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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
2 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-non-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-for-profit hospitals, non-for-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).
11 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.
15 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.
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