (1991), and Gertler (1989)), reported that nonprofits provide better service than for-profits in the nursing home market for the elderly, while other studies suggest no significant differentials in quality of service between those two kinds of providers (Nyman (1988); O'Brien(1983)). Moreover, studies by Gertler (1984) and Suzuki (2001) conclude that for-profit providers essentially offer better quality of services than the nonprofit providers. One reason why these empirical findings on quality of services are indefinite is that quality of long-term care could hardly be measured by a uniform index, such as the death or healing rate used in the study of quality of medical care. Thus, the diversity in measurement of quality of services might lead to different disputes on the quality of service in nonprofits and for-profits. For example, Weisbrod (1988) combines indexes such as degree of information disclosure to clients’ family, utilization of sedation, and family members’ satisfaction, as a comprehensive index of quality of services. Cohen and Spector (1996) employ staff intensity, and Holtman & Idson (1991) use staff experience as a measurement of quality of services. This inconclusiveness is also observed in the empirical studies of efficiency. For instance, Bishop (1980), Frech III (1985), Lee, Birnbaum & Bishop (1983), and Gertler (1992) discovered that nonprofits are relatively inefficient compared to for-profits, while Tuckman and Chang (1988) report that the differential was not significant. However, these studies have a serious defect in estimating efficiency: they do not control the effect of quality of service. These providers could produce different types of care—high quality at high cost or low quality at low cost. As a result, it is crucial to compare efficiency with a full consideration of quality of service8. Nyman & Bricker (1989), Fizel & Nunnikhoven (1992)

8 Gertler and Waldman (1992) and McKay (1988) suggest that the estimates based on cost functions could change substantially when adding some variables to stand for quality of service into the equations as explanatory variables.

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and Nyman (1988) are exceptions that compared efficiency, controlling for quality of services. All of these studies found that for-profits are more efficient than the nonprofits. 3. Data This study takes advantage of micro-level data from the Survey on Long Term Care Service (SLTCS)9, which was conducted by the Price Division of the Cabinet Office in November 2001. The overall sample is designed to be representative of the long-term care providers in Japan’s Kanto district. In the first stage, we checked the WAM-NET10 and constructed a complete list of at-home long-term care providers in the Kanto district, including Tokyo. In the second stage, 2000 providers are drawn from the list according to population weight in local government, where a provider operates by a random sampling procedure. In the third stage, we sent our questionnaire to 1941 providers11 by mail, and received responses from 442 providers. The response rate (22.8%) is a little low,12 probably because long-term care providers are generally busy in the season and other organizations tried to perform a similar survey for same care providers. Nevertheless, we have good reason to believe that the sample selection bias of our data is very small. Because of its sampling design, the distribution of providers by ownership is very similar to that of the census result conducted by the MHLW (Table 1)13. Our survey collected detailed data on (1) financial status (total expenditure, labor cost, rental cost, income, government subsidy, etc.); (2) service use (frequency and hours by each service category); (3) staff characteristics; (4) other attributes of providers (ownership, branch office, region, subsidiary business); and (5) a series of indexes of quality of service. Providers that have been running subsidiary businesses are required to report the related figures only concerning their at-home long-term care business. The descriptive statistics of the major variables employed in this paper are outlined in Table 2. 4. Comparison of Quality of Services Economists have not yet achieved agreement on an index to measure the quality of service in the long-term care market. In practice, however, some feasible measurement

9 Chief researcher of the project is Professor Shuzo Nishimura, Kyoto University. 10 WAM-NET is a search engine of long-term care providers run by the Social Welfare and Medicaid Agency. 11 We excluded 59 subsidiary companies from the samples. 12 A similar survey conducted by Wataru Suzuki and the Bank of Japan in 2001 had a response rate of 37.1 percent. 13 Nevertheless, samples employed in this paper are a slightly heavily distributed in the nonprofit providers.

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criteria of quality of services have been developed in Japan14. In this paper we combined these local criteria and propose an alternative comprehensive index for the assessment of quality of services. This comprehensive index includes 12 sub- indexes that are measured objectively and easily by each respondent. Moreover, every sub- index consists of four binary queries (1 point if yes, 0 otherwise). Hence, the highest possible is 48 points. Sub- index 1: Business management and maintenance l Does your establishment prepare its own service manual your staff? l Does your establishment hold seminars periodically to acquire care techniques? l Does your establishment require your staff to make a daily report of their jobs? l Does your establishment keep a detailed record of service contents or claims?

Sub- index 2: Staff management l Does your establishment prepare duty provisions for your staff? l Does your establishment give staff performance appraisals regularly? l Does your establishment manage a full follow-up for staff members after job rotation? l Does your establishment encourage staff members to acquire qualifications?

Sub- index 3: Provision of staff training l Does your establishment provide on-the-job orientation programs for new staff

members? l Does your establishment make staff members participate in professional training

programs conducted by local governments or outside organizations? l Does your establishment provide your own staff training regularly? l Does your establishment provide on-the-job training opportunities for your staff?

Sub- index 4: Qualification and experience of staff l Is the proportion of qualified staff15 higher than the sample average? l Is the proportion of staff with the qualification of social welfare counselor, welfare

caretaker, professional physical therapist (PT), or operational therapist (OT) higher than the sample average?

l Is the proportion of staff with more than five years experience as a home helper higher than the sample average?

l Is the proportion of staff with less than one year of experience as a home helper lower than the sample average?

14 For example, to make a third-party assessment of the quality of service, the city of Kobe, the city of

Yokohama, and Hokkaido Prefecture have designed their own sets of local criteria. 15 “Qualified staff” refers to those have at least a certified qualification of 2nd Band Home Helper.

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Sub- index 5: Service convenience l Can your establishment provide care service in the early morning? l Can your establishment provide care service in late night? l Can your establishment deal with emergencies? l Can your establishment provide services on holidays?

Sub- index 6: Customer-oriented policies l Does your establishment always visit customers’ homes and discuss at-home care

plans with them? l Does your establishment regularly communicate with the customer’s families for

consulting and receiving claims? l Does your establishment provide any support to encourage customers to live without

help? l Does your establishment employ knowledge of public health nurses, staff nurses, and

doctors for settling at-home care plans?

Sub- index 7: Information service and complaint processing system l Does your establishment set up a correspondence for counseling service for

costumers? l Does your establishment designate staff to process claims from customers? l Does your establishment promulgate its service content through brochures or home

pages on the web? l Does a customer have some tentative use of your services?

Sub- index 8: Protection of customer privacy l Does your establishment assign a specific administrator to keep records of service

use? l Does your establishment have a storage system in place to keep secure records? l Does your establishment have any legal requirements against disclosure of secrecy for

staff? l Does your establishment have any instructions for staff about the human rights of

clients? Sub- index 9: Handling of accidents and emergencies l Does your establishment reserve some regular doctors or cooperative medical

institutions for the customers? l Does your establishment provide any guiding manuals about accidents and

emergencies for staff?

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l Does your establishment have liability insurance? l Does your establishment assign specific staff to deal with accidents and emergencies?

Sub- index 10: Strategies toward hygiene and infectious disease l Does your establishment give regular instructions on prevention of infectious disease

to the staff? l Does your establishment set some disciplines about the uniforms of staffs? l Does your establishment employ any public health nurses or staff nurses to check the

health conditions of the customers regularly? l Does your establishment assign any staff members who are responsible for the

management of hygiene and prevention of infectious disease? Sub- index 11: Planning and transparency of the business l Does your establishment clarify the philosophy and strategies of the business in paper

documents? l Does your establishment publicize your business planning in paper documents? l Does your establishment release your budget planning in paper documents? l Does your establishment have any outside organizations or individuals who are

responsible for the audit of its financial reports? Sub- index 12: Clarity of contracting procedure l Does your establishment make formal contract documents for each deal of service

provided? l Does the document define the contract term and renewal provisions? l Does the document define the procedure and charges of cancellation? l Does the document refer to the amount of charge and deliver the receipt to the

customers?

In what follows, we compare the average quality of services between public and private providers. Table 3 employs the 12 sub- indexes listed above to present the mean scores by ownership of various types of providers. The ownership of at-home long-term service providers are categorized into the following three groups: for-profit providers, nonprofit providers, and public providers. More concretely, for-profit providers include business corporations, limited companies, private companies and individuals. Nonprofit providers consist of social welfare corporations excluding the social welfare association (“shakyo”), medical corporations, universal partnerships, cooperative associations, civil corporations (“zaidan” or “shadan”) and NPO organizations. Public providers include facilities by local government or the social welfare association (“shakyo”). Although we do not necessarily distinguish public providers from nonprofit providers, we believe it is better to differentiate

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these two kinds of providers in the at-home long-term care market in Japan because public providers could act quite differently from nonprofit private providers. We prepared two sets of scores to measure the quality of care service. The “total score” is calculated by simply adding up the obtained scores of each sub- index, and hence each query has been evaluated evenly. The “principle component score” is estimated by principle component analysis, where each index was evaluated with different weights16. “+” indicates that the score is significantly higher than for-profits providers while “-” refers to the reverse. First, we look at the total score. For-profit and nonprofit providers have an average score of 28.9 and 29.9 respectively. The average score of nonprofit providers is slightly higher than that of the for-profit ones, but the differential is not statistically significant. This is also the case for the principle component score. Nonprofit providers are dominant in “management and maintenance of service content,” “provision of staff training,” “qualification and experience of staffs,” and “planning and transparency of business,” but for-profits seem to be providing more “convenient” services, as is evident from the other sub- index. Furthermore, the quality of services supplied by public providers is significantly lower than that of for-profit providers both in the total score and the principle component score. Our results on the differentials in sub- indexes indicate that the services of public providers are worse than those of the for-profit providers in many items, such as “management and maintenance of service content,” “services convenience,” “information service and complaint procession,” “protection of customer privacy,” “handling accidents and emergencies,” “strategies toward hygiene and infectious disease,” and so on. Public providers have higher scores only in “qualification and experience of staffs” and “planning and transparency of business.” Table 4 presents a comparison of quality of services between newer and older providers. We define newer providers as those that participated in the at-home long term care business after 1999, one year before the launch of the public long-term care insurance system. The results report that older providers have a total score of 28.2, which is slightly lower than the counterpart score of newer providers (29.0). Nevertheless, newer providers have a significantly higher score in the principle component than do the older providers, and better scores in some sub- indexes, including “customers oriented policies,” “information service and complaint processing,” “protection of customer privacy,” “handling accidents and emergencies,” and “strategies toward hygiene and infectious disease.” Meanwhile, old providers have more qualified and experienced staffs. In sum, we present the following findings : (1) services of public providers are worse

16 We excluded index 4 (qualification and experience of staffs) from the principle component analysis because its loading factor (correlations to sub-index) is negative.

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than those of the nonprofits and for-profits; (2) there are no significant differentials in quality of services between nonprofit and for-profit providers; (3) newer providers possibly offer better quality of services than the older ones. However, what we discussed above is based on simple descriptive statistics; it is hard to figure out which factors are responsible for the observed differentials. For instance17, newer providers could seemingly supply better services simply because they include for-profit providers. Next, we compare the quality of services provided by different ownerships and operation length by estimating the following quality function.

uAGNXSQi

ii ++++++= ∑ ηρδγβα 0 (1)

where Q is the dependent variable that is the scores of each sub- index, the total scores, or the principle component scores. The explanatory variables include a nonprofit dummy (N=1 if nonprofit provider, 0 otherwise), a public provider dummy (G=1 if public provider, 0 otherwise) and a new provider dummy (A=1 if new provider, 0 otherwise). In addition, we also include number of staff (S) as a proxy of provider’s scale and a vector of other attribute variables X such as branch dummy, region dummy18, subsidiary business dummy19 that are likely to influence the quality of services. Equation (1) is estimated by OLS with a Huber-White Sandwich estimator of the variance, and hence the heteroscedasticity is adjusted to some extent. Table 5 highlights the estimated coefficients on the major explanatory variables. First, public provider dummy (G) is significantly negative for both the total scores and the principle component scores. Second, four public provider dummies in sub-indexes are also significantly negative, with the exception of “qualification and experience of staff.” Hence, our estimates indicate that the quality of services of public providers is relatively lower. On the other hand, the nonprofit dummy (N) is positive and significant both for the total scores and specific indexes such as “provision of staff training” and “planning and transparency of the business,” though it is not statistically significant in the result of the principle components scores. Moreover, the newer provider dummy (A) is positive and significant for the

17 Cross sectional distribution of providers by ownership and operation length is as follows.

For-profit Nonprofit Public

Newer 71% 56% 29%

Older 29% 44% 71%

18 Region dummies consist of three dummies, defined by the public long-term care payment system. 19 Subsidiary business dummies include eight categories: at-home assistance business, at-home bathing business, day care business, sales and lending of welfare equipment, food delivery business, short-stay business, medical facilities, at-home nursing, and rehabilitation business.

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principle component scores but it is not significant for the total scores. However, the impact of the new provider dummy on individual sub- indexes is not predictable ; we were thus not able to draw any clear conclusions. 5. Comparison of Efficiency In this section, we estimate cost functions to assess the efficiency of various types of providers using three types of cost functions: Cobb-Douglas cost function (eq. 2), Log-quadratic cost function (eq. 3) and Translog cost function (eq. 4).

uAGNQXYPCk

kkj

jji

ii ++++++++= ∑∑∑ ϕµηδγβαα lnlnln 0 (2)

uAGNQX

YYPPC

kkk

jjj

jjj

iii

iii

∑

∑∑∑∑++++++

++++=

ςϕµηρ

δγβαα 220 )(lnln)(lnlnln

(3)

∑∑∑

∑∑∑∑∑∑+++++++

++++=

mm

i kkiik

k llkkl

kkk

i jjiij

iii

uAGNQXYP

YYYPPPC

ςϕµµηρ

δγβαα

lnln

lnln21

lnlnln21

lnln 0

(4)

where 0,1 === ∑∑∑j

jkj

iji

i ρβα and jiij ββ =

The dependent variable is the log of total expenditure (lnC) of individual providers. The explanatory variables include the log of output ( lnY), which is embodied in the total hours of use of physical nursing care, house work assistance, and multiple services. The explanatory variables also include the log of factor prices (lnP), which are represented by the employee’s wage (labor cost / overall employment hours), and rental costs (rental costs / overall employment hours)20. In addition, other attributes of providers (X) such as branch dummy, region dummy, subsidiary business dummy, and years of operation are also included. Moreover, some variables to measure the quality of services such as the total scores and the principle component scores), nonprofit dummy (N), public provider dummy (G), and new provider dummy (A) are also included. These cost functions are estimated by OLS with

20 Major rental costs such as those paid for office space and equipment need to be compared in per-employee units.

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robust standard error, as we have done in the previous section. The results are reported in Table 6 (the total scores used as an index of quality of services) and Table 7 (the principle component scores used as an index of service quality). In all cases, the coefficients on output (lnY) and factor prices (lnP) are statistically significant and have the expected signs. On the other hand, the newer provider dummy is negative and statistically significant. In other words, newer providers are more efficient than older providers even after controlling for ownership effect and quality of services. This result is surprising because both newer and older providers must be able to afford fixed costs such as investing equipment, which should be cheaper or even zero for older providers21. Hence, the cost convergence hypothesis presented by Nanbu (2000) is not supported in the at-home long- term care market. Furthermore, the variable to stand for quality of services is positive, which implies that a tradeoff relationship could exist between quality and cost. Moreover, the dummy on the short-stay business is negative, and this result suggests that the scope of business may have a premium effect. On the contrary, the coefficients on the at-home bathing business dummy, at-home nursing, and the rehabilitation business dummy are positive and significant. As a result, the scope of business seems to not necessarily promote management efficiency. Unexpectedly, we observe that the public provider dummy is negative and significant in most cases in Tables 6 and 7. It is well known that public providers generally lack incentives to minimize costs; what we found is thus puzzling. We try to investigate further the differential of the cost structure between public and private providers. To figure out the inherent factors accounting for the public-private efficiency gap, Table 8 tabulates the share of “customers living nearby services centers,” proportion of part time helpers, rate of reliance on government subsidy22, and net utilization rate of long term care facilities respectively. The “customers living nearby service centers” refers to customers who can reach a service center within 30 minutes from their own homes or companies. Net utilization rate of long- term care facilities equals the share of hours to spend on total long-term care hours to total working hours of helpers. Table 8 reports that (1) public providers have a higher ratio of “customers living nearby service centers” (91.7 percent) than those of the for-profit providers (66.4 percent) and nonprofit providers (78.7 percent); (2) public providers have a higher rate of reliance on government subsidy and a lower proportion of part-time helpers than do the private providers; and (3) public providers have a higher net utilization rate of facilities than for-profit providers do. Now, we add these variables to additional explanatory variables. Table 9 reports selected parts of the new estimation results. The major findings are summarized as follows.

21 The coefficients on length of operation are negative and significant in equations 1,2,4, and 5. 22 Ordinarily, providers with a high rate of reliance on government subsidy could mean they have soft budget constraints and hence are relatively passive in stressing cost savings.

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First, the proportion of “customers living nearby service centers” significantly reduces costs and improves efficiency of management accordingly. Second, contrary to the prevailing perception, the effect of the higher proportion of part-time helpers is positive and significant 23. We have two hypotheses to explain this surprising result. The first hypothesis proposes that the cost-saving effect by employing more part-timers is already reflected in the coefficients on wage variables (lw,lw2). The second hypothesis suggests that employment of full-time helpers rather than part-timers could be more effective in saving labor costs because full time helpers are more capable to deal with accidents and emergencies. Third, the effect of the net utilization rate of facilities is positive and significant. This could be attributed to the fact that providers with a higher utilization rate offer services for customers who live far from service centers more frequently, which costs more. Finally, the rate of reliance on government subsidy seems to have no significant effect on cost differentials. It should be noted that the coefficient on the public provider dummy is no longer statistically significant in the new estimations reported in Table 9. As a result, the positive and significant effect of the public provider dummy on efficiency observed in Tables 6 and 7 should be misleading. In other words, it is not public ownership but the factors we examined above potent ially that lead to a significant effect on efficiency. In particular, two factors contribute to the seemingly efficiency of public providers: customers living nearby service centers and the proportion of part-time helpers. Public providers on average have a higher proportion of customers living nearby service centers essentially because they have acquired such customers before the start of the public long-term care insurance system. In short, public providers are not necessarily more efficient than other providers; what seems to be their relative efficiency may be simply be the result of their acquired benefits as earlier participants in the market.

6. Conclusion This paper evaluates the quality and efficiency of the at-home long-term care market in Japan, a market in which for-profit enterprises were allowed to enter after the introduction of the long-term care insurance in Spring of 2000. We take advantage of data from a unique self-conducted survey to compare the quality of services and efficiency of various types of providers with different ownerships, including for-profits, nonprofits and public-owned providers, and different lengths of operation. We present two major findings. First, contrary to the prevailing perception, there are no statistically significant differentials in the quality of services between for-profit and nonprofit providers. Although the non-profits have the advantages in qualification and experience of staff and provision of professional training, the quality of services provided by

23 Generally, part-time helpers are paid less than full-time helpers. Hence the proportion of part-time helpers should be negatively related with service costs.

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nonprofits is worse than that of the for-profit counterparts from a couple of perspectives. Second, our estimates on the cost function after controlling for quality of services demonstrate that the management of newer providers is more efficient than that of the older providers. We find that public-owned providers could not necessarily be more advantageous in efficiency than other providers under an “equal fitting” market and that there is no reason to believe that the for-profit providers were behaving opportunistically. In other words, our results indicate that the competition mechanism works effectively in the at-home long term care market and that free market policy contributes significantly toward improving the quality and the efficiency of the at-home long term care market in Japan. Further research should address such topics as how to promote equal fitting between public and private providers in the long-term care market, and whether to allow complete and unfettered entry of for-profits into the institutional care market, which is still prohibited in Japan.

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Holtmann, A.G. and T. Idson (1993), “Wage Determination of Registered Nurse in Proprietary and Nonprofit Nursing Homes,” Journal of Human Resources, vol.28, pp.l55-79

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17

Table 1 Distribution of providers by ownership%

Ownership Our survey MHWL

For-profit providersStock corporations, limited privatecompanies and individuals 40.1 41.1

Local public organizations 1.4 2.1

Social welfare corporations (excludingsocial welfare associations) 17.8 19.2

Social welfare associations 19.0 16.9

Medical corporations 5.5 9.9

Cooperative associations 4.7 4.9

Civil corporations 2.8 1.8

NPOs 7.9 3.3

Other organizations 1.0 0.7

100.0 100.0

Nonprofitproviders

Public providers

Sum

Note: The figures in the third column are calculated by the data of Survey on Long Term Care ServicePrice (SLTCS), and those in the fourth column are drawn from the census data conducted by Ministryof Health, Labor and Welfare in September , 2001.

18

Table 2 Descriptive Statistics

Obs. Mean Std. Dev. Minimum MaximumTotal cost (10,000JPY) 330 3339.245 14128.84 0 235900Labor cost (10,000 JPY) 329 2637.523 9407.77 0 143900Rental cost (10,000 JPY) 436 395.9977 3984.477 0 76702Overall income (10,000 JPY) 345 3562.919 14659.69 0 238300Government subsidy (10,000 JPY) 436 93.03899 498.7855 0 5931ln (Total cost) 330 6.883276 1.803306 -4.60517 12.37116Overall working hours of full time helpers per week 426 177.8662 328.8434 0 3640Overall working hours of part time helpers per week 426 405.4343 1935.499 0 37996Overall working hours of administrative staff per week 427 17.50585 78.6077 0 1200Overall working hours of nursing staff per week 427 17.08431 75.59009 0 1200Overall working hours of all staff per week 426 617.9718 2080.868 0 38416

Wage rate (income per hour) 318 4.146222 5.434532 0 42.66667

Rate of wage cost (labor cost per working hour) 407 0.5078188 3.521668 0 50.48809ln (rate of wage cost) 318 0.9740233 0.9856089 -4.60517 3.753652

ln (rental cost) 407 -3.391816 1.762788 -4.60517 3.921936

Overall utilization hours of physical nursing care per month -A 333 4049.282 17403.8 0 216650

Overall utilization hours of house work assitance per month -B 332 4684.831 17417.65 0 236850

Overall utilization hours of mulitiple services per month - C 332 6381.358 35316.82 0 569900

ln (A) 324 6.724366 1.664211 1.098612 12.28604

ln (B) 323 7.046112 1.658582 1.386294 12.37518

ln (C) 320 6.985084 1.721277 0.6931472 13.25322

Comprehensive index I of service quality (total scores) 432 28.6412 7.007352 3 43

ln (total score) 432 3.315429 0.3139353 1.098612 3.7612

Comprehensive index II of service quality (principle componentscores) 436 1.01E-07 0.9999999 -3.64372 2.13066

Length of operation 407 72.66585 106.7864 0 799

Subsidiary business dummy 1 (at-home assistance business) 436 0.7385321 0.439939 0 1

Subsidiary business dummy 2 (at-home bathing business) 436 0.1330275 0.3399946 0 1

Subsidiary business dummy 3 (day care business) 436 0.3211009 0.4674358 0 1Subsidiary business dummy 4 (sales and lending business ofwelfare equipment) 436 0.1330275 0.3399946 0 1

Subsidiary business dummy 5 (food delivery business) 436 0.1490826 0.356579 0 1

Subsidiary business dummy 6 (short-stay business) 436 0.1995413 0.4001147 0 1

Subsidiary business dummy 7 (medical facilities) 436 0.2087156 0.4068575 0 1Subsidiary business dummy 8 (at home nursing and rehabilitationbusiness) 436 0.0458716 0.2094468 0 1Branch office dummy 436 0.2568807 0.437415 0 1Dummy for special region 1 436 0.103211 0.3045838 0 1Dummy for special region 2 436 0.1513761 0.3588269 0 1Dummy for special region 3 436 0.146789 0.354302 0 1Proportion of customers living near services centers 409 7.660147 3.073352 0 10Rate of dependence on government subsidy 436 0.0347674 0.20019 0 3.640777Proportion of part time helpers 379 2.644158 6.158599 0 9.46667Net utilization rate of nursing facilities 405 6.26468 5.524687 0 10Dummy for newer providers 436 0.5619266 0.4967202 0 1Dummy for for-profit providers 436 0.3922018 0.4888022 0 1Dummy for nonprofit providers 436 0.3876147 0.4877655 0 1Dummy for Public providers 436 0.1995413 0.4001147 0 1

19

Table 3 Comparison of quality of services by ownership of the providers

Sub-index of quality of services For-profit providers

1 Business management and maintenance 2.83 3.00 + * 2.55 - **

2 Staff management 2.25 2.24 2.02

3 Provision of staff training 2.18 2.48 + *** 1.98

4 Qualification and experience of staff 1.76 1.97 + ** 2.26 + ***

5 Service convenience 2.60 2.24 - *** 1.98 - ***

6 Customer oriented policies 2.54 2.64 2.32

7 Information service and complaining processing system 2.32 2.38 1.87 - ***

8 Protection of customer privacy 2.43 2.45 2.10 - **

9 Handling of accidents and emergencies 2.81 2.82 2.09 - ***

10 Strategies toward hygiene and infectious disease 1.64 1.72 1.25 - ***

11 Planning and transparency of business 1.83 2.54 + *** 2.20 + ***

12 Clarity of contracting procedure 3.43 3.40 3.48

Total score 28.85 29.86 26.11 - **

Score of the principle component 0.036 0.174 -0.387 - **

Nonprofit providers Public providers

Note: On the right side of each score of for-profit and nonprofit providers, "+" implies that the score is significantly higher than that of for-profits,while "-" refers to the reverse. ***means 1% significant level, ** means 5% significant level, * means 10% significant level.

20

Table 4 Comparison of quality of services by length of operation

Sub-index of quality of services Older providers

1 Business management and maintenance 2.79 2.87

2 Staff management 2.13 2.23

3 Provision of staff training 2.23 2.27

4 Qualification and experience of staff 2.15 1.76 - ***

5 Service convenience 2.36 2.29

6 Customer oriented policies 2.37 2.68 + ***

7 Information service and complaining processing system 2.11 2.37 + ***

8 Protection of customer privacy 2.23 2.47 + ***

9 Handling of accidents and emergencies 2.56 2.74 + **

10 Strategies toward hygiene and infectious disease 1.54 1.63 + *

11 Planning and transparency of business 2.28 2.11

12 Clarity of contracting procedure 3.34 3.49

Total score 28.21 28.98

Score of the principle component -0.116 0.091 ### **

Newer providers

Note: On the right side of each score of for-profit and nonprofit providers, "+" implies that the score is significantly higherthan that of for-profits, while "-" refers to the reverse. ***means 1% significant level, ** means 5% significant level, *means 10% significant level.

21

Table 5 Estimation of service quality functions

coeff. t value coeff. t value coeff. t value

Case 1 Business management and maintenance 0.183 -1.37 -0.183 (-1.19) 0.041 -0.4 0.07Case 2 Staff management -0.097 (-0.63) -0.069 (-0.41) 0.139 -1.25 0.11

Case 3 Provision of staff training 0.318** -2.23 -0.096 (-0.58) 0.06 -0.55 0.09

Case 4 Qualification and experience of staff 0.205 -1.6 0.342** -2.24 -0.304*** (-3.07) 0.23Case 5 Service convenience -0.064 (-0.39) -0.554*** (-3.04) -0.257** (-2.05) 0.12

Case 6 Customer oriented policies 0.159 -1.11 -0.237 (-1.32) 0.275** -2.33 0.13

Case 7 Information service and complaining processing system0.076 -0.59 -0.368** (-2.42) 0.263** -2.56 0.09Case 8 Protection of customer privacy 0.136 -0.96 -0.105 (-0.62) 0.201* -1.77 0.05

Case 9 Handling of accidents and emergencies -0.058 (-0.5) -0.647*** (-4.79) 0.102 -1.12 0.13

Case 10 Strategies toward hygiene and infectious disease -0.073 (-0.61) -0.458*** (-3.71) 0.065 -0.74 0.13Case 11 Planning and transparency of business 0.808*** -4.53 0.245 -1.2 -0.039 (-0.28) 0.07Case 12 Clarity of contracting procedure 0.143 -1.2 0.138 -0.96 0.142 -1.48 0.10

Case 13 Total score 1.601* -1.76 -2.087* (-1.92) 0.593 -0.82 0.15Case 14 Score of the principle component 0.198 -1.59 -0.331** (-2.2) 0.163* -1.62 0.17

R2Nonprofit provider dummy Public provider dummy Newer provider dummyDependent variables

Note:(1) Estimations are based on the following equation: Q=a(0)+a(1)*S+a(2)*Nonprofitdummy+a(3)*public provider dummy+a(4)*New provider dummy+a(5)*branch dummy+a(6)*region dummy+a(7)multiplebusiness dummy+u where Q is the dependent variable which is the score of each sub-index (case 1 to 12), or the total scores (case 13), or the principle component scores (case 14).(2) This table highlights the estimated parameters of provider dummies only.(3) The equation in (1) is estimated by OLS with a Huber-White Sandwich estimator of variance, and hence the heteroskedasticity of residuals are adjusted to someextent.(4) ***means 1% significant level, ** means 5% significant level, * means 10% significant level.

22

Table 6 Estimation of cost functions with total score as an index of quality of services

t value t value t value

ln (Total utilization hours of physical nursing) -A 0.1305034 ** 2.41 0.2744461 1.03 0.66822 *** 2.71ln (Total utilization hours of physical nursing)^2 -0.0125307 -0.59 -0.0116364 -0.32ln (Total utilization hours of house work assistance)-B 0.1983239 *** 4.14 -0.5021995 ** -2.46 -0.9009475 *** -3.78ln (Total utilization hours of house work assistance)^2 0.0531557 *** 3.31 0.0635149 ** 2.38ln (Total utilization hours of multiple services) -C 0.1692487 0.75 -0.0365682 -0.17ln (Total utilization hours of multiple services)^2 0.1561639 *** 3.08 -0.0019616 -0.11 0.0171456 0.57ln (A)* ln (B) -0.0369205 -0.87ln (B)* ln (C) 0.0482346 0.98ln (C)* ln (A) -0.038126 -0.78ln (Wage) 0.5545788 *** 5.08 0.7015094 *** 5.54 0.6912696 *** 5.61ln (Wage)^2 -0.0708236 -1.42 -0.0548236 *** -4.21ln (Rental cost) 0.0040995 0.14 -0.0074053 -0.15 0.3087304 ** 2.5ln (Rental cost)^2 -0.002955 -0.32 0.0247214 *** 2.65ln (Wage)* ln (Rental cost) 0.0301022 * 1.88ln (A) * ln (Wage) 0.1770874 *** 3.36ln (B) * ln (Wage) 0.0086883 0.15ln (C) * ln (Wage) -0.1545696 ** -2.41ln (A) * ln (Rental cost) 0.0364844 1.51ln (B) * ln (Rental cost) -0.0553451 ** -2.07ln (C) * ln (Rental cost) -0.0123455 -0.48ln (quality of services) 0.2753913 1.23 0.3273649 1.47 0.3940938 * 1.75length of operation -0.001262 ** -2.07 -0.0011689 ** -2.37 -0.0010299 * -1.67dummy for branch office 0.0159358 0.11 0.0491589 0.37 0.0675421 0.55dummy for special region 1 0.2996738 1.34 0.3223407 1.55 0.2537962 1.39dummy for special region 2 0.0601059 0.48 0.0011281 0.01 0.0154946 0.11dummy for special region 3 -0.0678484 -0.54 -0.0693386 -0.57 -0.0834696 -0.6dummy for at-home assistance business -0.0730759 -0.59 -0.0855523 -0.71 -0.1112894 -0.89dummy for at-home bathing business 0.3931035 *** 3.03 0.4161889 *** 3.47 0.3969708 *** 2.94dummy for day care business -0.0675121 -0.58 -0.0398449 -0.34 -0.0380693 -0.3dummy for sales and lending business of welfare equipments 0.173006 1.1 0.1045636 0.75 0.2415388 1.61dummy for food delivery business 0.0463575 0.37 0.0703214 0.55 0.0732451 0.55dummy for short-stay business -0.6545475 ** -2.3 -0.651452 ** -2.18 -0.6153819 *** -2.75dummy for medical facilities 0.3371074 1.28 0.3346211 1.25 0.2893437 1.34dummy for at home nursing and rehabilitation business 0.3416049 * 1.92 0.2909876 1.63 0.2858262 1.38dummy for newer provider -0.4061605 *** -3.46 -0.4090204 *** -3.5 -0.3547408 *** -2.79dummy for nonprofit provider -0.0265734 -0.19 -0.0165092 -0.13 -0.0770982 -0.58dummy for public provider -0.2484345 -1.58 -0.2890197 * -1.86 -0.3351975 ** -1.99Constant 2.600399 *** 3.42 4.214837 *** 4.56 5.018539 *** 4.75

Observations 261 261 261R

20.6864 0.723 0.7625

Coeff. Coeff. Coeff.

Case 1:Cobb-Douglas Function

Case 2:Log-Quadratic Function

Case 3:Translog Function

Note:1) The dependent variable is the logarithm of the total expenditure (lnC) of individual provider. The explanatory variables include a nonprofit dummy (N=1 for nonprofit provider, N=0 otherwise), a public provider dummy (G=1 for public provider, G=0 otherwise) and a new provider dummy (A=1 for newer provider, A=0 otherwise) .2) The specifications for these results are discussed in the main text.3) ***means 1% significant level, ** means 5% significant level, * means 10% significant level.

23

Table 7 Estimation of cost functions with score of principle component as an index of quality of services

t value t value t valueln (Total utilization hours of physical nursing) -A 0.1275019 ** 2.36 0.2686886 1.01 0.6605247 *** 2.68ln (Total utilization hours of physical nursing)^2 -0.0122833 -0.58 -0.0107632 -0.29ln (Total utilization hours of house work assistance)-B 0.1978822 *** 4.13 -0.5023841 ** -2.46 -0.9009452 *** -3.79ln (Total utilization hours of house work assistance)^2 0.0531592 *** 3.31 0.0641564 ** 2.41ln (Total utilization hours of multiple services) -C 0.173963 0.77 -0.0346764 -0.16ln (Total utilization hours of multiple services)^2 0.1568401 *** 3.1 -0.0022789 -0.13 0.0169764 0.56ln (A) * ln (B) -0.0376831 -0.89ln (B) * ln (C) 0.0476921 0.97ln (C) * ln (A) -0.038155 -0.78ln (Wage) 0.5558188 *** 5.1 0.7024069 *** 5.53 0.6860532 *** 5.57ln (Wage)^2 -0.0705236 -1.41 -0.054563 *** -4.2ln (Rental cost) 0.0043481 0.15 -0.0076398 -0.16 0.3139468 ** 2.55ln (Rental cost)^2 -0.0031201 -0.34 0.0244657 *** 2.64ln (Wage) * ln (Rental cost) 0.0300974 * 1.89ln (A) * ln (Wage) 0.17575 *** 3.34ln (B) * ln (Wage) 0.0092461 0.16ln (C) * ln (Wage) -0.1529655 ** -2.39ln (A) * ln (Rental cost) 0.0367504 1.52ln (B) * ln (Rental cost) -0.0552806 ** -2.07ln (C) * ln (Rental cost) -0.0135004 -0.53ln (quality of services) 0.0867527 1.41 0.0971349 1.59 0.1179355 * 1.95length of operation -0.0012311 ** -2.02 -0.0011343 ** -2.31 -0.0009918 -1.61dummy for branch office 0.0084562 0.06 0.0418671 0.31 0.0579804 0.47dummy for special region 1 0.302108 1.35 0.3250649 1.56 0.2567267 1.41dummy for special region 2 0.0624414 0.5 0.0037663 0.03 0.018069 0.13dummy for special region 3 -0.0674057 -0.54 -0.0699043 -0.57 -0.0846296 -0.61dummy for at-home assistance business -0.0750864 -0.61 -0.0871299 -0.72 -0.1123821 -0.9dummy for at-home bathing business 0.3859238 *** 2.99 0.4091056 *** 3.43 0.3890785 *** 2.88dummy for day care business -0.0757276 -0.66 -0.0483188 -0.41 -0.0478614 -0.38dummy for sales and lending business of welfare equipments0.1738388 1.1 0.1041877 0.75 0.2402685 1.6dummy for food delivery business 0.0489182 0.4 0.0738902 0.58 0.0783803 0.59dummy for short-stay business -0.650488 ** -2.29 -0.6484111 ** -2.19 -0.6114909 *** -2.74dummy for medical facilities 0.3344278 1.28 0.3327976 1.25 0.2866871 1.33dummy for at home nursing and rehabilitation business 0.3384129 * 1.93 0.2880061 1.63 0.2819074 1.37dummy for newer provider -0.4084706 *** -3.49 -0.4111004 *** -3.53 -0.359142 *** -2.83dummy for nonprofit provider -0.0216574 -0.16 -0.0101705 -0.08 -0.0696265 -0.53dummy for public provider -0.2347359 -1.48 -0.2752851 * -1.76 -0.320006 * -1.9Constant 3.531248 *** 9.88 5.310764 *** 8.24 6.364263 *** 7.32

Observations 261 261 261R

20.6872 0.724 0.7625

Coeff. Coeff. Coeff.

Case 4:Cobb-Douglas Function

Case 5:Log-Quadratic Function

Case 6:Translog Function

Note:1) The dependent variable is the logarithm of the total expenditure (lnC) of individual provider. The explanatory variables include a nonprofit dummy (N=1 for nonprofit provider, N=0 otherwise), a public provider dummy (G=1 for public provider,G=0 otherwise) and a new provider dummy (A=1 for newer provider, A=0 otherwise) .2) The specifications for these results are discussed in the main text.3) ***means 1% significant level, ** means 5% significant level, * means 10% significant level.

24

Table 9 Estimation of cost functions while controlling the causes of public-private cost gap

t value t value t valueShare of customers living near service centers -0.0499144 *** -2.67 -0.0398483 ** -2.33 -0.0371903 ** -2.23Rate of dependency on government subsidy 0.0733227 0.91 0.0791739 0.94 0.0896262 0.53Proportion of part-time helpers 0.0287075 *** 3.95 0.0219499 *** 2.87 0.0194666 *** 2.46Net utilization rate of nursing facilities 0.0356116 * 1.95 0.0317763 * 1.68 0.0304991 * 1.73dummy for newer providers -0.3992696 *** -3.56 -0.4189824 *** -3.69 -0.3468201 *** -2.93dummy for nonprofit providers 0.0692175 0.47 0.0710147 0.5 0.0040507 0.03dummy for public providers -0.0575043 -0.31 -0.1006475 -0.6 -0.138093 -0.83Constant 2.759774 *** 3.91 3.951548 *** 4.57 4.150302 *** 4.05

Observations 237 237 237R

20.7549 0.773 0.7964

t value t value t valueShare of customers living near service centers -0.0502556 *** -2.69 -0.0402004 ** -2.35 -0.0378689 ** -2.27Rate of dependency on government subsidy 0.078735 0.98 0.085212 1.01 0.096604 0.57Proportion of part-time helpers 0.0283616 *** 3.89 0.0215756 *** 2.8 0.0191058 ** 2.41Net utilization rate of nursing facilities 0.0356588 * 1.95 0.0317763 * 1.68 0.0304651 * 1.73dummy for newer providers -0.4004665 *** -3.57 -0.4204428 *** -3.7 -0.348955 *** -2.95dummy for nonprofit providers 0.0807858 0.55 0.0838388 0.6 0.0182979 0.14dummy for public providers -0.0439579 -0.24 -0.0858354 -0.51 -0.1210823 -0.72Constant 3.959466 *** 10.09 5.262781 *** 8.39 5.644148 *** 6.68

Observations 237 237 237R

20.755 0.773 0.7964

Cobb-Douglas Function Log-Quadratic Function Translog FunctionCoeff. Coeff. Coeff.

Coeff. Coeff. Coeff.Cobb-Douglas Function Log-Quadratic Function Translog Function

Notes:(1)This table highlights the estimated coefficients on dummies for ownership and factors of public- private cost gap only.(2)The specifications for these results are discussed in the main text.(3) ***means 1% significant level, ** means 5% significant level, * means 10% significant level.

Table 8 Inherent factors accounting for the public- private efficiency gapUnit:%

Mean Std. Dev. Mean Std. Dev. Mean Std. Dev.

Share of customers living near service centers 66.4 32.6 78.7 29.1 91.7 21.2

Rate of dependency on government subsidy 0.7 3.3 2.1 6.5 12.1 42.8

Proportion of part time helpers 26.5 51.6 28.2 80.9 24.0 37.7

Net utilization rate of nursing facilities 59.2 32.1 64.5 80.9 65.7 23.4

For-profit providers Nonprofit providers Public providers

Note: See the text for detailed explanations of each factor.