RxConnect User Testing Study

Behavior Clinical Trial

Official title:

Safety, Performance, and User Perceptions of RxConnect When Used to Provide Patient-specific, Indication Based Prescribing Support

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05493072
• Other study ID #: 22CX7758
• Status: Completed
• Phase: N/A
• Start date: December 12, 2022
• Est. completion date: March 30, 2023

Study information

• Verified date: April 2023
• Source: Imperial College London
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 24
• Est. completion date: March 30, 2023
• Est. primary completion date: March 30, 2023
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• 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

Exclusion Criteria:

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

Related Conditions & MeSH terms

• Behavior

Intervention

Other:
• RxConnect
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.

Locations

Country	Name	City	State
United Kingdom	Imperial College NHS Healthcare Trust	London

Sponsors (2)

Lead Sponsor	Collaborator
Imperial College London	National Institute for Health Research, United Kingdom

Country where clinical trial is conducted

United Kingdom, 

References & Publications (7)

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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

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. — View Citation

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. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Workflow steps and order	will be documented and analysed using Hierarchical task analysis. This will provide an overview of the prescribing steps and there order and comparisons made between the control and the intervention arms.	90 minutes
Other	Qualitative feedback from participants	Audio of interviews will be transcribed verbatim and thematically analyses to provide insights from participants that can be utilised for recommendations for practice and research.	90 minutes
Primary	Number of prescribing errors per scenario	Subcategorised as - Incorrect drug, dose, route, frequency or patient.	90 minutes
Secondary	The magnitude of any dose errors (deviation from recommended dosing range)		90 minutes
Secondary	Time taken to prescribe each medication		90 minutes
Secondary	Prescribers perceived mental load per prescribing scenario	Using NASA task load index	90 minutes