{"id":{"repo_id":"bradford","oai_identifier":"oai:bradscholars.brad.ac.uk:10454/19818"},"canonical_url":"https://search.dev.ndltd.org/etd/bradford/oai:bradscholars.brad.ac.uk:10454/19818","repository":{"repo_id":"bradford","name":"University of Bradford","base_url":"https://bradscholars.brad.ac.uk/oai/request"},"display":{"title":"Towards the development of an integrated case-finding tool to facilitate the review of anticholinergic prescribing for frail older people","abstract":"Background: The cumulative effect of taking anticholinergic medicines (anticholinergic burden) is associated with adverse outcomes for older people. Prevalence of anticholinergic prescribing is increasing, and there is a need for tools to proactively identify at-risk patients for medication reviews. Aim: To explore the need for, and feasibility of, an integrated case-finding tool that predicts risks using electronic health records (EHRs), facilitating the review of anticholinergic medicines for frail older people. Methods: Mixed methods, adopting a pragmatic approach. A systematic review, prediction modelling of cohort study data, and qualitative interviews were undertaken. Results: The systematic review found anticholinergic exposure was associated with adverse outcomes for the frail; poorer physical function, falls, and mortality, indicating a need for a risk reducing intervention. In the prediction modelling study, predicting risks using composite measures of anticholinergic burden and frailty indicated limited feasibility. Neither enhanced the performance of best subset models using cohort study data. Their predictive utility needs to be investigated using EHR data, to determine their feasibility within primary care. The qualitative study found healthcare professionals needed a proactive tool, supporting risk prediction as a feasible approach. Factors influencing future implementation were; upskilling requirements, deprescribing confidence, patient reluctance, motivation, holistic care, interoperability, trust in risk prediction, remuneration, among other barriers and facilitators. Conclusions: Through identifying a need, and potential feasibility, foundations towards the future developments of a case-finding tool have been provided, informing an early tool prototype (AC-FRAIL). Recommendations for further work suggest a roadmap ahead, to maximise the potential for integrated solutions to proactively reduce anticholinergic risks.","abstract_html":"Background: The cumulative effect of taking anticholinergic medicines (anticholinergic burden) is associated with adverse outcomes for older people. Prevalence of anticholinergic prescribing is increasing, and there is a need for tools to proactively identify at-risk patients for medication reviews. Aim: To explore the need for, and feasibility of, an integrated case-finding tool that predicts risks using electronic health records (EHRs), facilitating the review of anticholinergic medicines for frail older people. Methods: Mixed methods, adopting a pragmatic approach. A systematic review, prediction modelling of cohort study data, and qualitative interviews were undertaken. Results: The systematic review found anticholinergic exposure was associated with adverse outcomes for the frail; poorer physical function, falls, and mortality, indicating a need for a risk reducing intervention. In the prediction modelling study, predicting risks using composite measures of anticholinergic burden and frailty indicated limited feasibility. Neither enhanced the performance of best subset models using cohort study data. Their predictive utility needs to be investigated using EHR data, to determine their feasibility within primary care. The qualitative study found healthcare professionals needed a proactive tool, supporting risk prediction as a feasible approach. Factors influencing future implementation were; upskilling requirements, deprescribing confidence, patient reluctance, motivation, holistic care, interoperability, trust in risk prediction, remuneration, among other barriers and facilitators. Conclusions: Through identifying a need, and potential feasibility, foundations towards the future developments of a case-finding tool have been provided, informing an early tool prototype (AC-FRAIL). Recommendations for further work suggest a roadmap ahead, to maximise the potential for integrated solutions to proactively reduce anticholinergic risks.","abstract_has_math":false,"creators":["Mehdizadeh, David"],"institution":"University of Bradford","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Petty, Duncan R.","Faisal, Muhammad","Johnson, O.A.","Gardner, Peter"],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022","date_published":"2022","updated_at":"2026-07-24T01:15:46Z","subjects":["Anticholinergic burden","Fraility","Deprescribing","Medication review","Risk stratification","Case finding","Anticholinergic prescribing"],"languages":["en"],"rights":["\"Creative
The University of Bradford theses are licenced under a Creative Commons Licence."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10454/19818","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Petty, Duncan R.","Faisal, Muhammad","Johnson, O.A.","Gardner, Peter"]},{"key":"dc:creator","label":"Author","values":["Mehdizadeh, David"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2024-02-27T12:15:01Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2024-02-27T12:15:01Z"]},{"key":"dc:date.issued","label":"Date","values":["2022"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["School of Pharmacy and Medical Sciences. Faculty of Life Sciences"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Bradford"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["PhD"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Anticholinergic burden","Fraility","Deprescribing","Medication review","Risk stratification","Case finding","Anticholinergic prescribing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["\"Creative
The University of Bradford theses are licenced under a Creative Commons Licence."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10454/19818"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Background: The cumulative effect of taking anticholinergic medicines (anticholinergic burden) is associated with adverse outcomes for older people. Prevalence of anticholinergic prescribing is increasing, and there is a need for tools to proactively identify at-risk patients for medication reviews. Aim: To explore the need for, and feasibility of, an integrated case-finding tool that predicts risks using electronic health records (EHRs), facilitating the review of anticholinergic medicines for frail older people. Methods: Mixed methods, adopting a pragmatic approach. A systematic review, prediction modelling of cohort study data, and qualitative interviews were undertaken. Results: The systematic review found anticholinergic exposure was associated with adverse outcomes for the frail; poorer physical function, falls, and mortality, indicating a need for a risk reducing intervention. In the prediction modelling study, predicting risks using composite measures of anticholinergic burden and frailty indicated limited feasibility. Neither enhanced the performance of best subset models using cohort study data. Their predictive utility needs to be investigated using EHR data, to determine their feasibility within primary care. The qualitative study found healthcare professionals needed a proactive tool, supporting risk prediction as a feasible approach. Factors influencing future implementation were; upskilling requirements, deprescribing confidence, patient reluctance, motivation, holistic care, interoperability, trust in risk prediction, remuneration, among other barriers and facilitators. Conclusions: Through identifying a need, and potential feasibility, foundations towards the future developments of a case-finding tool have been provided, informing an early tool prototype (AC-FRAIL). Recommendations for further work suggest a roadmap ahead, to maximise the potential for integrated solutions to proactively reduce anticholinergic risks."]},{"key":"dc:title","label":"Title","values":["Towards the development of an integrated case-finding tool to facilitate the review of anticholinergic prescribing for frail older people"]}]}],"canonical_facts":{"dc:contributor.advisor":["Petty, Duncan R.","Faisal, Muhammad","Johnson, O.A.","Gardner, Peter"],"dc:creator":["Mehdizadeh, David"],"dc:date.accessioned":["2024-02-27T12:15:01Z"],"dc:date.available":["2024-02-27T12:15:01Z"],"dc:date.issued":["2022"],"dc:description.abstract":["Background: The cumulative effect of taking anticholinergic medicines (anticholinergic burden) is associated with adverse outcomes for older people. Prevalence of anticholinergic prescribing is increasing, and there is a need for tools to proactively identify at-risk patients for medication reviews. Aim: To explore the need for, and feasibility of, an integrated case-finding tool that predicts risks using electronic health records (EHRs), facilitating the review of anticholinergic medicines for frail older people. Methods: Mixed methods, adopting a pragmatic approach. A systematic review, prediction modelling of cohort study data, and qualitative interviews were undertaken. Results: The systematic review found anticholinergic exposure was associated with adverse outcomes for the frail; poorer physical function, falls, and mortality, indicating a need for a risk reducing intervention. In the prediction modelling study, predicting risks using composite measures of anticholinergic burden and frailty indicated limited feasibility. Neither enhanced the performance of best subset models using cohort study data. Their predictive utility needs to be investigated using EHR data, to determine their feasibility within primary care. The qualitative study found healthcare professionals needed a proactive tool, supporting risk prediction as a feasible approach. Factors influencing future implementation were; upskilling requirements, deprescribing confidence, patient reluctance, motivation, holistic care, interoperability, trust in risk prediction, remuneration, among other barriers and facilitators. Conclusions: Through identifying a need, and potential feasibility, foundations towards the future developments of a case-finding tool have been provided, informing an early tool prototype (AC-FRAIL). Recommendations for further work suggest a roadmap ahead, to maximise the potential for integrated solutions to proactively reduce anticholinergic risks."],"dc:identifier.uri":["http://hdl.handle.net/10454/19818"],"dc:language.iso":["en"],"dc:publisher.department":["School of Pharmacy and Medical Sciences. Faculty of Life Sciences"],"dc:publisher.institution":["University of Bradford"],"dc:rights":["\"Creative
The University of Bradford theses are licenced under a Creative Commons Licence."],"dc:subject":["Anticholinergic burden","Fraility","Deprescribing","Medication review","Risk stratification","Case finding","Anticholinergic prescribing"],"dc:title":["Towards the development of an integrated case-finding tool to facilitate the review of anticholinergic prescribing for frail older people"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["PhD"]},"updated_at":"2026-07-24T01:15:46Z"}