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Objectives: eHealth and innovation are often regarded as synonyms - not least because eHealth technologies and applications are new to their users. This position paper challenges this view and aims at exploring the nature of eHealth innovation against the background of common definitions of innovation and facts from the biomedical and health informatics literature. A good understanding of what constitutes innovative eHealth developments allows the degree of innovation to be measured and interpreted.
Methods: To this end, relevant biomedical and health informatics literature was searched mainly in Medline and ACM digital library. This paper presents seven facts about implementing and applying new eHealth developments hereby drawing on the experience published in the literature.
Results: The facts are: 1. eHealth innovation is relative. 2. Advanced clinical practice is the yardstick. 3. Only used and usable eHealth technology can give birth to eHealth innovatio. 4. One new single eHealth function does not make a complex eHealth innovation. 5. eHealth innovation is more evolution than revolution. 6. eHealth innovation is often triggered behind the scenes; and 7. There is no eHealth innovation without sociocultural change.
Conclusions: The main conclusion of the seven facts is that eHealth innovations have many ingredients: newness, availability, advanced clinical practice with proven outcomes, use and usability, the supporting environment, other context factors and the stakeholder perspectives. Measuring eHealth innovation is thus a complex matter. To this end we propose the development of a composite score that expresses comprehensively the nature of eHealth innovation and that breaks down its complexity into the three dimensions: i) eHealth adoption, ii) partnership with advanced clinical practice, and iii) use and usability of eHealth. In order to better understand the momentum and mechanisms behind eHealth innovation the fourth dimension, iv) eHealth supporting services and means, needs to be studied. Conceptualising appropriate measurement instruments also requires eHealth innovation to be distinguished from eHealth sophistication, performance and quality, although innovation is intertwined with these concepts. The demanding effort for defining eHealth innovation and measuring it properly seem worthwhile and promise advances in creating better systems. This paper thus intends to stimulate the necessary discussion.
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.
Information Technology (IT) continues to evolve and develop with electronic devices and systems becoming integral to healthcare in every country. This has led to an urgent need for all professions working in healthcare to be knowledgeable and skilled in informatics. The Technology Informatics Guiding Education Reform (TIGER) Initiative was established in 2006 in the United States to develop key areas of informatics in nursing. One of these was to integrate informatics competencies into nursing curricula and life-long learning. In 2009, TIGER developed an informatics competency framework which outlines numerous IT competencies required for professional practice and this work helped increase the emphasis of informatics in nursing education standards in the United States. In 2012, TIGER expanded to the international community to help synthesise informatics competencies for nurses and pool educational resources in health IT. This transition led to a new interprofessional, interdisciplinary approach, as health informatics education needs to expand to other clinical fields and beyond.
In tandem, a European Union (EU) - United States (US) Collaboration on eHealth began a strand of work which focuses on developing the IT skills of the health workforce to ensure technology can be adopted and applied in healthcare. One initiative within this is the EU*US eHealth Work Project, which started in 2016 and is mapping the current structure and gaps in health IT skills and training needs globally. It aims to increase educational opportunities by developing a model for open and scalable access to eHealth training programmes. With this renewed initiative to incorporate informatics into the education and training of nurses and other health professionals globally, it is time for educators, researchers, practitioners and policy makers to join in and ROAR with TIGER.
The TIGER Initiative
(2016)
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: While health informatics recommendations on competencies and education serve as highly desirable corridors for designing curricula and courses, they cannot show how the content should be situated in a specific and local context. Therefore, global and local perspectives need to be reconciled in a common framework.
Objectives: The primary aim of this study is therefore to empirically define and validate a framework of globally accepted core competency areas in health informatics and to enrich this framework with exemplar information derived from local educational settings.
Methods: To this end, (i) a survey was deployed and yielded insights from 43 nursing experts from 21 countries worldwide to measure the relevance of the core competency areas, (ii) a workshop at the International Nursing Informatics Conference (NI2016) held in June 2016 to provide information about the validation and clustering of these areas and (iii) exemplar case studies were compiled to match these findings with the practice. The survey was designed based on a comprehensive compilation of competencies from the international literature in medical and health informatics.
Results: The resulting recommendation framework consists of 24 core competency areas in health informatics defined for five major nursing roles. These areas were clustered in the domains “data, information, knowledge”, “information exchange and information sharing”, “ethical and legal issues”, “systems life cycle management”, “management” and “biostatistics and medical technology”, all of which showed high reliability values. The core competency areas were ranked by relevance and validated by a different group of experts. Exemplar case studies from Brazil, Germany, New Zealand, Taiwan/China, United Kingdom (Scotland) and the United States of America expanded on the competencies described in the core competency areas.
Conclusions: This international recommendation framework for competencies in health informatics directed at nurses provides a grid of knowledge for teachers and learner alike that is instantiated with knowledge about informatics competencies, professional roles, priorities and practical, local experience. It also provides a methodology for developing frameworks for other professions/disciplines. Finally, this framework lays the foundation of cross-country learning in health informatics education for nurses and other health professionals.
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.
Background
Against the background of a steadily increasing degree of digitalization in health care, a professional information management (IM) is required to successfully plan, implement, and evaluate information technology (IT). At its core, IM has to ensure a high quality of health data and health information systems to support patient care.
Objectives
The goal of the present study was to define what constitutes professional IM as a construct as well as to propose a reliable and valid measurement instrument.
Methods
To develop and validate the construct of professionalism of information management (PIM) and itsmeasurement, a stepwise approach followed an established procedure from information systems and behavioral research. The procedure included an analysis of the pertaining literature and expert rounds on the construct and the
instrument, two consecutive and comprehensive surveys at the national and international level, exploratory and confirmatory factor analyses as well as reliability and validity testing.
Results
Professionalism of information management was developed as a construct consisting of the three dimensions of strategic, tactical, and operational IMas well as of the regularity and cyclical phases of IM procedures as the two elements of professionalism.
The PIM instrument operationalized the construct providing items that incorporated IM procedures along the three dimensions and cyclical phases. These procedures had to be evaluated against their degree of regularity in the instrument. The instrument proved to be reliable and valid in two consecutive measurement phases
and across three countries.
Conclusion
It can be concluded that professionalism of information management is a meaningful construct that can be operationalized in a scientifically rigorous manner. Both science and practice can benefit from these developments in terms of improved self-assessment, benchmarking capabilities, and eventually, obtaining a better understanding of health IT maturity.
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
Digital health technologies enable patients to make a personal contribution to the improvement of their health by enabling them to manage their health. In order to exploit the potential of digital health technologies, Internet-based networking between patients and health care providers is required. However, this networking and access to digital health technologies are less prevalent in sociodemographically deprived cohorts. The paper explores how the use of digital health technologies, which connect patients with health care providers and health insurers has changed during the COVID-19 pandemic.
Methods
The data from a German-based cross-sectional online study conducted between April 29 and May 8, 2020, were used for this purpose. A total of 1.570 participants were included in the study. Accordingly, the influence of sociodemographic determinants, subjective perceptions, and personal competencies will affect the use of online booking of medical appointments and medications, video consultations with providers, and the data transmission to health insurers via an app.
Results
The highest level of education (OR 1.806) and the presence of a chronic illness (OR 1.706) particularly increased the likelihood of using online booking. With regard to data transmission via an app to a health insurance company, the strongest increase in the probability of use was shown by belonging to the highest subjective social status (OR 1.757) and generation Y (OR 2.303). Furthermore, the results show that the higher the subjectively perceived restriction of the subjects' life situation was due to the COVID-19 pandemic, the higher the relative probability of using online booking (OR 1.103) as well as data transmission via an app to a health insurance company (OR 1.113). In addition, higher digital literacy contributes to the use of online booking (OR 1.033) and data transmission via an app to the health insurer (OR 1.034).
Conclusions
Socially determined differences can be identified for the likelihood of using digital technologies in health care, which persist even under restrictive conditions during the COVID-19 pandemic. Thus, the results indicate a digital divide with regard to the technologies investigated in this study.
Introduction: Handovers are a central process for ensuring information continuity in patient care and, therefore, possess a major influence on patient safety as errors due to poor handovers can lead to life-threatening events. Education to improve handovers and ensure safe patient care can be supported by using critical incident reporting systems (CIRS). The aim of the study is to perform a content analysis of a national CIRS-database with regard to identifying adverse events in handovers situations and to derive competencies for the development of continuing education from these findings.
Methods: A meta model served as a research framework to merge the empirical findings with the London protocol of analysing critical events and the Canadian framework of safety competencies. Relevant cases to be investigated were searched in a freely accessible German CIRS database.
Results: A total of 253 case descriptions were found and analysed. Team factors emerged as the most frequently reported influencing factors following the analysis of the London protocol. Communication errors and missing information as well as a lack of appropriate standards and processes appeared to be the main reasons for critical events to occur. Most of the events happened in units involving surgery and intensive care. A mapping of patient safety competences with the reasons for critical events was conducted in order to determine the practical, concrete and handover related competencies.
Conclusion: Data from a CIRS database and theoretical frameworks can be combined to extract meaningful information about patient safety risks in handover situations. The results are useful for developing curricula to improve handovers based on patient safety competencies.
Background: IT adoption is a process that is influenced by different external and internal factors. This study aimed
1. to identify similarities and differences in the prevalence of medical and nursing IT systems in Austrian and German hospitals, and
2. to match these findings with characteristics of the two countries, in particular their healthcare system, and with features of the hospitals.
Methods: In 2007, all acute care hospitals in both countries received questionnaires with identical questions. 12.4% in Germany and 34.6% in Austria responded.
Results: The surveys revealed a consistent higher usage of nearly all clinical IT systems, especially nursing systems, but also PACS and electronic archiving systems, in Austrian than in German hospitals. These findings correspond with a significantly wider use of standardised nursing terminologies and a higher number of PC workstations on the wards (average 2.1 PCs in Germany, 3.2 PCs in Austria). Despite these differences, Austrian and German hospitals both reported a similar IT budget of 2.6% in Austria and 2.0% in Germany (median).
Conclusions: Despite the many similarities of the Austrian and German healthcare system there are distinct differences which may have led to a wider use of IT systems in Austrian hospitals. In nursing, the specific legal requirement to document nursing diagnoses in Austria may have stimulated the use of standardised terminologies for nursing diagnoses and the implementation of electronic nursing documentation systems. Other factors which correspond with the wider use of clinical IT systems in Austria are: good infrastructure of medical-technical devices, rigorous organisational changes which had led to leaner processes and to a lower length of stay, and finally a more IT friendly climate. As country size is the most pronounced difference between Germany and Austria it could be that smaller countries, such as Austria, are more ready to translate innovation into practice.
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.
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.
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.
Introduction: Establishing continuity of care in handovers at changes of shift is a challenging endeavor that is jeopardized by time pressure and errors typically occurring during synchronous communication. Only if the outgoing and incoming persons manage to collaboratively build a common ground for the next steps of care is it possible to ensure a proper continuation. Electronic systems, in particular electronic patient record systems, are powerful providers of information but their actual use might threaten achieving a common understanding of the patient if they force clinicians to work asynchronously. In order to gain a deeper understanding of communication failures and how to overcome them, we performed a systematic review of the literature, aiming to answer the following four research questions: (1a) What are typical errors and (1b) their consequences in handovers? (2) How can they be overcome by conventional strategies and instruments? (3) electronic systems? (4) Are there any instruments to support collaborative grounding?
Methods: We searched the databases MEDLINE, CINAHL, and COCHRANE for articles on handovers in general and in combination with the terms electronic record systems and grounding that covered the time period of January 2000 to May 2012.
Results: The search led to 519 articles of which 60 were then finally included into the review. We found a sharp increase in the number of relevant studies starting with 2008. As could be documented by 20 studies that addressed communication errors, omission of detailed patient information including anticipatory guidance during handovers was the greatest problem. This deficiency could be partly overcome by structuring and systematizing the information, e.g. according to Situation, Background, Assessment and Recommendation schema (SBAR), and by employing electronic tools integrated in electronic records systems as 23 studies on conventional and 22 articles on electronic systems showed. Despite the increase in quantity and quality of the information achieved, it also became clear that there was still the unsolved problem of anticipatory guidance and presenting “the full story” of the patient. Only a small number of studies actually addressed how to establish common ground with the help of electronic tools.
Discussion: The increase in studies manifests the rise of great interest in the handover scenario. Electronic patient record systems proved to be excellent information feeders to handover tools, but their role in collaborative grounding is unclear. Concepts of how to move to joint information processing and IT-enabled social interaction have to be implemented and tested.
The demand for evidence-based health informatics and benchmarking of 'good' information systems in health care gives an opportunity to continue reporting on recent papers in the German journal GMS Medical Informatics, Biometry and Epidemiology (MIBE) here. The publications in focus deal with a comparison of benchmarking initiatives in German-speaking countries, use of communication standards in telemonitoring scenarios, the estimation of national cancer incidence rates and modifications of parametric tests. Furthermore papers in this issue of MIM are introduced which originally have been presented at the Annual Conference of the German Society of Medical Informatics, Biometry and Epidemiology. They deal as well with evidence and evaluation of 'good' information systems but also with data harmonization, surveillance in obstetrics, adaptive designs and parametrical testing in statistical analysis, patient registries and signal processing.
Background:
Chronic health conditions are on the rise and are putting high economic pressure on health systems, as they require well-coordinated prevention and treatment. Among chronic conditions, chronic wounds such as cardiovascular leg ulcers have a high prevalence. Their treatment is highly interdisciplinary and regularly spans multiple care settings and organizations; this places particularly high demands on interoperable information exchange that can be achieved using international semantic standards, such as Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT).
Objective:
This study aims to investigate the expressiveness of SNOMED CT in the domain of wound care, and thereby its clinical usefulness and the potential need for extensions.
Methods:
A clinically consented and profession-independent wound care item set, the German National Consensus for the Documentation of Leg Wounds (NKDUC), was mapped onto the precoordinated concepts of the international reference terminology SNOMED CT. Before the mapping took place, the NKDUC was transformed into an information model that served to systematically identify relevant items. The mapping process was carried out in accordance with the ISO/TR 12300 formalism. As a result, the reliability, equivalence, and coverage rate were determined for all NKDUC items and sections.
Results:
The developed information model revealed 268 items to be mapped. Conducted by 3 health care professionals, the mapping resulted in moderate reliability (κ=0.512). Regarding the two best equivalence categories (symmetrical equivalence of meaning), the coverage rate of SNOMED CT was 67.2% (180/268) overall and 64.3% (108/168) specifically for wounds. The sections general medical condition (55/66, 83%), wound assessment (18/24, 75%), and wound status (37/57, 65%), showed higher coverage rates compared with the sections therapy (45/73, 62%), wound diagnostics (8/14, 57%), and patient demographics (17/34, 50%).
Conclusions:
The results yielded acceptable reliability values for the mapping procedure. The overall coverage rate shows that two-thirds of the items could be mapped symmetrically, which is a substantial portion of the source item set. Some wound care sections, such as general medical conditions and wound assessment, were covered better than other sections (wound status, diagnostics, and therapy). These deficiencies can be mitigated either by postcoordination or by the inclusion of new concepts in SNOMED CT. This study contributes to pushing interoperability in the domain of wound care, thereby responding to the high demand for information exchange in this field. Overall, this study adds another puzzle piece to the general knowledge about SNOMED CT in terms of its clinical usefulness and its need for further extensions.
Objectives: This study aimed at the construction of what the core of eHealth policy making is, offering new perspectives about high priority procedures along the policy making process
Methods: Following Grounded Theory methodology, 59 qualitative telephone interviews with a broad variety of stakeholders from Austria, Switzerland and Germany were conducted
Results: The findings hinted at five priorities of eHealth policy making: strategy, consensus-building, decision-making, implementation and evaluation that emerged from the stakeholders’ perception of the eHealth policy. Hereby strategy, consensus-building and implementation gained the highest attention
Conclusions: These findings suggest three high priorities in eHealth policy: 1) developing and pursuing a consistent eHealth strategy, 2) investing time and resources into consensus-building to clear up difficulties early on in the process, 3) governing implementation towards serving patient care through systems fit for practice.
Public Interest Summary: Digitalisation is playing an increasingly crucial role in providing high quality health care. However, different countries have pursued different political paths. In this study, we wanted to know how the stakeholders perceived the political process in their country to identify strengths and weaknesses. We, therefore, conducted interviews about digital health policy with experts from Austria, Switzerland and Germany covering the full spectrum of stakeholders. The findings suggest three political musts: 1) a convincing and coherent strategy followed throughout the entire process, 2) consensus- building among the stakeholders, 3) using “fit for practice” as the yardstick to measure political success.
Background:
While aiming for the same goal of building a national eHealth Infrastructure, Germany and the United States pursued different strategic approaches – particularly regarding the role of promoting the adoption and usage of hospital Electronic Health Records (EHR).
Objective:
To measure and model the diffusion dynamics of EHRs in German hospital care and to contrast the results with the developments in the US.
Materials and methods:
All acute care hospitals that were members of the German statutory health system were surveyed during the period 2007–2017 for EHR adoption. Bass models were computed based on the German data and the corresponding data of the American Hospital Association (AHA) from non-federal hospitals in order to model and explain the diffusion of innovation.
Results:
While the diffusion dynamics observed in the US resembled the typical s-shaped curve with high imitation effects (q = 0.583) but with a relatively low innovation effect (p = 0.025), EHR diffusion in Germany stagnated with adoption rates of approx. 50% (imitation effect q = -0.544) despite a higher innovation effect (p = 0.303).
Discussion:
These findings correlate with different governmental strategies in the US and Germany of financially supporting EHR adoption. Imitation only seems to work if there are financial incentives, e.g. those of the HITECH Act in the US. They are lacking in Germany, where the government left health IT adoption strategies solely to the free market and the consensus among all of the stakeholders.
Conclusion:
Bass diffusion models proved to be useful for distinguishing the diffusion dynamics in German and US non-federal hospitals. When applying the Bass model, the imitation parameter needs a broader interpretation beyond the network effects, including driving forces such as incentives and regulations, as was demonstrated by this study.