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Health IT adoption research is rooted in Rogers' Diffusion of Innovation theory, which is based on longitudinal analyses. However, many studies in this field use cross-sectional designs. The aim of this study therefore was to design and implement a system to (i) consolidate survey data sets originating from different years (ii) integrate additional secondary data and (iii) query and statistically analyse these longitudinal data. Our system design comprises a 5-tier-architecture that embraces tiers for data capture, data representation, logics, presentation and integration. In order to historicize data properly and to separate data storage from data analytics a data vault schema was implemented. This approach allows the flexible integration of heterogeneous data sets and the selection of comparable items. Data analysis is prepared by compiling data in data marts and performed by R and related tools. IT Report Healthcare data from 2011, 2013 and 2017 could be loaded, analysed and combined with secondary longitudinal data.
Frequent users of emergency departments (ED) pose a significant challenge to hospital emergency services. Despite a wealth of studies in this field, it is hardly understood, what medical conditions lead to frequent attendance. We examine (1) what ambulatory care sensitive conditions (ACSC) are linked to frequent use, (2) how frequent users can be clustered into subgroups with respect to their diagnoses, acuity and admittance, and (3) whether frequent use is related to higher acuity or admission rate. We identified several ACSC that highly increase the risk for heavy ED use, extracted four major diagnose subgroups and found no significant effect neither for acuity nor admission rate. Our study indicates that especially patients in need of (nursing) care form subgroups of frequent users, which implies that quality of care services might be crucial for tackling frequent use. Hospitals are advised to regularly analyze their ED data in the EHR to better align resources.
Das Ausmaß der Digitalisierung im Gesundheitswesen bemisst sich daran, wie gut die vorhandene IT Informationslogistik bedienen kann. Der IT-Report Gesundheitswesen ist eine Umfragereihe, die seit 16 Jahren den Digitalisierungsgrad in Krankenhäusern untersucht und eine Familie von Composite Scores bereitstellt, insbesondere den Workflow Composite Score (WCS) zur Messung der klinischen Informationslogistik. Dieser lag mit durchschnittlich 56 von 100 Punkten im Jahr 2017 nur knapp über der Marke von 50 Punkten. Weitere Sub-Scores wie z. B. der für den Aufnahmeprozess lagen mit 44 Punkten sogar darunter. Dieses Ergebnis zeigt, dass es ein großes Potenzial zur Verbesserung gibt, das ausgeschöpft werden muss, soll Digitalisierung ihren Effekt der Vernetzung, Transparenz, Datenanalytik und Wissensgenerierung entfalten.
Background
Diabetes mellitus is a major global health issue with a growing prevalence. In this context, the number of diabetic complications is also on the rise, such as diabetic foot ulcers (DFU), which are closely linked to the risk of lower extremity amputation (LEA). Statistical prediction tools may support clinicians to initiate early tertiary LEA prevention for DFU patients. Thus, we designed Bayesian prediction models, as they produce transparent decision rules, quantify uncertainty intuitively and acknowledge prior available scientific knowledge.
Method
A logistic regression using observational collected according to the standardised PEDIS classification was utilised to compute the six-month amputation risk of DFU patients for two types of LEA: 1.) any-amputation and 2.) major-amputation. Being able to incorporate information which is available before the analysis, the Bayesian models were fitted following a twofold strategy. First, the designed prediction models waive the available information and, second, we incorporated the a priori available scientific knowledge into our models. Then, we evaluated each model with respect to the effect of the predictors and validity of the models. Next, we compared the performance of both models with respect to the incorporation of prior knowledge.
Results
This study included 237 patients. The mean age was 65.9 (SD 12.3), and 83.5% were male. Concerning the outcome, 31.6% underwent any- and 12.2% underwent a major-amputation procedure. The risk factors of perfusion, ulcer extent and depth revealed an impact on the outcomes, whereas the infection status and sensation did not. The major-amputation model using prior information outperformed the uninformed counterpart (AUC 0.765 vs AUC 0.790, Cohen’s d 2.21). In contrast, the models predicting any-amputation performed similarly (0.793 vs 0.790, Cohen’s d 0.22).
Conclusions
Both of the Bayesian amputation risk models showed acceptable prognostic values, and the major-amputation model benefitted from incorporating a priori information from a previous study. Thus, PEDIS serves as a valid foundation for a clinical decision support tool for the prediction of the amputation risk in DFU patients. Furthermore, we demonstrated the use of the available prior scientific information within a Bayesian framework to establish chains of knowledge.
Background: The majority of health IT adoption research focuses on the later stages of the IT adoption process: namely on the implementation phase. The first stage, however, which is defined as the knowledge-stage, remains widely unobserved. Following Rogers’ Diffusion of Innovation Theory (DOI) this paper presents a research framework to examine the possible lack of shared IT awareness-knowledge, i.e. an information gradient, of two crucial stakeholders, the Chief Information Officer (CIO) and the Director of Nursing (DoN). This study shall answer the following research questions: (1.) Does this gradient exist? (2.) Which direction does it have? (3.) Are certain health IT (HIT) attributes associated with a potential gradient? (4.) Which determinants of diffusion go along with this gradient?
Method: Results of two surveys that focused on the topic “IT support of clinical workflows” from the viewpoint of CIOs and DoNs with corresponding datasets from 75 hospitals were used in a secondary data analysis. The gradient was operationalised by measuring the disagreement of CIOs and DoNs on the availability and implementation status of 29 IT functions. HIT attributes tested were relevance and market penetration of the IT functions, determinants of diffusion were inter-professional leadership and IT service density.
Results: The analysis revealed a significant disagreement on the availability of 9 out of 29 HIT functions. In 23 HIT functions, the CIOs reported a higher implementation status than the DoNs, which pointed to a trend for a unidirectional gradient. The disagreement was significantly lower when the relevance of the IT function was high. Both determinants of diffusion correlated significantly negative with the degree of disagreement.
Conclusion: This is the first study to empirically examine shared awareness-knowledge of two IT-stakeholders that are crucial for triggering IT adoption on the frontline level in hospitals. It could be shown that a gradient and thus a lack of shared awareness-knowledge existed and was associated with certain factors. In conclusion, hospitals should implement improved cooperation between IT staff and clinicians and IT service density when establishing the prerequisites for successful IT adoption processes.
Health IT and communication systems are indispensable in German hospitals for clinical as well as administrative process support. However, IT is often regarded as a “black box” for hospital CEOs. Thus, the question arises how can CEOs decide if they do not know what is in the box? In order to answer this question, half-structured interviews with 14 German hospital CEOs were conducted. They revealed three principle decision processes: the supported decision, the joint decision and the corporate level decision. In all cases, the hospital CEO and the CIO interacted to reach the final decision, most strongly in the joint decision mode and least strongly in the corporate decision mode. Only the joint decision mode definitely forced the CEO to open the “black box” of IT. In the era of digitalisation, however, CEOs must develop better competencies to decide over complex matters.
Health IT systems are employed to support continuity of care via information continuity, while management continuity is often neglected. This study aims at investigating issues of management continuity when developing a collaborative decision support system for chronic wounds. Thirty-three experts from a variety of professions and disciplines discussed problems and possible solutions in four workshops. The following topics emerged from the discussion: existing networks involving payers, responsibilities as well as good discharge management. These topics clearly address management continuity and are also relevant for the scenario of inter-professional wound care across different settings.
Background: IT is getting an increasing importance in hospitals. In this
context, major IT decisions are often made by CEOs who are not necessarily IT
experts. Objectives: Therefore, this study aimed at a) exploring different types of IT
decision makers at CEO level, b) identifying hypotheses if trust exists between these
different types of CEOs and their CIOs and c) building hypotheses on potential
consequences regarding risk taking and innovation. Methods: To this end, 14
qualitative interviews with German hospital CEOs were conducted to explore the
research questions. Results: The study revealed three major types: IT savvy CEOs,
IT enthusiastic CEOs and IT indifferent CEOs. Depending on these types, their
relationship with the CIO varied in terms of trust and common language. In case of
IT indifferent CEOs, a potential vicious circle of lack of IT knowledge, missing trust,
low willingness to take risks and low innovation power could be identified.
Conclusion: In order to break of this circle, CEOs seem to need more IT knowledge
and / or greater trust in their CIO.
Radiology has a reputation for having a high affinity to innovation – particularly with regard to information technologies. Designed for supporting the peculiarities of radiological diagnostic workflows, Radiology Information Systems (RIS) and Picture Archiving and Communication Systems (PACS) developed into widely used information systems in hospitals and form the basis for advancing the field towards automated image diagnostics. RIS and PACS can thus serve as meaningful indicators of how quickly IT innovations diffuse in secondary care settings – an issue that requires increased attention in research and health policy in the light of increasingly fast innovation cycles. We therefore conducted a retrospective longitudinal observational study to research the diffusion dynamics of RIS and PACS in German hospitals between 2005 and 2017. Based upon data points collected within the “IT Report Healthcare” and building on Rogers’ Diffusion of Innovation (DOI) theory, we applied a novel methodological technique by fitting Bayesian Bass Diffusion Models on past adoption rates. The Bass models showed acceptable goodness of fit to the data and the results indicated similar growth rates of RIS and PACS implementations and suggest that market saturation is almost reached. Adoption rates of PACS showed a slightly higher coefficient of imitation (q = 0.25) compared to RIS (q = 0.11). However, the diffusion process expands over approximately two decades for both systems which points at the need for further research into how innovation diffusion can be accelerated effectively. Furthermore, the Bayesian approach to Bass modelling showed to have several advantages over the classical frequentists approaches and should encourage adoption and diffusion research to adapt similar techniques.