Do different uses of performance measurement systems in hospitals yield different outcomes?

Background Inspired by the new public management movement, many public sector organizations have implemented business-like performance measurement systems (PMSs) in an effort to improve organizational efficiency and effectiveness. However, a large stream of the accounting literature has remained critical of the use of performance measures in the public sector because of the inherent difficulty in measuring output and the potential adverse effects of performance measurement. Although we acknowledge that PMSs may indeed sometimes yield adverse effects, we highlight in this study that the effects of PMSs depend on the way in which they are used. Purpose The aim of this study was to investigate various uses of PMSs among hospital managers and their effects on hospital outcomes, including process quality, degree of patient-oriented care, operational performance, and work culture. Methodology We use a survey sent to 432 Dutch hospital managers (19.2% response rate, 83 usable responses). For our main variables, we rely on previously validated constructs where possible, and we conduct ordinary least squares regressions to explore the relation between PMS use and hospital outcomes. Results We find that the way in which PMSs are used is associated with hospital outcomes. An exploratory use of PMS has a positive association with patient-oriented care and collective work culture. Furthermore, the operational use of PMSs is positively related to operational performance but negatively related to patient-oriented care. There is no single best PMS use that positively affects all performance dimensions. Practice Implications The way in which managers use PMSs is related to hospital outcomes. Therefore, hospital managers should critically reflect on how they use PMSs and whether their type of use is in line with the desired hospital outcomes. </p

Boundaries of Focus and Volume: An Empirical Study in Neonatal Intensive Care

Our study contributes to the scholarly debate whether organizational units should have a narrow focus and admit a homogeneous patient cluster or whether they should admit a pool of patient clusters. We investigate whether the benefits of increased volume through pooling patients outweigh the disadvantages of increased heterogeneity and pursue our analysis in the context of neonatal care. Our empirical studies relies on 4020 patient episodes collected in 18 German neonatal intensive care units and we distinguish between two patient clusters that differ with respect to the inherent medical risk and operational heterogeneity. Cluster 1 consists of very-low birth weight (VLBW) infants with increased risk of complications but similar service trajectories and lower operational heterogeneity. Cluster 2 contains non-VLBW infants with lower risk of complications but more diversity in disease patterns and higher operational heterogeneity. Our analysis shows that cluster volume, that is, the unit's absolute patient volume in a cluster, is positively related to process outcomes as indicated by decreasing length of stay. This relationship is found for both clusters. Regarding focus, we do not find any evidence of positive effects. In fact, we even find that cluster focus, that is, the unit's relative volume of the cluster, is detrimentally related to process outcomes for non-VLBW patients with lower risk of complications and more operational heterogeneity. This indicates that organizational units providing services for complex patients should not have a narrow focus, but should rather provide services for related patient clusters in order to achieve higher volume levels within the unit

Prioritization of surgical patients during the COVID-19 pandemic and beyond:A qualitative exploration of patients’ perspectives

IntroductionDuring the COVID-19 pandemic, prioritizing certain surgical patients became inevitable due to limited surgical capacity. This study aims to identify which factors patients value in priority setting, and to evaluate their perspective on a decision model for surgical prioritization.MethodsWe enacted a qualitative exploratory study and conducted semi-structured interviews with N = 15 patients. Vignettes were used as guidance. The interviews were transcribed and iteratively analyzed using thematic analysis.ResultsWe unraveled three themes: 1) general attitude towards surgical prioritization: patients showed understanding for the difficult decisions to be made, but demanded greater transparency and objectivity; 2) patient-related factors that some participants considered should, or should not, influence the prioritization: age, physical functioning, cognitive functioning, behavior, waiting time, impact on survival and quality of life, emotional consequences, and resource usage; and 3) patients’ perspective on a decision model: usage of such a model for prioritization decisions is favorable if the model is simple, uses trustworthy data, and its output is supervised by physicians. The model could also be used as a communication tool to explain prioritization dilemmas to patients.ConclusionSupport for the various factors and use of a decision model varied among patients. Therefore, it seems unrealistic to immediately incorporate these factors in decision models. Instead, this study calls for more research to identify feasible avenues and seek consensus

Big Data Health Care Innovations:Performance Dashboarding as a Process of Collective Sensemaking

Big data is poised to revolutionize health care, and performance dashboards can be an important tool to manage big data innovations. Dashboards show the progress being made and provide critical management information about effectiveness and efficiency. However, performance dashboards are more than just a clear and straightforward representation of performance in the health care context. Instead, the development and maintenance of informative dashboards can be more productively viewed as an interactive and iterative process involving all stakeholders. We refer to this process as dashboarding and reflect on our learnings within a large European Union–funded project. Within this project, multiple big data applications in health care are being developed, piloted, and scaled up. In this paper, we discuss the ways in which we cope with the inherent sensitivities and tensions surrounding dashboarding in such a dynamic environment. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/1677

Do different uses of performance measurement systems in hospitals yield different outcomes?

Background: Inspired by the new public management movement, many public sector organizations have implemented business-like performance measurement systems (PMSs) in an effort to improve organizational efficiency and effectiveness. However, a large stream of the accounting literature has remained critical of the use of performance measures in the public sector because of the inherent difficulty in measuring output and the potential adverse effects of performance measurement. Although we acknowledge that PMSs may indeed sometimes yield adverse effects, we highlight in this study that the effects of PMSs depend on the way in which they are used. Purpose: The aim of this study was to investigate various uses of PMSs among hospital managers and their effects on hospital outcomes, including process quality, degree of patient-oriented care, operational performance, and work culture. Methodology: We use a survey sent to 432 Dutch hospital managers (19.2% response rate, 83 usable responses). For our main variables, we rely on previously validated constructs where possible, and we conduct ordinary least squares regressions to explore the relation between PMS use and hospital outcomes. Results: We find that the way in which PMSs are used is associated with hospital outcomes. An exploratory use of PMS has a positive association with patient-oriented care and collective work culture. Furthermore, the operational use of P

eHealth Applications to Support Independent Living of Older Persons: Scoping Review of Costs and Benefits Identified in Economic Evaluations

__Background:__ eHealth applications are constantly increasing and are frequently considered to constitute a promising strategy for cost containment in health care, particularly if the applications aim to support older persons. Older persons are, however, not the only major eHealth stakeholder. eHealth suppliers, caregivers, funding bodies, and health authorities are also likely to attribute value to eHealth applications, but they can differ in their value attribution because they are affected differently by eHealth costs and benefits. Therefore, any assessment of the value of eHealth applications requires the consideration of multiple stakeholders in a holistic and integrated manner. Such a holistic and reliable value assessment requires a prof

Understanding the Uptake of Big Data in Health Care: Protocol for a Multinational Mixed-Methods Study

Background: Despite the high potential of big data, their applications in health care face many organizational, social, financial, and regulatory challenges. The societal dimensions of big data are underrepresented in much medical research. Little is known about integrating big data applications in the corporate routines of hospitals and other care providers. Equally little is understood about embedding big data applications in daily work practices and how they lead to actual improvements for health care actors, such as patients, care professionals, care providers, information technology companies, payers, and the society. Objective: This planned study aims to provide an integrated analysis of big data applications, focusing on the interrelations among concrete big data experiments, organizational routines, and relevant systemic and societal dimensions. To understand the similarities and differences between interactions in various contexts, the study covers 12 big data pilot projects in eight European countries, each with its own health care system. Workshops will be held with stakeholders to