1. Introduction

The Health Information Technology for Economic and Clinical Health (HITECH) Act, enacted as part of the American Recovery and Reinvestment Act of 2009, promotes the adoption and use of Health Information Technology (HIT) by providing significant financial incentives and penalties to healthcare organizations. With large investments in information technology such as Electronic Health Record (EHR) systems, questions related to financial and productive payoffs become increasingly important. EHRs meet the goals of integrating patient medical history with current treatment thereby facilitating improved quality of care and increased productivity, but are expensive for organizations, potentially impacting financial performance and productivity (Kohli and Tan, 2016; Devaraj and Kohli, 2000; Li and Collier, 2000). Since the enactment of HITECH, the adoption rate of EHR systems has increased significantly.1 As of 2015, 84% of hospitals report adopting at least a basic EHR system, representing a nine-fold increase since 2008 (Henry et al., 2016). To encourage EHR adoption, the Centers for Medicare & Medicaid Services (CMS) provides incentive payments to hospitals that successfully demonstrate Meaningful Use of EHR technology. The meaningful use initiative supports several health care goals including the improvement of quality, safety, and efficiency; the reduction of health disparities; the engagement of patients and families in care decisions; the improvement of public health; and the ascertainment of privacy and security of patient health information. Ultimately, it is hoped that Meaningful Use compliance will result in better clinical outcomes, improved population health outcomes, increased transparency and efficiency, empowered individuals, and more robust research data on health systems (HealthIT.gov, 2015). Introduced in three stages, Meaningful Use Stage2 1 focused on data capture and sharing from 2011 to 2014. Stage 2 focuses on advance clinical processes from 2015 to 2017, and Stage 3 focuses on improved outcomes after 2017 (Holland, 2015). Meaningful Use sets specific objectives that hospitals must achieve to qualify for CMS incentive payments. For example, to meet Meaningful Use Stage 2 requirements for 2015 to 2017, EHR systems should support objectives such as protecting electronic health information and using clinical decision support systems to improve performance (CMS, 2016). In addition to CMS Meaningful use standards, HITECH also requires EHR systems be interconnected to improve the quality of health care. Because of these issues and requirements, Accounting Information Systems researchers continue to call for an expansion of healthcare research to include business process influences (Fichman et al., 2011). In theory, IT investment can improve healthcare service efficiency and generate positive financial returns (Menon et al., 2000). However, the expected efficiencies and quality improvements remain elusive. Adding to these concerns, previous research used organizational data developed prior to the HITECH Act and its financial incentives. With the rapid adoption of EHRs, an examination of contemporary IT environments is required.

The Health Information Technology for Economic and Clinical Health (HITECH) Act, enacted as part of the American Recovery and Reinvestment Act of 2009, promotes the adoption and use of Health Information Technology (HIT) by providing significant financial incentives and penalties to healthcare organizations. With large investments in information technology such as Electronic Health Record (EHR) systems, questions related to financial and productive payoffs become increasingly important. EHRs meet the goals of integrating patient medical history with current treatment thereby facilitating improved quality of care and increased productivity, but are expensive for organizations, potentially impacting financial performance and productivity (Kohli and Tan, 2016; Devaraj and Kohli, 2000; Li and Collier, 2000). Since the enactment of HITECH, the adoption rate of EHR systems has increased significantly.1 As of 2015, 84% of hospitals report adopting at least a basic EHR system, representing a nine-fold increase since 2008 (Henry et al., 2016). To encourage EHR adoption, the Centers for Medicare & Medicaid Services (CMS) provides incentive payments to hospitals that successfully demonstrate Meaningful Use of EHR technology. The meaningful use initiative supports several health care goals including the improvement of quality, safety, and efficiency; the reduction of health disparities; the engagement of patients and families in care decisions; the improvement of public health; and the ascertainment of privacy and security of patient health information. Ultimately, it is hoped that Meaningful Use compliance will result in better clinical outcomes, improved population health outcomes, increased transparency and efficiency, empowered individuals, and more robust research data on health systems (HealthIT.gov, 2015). Introduced in three stages, Meaningful Use Stage2 1 focused on data capture and sharing from 2011 to 2014. Stage 2 focuses on advance clinical processes from 2015 to 2017, and Stage 3 focuses on improved outcomes after 2017 (Holland, 2015). Meaningful Use sets specific objectives that hospitals must achieve to qualify for CMS incentive payments. For example, to meet Meaningful Use Stage 2 requirements for 2015 to 2017, EHR systems should support objectives such as protecting electronic health information and using clinical decision support systems to improve performance (CMS, 2016). In addition to CMS Meaningful use standards, HITECH also requires EHR systems be interconnected to improve the quality of health care. Because of these issues and requirements, Accounting Information Systems researchers continue to call for an expansion of healthcare research to include business process influences (Fichman et al., 2011). In theory, IT investment can improve healthcare service efficiency and generate positive financial returns (Menon et al., 2000). However, the expected efficiencies and quality improvements remain elusive. Adding to these concerns, previous research used organizational data developed prior to the HITECH Act and its financial incentives. With the rapid adoption of EHRs, an examination of contemporary IT environments is required.

With the rapid development of information technology, the competition becomes rigorous in medical service market, which prompts the hospitals to improve their working efficiency and quality. Hospital information system (HIS) [12], which obtains the medical management policies and measurements by data analysis, was introduced to support the hospital management by inputting/outputting the medical activities data on a mobile terminal. By providing some successful examples and the experiences of computer applications, Kuperman et al. [9] presented the guidance on how to design a HIS with few mistakes. Afterwards, from the aspects of hospital stays and hospitalization cost, Evans et al. [28] used the HIS to assess the effects of adverse drug affairs. Nevertheless, the limitations of the HISs gradually emerge in practice with the accumulation of the clinical and administrative data. In such a case, the hospital decision support system (HDSS) [34], which possesses various data analysis and data mining techniques, was provided to deal with the extensive data of medical management. By the HDSS, some new findings and laws of the clinical medicine and hospital management can be obtained. Since the HDSS is effective to assist the hospital management strategies, many researchers have made efforts to investigate the problems related to the HDSS. Zhang et al. [34] applied the online analytical processing (OLAP) into the HDSS to solve the medical decision-making problems. With data summary and visual tools, Barrett et al. [16] established the nonlinear models to design the decision support systems for pediatric pharmacotherapy. In addition, Shklovskiy-Kordi et al. [26] proposed a method to process the clinical data.

1. Introduction

2. Material and methods

3. Results

4. Conclusion

References

The growing financial problems of healthcare institutions contribute to the search for methods of properly distributing and clearly justifying resources. One of these is detecting the length of stay outliers (LOS) accounting for an important share of hospital costs. The purpose of this study is to analyze the factors facilitating identification of hospital LOS outliers. A total of 4570 patients were analyzed. To select the outliers, I used the inter-quartile method, using the median and the inter-quartile distance. The LOS outliers comprised 5,4% of the study sample and accounted for almost 15% of total hospital costs and 25% of total inpatient days. The median and range of the total costs for LOS outliers were (€) 3145,26 (1930,54-4670,88). The status of an LOS outlier was associated with age and type of admission. Eighty three percent of the LOS were admitted to the hospital in an acute way. Most of the LOS outliers (56% of all LOS outliers) were younger than the mean for the study population. There was no significant correlation between the reason for discharge, the type of department or the gender and being an LOS outlier. It is concluded that identifying the LOS outliers can contribute to better knowledge of hospital costs and help the management of these institutions control those costs.

Introduction

Concern over the rising resources consumed by health care costs has become widespread in many countries in recent years. The growing year to year financial problems of health care sector entities have contributed to the intensive search for the causes of this situation and the solutions that could change it (Russell-Weisz et al., 2004; Freitas et al., 2012; Russell-Weisz et al., 2000). One of the ways to do this is to improve the system of managing the costs in hospitals. To do this, hospitals have attempted to develop a systematic approach for identifying the exceptional episodes connected with extreme lengths of stay. Moreover, the length of stay is an important measure of resource utilization. For this reason, analyzing the LOS outliers is fundamental for the management and financing of hospitals. Many hospitals have used or still use length of stay for managing the efficiency of resource utilization Prospective payment schemes in health care often include special funding for cost outliers. In order to share the risk of an extremely long stay of a patient in hospital, in many health care financial systems high LOS outliers receive additional payments for each day above the high outlier threshold (Antioch et al., 2007; Russell-Weisz et al., 2004).The separate reimbursement of outliers is important for protecting both patients and managers (Freitas et al., 2012).

1. Introduction

2. Analysis

3. Conclusion and discussion

References

The aim of this paper is to discuss the effect of horizontal integration of hospitals on efficiency of hospitals. Whereas Czech hospitals use about 50% of all expenditure on healthcare, it is necessary to focus on their thriftiness and efficiency. Hospitals must work with limited economic resources and it is essential to know how to use these resources efficiently. In the last two decades we can see strong trends of hospitals integration. We now have five holdings and the last one was founded in January 2015. Annual reports were used for analysis from each hospital from 2004 to 2013, and also information from the Institute of Health Information and Statistics of the Czech Republic. Parts of the annual reports include economic and also non-economic results. This data was statistically analyzed and examined according to whether there was a significant improvement in values after integration. For example, a linear trend was used for evaluation by using a coefficient correlation and a t-test was used for statistical significance. One of the limitations of the research was that the research was based on only two specific samples existing in the Czech Republic. Other holdings have either a very short or a very long period of being integrated and therefore it is very difficult to find specific comparable information. Other limitations of this research were the choice of appropriate financial and also non-financial indicators. Results from analysis were compared with results of other published studies in other countries.

Introduction

In the Czech Republic until 1991 there was a system of financing health care by means of the state budget, but in 1992 the system was replaced, whereby health care is financed by health insurance. From this year on, public health insurance financed health care by means of payment according to performance. Hospital performance was shown in points and the value of points was derived from income and expenses of the health insurance. This unfortunately led to the pursuit of points, unnecessarily long hospital stays and of course also to a lack of financial resources for health care. From 1. 1. 1997 the Department of Health introduced a new system list of health performance, whereby the points value directly determined the charge in Koruns. In 2007 there was another fundamental change to the system and hospitals were financed by means of so-called across-the-board payments. The amount of this acrossthe-board payment was based on the assumption that the vast majority of hospital expense is fixed i.e. it is not determined by the number of patients or the number of actions undertaken. According to Gladkij et al. (2003), these expenses formed about 75 % of total hospital expenses. The amount of this across-the-board payment was established on the basis of actual performance done in the previous year.

1. Introduction

2. Literature

3. Findings

4. Conclusion

References

In medical sector a huge reform has started by health transformation program came into effect in 2003 in Turkey. The primary purpose is to provide to level up the service standard of the public hospitals with the same one of the private hospitals, even maintaining this service standard increasingly. The Public Hospitals Association was established for levelling up the service quality of the public hospitals and optimization of their financial capabilities in 2011. So, the necessary infrastructure is prepared for both serving the patients and making profit. Therefore, financial statements and various statistical information of 10 public hospitals in Zonguldak have been analysed. The implementation consists of data belong to 2009-2012 period. According to findings obtained the income of the public hospitals increased between 2009-2012 periods. However, the expenses have increased more.

Introduction

By implementation of “Health Transformation Program” in medical sector it took a new turn in 2003 in Turkey. The economical objective of this program is to provide the implementation of neo-liberal economical politics in medical sector, as well. By raising the standard of health service provided by the state, the Health Transformation Program offers an effective and productive service. This can only be carried out by placing more importance on financial management in public health institutions (Ercan et al., 2013, p.55-56). By optimization in cash management and debt follow-up the same result can be obtained in financial management of health institutions, as well (Bertoneche and Knight, 2001, p.90). Today’s technology is in a rapid and continuous change and development. Each passing day advancing technology is being used more for enhancing the quality of the health services. However the prices of newly discovered and produced medical devices are quite high and then this causes the health institutions making higher investment. The increasing costs are continously rising against undetermined prices which causes damage of the businesses, even collapsing of them (Gourieroux and Jasiak, 2007, p.1-2). Because as the debt increases, so does the financial risk (Ercan and Ban, 2008, p.189). The financial structure is deteriorated in this way (Civan and Dayi, 2013, p.13).

Primary health-care services are a major element of any health-care system (Raposo et al., 2009), as it brings health care closer to citizens’ place of residence and work, operating as their first level of contact with health-care system (Cueto, 2004). Public primary health-care services in Greece are delivered through a dual system of primary health-care centres, and hospital outpatient services, which are part of the National Healthcare System and Social Insurance Organization (Papanikolaou and Zygiaris, 2014; Fotiadis and Vassiliadis, 2013). Despite the efforts that have been undertaken over the past decade to modernize and improve the national health-care services (Papanikolaou and Ntani, 2008), its structural and functional efficiency needs to be further improved by upgrading the quality of the relevant services offered (Oikonomou et al., 2015). The ongoing recession puts even more to find ways to balance out the deteriorating government spending on public health system via an effective mechanism that will improve these services. This becomes even more important as the vast majority of individuals, due to tight economic conditions, report to the public system first, leaving the private as the last resort. For the state and health-care organizations to plan and deliver better primary health-care services, it is fundamental to identify and assess which service factors should be improved to meet some high standards and gain positive behavioral responses (Raposo et al., 2009; Meesala and Paul, 2016). Our intention is to go beyond the study of individual factors and their effect on the health-care system by measuring the quality of the delivered primary health-care services from hospital outpatient departments and especially the customeroriented quality assessment measures where several behavioral responses are rooted (Dagger et al., 2007; Oikonomou et al., 2015). Despite the fact that primary health-care services are a vital substance for a wellfunctioning society, there are only a few reliable and valid instruments to effectively measure service quality and tackle the complexities of the primary health-care service setting. Previous service quality conceptualization efforts usually use multidimensional models to assess service quality in the health-care context (Otani and Kurz, 2003; Dagger et al., 2007; Raposo et al., 2009; Sumaedi et al., 2016; Miranda et al., 2012; Shabbir et al., 2016). Based on the fact that customers tend to judge their experience as a whole rather than evaluating each single sub-process separately (Sousa and Voss, 2012), many studies consider service quality as a multidimensional reflectively measured higher-order construct (Sumaedi et al., 2016; Hossain et al., 2015). However, existing literature argues that the formative measurement approach with composite indicators might be more appropriate to uncover the formation of service quality perception (Collier and Bienstock, 2006; Carlson and O’Cass, 2011; Sousa and Voss, 2012).

Healthcare is considered a ‘credence’ good – an offering that consumers will never be able to evaluate owing to deficient medical knowledge (Bloom and Reeve, 1990). Additionally, conceptualising and measuring service quality in a healthcare setting is more important and simultaneously more complex (Taner and Antony, 2006). However, researchers need to come up with ways to measure healthcare service quality, because unless we measure we cannot manage and improve healthcare services (Lohr, 2015). The literature indicates that there is a variability and confusion in how quality is conceptualized and operationalized (Sower et al., 2001). Many researchers attempt to define and conceptualize hospital service quality. Pai and Chary (2013), for example, show that the Parasuraman et al., (1985, 1988) SERVQUAL/modified SERVQUAL questionnaire is conventionally practiced in healthcare. They also pointed out studies where SERVQUAL items have not loaded onto respective dimensions highlighting a five-component structure that is lacking, suggesting a new questionnaire needs developing. New instruments, designed for healthcare setting: PRIVHEALTHQUAL (Ramsaran-Fowdar, 2008) for private and PubHosQual (Aagja and Garg, 2010) for public settings, have emerged. Studies adopting these instruments are scarce because these scales are hospital specific and not a general scale that measures hospital service quality in any hospital context. An instrument that could measure hospital service quality (HSQ) in any hospital settings has gained importance. Pai and Chary (2016) proposed their conceptual framework for measuring hospital service quality using nine dimensions. Their framework, unlike other instruments such as SERVQUAL (Parasuraman et al., 1988), PRIVHEALTHQUAL (Ramsaran-Fowdar, 2008) and PubHosQual (Aagja and Garg, 2010) has an additional dimension (relationship) in line with researchers such as Carman (1990) and Reynoso and Moore (1995), who suggested adding service specific dimensions to SERVQUAL, there exists no empirical studies to support or refute their conceptual framework. As there are no research studies that used Pai and Chary’s framework (2016), our purpose is to empirically appraise this framework and addresses literature gaps.

1.1 Sampling

China covers a large territory, which can be divided into three parts by longitude: eastern part, central part and western part. Considering of the geographical influence and difference scales of cities, we randomly selected 200 managers at 50 different hospitals from 15 provinces such as Beijing, Shanghai, Guangdong, Jiangsu, Zhejiang, Fujian, Shandong, Hubei, Hunan, Henan, Heilongjiang, Guangxi, Shaanxi, Xinjiang, Sichuan and other provinces and autonomous regions. Among all those provinces, 7 were from eastern part, 6 from central part and 2 from western part.

1.2 Questionnaire Design

Considering of the actual situation of Chinese hospitals, a questionnaire named “hospital knowledge management implementation status questionnaire” with 22 questions was designed on the basis of literature review and experts appraisal[5-9]. In case that survey objects have different understanding of the concept “hospital knowledge management”, a common and uniform definition was given in the foreword of the questionnaire. Besides, the questionnaire was designed, revised and completed by four experts on management science, two statisticians, and three medical professionals.

1.3 Data Collection

200 questionnaires were distributed face to face or online. Twenty paper questionnaires were conducted face to face and 20 of them were returned. 180 internet-based surveys were conducted and 118 of them were returned. 138 valid questionnaires were returned totally (at least 2 questionnaires were collected in each of 50 hospitals) and effective response rate was 69.0%. Data were analyzed by descriptive study via qualitative analysis, quantitative analysis and analytic hierarchy process.

Surgical care in low- and middle-income countries (LMICs) has suffered from insufficient prioritization, especially in rural settings1–4. Low-income countries struggle with an insufficient surgical workforce; the surgical specialist workforce density is 0⋅7 per 100 000 population5, far below the recommendation1 of 20 per 100 000 population. In addition, surgical facilities and equipment are often inadequate6. The combination of lack of trained personnel and equipment has resulted in a lack of safe and affordable access to surgical care for 90 per cent of patients who need it, contributing to high rates of surgical morbidity and mortality in LMICs1. It is now recognized that surgical care has a central role in the management of many medical conditions1, but little is known about the cost of providing surgical care in LMICs. Because of a history of patients with conditions that need surgical intervention being referred to higher-level hospitals and the perception that higher-level hospitals should provide surgery, surgical care is often viewed as expensive compared with the medical management of other diseases2,3,7. However, a systematic review3 of the cost-effectiveness of surgical care showed that most essential surgical interventions, such as general surgery, caesarean sections and orthopaedic surgery, are cost-effective in LMICs. The Lancet Commission on Global Surgery recommended that caesarean section, laparotomy and open fracture treatment, collectively referred to as the ‘bellwether procedures’, be available to patients at district hospitals1. The bellwether procedures are important to provide timely access to these procedures at district hospitals, but their availability also correlates with a facility’s ability to perform a broad array of other essential surgical services1. However, in sub-Saharan Africa few district hospitals provide laparotomy8, and even fewer estimate its costs9. In Rwanda, the majority (82⋅5 per cent) of surgical interventions are performed at district hospitals, and over half of these interventions are caesarean sections10. Patients needing a laparotomy or open fracture treatment, however, are commonly referred to tertiary hospitals11. Over the past several years, Rwanda has been intensively training surgical specialists via the Rwanda Human Resources for Health Program12. In addition, the Rwandan Ministry of Health is decentralizing the provision of essential surgical care by establishing provincial hospitals as newly appointed rural referral hospitals13. As the pipeline of trained surgical providers expands to these rural hospitals where surgical infrastructure already exists, the next two procedures to be included in the surgical package are laparotomy and open fracture treatment. Knowing the cost of these procedures at rural African district hospitals is essential for planning for availability of laparotomy and determining the reimbursement package for treatment. The aim of this study was to examine the cost of laparotomy for patients with acute abdominal conditions at a rural district hospital in Rwanda.

Computed medical record database management is increasingly important as information and computer technology progress rapidly. Medical records contain treatment history and relevant experiences pertaining to the patients need to be documented accurately and efficiently. In many parts of the worlds, including Malaysia, clinical documentations are still being handwritten on forms and filed into paper medical records. The shortcomings of paper records are well identified, for example, illegibility and poorly organized records may lead to information gaps or inconsistencies, when used by another or even the same user later on. Hardcopies of documents are slow to be transferred around, with higher risk of being misplaced. In addition, when handled by multi-users in multi-locations, the quality of safekeeping can be significantly affected. [1, 2]. The advent of computer technology has introduced enormous possibilities for electronic documentation and usage of electronic medical records. The motivation of this system is to create a tailor-made computerized brain database management system for the Radiology Department of selected hospitals in Malaysia. This is achieved by studying the existing system and its problems, and then designed an appropriate database system. The work flow of the old filing system is first to create record, on which the diagnosis and treatment report are documented by various personnel. The report is then filed and stored in the department. This is repeated until the patient is discharged, where the record is then taken out and stored in the Medical Record Unit of the hospital. With respect to the scanning records, the medical images are also stored in the paper folder record. After the installation of the new system, the database will be used to deduce certain useful information about the brain infarction patients in the hospital. In Malaysia, stroke is the main cause of mortality and morbidity, after heart disease and cancer. Stroke is a multiple factorial disease regulated by modifiable and non-modifiable risk factors. Modifiable factors include a history of hypertension, diabetes mellitus, obesity, smoking and obstructive sleeping apnea syndrome. Nonmodifiable factors include age, sex and race. Stroke is known as a cerebrovascular accident (CVA), which is rapidly developing loss of brain function due to disturbance in the blood supply to the brain. Ischemia caused by blockage, or a hemorrhage is known as the common reason for stroke [3]. On brain imaging method, computed tomography (CT) and magnetic resonance imaging (MRI) are the most commonly imaging methods used in Malaysia. MRI has proven to have a better reliability and sensitivity than CT in brain imaging, and it is a proven research and diagnostic tool. However, CT scan is also widely available, being fast, easy, and less expensive than MRI [4 – 7].

The delivery of high-quality service is the key to success in service industries. In the present era of intense competition, monitoring and improving service quality is highly essential for developing efficiency and business volume (Anderson and Zeithamal, 1984; Babakus and Boller, 1992; and Garvin, 1983). In both manufacturing and service industries, quality improvement is the principal factor that impacts consumer satisfaction and consumer’s purchase intention (Oliver, 1980). Several scholars agree that the quality is critical to consumer’s satisfaction (Omar and Schiffman, 1995; Gremler et al., 2001; and Radwin, 2000). Several business organizations focus on service-quality issues to drive customer’s satisfaction above the rest (Kumar et al., 2008). The healthcare industry in developing countries like India, has recorded a relatively high growth rate with a high demand for its services from both foreign and local patients; despite constraints such as inadequate amount of hospital beds and shortage of highly qualified doctors. But, the growth could be sustained throughout several years that lie ahead (Burns, 2014). Delivery of high-quality service and building patient loyalty are considered to be critical anchors (Anderson and Zeithamal, 1984). The specific dimensions of quality service that contributes substantially to patient’s satisfaction need to be identified. Thus, hospital management can prioritize better their focus on such specific factors, despite the heavy reliance of patients on physicians who first treat them and also refers them to certain a hospital. The overall Indian healthcare market is worth US$65 billion (Burns, 2014). Healthcare industry in India is a source of employment and revenue with strong domestic demand, corporatization of healthcare, rise in innovation, influx of medical tourism, and government pushes. India spends just 4% of its GDP on healthcare, while USA spends 17% of its GDP, while the share of government national healthcare expenditure is 50% in USA compared to a little more than 25% in India (Burns, 2014). On the other hand, India has world-class medical facilities attracting a large number of medical tourists who get a high-quality medical care at the cost of just a fraction of what it costs in USA. In India, only middle and upper classes have access to quality healthcare. Healthcare expenditure is a major cause of household debt in India, since many patients borrow money or sell off their assets to meet their healthcare expenditure, as the majority of the people do not have medical insurance. The hospital industry has become quite competitive in recent times (Raju and Lonial, 2002). Hospitals are interested in identifying the most critical factors in hospitals that, if managed well, will ensure survival and success in the future. For this to happen, the strategic factors need to be identified. Some hospitals are also taking efforts to promote their business overseas in the ‘medical tourism’ segment. They could prioritize areas related to quality management and should determine them most astutely. This euphoria and excitement about healthcare industry is worth examining in the context of service quality. Particularly, after the competitive space becomes crowded and rules of the game get tougher in the sector, quality matters a lot for succeeding in the long run.

Framing the question Hospitals are hard organizations to change. Publicly owned and operated hospitals even more so. In many countries, both managers and staff anticipate, despite constant calls for improvements in efficiency, quality, and responsiveness, that little will be different tomorrow or next year. Similarly, politicians, seeking to outflank these intra-institutional expectations, have learned to introduce major reforms early in their term to maximize what leverage they have over public hospital managers and staff. This creates a narrow window for organizational change in public hospitals which, combined with the standard political hazards [1], still has only a relatively low probability of success, and thus further reinforces the view of hospital management and staff that ‘this too shall pass’. Conversely, while public hospitals remain broadly insulated from major policy-driven change, there continues to be rapid successful change in the practice of medicine. This can be seen in clinical treatments, diagnostic technology, in reduced lengths of stay and increased ambulatory treatment, all in spite of a shift to patients being older, more complex and with increasing amounts of chronic disease. Taken together, these conflicting trends result in most public hospital change being technical and functional rather than organizational and institutional. Even as clinical responses change relatively rapidly, departmental and institutional routines remain broadly insulated, ensuring organizational stability for many regular daily activities. This can be an important positive from the perspective of hospital staff, and, sometimes, patients, but not always for the latter if it means long waits in a traditional outpatient department or the other tedious things that patients have to do to accommodate ingrained hospital routines. In routine operating aspects, stability also can mean organizational stasis and inertia regarding clinical issues as well as larger policy and management objectives – an important negative from the perspective of health sector reform [2]. This intricate pattern of public hospitals’ internal resilience and external resistance can be observed in a variety of countries and in a range of different financial and institutional circumstances. Among the most visible examples have been the mixed success achieved over the past 20 years to eliminate unacceptably long waiting times for elective procedures in English and Swedish hospitals [3, 4]. Further examples can be observed in the slow pace of organizational and institutional change in public hospitals following major reform in the English NHS [5] and resistance to structural change in the Norwegian [6] health systems; the unsteady development of hospital level semi-autonomy in some newly built hospitals in some Spanish provinces [7], and the complexity of introducing elements of institutional self-management in Estonia [8]. Examples of similar reactions to efforts to introduce major organizational change can be found in Portugal [9] as well as in Israel [10].