Impact of the Goal‐directed Medication Review Electronic Decision Support System on Drug Burden Index: A cluster‐randomised clinical trial in primary care

2020 ◽  
Author(s):  
Lisa Kouladjian O'Donnell ◽  
Danijela Gnjidic ◽  
Mouna Sawan ◽  
Emily Reeve ◽  
Patrick J. Kelly ◽  
...  
Keyword(s):  
Primary Care ◽  
Clinical Trial ◽  
Decision Support ◽  
Support System ◽  
Medication Review ◽  
Randomised Clinical Trial ◽  
Electronic Decision Support ◽  
Drug Burden Index ◽  
Cluster Randomised ◽  
Electronic Decision Support System

scholarly journals Correction to: Implementation of the goal-directed medication review electronic decision support system (G-MEDSS)© into home medicines review: a protocol for a clusterrandomised clinical trial in older adults

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Lisa Kouladjian O’Donnell ◽  
Mouna Sawan ◽  
Emily Reeve ◽  
Danijela Gnjidic ◽  
Timothy F. Chen ◽  
...  
Keyword(s):  
Older Adults ◽  
Clinical Trial ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Medication Review ◽  
Electronic Decision Support ◽  
Electronic Decision Support System ◽  
Home Medicines Review

An amendment to this paper has been published and can be accessed via the original article.

scholarly journals Implementation of the Goal-directed Medication review Electronic Decision Support System (G-MEDSS)© into home medicines review: a protocol for a cluster-randomised clinical trial in older adults

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Lisa Kouladjian O’Donnell ◽  
Mouna Sawan ◽  
Emily Reeve ◽  
Danijela Gnjidic ◽  
Timothy F. Chen ◽  
...  
Keyword(s):  
Older Adults ◽  
Decision Support ◽  
Decision Support System ◽  
Clinical Outcomes ◽  
Support System ◽  
Medication Review ◽  
Clinical Decision ◽  
Randomised Clinical Trial ◽  
Patient Specific ◽  
Electronic Decision Support System

Abstract Background Older people living in the community have a high prevalence of polypharmacy and are vulnerable to adverse drug events. Home Medicines Review (HMR) is a collaborative medication review service involving general practitioners (GPs), accredited clinical pharmacists (ACPs) and patients, which aims to prevent medication-related problems. This study aims to evaluate the implementation of a Computerised Clinical Decision Support System (CCDSS) called G-MEDSS© (Goal-directed Medication Review Electronic Decision Support System) in HMRs to deprescribe anticholinergic and sedative medications, and to assess the effect of deprescribing on clinical outcomes. Methods This study consists of 2 stages: Stage I – a two-arm parallel-group cluster-randomised clinical trial, and Stage II – process evaluation of the CCDSS intervention in HMR. Community-dwelling older adults living with and without dementia who are referred for HMR by their GP and recruited by ACPs will be included in this study. G-MEDSS is a CCDSS designed to provide clinical decision support for healthcare practitioners when completing a medication review, to tailor care to meet the patients’ goals and preferences. The G-MEDSS contains three tools: The Goals of Care Management Tool, The Drug Burden Index (DBI) Calculator©, and The revised Patients’ Attitudes Towards Deprescribing (rPATD) questionnaire. The G-MEDSS produces patient-specific deprescribing reports, to be included as part of the ACPs communication with the patient’s GP, and patient-specific reports for the patient (or carer). ACPs randomised to the intervention arm of the study will use G-MEDSS to create deprescribing reports for the referring GP and for their patient (or carer) when submitting the HMR report. ACPs in the comparison arm will provide the usual care HMR service (without the G-MEDSS). Outcomes The primary outcome is reduction in DBI exposure 3 months after HMR ± G-MEDSS intervention between comparison and intervention groups. The secondary outcomes include changes in clinical outcomes (physical and cognitive function, falls, institutionalisation, GP visits, medication adherence and mortality) 3-months after HMR. Discussion This study is expected to add to the evidence that the combination of CCDSS supporting medication review can improve prescribing and clinical outcomes in older adults. Trial registration The trial was registered on the Australian New Zealand Clinical Trials Registry ACTRN12617000895381 on 19th June 2017.

Implementation of the goal-directed medication review electronic decision support system (G-MEDSS)

2018 ◽  
Vol 14 (8) ◽  
pp. e42-e43 ◽  
Author(s):  
Mouna Sawan ◽  
Lisa Kouladjian O’Donnell ◽  
Emily Reeve ◽  
Danijela Gnjidic ◽  
Timothy Chen ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Medication Review ◽  
Electronic Decision Support ◽  
Electronic Decision Support System

scholarly journals Evaluation of a multicomponent programme for the management of musculoskeletal pain and depression in primary care: a cluster-randomised clinical trial (the DROP study)

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Enric Aragonès ◽  
Germán López-Cortacans ◽  
Antonia Caballero ◽  
Josep Ll. Piñol ◽  
Elisabet Sánchez-Rodríguez ◽  
...  
Keyword(s):  
Primary Care ◽  
Clinical Trial ◽  
Musculoskeletal Pain ◽  
Randomised Clinical Trial ◽  
Cluster Randomised

An Electronic Decision Support System to Motivate People With Severe Mental Illnesses to Quit Smoking

2011 ◽  
Vol 62 (4) ◽  
pp. 360-366 ◽  
Author(s):  
Mary F. Brunette ◽  
Joelle C. Ferron ◽  
Gregory J. McHugo ◽  
Kristin E. Davis ◽  
Timothy S. Devitt ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Mental Illnesses ◽  
Electronic Decision Support ◽  
Quit Smoking ◽  
Electronic Decision Support System

scholarly journals Self-Selection of Bathroom-Assistive Technology: Development of an Electronic Decision Support System (Hygiene 2.0) (Preprint)

2019 ◽  
Author(s):  
Manon Guay ◽  
Karine Latulippe ◽  
Claudine Auger ◽  
Dominique Giroux ◽  
Noémie Séguin-Tremblay ◽  
...  
Keyword(s):  
Older Adults ◽  
Decision Support ◽  
Decision Support System ◽  
Assistive Technology ◽  
Support System ◽  
Community Dwelling ◽  
User Centered Design ◽  
Electronic Decision Support ◽  
Electronic Decision Support System ◽  
Community Dwelling Older Adults

BACKGROUND A clinical algorithm (Algo) in paper form is used in Quebec, Canada, to allow health care workers other than occupational therapists (OTs) to make bathroom adaptation recommendations for older adults. An integrated knowledge transfer process around Algo suggested an electronic version of this decision support system (electronic decision support system [e-DSS]) to be used by older adults and their caregivers in search of information and solutions for their autonomy and safety in the bathroom. OBJECTIVE This study aims to (1) create an e-DSS for the self-selection of bathroom-assistive technology by community-dwelling older adults and their caregivers and (2) assess usability with lay users and experts to improve the design accordingly. METHODS On the basis of a user-centered design approach, the process started with content identification for the prototype through 7 semistructured interviews with key informants of various backgrounds (health care providers, assistive technology providers, and community services) and 4 focus groups (2 with older adults and 2 with caregivers). A thematic content transcript analysis was carried out and used during the creation of the prototype. The prototype was refined iteratively using think-aloud and observation methods with a clinical expert (n=1), researchers (n=3), OTs (n=3), older adults (n=3), and caregivers (n=3), who provided information on the usability of the e-DSS. RESULTS Overall, 4 themes served as the criteria for the prototype of the electronic Algo (Hygiene 2.0 [H<sub>2</sub>.0]): focus (safety, confidentiality, well-being, and autonomy), engage, facilitate (simplify, clarify, and illustrate), and access. For example, users first pay attention to the images (engage and illustrate) that can be used to depict safe postures (safety), illustrate questions embedded in the decision support tool (clarify and illustrate), and demonstrate the context of the use of assistive technology (safety and clarify). CONCLUSIONS The user-centered design of H<sub>2</sub>.0 allowed the cocreation of an e-DSS in the form of a website, in line with the needs of community-dwelling older adults and their caregivers seeking bathroom-assistive technology that enables personal hygiene. Each iteration improved usability and brought more insight into the users’ realities, tailoring the e-DSS to the implementation context.

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