| Title |
Development and validation of a model for the adoption of structured and standardised data recording among healthcare professionals
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, June 2018
|
| DOI | 10.1186/s12911-018-0640-8 |
| Pubmed ID | |
| Authors |
Erik Joukes, Ronald Cornet, Martine C. de Bruijne, Nicolette F. de Keizer, Ameen Abu-Hanna |
| Abstract |
Healthcare professionals provide care to patients and during that process, record large quantities of data in patient records. Data in an Electronic Health Record should ideally be recorded once and be reusable within the care process as well as for secondary purposes. A common approach to realise this is to let healthcare providers record data in a standardised and structured way at the point of care. Currently, it is not clear to what extent this structured and standardised recording has been adopted by healthcare professionals and what barriers to their adoption exist. Therefore, we developed and validated a multivariable model to capture the concepts underlying the adoption of structured and standardised recording among healthcare professionals. Based on separate models from the literature we developed a new theoretical model describing the underlying concepts of the adoption of structured and standardised recording. Using a questionnaire built upon this model we gathered data to perform a summative validation of our model. Validation was done through partial least squares structural equation modelling (PLS-SEM). The quality of both levels defined in PLS-SEM analysis, i.e., the measurement model and the structural model, were assessed on performance measures defined in literature. The theoretical model we developed consists of 29 concepts related to information systems as well as organisational factors and personal beliefs. Based on these concepts, 59 statements with a 5 point Likert-scale (fully disagree to fully agree) were specified in the questionnaire. We received 3584 responses. The validation shows our model is supported to a large extent by the questionnaire data. Intention to record in a structured and standardised way emerged as a significant factor of reported behaviour (β = 0.305, p < 0.001). This intention is influenced most by attitude (β = 0.512, p < 0.001). This model can be used to measure the perceived level of adoption of structured and standardised recording among healthcare professionals and further improve knowledge on the barriers and facilitators of this adoption. |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 3 | 33% |
| United Kingdom | 2 | 22% |
| Norway | 1 | 11% |
| Unknown | 3 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 44% |
| Members of the public | 3 | 33% |
| Practitioners (doctors, other healthcare professionals) | 2 | 22% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 61 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 16% |
| Student > Ph. D. Student | 9 | 15% |
| Professor | 4 | 7% |
| Student > Bachelor | 4 | 7% |
| Student > Doctoral Student | 3 | 5% |
| Other | 10 | 16% |
| Unknown | 21 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 13% |
| Nursing and Health Professions | 6 | 10% |
| Engineering | 6 | 10% |
| Computer Science | 4 | 7% |
| Sports and Recreations | 2 | 3% |
| Other | 10 | 16% |
| Unknown | 25 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 July 2018.
All research outputs
#4,587,761
of 25,008,338 outputs
Outputs from BMC Medical Informatics and Decision Making
#384
of 2,121 outputs
Outputs of similar age
#81,597
of 335,398 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#9
of 30 outputs
Altmetric has tracked 25,008,338 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,121 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done well, scoring higher than 81% of its peers.
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We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.