Review: Polypharmacy and precision medicine — R0/PR2 DOI Creative Commons

Опубликована: Ноя. 23, 2022

Precision medicine is an approach to maximise the effectiveness of disease treatment and prevention minimise harm from medications by considering relevant demographic, clinical, genomic environmental factors in making decisions. complex, even for decisions about single drugs diseases, as it requires expert consideration multiple measurable that affect pharmacokinetics pharmacodynamics, many patient-specific variables. Given increasing number patients with conditions medications, there a need apply lessons learned precision monotherapy management optimise polypharmacy. However, optimisation polypharmacy particularly challenging because vast interacting influence drug use response. In this narrative review, we aim provide latest research findings achieve context Specifically, review aims (1) summarise challenges achieving specific polypharmacy; (2) synthesise current approaches (3) summary literature field prediction unknown drug–drug interactions (DDI) (4) propose novel For our proposed model be implemented routine clinical practice, comprehensive intervention bundle needs integrated into electronic medical record using bioinformatic on wide range data predict effects regimens individual. addition, clinicians trained interpret results sources including pharmacogenomic testing, DDI physiological-pharmacokinetic-pharmacodynamic modelling inform their medication reviews. Future studies are needed evaluate efficacy test generalisability so can at scale, aiming improve outcomes people

Язык: Английский

Polypharmacy and precision medicine DOI Creative Commons
Kenji Fujita, Nashwa Masnoon, John Mach

и другие.

Cambridge Prisms Precision Medicine, Год журнала: 2023, Номер 1

Опубликована: Янв. 1, 2023

Precision medicine is an approach to maximise the effectiveness of disease treatment and prevention minimise harm from medications by considering relevant demographic, clinical, genomic environmental factors in making decisions. complex, even for decisions about single drugs diseases, as it requires expert consideration multiple measurable that affect pharmacokinetics pharmacodynamics, many patient-specific variables. Given increasing number patients with conditions medications, there a need apply lessons learned precision monotherapy management optimise polypharmacy. However, optimisation polypharmacy particularly challenging because vast interacting influence drug use response. In this narrative review, we aim provide latest research findings achieve context Specifically, review aims (1) summarise challenges achieving specific polypharmacy; (2) synthesise current approaches (3) summary literature field prediction unknown drug-drug interactions (DDI) (4) propose novel For our proposed model be implemented routine clinical practice, comprehensive intervention bundle needs integrated into electronic medical record using bioinformatic on wide range data predict effects regimens individual. addition, clinicians trained interpret results sources including pharmacogenomic testing, DDI physiological-pharmacokinetic-pharmacodynamic modelling inform their medication reviews. Future studies are needed evaluate efficacy test generalisability so can at scale, aiming improve outcomes people

Язык: Английский

Процитировано

17
Clinical decision support system in emergency telephone triage: A scoping review of technical design, implementation and evaluation DOI Creative Commons

J. Michel,

A Manns,

Sofia Boudersa

и другие.

International Journal of Medical Informatics, Год журнала: 2024, Номер 184, С. 105347 - 105347

Опубликована: Янв. 25, 2024

Emergency department overcrowding could be improved by upstream telephone triage. triage aims at managing and orientating adequately patients as early possible distributing limited supply of staff materials. This complex task with the use Clinical decision support systems (CDSS). The aim this scoping review was to identify literature gaps for future development evaluation CDSS

Язык: Английский

Процитировано

6
Computerized clinical decision support systems for prescribing in Primary Care: characteristics and implementation impact. Scoping review and Evidence and gap maps. DOI Creative Commons
Héctor Acosta-García, Juan Ruano,

Francisco Gómez‐García

и другие.

Health Policy and Technology, Год журнала: 2025, Номер unknown, С. 100976 - 100976

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Medication Management in Patients With Polypharmacy in Primary Care: A Scoping Review of Clinical Practice Guidelines DOI Creative Commons
L Engels, Marjan van den Akker, Petra Denig

и другие.

Journal of Evidence-Based Medicine, Год журнала: 2025, Номер 18(1)

Опубликована: Март 1, 2025

Inappropriate polypharmacy increases the risk of medication-related issues. Adequate management is a challenge involving different healthcare professionals, complex decision-making and ideally including patient involvement. The objective this scoping review was to provide an overview national recommendations for medication patients with in primary care. A clinical practice guidelines focusing on adults polypharmacy, applicable care performed. Databases (G-I-N, Turning Research into Practice PubMed), network, global report were screened published after 2000 English, Dutch, German, Spanish, French, or Russian. Raw data extracted duplicate using extraction framework strategies, involvement involvement, implementation. Qualitative content analysis used. Guideline quality assessed AGREE-II. study registered Open Science Framework. Eight originating from eight countries included. most common recommended strategy conducted by general practitioner and/or community pharmacist. Tasks target population differed per guideline. Most process, mostly elicit patient's experiences treatment goals. Few included advice implementation recommendations. Three out good (AGREE-II score >70% 5/6 domains). review, as Guidance task division less clear. This illustrates room guideline improvements.

Язык: Английский

Процитировано

0
ABiMed: An intelligent and visual clinical decision support system for medication reviews and polypharmacy management DOI Creative Commons

Mouazer Abdelmalek,

Léguillon Romain,

Boudegzdame Nada

и другие.

BMC Medical Informatics and Decision Making, Год журнала: 2025, Номер 25(1)

Опубликована: Апрель 23, 2025

Язык: Английский

Процитировано

0
Artificial Intelligence–Based Clinical Decision Support Systems in Geriatrics: An Ethical Analysis DOI Creative Commons
Tobias Skuban-Eiseler, Marcin Orzechowski, Michael Denkinger

и другие.

Journal of the American Medical Directors Association, Год журнала: 2023, Номер 24(9), С. 1271 - 1276.e4

Опубликована: Июль 12, 2023

To provide an ethical analysis of the implications usage artificial intelligence-supported clinical decision support systems (AI-CDSS) in geriatrics.Ethical based on normative arguments regarding use AI-CDSS geriatrics using a principle-based framework.Normative identified 29 articles geriatrics.Our is literature search that was done to determine are currently discussed AI-CDSS. The relevant were subjected detailed qualitative considerations Supplementary Datamentioned therein. We then within frame 4 principles medical ethics according Beauchamp and Childress with respect needs frail older adults.We found total 5089 articles; met inclusion criteria subsequently analysis. could not identify any systematic geriatrics. very unsystematic scattered, existing has predominantly technical focus emphasizing technology's utility. In extensive analysis, we systematically discuss geriatrics.AI-CDSS can be great asset, especially when dealing patients cognitive disorders; however, from perspective, see need for further research. By AI-CDSS, patients' values beliefs might overlooked, quality doctor-patient relationship altered, endangering compliance Childress.

Язык: Английский

Процитировано

9
Validation of a novel Artificial Pharmacology Intelligence (API) system for the management of patients with polypharmacy DOI
Dorit Dil-Nahlieli,

Arie Ben‐Yehuda,

Daniel Souroujon

и другие.

Research in Social and Administrative Pharmacy, Год журнала: 2024, Номер 20(7), С. 633 - 639

Опубликована: Апрель 10, 2024

Язык: Английский

Процитировано

2
Automated Detection of Patients at High Risk of Polypharmacy including Anticholinergic and Sedative Medications DOI Open Access

Amirali Shirazibeheshti,

Alireza Ettefaghian,

Farbod Khanizadeh

и другие.

International Journal of Environmental Research and Public Health, Год журнала: 2023, Номер 20(12), С. 6178 - 6178

Опубликована: Июнь 19, 2023

Ensuring that medicines are prescribed safely is fundamental to the role of healthcare professionals who need be vigilant about risks associated with drugs and their interactions other (polypharmacy). One aspect preventative use artificial intelligence identify patients at risk using big data analytics. This will improve patient outcomes by enabling pre-emptive changes medication on identified cohort before symptoms present. paper presents a mean-shift clustering technique used groups highest polypharmacy. A weighted anticholinergic score drug interaction were calculated for each 300,000 records registered major regional UK-based provider. The two measures input into algorithm this grouped clusters reflecting different levels polypharmaceutical risk. Firstly, results showed that, most data, average scores not correlated and, secondly, high outliers have one measure but both. These suggest any systematic recognition high-risk should consider both drug–drug avoid missing patients. was implemented in management system easily automatically identifies far faster than manual inspection records. much less labour-intensive can focus assessment only within group(s), more timely clinical interventions where necessary.

Язык: Английский

Процитировано

6
Development and translation of human-AI interaction models into working prototypes for clinical decision-making DOI
Muhammad Hussain, Ioanna Iacovides, Tom Lawton

и другие.

Designing Interactive Systems Conference, Год журнала: 2024, Номер unknown, С. 1607 - 1619

Опубликована: Июнь 29, 2024

In the standard interaction model of clinical decision support systems, system makes a recommendation, and clinician decides whether to act on it.However, this can compromise patient-centeredness care level involvement.There is scope develop alternative models, but we need methods for exploring comparing these assess how they may impact decision-making.Through collaborating with clinical, AI safety, HCI experts, patient representatives, co-designed number human-AI models decision-making.We then translated into 'Wizard Oz' prototypes, where created scenarios designed user interfaces different types output.In paper, present illustrate used co-design approach translate them functional prototypes that be tested users explore potential impacts decision-making.

Язык: Английский

Процитировано

1
Adaptive questionnaires for facilitating patient data entry in clinical decision support systems: methods and application to STOPP/START v2 DOI Creative Commons
Jean-Baptiste Lamy,

Mouazer Abdelmalek,

Léguillon Romain

и другие.

BMC Medical Informatics and Decision Making, Год журнала: 2024, Номер 24(1)

Опубликована: Ноя. 5, 2024

Abstract Clinical decision support systems are software tools that help clinicians to make medical decisions. However, their acceptance by is usually rather low. A known problem they often require manually enter a lot of patient data, which long and tedious. Existing solutions, such as the automatic data extraction from electronic health record, not fully satisfying, because low quality availability. In practice, many still include questionnaire for entry. this paper, we propose an original solution simplify entry, using adaptive questionnaire, i.e. evolves during user interaction, showing or hiding questions dynamically. Considering rule-based systems, designed methods determining relationships between rules translating system’s clinical into display determine items show in optimal order priority among questionnaire. We applied approach system implementing STOPP/START v2, guideline managing polypharmacy. it permits reducing about two thirds number conditions displayed both on cases real data. Presented focus group sessions, was found “pretty easy use”. future, could be other guidelines, adapted entry patients.

Язык: Английский

Процитировано

1