The diffusion of innovative diabetes technologies as a fundamental cause of social inequalities in health. The Nord‐Trøndelag Health Study, Norway

Weiss, Daniel; Sund, Erik R.; Freese, Jeremy; Krokstad, Steinar

doi:10.1111/1467-9566.13147

Cited by 18 publications

(15 citation statements)

References 44 publications

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“…The remaining (17/41, 41%) studies discussed the related health outcomes caused by the lack of or limited access to digital health technologies [ 1 , 18 , 36 , 37 , 40 , 42 , 43 , 45 , 48 , 49 , 54 - 56 , 58 , 60 , 65 , 67 ]. Researchers have reported different health outcomes following the introduction of digital health technology interventions, including disease incidence rates and mortality, with particular attention paid to chronic diseases and Black groups [ 49 , 56 , 58 , 60 ].…”

Section: Resultsmentioning

confidence: 99%

Inequities in Health Care Services Caused by the Adoption of Digital Health Technologies: Scoping Review

Yao¹,

Wen-li²,

Evans³

et al. 2022

J Med Internet Res

166

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Background Digital health technologies (ie, the integration of digital technology and health information) aim to increase the efficiency of health care delivery; they are rapidly adapting to health care contexts to provide improved medical services for citizens. However, contrary to expectations, their rapid adoption appears to have led to health inequities, with differences in health conditions or inequality in the distribution of health care resources among different populations. Objective This scoping review aims to identify and describe the inequities of health care services brought about by the adoption of digital health technologies. The factors influencing such inequities, as well as the corresponding countermeasures to ensure health equity among different groups of citizens, were also studied. Methods Primary studies and literature, including articles and reviews, published in English between 1990 and 2020 were retrieved using appropriate search strategies across the following three electronic databases: Clarivate Analytics’ Web of Science, PubMed, and Scopus. Data management was performed by two authors (RY and WZ) using Thomson Endnote (Clarivate Analytics, Inc), by systematically screening and identifying eligible articles for this study. Any conflicts of opinion were resolved through discussions with the corresponding author. A qualitative descriptive synthesis was performed to determine the outcomes of this scoping review. Results A total of 2325 studies were collected during the search process, of which 41 (1.76%) papers were identified for further analysis. The quantity of literature increased until 2016, with a peak in 2020. The United States, the United Kingdom, and Norway ranked among the top 3 countries for publication output. Health inequities caused by the adoption of digital health technologies in health care services can be reflected in the following two dimensions: the inability of citizens to obtain and adopt technology and the different disease outcomes found among citizens under technical intervention measures. The factors that influenced inequities included age, race, region, economy, and education level, together with health conditions and eHealth literacy. Finally, action can be taken to alleviate inequities in the future by government agencies and medical institutions (eg, establishing national health insurance), digital health technology providers (eg, designing high-quality tools), and health care service recipients (eg, developing skills to access digital technologies). Conclusions The application of digital health technologies in health care services has caused inequities to some extent. However, existing research has certain limitations. The findings provide a comprehensive starting point for future research, allowing for further investigation into how digital health technologies may influence the unequal distribution of health care services. The interaction between individual subjective factors as well as social support and influencing factors should be included in future studies. Specifically, access to and availability of digital health technologies for socially disadvantaged groups should be of paramount importance.

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Section: Resultsmentioning

confidence: 99%

Inequities in Health Care Services Caused by the Adoption of Digital Health Technologies: Scoping Review

Yao¹,

Wen-li²,

Evans³

et al. 2022

J Med Internet Res

166

View full text Add to dashboard Cite

show abstract

“…9 Furthermore, earlier adoption of technology has been associated with higher socioeconomic status. 29 The participants in this study already had well-controlled diabetes relative to the general clinic population (registry data indicating average HbA1c in children being 8.1%-9.3%). 9 In addition, the majority of participants were already using insulin pumps and CGMs before starting Control-IQ, so it is unknown if the levels of adherence to the system and glycemic outcomes would be achievable to individuals less familiar with diabetes technology.…”

Section: Messer Et Almentioning

confidence: 94%

Real-World Use of a New Hybrid Closed Loop Improves Glycemic Control in Youth with Type 1 Diabetes

Messer

Berget

Pyle

et al. 2021

Diabetes Technology & Therapeutics

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Objective: To describe real-world outcomes for youth using the Tandem t:slim X2 insulin pump with Control-IQ technology (''Control-IQ'') for 6 months at a large pediatric clinic. Methods: Youth with type 1 diabetes, who started Control-IQ for routine care, were prospectively followed. Data on system use and glycemic control were collected before Control-IQ start, and at 1, 3, and 6 months after start. Mixed models assessed change across time; interactions with baseline hemoglobin A1c (HbA1c) and age were tested. Results: In 191 youth (median age 14, 47% female, and median HbA1c 7.6%), percent time with glucose levels 70-180 mg/dL (time-in-range [TIR]) improved from 57% at baseline to 66% at 6 months (P < 0.001). The proportion of participants reaching TIR target (>70%) doubled from 23.5% at baseline to 47.8% at 3 months, sustaining at 46.7% at 6 months (P < 0.001). Glucose management indicator (approximation of HbA1c) improved from 7.5% at baseline to 7.1% at 3 months and 7.2% at 6 months (P < 0.001). Those with higher baseline HbA1c experienced the most substantial improvements in glycemic control. Percent time using the Control-IQ feature was 86.4% at 6 months, and <4% of cohort discontinued use. Conclusion:The Control-IQ system clinically and significantly improved glycemic control in a large sample of youth. System use was high at 6 months, with only a small proportion discontinuing use, indicating potential for sustaining results long term.

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“…Thus, the relationship between the diffusion of an innovation and social inequality is first positive, then negative. Empirical research suggests that the social gradients in use and access are steeper for medical technologies in an early stage of diffusion, and that this pattern also is manifested as inequality in health outcomes (Glied & Lleras-Muney, 2008;Wang et al, 2012;Weiss et al, 2020;Zapata-Moya et al, 2019).…”

mentioning

confidence: 99%

The radically unequal distribution of Covid-19 vaccinations: a predictable yet avoidable symptom of the fundamental causes of inequality

Rydland

Friedman

Stringhini

et al. 2022

Humanit Soc Sci Commun

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The Covid-19 pandemic-and its social and economic fallout-has thrust social and health-related inequalities into the spotlight. The pandemic, and our response to it, has induced new inequalities both within and between nations. However, now that highly efficacious vaccines are available, one might reasonably presume that we have in our hands the tools to address pandemicassociated inequalities. Nevertheless, two prominent social science theories, fundamental cause theory and diffusion of innovation theory suggest otherwise. Together, these theories predict that better resourced individuals and countries will jockey to harness the greatest vaccine benefit for themselves, leaving large populations of disadvantaged people unprotected. While many other life-saving prevention measures have been distributed unequally in ways these theories would predict, the COVID-19 vaccines represent a different kind of case. As the disease is so highly infectious and because mutations lead to new variants so rapidly, any inequality-generating process that leaves disadvantaged individuals and countries behind acts to put everyone-rich and poor-at risk. It is time that we ensure the equitable distribution of this life-saving benefit. As the fundamental cause and diffusion of innovation theories help illuminate processes that regularly produce inequities, we turn to them to reason about the rollout of the COVID-19 vaccines. Specifically, employ them to suggest countermoves that may be necessary to avoid an irrational and inequitable vaccine rollout that ends up unfavorably affecting all people.

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The diffusion of innovative diabetes technologies as a fundamental cause of social inequalities in health. The Nord‐Trøndelag Health Study, Norway

Cited by 18 publications

References 44 publications

Inequities in Health Care Services Caused by the Adoption of Digital Health Technologies: Scoping Review

Inequities in Health Care Services Caused by the Adoption of Digital Health Technologies: Scoping Review

Real-World Use of a New Hybrid Closed Loop Improves Glycemic Control in Youth with Type 1 Diabetes

The radically unequal distribution of Covid-19 vaccinations: a predictable yet avoidable symptom of the fundamental causes of inequality

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