The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
IT-adoption and the interaction of task, technology and individuals: a fit framework and a case study
Open accessAbstract
Background: Factors of IT adoption have largely been discussed in the literature. However, existing frameworks (such as TAM or TTF) are failing to include one important aspect, the interaction between user and task. Method: Based on a literature study and a case study, we developed the FITT framework to help analyse the socio-organisational-technical factors that influence IT adoption in a health care setting. Results: Our FITT framework (" F it between I ndividuals, T ask and T echnology") is based on the idea that IT adoption in a clinical environment depends on the fit between the attributes of the individual users (e.g. computer anxiety, motivation), attributes of the technology (e.g. usability, functionality, performance), and attributes of the clinical tasks and processes (e.g. organisation, task complexity). We used this framework in the retrospective analysis of a three-year case study, describing the adoption of a nursing documentation system in various departments in a German University Hospital. We will show how the FITT framework helped analyzing the process of IT adoption during an IT implementation: we were able to describe every found IT adoption problem with regard to the three fit dimensions, and any intervention on the fit can be described with regard to the three objects of the FITT framework (individual, task, technology). We also derive facilitators and barriers to IT adoption of clinical information systems. Conclusion: This work should support a better understanding of the reasons for IT adoption failures and therefore enable better prepared and more successful IT introduction projects. We will discuss, however, that from a more epistemological point of view, it may be difficult or even impossible to analyse the complex and interacting factors that predict success or failure of IT projects in a socio-technical environment.
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![Figure 1 Information success model by DeLone [5].](/paper-figures/9aa6529e88664798ba87020099bc2d52/it-adoption-and-the-interaction-of-task-technology-and-individuals-a-fit-figure-1.jpg)
![Figure 2 Technology acceptance model (TAM) by Davis [14].](/paper-figures/f48c91b22ca540a7bb24c16b6fcd6624/it-adoption-and-the-interaction-of-task-technology-and-individuals-a-fit-figure-2.jpg)
![Figure 3 Task-Technology-Fit model (TTF) by Goodhue [8], [13], [18].](/paper-figures/89c7ec6b041b422692bb23567ea03777/it-adoption-and-the-interaction-of-task-technology-and-individuals-a-fit-figure-3.jpg)







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In the citing paper
“The complex supply chains and convoluted communication processes between hospitals, local service providers, software suppliers, and NHS Connecting for Health that we previously described, persisted over time.38”
From Implementation and adoption of nationwide electronic health records in secondary care in England: final qualitative results from prospective national evaluation in early adopter hospitals (2011) · cites this paper as [38]
Experimental — accuracy not yet measuredIn the citing paper
“Although a purely theory-based approach—which might for instance add the compatibility variable from Rogers’ Innovation Diffusion Theory [63]—can be useful, empirical work may still be necessary to (a) determine whether those variables are relevant to health care, and (b) contextualize these new variables in order to determine, for example, what “compatibility” means in health care [57, 135].”
From The Technology Acceptance Model: Its past and its future in health care (2010) · cites this paper as [57]
In the citing paper
“FITT postulates that the introduction of new technology leads to positive changes in care system only if the attributes of the user group, the characteristics of the implemented technology, and the affected tasks match each other”
From Demystifying theory and its use in improvement (2015) · cites this paper as [68]
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Cites
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- Mahler C, Ammenwerth E, Eichstädter R, Hoppe B, Mansmann U, Tautz A, Wagner A: Evaluation of computer-based nursing documentation - final report - part: documentation analysis (in German). 2002, University Hospitals of Heidelberg
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Metadata
- Authors
- Ammenwerth, E., Iller, C., & Mahler, C.
- Affiliations
- UMIT TIROL - Private University for Health Sciences and Health Technology (AT)
- Heidelberg University (DE)
- University Hospital Heidelberg (DE)
- Corresponding author
- Ammenwerth, Elske
- Venue
- BMC Medical Informatics and Decision Making
- Published
- 2006-01-09
- Volume
- 6
- Issue
- 1
- Pages
- 3-3
- ISSN
- 1472-6947 (ISSN-L)
- PMC
- PMC1352353
- OpenAlex
- W1480033610
- Cited by
- 459
- References
- 39
- Citations by year
- 2026: 22 · 2025: 22 · 2024: 27 · 2023: 27 · 2022: 25 · 2021: 45 · 2020: 23 · 2019: 35 · 2018: 26 · 2017: 19 · 2016: 23 · 2015: 20 · 2014: 22 · 2013: 17 · 2012: 23
- FWCI
- 29.18
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Informatics and Decision Making (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Keywords
- information technology adoption, clinical information systems, computer anxiety, usability, task complexity, socio-technical factors, university hospital
- MeSH terms
- Anxiety, Attitude of Health Personnel, Attitude to Computers, Decision Making, Diffusion of Innovation, Germany, Hospital Information Systems, Hospitals, University, Humans, Medical Informatics Computing, Motivation, Task Performance and Analysis, Technology, User-Computer Interface, Organizational Culture, Organizational Case Studies, Nursing Informatics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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