RxConnect User Testing Study

Not Applicable

Completed

Conditions: Behavior

Interventions: Other: RxConnect

Registration Number: NCT05493072

Lead Sponsor: Imperial College London

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.

Detailed Description: Not available

Recruitment & Eligibility

Status: COMPLETED

Sex: All

Target Recruitment: 24

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

Study & Design

Study Type: INTERVENTIONAL

Study Design: CROSSOVER

Arm && Interventions

Group	Intervention	Description
1 - Control (scenarios 1-5) then intervention (scenarios 6-10)	RxConnect	Observation of control arm practice for scenarios 1-5, followed by intervention arm for scenarios 6-10.
2- Intervention (scenarios 6-10) then control (scenarios 1-5)	RxConnect	Observation of intervention arm for scenarios 6-10, followed by control arm practice for scenarios 1-5
3- Intervention (scenarios 1-5) then control (scenarios 6-10)	RxConnect	Observation of intervention arm practice for scenarios 1-5, followed by control arm for scenarios 6-10.
4- Control (scenarios 6-10) then intervention (scenarios 1-5)	RxConnect	Observation of control arm practice for scenarios 6-10, followed by intervention arm for scenarios 1-5.

Primary Outcome Measures

Name	Time	Method
Number of Prescribing Errors by Study Arm	60 minutes	Sub analysis of errors by type available in full report

Secondary Outcome Measures

Name	Time	Method
Number of Medication Orders With a Large Magnitude Error (Greater Than 25% of the Recommended Dosing Range)	60 minutes	Dosing errors with a deviation of more than 25% from the recommended range were categorised as large magnitude errors.
Time Taken to Prescribe Each Medication	60 minutes	For the first scenario, TTP was calculated from the moment the participant began reading the scenario to task completion, while for subsequent scenarios, timing started from the completion of the previous scenario. The endpoint for each scenario was marked by the participant's submission of the medication order on the electronic prescribing (eP) system.
Measurement of the Prescribers Perceived Mental Load Per Prescribing Scenario	60 minutes	Measurement of the Prescribers perceived mental load per prescribing scenario, Using NASA task load index (TLX). An overall workload score combining all 6 NASA TLX domains was calculated (minimum 0 lower workload - maximum 126 highest workload).