Refine
Year of publication
Document Type
- Conference Proceeding (45)
- Article (27)
- Working Paper (7)
- Book (2)
- Part of a Book (1)
Language
- English (82) (remove)
Is part of the Bibliography
- yes (82)
Keywords
- COVID-19 (2)
- eHealth (2)
- health information technology (2)
- Bass model (1)
- CEO (1)
- CEO-CIO relationship (1)
- Clinical handover (1)
- Common ground (1)
- Communication (1)
- Computerized patient records (1)
Institute
- Fakultät WiSo (81)
Background:
Contact tracing apps are potentially useful tools for supporting national COVID-19 containment strategies. Various national apps with different technical design features have been commissioned and issued by governments worldwide.
Objective:
Our goal was to develop and propose an item set that was suitable for describing and monitoring nationally issued COVID-19 contact tracing apps. This item set could provide a framework for describing the key technical features of such apps and monitoring their use based on widely available information.
Methods:
We used an open-source intelligence approach (OSINT) to access a multitude of publicly available sources and collect data and information regarding the development and use of contact tracing apps in different countries over several months (from June 2020 to January 2021). The collected documents were then iteratively analyzed via content analysis methods. During this process, an initial set of subject areas were refined into categories for evaluation (ie, coherent topics), which were then examined for individual features. These features were paraphrased as items in the form of questions and applied to information materials from a sample of countries (ie, Brazil, China, Finland, France, Germany, Italy, Singapore, South Korea, Spain, and the United Kingdom [England and Wales]). This sample was purposefully selected; our intention was to include the apps of different countries from around the world and to propose a valid item set that can be relatively easily applied by using an OSINT approach.
Results:
Our OSINT approach and subsequent analysis of the collected documents resulted in the definition of the following five main categories and associated subcategories: (1) background information (open-source code, public information, and collaborators); (2) purpose and workflow (secondary data use and warning process design); (3) technical information (protocol, tracing technology, exposure notification system, and interoperability); (4) privacy protection (the entity of trust and anonymity); and (5) availability and use (release date and the number of downloads). Based on this structure, a set of items that constituted the evaluation framework were specified. The application of these items to the 10 selected countries revealed differences, especially with regard to the centralization of the entity of trust and the overall transparency of the apps’ technical makeup.
Conclusions:
We provide a set of criteria for monitoring and evaluating COVID-19 tracing apps that can be easily applied to publicly issued information. The application of these criteria might help governments to identify design features that promote the successful, widespread adoption of COVID-19 tracing apps among target populations and across national boundaries.
Background:
Large health organizations often struggle to build complex health information technology (HIT) solutions and are faced with ever-growing pressure to continuously innovate their information systems. Limited research has been conducted that explores the relationship between organizations’ innovative capabilities and HIT quality in the sense of achieving high-quality support for patient care processes.
Objective:
The aim of this study is to explain how core constructs of organizational innovation capabilities are linked to HIT quality based on a conceptual sociotechnical model on innovation and quality of HIT, called the IQHIT model, to help determine how better information provision in health organizations can be achieved.
Methods:
We designed a survey to assess various domains of HIT quality, innovation capabilities of health organizations, and context variables and administered it to hospital chief information officers across Austria, Germany, and Switzerland. Data from 232 hospitals were used to empirically fit the model using partial least squares structural equation modeling to reveal associations and mediating and moderating effects.
Results:
The resulting empirical IQHIT model reveals several associations between the analyzed constructs, which can be summarized in 2 main insights. First, it illustrates the linkage between the constructs measuring HIT quality by showing that the professionalism of information management explains the degree of HIT workflow support (R²=0.56), which in turn explains the perceived HIT quality (R²=0.53). Second, the model shows that HIT quality was positively influenced by innovation capabilities related to the top management team, the information technology department, and the organization at large. The assessment of the model’s statistical quality criteria indicated valid model specifications, including sufficient convergent and discriminant validity for measuring the latent constructs that underlie the measures of HIT quality and innovation capabilities.
Conclusions:
The proposed sociotechnical IQHIT model points to the key role of professional information management for HIT workflow support in patient care and perceived HIT quality from the viewpoint of hospital chief information officers. Furthermore, it highlights that organizational innovation capabilities, particularly with respect to the top management team, facilitate HIT quality and suggests that health organizations establish this link by applying professional information management practices. The model may serve to stimulate further scientific work in the field of HIT adoption and diffusion and to provide practical guidance to managers, policy makers, and educators on how to achieve better patient care using HIT.
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: Crowding in emergency departments (ED) has a negative impact on quality of care and can be averted by allocating additional resources based on predictive crowding models. However, there is a lack in effective external overall predictors, particularly those representing public activity.
Objectives: This study, therefore, examines public activity measured by regional road traffic flow as an external predictor of ED crowding in an urban hospital.
Methods: Seasonal autoregressive cross-validated models (SARIMA) were compared with respect to their forecasting error on ED crowding data.
Results: It could be shown that inclusion of inflowing road traffic into a SARIMA model effectively improved prediction errors.
Conclusion: The results provide evidence that circadian patterns of medical emergencies are connected to human activity levels in the region and could be captured by public monitoring of traffic flow. In order to corroborate this model, data from further years and additional regions need to be considered. It would also be interesting to study public activity by additional variables.
Background: For more than 30 years, there has been close cooperation between Japanese and German scientists with regard to information systems in health care. Collaboration has been formalized by an agreement between the respective scientific associations. Following this agreement, two joint workshops took place to explore the similarities and differences of electronic health record systems (EHRS) against the background of the two national healthcare systems that share many commonalities.
Objectives: To establish a framework and requirements for the quality of EHRS that may also serve as a basis for comparing different EHRS.
Methods: Donabedian's three dimensions of quality of medical care were adapted to the outcome, process, and structural quality of EHRS and their management. These quality dimensions were proposed before the first workshop of EHRS experts and enriched during the discussions.
Results: The Quality Requirements Framework of EHRS (QRF-EHRS) was defined and complemented by requirements for high quality EHRS. The framework integrates three quality dimensions (outcome, process, and structural quality), three layers of information systems (processes and data, applications, and physical tools) and three dimensions of information management (strategic, tactical, and operational information management).
Conclusions: Describing and comparing the quality of EHRS is in fact a multidimensional problem as given by the QRF-EHRS framework. This framework will be utilized to compare Japanese and German EHRS, notably those that were presented at the second workshop.
Multinational health IT benchmarks foster cross-country learning and have been employed at various levels, e.g. OECD and Nordic countries. A bi-national benchmark study conducted in 2007 revealed a significantly higher adoption of health IT in Austria compared to Germany, two countries with comparable healthcare systems. We now investigated whether these differences still persisted. We further studied whether these differences were associated with hospital intrinsic factors, i.e. the innovative power of the organisation and hospital demographics. We thus performed a survey to measure the “perceived IT availability” and the “innovative power of the hospital” of 464 German and 70 Austrian hospitals. The survey was based on a questionnaire with 52 items and was given to the directors of nursing in 2013/2014. Our findings confirmed a significantly greater IT availability in Austria than in Germany. This was visible in the aggregated IT adoption composite score “IT function” as well as in the IT adoption for the individual functions “nursing documentation” (OR = 5.98), “intensive care unit (ICU) documentation” (OR = 2.49), “medication administration documentation” (OR = 2.48), “electronic archive” (OR = 2.27) and “medication” (OR = 2.16). “Innovative power” was the strongest factor to explain the variance of the composite score “IT function”. It was effective in hospitals of both countries but significantly more effective in Austria than in Germany. “Hospital size” and “hospital system affiliation” were also significantly associated with the composite score “IT function”, but they did not differ between the countries. These findings can be partly associated with the national characteristics. Indicators point to a more favourable financial situation in Austrian hospitals; we thus argue that Austrian hospitals may possess a larger degree of financial freedom to be innovative and to act accordingly. This study is the first to empirically demonstrate the effect of “innovative power” in hospitals on health IT adoption in a bi-national health IT benchmark. We recommend directly including the financial situation into future regression models. On a political level, measures to stimulate the “innovative power” of hospitals should be considered to increase the digitalisation of healthcare.
Objective: To pilot benchmark measures of health information and communication technology (ICT) availability and use to facilitate cross-country learning.
Materials and Methods: A prior Organization for Economic Cooperation and Development–led effort involving 30 countries selected and defined functionality-based measures for availability and use of electronic health records, health information exchange, personal health records, and telehealth. In this pilot, an Organization for Economic Cooperation and Development Working Group compiled results for 38 countries for a subset of measures with broad coverage using new and/or adapted country-specific or multinational surveys and other sources from 2012 to 2015. We also synthesized country learnings to inform future benchmarking.
Results: While electronic records are widely used to store and manage patient information at the point of care—all but 2 pilot countries reported use by at least half of primary care physicians; many had rates above 75%—patient information exchange across organizations/settings is less common. Large variations in the availability and use of telehealth and personal health records also exist.
Discussion: Pilot participation demonstrated interest in cross-national benchmarking. Using the most comparable measures available to date, it showed substantial diversity in health ICT availability and use in all domains. The project also identified methodological considerations (e.g., structural and health systems issues that can affect measurement) important for future comparisons.
Conclusion: While health policies and priorities differ, many nations aim to increase access, quality, and/or efficiency of care through effective ICT use. By identifying variations and describing key contextual factors, benchmarking offers the potential to facilitate cross-national learning and accelerate the progress of individual countries.
Background: Clinical information logistics is the backbone of care workflows inside and outside of hospitals. Due to the great potential of health IT to support clinical processes its contribution needs to be regularly monitored and governed. IT benchmarks are a well-known instrument to optimise the availability and use of IT by guiding the decision making process. The aim of this study was to translate IT benchmarking results that were grounded on a hierarchical workflow scoring system into an appropriate visualisation concept.
Methods: To this end, a three-dimensional multi-level model was developed, which allowed the decomposition of the highly aggregated workflow composite score into score views for the individual clinical workflows concerned and for the descriptors of these workflows. Furthermore this multi-level model helped to break down the score views into single and multiple indicator views.
Results: The results could be visualised per hospital in comparison to the results of organisations of similar size and ownership (peer reference groups) and in comparison to different types of innovation adopters. The multi-level model was implemented in a benchmark of 199 hospitals and evaluated by the chief information officers. The evaluation resulted in high ratings for the comprehensibility of the different types of views of the scores and indicators.
Conclusions: The implementation of the multi-level model in a large benchmark of hospitals proved to be feasible and useful in terms of the overall structure and the different indicator views. There seems to be a preference for less complex and familiar views.
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.
Background: Availability and usage of individual IT applications have been studied intensively in the past years. Recently, IT support of clinical processes is attaining increasing attention. The underlying construct that describes the IT support of clinical workflows is clinical information logistics. This construct needs to be better understood, operationalised and measured.
Objectives: It is therefore the aim of this study to propose and develop a workflow composite score (WCS) for measuring clinical information logistics and to examine its quality based on reliability and validity analyses.
Methods: We largely followed the procedural model of MacKenzie and colleagues (2011) for defining and conceptualising the construct domain, for developing the measurement instrument, assessing the content validity, pretesting the instrument, specifying the model, capturing the data and computing the WCS and testing the reliability and validity.
Results: Clinical information logistics was decomposed into the descriptors data and information, function, integration and distribution, which embraced the framework validated by an analysis of the international literature. This framework was refined selecting representative clinical processes. We chose ward rounds, pre- and post-surgery processes and discharge as sample processes that served as concrete instances for the measurements. They are sufficiently complex, represent core clinical processes and involve different professions, departments and settings. The score was computed on the basis of data from 183 hospitals of different size, ownership, location and teaching status. Testing the reliability and validity yielded encouraging results: the reliability was high with r(split-half) = 0.89, the WCS discriminated between groups; the WCS correlated significantly and moderately with two EHR models and the WCS received good evaluation results by a sample of chief information officers (n = 67). These findings suggest the further utilisation of the WCS.
Conclusion: As the WCS does not assume ideal workflows as a gold standard but measures IT support of clinical workflows according to validated descriptors a high portability of the WCS to other hospitals in other countries is very likely. The WCS will contribute to a better understanding of the construct clinical information logistics.