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University of Amsterdam

Faculty Economics and Business

Bachelor Thesis business Economics, Finance and Organization track

The relationship between Dutch hospital financial results and the quality of

medical care delivered.

June 2016

Tom Pastoors

Student number: 5668387

Thesis supervisor: Dr. P.J.P.M Versijp

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Verklaring eigen werk

Hierbij verklaar ik, Tom Pastoors, dat ik deze scriptie zelf geschreven heb en dat ik de volledige

verantwoordelijkheid op me neem voor de inhoud ervan.

Ik bevestig dat de tekst en het werk dat in deze scriptie gepresenteerd wordt origineel is en dat ik

geen gebruik heb gemaakt van andere bronnen dan die welke in de tekst en in de referenties worden

genoemd.

De Faculteit Economie en Bedrijfskunde is alleen verantwoordelijk voor de begeleiding tot het

inleveren van de scriptie, niet voor de inhoud.

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1.Introduction

The market for specialized medical care in The Netherlands is served by hospitals that are private,

non-profit organizations. Despite of that these hospitals are private organizations, the Dutch

government is influencing their policy to secure the quality, efficiency and accessibility of

medical care (Kerste, 2010). The Dutch national healthcare expenditures increased from 40,3 billion

euro’s to 95 billion euro’s between 1998 and 2014. One of the challenges that healthcare policy

makers have been facing for the past years is limiting its increasing costs (CBS 2014, VWS 2011).

The Dutch government is taking measures to limit healthcare expenditures. One of these measures,

expanding regulated market competition in the hospital industry is one of the pillars of Dutch

government policy (Kerste, 2010). The regulated market competition will improve efficiency and

will force the hospitals to meet patients demands (Kerste, 2010). Economic market theory states that

for-profit healthcare institutions will be more cost-efficient that their non-profit counterparts as a

result of market generated incentives (Clark, 1980, Cutler 2000). The property rights theory

prescribes that for profit firms, that pay out their profits to investors, will operate more efficient and

at lower costs than non-profit firms (Clarkson, 1972). At this moment hospitals in the Netherlands

are financed with debt, patient revenues and government grants.

When hospitals are highly leveraged the expected interest rate that has to be paid to the

creditors is likely to be high. A large share of any future benefits of a possible investment wills go to

these creditors, the problem of debt-overhang can arise. Valuable investments which could have

positive effect on the value of the firm can be passed (Myers, 1977). When necessary medical care

investments aren’t executed because of the amount of debt, the quality and efficiency can diminish.

Within the efforts to limit healthcare expenditures the place of the regulated market

competition in the hospital industry and the owner structure of hospitals remains a topic of debate.

The possibility for a conversion from private non-profit towards private for-profit hospitals is a

topic of debate among policy makers. The Dutch parliament is currently handling a state bill for the

possibility for investment opportunities in specialized medical care (VWS, 2016). In order to

increase healthcare financing, the possibility to pay out profit to equity holders is reviewed. When

this is possible, hospitals will be able to attract risk bearing equity holders to raise liquidity. As a

result of that the quality, the service and the expediency are expected to increase (Kerste, 2010).

In the United States of America hospitals historically were large charitable and non-for

profit organizations, but over the past decades more and more hospitals converted towards for-profit

firms (Sloan, 2000). In the period between 1990 and 1997 the percentage of for-profit U.S. General

Hospital increased from 6% to 16% (Baker 2000). Over the past decades many policymakers in the

United States opted for market driven healthcare systems. In these market-driven systems hospitals

are free to set the quantity and quality of the health care they deliver. For quite a long time there is a

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growing concern that the profit driven motives of these hospitals are harming the patients interests,

research proved that these market based healthcare systems can have unfavourable effects on the

quality of healthcare (Schlesinger, 1987 ). Hospital based in The Netherlands were financed

historically by a financial budget, the quantity of treatments provided wasn’t leading for their

amount of financial compensation. After the introduction of the 2006 healthcare law, hospitals are

paid for their amount of treatments (NZA, 2007). This type of financing can compromise the quality

of care, because hospitals have an incentive maximize their amount of treatments and lower their

costs. When hospitals will become for-profit firms cost reduction and quantity maximization will be

more important. The question arises if these incentives will influence the quality of delivered

hospital care. This thesis seeks to answer the following question. Is there a relationship between

hospital financial results and the quality of hospital care in The Netherlands? In part II the existing

literature and evidence on the relationship between ownership and the quality of care is reviewed.

Within this search I identified financial parameters that are a result of market or profit driven

incentives. In Part III these financial parameters were tested on a dataset on quality outcomes and

financial data of hospitals in The Netherlands. I tested the relationship between the amount of debt

and the quality of hospital care to investigate the possible existence of a debt overhang problem that

influences quality of hospital care.

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II. Literature.

Research on the quality of hospital medical care is mainly targeting patient and treatment

specific factors. This medical research is focusing on how, when and which medical procedures

should be performed to improve the quality of care. Weiner et al (Weiner, 2006) state that hospitals

in the United States can improve quality on changing other factors that the treatments itself. They

claim that 25 % of all hospital deaths might be preventable, nearly 180,000 patients die each year as

a results of iatrogenic, caused by medical professionals, medical conditions. One third of abnormal

laboratory tests results are not adequately handled by clinicians, one third of the medication

prescribed to hospital patients are not indicated and one third of several hospital procedures are not

improving the patients’ health but are exposing them to risks (Brook 1990, Weiner 2006). Based on

the current medical knowledge some medical procedures can be labelled as unnecessary. These

procedures can be the results of wrong, possibly profit driven incentives. In contrast to other

western countries, the shift from government owned to non-for profit and from there on to for-profit

hospitals has been going on for several decades in the United States. With the transformation to

profit driven firms the discussion on its effects on the quality of care arose. Most research on

hospitals ownership, financial results and the quality of medical care was performed in the United

States. Although many researchers investigated this topic, there is no consensus on whether or not

profit or non-profit hospitals deliver better medical care (Rosenau, 2003). There is also no

consensus on the effect that market competition between hospitals has on the quality of the medical

care delivered.

Hospital ownership type and quality of care.

Authors that are convinced of comparative advantages of for-profit medical organizations, claim

that these organizations are operating in a more efficient way (Marsteller, 1998). After observing

several conversions from non-profit or government owned to for-profit, some authors conclude that

these institutions contribute to society in terms of charity medical care as much as their non-profit

counterparts (Sloan, 2000). They could provide hospital care at lower cost and return the same level

of quality (Rosenau, 2003). The discussion on whether or not for-profit hospitals would be more

efficient exceeds the property rights theory. Drucker argues that non-profits firms are performing

better than for-profit firms, they are more competent the motivation of and increasing the number of

high educated employees (Drucker, 1989). Medical care providers are an example of firms that are

knowledge based (Rosenau, 2003). Nelson claims in a paper on the efficiency of managers in non-

profit firms that they have capabilities that differ from managers in for-profit firms. Managers who

run non-profit firms have a history of managing under challenging conditions, they have experience

in motivating their workforce and developing non-financial goals (Nelson, 1999). At the other end

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of the discussion on the performance difference between for- profit and non-profit firms are the

arguments of efficiency and market discipline. For-profit hospitals and other firms that are owned

by equity holding investors are said to be more sensitive to the effects of market discipline (Jensen,

1983). Other authors point at for-profit hospitals as the initiators of increasing costs of medical care

(Parker, 1997).

Rosenau (2003) systematically surveyed al known peer-reviewed articles on performance of

for–profit and Non-profit United States hospitals between 1980 and 2002. They included articles

that investigated the effect of the organizational form on the performance of the hospital. These

papers compared the performance differences between for-profit and non-profit hospitals. The

performance criteria they distinguished where access, quality, cost or efficiency and the amount of

charity care. The outcome is displayed as relative performance in favour of non-for profit, in favour

of for-profit or indifferent. In their synthesis of research papers they concluded that authors use a

wide spread of definitions of cost performance, efficiency and quality. “We observed that the

inventoried studies used the term cost performance to refer to expenses per patient, cost per patient

day, cost per case, net patient revenues, markup, profitability, efficiency, or surplus. It also included

economic efficiency, price efficiency, and productivity. The studies defined quality in several

different ways, including lower adverse event rates, lower mortality rates, lower noncompliance

notification, and a broader array of services (Rosenau 2003).”They included a total of 75 papers

that compared non-profit and for-profit hospital performance. Out of these 75 papers, 24 were

reporting on the quality of medical care delivered, 37 of these papers reported on costs performance

or efficiency. Twelve (50%) of the papers on quality of care reported that the quality of non-profit

hospitals was superior to the quality of for-profit hospitals. Three (13%) of the papers concluded

that for-profit hospitals provided better care than non-for profit. Nine (38%) papers that compared

the quality between profit and non-profit hospitals concluded that the quality was indifferent. Out of

those 37 papers that compared cost efficiency between the two type of organizational forms 23

(62%) papers concluded that non-profit were more cost effective that for-profit hospitals. Five

(14%) papers concluded that for-profit firms were more efficient. Nine (24%) papers concluded that

there was no clear difference. Their overall conclusion on all topics of performance is that: “Most

studies (60 percent) reported that non-profit hospitals have better relative performance than for-

profit hospitals, clear evidence of their organizational effectiveness. Thirty-one percent were

inconclusive, and 8 percent reported that for-profits were better (Rosenau, 2003).”

In their article Cutler and Horwitz (2000) explicated three factors that can determine a

hospital’s choice between a for-profit or non-for profit organizational (Cutler, 2000). The first factor

that influences the choice between non-profit or for-profit form can be related to the amounts of

profits that are made. The organizational form of non-profit hospitals does not allow them to pay

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out their profits. When financial balances are rising these non-profit institutes might decide to

change into a for-profit form in other to be able to pay out profits. Hospital managers may also

decide to remain a non-profit firm to be to finance future activities that are not very profitable but

that are marked as important by these managers like charity care, research of teaching purposes

(Cutler, 2000). The second factor they defined that could influence the organizational form is the

access to external financing. For-profit firms have access to more financial instruments than for-

profit firms. Equity financing is widely available to for-profit hospitals, non-profit hospitals can

decide to convert to a for-profit form when they have no more access to debt in times that they need

more working capital (Cutler, 2000). The third factor influencing the choice of organizational form

that they recite is that of market imperfections. One of these market imperfections is the problem of

information asymmetry in the hospital industry. It is hard for patients to make a rational choice on

what medical treatments might be of value for them on their own. This information asymmetry

forces patients to stick to the healthcare providers preferences. For-profit firms are more likely to

skimp more on the quality, if this will result in a higher profit, that non-profit firms if the patients or

customers aren’t able to valuate quality (Cutler, 2000).The absence of shareholders in case of non-

profit firms will prevent them on skimp on the quality just to get the highest possible dividend or

return. Another reasoning can be that more profitability and a higher pay out may lead to attracting

more capable managers, well managed firms are likely to have better outcome than poorly managed

firms (Cutler, 2000).

In an empirical research on 90 days mortality rates after an ischaemic heart disease event,

McClellan and Staiger compared outcome differences between for profit and non-for profit

hospitals in three U.S bases counties. They conclude that there is a negative relationship between

mortality and the amount of treatments performed and that non-profit hospitals have a slight lower

mortality rate than for-profit hospitals. At the same time they mention that there is a large variation

between hospitals and that quality is hard to compare, this suggests that there are other factors that

influence quality more than ownership type does (McClellan, 2000).

Financial variables and the quality of care

Rosenau(2003), Cutler(2000) and McClellan (2000) focused on quality and efficiency

differences between for-profit and non-profit hospitals and possible incentives for hospitals to

convert towards a for-profit form. As a result of the recent economic downturn, United States based

hospitals faced fiscal constraints (Dong 2015). Dong et al attempted to determine if financial

performance driven hospital management affected the quality of care. He questions to what extend

do these financial parameters have an impact on treated patients? He reviewed all available

literature on the correlation between quality of care and hospital financial performance. The

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identified factors were tested on a large dataset on quality of cardiac care in the United States

(Dong, 2015). I will summarize his most important findings. Some authors argue that profitability

has a positive effect on the quality of care delivered, hospitals can offer a higher quality standard

when the financial resources allow these hospitals to invest in quality, diminished financial results

will be followed by a lower quality of care provided (Newhouse 1970, Spence 1975, Dong 2015).

As a result of the profitably, investments and the and following increase in quality, physicians will

refer their patients to these hospitals as they are committed to health of their patients (Newhouse

1975, Dong, 2015). A study on a 6 year longitudinal data on general acute care in 11 American

States showed that a worse operating margin forced to cut on expenditures on medical equipment,

resulting in lower quality of medical care (Bazzoli, 2008). A of lack of operating efficiency can

result in a shortage of funds for important primary processes (Blegen, 2001 ). Valdmanis et al argue

that reducing slack resources, waste full capacity and closing down of limiting dysfunctional

operation can result in a incensement of quality (Valdmanis, 2008). Several papers investigated the

effect of the amount financial Leverage or debt on the quality of care. Non-profit hospitals are

encouraged to take on more debt capital as a result of the tax-exempt conduit bonds advantages

(Valvona, 1988). More financing possibilities can result more investment in quality. Wedig states

that investments in quality, infrastructure and technology demand large scale investments demands

the possibility to raise additional funds. Taking more debt can result in higher bankruptcy risk

which may force hospital to take on less debt, the debt/ asset ratio will be lower (Wedig, 1988).

Asset liquidity, the company’s capability to pay short-term and long-term obligations was identified

in multiple papers as a factor influencing quality. A hospital’s optimal capital structure is influenced

by that firm asset liquidity. Hospitals with better asset liquidity can afford a higher level of debt,

liquidity lowers the costs of leverage. This enables hospitals with a higher asset liquidity to raise

capital to invest in quality enhancing projects (Shleifer, 1992). Bazzoli’s paper on quality of general

acute care pointed out that hospitals with a lower asset liquidity ratio, defined as cash flow/

revenues, had a higher number of incidents at their acute care facility (Bazzoli, 2008).

Prior studies showed that hospital staffing, in particular hospital nurse staffing is of

influence of a wide spread of patient related complications. A shortage on well trained nurses

resulted in an incensement of expected patient mortality (Aiken, 2002), and also patient falling

incidents increased (Blegen, 1998). Hospital nurse staffing and working conditions problems

increased the number of medication errors (Blegen, 1998). These problems also had an adverse

effect on the number of infections of hospitalized patients (Stone, 2007). Dong et al found a positive

relation between wage expenses and the quality of cardiac care. When hospitals are demanding a

higher standard of quality they can employ more experienced and higher trained nurses, these

enhancement require a higher level of remuneration for these employees (Feldstein, 1971).The

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effect of staffing on the quality of medical care implies that increasing labor costs will result in a

higher quality (Dong, 2015). The effect of increasing number of high trained workers will not

improve quality until infinity (Blegen, 2001). Along the same line of earlier reasoning, spending too

many resources on labor can result in lower operating margin, profitability and wasteful capacity.

This may lead to lower quality of care (Picone, 2003). Prior studies identified multiple hospital

financial variables that can influence the quality of medical care in different ways. Table 1

summarizes financial variables that proved to be correlated to quality of care in prior research.

Table 1: Overview of financial variables related to quality of care.

Variable Effect on quality Reference

Profitability positive Dong, Spence, Newhouse,

Negative Valdmanis

Debt or leverage level Positive Dong, Valvona, Sloan

negative Wedig

Asset liquidity Positive Sleifer, Bazzoli

Labour costs Positive Dong, Blegen.

Negative Picone.

Operating efficiency Positive Blegen, Picone,Valdmanis

How to define the quality of hospital medical care?

The quality of medical care is difficult to measure. In his 2000 paper, Cutler describes three main

reasons for this. Because it is difficult to identify comprehensive measures of quality, a

comprehensive measure should include not only the patients’ health, but also satisfaction and the

process of care. His second argument is that there, until recently were no reliable data sets available

that gave information on long term health outcomes. The third argument is that of inadequate

information on the mix of patients at different hospitals (Cutler, 2010). Patient’s characteristics, like

age, comorbidities, severity of their disease differ between hospitals. Most hospitals are treating

certain subgroups of patients, for example a specialized trauma centre or cancer institute is most

likely to incur different mortality rates than an eye hospital. For that reason quality indicators are

difficult to compare, mortality rates, complication rates and re-admission rates between hospitals

aren’t suitable for comparison without correcting of influencing factors (Cutler, 2010).

For that reason Jarman initiated the calculation of The Hospital Standardized Mortality Rate

in England (Jarman , 1999). From 2005 on Jarman is calculating the HSMR for the Netherlands.

This is done in collaboration with the institutes Dr Foster Intelligence in London, Kiwa Prismant,

Imperial College London, and De Praktijk Index in the Netherland (CBS, 2014).The Hospital

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Standardized Mortality Rate further referred to as the HSMR, is a numeric indicator of hospital

quality. The HSMR compares actual hospital mortality and expected hospital mortality based on

certain patient characteristics. “The HSMR adjusts for factors that affect in-hospital mortality rates,

such as patient age, sex, length of stay, admission status, comorbidity group, transfers and the

number of patients treated in the hospital.” (CBS, 2014). The HSMR includes 50 groups of

diagnoses that are responsible for 80% of the hospital deaths incurred. A score of 100 is the

calculated or expected hospital specific mortality rate. A score above 100 indicated more deaths

than expected, a score under 100 indicates a mortality rate lower than expected. This rate enables us

to compare hospital the expected with actual hospital mortality, which enables us to measure

healthcare quality between hospitals.

The HSMR is used in several other countries as a hospital medical care quality indicator, countries

that do so are; The United States of America, Canada, The United Kingdom, Australia, Japan,

Germany, Denmark and Sweden. Dutch hospitals are obligated to publish their HSRM score to

make medical care performance more transparent. The HSMR is a proximate of the expected

number of mortalities; a proximate comes with several limitations. It is not possible to adjust

perfectly for the patient case mix. Hospitals can differ in their admission and discharge policies,

which can result in deaths outside of the hospitals registration. Besides the case mix there is also the

bias factor that not all hospitals are authorised to perform all kinds in interventions (CBS, 2014).

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III. Methods.

I tested the hypothesis that the amount of assets, the operating efficiency, the asset liquidity, the

salary expenses, the amount of investment and the profitability are positively related to the quality

of care, and thus negatively correlated to the HSMR. My hypothesis on the financial leverage is that

it is from a certain point on negatively correlated to the quality of care and thus positively to the

HSMR.

To test the relationship between financial characteristic and quality scores I used financial

data of all general and academic hospitals in The Netherlands. Private hospitals and specialized

clinics that did not delivered general health care and did not comply with the HSRM publication

obligation were excluded. The data set consists of financial data collected from Dutch hospital’s

financial annual reports. To test the relationship between the hospital’s financial results and the

quality of hospital care in The Netherlands I performed a multivariate regression analysis with

backward elimination of variables based on their p-value. A p-value ≤0.10 is considered to be

significant. The dependent variable is the quality of care, the hospital’s financial results are used as

independent variables. To be able to test relationship between financial results and quality of

hospital care in a statistical model the concepts financial results and quality of hospital care needed

to be quantified. To quantify the quality of Dutch hospital care, The Hospital Standardized

Mortality rate for the year 2013 was used, the HSMR was used in the model as the dependent

variable. Independent variables that are used in a regression analysis are variables that proved to be

correlated to quality of hospital care in previous papers, all denoted in euros. Assets, investments

and the dummy variable “Randstad” were added. The dummy variable “Randstad” was added to

correct for expensive real-estate and thus higher Asset prices. The natural logarithm of a hospital’s

total amount of assets was used to avoid outliers and correct for skewness distributing.

Financial leverage was defined as the total amount of long term debt divided by the amount of total

assets. To test the relation between a high financial leverage ratio and quality I added a dummy that

included the top 20% highest leverage ratios.

Operating efficiency was defined as the total revenues over 2013 divided by the total amount

of assets. The current ratio was used as the variable for asset liquidity, defined as the amount of

current assets divided by the amount of current liabilities. Salary expenses were included as the

amount of salary divided by revenues. Because the results of investments most likely are not visible

in the year that they were incurred, I used the average amount of investments over the year 2010 to

2013, divided by the revenues over 2013. Profitability was defined as Earnings Before Interest,

Taxes, Depreciation and Amortization, divided by revenues. All Variables with the same

denominator, revenues and assets were tested separately to avoid the problem of multicollinearity. A

multicollinearity test was performed as well, were a tolerance below 0.10 indicated a

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multicollinearity problem. Variables that proved to be significant in a univariate model were again

tested in a multivariate model. The dataset did not provided information to split up salary expenses

in medical and supportive functions. Neither did it provide information to split up assets in real-

estate and medical equipment.

The multivariate regression model used:

X1=Total assets: Natural logarithm Assets

X2=Financial leverage: Long term debt/ Total assets

X3=Operating efficiency: Revenue/ Total assets

X4=Asset liquidity: Current assets/ Current liabilities; Current Ratio

X5=Salary expenses: Salary / Revenues

X6=Investments: Average annual investments 2010-2013/ revenues

X7=Profitability: EBITDA/Revenues.

X8=Dummy variable 1 Expensive real estate; Randstad located hospitals 1, non-Randstad 0.

X9=Dummy variable 2 Top 20% highest financial leverage ratios. Top 20% 1, all else 0.

The following model will be tested:

Yi = β0 + β1X1+ β2X2 + β3X3+ β4X4 + β5X5 +β6X6+β7X7+ β8X8+ β9X9 εi

H0: β1= β2= β3= β4= β5 = β6= β7= β8= β9= 0

H1: βi ≠ 0, for at least one i.

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IV. Results.

HSMR data and financial results were available for 72 out of 88 academic and public hospitals in

The Netherlands that were obligated to publicize their HSMR scores. There is a wide variation in

financial characteristics between hospitals. For example the total amount of assets varied between

57 million euros of the Havenziekenhuis in Rotterdam and to 1,6 billion euros of the Erasmus

medical centre also located in Rotterdam. Personnel expenses varied from 47% of revenues in the

Hagaziekenhuis in The Hague to 72 % in the Maasstadziekenhuis in Rotterdam. There was also a

wide variation in HSMR scores from 65 for the Martini ziekenhuis in Groningen, indicating less

mortality than expected, to 137 for the Maasstad ziekenhuis indicating more mortalities than

expected. Most hospitals that were not able to provide the HSMR score over 2013 failed to because

their internal data recording did not suffice. Table 2 summarizes all hospital characteristics.

Table 2: Descriptive statistics, n=72

Minimum Maximum Mean Std. deviation.

HSMR 2013 65 137 99,40 14,58

Total assets 57478164 1550566000 311427708,96 279412961,533

Long term debt 136134 690679000 129294259,28 127178536,616

Revenues 61049045 1298077000 289526871,58 264541450,216

Personnel expenses 35423744 721777000 161707888,25 154181521,385

EBITDA 3680173 132509000 33238810,75 26355258,679

Average investments 1396250 219650250 30991838,33 34342654,607

1: Log total assets 17,8669 21,1619 19,2600 ,7517

2: Financial leverage ,0018 ,6403 ,3967 ,1133

3: Operating efficiency ,5038 1,5565 ,9654 ,2086

4: Curent ratio ,2057 2,2925 1,0890 ,3662

5: Salary expenses ,4704 ,7204 ,5504 ,0420

6: Investments ,0086 ,3302 ,10507 ,0607

7: Profitability ,04304 ,2092 ,1221 ,0275

8: Dummy Randstad 0 1 ,46 ,502

9: Dummy top 20 %

leverage ratios 0 1 ,19 ,399

Table 3 shows the multivariate regression analysis. The only significant variable after backward

elimination was the amount of salary expenses divided by the total revenues. The direction of the

coefficient indicates that a higher proportion of personnel expenses is correlated to a higher than

expected hospital mortality rate. Other variables that proved to be significant P<0.10 were

profitability and the natural logarithm of total assets. These two were not significant in a

multivariate model. To control for multicollinearity a regression with those three variables was

performed (table 4), collinearity statistics did not indicated multicollinearity. Higher amount of

assets indicate a higher HSMR (p-value = 0.081708, R square: 0.0427), a higher profitability

indicated a lower HSMR than expected ( P = 0.0106, R Square 0.0896). Salary expenses divided by

total revenues was the best predictor of the HSMR score and explained more of the variance in

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HSMR that the other two significant predictors; the R- square was 0.1432.

Table 3: Regression of hospital quality on financial characteristics

Dependant variable:

HSMR

(1) (2) (3) (4) (5)

1:Total assets

2,4486(0,9626)

4,007*

(1,7661)

3,1087

(1,4485)

2. Financial leverage 27,1110(1,1888)

3. Operating efficiency 5,1719(0,4491)

4. Current ratio 2,8380(0,5730)

5. Salary expenses 101,3502**

(2,1393)

131,3731***

(3,4201)

103,2893**

(2,3175)

6. Investments 24,0866(0,7282)

7. Profitability

-

80,8216(0,7282)

-158,593***

(-2,6246)

-65,8694

(-0,9655)

8. Dummy Randstad 4,3590(1,3110)

9. Dummy top leveraged -5,3996(1,3110)

Constant

2,4486(-0,2647) 27,0951(1,2779) 118,7627***

(15,7113)

22,22579

(0,5083)

-9,2816(

-0,1832)

R-squared

0,1432

0,0896

0,0427

Adjusted R-squared 0,1281

0,1468

F significance. 0,0373

0,0010

0,0106

0,0817

0,0031

In regression (1) all variables were tested in one model. Regression 2 included salary expenses, regression 3

profitability and regression 4 total assets. In regression 5 the variables assets, salary expenses and profitability were

tested together. T-statistics are shown in the parentheses. ***, ** and * is indicating a statistical significance level of

1%, 5% and 10% respectively.

Table 4: Collinearity Statistics

Model Tolerance VIF

Constant

Assets .982 1.019

Salary expenses .729 1.371

Profitability .725 1.380

Figure 1 displays the scatter plot of HSMR and salary expenses, indicating a positive relation

between salary expenses and HSMR. Since a higher HSMR is indicating worse quality, an increased

salary/revenues ratio is associated with a higher amount of expected mortalities.

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Figure 1.

Referring to earlier formulated hypotheses, this data did not support that the variables

financial leverage, the operating efficiency, the current ratio, the amount of investments and the

dummies Randstad and top 20% leverage ratio are correlated to the quality of hospital care. The

variables total assets, the salary expenses and the profitability proved to be correlated to the HSMR.

The variables total assets and salary expenses were significant but in the opposite direction than

formulated in my hypothesis. That an increasing amount of salary expenses can be related to worse

quality is supported by earlier research (Picone, 2003).

The variable profitability was negatively correlated to the HSMR, resulting in a positive

relationship to quality, as formulated in my hypothesis. Although the latter variable was supporting

the hypothesis, the amount of explained variance of the HSMR is small. This finding is also

supported by earlier research (Newhouse 1970, Spence 1975, Dong 2015).

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V. Conclusion

The main results of this research are that most tested variables are not correlated to the quality of

hospital care. Three variables were correlated separately, but were not significant in a multivariate

model. My research indicates that the independent variable wage expenses, defined as salary

divided by revenues is positively correlated to the HSMR score, this indicates that higher personnel

or wage expense is correlated to a higher number of hospital deaths than expected based on the

patients characteristics. The univariate model’s R square is 0,1432. The effect of this variable was

the opposite of what was formulated in my hypothesis. Although higher personnel expenses are

expected to increase quality, we might have been looking an obverse effect of too high wage

expenses, unit a point that the quality does not improve any further. Like Picone and Belgen argue,

a waste of financial resources might result in a loss of efficiency to a point that other important

quality enhancing expenses are under pressure (Picone 2003, Belgen 2001).

The other predictors that only proved to be only significant predictors in a univariate model were

the Natural logarithm of Assets and the hospital’s profitability, defined as EBITDA/Revenues.

These predictors only explained a small amount of the variance: R square 0.0427 and 0.0896.

The direction of the variable profitability supports my hypothesis that profitability is related to

better quality, this finding is supported by earlier research (Newhouse 1970, Spence 1975, Dong

2015).

The fact that most variables in this dataset are not correlated to quality of medical care might

be the result of a limited dataset. Data on more consecutive years or time series data might reveal

other insights. Further research could divide salary expenses in a way that is split up in wages that

contribute to the primary process of medical care and supportive functions. As described in part II,

the HSMR is a proximate for the quality of medical care as mentioned earlier, a comprehensive

measure should include not only the patients’ health, but also satisfaction and the process of care

(Cutler, 2000). Future development of more subtle indicators than mortality rate might enable

researchers to compare the quality of medical care in a more effective and more informative way.

The effect on the quality of care in case of a future admittance of equity financing is the hospital

sector is not clear. The relative quality superiority in the US is mostly in favour of the non-profit

hospitals (Roseanu, 2003). The hospital market in The Netherland differs from the situation in the

United States. It is simply not possible to measure the effect of equity in healthcare here without

any pilot studies. When equity financing is allowed, the effect of market discipline is likely to affect

the profitability and operating efficiency. These factors are observable in present the non-equity

situation in The Netherlands. Profitability showed to have negative correlation, although weak, to

the mortality rate. In other words a higher profitability is associated with a lower mortality rate and

thus a better quality of medical care.

17

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