Publications by authors named "Jacqueline K Kueper"

4 Publications

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Primary Care Informatics Response to Covid-19 Pandemic: Adaptation, Progress, and Lessons from Four Countries with High ICT Development.

Yearb Med Inform 2021 Apr 21. Epub 2021 Apr 21.

Nuffield Department of Primary Care Health Sciences, University of Oxford, UK.

Objective: Internationally, primary care practice had to transform in response to the COVID pandemic. Informatics issues included access, privacy, and security, as well as patient concerns of equity, safety, quality, and trust. This paper describes progress and lessons learned.

Methods: IMIA Primary Care Informatics Working Group members from Australia, Canada, United Kingdom and United States developed a standardised template for collection of information. The template guided a rapid literature review. We also included experiential learning from primary care and public health perspectives.

Results: All countries responded rapidly. Common themes included rapid reductions then transformation to virtual visits, pausing of non-COVID related informatics projects, all against a background of non-standardized digital development and disparate territory or state regulations and guidance. Common barriers in these four and in less-resourced countries included disparities in internet access and availability including bandwidth limitations when internet access was available, initial lack of coding standards, and fears of primary care clinicians that patients were delaying care despite the availability of televisits.

Conclusions: Primary care clinicians were able to respond to the COVID crisis through telehealth and electronic record enabled change. However, the lack of coordinated national strategies and regulation, assurance of financial viability, and working in silos remained limitations. The potential for primary care informatics to transform current practice was highlighted. More research is needed to confirm preliminary observations and trends noted.
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April 2021

Cognition and motor function: The gait and cognition pooled index.

PLoS One 2020 11;15(9):e0238690. Epub 2020 Sep 11.

Department of Epidemiology & Biostatistics, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada.

Background: There is a need for outcome measures with improved responsiveness to changes in pre-dementia populations. Both cognitive and motor function play important roles in neurodegeneration; motor function decline is detectable at early stages of cognitive decline. This proof of principle study used a Pooled Index approach to evaluate improved responsiveness of the predominant outcome measure (ADAS-Cog: Alzheimer's Disease Assessment Scale-Cognitive Subscale) when assessment of motor function is added.

Methods: Candidate Pooled Index variables were selected based on theoretical importance and pairwise correlation coefficients. Kruskal-Wallis and Mann-Whitney U tests assessed baseline discrimination. Standardized response means assessed responsiveness to longitudinal change.

Results: Final selected variables for the Pooled Index include gait velocity, dual-task cost of gait velocity, and an ADAS-Cog-Proxy (statistical approximation of the ADAS-Cog using similar cognitive tests). The Pooled Index and ADAS-Cog-Proxy scores had similar ability to discriminate between pre-dementia syndromes. The Pooled Index demonstrated trends of similar or greater responsiveness to longitudinal decline than ADAS-Cog-Proxy scores.

Conclusion: Adding motor function assessments to the ADAS-Cog may improve responsiveness in pre-dementia populations.
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October 2020

Artificial Intelligence and Primary Care Research: A Scoping Review.

Ann Fam Med 2020 05;18(3):250-258

Departments of Epidemiology & Biostatistics, Computer Science, Schulich Interfaculty Program in Public Health, Statistical & Actuarial Sciences, Western University, London, Ontario, Canada.

Purpose: Rapid increases in technology and data motivate the application of artificial intelligence (AI) to primary care, but no comprehensive review exists to guide these efforts. Our objective was to assess the nature and extent of the body of research on AI for primary care.

Methods: We performed a scoping review, searching 11 published or gray literature databases with terms pertaining to AI (eg, machine learning, bayes* network) and primary care (eg, general pract*, nurse). We performed title and abstract and then full-text screening using Covidence. Studies had to involve research, include both AI and primary care, and be published in Eng-lish. We extracted data and summarized studies by 7 attributes: purpose(s); author appointment(s); primary care function(s); intended end user(s); health condition(s); geographic location of data source; and AI subfield(s).

Results: Of 5,515 unique documents, 405 met eligibility criteria. The body of research focused on developing or modifying AI methods (66.7%) to support physician diagnostic or treatment recommendations (36.5% and 13.8%), for chronic conditions, using data from higher-income countries. Few studies (14.1%) had even a single author with a primary care appointment. The predominant AI subfields were supervised machine learning (40.0%) and expert systems (22.2%).

Conclusions: Research on AI for primary care is at an early stage of maturity. For the field to progress, more interdisciplinary research teams with end-user engagement and evaluation studies are needed.
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May 2020

The Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog): Modifications and Responsiveness in Pre-Dementia Populations. A Narrative Review.

J Alzheimers Dis 2018 ;63(2):423-444

Department of Epidemiology and Biostatistics, The University of Western Ontario, London, ON, Canada.

The Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) was developed in the 1980s to assess the level of cognitive dysfunction in Alzheimer's disease. Advancements in the research field have shifted focus toward pre-dementia populations, and use of the ADAS-Cog has extended into these pre-dementia studies despite concerns about its ability to detect important changes at these milder stages of disease progression. If the ADAS-Cog cannot detect important changes, our understanding of pre-dementia disease progression may be compromised and trials may incorrectly conclude that a novel treatment approach is not beneficial. The purpose of this review was to assess the performance of the ADAS-Cog in pre-dementia populations, and to review all modifications that have been made to the ADAS-Cog to improve its measurement performance in dementia or pre-dementia populations. The contents of this review are based on bibliographic searches of electronic databases to locate all studies using the ADAS-Cog in pre-dementia samples or subsamples, and to locate all modified versions. Citations from relevant articles were also consulted. Overall, our results suggest the original ADAS-Cog is not an optimal outcome measure for pre-dementia studies; however, given the prominence of the ADAS-Cog, care must be taken when considering the use of alternative outcome measures. Thirty-one modified versions of the ADAS-Cog were found. Modification approaches that appear most beneficial include altering scoring methodology or adding tests of memory, executive function, and/or daily functioning. Although modifications improve the performance of the ADAS-Cog, this is at the cost of introducing heterogeneity that may limit between-study comparison.
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June 2019