Development of an algorithm to detect and reduce complexity of drug treatment and its technical realisation

Abstract

Background: The increasing complexity of current drug therapies jeopardizes patient adherence. While individual needs to simplify a medication regimen vary from patient to patient, a straightforward approach to integrate the patients' perspective into decision making for complexity reduction is still lacking. We therefore aimed to develop an electronic, algorithm-based tool that analyses complexity of drug treatment and supports the assessment and consideration of patient preferences and needs regarding the reduction of complexity of drug treatment. Methods: Complexity factors were selected based on literature and expert rating and specified for integration in the automated assessment. Subsequently, distinct key questions were phrased and allocated to each complexity factor to guide conversation with the patient and personalize the results of the automated assessment. Furthermore, each complexity factor was complemented with a potential optimisation measure to facilitate drug treatment (e.g. a patient leaflet). Complexity factors, key questions, and optimisation strategies were technically realized as tablet computer-based application, tested, and adapted iteratively until no further technical or contentrelated errors occurred. Results: In total, 61 complexity factors referring to the dosage form, the dosage scheme, additional instructions, the patient, the product, and the process were considered relevant for inclusion in the tool; 38 of them allowed for automated detection. In total, 52 complexity factors were complemented with at least one key question for preference assessment and at least one optimisation measure. These measures included 29 recommendations for action for the health care provider (e.g. to suggest a dosage aid), 27 training videos, 44 patient leaflets, and 5 algorithms to select and suggest alternative drugs.

Prevalence and patient-rated relevance of complexity factors in medication regimens of community-dwelling patients with polypharmacy

“…Is it difficult for you to use this drug always at the same day of the week?" for the complexity factor once weekly administration) [5]. If the patient indicated to experience any difficulties, the complexity factor was considered to be relevant for the patient in the analysis.…”

“…To integrate the patient's assessment of prevalent complexity, we have previously developed an electronic tool that combines an automated analysis of complexity of drug treatment with an individual assessment of the relevance of each complexity factor for the respective patient [5]. The electronic tool considers 38 complexity factors that can be identified automatically in structured medication data and can be assigned to one of the following categories: dosage form, dosage scheme, process characteristics, product characteristics, and additional instructions.…”

Process Evaluation of the SImplification of Medications Prescribed to Long-tErm Care Residents (SIMPLER) Cluster Randomized Controlled Trial: A Mixed Methods Study

“…One participant suggested that prescribers could use MRS GRACE to guide simplification when preparing new medication charts as a potential point for future intervention. Previous studies in other settings have utilized screening tools, algorithms and/or electronic medication chart prompts to identify individuals with complex medication regimens [ 37 , 38 , 39 ]. Additionally, in the Australian state of Victoria, a medication quality indicator ‘percentage of residents with more than four medication administration times’ was developed, validated and implemented across all 180 public-sector RACFs as a prompt to reduce unnecessary complexity [ 16 ].…”

HIOPP-6 – a pilot study on the evaluation of an electronic tool to assess and reduce the complexity of drug treatment considering patients’ views

“…The tool was exploratively evaluated in a controlled, prospective, pilot study with general practitioners (GP) allocated to three study groups. Group 1 (G I_with ) used the full version of the tool [ 11 ], while group 2 (G I_without ) used a version of the tool with limited functionality that did not propose key questions and, therefore, lacked personalization of the automated results. Group 3 (G C ) was a control group representing routine care where physicians did neither receive a training in complexity reduction nor use any version of the tool.…”

“…Therefore, an electronic tool was developed that is applied by health professionals but attempts to comprehensively consider the patient perspective [ 11 ]. It automatically screens structured medication data for 38 known factors contributing to complexity (automated assessment).…”