RxConnect User Testing Study

NCT05493072 | Completed Results

• 1 other identifier: 22CX7758
• Study Type: interventional
• Target: 24
• Locations: 1 country
• Sites: 1

Brief Summary

Background Medication errors are the leading cause of preventable harm in healthcare settings worldwide. An estimated 237 million medication errors occur in England alone every year, with 66 million considered clinically significant. There is an estimated cost to the NHS from definitely avoidable adverse drug reactions as a result of these errors of £98.5 million per year, consuming 181,626 bed-days and causing to 712 deaths. Medication related clinical decision support systems, often integrated with electronic prescribing systems, are rapidly increasing in number over the last few decades, ranging from drug-drug interaction alerts to allergy checks and formulary support. A recent systematic review summarised that these systems are still relatively immature, with limited use of patient-specific input or human factors research used to develop them. There is an opportunity to improve these systems significantly for the benefit of the user and for patient safety. The World Health Organization propose that interventions to reduce medication error should include the development of technologies that are well understood and designed for the systems and practice they are applied to. Human factors and usability engineering is an integral part of developing medical devices, such as clinical decision support (CDS) systems, to ensure that such devices are easy to use and can be used safely as intended. User testing / usability testing, which may incorporate several methods, should be conductive throughout the development process (at formative, summative assessment, and during post-market surveillance). These methods are now becoming more common place in healthcare technology research and should continue to support the development of new technologies. RxConnect RxConnect, a newly registered UKCA marked medical device, is an on-demand clinical decision support tool that receives medication and patient inputs and uses them to filter an underlying formulary, such as the BNF, and perform dosing calculations, as needed, to return patient-specific dosing recommendations. RxConnect does not have a user interface and relies on an integration with third-party systems, such as electronic prescribing systems, to deliver CDS services to clinical end users. For this study a prototype user interface for RxConnect that emulates a typical electronic prescribing system will be used. The study team hypothesise that use of RxConnect as a digital prescribing aid is quicker, easier, and as safe to use as currently available prescribing aids. This study aims to utilise user testing to prove or disprove the above hypothesis and to generate quantitative and qualitative outputs to support the continued development of RxConnect prior to clinical deployment.

Conditions

Behavior

Keywords

Medication safety; Prescribing practice; Prescribing behaviour

Outcome Measures

Primary Outcomes (1)

• Number of Prescribing Errors by Study Arm

  Sub analysis of errors by type available in full report

  60 minutes

Secondary Outcomes (3)

• Number of Medication Orders With a Large Magnitude Error (Greater Than 25% of the Recommended Dosing Range)

  60 minutes

• Time Taken to Prescribe Each Medication

  60 minutes

• Measurement of the Prescribers Perceived Mental Load Per Prescribing Scenario

  60 minutes

Other Outcomes (2)

• Erroneous Medication Orders by Hierarchial Task Analysis (Identifying Vulnerable Steps in the Prescribing Workflow).

  60 minutes

• Number of Participants That Gave Qualitative Feedback

  60 minutes

Study Arms (2)

Control

NO INTERVENTION

Observation of control arm practice for 5 medication scenarios

Intervention

EXPERIMENTAL

Observation of intervention practice for 5 medication scenarios

Other: RxConnect

Interventions

RxConnect OTHER

Participants use RxConnect, an on-demand clinical decision support tool that receives medication and patient inputs and uses them to filter an underlying formulary, such as the BNF, and perform dosing calculations, as needed, to return patient-specific dosing recommendations.

Intervention

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• Willingness to consent and participate
• Medical doctor - Foundation year 1 and above OR registered non-medical prescriber (e.g. nurses or pharmacists)
• Regular (at least weekly) experience in prescribing medications as part of working role

You may not qualify if:

• Infrequent prescribing practice (less than once a week)
• Not willing to participate

Sponsors & Collaborators

• Imperial College London: lead
• National Institute for Health Research, United Kingdom: collaborator

Study Sites (1)

Imperial College NHS Healthcare Trust

London, United Kingdom

Location

Related Publications (8)

• Donaldson LJ, Kelley ET, Dhingra-Kumar N, Kieny MP, Sheikh A. Medication Without Harm: WHO's Third Global Patient Safety Challenge. Lancet. 2017 Apr 29;389(10080):1680-1681. doi: 10.1016/S0140-6736(17)31047-4. No abstract available.

  PMID: 28463129 BACKGROUND

• MHRA. Guidance on applying human factors and usability engineering of medical devices including drug-device combination products in Great Britain. 2021;(January):35. Available from: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/970563/Human-Factors_Medical-Devices_v2.0.pdf

  BACKGROUND

• Holden RJ, Abebe E, Russ-Jara AL, Chui MA. Human factors and ergonomics methods for pharmacy research and clinical practice. Res Social Adm Pharm. 2021 Dec;17(12):2019-2027. doi: 10.1016/j.sapharm.2021.04.024. Epub 2021 May 2.

  PMID: 33985892 BACKGROUND

• Novak LL, Holden RJ, Anders SH, Hong JY, Karsh BT. Using a sociotechnical framework to understand adaptations in health IT implementation. Int J Med Inform. 2013 Dec;82(12):e331-44. doi: 10.1016/j.ijmedinf.2013.01.009. Epub 2013 Apr 3.

  PMID: 23562140 BACKGROUND

• Elliott RA, Camacho E, Jankovic D, Sculpher MJ, Faria R. Economic analysis of the prevalence and clinical and economic burden of medication error in England. BMJ Qual Saf. 2021 Feb;30(2):96-105. doi: 10.1136/bmjqs-2019-010206. Epub 2020 Jun 11.

  PMID: 32527980 RESULT

• Tolley CL, Slight SP, Husband AK, Watson N, Bates DW. Improving medication-related clinical decision support. Am J Health Syst Pharm. 2018 Feb 15;75(4):239-246. doi: 10.2146/ajhp160830.

  PMID: 29436470 RESULT

• Aufegger L, Serou N, Chen S, Franklin BD. Evaluating users' experiences of electronic prescribing systems in relation to patient safety: a mixed methods study. BMC Med Inform Decis Mak. 2020 Apr 3;20(1):62. doi: 10.1186/s12911-020-1080-9.

  PMID: 32245467 RESULT

• Feather C, Clarke J, Appelbaum N, Darzi A, Franklin BD. Comparing safety, performance and user perceptions of a patient-specific indication-based prescribing tool with current practice: a mixed methods randomised user testing study. BMJ Qual Saf. 2025 Oct 17;34(11):737-746. doi: 10.1136/bmjqs-2024-017733.

  PMID: 39577867 DERIVED

MeSH Terms

Conditions

Behavior

Results Point of Contact

• Title: Calandra Feather
• Organization: Imperial College NHS Healthcare Trust

calandra.feather@nhs.net

07977185577

Publication Agreements

• PI is Sponsor Employee: No
• Restrictive Agreement: No

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Purpose: BASIC SCIENCE
• Intervention Model: CROSSOVER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 25, 2022
• First Posted: August 9, 2022
• Study Start: December 12, 2022
• Primary Completion: March 30, 2023
• Study Completion: March 30, 2023
• Last Updated: March 24, 2025
• Results First Posted: March 24, 2025

Record last verified: 2025-03

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)