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Das Thema Digitalisierung ist in aller Munde – gerade auch im Bereich Krankenhaus. Allerdings noch nicht zuverlässig und im großen Stile valuiert sind die Fragen: Wie digitalisiert ist die Gesamtheit der deutschen Krankenhäuser tatsächlich? Wie entwickelt sich der Digitalisierungsgrad über die Zeit und im Vergleich zu anderen Nationen? Welchen Maßstab sollte man anlegen? Die Autoren stellen im folgenden Artikel ihren Ansatz für eine bundesweite Erfassung der Krankenhausdigitalisierung vor. Im Ergebnis weisen die betrachteten Krankenhäuser deutliche Optimierungspotenziale auf. Diese reichen von der mobilen Verfügbarkeit elektronischer Patientendaten und IT-Funktionen bis hinzu Fragen der Integration und Interoperabilität der im Einsatz befindlichen Systeme.
Background and purpose:
Clinical information logistics is a construct that aims to describe and explain various phenomena of information provision to drive clinical processes. It can be measured by the workflow composite score, an aggregated indicator of the degree of IT support in clinical processes. This study primarily aimed to investigate the yet unknown empirical patterns constituting this construct. The second goal was to derive a data-driven weighting scheme for the constituents of the workflow composite score and to contrast this scheme with a literature based, top-down procedure. This approach should finally test the validity and robustness of the workflow composite score.
Methods:
Based on secondary data from 183 German hospitals, a tiered factor analytic approach (confirmatory and subsequent exploratory factor analysis) was pursued. A weighting scheme, which was based on factor loadings obtained in the analyses, was put into practice.
Results:
We were able to identify five statistically significant factors of clinical information logistics that accounted for 63% of the overall variance. These factors were “flow of data and information”, “mobility”, “clinical decision support and patient safety”, “electronic patient record” and “integration and distribution”. The system of weights derived from the factor loadings resulted in values for the workflow composite score that differed only slightly from the score values that had been previously published based on a top-down approach.
Conclusion:
Our findings give insight into the internal composition of clinical information logistics both in terms of factors and weights. They also allowed us to propose a coherent model of clinical information logistics from a technical perspective that joins empirical findings with theoretical knowledge. Despite the new scheme of weights applied to the calculation of the workflow composite score, the score behaved robustly, which is yet another hint of its validity and therefore its usefulness.
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.
Benchmarking, sprich die Vergleichsanalyse von Prozessen mit festgelegtem Bezugswert, findet zunehmend Einzug in die Welt der Gesundheits-IT. Dabei spielen jedoch viele Faktoren zusammen, die einen einfachen Vergleich von IT-Kosten bei Weitem übersteigen. Eine Forschungsgruppe der Hochschule Osnabrück hat mit dem IT-Benchmark Gesundheitswesen ein Analysetool vorgelegt, das auch einen Länder- vergleich ermöglicht.
IT braucht Leadership
(2014)
Die Ergebnisse des IT-Reports Gesundheitswesen zeigen, dass der Pro-zess der Visitenvorbereitung, -durch-führung und -nachbereitung am besten durch IT unterstützt wurde, gefolgt von der OP- Vorbereitung, der OP-Nachbereitung und schließlich der Entlassung (Abbildung l). Von möglichen zehn Punkten in dem jeweiligen Prozess-Score erreichte im Mittel nur die Visite einen Wert über 6,0. Mit 5,3 erzielte der Entlassungsprozess einen deutlich niedrigeren Wert.
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.
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.
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.