跳至主要内容
临床试验/NCT05493072
NCT05493072已完成不适用

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

Imperial College London1 个研究点 分布在 1 个国家目标入组 24 人开始时间: 2022年12月12日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
入组人数
24
试验地点
1
主要终点
Number of Prescribing Errors by Study Arm

研究概览

简要总结

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.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Crossover
主要目的
Basic Science
盲法
Single (Participant)

入排标准

性别
All
接受健康志愿者

入选标准

  • 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

排除标准

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

结局指标

主要结局

Number of Prescribing Errors by Study Arm

时间窗: 60 minutes

Sub analysis of errors by type available in full report

次要结局

  • 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)

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

Loading locations...

相似试验