How Patient Work Changes Over Time for People With Multimorbid Type 2 Diabetes: Qualitative Study

Yin, Kathleen; Jung, Joshua; Coiera, Enrico; Ho, Kenneth; Vagholkar, Sanjyot; Blandford, Ann; Rapport, Frances; Lau, Annie

doi:10.2196/25992

Cited by 5 publications

(6 citation statements)

References 33 publications

(38 reference statements)

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“…Fifteen participants were invited from a previous study of 26 consumers investigating patient work in community-dwelling individuals with Type 2 diabetes mellitus and chronic comorbidities. 14 , 15 Participants were interviewed during the first COVID-19 lockdown period in Sydney, Australia, May–June 2020. Of the 11 participants not interviewed, 5 were unwilling, 4 could not be contacted, 1 was hospitalized, and 1 had died.…”

Section: Methodsmentioning

confidence: 99%

Consumer workarounds during the COVID-19 pandemic: analysis and technology implications using the SAMR framework

Yin

Coiera

Jung

et al. 2022

Journal of the American Medical Informatics Association

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Objective To understand the nature of health consumer self-management workarounds during the COVID-19 pandemic, to classify these workarounds using the Substitution, Augmentation, Modification, and Redefinition (SAMR) framework, and to see how digital tools had assisted these workarounds. Materials and Methods We assessed 15 self-managing elderly patients with Type 2 diabetes, multiple chronic co-morbidities, and low digital literacy. Interviews were conducted during COVID-19 lockdowns in May-June 2020 and participants were asked about how their self-management had differed from before. Each instance of change in self-management were identified as consumer workarounds and were classified using the SAMR framework to assess the extent of change. We also identified instances where digital technology assisted with workarounds. Results Consumer workarounds in all SAMR levels were observed. Substitution, describing change in work quality or how basic information was communicated, was easy to make and involved digital tools that replaced face-to-face communications, such as the telephone. Augmentation, describing changes in task mechanisms that enhanced functional value, did not include any digital tools. Modification, which significantly altered task content and context, involved more complicated changes such as making video calls. Redefinition workarounds created tasks not previously required, such as using Google Home to remotely babysit grandchildren, had transformed daily routines. Discussion and Conclusion Health consumer workarounds need further investigation as health consumers also use workarounds to bypass barriers during self-management. The SAMR framework had classified the health consumer workarounds during COVID, but the framework needs further refinement to include more aspects of workarounds.

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Section: Methodsmentioning

confidence: 99%

Consumer workarounds during the COVID-19 pandemic: analysis and technology implications using the SAMR framework

Yin

Coiera

Jung

et al. 2022

Journal of the American Medical Informatics Association

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“…This publication uses the data set collected from Yin et al ( 17 ), which was previously published ( 16 ). Detailed data collection methodology and ethics permissions are provided elsewhere ( 17 ).…”

Section: Methodsmentioning

confidence: 99%

“…All quantitative and qualitative data sources mentioned in previous publications (camera screenshots, interview transcripts, Time-Use Diary, researchers' field notes, photos of the participant's dwelling, etc.) were used to develop these case profiles ( 16 , 17 ). We utilized a within-case studies approach ( 21 ), identifying the unique attributes and contextual experiences of each case profile before identifying general patterns across participants.…”

Section: Methodsmentioning

confidence: 99%

“…In this paper, we improve the persona design process by proposing a data-driven approach to developing and validating personas, focusing on the “patient work” of T2DM patients living in the community ( 16 , 17 ). “Patient work” collectively refers to the large variety of tasks that people must conduct during self-management of health conditions, and the comprehensive contextual factors that alter how these tasks are performed ( 18 , 19 ).…”

Section: Introductionmentioning

confidence: 99%

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Patient Work Personas of Type 2 Diabetes—A Data-Driven Approach to Persona Development and Validation

Galliford

Yin²,

Blandford³

et al. 2022

Front. Digit. Health

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IntroductionMany have argued that a “one-size-fits-all” approach to designing digital health is not optimal and that personalisation is essential to achieve targeted outcomes. Yet, most digital health practitioners struggle to identify which design aspect require personalisation. Personas are commonly used to communicate patient needs in consumer-oriented digital health design, however there is often a lack of reproducible clarity on development process and few attempts to assess their accuracy against the targeted population. In this study, we present a transparent approach to designing and validating personas, as well as identifying aspects of “patient work,” defined as the combined total of work tasks required to manage one's health and the contextual factors influencing such tasks, that are sensitive to an individual's context and may require personalisation.MethodsA data-driven approach was used to develop and validate personas for people with Type 2 diabetes mellitus (T2DM), focusing on patient work. Eight different personas of T2DM patient work were constructed based physical activity, dietary control and contextual influences of 26 elderly Australian participants (median age = 72 years) via wearable camera footage, interviews, and self-reported diaries. These personas were validated for accuracy and perceived usefulness for design, both by the original participants and a younger (median age bracket = 45–54 years) independent online cohort f 131 T2DM patients from the United Kingdom and the United States.ResultsBoth the original participants and the independent online cohort reported the personas to be accurate representations of their patient work routines. For the independent online cohort, 74% (97/131) indicated personas stratified to their levels of exercise and diet control were similar to their patient work routines. Findings from both cohorts highlight aspects that may require personalisation include daily routine, use of time, and social context.ConclusionPersonas made for a specific purpose can be very accurate if developed from real-life data. Our personas retained their accuracy even when tested against an independent cohort, demonstrating their generalisability. Our data-driven approach clarified the often non-transparent process of persona development and validation, suggesting it is possible to systematically identify whether persona components are accurate or. and which aspects require more personalisation and tailoring.

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“…However, it is the leap in performance brought about by the combination of rising computational capacity and neural network technology that accounts for this most recent surge in interest from various health care stakeholders [ 5 ]. Despite interest and investment from academia, industry, and policy makers, a notable paucity of real-world applications of AI-enabled CCDSTs persists [ 6 ]. This is a mark of a translational gap known as the “AI chasm” [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Stakeholder Perspectives on Clinical Decision Support Tools to Inform Clinical Artificial Intelligence Implementation: Protocol for a Framework Synthesis for Qualitative Evidence

Al-Zubaidy¹,

Hogg²,

Maniatopoulos³

et al. 2022

JMIR Res Protoc

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Background Quantitative systematic reviews have identified clinical artificial intelligence (AI)-enabled tools with adequate performance for real-world implementation. To our knowledge, no published report or protocol synthesizes the full breadth of stakeholder perspectives. The absence of such a rigorous foundation perpetuates the “AI chasm,” which continues to delay patient benefit. Objective The aim of this research is to synthesize stakeholder perspectives of computerized clinical decision support tools in any health care setting. Synthesized findings will inform future research and the implementation of AI into health care services. Methods The search strategy will use MEDLINE (Ovid), Scopus, CINAHL (EBSCO), ACM Digital Library, and Science Citation Index (Web of Science). Following deduplication, title, abstract, and full text screening will be performed by 2 independent reviewers with a third topic expert arbitrating. The quality of included studies will be appraised to support interpretation. Best-fit framework synthesis will be performed, with line-by-line coding completed by 2 independent reviewers. Where appropriate, these findings will be assigned to 1 of 22 a priori themes defined by the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability framework. New domains will be inductively generated for outlying findings. The placement of findings within themes will be reviewed iteratively by a study advisory group including patient and lay representatives. Results Study registration was obtained from PROSPERO (CRD42021256005) in May 2021. Final searches were executed in April, and screening is ongoing at the time of writing. Full text data analysis is due to be completed in October 2021. We anticipate that the study will be submitted for open-access publication in late 2021. Conclusions This paper describes the protocol for a qualitative evidence synthesis aiming to define barriers and facilitators to the implementation of computerized clinical decision support tools from all relevant stakeholders. The results of this study are intended to expedite the delivery of patient benefit from AI-enabled clinical tools. Trial Registration PROSPERO CRD42021256005; https://tinyurl.com/r4x3thvp International Registered Report Identifier (IRRID) DERR1-10.2196/33145

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How Patient Work Changes Over Time for People With Multimorbid Type 2 Diabetes: Qualitative Study

Cited by 5 publications

References 33 publications

Consumer workarounds during the COVID-19 pandemic: analysis and technology implications using the SAMR framework

Consumer workarounds during the COVID-19 pandemic: analysis and technology implications using the SAMR framework

Patient Work Personas of Type 2 Diabetes—A Data-Driven Approach to Persona Development and Validation

Stakeholder Perspectives on Clinical Decision Support Tools to Inform Clinical Artificial Intelligence Implementation: Protocol for a Framework Synthesis for Qualitative Evidence

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