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Design, development, and deployment of an indication- and kidney function-based decision support tool to optimize treatment and reduce medication dosing errors.

ABSTRACT: Delivering clinical decision support (CDS) at the point of care has long been considered a major advantage of computerized physician order entry (CPOE). Despite the widespread implementation of CPOE, medication ordering errors and associated adverse events still occur at an unacceptable level. Previous attempts at indication- and kidney function-based dosing have mostly employed intrusive CDS, including interruptive alerts with poor usability. This descriptive work describes the design, development, and deployment of the Adult Dosing Methodology (ADM) module, a novel CDS tool that provides indication- and kidney-based dosing at the time of order entry. Inclusion of several antimicrobials in the initial set of medications allowed for the additional goal of optimizing therapy duration for appropriate antimicrobial stewardship. The CDS aims to decrease order entry errors and burden on providers by offering automatic dose and frequency recommendations, integration within the native electronic health record, and reasonable knowledge maintenance requirements. Following implementation, early utilization demonstrated high acceptance of automated recommendations, with up to 96% of provided automated recommendations accepted by users.

SUBMITTER: Hirsch JS

PROVIDER: S-EPMC8242134 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Design, development, and deployment of an indication- and kidney function-based decision support tool to optimize treatment and reduce medication dosing errors.

Hirsch Jamie S JS Brar Rajdeep R Forrer Christopher C Sung Christine C Roycroft Richard R Seelamneni Pradeep P Dabir Hemala H Naseer Ambareen A Gautam-Goyal Pranisha P Bock Kevin R KR Oppenheim Michael I MI

JAMIA open 20210401 2

Delivering clinical decision support (CDS) at the point of care has long been considered a major advantage of computerized physician order entry (CPOE). Despite the widespread implementation of CPOE, medication ordering errors and associated adverse events still occur at an unacceptable level. Previous attempts at indication- and kidney function-based dosing have mostly employed intrusive CDS, including interruptive alerts with poor usability. This descriptive work describes the design, developm ...[more]

PMID: 34222830

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Project description:BackgroundPolypharmacy and inappropriate continuation of medicines can lead to a significant risk of adverse drug events and drug interactions with patient harm and escalating health care costs as a result. Thorough review of patients' medications focusing on the need for each drug can reduce the potential for harm. Limitations in performing effective medicine reviews in practice include consultation time constraints and funding for pharmacy services. We will aim to overcome these problems by designing an automatic electronic decision support tool (the medicines optimization/review and evaluation (MORE) module) that is embedded in general practice electronic records systems. The tool will focus on medicines optimization and reducing polypharmacy to aid prescribers in reviewing medicines and improve patient outcomes.ObjectiveThe objectives of this study are: (1) to develop an electronic decision support tool to assist prescribers in performing clinical medication reviews with a particular focus on patients experiencing multimorbidity and polypharmacy, and (2) evaluate and assess the use of the electronic decision support tool, providing pilot data on its usefulness in supporting prescribers during consultations with patients.MethodsThe first three study phases involve development of clinical rules outlining clinical interventions and the creation and validation of the MORE decision support tool. Phase four is a community-based, single-blind, prospective, 6-month controlled trial involving two interventions and two control general practices, matched for practice demographics. We will be measuring the number of times prescribers engage with the tool, total number of interventions suggested by the tool, and total number of times prescribers change medicines in response to recommendations. There will also be prospective follow-up of patients in the intervention group to examine whether changes to medications are upheld, and to determine the number of hospitalizations or emergency department visits within 6 months of a medicine intervention. Comparisons between control and intervention practices will measure the changes in proportions of patients with polypharmacy and inappropriately prescribed medicines before and after the introduction of the electronic decision support tool, proportions of patients receiving appropriate treatment in each practice, and changed, maintained, or improved health status, hospitalizations, and deaths in the study year. Initiation rates of inappropriately prescribed medicines will be measured as a secondary outcome. As well as external assessment of the extent of use and application of the tool, prescribers will receive monthly practice progress reports detailing the proportion of their patients experiencing polypharmacy and taking inappropriately prescribed medicines identified for review.ResultsPhase one has now been completed and the decision support tool is under development. Final data analysis is expected to be available in December 2016.ConclusionsThis study will establish whether the MORE decision support tool stands up to real world conditions and promotes changes in prescribing practice.

Project description:Poorly designed labels and dosing tools contribute to dosing errors. We examined the degree to which errors could be reduced with pictographic diagrams, milliliter-only units, and provision of tools more closely matched to prescribed volumes. This study involved a randomized controlled experiment in 3 pediatric clinics. English- and Spanish-speaking parents (n = 491) of children ≤8 years old were randomly assigned to 1 of 4 groups and given labels and dosing tools that varied in label instruction format (text and pictogram, or text only) and units (milliliter-only ["mL"] or milliliter/teaspoon ["mL/tsp"]). Each parent measured 9 doses of liquid medication (3 amounts [2, 7.5, and 10 mL] and 3 tools [1 cup, 2 syringes (5- and 10-mL capacities)]) in random order. The primary outcome was dosing error (>20% deviation), and large error (>2× dose). We found that 83.5% of parents made ≥1 dosing error (overdosing was present in 12.1% of errors) and 29.3% of parents made ≥1 large error (>2× dose). The greatest impact on errors resulted from the provision of tools more closely matched to prescribed dose volumes. For the 2-mL dose, the fewest errors were seen with the 5-mL syringe (5- vs 10-mL syringe: adjusted odds ratio [aOR] = 0.3 [95% confidence interval: 0.2-0.4]; cup versus 10-mL syringe: aOR = 7.5 [5.7-10.0]). For the 7.5-mL dose, the fewest errors were with the 10-mL syringe, which did not necessitate measurement of multiple instrument-fulls (5- vs 10-mL syringe: aOR = 4.0 [3.0-5.4]; cup versus 10-mL syringe: aOR = 2.1 [1.5-2.9]). Milliliter/teaspoon was associated with more errors than milliliter-only (aOR = 1.3 [1.05-1.6]). Parents who received text only (versus text and pictogram) instructions or milliliter/teaspoon (versus milliliter-only) labels and tools made more large errors (aOR = 1.9 [1.1-3.3], aOR = 2.5 [1.4-4.6], respectively). Provision of dosing tools more closely matched to prescribed dose volumes is an especially promising strategy for reducing pediatric dosing errors.

Dataset Information

Design, development, and deployment of an indication- and kidney function-based decision support tool to optimize treatment and reduce medication dosing errors.

Publications

Design, development, and deployment of an indication- and kidney function-based decision support tool to optimize treatment and reduce medication dosing errors.

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