Socioeconomic, rural, and insurance-based inequities in robotic lung cancer resections

Erhunmwunsee, Loretta; Bhandari, Prasha; Sosa, Ernesto; Sur, Melissa; Ituarte, Philip H.G.; Lui, Natalie S.

doi:10.21037/vats.2020.02.01

Cited by 5 publications

(9 citation statements)

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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%

“…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 ]. For example, the average blood sugar level of diabetic patients who use innovative health technologies generally drops [ 49 ], and the use of robotic lobectomy is limited by sociodemographic factors, leading to significant treatment differences in patients with lung cancer [ 67 ].…”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, SES (eg, education and income) [ 69 ] was also discussed. Some (18/41, 44%) studies have reported differences in the acquisition and adoption of digital health technologies by different groups of citizens based on a combination of income and education [ 18 , 24 , 33 , 34 , 36 , 37 , 42 , 44 , 46 , 47 , 49 , 50 , 53 , 56 , 59 - 61 , 64 ], whereas others (13/41, 32%) have independently explored the 2 dimensions of income [ 32 , 35 , 38 , 52 , 55 , 58 , 65 - 67 ] and educational attainment [ 19 , 44 , 54 , 62 ].…”

Section: Resultsmentioning

confidence: 99%

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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

167

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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%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

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

167

View full text Add to dashboard Cite

show abstract

“…44 Though it is not possible in the NCDB to determine the rurality of the treating hospital, prior research suggests rurally located hospitals are much less likely to perform robotic surgery. 20 It is probable that patients from nonmetropolitan or rural areas who have the resources and ability are traveling to regionalized high volume hospitals in metropolitan areas for surgical treatment, thus increasing their likelihood of receiving RARP. 44 Of the sociodemographic variables in the NCDB, insurance payor status is the only one tied directly to the individual patient, while educational attainment and income are linked to geographic areas designated by Zip Code Tabulation Area (ZCTA).…”

Section: Discussionmentioning

confidence: 99%

“…In thoracic surgery, prior research has demonstrated that low-income status, lack of insurance, or treatment at a rural hospital were all independent contributors to reduced likelihood of undergoing robotic lobectomy. 20 Similarly, the rates of implementation of MIS for general surgery procedures including appendectomy, cholecystectomy, hemicolectomy, and hernia repair have been significantly lower for the same patient population. 21,22 Among gynecologic procedures, robotic hysterectomy has grown tremendously in use over the last decade, however, rurality and lack of private insurance were again correlated with reduced likelihood of MIS.…”

Section: Introductionmentioning

confidence: 99%

Disparities in access to robotic technology and perioperative outcomes among patients treated with radical prostatectomy

Logan

Mahenthiran

Siddiqui

et al. 2023

Journal of Surgical Oncology

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Background Most radical prostatectomies are completed with robotic assistance. While studies have previously evaluated perioperative outcomes of robot‐assisted radical prostatectomy (RARP), this study investigates disparities in access and clinical outcomes of RARP. Study Design The National Cancer Database (NCDB) was used to identify patients who received radical prostatectomy for cancer between 2010 and 2017 with outcomes through 2018. RARP was compared to open radical prostatectomy (ORP). Odds of receiving RARP were evaluated while adjusting for covariates. Overall survival was evaluated using a propensity‐score matched cohort. Results Overall, 354 752 patients were included with 297 676 (83.9%) receiving RARP. Patients who were non‐Hispanic Black (82.8%) or Hispanic (81.3%) had lower rates of RARP than non‐Hispanic White (84.0%) or Asian patients (87.7%, p < 0.001). Medicaid or uninsured patients were less likely to receive RARP (75.5%) compared to patients with Medicare or private insurance (84.4%, p < 0.001). Medicaid or uninsured status was associated with decreased odds of RARP in adjusted multivariable analysis (OR 0.61, 95% CI 0.49–0.76). RARP was associated with decreased perioperative mortality and improved overall survival compared to ORP. Conclusion Patients who were underinsured were less likely to receive RARP. Improved access to RARP may lead to decreased disparities in perioperative outcomes for prostate cancer.

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Advancing minimally invasive hepato-pancreato-biliary surgery: barriers to adoption and equitable access

Armstrong,

Lu,

Wang

et al. 2024

Surg Endosc

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Socioeconomic, rural, and insurance-based inequities in robotic lung cancer resections

Cited by 5 publications

References 0 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

Disparities in access to robotic technology and perioperative outcomes among patients treated with radical prostatectomy

Advancing minimally invasive hepato-pancreato-biliary surgery: barriers to adoption and equitable access

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