Not every public sector is a field: evidence from the recent overhaul of the English NHS

ABSTRACT

A structural interpretation of institutionalism has become dominant in public management research. Yet, studies tend to assume an institutional-level phenomenon without specifying how an organizational field was identified or whether structural characteristics can indeed be found in the organizational population studied. This lacuna is illustrated by exploring the structural interpretation of the field construct in the case of the recent overhaul of English primary care. Findings demonstrate the need for a more robust application of institutionalism in empirical research. Possible research problems for public management and a future research agenda based on a more relational approach to fields are discussed.     

Healthcare professionals’ perceptions of risk in the context of genetic testing for the prediction of chronic disease: a qualitative metasynthesis

Advances in genomic technologies and a growing trend towards stratified and preventive approaches to medicine mean that increasing numbers of individuals may have access to information about their genetic makeup, and their risk of developing diseases. This is likely to impact on healthcare professionals involved in the delivery of genetic tests, or in supporting patients who are affected by a disease with a genetic risk factor. It is therefore important to understand healthcare professionals’ perceptions about providing these services, and how they feel about communicating information about genetic risk to patients. This paper provides a systematic review and metasynthesis of qualitative research exploring healthcare professionals’ perceptions of genetic risk in the context of predictive genetic testing for chronic disease. Healthcare professionals expressed a range of reservations about the utility of predictive testing in this context. Professionals judged patients’ understanding of risk information to be limited and subject to bias and a range of sociocultural influences. Concerns about the psychosocial impact of genetic risk information were frequently cited, both in relation to individual patients and the wider impact on their families and communities. The need for provision of multidisciplinary support was described. The concept of responsibility was also an important theme. Healthcare professionals recognized the responsibility that accompanies risk knowledge, and that ultimately this responsibility lies with the patient, not the provider. Our analysis suggests that professionals’ evaluation of the utility of predictive genetic testing is influenced not only by resource deficits, but may also be interpreted as a response to challenging ethical and social issues associated with genetic risk, that are not well aligned with current medical practice.     

Getting management accounting off the ground: post-colonial neoliberalism in healthcare budgets

Taking Modell's [(2014) The societal relevance of management accounting: an introduction to the special issue. Accounting and Business Research, 44 (2), 83–103] ‘societal relevance of management accounting’ agenda forward, and based on a cost accounting initiative in a Sri Lankan hospital, this paper examines how management accounting is implicated in societal relevance. It reports on a post-colonial neoliberal state's use of cost-saving experiments and the resultant emancipation of the individuals involved. It conducts a bottom-up analysis, from micro events in the hospital to policymaking at the level of the Provincial Council. This analysis suggests that cost accounting acts as a mediating instrument: it begins to loosen the old Keynesian post-colonial bureaucratic budget confinements, creates a social space for individuals to consider cost-saving experiments, and addresses wider policy concerns about hospital resource management. The story is illuminated by Gilles Deleuze's and Zigmund Bauman's ideas on post-panoptic societies: old confinements are being problematised and new flexible, ‘liquid’ spaces created, in which individuals are emancipated in terms of their ability to influence resource management within and beyond the organisational constituency.     

Patient and Public Involvement in Healthcare Quality Improvement: How organizations can help patients and professionals to collaborate

Abstract

Citizens across the world are increasingly called upon to participate in healthcare improvement. It is often unclear how this can be made to work in practice. This 4-year ethnography of a UK healthcare improvement initiative showed that patients used elements of organizational culture as resources to help them collaborate with healthcare professionals. The four elements were: (1) organizational emphasis on non-hierarchical, multidisciplinary collaboration; (2) organizational staff ability to model desired behaviours of recognition and respect; (3) commitment to rapid action, including quick translation of research into practice; and (4) the constant data collection and reflection process facilitated by improvement methods.     

Does intellectual capital mediate the relationship between HRM and organizational performance? Perspective of a healthcare industry in Taiwan

Previous studies indicate that the linkage between human resource management (HRM) practices and organizational performance is tenuous. Some key intermediate elements evidently have not been accounted for. In an era where intangibles have become the source of wealth and progress, intellectual capital could be one of the missing links. Therefore, this study predicts that the three components of intellectual capital, namely, human capital, relational capital, and organizational capital, mediate the relationship between HRM practices and organizational performance. Data from 277 hospitals, with a response rate of 56%, confirm the mediation role of intellectual capital in explaining the effect of HRM practices on organizational performance.     

Can locker box logistics enable more human-centric medical supply chains?

The fast flow of goods into hospitals is often stalled by the external–internal supply chain interface (i.e. the receipts department). This issue is particularly pertinent regarding the delivery of urgent items for specific patients or in the event of low inventory levels. An unattended electronic locker bank to which individual urgent items can be delivered and subsequently collected by the ‘user’ was proposed for Great Ormond Street Hospital in London, UK. The feasibility of this concept is quantified using a hill-climbing model operating with a significant database of consignment movements and qualitatively using staff interviews. Results indicate that a locker bank measuring 4 m length, 1.7 m height and 0.8 m depth, comprising 11 partitions, would be required to accommodate all urgent consignments for any given day. Staff perceptions of the concept were positive suggesting the locker would potentially improve the speed and quality of health care delivered to patients.     

Healthcare information systems: data mining methods in the creation of a clinical recommender system

Recommender systems have been extensively studied to present items, such as movies, music and books that are likely of interest to the user. Researchers have indicated that integrated medical information systems are becoming an essential part of the modern healthcare systems. Such systems have evolved to an integrated enterprise-wide system. In particular, such systems are considered as a type of enterprise information systems or ERP system addressing healthcare industry sector needs. As part of efforts, nursing care plan recommender systems can provide clinical decision support, nursing education, clinical quality control, and serve as a complement to existing practice guidelines. We propose to use correlations among nursing diagnoses, outcomes and interventions to create a recommender system for constructing nursing care plans. In the current study, we used nursing diagnosis data to develop the methodology. Our system utilises a prefix-tree structure common in itemset mining to construct a ranked list of suggested care plan items based on previously-entered items. Unlike common commercial systems, our system makes sequential recommendations based on user interaction, modifying a ranked list of suggested items at each step in care plan construction. We rank items based on traditional association-rule measures such as support and confidence, as well as a novel measure that anticipates which selections might improve the quality of future rankings. Since the multi-step nature of our recommendations presents problems for traditional evaluation measures, we also present a new evaluation method based on average ranking position and use it to test the effectiveness of different recommendation strategies.     

Use of a Markov decision process model for treatment selection in an asymptomatic disease with consideration of risk sensitivity

Some potentially dangerous diseases are completely asymptomatic. Their diagnosis as incidental findings of ever-more-sensitive medical imaging can leave patients and physicians in something of a quandary. The patient feels well, and potential interventions to stave off long-term deterioration or death bring with them immediate risks. We discuss the use of a Markov Decision Process (MDP) model (rather than Monte Carlo simulation of a Markov Model) to create a tool for analyzing individual treatment decisions for asymptomatic chronic diseases where a patient’s condition cannot improve. We formulate a finite-horizon MDP model to determine optimal treatment plans and discuss three distinct optimality criteria: (a) maximizing expected quality-adjusted-life years with and without discounting, (b) maximizing the expected number of life years in good health, and (c) maximizing the expected utility for number of years in good health. In (c) we assume exponential utility and consider different risk aversion factors reported in the medical literature. We illustrate the model’s use by considering asymptomatic intracranial aneurysm. Our model builds on a simulation model [19] created to examine treatment recommendations based on cost-effectiveness. We demonstrate that incorporating risk aversion leads to “no treatment” recommendations for some types of aneurysm. Furthermore, the use of alternate patient-selected criteria leads to recommendations that vary from [19] in several scenarios. We also discuss the use of the software as a decision support tool to help make individualized treatment recommendations and demonstrate that the computational performance of the algorithm makes its use feasible during a short office visit.