Development and Preliminary Validation of LoAD Calc, a Mobile App for Calculating the Maximum Safe Single Dose of Local Anesthetics

Comparing the Effectiveness of a Clinical Decision Support Tool in Reducing Pediatric Opioid Dose Calculation Errors: PediPain App vs. Traditional Calculators - A Simulation-Based Randomised Controlled Study

Wrong dose calculation medication errors are widespread in pediatric patients mainly due to weight-based dosing. PediPain app is a clinical decision support tool that provides weight- and age- based dosages for various analgesics. We hypothesized that the use of a clinical decision support tool, the PediPain app versus pocket calculators for calculating pain medication dosages in children reduces the incidence of wrong dosage calculations and shortens the time taken for calculations. The study was a randomised controlled trial comparing the PediPain app vs. pocket calculator for performing eight weight-based calculations for opioids and other analgesics. Participants were healthcare providers routinely administering opioids and other analgesics in their practice. The primary outcome was the incidence of wrong dose calculations. Secondary outcomes were the incidence of wrong dose calculations in simple versus complex calculations; time taken to complete calculations; the occurrence of tenfold; hundredfold errors; and wrong-key presses. A total of 140 residents, fellows and nurses were recruited between June 2018 and November 2019; 70 participants were randomized to control group (pocket calculator) and 70 to the intervention group (PediPain App). After randomization two participants assigned to PediPain group completed the simulation in the control group by mistake. Analysis was by intention-to-treat (PediPain app = 68 participants, pocket calculator = 72 participants). The overall incidence of wrong dose calculation was 178/576 (30.9%) for the control and 23/544 (4.23%) for PediPain App, P < 0·001. The risk difference was - 32.8% [-38.7%, -26.9%] for complex and - 20.5% [-26.3%, -14.8%] for simple calculations. Calculations took longer within control group (median of 69 Sects. [50, 96]) compared to PediPain app group, (median 48 Sects. [38, 63]), P < 0.001. There were no differences in other secondary outcomes. A weight-based clinical decision support tool, the PediPain app reduced the incidence of wrong doses calculation. Clinical decision support tools calculating medications may be valuable instruments for reducing medication errors, especially in the pediatric population.

Local anaesthetics risks perception: A web-based survey

Background

The use of local anaesthetics (LAs) is usually associated with few adverse effects, but local anaesthetic systemic toxicity (LAST) can result in serious harm and even death. However, practitioner awareness regarding this risk has been little studied.

Methods

This was a closed, web-based study carried out at two Swiss university hospitals using a fully automated questionnaire. The main objective was to evaluate LAST awareness and LA use among various medical practitioners. The secondary objective was to determine whether these physicians felt that a tool designed to compute maximum safe LA doses should be developed.

Results

The overall participation rate was 40.2 % and was higher among anaesthesiologists (154/249, 61.8 % vs 159/530, 30.0 %; P < .001). Anaesthesiologists identified the risk of LAST and the systems involved more frequently than non-anaesthesiologists (85.1 % vs 43.4 %, P < .001). After adjusting for years of clinical experience, age, country of diploma, frequency of LA use, clinical position and being an anaesthesiologist, the only significant associations were this latter factor (P < .001) and clinical position (P = .016 for fellows and P = .046 for consultants, respectively). Most respondents supported the development of a tool designed to compute maximum safe LA doses (251/313, 80.2 %) and particularly of a mobile app (190/251, 75.7 %).

Conclusions

LAST awareness is limited among practitioners who use LAs on a regular basis. Educational interventions should be created, and tools designed to help calculate maximum safe LA doses developed. The actual frequency of unsafe LA doses administration would also deserve further study.

Impact of a Mobile App (LoAD Calc) on the Calculation of Maximum Safe Doses of Local Anesthetics: Protocol for a Randomized Controlled Trial

BACKGROUND

Local anesthetics (LAs) are regularly used to alleviate pain during medical or surgical procedures. Their use is generally considered safe, but exceeding the maximum recommended doses can lead to LA systemic toxicity, a rare but potentially lethal complication. Determining maximum safe doses is therefore mandatory before performing local anesthesia, but rules are often unclear and the factors affecting dose calculation are numerous. Mobile health apps have been shown to help clinical decision-making, but most currently available apps present significant limitations. The Local Anesthetics Dose Calculator (LoAD Calc) app was designed to overcome these limitations by taking all relevant parameters into account. Before deploying this app in a clinical setting, it should be tested to determine its effectiveness and whether clinicians would be willing to use it.

OBJECTIVE

The primary objective will be to evaluate the effectiveness of the LoAD Calc app through written simulated cases. The secondary objective will be to determine whether physicians find this app easier, faster, and safer than the methods they generally use.

METHODS

We describe a parallel-group randomized controlled trial protocol. Anesthesiologists working at the Geneva University Hospitals will be invited to participate. Participants will be asked to compute the maximum dose of LA in 10 simulated clinical cases using 3 different LAs. The maximum safe dose will be determined manually using the same calculation rules that were used to develop LoAD Calc, without using the app itself. An overdose will be considered any dose higher than the correct dose, rounded to the superior integer, while an underdose will be defined as the optimal calculated dose minus 20%, rounded to the inferior integer. Randomization will be stratified according to current position (resident vs registrar). The participants allocated to the LoAD Calc (experimental) group will use the LoAD Calc app to compute the maximum safe LA doses. Those allocated to the control group will be asked to use the method they generally use. The primary outcome will be the overall overdose rate. Secondary outcomes will include the overdose rate according to ideal and actual body weight and to each specific LA, the overall underdose rate, and the time taken to complete these calculations. The app's usability will also be assessed.

RESULTS

A sample size of 46 participants will be needed to detect a difference of 10% with a power of 90%. Thus, a target of 50 participants was set to allow for attrition and exclusion criteria. We expect recruitment to begin during the winter of 2023, data analysis in the spring of 2024, and results by the end of 2024.

CONCLUSIONS

This study should determine whether LoAD Calc, a mobile health app designed to compute maximum safe LA doses, is safer and more efficient than traditional LA calculation methods.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/53679.