Implementing a National Electronic Referral Program: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Electronic referrals or e-referrals can be defined as the electronic transmission of patient data and clinical requests between health service providers. National electronic referral systems have proved challenging to implement due to problems of fit between the technical systems proposed and the existing sociotechnical systems. In seeming contradiction to a sociotechnical approach, the Irish Health Service Executive initiated an incremental implementation of a National Electronic Referral Programme (NERP), with step 1 including only the technical capability for general practitioners to submit electronic referral requests to hospital outpatient departments. The technology component of the program was specified, but any changes required to embed that technology in the existing sociotechnical system were not specified. OBJECTIVE: This study aimed to theoretically frame the lessons learned from the NERP step 1 on the design and implementation of a national health information technology program. METHODS: A case study design was employed, using qualitative interviews with key stakeholders of the NERP step 1 (N=41). A theory-driven thematic analysis of the interview data was conducted, using Barker et al's Framework for Going to Full Scale. RESULTS: The NERP step 1 was broadly welcomed by key stakeholders as the first step in the implementation of electronic referrals-delivering improvements in the speed, completeness of demographic information, and legibility and traceability of referral requests. National leadership and digitalized health records in general practice were critical enabling factors. Inhibiting factors included policy uncertainty about the future organizational structures within which electronic referrals would be implemented; the need to establish a central referral office consistent with these organizational structures; outstanding interoperability issues between the electronic referral solution and hospital patient administration systems; and an anticipated need to develop specialist referral templates for some specialties. A lack of specification of the sociotechnical elements of the NERP step 1 inhibited the necessary testing and refinement of the change package used to implement the program. CONCLUSIONS: The key strengths of the NERP step 1 are patient safety benefits. The NERP was progressed beyond the pilot stage despite limited resources and outstanding interoperability issues. In addition, a new electronic health unit in Ireland (eHealth Ireland) gained credibility in delivering national health information technology programs. Limitations of the program are its poor integration in the wider policy and quality improvement agenda of the Health Service Executive. The lack of specification of the sociotechnical elements of the program created challenges in communicating the program scope to key stakeholders and restricted the ability of program managers and implementers to test and refine the change package. This study concludes that while the sociotechnical elements of a national health information technology program do not need to be specified in tandem with technical elements, they do need to be specified early in the implementation process so that the change package used to implement the program can be tested and refined.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".