A Qualitative Study to Explore the Barriers to Adoption of Clinical Decision Support Systems
Conditions: Clinical Decision Support System (CDSS)
Sponsor: Medway NHS Foundation Trust

 
 
 
 
Medway NHS Foundation Trust
Project Reference: 1366 / IRAS ID: 365984
A QUALITATIVE STUDY TO 
EXPLORE THE BARRIERS TO 
ADOPTION OF CLINICAL DECISION 
SUPPORT SYSTEMS (CDSS-ADOPT)  
Study Protocol v1.6 (06/01/2026) 
NCT number pending 
 

 
 
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Research Study Protocol 
 
 
 
 
1. Researcher details 
1.1 Applicant details  
Name  
Saad Muhammad 
Department  
Medical Education 
Phone number 
01634 830000 
Email  
Saad.muhammad@nhs.net  
1.2 Co-applicants/external partner details 
Name  
 
Department/company   
Phone number 
 
Email  
 
1.3 Other applicants/applicant information  
RO Reference: 1366 
IRAS Project ID:  365984 
2. Study Information and overview 
2.1 Study details 
Study title  
A Qualitative Study to Explore the Barriers to Adoption of 
Clinical Decision Support Systems 
Study classification  
(i.e. Research/Service Evaluation) 
Research 
Department  
(Please state where the study will be 
conducted & the name of the 
departmental manager) 
Medical Education – Dr Ashike Choudhury (Director of 
Medical Education) 
Protocol Version Number  
(Please state version number e.g. 1, 2) 
1.6 
Protocol Version Date  
(Please date protocol) 
06/01/2025 

 
 
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2.2 lay overview of the project 
Please provide an overview of the project in lay (non-scientific/no jargon) language. This overview 
should be understandable to most people. 
 
This study will explore the barriers and facilitators influencing the use of Clinical Decision Support 
Systems (CDSS) among emergency department (ED) clinicians in an NHS district general hospital. 
The ED represents a uniquely demanding environment characterised by high patient turnover, time 
pressure, and complex, multidisciplinary decision-making. These conditions make it both an optimal 
and a challenging context for the integration of CDSS, whose potential to improve diagnostic 
accuracy, patient safety, and workflow efficiency. 
By employing a qualitative methodology (semi-structured interviews and user persona development), 
this study aims to generate detailed context-specific insights into clinicians’ perceptions, workflow 
challenges, and information needs. Unlike prior research which has often adopted quantitative or 
system-centric approaches, this investigation will foreground the human factors that influence CDSS 
adoption within frontline NHS care. 
The findings are expected to inform practical, evidence-based strategies for the design and 
implementation of CDSS tools that better align with real-world clinical workflows. In doing so, this 
research will contribute to the academic understanding of CDSS adoption while offering actionable 
insights to support NHS digital transformation initiatives in the ED and, ultimately, across the wider 
hospital environment. 
2.3 Background/Literature review                                                                                                
Please provide any relevant background information to support the research area/disease. The 
subtitles below are to help guide you on what is required within this section. Please include published 
findings, Add full reference to the Reference List (Section 11). The Knowledge and Library Services 
can assist with completing a literature search and horizon scan please by visiting Request a Search - 
Medway NHS KLS  
 
Background 
CDSS have demonstrated measurable benefits across multiple domains of hospital practice. They are 
associated with reductions in prescribing errors of up to 55%, improvements in adherence to 
evidence-based guidelines of 25–30%, and gains in diagnostic accuracy for conditions such as 
pneumonia and cardiovascular risk compared with clinician judgement alone[1]. Despite this evidence, 
adoption in everyday practice remains limited. Liberati et al. and Chen et al. highlighted persistent 
socio-technical barriers, including poor workflow integration, usability issues, perceived increases in 
workload, lack of clinician trust, and concerns about autonomy[2,3]. Research by Meunier et al. and 
Mebrahtu et al. further note that even within single departments, uptake varies considerably across 
clinician subgroups, shaped by differences in experience, confidence, and perceptions of 
technology[4,5]. 
National health policy places increasing emphasis on overcoming these barriers. The NHS 10-Year 
Health Plan identifies digital transformation as a central strategic priority, calling for a transition from 
analogue to digital working and for innovations to be embedded across care settings[6]. Similarly, the 
Darzi Report[7] stresses that the NHS is under unprecedented strain and identifies technology, as a 
crucial lever for reinvention and improvement. NHS England’s recent report titled “Supporting 
Clinical Decisions with Health Information Technology” also underscores the importance of 
developing local evidence and implementation strategies to realise the full potential of decision 
support tools[8]. 

 
 
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Whilst previous research highlight measurable benefits[1], these benefits are rarely realised in practice 
due to socio-technical constraints[2,3]. Moreover, as CDSS evolve from rule-based systems to AI-
driven decision models, concerns around explainability, trust, and workflow integration have become 
even more pronounced. This underscores the importance of qualitative research that can capture how 
clinicians actually perceive and interact with such systems in their daily work. 
Rationale: 
Despite growing evidence that CDSS can improve patient safety, enhance adherence to clinical 
guidelines, and increase efficiency within healthcare settings[1], their adoption in emergency 
departments (EDs) remains inconsistent and limited. Studies have identified barriers such as poor 
workflow integration, usability issues, lack of trust in the system’s recommendations, and perceived 
increases in workload[2-4]. However, much of the existing literature is either quantitative or focused on 
single-system evaluations, leaving a qualitative gap in understanding how these barriers manifest in 
the real-world context of EDs within NHS district general hospitals. 
This gap is particularly significant given that EDs operate under conditions of high patient turnover, 
time pressure, and reliance on multi-disciplinary teams - all of which heighten the need for efficient, 
evidence-based decision-making. Understanding why CDSS adoption remains low among ED 
clinicians is therefore critical to improving clinical consistency, patient safety, and overall system 
efficiency. Furthermore, this aligns directly with the NHS 10-Year Plan and Darzi Report, which both 
prioritise digital transformation and the integration of advanced technologies into care delivery. 
Identifying these barriers qualitatively will help inform future implementation strategies, ensuring that 
CDSS tools are both usable and sustainable within the NHS context. 
 
2.4 Aims & Objectives                                                                                                                             
• Please insert a detailed description of the objectives and the purpose of the study.  
• Please include a specific statement of the primary endpoints and the secondary endpoints, if any, to 
be measured during the study. 
Objectives must be SMART 
S: Specific 
M: Measurable 
A: Achievable 
R: Relevant 
T: Time bound 
 
To explore the barriers and facilitators experienced by emergency department clinicians in adopting 
and using Clinical Decision Support Systems (CDSS) in a single NHS district general hospital. 
 
2. Methodology                                                                                                                               Please 
provide information as to how the study will be conducted; to include where/how and by who the data 
will be collected and analysed, the proposed duration of the study etc. The subtitles below are to help 
guide you on what is required in this section.   
Study Design:  
Cross-sectional qualitative study using semi-structured interviews. 
Study Setting:  
The study will be carried out in the Emergency Department (ED) of Medway Maritime Hospital. 

 
 
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Study Period:  
Interviews carried out between 10th-31st January 2026 
 
Study Population:  
• 
Emergency Department (ED) clinicians in patient-facing roles who routinely use or refer to 
clinical guidelines, protocols, or decision support systems (CDSS) to inform patient care. This 
includes ED doctors of all grades (consultants, registrars, junior doctors), Advanced Clinical 
Practitioners (ACPs), triage and staff nurses, Physician Assistants (PAs), and Clinical Support 
Workers (CSWs) working in the ED of the participating hospital. 
Inclusion Criteria: 
• 
Employed by Medway NHS Foundation Trust at the time of recruitment 
• 
Working clinically within the Emergency Department 
• 
Clinical grade of FY1, FY2, SHO/CTF, SAS/Registrar, Consultant, Nurse, Advanced Clinical 
practitioner, Physician Assistant, or Clinical Support Worker  
• 
Involved in the assessment and management of adult emergency department patients 
• 
Have routine access to the Trust electronic patient record system (Sunrise EPR) during clinical 
duties 
• 
Able to provide informed consent to participate 
• 
Aged 18 years or older 
Exclusion Criteria: 
• 
Bank, agency, or locum staff who are not permanently or regularly employed by the 
department. 
• 
Staff currently on leave, secondment, or not actively practising in the ED during the data 
collection period. 
• 
Clinicians currently involved in the design, management, or evaluation of the CDSS system 
under study. 
 
Sample Size Calculation:  
Aim for 10-12 total interviews to achieve thematic saturation.  
 
Sampling Method:  
This study will use purposive sampling with maximum variation to ensure representation across key 
categories of Emergency Department clinicians who use clinical decision support systems. 
Participants will be selected to capture a range of roles and experiences, including Advanced Clinical 
Practitioners (ACPs), Physician Associates (PAs), Clinical Support Workers (CSWs), nurses, and 
doctors at different levels (Foundation Year 1–2, Senior House Officers, Registrars, and Consultants). 
Recruitment will continue until data saturation is achieved within and across these categories, 
anticipated at approximately one to two participants per role group. 

 
 
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End of Study:  
The study will be considered complete once all of the following activities have been concluded: 
• All planned participant interviews have been conducted or recruitment has 
formally ceased following achievement of data saturation 
• All interview recordings have been transcribed, anonymised, and verified 
for accuracy 
• All source audio files have been securely deleted in accordance with the 
data management plan 
• Qualitative data analysis has been completed and final themes have been 
agreed 
• The final study report has been completed and submitted to the sponsoring 
organisation (Medway NHS Foundation Trust) 
At this point, no further data collection or analysis will take place, and the study will move into the 
data archiving phase as described in the data protection section of this protocol  
Data Collection Methods 
 
Study Instrument:  
 
The interview schedule was developed using two key frameworks to guide development; this 
included: 
1. The NASSS-CAT (Short) toolkit[10] (Non-adoption, Abandonment, Scale-up, Spread 
and Sustainability – Complexity Assessment Tool) due to its focus on the multiple 
domains that shape the adoption and sustained use of health technologies 
2. Findings from contemporary research outlined by Newton et al., on clinicians’’ the 
acceptance and use of CDSS over time[11]. 
The tool has then undergone face validation by experts in Data Science, Digital Health Technologies 
and Research Methodology. 
The interview schedule was pre-tested among clinicians working in the emergency department 
(excluded from study population) by the chief investigator to identify issues with clarity and 
coherence. Minor revisions were made following these pre-tests.  
 
Study Implementation:  
Semi-structured interviews will be audio-recorded using a secure, password-protected digital recorder. 
Recordings will be transcribed verbatim by the chief investigator, and all transcripts will be 
anonymised prior to analysis by removing identifiable details such as names, roles, or locations. 
Interviews to be carried out in the library training room 1 located in the education centre of Medway 
Maritime Hospital. 
Documents will be kept locked in a secure storage facility in the Trust. Only the chief investigator 
will have access to these documents. Once scanned and digitised, these paper documents will then be 
destroyed. 

 
 
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All data (audio files, transcripts, and digitised documents) will be stored securely on the institution’s 
encrypted OneDrive system, accessible only to the chief investigator. 
 
 
3. Analysis 
4.1 Planned analysis 
Data will be analysed using thematic analysis, following Braun and Clarke’s six-phase approach[9] 
outlined below:  
1. Familiarisation with the data (reading and re-reading transcripts and field notes). 
2. Generating initial codes. 
3. Searching for themes across the data set. 
4. Reviewing themes. 
5. Defining and naming themes. 
6. Producing the final report. 
A hybrid inductive-deductive analytic strategy will be applied; initial inductive (data-driven) coding 
will allow themes to emerge naturally from participants’ accounts. In parallel, deductive coding will 
draw on the domains of the NASSS-CAT (Short) framework[10], providing a structured lens through 
which to interpret barriers and facilitators to CDSS adoption. The NASSS domains will be used as 
higher-order organisational categories to support theme development, comparison across professional 
groups, and interpretation of system-level influences. Reflexive memo-writing will be used 
throughout to ensure transparency and analytic rigour. 
Coding and theme development will be carried out by the chief investigator. Reflexive notes will be 
maintained throughout analysis to ensure transparency and interpretive rigour. Anonymised transcripts 
will be coded with the help of automated coding software (NVivo) and manual coding when required. 
4.2 Person performing the analysis?  
Chief Investigator with the Help of the R&I Department of the Medway NHS Foundation trust 
4. Risks and benefits 
5.1 Risks of study participation  
Participation in this study is considered low risk. The potential risks or burdens include minor 
inconvenience due to time commitments for interviews, and the possibility of mild emotional 
discomfort when discussing barriers or frustrations related to clinical decision support systems and 
workflow. Participation will be entirely voluntary, and individuals may withdraw at any time without 
penalty. 
 
5.2 Benefits of study participation  

 
 
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The anticipated benefits include contributing to the improvement of CDSS design and implementation 
within the Emergency Department, supporting more effective and user-centred clinical workflows. 
The findings may also benefit other departments and healthcare organisations planning to adopt or 
optimise CDSS, aligning with the NHS Long Term Plan’s objectives for digital transformation and 
data-driven clinical decision-making. 
 
5.3 Risk Assessment performed? 
Performed 10/12/2025 
5. Data protection                                                                 
Please describe how the data will be collected per the General Data Protection Regulation (GDPR). 
Include details of procedures for data handling, record keeping and archiving arrangements both 
during and post-study, including the location of data, accessibility rights and security provisions. 
All research data will be stored in compliance with institutional and NHS data governance policies. 
Signed consent forms will be scanned and stored securely in an encrypted folder on the institution’s 
NHS OneDrive system, accessible only to the chief investigator and authorised supervisors. Physical 
copies will then be securely shredded. 
Audio recordings of interviews will be used solely for transcription and deleted immediately after 
transcripts are checked for accuracy and anonymised. Anonymised interview transcripts and digitised 
field notes will be retained securely on the institution’s encrypted NHS OneDrive system for a period 
of 10 years following study completion, after which they will be permanently deleted. 
 
6. Funding  
7.1 Does this project require funding? 
No 
7.2 Has funding been secured  
N/A 
7.3 Have you completed a study budget  
 
N/A 

 
 
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7. Ethical considerations  
Please list any factors of your project that may lead to ethical issues.  
Also elaborate on  
 Ethics Approval:  
HRA Approval pending 
Informed Consent:  
Participants will be given a copy of the participant information sheet with the opportunity to ask any 
questions. A consent form will then be signed to confirm willingness to be included in the study. 
Confidentiality:  
All data will be treated as strictly confidential. During transcription, any identifying information such 
as participant names, colleague names, or specific departmental or hospital references will be removed 
or replaced with pseudonyms. Participants will be assigned unique codes in the form of a participant 
number, and findings will be reported using generic descriptors (e.g., “ED nurse”, “registrar”, 
“ACP”) to ensure anonymity. 
Only the chief and associate chief investigators/co-researchers will have access to the original 
recordings and identifying information, which will be securely stored and deleted after transcription 
and anonymisation. All outputs (reports, publications, and presentations) will present findings in 
aggregate form and will not include any information that could directly or indirectly identify 
individuals or the study site. 
 
8. Dissemination plans 
Please list all the ways you plan to share the findings of this project. This may include scientific 
journal publications, conference presentations etc. 
The results of this study aim to be published in scientific journal publications, conference 
presentations, and shared with the Trust management. 
9. Any other relevant information 
 
10. Reference List  
Please add in full references you have added into text in the above sections. Use Harvard referencing 
style (For examples see link https://www.scribbr.co.uk/referencing/harvard-style/ ). If your field has a 
selected referencing style use that one.   

 
 
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1. Sutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An 
overview of clinical decision support systems: benefits, risks, and strategies for 
success. NPJ Digit Med. 2020 Feb 6;3:17. doi: 10.1038/s41746-020-0221-y. 
PMID: 32047862; PMCID: PMC7005290 
2. Liberati EG, Ruggiero F, Galuppo L, Gorli M, González-Lorenzo M, Maraldi M, 
Ruggieri P, Polo Friz H, Scaratti G, Kwag KH, Vespignani R, Moja L. What 
hinders the uptake of computerized decision support systems in hospitals? A 
qualitative study and framework for implementation. Implement Sci. 2017 Sep 
15;12(1):113. doi: 10.1186/s13012-017-0644-2. PMID: 28915822; PMCID: 
PMC5602839 
3. Chen W, O'Bryan CM, Gorham G, Howard K, Balasubramanya B, Coffey P, 
Abeyaratne A, Cass A. Barriers and enablers to implementing and using clinical 
decision support systems for chronic diseases: a qualitative systematic review and 
meta-aggregation. Implement Sci Commun. 2022 Jul 28;3(1):81. doi: 
10.1186/s43058-022-00326-x. PMID: 35902894; PMCID: PMC9330991 
4. Meunier PY, Raynaud C, Guimaraes E, Gueyffier F, Letrilliart L. Barriers and 
Facilitators to the Use of Clinical Decision Support Systems in Primary Care: A 
Mixed-Methods Systematic Review. Ann Fam Med. 2023 Jan-Feb;21(1):57-69. 
doi: 10.1370/afm.2908. PMID: 36690490; PMCID: PMC9870646 
5. Mebrahtu TF, Skyrme S, Randell R, Keenan AM, Bloor K, Yang H, Andre D, 
Ledward A, King H, Thompson C. Effects of computerised clinical decision 
support systems (CDSS) on nursing and allied health professional performance and 
patient outcomes: a systematic review of experimental and observational studies. 
BMJ Open. 2021 Dec 15;11(12):e053886. doi: 10.1136/bmjopen-2021-053886. 
PMID: 34911719; PMCID: PMC8679061 
6. Department of Health and Social Care; Prime Minister’s Office; 10 Downing 
Street. Fit for the Future: 10 Year Health Plan for England. CP 1350, ISBN 978-1-
5286-5807-2. Published 3 July 2025; last updated 30 July 2025. Available at: 
https://www.gov.uk/government/publications/10-year-health-plan-for-england-fit-
for-the-future 
7. Department of Health and Social Care. Independent investigation of the NHS in 
England. Published 12 September 2024, last updated 15 November 2024. Available 
at: https://www.gov.uk/government/publications/independent-investigation-of-the-
nhs-in-england 
8. NHS England (2023) Supporting clinical decisions with health information 
technology: An implementation guide for clinical decision support systems, 16 
August 2023. Available at: https://www.england.nhs.uk/long-read/supporting-
clinical-decisions-with-health-information-technology/ (Accessed: 18/08/2025). 
9. Ahmed, S.K., Mohammed, R.A., & Nashwan, A.J. (2025). Using thematic analysis 
in qualitative research. Journal of Medicine, Surgery and Public Health, 6, 100198. 
https://doi.org/10.1016/j.glmedi.2025.100198 
10. Thrive by Design (no date) NASSS-CAT toolkit. Available at: 
https://www.thrivebydesign.org.uk/our-learning/nasss-cat-toolkit (Accessed: 
17/10/2025). 
11. Newton, N., Bamgboje-Ayodele, A., Forsyth, R., Tariq, A. & Baysari, M. T. (2025) 
‘A systematic review of clinicians’ acceptance and use of clinical decision support 
systems over time’, npj Digital Medicine, 8, Article 309. doi: 10.1038/s41746-025-
01662-7. 

 
 
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