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UNHCR update on legislative changes affecting displaced persons November - De...DonbassFullAccess
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Hungary does poorly across the board in The Economist
Intelligence Unit’s Mental Health Integration Index, coming
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UNHCR update on legislative changes affecting displaced persons November - De...DonbassFullAccess
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Hungary does poorly across the board in The Economist
Intelligence Unit’s Mental Health Integration Index, coming
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This new Economist Intelligence Unit (EIU) report, commissioned by Gilead Sciences, explores important questions about the Portuguese healthcare system.
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Italian Regions are the accountable entities for healthcare policies: their activity is not limited to
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Last the analysis between our theoretical approach based on law and the real economic balance. Furthermore it
will be analyzed the National and Regional Healthcare System financing (in)-stability, highlighting current cash
flows, sources and investments using the “separation” of the Healthcare accounting items in the Balance Sheet.
Through chi-square test analysis and method of OLS the group of study look a possible relation be-tween
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Essential Package of Health Services and Health Benefit Plans Mapping BriefHFG Project
Many governments are scaling up health benefit plans, such as social health insurance, to increase population health coverage. This brief presents findings from a mapping between the services covered under the country’s prominent health benefit plan(s) to the country’s Essential Package of Health Services. The mapping analyzes the extent to which the plan(s) cover essential services.
Essential Package of Health Services and Health Benefit Plans Mapping BriefHFG Project
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Traditional markets in Indonesia were created so that people from all walks of life can fulfill their needs, especially staple food products, without having to spend a lot of money. However, the prices of food products in different markets vary depending on the consumers of the particular market. The aims of this article were to compare the price difference of staple food products in several traditional markets and to find out the factors that cause the price difference. The data were collected by carrying out a survey to five traditional markets around Jakarta regarding the prices of ten staple food products. The data were analyzed quantitatively using statistical calculation ANOVA from SPSS version 22, and also qualitatively to discuss several factors underlying the price differences. Results revealed that price differences of staple food products were not only caused by market location, but other factors such as pricing strategy and consumer specification. This research implied that traditional markets were still chosen by Indonesian consumers to fulfill their needs because of the competitive price.
Airport enterprise innovation performance is a crucial issue that planners, decision makers and managers should focus in order to drive the airport enterprise performance towards sustainable development. The strategic infrastructure needs, and investments need to include improvements across all major factors that affect the innovation dimension of sustainable development.
Key objective of the paper is to highlight the challenges in airport enterprise management towards sustainable development in terms of innovation improvement. A performance evaluation towards innovation and sustainable development framework is adopted and a case study application highlights the crucial role of airport enterprise management performance innovation dimension towards sustainable development. Conventional wisdom is to stimulate the interest on topic and promote a framework addressing to evaluate airport enterprise management performance towards innovation and sustainable development.
In the business world, companies need high performance. Performance is the result or overall success rate of a person over a period of time in carrying out tasks compared to various possibilities, such as predetermined standards of work, targets, or criteria. The purpose of the study was to analyze the influence of intellectual intelligence, emotional intelligence, and spiritual intelligence on employee performance. The population in this study were 63 employees of PT PLN (Persero). This study uses quantitative associative, with data analysis used is multiple linear regression analysis. The results showed that both intellectual intelligence, emotional intelligence, and spiritual intelligence had a positive and significant effect on employee performance. Intellectual intelligence has the greatest influence on employee performance, followed by spiritual intelligence and emotional intelligence. Intellectual intelligence, emotional intelligence and spiritual intelligence together have an effect of 52.4% on employee performance, and the remaining 47.6% is influenced by other factors not explained in this study.
The main purpose of the research study is to analyze the effect of organizational commitment, job satisfaction and work insecurity as well as their impact on the performance of Bank Aceh Syariah. The samples of the research are 209 employees which are selected with survey methods. Data was collected by using questionnaire, and then the data was analyzed with statistical methods of structural equation model (SEM). The study found that the organizational commitment and job satisfaction have a negative effect on turnover intention, but positive effect on the performance of Bank Aceh Syariah. The work insecurity has a positive effect on turnover intention, but negatif effect on the performance of the bank.
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This paper is an analysis on the impact machine learning, Artificial Intelligence, and robotics has on the supply chain management. The analysis covers the basis of AI in the SCM mechanisms while defining it from the ground up. Later on, to shed a true light on supply first the paper zooms in on the effects of machines in marketing. From what particular methodologies are deployed in today’s environment extending all the way to its anticipated outcomes. As the reader progresses he/she will find valuable studies on the main segments of machine learning within the supply chain itself. Certain novelties and innovations are scrutinized regarding SCM alongside these studies. These innovations are exemplified by certain cases presented in Part 3. The penultimate section briefly examines the possible drawbacks of the surge in machine application in SCM. The final section compiles the ideas presented in the paper as a whole and gives a glimpse of an estimate for the near future.
Huang (2018) decomposes the differences in quantile portfolio returns using distribution regression. The main issue of using distribution regression is that the decomposition results are path dependent. In this paper, we are able to obtain path independent decomposition results by combining the Oaxaca-Blinder decomposition and the recentered influence function regression method. We show that aggregate composition effects are all positive across quantiles and the market factor is the most significant factor which has detailed composition effect monotonically decreasing with quantiles. The main decomposition results are consistent with Huang (2018)
In Kenya, the newly promulgated constitution of 2010 (CoK, 2010), provides the basis of monitoring and evaluation as an important tool for operationalizing National and County Government projects to ensure projects success, integrity, transparency and accountability. The county governments are responsible for delivering basic services in collaboration with other agencies and partners to enhance quality of life: however, the county government projects has been marred by lack of integrity, transparency, accountability and litany of other monitoring and evaluation weakness which has undermined the impacts and success of projects including Regional Economic Blocs. Lake Region Economic Bloc (LREB) which comprised of fourteen counties bordering Lake Victoria Basin is not sparred either. The study was conducted in six LREB Counties namely, Migori, Homabay, Kisumu, Siaya, Kakamega and Vihiga chosen in a random manner. This study specifically assessed the effectiveness of Monitoring and Evaluation methods on the Performance of County Governments Projects. The study was guided by the theory of change. The research was carried out using descriptive survey design which entails both qualitative and quantitative data collection procedures. The researcher used stratified random sampling techniques to draw a sample from the study population. The qualitative method focused on group discussion and in-depth interviews. The quantitative techniques employed questionnaires to 398 purposively selected subjects from the county projects. Data collection was from two main sources; primary and secondary. Secondary sources included relevant county documents, constitution, legislations, policy documents and reports among others. The Study employed questionnaires, Focus group discussion and Interview guide as its primary data collection method. Statistical Package for Social Science (SPSS) version 18.0 was used for analysis. Data was analyzed using descriptive and inferential statistics techniques and presented in tables and figures. The study findings indicated thatM&E methods, indicated by the coefficient of effectiveness (R2) which is also evidenced by F change 109.403>p-values (0.05). This implies that this variableis significant (since the p values<0.05) and therefore should be considered as part of effectiveness of M&E systems on the performance of County Governments projects. The study concludes that there are no effective and adequate projects monitoring and evaluation methods in place for County Government Projects, which can facilitate the achievement of desired projects performance and outcomes. The study recommends that the County Government should develop a clear M&E methods for each project with clear data collection, analysis, reporting and implementation methods. This Study recommends further research to be conducted in the other Regional County Economic Blocs.
Regardless of where the Igbo man is, within or without the Igbo regions, trust is one of the foremost vital tool in business dealings and negotiations. This study aims at revealing the kind of trust apparent, and unique to the Igbo-men in business, how the Igbo-men build trust in their business, the antecedents of trust building in Igbo land, and the impacts of those trust in business dealings and negotiation. Through the process of content data analysis, results were drawn from a percentage margin of answers and feedbacks generated from real life experiences and discussions from unstructured interview from selected Igbo-men across the five states of the south-east region of Nigeria, which shows that 70% percentage of the Igbos practice the affective based trust in business dealings and negotiations, while 18% percentage practice cognitive based trust, 7% engages in both affective and cognitive based trust, and the remaining 5% are undecided.
This study is directed to determine the role of government treasurer in state university in tax compliance. With the spirit of the state apparatus, especially the Civil Servant, in reporting the taxes, it is expected to become a continuously growing and infectious snowball to the taxpayers to report their taxes correctly, completely and clearly as well as to avoid administrative sanctions that are subject to such non-compliance. This study method used is qualitative, the source of this study is government treasurer. The use of this qualitative approach is based on the concept of natural setting, grounded theory, descriptive, more concerned with the process than the outcome, temporary design, and research results are negotiated and agreed upon. The results show that treasurers have a big role in tax compliance, but however, there are still many obstacles that must be faced in fulfilling their financial obligations. this research was conducted only in one state university, so that data that could be processed was very limited.
The corporate governance is a popular topic within two last decade, and the emerging economies are practicing &enhancing their performances. The review is conducted to assess the effectiveness of the corporate governance implications on firm’s performances. The study followed the deductive approach and the journal articles, and the reports have used the source of the review. As per the literature findings, the researcher developed a conceptual design for the case review. The independent variable is the corporate governance mechanism, and the dependent variable is organizations performances. Both independent and dependent variables comprise the different type of corporate governance practice and the different function of the organizational performances. The review found that all the types of corporate governance practices are influenced to the organizational performance and the better corporate governance mechanism can enhance all type of performances.
Innovative work behavior is likely to be an important need for the increasing performance of the hospital to provide the health public services. Theoretically and empirically, the behaviors be related to employee perception on management support, information technology and employee empowerment. The study aims to determine the effect of management supports and information technology on employee empowerment as well as their impact on the innovative work behaviors of the employee of dr. Zainoel Abidin District Hospital Banda Aceh. The study conducted of 302 employees of the hospital. The data collected by questionnaire and then the data is analyzed by statistical means of structural equation model (SEM). The study found that management support and information technology have a positive and significant effect on the employee empowerment and innovative work behavior. The employee empowerment mediates the effect of management supports and information technology on the innovative work behavior.
This research deals with an insight and analysis of the economy projectification in a smaller country, here represented by Croatia. The study was inspired by similar research conducted in Germany, Island and Norway and it is based on similar but partly adapted methodology. The objective of this study is to measure level of economy projectification in a smaller country, and to provide relevant data related for the level of project work. The random sample of 250 companies, from both public and private sectors, was selected across nine sectors of the economy. A stratified random sampling was drawn and interviews were conducted via telephone, so as on-line survey. While analysing collected data and considering the objectives of this paper, only basic statistical analyses were applied for calculating averages and mean values. This study confirmed that projectification trends and figures in a smaller country are similar to those in larger or developed countries. During the period of last five years, the projectification level of the Croatian economy was increased from 27% (in 2013.) to33% (in 2018.). The results show significant difference in projectification among the different sectors of economy, so as changes and trends over the recent time period.
This paper is designed to show how integrated process planning and cross employee planning can be a vital part to any business operation. It will also uncover how different integrated processes and employee relations will help a business to grow. Various topics ranging from enterprise resource planning, integrated planning in supply chains, the non-linear approach, innovation and digitalization coupled with cross training and empowerment, Human resources, and Manager Employee relations complement each other and could bring an organization together. Various thought processes and intellectual reasoning skills were instrumental in all consideration of this project. Many antiquated processes were changed over the years to update operations in the business world where conventional means were not effective. Integrating product planning and employee planning optimized operations both in the product and service industry and I will accent many of these optimizations. With recent technological advances and human relations tactics, project management and organization has been streamlined and works more productively than its predecessors. Regardless of the industry, integrated process planning, and cross employee planning could possible turn a dinosaur into a competitive part of the economy.
One of the problems in big cities are transportation.They solve this problem by providing mass transportation such bus or train. People use this facility to travel between surrounding cities or within the city. Jakarta recently has a new public transportation called TransJakarta which serving people travelingfrom nearby cities and in the city.In order to move or doing business between places people in Jakarta use TransJakarta This research aims to analyse ticket price, service quality and customer value toward customer satisfaction. We conducted a research by using questionnaires given to thepassangers and developed a model using a multiple regression to process the result from questionnaires. Samples were taken from The number of sample for this reseach was 130 customers taken from one bus stop which passengers traveled from BSD City to Grogol and Slipi. The results from partial testing showed that customer value andservice quality have effect on customer satisfaction while ticket price does not have effect on customer satisfaction.
This study aims to examine the mediating effect of Trust in the relationship between Perceived Website Quality (PWQual), eWOM, and Perceived Benefits on Consumer Attitudes Toward Online Shopping in Indonesia. The sample in this research are online shopping consumers in Indonesia there 118 respondents. The design research used a survey model purposive sampling method as a sampling technique. The data analyze in this research used Structural Equation Modeling (SEM) as an analysis technique with AMOS as analysis tools. This research shows that : Perceived Website Quality has a significant effect on Perceived Benefits and Trust, Perceived Benefits and Trust has a significant effect on Consumer Attitudes Toward Online Shopping, Perceived Website Quality has a significant effect on Consumer Attitudes Toward Online Shopping through Trust
Dairying is one of the livestock productions practiced almost all over Ethiopia, involving a vast number of small, medium, or large-sized, subsistence or market-oriented farms. However, the structure and performance of dairy sectors and its products marketing both for domestic consumption and for export is generally perceived poor in Ethiopia due to different challenges. These challenges vary across different production system to another and/or from one location to another. Among other challenges seasonality of production, spoilage (lack of milk collecting facilities), poor animal health and management, inadequate supply of quality feed, low productivity and genetics ,quality problem, weak vertical integration, absence processing plant, inadequate permanent trade routes and other facilities like feeds, water, holding grounds, lack or non-provision of transport, lack of access to land, ineffectiveness and inadequate infrastructural and institutional set-ups, prevalence of diseases, lack of credit and inadequate market information are dominant in Ethiopia. Therefore, market infrastructure facilities, producers cooperative, feed quality and quantity provision system need to be strengthen for effective dairy value chain development.
This research paper examines customer intention to reorder in respect to delivery service and product satisfaction. Our research model includes delivery service, satisfaction and reorder intention. Satisfaction in this research model work as mediating variable. A survey method was adopted to collect data, collected data were analysis using SPSS to see the correlation between variables. A significant relationship was found between delivery service and reorder intention as well as moderating role was also note with satisfaction and reorder intention.
This paper examines the impact of internet use on student performance. In this cross-sectional study, one hundred twenty survey responses were collected from plus two-level students from BirendranagarSurkhet. The respondents were selected from class 11 and 12 students randomly. Frequency of internet use, location of internet use, cooperation from teachers for internet learning and peer group influence on internet use for academic purpose has been analyzed with their academic performance.one sample t test was used to analyze the data. The finding concludes all these variables have positive impact if the student use internet for learning process. Similarly, the analysis shows that the student who used internet at home for learning purpose has found highest academic achievement.
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Concentration of Inpatient Health Care Providers in Poland
1. www.theijbmt.com 92|Page
The International Journal of Business Management and Technology, Volume 3 Issue 1 January - February 2019
ISSN: 2581-3889
Research Article Open Access
Concentration of Inpatient Health Care Providers in
Poland
Justyna Rój
Department of Operational Research
The Poznań University of Economics and Business,
Al.Niedpodległości 10; 61-875 Poznań
Abstract
The purpose of this study is to measure the concentration level of inpatient health care providers such as general hospitals,
psychiatric hospitals, chronic medical care home, nursing homes, hospices in Poland, which will allow to identify inequities to access
to inpatient health care services. The Herfindahl-Hirschman Index (HHI) was used to investigate the concentration level of the
inpatient health care providers sector in Poland, which is also treated in the literature as a proxy of competition. To understand how
market of each particular inpatient health care providers has become structured and thus competitive the data for inpatient health
care providers spanning all Poland for the period of 2010-2017 were collected. The concentration of inpatient health care providers
was measured based on the aggregated data at the voivodeship level and for general hospitals, it was measured separately in each of
the 16 voivodeships in Poland based on the aggregated data at the powiat level. This approach arises from the limitation in the
availability of data Data are collected from the public statistical system. The HHI indices support the assertion that in the period of
analysis the entire inpatient health care providers sector in Poland has not been at average concentrated – apart from the nursing
homes where the moderate level of concentration was identified. Moreover, the increase of HHI in analyzed period in case of hospices
and chronic medical care homes can be troublesome, because it can signal of growing concentration in the future and then getting
also less competitive. However, concentration of general hospitals when analyzed at the lower level of hospital structure appeared
uneven.
Keywords: health care, inpatieitn care, concentration, Herfindahl-Hirschman Index, Poland
I. INTRODUCTION
Both developed and developing countries are faced with the problem of inability to satisfy health needs of their
inhabitants [1]. Thus, most of industrialized countries have been developing their health care systems continuously in
purpose to improve their equality, efficiency as well as quality of health care. However, to devise an effective, fair,
accessible and cost-conscious healthcare system is difficult for any country [2]. To guarantee the rights to health
mentioned in the Constitution of World Health Organization, the realization of them must involve not only a concerted
and sustained effort to improve health across all populations but also reduction of inequities in the enjoyment health.
According to WHO, equity must be reached not only between countries but also within countries [3].
A common interpretation of equity in health care is that health care services ought to be allocated on the basis of medical
need, rather than on the basis of such features as race, income, gender or area of residence [4]. Equity matters as it refers
to fair opportunity for everyone to attain their full health potential regardless of biological or demographic, geographic,
social, economic status. It entails the minimization of differences in access, quality, coverage, use and utility of health
care between groups of the population categorized by above characteristics [5].
As a significant share of gross domestic product is consumed by the health services and especially for these provided in
the form of inpatient care, thus inpatient care seems to be also crucial from the point of view of society’s welfare [6]. The
difference between the inpatient and outpatient care is how long a patient must remain in the facility to have their
procedure to be performed. In case of inpatient care, the overnight hospitalization is required, which means that patients
must stay at the health care providers where their procedure was done for at least one night. During this time, they will
be supervised by nurses or doctors. In case of outpatient care, such procedures are performed, which do not require the
patients to spend night being supervised [7].
2. www.theijbmt.com 93|Page
Concentration of Inpatient Health Care Providers in Poland
Thus measuring concentration of inpatient health care providers is increasingly important for analysis of health care
markets as well as policies and as inpatient health care providers and especially general hospitals are the largest part of
health care systems in every developed country. Thus the purpose of this study is to fill an important gap in the
literature on health inequalities through empirical research on concentration of inpatient infrastructural resources such
as beds in Poland. Polish studies in this area are very limited. thus, the purpose of this article is the analysis of their level
concentration in Poland. The higher the level of concentration thus the distribution of particular resource can be very
uneven.
The literature has almost an exclusive focus on the U.S.health care market [8] and there is growing literature on hospital
concentration as well as competition in the Netherlands - for example [9] as well as some fragmented information on
hospital market concentration in other countries like Greece [10] the U.K. [11] or Taiwan [12] and Germany [13].
Considering the relevance of the Polish hospital sector for the whole health care system, there is surprisingly little
research addressing these issues. There are some in Poland but from the different context [14] In the context of the above
setting, the aim of this study is to calculate concentration measures for the Polish inpatient care market and to find out
the clear picture of how strong the concentration actually is. Moreover, these results are put within the context of the
health reforms that have caused this development, which may be of interest to policy makers.
II. THE POLISH HEALTH CARE SECTOR CHARACTERISTIC
The Republic of Poland is a country with the location in central and eastern Europe with both population of 38.1 million
and area of 312 685 km2 in 2018 [15]. It is also the largest country among the new Member States admitted to the EU
after 2004. The Human Development Index for Poland was 0.865 in 2018.
The elimination of geographical and social inequalities in health is being one of the strategic objectives of the past and
present National Health Programs in Poland [3]. However, the right to equity in health is also guaranteed by the Polish
Constitutions. As according to Article 68 of the 1997 Constitution of the Republic of Poland, all citizens, regardless of
their financial status have the right to equal access, which should be ensured by the public authorities. Thus, the Polish
Constitution of 1997 grants a general right to health care to every citizen as detailed conditions for as well as the scope
of, the provision of services shall be established by statute. Moreover, special health care should be granted to children,
pregnant women, handicapped people and persons of advanced age. In addition, public authorities are mandated to
combat epidemics illnesses and prevent the negative health consequences of environmental degradation. They should
also support the development of physical culture especially among children and adolescents [16].
In Poland, many reforms were performed. The national government budget has historically been the main source of
health care financing and radical change of this system happened in 1999 while the implementation of market economy
took placed earlier it means in 1989 [17]. In January 1999 - by introducing the 1997 General Health Insurance Act [18]- a
new general obligatory health insurance system entered into force, which changed the system of financing. And as a
result of this reform the purchaser and provider functions were split. It can be said that the decentralization of the
system was placed [19]. It means that a first step toward introducing elements of competition was made to ensure to
foster competition between providers in purpose to improve quality and efficiency.
These changes in Polish healthcare system to some extent follow principals of the Bismarck’s model as gradual
decentralization of management and financing have been implemented since the early 1990 [20]. Thus it has the
character of an insurance model, although in fact it can be thought of as a insurance – budget health care system with
the dominance of insurance [21].
The function of purchaser was taken over by – 16 regional Health Insurance Organizations (the so-called Sickness Funds
– one in each region) and one trade (nationwide) Health Insurance Organization. Thus funds for health care came from
two main sources the first from above insurance funds and second, government budgets (state, provinces or gminas)
continued to finance public health services [17]. Also in order to promote the efficient use of financial resources, a split
between the payer and the owners of health care institutions was introduced [22].
And the process of health care services purchase has been based on selective contracting between the payer/purchaser
(initially the Sickness Funds) and health care providers [3].
What is also important, that in this same year (1999), a new administrative organization of the country was introduced:
as powiats (districts/counties) were entered as the intermediate level of territorial self-government, between the gminas
(municipalities), at the lowest level, and the voivodeship (regions). It is important in the context of health care as powiat
authorities became the owners/funding bodies for the with the remaining public hospitals owned by the voivodeship
and medical universities and others (mainly the Ministry of Health). Moreover, the number of voivodeships was
reduced from 49 to 16. As a result of this reform and changes the ownership structure of especially public hospitals
became not only more complex but also more fragmented [23, 24].
Because of considerable differentiation of the number and quality of services in individual regions this system met with
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Concentration of Inpatient Health Care Providers in Poland
the criticism of new left - side government, which adopted of different solutions - instead of improving this system - it
means the law on general insurance in the National Health Fund, was enforced on April 1, 2003 [25]. Under this law
Health Insurance Organizations ceased to exist. They have been replaced by the National Health Fund with many
branches – each in one region. It meant that the public funds for health care was again centralized.
Shortly, the law on universal insurance in the National Health Fund met – this time - with the criticism of opposition. In
January 2004 it was legally qualified as not standing in accordance with the Constitution. As a result of it, the Seym of
the Republic of Poland passed on 30 July 2004 the law on health benefits financed from public means but the general
idea of insurance in National Health Fund left.
While, the major task of the NHF is to finance health services provided to the entitled population, it also manages the
process of contracting health services with public and non-public service providers (setting their value, volume and
structure), monitors the fulfillment of contractual terms and being in charge of contract accounting. The quality and
accessibility of health care services are to a certain extent influenced by the negotiated terms [25]. It means that NHF
regional branches are responsible for the entire process of contracting and as result of it, each regional branch of the
NHF is responsible for securing continuous provision of health care services for its population within the available
financial resources. All health care providers must meet certain criteria to be able to apply and compete for the contracts
with the NHF [16]. Thus the provision of is determined by health care service provider resources on the one hand while
also by the ability to finance the services by the NHF on the other hand [24].All principles regarding to contracting are
specified in the 2004 Law on Health Care Services Financed from Public Sources and are also regulated by the Civil
Code. The specification of contracting procedures for various types of service is provided in the decrees of the President
of the NHF [3].
Then the new regulations, which apply to among others inpatient health care – it means the 2011 Law on Therapeutic
Activity, which came into force on 1 July 2011'[26]. Apart from transformation of many public providers into companies
governed by the Commercial Code (i.e. a limited liability company or a joint stock company), the Act on Therapeutic
Activity introduced major changes to health care services provision. One of the most important was the introduction of a
new legal term, such as ‘therapeutic entity’, which replaced the term health care unit, introduced by the 1991 Act on
Health Care Units [23].
Some further fundamental changes took placed in 2011 by introducing the 2011 Law on Therapeutic Activity, health care
services can be provided by public and non-public health care units as well as by individual and group medical
practices. Therapeutic activity comprises inpatient services (in hospitals and other institutions, such as hospices or
nursing homes etc –article 8 of this Act) and outpatient services [23]. According to articles 8 and 9 of Act 2011 inpatient
care can be provided by either hospital or units different then hospitals such as: chronic medical care homes, nursing
homes and hospices. In hospices, comprehensive healthcare, psychological and social care for patients in the terminal
state are provided as well as a care for the families of these patients. In nursing homes, 24-hour health services are
provided that cover the care and rehabilitation of patients who do not require hospitalization, and provide them with
medicinal products and medical devices, rooms and meals appropriate to their health, as well as providing health
education for patients and their family members, and preparing them for self-care and self-care at home. In chronic
medical care homes, providing 24-hour health services that cover the care, care and rehabilitation of patients who do not
require hospitalization, and provide them with medicinal products needed to continue treatment, rooms and meals
appropriate to health, as well as providing health education for patients and their family members, and preparing these
people for self-care and self-care at home. While the hospital is characterized by offering permanent readiness to admit
patients and providing them with medical services [26]. General hospitals provide the most complex health services and
of the highest level of specialization thus they play an extremely important role in the health care system. That's why, so
much attention on their activity is paid by local communities especially on public hospitals especially that apart of
provision of health services they also often fulfill additional social tasks [27].
III. DATA AND METHOD
To understand how hospital markets have become structured and thus also competitive the data for general hospitals,
psychiatric hospitals, chronic medical care home, nursing homes, hospices spanning all Poland for the period of 2010-
2017 were collected. Data are collected from the public statistical system, it means from the Statistic Poland from the
database such as Knowledge Database Health and Health Care of Statistic Poland (Statistics Poland, 2010-2017) [28] and
also from the next one such as the Local Data Bank [29].
In this study, number of beds was used as the measure of inpatient health care activity because these data are available
but it also very good indicator of market share. Thus, the market shares of inpatient care providers in this study are
based on share of their beds. There are three different basic concepts, which are frequently applied in empirical research
to define the relevant geographic market to measure concentration and also competition i.e. geopolitical boundaries, the
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fixed radius and the patient flow technique [30]. For the purpose of this empirical research the approach of geopolitical
boundaries was chosen. In accordance with the 1998 Law, Polish territory is divided into three level. First, all territory is
divided into 16 voivodeships, which are further divided into powiats and these are divided into communities.
So, the concentration of hospitals was measured in each of the 16 voivodeship in Poland but because of limited access to
data of individual inpatient health care providers (at micro level) thus in this research the aggregated data at the
powiats (counties) level were used. As there is two types of powiats (counties) in Poland – rural and town with district
rights thus results will be also discussed in the context of different type of powiats (counties) as well.
As some regions in Poland can be differentiated according to their similarities in terms of economic, landscape,
ethnographic features. The division of voivodeships by region – according to Central Statistical Office is presented in
the table 3.1.
Table 3.1: The division of voivodeships by region in Poland in the years from 2010-2017
Region of Poland Voivodeship
Central region ○ łódzkie; ○ mazowieckie;
Southern region ○ małopolskie; ○ śląskie;
Eastern region ○ lubelskie; ○ podkarpackie;
○ podlaskie; ○ świętokrzyskie;
North – western region ○ lubuskie; ○ wielkopolskie;
○ zachodniopomorskie;
South – western region ○ dolnośląskie; ○ opolskie;
Northern region ○ kujawsko-pomorskie; ○ pomorskie;
○ warmińsko- mazurskie;
Source: Statistics Poland [15].
As the both period and level of analysis are mainly determined by the availability of data, but it is still sufficient to
examine the dynamics of chosen geographic market in the aspect of degree of concentration and also competition.
Because some of the most important changes in the health care system took place in the analyzed period thus it is quite
sufficient period for such analysis.
To measure the intensity (degree) of competition the Herfindahl-Hirschman Index (HHI) is employed. It is the common
and undoubtedly popular indicator for market structure, i.e. market concentration which is used in most studies.
The market concentration is an important aspect of industrial structure. HHI is used to represent the dispersion of firms
(hospitals) within one industry and thus it is the most commonly employed variable to indicate the degree of
competition [31].
In fact both the theory of economics and considerable empirical evidence suggest that, other things being equal, the
concentration of firms / hospitals is an important element of the market structure and a determinant of competition [32]
Thus, the Herfindahl-Hirschman Index (HHI) is also used as the proxy for hospital competition. The Herfindahl-
Hirschman index as a statistical measure of concentration, was developed independently by A. O. Hirschman (1945) [33]
and O. C. Herfindahl (1950) [34], however it is better known as the Herfindahl index [36]. It capture the number and
relative size of firms / hospitals and thus the HHI accounts for the number of hospitals in a market, as well as
concentration, by incorporating the relative size (that is, market share) of all hospitals in a market [32].
Because of the importance attached to market concentration as an indicator of competition and the relative ease of
calculating the HHI, this index serves as an efficient screening device for regulators and also as a planning tool [32].
HHIs are the standard measure used for example in empirical work in economics, health services research and other
disciplines. The HHI is also used by the U.S. antitrust authorities as a first starting point for more thorough
investigations if a merger or an acquisition is to be assessed [37].
The HHI can be defined as the sum of squared market (area) shares of hospitals participating in the market (area). And
it is expressed by the following formula [35]:
HHI = ∑n i=1 (MSi)2 (1)
where:
MSi - represents the market (area) share of hospital I as well as it stands for market
concentration
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n – number of hospitals in the market (area).
As this index is the sum of the squared market share of each inpatient car providers or hospital system in the market
(and ofently multiplied then by 10 000) then for example, a market with only one particular provider would have a
squared market share equal to 1, (and thus an HHI of 10 000). Conversely, a market with a large number of small
providers would have a small sum of squared market shares, and thus an HHI near 0. As is standard, the markets are
considered highly concentrated if they have an HHI greater than 0.25 (2500), moderately concentrated if they have an
HHI between 0.15 and 0.25 (1500 and 2500), unconcentrated if they have an HHI between 0.01 and 0.15 (100 and 1500),
and highly competitive if they have an HHI below 0.01 (100) [38]. Reductions in the number of providers and
concentration of marketshare into fewer of them increases the HHI, so that higher HHI values are consistent with less
competitive markets. Considering the extreme case of only one firm, i.e. a monopolist, it would have the highest level of
concentration (1 or 10 000). On the other hand, a perfectly competitive market would have the lowest level of
concentration, determined by the large number of providers / hospitals [35].
Thus the results of empirical analysis of concentration among hospitals in Poland are presented in the next sections.
IV. RESULTS AND DISCUSSION
This section gives a detailed account of research results. The number of hospitals varies over the period of analysis but
at average the empirical research includes the group of at average 916 general hospitals yearly and only 48 psychiatric
hospitals. The base of chronical medical care home is at the level of 381 at average yearly and 151 nursing homes and
almost a half less of hospices as 79 of them at average yearly. Generally the number of each in patient health care
providers presents the growing tendency. The relatively highest change can be observed for hospices as the number of
them increased by almost 42%, the smallest is in case of psychiatric hospitals as the increase by 2.13%, which nominally
means the increase by only such hospitals in period from 2010 to 2017. The number of rest kinds of inpatient health care
providers increased from 17.52% to 25.76% in the analyzed period.
Table 4.1: Number of inpatients care providers in Poland in years 2010 to 2017
year general
hospitals
psychiatric
hospitals
chronic
medical care
home
nursing
homes
hospices
2010 795 47 330 137 67
2011 814 48 367 138 79
2012 913 49 361 158 83
2013 966 48 379 152 73
2014 979 49 388 155 73
2015 956 48 408 152 82
2016 957 48 400 154 80
2017 951 48 415 161 95
average 916 48 381 151 79
change 19.62% 2.13% 25.76% 17.52% 41.79%
Source: Statistics Poland (2010-2017)[28]
According to the data, which are presented in the table 4.2, it is appeared that at average the highest base of beds are in
the disposition of general hospitals (185.656 beds), then of chronic medical care homes (22.827) and psychiatrist hospitals
(17.705). Relatively smaller base of beds is in the dispositions of nursing homes as at average it was 6.569 and in case of
hospices as it was 1.427. Moreover, the number of beds also increased in analyzed period at inpatient health care
providers apart from psychiatric hospitals, where slight decrease of beds took place.
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Table 4.2: Number of beds of inpatient care providers in Poland in years 2010 to 2017
year general
hospitals
psychiatric
hospitals
chronic
medical care
homes
nursing
homes
hospices
2010 181 077 17 750 19 250 5 688 1 126
2011 180 606 17 761 21 118 5 699 1 263
2012 188 820 17 529 21 187 6 755 1 389
2013 187 763 17 505 22 302 6 401 1 307
2014 188 116 17 736 23 099 7 027 1 334
2015 186 994 17 759 24 872 6 706 1 550
2016 186 607 17 868 25 176 6 749 1 640
2017 185 263 17 730 25 615 7 528 1 809
average 185 656 17 705 22 827 6 569 1 427
change 2.31% -0.11% 33.06% 32.35% 60.66%
Source: Statistics Poland (2010-2017)[28]
The calculated HHI for inpatient health care markets by each types of providers and year are presented in the table 4.3 .
And as HHI is also a proxy of competition thus this table displays the changes in the structure of Polish hospital market
from 2010 to 2017 , but also as HHI is a measure of providers concentration in an industry thus it is also the indicator of
inequality as well.
So, based on the results, it can be found that there is not concentration of general hospitals, psychistric hospitals, chronic
medical care home and hospices in any of the voidaships in Poland. Some moderate level of concentration can be
noticed only in case of nursing homes. So it means that the distribution of nursing homes beds is less even comparing
with the others inpatient care. However, the positive is that HHI decreased from 1170.99 in 2010 to 1147.39 in 2017. This
same tendency can be observed for the general hospitals, psychistric hospital as the HHI change from 816.61 in 2010 to
811.57 in 2017 for the first type of hospital and respectively from 844.12 in 2010 to 843.90 in 2017 for the psychiatric
hospitals. It is higly positive as apart from not existance of concentrations, there is also the improvement, which means
quite even distribution of them. That's way, the increase of HHI in case of hospices and chronic medical care homes can
be troublesome, because it can signal of growing concentration in the future and then getting also less competitive.
While, high levels of market concentration in the inpatient care sector are likely to result in market power which can
hamper competition and has negative effects on both patients and as well as third party payers. Then such distribution
of inpatieitn infrastructure might affect both the performance of the hospital sector as well as inequities in access to
services.
Table 4.3. The value of HHI* for inpatient care market in Poland in years 2010-2017
year general
hospitals
psychiatric
hospitals
chronic
medical care
homes
nursing
homes
hospices
2010 816.61 844.12 960.11 1170.99 882.97
2011 815.35 835.32 991.41 1138.68 887.26
2012 811.65 835.32 933.33 1232.69 877.29
2013 813.57 847.74 937.83 1088.07 918.16
2014 810.26 861.32 951.14 1112.53 886.75
2015 809.48 851.77 937.29 1179.49 929.43
2016 811.05 847.35 951.03 1098.14 946.21
2017 811.57 843.90 971.77 1147.39 902.84
average 812.44 846.81 954.24 1146.00 903.86
Source: Statistics Poland (2010-2017)[28]
* because of low level of the HHI, this apparoach as multipluing by 10000 was used.
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Concentration of Inpatient Health Care Providers in Poland
Because of availability of data it was possible to analyze the concentration level of general hospitals in deeper way
it means the the level of powiats. The general hospitals are characterized by multi-profile activity where patients stay no
longer than 30 days and are the main, dominant form of inpatient health care, however after the increasing tendency of
the number of them in the year from 2010- 2014 then the decrease can be observed as the number of general hospitals
changed from 979 in 2014 to 951 in the year 2017, it means by 19.62%. The relatively higher change can be observed in
case of zachodnipomorskie and opolskie as by 41.94% and 40.91% relatively. Only in one voivodeship the decreased can
be observed as in wielkopolskie at the level of 6.06% (table 4.4).
Table 4.4: Number of general hospitals in Poland in years 2010-2017 (excluding hospital branches)
Source: Statistics Poland; Local Data Bank [29]
According to the data, which are presented in the table 4.5, it is appeared that all general hospitals had in the disposition
the base of at average 185.656 bed yearly. The number of beds also increased from 181,077 in 2010 to 188,820 in 2012 and
then after slight variation again increased in 2014 to 188,116 and then the decrease can be observed to 185,263 in 2017.
Generally during all period of analysis, there is the increase of number of beds in general hospitals by 2,31%.
Table 4.5: Number of beds in general hospitals in Poland in years 2010-2017
Source: Statistics Poland, Local Data Bank [29]
voivodeship / year 2010 2011 2012 2013 2014 2015 2016 2017 change
DOLNOŚLĄSKIE 3,62%
KUJAWSKO-POMORSKIE 8,61%
LUBELSKIE -0,89%
LUBUSKIE 5,01%
ŁÓDZKIE -5,59%
MAŁOPOLSKIE 5,00%
MAZOWIECKIE 7,70%
OPOLSKIE 4,15%
PODKARPACKIE 6,94%
PODLASKIE -0,10%
POMORSKIE 6,29%
ŚLĄSKIE -3,46%
ŚWIĘTOKRZYSKIE -4,97%
WARMIŃSKO-MAZURSKIE 12,10%
WIELKOPOLSKIE -0,21%
ZACHODNIOPOMORSKIE 1,40%
TOTAL 2,31%
14 126 14 111 14 816 15 073 14 907 14 841 14 899 14 637
9 018 9 024 9 507 9 642 9 891 9 846 9 860 9 794
11 290 11 293 11 836 11 502 11 367 11 307 11 256 11 190
4 191 4 219 4 537 4 469 4 443 4 402 4 347 4 401
13 533 13 407 13 134 13 428 13 291 12 985 12 777 12 776
14 274 14 362 14 952 14 868 14 976 14 861 14 919 14 988
24 186 24 353 26 259 26 525 26 147 25 929 26 240 26 049
4 387 4 381 4 973 4 930 4 857 4 604 4 741 4 569
9 556 9 555 10 100 10 180 10 289 10 249 10 342 10 219
5 970 5 699 5 851 5 850 5 893 5 933 6 025 5 964
8 708 8 542 9 068 9 459 9 333 9 506 9 119 9 256
25 989 25 568 26 001 25 898 25 757 25 526 25 418 25 091
6 445 6 447 6 581 6 202 6 309 6 313 6 312 6 125
5 985 6 282 6 700 6 675 6 639 6 668 6 757 6 709
15 633 15 617 16 118 14 659 15 665 15 756 15 422 15 600
7 786 7 746 8 387 8 403 8 352 8 268 8 173 7 895
181 077 180 606 188 820 187 763 188 116 186 994 186 607 185 263
voivodeship / year 2010 2011 2012 2013 2014 2015 2016 2017 change
DOLNOŚLĄSKIE 67 72 80 80 83 79 82 81 20,90%
KUJAWSKO-POMORSKIE 38 39 42 42 42 43 40 41 7,89%
LUBELSKIE 42 45 50 58 59 57 55 53 26,19%
LUBUSKIE 19 20 25 25 25 26 24 24 26,32%
ŁÓDZKIE 61 62 66 74 71 68 67 65 6,56%
MAŁOPOLSKIE 71 69 75 84 85 81 90 87 22,54%
MAZOWIECKIE 98 106 115 120 120 112 108 118 20,41%
OPOLSKIE 22 23 28 28 29 28 30 31 40,91%
PODKARPACKIE 35 32 39 39 41 41 40 41 17,14%
PODLASKIE 30 31 33 35 36 34 37 36 20,00%
POMORSKIE 41 40 51 54 55 54 53 44 7,32%
ŚLĄSKIE 115 116 134 145 151 152 155 155 34,78%
ŚWIĘTOKRZYSKIE 22 22 25 25 25 25 25 25 13,64%
WARMIŃSKO-MAZURSKIE 37 39 43 42 44 43 45 44 18,92%
WIELKOPOLSKIE 66 65 67 64 63 65 60 62 -6,06%
ZACHODNIOPOMORSKIE 31 33 40 51 50 48 46 44 41,94%
Poland – total 795 814 913 966 979 956 957 951 19,62%
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It can be also noted that in case of 10 voivodeships, the increase of beds took place while in case of 6 of them the
decrease. The higher relatively increase too place in the warmińsko-mazurskie as it was 12.10% while the higher
decrease in łódzkie as it was by 5.59%. It means, that some variation and differentiation between voivodeships can be
observed.
Table 4.6: Number of persons per bed in general hospitals in Poland in years 2010-2017
Source: Statistics Poland; Local Data Bank [29]
Table 4.6. presents data regarding number of persons per bed. Generally the decrease can be observed as at level of
Poland by 2.50%. Even the number of hospitals and number of bed present growing tendency thus the number of
persons per bed shows decreasing tendency. Only in 4 voivodeships the increase took place as in łódzkie, śląskie,
świetokrzyskie and wielkopolskie. Especially the interesting situation can be noticed in the voivodeship wielkopolskie
as the decrease of number of general hospitals and beds was followed by the increase of number of persons per bed.
The descriptive statistics reported in Table 4.7. suggest that the average concentration results in an HHI of 0.1455 in 2010
and 0.1598 in 2017 with a median of 0.1478 in 2010 and 0.1580 in 2017. According to these numbers, at least 50% of Polish
hospitals (in fact powiats hospital systems as measured at the level of powiats ) are located in markets with a
concentration of 0.1580 in 2017 or above. These markets are above of 0.15, which usually serves as an indicator for a
moderately level of concentration. As the standard deviation presents that between 0.0460 in 2010 and 0.0522 in 2017, so
it shows that the hospital concentration is quite differentiated in Poland.
Table 4.7: Descriptive statistics of HHI of general hospitals in Poland for years 2010-2017
Source: author's calculation according to the data from Statistics Poland, Local Data Bank [29]
The calculated HHI for hospital markets by voivodeships and year are presented in the table 4.8. As HHI is a measure of
hospitals concentration in an industry thus it shows also the level of inequality. In addition to it, HHI is also a proxy of
competition thus this table displays the changes in the structure of Polish hospital market from 2010 to 2017.
So, based on the results, above all, it can be found that the concentration of general hospitals in the analyzed
voivodeship / year 2010 2011 2012 2013 2014 2015 2016 2017 change
DOLNOŚLĄSKIE 207 207 197 193 195 196 195 198 -4,20%
KUJAWSKO-POMORSKIE 233 233 221 217 211 212 211 213 -8,72%
LUBELSKIE 193 192 183 187 189 189 190 190 -1,54%
LUBUSKIE 244 243 226 229 230 231 234 231 -5,31%
ŁÓDZKIE 188 189 192 187 188 192 195 194 3,10%
MAŁOPOLSKIE 234 233 224 226 225 227 227 226 -3,30%
MAZOWIECKIE 218 217 202 200 204 206 204 207 -5,18%
OPOLSKIE 232 231 203 204 206 216 209 217 -6,60%
PODKARPACKIE 223 223 211 209 207 208 206 208 -6,57%
PODLASKIE 202 211 205 204 202 200 197 199 -1,68%
POMORSKIE 261 267 253 243 247 243 254 251 -3,79%
ŚLĄSKIE 178 181 178 178 178 179 179 181 1,84%
ŚWIĘTOKRZYSKIE 199 198 194 204 200 199 198 204 2,37%
WARMIŃSKO-MAZURSKIE 243 231 217 217 217 216 213 214 -12,04%
WIELKOPOLSKIE 220 221 215 237 222 221 226 224 1,67%
ZACHODNIOPOMORSKIE 221 222 205 205 205 207 209 216 -2,25%
Poland 213 213 204 205 205 206 206 207 -2,50%
Statistcs / year 2010 2011 2012 2013 2014 2015 2016 2017
average 0,1455 0,1451 0,1561 0,1564 0,1590 0,1567 0,1585 0,1598
standard deviation 0,0460 0,0441 0,0491 0,0487 0,0521 0,0492 0,0515 0,0522
median 0,1478 0,1445 0,1576 0,1567 0,1546 0,1556 0,1558 0,1580
maximum 0,2115 0,2064 0,2323 0,2340 0,2372 0,2295 0,2399 0,2458
minimum 0,0502 0,0503 0,0521 0,0534 0,0516 0,0519 0,0529 0,0532
coeffi cient of variation 0,0021 0,0019 0,0024 0,0024 0,0027 0,0024 0,0027 0,0027
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Concentration of Inpatient Health Care Providers in Poland
voivodeships is uneven. There are some voivodeships that have the value of HHI at around 0.0520 and there are
voivodeships with the value of HHI more then 0.20. It means, that the value of HHI of voivodeships with the most
concentrated market is around fourth times higher then the value of the least concentrated market.
Also, it was found out that the average value of HHI of analyzed hospitals within this period increased from 0.145 in
2010 to 0.155 in 2017, what means that at average their became more concentrated and thus less competitive. In case of
only one voivodeship the decrease of the HHI value can be noticed, which means the improvement in the level of
competition because of the decrease of concentration level. However, for the rest of voivodeships the increase can be
noticed which means the increase of concentration. The relatively highest increase took place in the following
voivodeships such as: warmińsko-mazurskie by 25.69% then mazowieckie – by 20.49% and in łódzkie – by 18.45%. This
voivodeships are located at the East and Central of Poland.
According to both the idea of HHI measurement and the empirical literature on hospital markets, this trend is likely to
have a negative effect on competition outcomes. High levels of market concentration in the hospital sector are likely to
result in market power which can hamper competition and has negative effects on both patients and as well as third
party payers. Then such distribution of hospital infrastructure might affect both the performance of the hospital sector
as well as inequities in access to services.
Table 4.8: The value of HHI for hospital market in Poland in years 2010-2017
Source: author's calculation according to the data from Statistcs Poland, Local Data Bank [29]
When the HHI takes the value between 0.15 to 0.25 then the hospital market is treated as moderately concentrated. In
Poland, the HHI for general hospitals took at average the value above 0.15 and less then 0.25 in the following provinces:
dolnośląskie, kujawsko-pomorskie, łodzkie, małopolskie, mazowieckie, opolskie, podlaskie, pomorskie, wielkopolskie,
zachodniopomorskie. Four of them had even more then 0.20 – it means łodzkie, mazowieckie, podlaskie,
zachodniopomorskie. At average the unconcentrated market are: lubelskie, lubuskie, podkarpackie, ślaskie,
świętokrzyskie, warmińsko – mazurskie with the HHI taken the value lower then 0.15 and in case of śląskie and
podkarpackie the HHI took the lowest value as 0.05 and 0.08 respectively. Such values displayed by the voivodeships
śląsie and podkarpackie showed that hospital market is quite competitive.
Based on the analysis of every voivodeships and powiats (counties), some tendency also was noticed. First at all that
there are some town with powiats (counties) rights which are characterized by the relatively high as at average 34-46
percent share of all hospitals beds in their respective province. These are the following cities: Warsaw (46%), Łódż (45%),
Szczecin (43%), Białystok (42%), Kraków (40%), Poznań (38%), Wrocław (35%), Gdańsk (34%), Bydgoszcz (34%), Lublin
(33%), which are located all over the territory of Poland.
voivodeship / year 2010 2011 2012 2013 2014 2015 2016 2017 average change
DOLNOŚLĄSKIE 0,14 0,13 0,16 0,15 0,15 0,15 0,15 0,16 0,15 12,64%
KUJAWSKO-POMORSKIE 0,15 0,14 0,16 0,16 0,16 0,16 0,16 0,17 0,16 13,60%
LUBELSKIE 0,13 0,13 0,14 0,14 0,14 0,14 0,14 0,14 0,14 11,53%
LUBUSKIE 0,12 0,12 0,11 0,11 0,11 0,12 0,12 0,12 0,12 -1,37%
ŁÓDZKIE 0,21 0,21 0,22 0,21 0,23 0,23 0,24 0,25 0,22 18,45%
MAŁOPOLSKIE 0,17 0,17 0,19 0,19 0,19 0,19 0,19 0,19 0,19 11,47%
MAZOWIECKIE 0,20 0,20 0,23 0,23 0,24 0,23 0,24 0,24 0,23 20,49%
OPOLSKIE 0,15 0,15 0,18 0,18 0,18 0,17 0,17 0,17 0,17 8,56%
PODKARPACKIE 0,08 0,08 0,08 0,08 0,09 0,09 0,09 0,09 0,08 15,00%
PODLASKIE 0,21 0,20 0,22 0,22 0,22 0,21 0,21 0,21 0,21 -2,15%
POMORSKIE 0,15 0,15 0,14 0,15 0,15 0,14 0,15 0,14 0,15 -6,02%
ŚLĄSKIE 0,05 0,05 0,05 0,05 0,05 0,05 0,05 0,05 0,05 6,03%
ŚWIĘTOKRZYSKIE 0,13 0,13 0,14 0,13 0,13 0,13 0,13 0,14 0,13 8,11%
WARMIŃSKO-MAZURSKIE 0,10 0,11 0,12 0,12 0,12 0,13 0,12 0,12 0,12 25,69%
WIELKOPOLSKIE 0,15 0,15 0,16 0,16 0,17 0,17 0,16 0,16 0,16 5,73%
ZACHODNIOPOMORSKIE 0,20 0,20 0,20 0,20 0,21 0,21 0,22 0,22 0,21 10,81%
average 0,145 0,145 0,156 0,156 0,159 0,157 0,158 0,160 0,155 9,82%
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Concentration of Inpatient Health Care Providers in Poland
4.9.: Cities with powiat status and their market shares measured by the number of beds in year 2010-2017
Source: author's calculation according to the data from Statistcs Poland, Local Data Bank [29]
All results were also analyzed taking into account the type of powiats (counties) and percent share of all hospitals beds
in their respective voivodeships. In this analysis, also the location of voivodeships in the geographical region (according
to table 3.1) was taken into account
The central region covers two voivodeships: mazowieckie and łódzkie. From the analysis presented above it is appeared
that those two voivodeships were one of the leading voivodeships in terms of market concentration in years 2010 - 2017.
Also in this region two cities with the highest percent share of all hospitals beds in their respective voivodeships are
located – it means: Warsaw with the 46 percent share of all hospitals beds in mazowieckie voivodeships and Łódż with
45 percent share of all hospitals beds in łódzkie voivodeship.
Southern region covers two voivodeships: małopolskie and śląskie. Voivodeship of śląskie was characterized as the one
with the lowest degree of hospital market concentration and relatively small. In fact, only one town with powiat
(counties) rights – it means Katowice – had at average 14 percent share of all hospitals beds in the voivodeship and the
rest of powiats of both types had from 0-6 percent share of all hospitals beds in this voivodeship. In case of małopolska,
the pattern is similar but with higher percent share of hospitals beds in the city of Krakow – it means 40 percent. The rest
of both types of powiats (counties) had at average 0-7 percent share of all hospitals beds in the voivodeships.
Eastern region covers four voivodeships: lubelskie, podkarpackie, podlaskie, świętokrzyskie. In the province of
lubelskie, the dominance of city Lublin could be seen. This city had 33 percent while the rest of voivodeships had of
from 0.004 to 7 percent share of all hospitals beds in this voivodeship. In the second voivodeship of this region -
podkarpackie - there was one city of Rzeszów with 22 percent at average in the analyzed period and the rest of powiats
with 1-9 percent share of all hospitals beds in this voivodeships. Third voivodeship of this region had one city –
Białystok – with the 42 percent share and two cities – Suwałki and Łomża – with 8.5 and 10.3 percent share of all
hospitals beds in the voivodeships respectively. The rest of powiats had between 0-5.6 percent share of all hospitals beds
in the voivodeship. The last of voivodeship in this region is świętokrzyskie with the dominance of city Kielce with the
29.5 percent share of all hospitals beds in the voivodeship. There were three powiats with 8 - 9 percent and the rest
powiats with the 1-7 percent share of all hospitals beds in the voivodeship.
Northern region of Poland covers three voivodeships: kujawsko-pomorskie, pomorskie, warmińsko-mazurskie. In the
kujawsko-pomorskie voivodeship, the city of Bydgoszcz had 34 percent then the following cities: Toruń - 14 percent,
Grudziąc - 10 percent and Wrocławek – 7 percent shares of all hospitals beds in the voivodeship. The rest of powiats had
0.32-5.55 percent share of all hospitals beds in the voivodeship. The second voivodeship – warmińsko- mazurskie
presented different pattern: the city of Olsztyn had 26 percent and city of Elbląg 17 percent share of all hospitals beds in
the voivodeship while the rest powiats were with the 0.67-7 percent share of all hospitals beds in the province. The last
voivodeship in this region – pomorskie – could be characterized by the city of Gdańsk with 34 percent and the city of
Gdynia with 10 percent share of all hospitals beds in the voivodeship. The rest of both types powiats had below 7.48
percent share of all hospitals beds in the voivodeship.
North-western region of Poland covers three voivodeships: lubuskie, wielkopolskie, zachodniopomorskie. In the
province of lubuskie there were two cities with the highest percentage share of all hospitals beds in the voivodeship.
These are: Gorzów Wielkopolski – 20 percent and Zielona Góra with 19 percent. The rest of powiats had from 1-9
percent share of all hospitals beds in the voivodeship apart from powiat nowosolski with more then 11 percent. In the
voivodeship of wielkopolska, only city of Poznań had 38 percent and the rest of both types of powiats had 0-6 percent
share of all hospitals beds in the voivodeship. In the third voivodeship of this region – it means – zachodniopomorskie –
the city of Szczecin had 43 percent and city of Koszalin had 9 percent with the rest of both types of powiats of 0-5
percent share of all hospitals beds in the voivodeship.
voivodeship 2010 2011 2012 2013 2014 2015 2016 2017 average
DOLNOŚLĄSKIE Wrocław 0,34 0,33 0,37 0,36 0,35 0,35 0,35 0,36 0,35
KUJAWSKO-POMORSKIE Bydgoszcz 0,32 0,31 0,35 0,34 0,34 0,34 0,35 0,35 0,34
LUBELSKIE Lublin 0,32 0,32 0,34 0,34 0,34 0,34 0,34 0,34 0,33
ŁÓDZKIE Łódź 0,43 0,43 0,44 0,43 0,46 0,45 0,46 0,47 0,45
MAŁOPOLSKIE Kraków 0,38 0,38 0,40 0,41 0,42 0,41 0,41 0,41 0,40
MAZOWIECKIE Warszawa 0,43 0,43 0,47 0,47 0,47 0,46 0,48 0,48 0,46
PODLASKIE Białystok 0,42 0,41 0,43 0,43 0,43 0,42 0,42 0,42 0,42
POMORSKIE Gdańsk 0,34 0,34 0,33 0,35 0,34 0,33 0,34 0,33 0,34
WIELKOPOLSKIE Poznań 0,36 0,36 0,37 0,37 0,39 0,39 0,38 0,38 0,38
ZACHODNIOPOMORSKIE Szczecin 0,41 0,41 0,42 0,42 0,43 0,43 0,44 0,44 0,43
name of city
with powiat
status
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Concentration of Inpatient Health Care Providers in Poland
South – western region of Poland covers two voivodeships: dolnośląskie and opolskie. In the dolnośląskie voivodeship
one city had 35 percent share of all hospitals beds in the voivodeship and it is Wrocław. The rest of both types powiats
had from 1-7 percent share of all hospitals beds in the voivodeship. Then in opolskie voivodeship, the city of Opole had
29 percent and one of another type of county - (powiat) nyski - 24 percent share of all hospitals beds in the voivodeship.
While the rest of powiats had between 3 to 9 percent share of all hospitals beds in the voivodeship.
Based on the above analysis it can be summed up that the pattern of market concentration across settlement
structures in Poland can be defined as moderately concentrated and thus moderately competitive with tendency to
higher degree of concentration and less competitiveness. In every voivodeship there is one to three dominant cities
because of the relatively high percentage share of all hospitals beds in the relevant voivodeship. Results also proved that
the concentration of general hospitals services measured by hospitals beds is uneven and thus the access to services can
be differential.
V. CONCLUSION
On basis of the HHI, this paper reports on a concentration level of inpatient health care providers. This study has several
major findings. Empirical results discussed above support the assertion that in the period of analysis the entire general
hospitals sector in Poland has been at average moderately concentrated and thus moderately competitive with the
growing tendency to higher concentration and less competitive. Moreover, the concentration of hospitals services is
diversified across the voivodeships of Poland and it is quite uneven. In case of others inpatient health care providers –
when making the analysis on more aggregated level of data – it appeared that the moderate level of concentration was
found in case of nursing homes. The analysis also shows that changes on the health care market which took place in the
analyzed period especially statutory changes regarding hospitals in 2011 affected the level of concentration and thus
competition.
However, as with most empirical studies, the findings are also limited mainly by the scope of available data set. As this
paper has relied on the aggregated data thus the validity conclusions is limited to some extend. This is why, the serious
efforts - to develop better sources of data to improve concentration and thus equity measurement should be taken by
government. It could have a large impact on studies of equity.
Later on, it is possible also to test whether the level of concentration has any influence on the quality and costs of
inpatients health care providers activities.
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