Safety, Performance, and User Perceptions of RxConnect When Used to Provide Patient-specific, Indication Based Prescribing Support
Phase: NA
Conditions: Behavior
Sponsor: Imperial College London

 
 
 
 
 
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Safety, 
performance, 
and 
user 
perceptions of RxConnect when used 
to provide patient-specific, indication 
based prescribing support 
 
Short title: RxConnect user testing study 
 
Study Management Group 
Principal Investigator: Professor Bryony Franklin 
 
 
 
Co-investigators: Calandra Feather 
 
Clinical Queries 
Clinical queries should be directed to Calandra Feather who will direct the query to the 
appropriate person 
 
Sponsor 
 
Imperial College London is the main research Sponsor for this study. For further information 
regarding the sponsorship conditions, please contact the Head of Research Governance and 
Integrity. 
Research Governance and Integrity Team 
Imperial College London and Imperial College Healthcare NHS Trust 
Room 215, Level 2, Medical School Building 
Norfolk Place 
London, W2 1PG 
Tel: 0207 594 1862 
 
 
This protocol describes the RxConnect user testing study and provides information about 
procedures for entering participants. Every care was taken in its drafting, but corrections or 
amendments may be necessary. These will be circulated to investigators in the study. 
Problems relating to this study should be referred, in the first instance, to the Principal 
Investigator.  
 
This study will adhere to the principles outlined in the UK Policy Frame Work for Health and 
Social Care Research It will be conducted in compliance with the protocol, Data Protection 
Act 2018 and General Data Protection Regulations (Europe) and other regulatory 
requirements as appropriate.  
 

 
 
 
 
 
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TABLE OF CONTENTS 
Contents 
1. INTRODUCTION 
3 
Background 
3 
RxConnect 
3 
2. STUDY OBJECTIVES 
4 
Primary objective 
4 
Secondary objectives 
4 
3. STUDY DESIGN 
4 
Study Design 
4 
Sample size 
6 
Data collection and management 
6 
Duration of study 
7 
Study outcome measures  
7 
Statistics and data analysis 
8 
4. PARTICIPANT RECRUITMENT 
9 
Inclusion Criteria 
9 
Exclusion Criteria 
9 
Withdrawal Criteria 
10 
Follow up 
10 
5. ADVERSE EVENTS 
10 
Definitions 
10 
Reporting procedures 
10 
6. REGULATORY ISSUES 
11 
Ethics approval 
11 
Consent 
11 
Confidentiality 
12 
Indemnity 
12 
Sponsor 
12 
Funding 
12 
Audits 
12 
7. PUBLICATION POLICY 
12 
8. REFERENCES 
12 
9. APPENDIX 1: DRAFT SEMI-STRUCTURED INTERVIEW TOPIC GUIDE 
13 
10. APPENDIX 2: DRAFT STUDY SESSION STANDARD OPERATING PROCEDURE 
14 
 
 
 
 
 

 
 
 
 
 
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1. INTRODUCTION  
 
Background 
Medication errors are the leading cause of preventable harm in healthcare settings worldwide 
(1). An estimated 237 million medication errors occur in England alone every year, with 66 
million considered clinically significant (2). 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(2).  
 
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 (3). 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 (1). 
 
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 (4). 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) (4). These methods are now 
becoming more common place in healthcare technology research and should continue to 
support the development of new technologies (4–7). 
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 

 
 
 
 
 
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qualitative outputs to support the continued development of RxConnect prior to clinical 
deployment. 
 
2. STUDY OBJECTIVES 
Primary objective  
To determine whether the use of RxConnect as a prescribing aid, when compared with usual 
practice decreases or increases the number of prescribing errors 
Secondary objectives 
To determine whether the use of RxConnect as a prescribing aid, when compared with usual 
practice- 
1. Decreases or increases the magnitude of dose errors 
2. Decreases or increases the time to prescribe a medication 
3. Decreases or increases the mental load as perceived by the prescriber 
4. Alters the prescribing workflow 
 
To explore the opinions of the participants regarding the use of RxConnect as a prescribing 
aid and indication-based prescribing more generally. 
 
3. STUDY DESIGN 
Study Design 
A mixed-methods cross-over observational study will be conducted to explore the safety, 
performance, and user perceptions of utilising RxConnect to support prescribing, in 
comparison to current practice.  
 
Direct observation of participants will be conducted using multi-angle audio-visual recording, 
this will be set up behind the computer workstation, to capture the computer display and from 
above to capture the workstation. The cameras will not be angled to take footage of the 
participant face. A member of the research team will also be present through the study 
session. 
Prescribing scenarios will be presented on laminated paper along with any relevant patient 
information, e.g. patient gender, age, weight, diagnosis, relevant medical history, relevant 
laboratory results.   
 
Intervention arm: Prescribing with RxConnect via a prototype user interface 
Participants will be asked to complete a number of practice prescribing tasks whilst thinking 
aloud to describe their thought process and actions. To undertake the prescribing tasks, 
participants will be asked to use the prototype user interface emulating an electronic 
prescribing front end, which presents RxConnect medication guidance to the clinical end user 
(the participant). 
Once familiarised with the software workflow, the test prescribing tasks will be given to the 
participant. For these tasks the participants will be asked to perform the task without the need 
to think aloud. If the participant wishes to continue to think aloud so long as it doesn’t distract 

 
 
 
 
 
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them from completing the task. The medication order the participants have generated using 
RxConnect support via the user interface will then auto populate a medication order form.  
 
Control arm: Prescribing on Cerner with existing resources 
Participants will be asked to perform similarly simple and then complex tasks using their usual 
practice methods when prescribing. Access will be provided to the prescribers usual electronic 
prescribing platform, including links to the British National Formulary, Medicines complete, 
local antimicrobial stewardship application, local intranet, and a generic online search engine. 
A hard copy of the BNF and BNFc will also be readily available. 
As with the intervention arm, if the participant wishes to continue to think aloud so long as it 
doesn’t distract them from completing the task. Participants will be asked to enter their 
medication order for the patient within a ‘test ward’ on the Cerner Millennium Powerchart 
system. 
 
Order of control vs intervention arm-  
Each participant will be randomly assigned to begin with either the control arm or the 
intervention arm (Group 1 and Group 2, see Table 1). With an equal number of participants 
being in each group. A random team generator (https://www.randomlists.com/team-generator) 
will be used for randomisation (see Figure 1) and participants will be assigned their ‘participant 
number’ in the order of their participation in the study. 
 
Table 1 - Order of study arms, Group 1 and Group 2 
Group 1 
Group 2 
Practice 1 (simple) RxConnect 
Practice 2 (complex) RxConnect 
Test scenario 1 Control 
Test scenario 2 Control 
Test scenario 3 Control 
Test scenario 4 RxConnect 
Test scenario 5 RxConnect 
Test scenario 6 RxConnect 
Practice 1 (simple) RxConnect 
Practice 2 (complex) RxConnect 
Test scenario 1 RxConnect 
Test scenario 2 RxConnect 
Test scenario 3 RxConnect 
Test scenario 4 Control 
Test scenario 5 Control 
Test scenario 6 Control 
 
Figure 1 Example of participants randomised into two groups 

 
 
 
 
 
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Sample size 
A target of 30-50 participants is desirable for this descriptive exploratory mixed methods 
study. This number has been selected pragmatically to account for approximately 5 
participants per day over 10 working days.  
Sample size sufficient to calculate statistical significance will not be feasible, therefore a power 
calculation will not be required.  
Data collection and management 
Data collection 
Data will be collected via audio-visual recording which will take place on the SimWard, 
Paterson Building, St Marys Hospital. A Scotia Medical Observation Training System (smots, 
Scotia UK, Edinburgh, UK), with two 3- axis, ceiling- mounted video cameras, and three 
mobile, high-definition cameras equipped with boom microphones, will be used. The cameras 
will be angles at the computer screen ann onto the workstation and will not take footage of 
participants faces. Participants will be asked to remove or cover any name badges that may 
identify them prior to recording commencing. 
The researcher will also keep field notes to assist with later analysis of the observations and 
interviews. The interviews will be transcribed verbatim by the study researcher prior to 
thematic analysis.  
Participant demographic information will be collected via a short ‘demographic questionnaire’ 
at the beginning of the user testing session. Nasa Task Load Index questionnaires will be 
complete by the participant after each of the intervention arms.  
 
Data management 
Physical copies of the consent forms and participant list with pseudonymised participant study 
numbers will be kept within a locked room with swipe card access to the floor of the 
department.  

 
 
 
 
 
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Audio-visual recordings of the observations and semi-structured interview (See Appendix 1 
for a sample interview guide), psuedoanonymised data capture forms and interview transcripts 
will be stored on an encrypted hard drive and kept in a locked room with swipe card access to 
the floor of the department. Interview transcripts will use the participant’s psuedoanonymous 
study code in place of their name. 
 
Publication of study findings will not contain identifiable data, participants will be given a study 
code name and only referred to by their profession and speciality. 
Data and all appropriate documentation will be stored for a minimum of 10 years after the 
completion of the study.   
Duration of study 
The duration of the study will be six months from the date of the first participant recruited. 
Study outcome measures  
The following outcomes will be measured-  
Primary outcome measure-  
 
Number of prescribing errors per scenario 
o 
Subcategorised as - Incorrect drug, dose, route, frequency or patient.  
 
Secondary outcome measures- 
• 
The magnitude of any dose errors (deviation from recommended dosing range) 
• 
Time taken to prescribe each medication  
• 
Prescribers perceived mental load per prescribing scenario  
• 
Hierarchical task analysis 
• 
Qualitative feedback from participants 
 
Number and magnitude of prescribing errors 
We define a prescribing error as any of the following errors: 
- 
Incorrect prescribed dose: prescribed doses that deviate from the recommended dose in 
the BNF/ BNFc or local guideline by more than 10%. 
o 
If the recommended dose is a range, deviations will be calculated from the max/min 
of the range, whichever is closest to the user calculated dose. If there are multiple 
recommended dose options e.g., from the BNF and from local guidelines, the 
researcher will calculate deviations based on the most appropriate source for the 
indication. When all sources are deemed equally valid, the researcher will record 
the smallest deviation allowed. 
o 
Magnitude of dosing error will be calculated as a percentage deviation from the 
recommended dose.  
- 
Incorrect prescribed route: a medication prescribed via a route that deviates from the 
recommended route for the medication and dose as per the BNF/BNFc or local guidelines. 
- 
Incorrect prescribed frequency: a medication prescribed for a frequency that deviates from 
the recommended frequency or that accumulated to a total daily dose for the medication 
and dose as per the BNF/BNFc or local guidelines. 
- 
Incorrect patient: a medication order issued to incorrect patient’s electronic medication 
chart. 
 

 
 
 
 
 
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Time 
The length of time for each prescribing scenario will be calculated from the time the participant 
begins to read the first scenario, and for subsequent scenarios from the time they complete 
one scenario and move onto the next.  
 
Task load index  
At the end of each scenario the user will be provided with an online NASA TLX (task load 
index) form to complete (8).  
 
Hierarchical task analysis 
Hierarchical task analysis (HTA) will be conducted for each of scenario, a framework will be 
created apriori based on the anticipated task steps and previous research (9,10), however any 
additional steps will be added if observed during video analysis. HTA results for participants 
using RxConnect will be compared to their usual practise.  
 
Qualitative interviews 
Following completion of the user testing scenarios, the participant will be invited to take part 
in a short semi-structured interview regarding their experience of using RxConnect and other 
more generic questions regarding the use of digital dosing support and indication-based 
prescribing. (See Appendix 1 for a sample interview guide).  
Statistics and data analysis  
 
Sample size 
A sample size of 30-50 participants is desirable for this descriptive exploratory mixed methods 
study. A sample size calculation is therefore not relevant for this study.   
 
Statistical analysis 
Categorical data (error counts) from the control arm and intervention arm will be compared 
using the chi-square test.  
Continuous data (magnitude of error, time, task load) will be measured using Mann-Whitney 
test for non-parametric data.  
Sub analysis will explore the effect of possible confounders will be measured using 
multivariate logistic regression, subject to effect size and sample size limitations.  
Variables which may be accounted for include - group number, scenario number, prescribing 
scenario complexity, prescriber grade, prescriber speciality, control arm or intervention arm. 
 
Hierarchical task analysis 
Hierarchical task analysis will be conducted to provide an overview of the prescribing workflow 
for the control arm and intervention. Vulnerable process steps can be highlighted if they are 
associated with increased error or time taken when prescribing the scenarios, along with any 
feedback from participants during practice, observation or in the qualitative interview. 
 
Thematic analysis 
Thematic analysis will be conducted using data from throughout the observations and the 
qualitative interviews (11). 

 
 
 
 
 
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4. PARTICIPANT RECRUITMENT 
A convenience sample of study participants will be recruited from across Imperial College NHS 
Healthcare Trust. Study participants will be doctors and non-medical prescribers whose usual 
course of work involves the prescribing of medication. 
Targeted sampling may be conducted to gain participants from a wide range of specialities/ 
levels of seniority including but not limited to-  
 
 
• 
Seniority- 
o 
 Foundation Year 1 and 2, Senior House Officers, Registrars, 
Consultants, Non-medical prescribers (nurses and pharmacists) 
• 
Specialities, 
o 
 Medical, Surgical, Paediatrics, Neonatal, Emergency medicine 
 
Department leads and managers will be approached to gain permission prior to any approach 
of relevant medical staff and will be asked to disseminate invitations to participate in this study. 
Staff will be sent an email via their trust email address via the departments ‘email group’. In 
addition, an advert will be placed on the trust intranet and further advertisement of the study 
through word of mouth via established working relationships within ICHT and ICL.  
Participants will be provided with a participant information sheet at least a week prior to 
commencing any recruitment/data collection.  
On the day of participating, participants will have the option to ask any further questions before 
deciding to take part and a copy of the participant information sheet will be available as either 
paper copy or via email as a PDF. 
 
As participants will be NHS staff, there will be an expectation that participants will have 
adequate English language skills (reading, written and verbal) to be able to provide informed 
consent and participate. However, if adaptations are required for a member of staff to 
participate, (such as information sheets printed in larger font/different colours) this will be 
accommodated as per any normal adaptations required for working. 
 
Participation in the study should take approximately 90 minutes and will not detract from 
clinical duties, where possible participation should be during non-clinical hours and/or when 
appropriate clinical cover is available. 
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 

 
 
 
 
 
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Withdrawal Criteria 
Participants are free to withdraw consent at any point. For any data collected up to that point 
consent will be sought to use this data, if consent declined then data will be digitally deleted, 
and any paper documentation disposed of as confidential waste. If a participant wishes to 
withdraw their consent at a later date, this can only be accommodated if analysis of the study 
results has not yet begun. 
Follow up 
Participants will not require any further follow up after completing their session. Should 
participants wish to be informed when the results are published, they may leave a contact 
email address on their consent form, as per the participant information sheet and consent 
form. In the case of any incidental findings during the observations, such as repeated 
erroneous prescribing which may indicate educational needs for one or more participants, the 
participants will be informed in a discrete and sensitive manner and the participants line 
manager and practice educator will be informed.  
 
The end of the study is defined as when the data is collected from the last participant. 
 
5. Adverse events  
Definitions  
Adverse Event (AE): any untoward medical occurrence in a patient or clinical study subject.   
 
Serious Adverse Event (SAE): any untoward medical occurrence or effect that: 
• 
Results in death 
• 
Is life-threatening – refers to an event in which the subject was at risk of death at the 
time of the event; it does not refer to an event which hypothetically might have caused 
death if it were more severe 
 
• 
Requires hospitalisation, or prolongation of existing inpatients’ hospitalisation 
• 
Results in persistent or significant disability or incapacity 
• 
Is a congenital anomaly or birth defect 
 
Medical judgement should be exercised in deciding whether an AE is serious in other situations.  
Important AEs that are not immediately life-threatening or do not result in death or hospitalisation 
but may jeopardise the subject or may require intervention to prevent one of the other outcomes 
listed in the definition above, should also be considered serious. 
Reporting procedures  
All adverse events should be reported.  Depending on the nature of the event the reporting 
procedures below should be followed.  Any questions concerning adverse event reporting should be 
directed to the Chief Investigator in the first instance.   
 
Non serious AEs 

 
 
 
 
 
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All such events, whether expected or not, should be recorded- it should be specified if only some non-
serious AEs will be recorded, any reporting should be consistent with the purpose of the trial end 
points.  
 
Serious AEs 
An SAE form should be completed and emailed to the Chief Investigator within 24 hours.  However, 
relapse and death due to a pre-existing condition, and hospitalisations for elective treatment of a pre-
existing condition do not need reporting as SAEs. 
 
All SAEs should be reported to the <name of REC> where in the opinion of the Chief Investigator, the 
event was: 
• 
‘related’, ie resulted from the administration of any of the research procedures; and 
• 
‘unexpected’, ie an event that is not listed in the protocol as an expected occurrence 
 
Reports of related and unexpected SAEs should be submitted within 15 days of the Chief Investigator 
becoming aware of the event, using the NRES SAE form for non-IMP studies.  The Chief Investigator 
must also notify the Sponsor of all related and unexpected SAEs. 
 
Local investigators should report any SAEs as required by their Local Research Ethics Committee, 
Sponsor and/or Research & Development Office. 
 
Contact details for reporting SAEs 
RGIT@imperial.ac.uk 
CI email (and contact details below) 
Please send SAE forms to: bryony.franklin@nhs.net   
 
6. REGULATORY ISSUES 
Ethics approval 
The Study Coordination Centre has obtained approval from the Health Research Authority 
(HRA). The study has received confirmation of capacity and capability from each participating 
NHS Trust before accepting participants into the study or any research activity is carried out. 
The study will be conducted in accordance with the recommendations for physicians involved 
in research on human subjects adopted by the 18th World Medical Assembly, Helsinki 1964 
and later revisions. 
Consent  
Consent to enter the study must be sought from each participant only after a full explanation 
has been given, an information leaflet offered and time allowed for consideration.  Signed 
participant consent should be obtained.  The right of the participant to refuse to participate 
without giving reasons must be respected.  After the participant has entered the study the 
clinician remains free to give alternative treatment to that specified in the protocol at any stage 
if he/she feels it is in the participant’s best interest, but the reasons for doing so should be 

 
 
 
 
 
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recorded.  In these cases the participants remain within the study for the purposes of follow-
up and data analysis.  All participants are free to withdraw at any time from the protocol 
treatment without giving reasons and without prejudicing further treatment. 
 
Confidentiality 
The Chief Investigator will preserve the confidentiality of participants taking part in the study 
and is registered under the Data Protection Act. 
 
Data will be pseudonymised. 
 
Indemnity 
Imperial College London holds negligent harm and non-negligent harm insurance policies 
which apply to this study. 
 
Sponsor 
Imperial College London will act as the main Sponsor for this study.  Delegated responsibilities 
will be assigned to the NHS trusts taking part in this study. 
Funding 
The National Institute for Health and Care Research are funding this study. Infrastructure 
support for this research was provided by the NIHR Imperial Biomedical Research Centre 
(BRC) and the NIHR Imperial Patient Safety Translational Research Centre (PSTRC).  
 
Participants and individual researchers will not receive any payments, 
reimbursement of expenses or any other benefits or incentives for taking part in this 
research.  
 
Audits  
The study may be subject to audit by Imperial College London under their remit as sponsor 
and other regulatory bodies to ensure adherence to GCP and the UK Policy Frame Work for 
Health and Social Care Research.  
 
7. PUBLICATION POLICY 
The results of this study will be disseminated through open peer reviewed journals and 
presentation at relevant local meetings and national/international conferences.  
 
8. REFERENCES 
1.  
Medication Without Harm - Global Patient Safety Challenge on Medication 
Safety. Geneva; 2017.  
2.  
Elliott RA, Camacho E, Campbell F, Jankovic D, James MS, Kaltenthaler E, et 

 
 
 
 
 
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al. Prevalence and Economic Burden of Medication Errors in the Nhs in 
England. Policy Res Unit Econ Eval Heal Care Interv [Internet]. 2018;1–174. 
Available from: http://www.eepru.org.uk/wp-content/uploads/2018/02/eepru-
report-medication-error-feb-2018.pdf 
3.  
Tolley CL, Slight SP, Husband AK, Watson N, Bates DW. Improving 
medication-related clinical decision support. Am J Heal Pharm. 
2018;75(4):239–46.  
4.  
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/a
ttachment_data/file/970563/Human-Factors_Medical-Devices_v2.0.pdf 
5.  
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;20(1):1–8.  
6.  
Holden RJ, Abebe E, Russ-Jara AL, Chui MA. Human factors and ergonomics 
methods for pharmacy research and clinical practice. Res Soc Adm Pharm 
[Internet]. 2021;17(12):2019–27. Available from: 
https://doi.org/10.1016/j.sapharm.2021.04.024 
7.  
Novak LL, Holden RJ, Anders SH, Hong JY, Karsh B-T. Using a sociotechnical 
framework to understand adaptations in health IT implementation Laurie. 
2013;82(12):1–27.  
8.  
Nasa. NASA Task Load Index. Hum Ment Workload [Internet]. 2006;1(6):21–
21. Available from: 
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&do
pt=Citation&list_uids=16243365 
9.  
Appelbaum N, Clarke J, Feather C, Franklin B, Sinha R, Pratt P, et al. 
Medication errors during simulated paediatric resuscitations: A prospective, 
observational human reliability analysis. BMJ Open. 2019;9(11).  
10.  Sutherland A, Ashcroft DM, Phipps DL. Exploring the human factors of 
prescribing errors in paediatric intensive care units. Arch Dis Child. 
2019;104(6):588–95.  
11.  Braun V, Clarke V. Successful qualitative research : a practical guide for 
beginners. SAGE; 2013. 382 p.  
 
 
9. Appendix 1: Draft semi-structured interview topic guide 
 
RxConnect user testing questions- 
• 
Please tell me how you found today’s user testing session. 
o 
Could you describe how you found using RxConnect to complete the 
prescribing tasks. 
o 
How did this compare with your current prescribing practice? 
• 
What effect do you think a system such as RxConnect could have on your prescribing 
practice?   

 
 
 
 
 
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o 
If positive, in what way? 
o 
If negative, in what way?  
o 
Is there anything that you think would benefit from changing/improving? 
 
Indication-based prescribing workflow questions –  
• 
Did you utilise the option to search by indication as opposed to by medication first? 
• 
How does this align with your current prescribing workflow, both your mental workflow 
and decision making as well as the physical act of prescribing, for example entering 
the information onto the prescription? 
• 
Would you consider an indication-first prescribing workflow to be better/worse/the 
same as current prescribing workflows.  For example, searching for an indication and 
then selecting a medication, rather than searching for the medication.  
 
Probes – 
• 
Can you expand on that 
• 
Do you have any examples – 
o 
where this would have been useful...? 
o 
where this may have hindered...? 
o 
specific patient groups 
o 
specific medication types – antimicrobial stewardship 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
10. Appendix 2: Draft Study session standard operating 
procedure 
 
 
1. Participant will have already received an invitation to participate and agreed a time to 
take part in the study. 
2. Participant arrives at pre-specified time, confirms they have received the PIS and has 
had any questions answered. 

 
 
 
 
 
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3. Participant to complete the consent form and an online copy to be sent to the 
participant to retain for their own records. Participants will be asked to remove or cover 
any name badges that may identify themselves.  
4. Audio-visual recording to begin. 
5. Participant training and briefing- 
 
Participant RxConnect training- 
A brief introductory video to be played to the participant showing how to use 
RxConnect.  
 
Participant study briefing- 
Participants to be briefed as to the purpose of the user testing and that scenarios will 
be presented that may cover a number of conditions, complexities and potentially error 
prone prescribing tasks, e.g. patients with contraindicated conditions, considerations 
and less frequently prescribed medications. 
 
6. Participant encouraged to ‘think aloud’ when completing the following tasks. 
Participants are provided with two prescribing practice scenarios to complete using 
RxConnect and document the medication order on the paper form provided.  
7. Confirm that the user is happy with how to use RxConnect and have any questions 
answered, a third prescribing practice scenario can be used if required. 
8. Depending on allocation of control first or intervention first the participant is to complete 
4 prescribing scenarios independently, they may ‘think aloud’ if the desire but this 
should not distract from the task.  
9. Following each individual scenario, the participant is to complete a NASA TLX form.  
10. Qualitative interview-  
Confirm that the participant consents to continue with a short semi-structured interview. 
Conduct the interview using the topic guide 
11. Discontinue audio-visual recording.