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

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

Have Dutch Hospitals Saved Lives and Reduced Costs? A longitudinal patient-level analysis over the years 2013–2017

The purpose of this paper is to shed light on the ongoing Dutch health system reforms and identify whether hospital costs and hospital outcomes have changed over time. We present an empirical analysis that is based on granular micro-costing data and focuses on conditions for which mortality is indicative of outcome quality, that is, acute myocardial infarction (AMI), chronic heart failure (CHF), and pneumonia (PNE). We deploy a dataset of more than 80,000 inpatient episodes over 5 years (2013–2017) to estimate regression models that control for variation between patients and hospitals. We have three main findings. First, our results do not indicate significant outcome improvements over the years; that is, there is no time trend for mortality. Second, there is heterogeneity in cost developments: for patients who survive their inpatient stay, our data indicate that costs increase significantly by 0.9% per year for AMI patients, while costs decrease significantly by 1.7% per year for CHF patients and by 1.9% per year for PNE patients. For patients who pass away during their inpatient stay, our data do not indicate significant time trends. Third and finally, our results suggest the existence of substantial cost variation between hospitals.</p

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 discuss the findings, our recommendations, and the implementation. Dissemination is supported by visual representations developed to share the knowledge gained. Methods: This study will utilize a mixed-methods approach that combines performance measurements, interviews, document analysis, and cocreation workshops. Analysis will be structured around the following four key dimensions: performance, embedding, legitimation, and value creation. Data and their interrelations across the dimensions will be synthesized per application and per country. Results: The study was funded in August 2017. Data collection started in April 2018 and will continue until September 2021. The multidisciplinary focus of this study enables us to combine insights from several social sciences (health policy analysis, business administration, innovation studies, organization studies, ethics, and health services research) to advance a holistic understanding of big data value realization. The multinational character enables comparative analysis across the following eight European countries: Austria, France, Germany, Ireland, the Netherlands, Spain, Sweden, and the United Kingdom. Given that national and organizational contexts change over time, it will not be possible to isolate the factors and actors that explain the implementation of big data applications. The visual representations developed for dissemination purposes will help to reduce complexity and clarify the relations between the various dimensions. Conclusions: This study will develop an integrated approach to big data applications that considers the interrelations among concrete big data experiments, organizational routines, and relevant systemic and societal dimensions

e-health waardenmodel

Voor de structurele financiering van e-health is het belangrijk om de toegevoegde waarde hiervan inzichtelijk te maken. Dat gebeurt op dit moment op verschillende manieren. Soms kijkt men alleen naar de financiële opbrengsten voor de zorginstelling of leverancier, soms wordt ook de maatschappelijke waarde meegenomen. In het onderzoeksproject Waardemodel e-health ontwikkelde we een integraal model dat alle kosten en inspanningen afzet tegen alle baten en opbrengsten, voor verschillende stakeholders. In het rapport wordt een overzicht gegeven van de verschillende methoden om waarde te bepalen, met uitleg over het doel, voor- en nadelen van iedere methode. Daarnaast wordt het model uitgelegd en een handleiding gegeven hoe je met het model kunt werken