In recent years, technology has been increasingly incorporated within healthcare for the provision of safe and efficient delivery of services. Although this can be attributed to the benefits that can be harnessed, digital technology has the potential to exacerbate and reinforce preexisting health disparities. Previous work has highlighted how sociodemographic, economic, and political factors affect individuals’ interactions with digital health systems and are termed social determinants of health [SDOH]. But, there is a paucity of literature addressing how the intrinsic design, implementation, and use of technology interact with SDOH to influence health outcomes. Such interactions are termed digital determinants of health [DDOH]. This paper will, for the first time, propose a definition of DDOH and provide a conceptual model characterizing its influence on healthcare outcomes. Specifically, DDOH is implicit in the design of artificial intelligence systems, mobile phone applications, telemedicine, digital health literacy [DHL], and other forms of digital technology. A better appreciation of DDOH by the various stakeholders at the individual and societal levels can be channeled towards policies that are more digitally inclusive. In tandem with ongoing work to minimize the digital divide caused by existing SDOH, further work is necessary to recognize digital determinants as an important and distinct entity.

PURPOSE: We identified (1) differences in localized prostate cancer (PCa) risk group at presentation and (2) disparities in access to initial treatment for Asian American, Native Hawaiian, and Pacific Islander (AANHPI) men with PCa after controlling for sociodemographic factors. METHODS: We assessed all patients in the National Cancer Database with localized PCa with low-, intermediate-, and high-risk disease who identified as Thai, White, Asian Indian, Chinese, Vietnamese, Korean, Japanese, Filipino, Hawaiian, Pacific Islander, Laotian, Pakistani, Kampuchean, and Hmong. Multivariable logistic regression defined adjusted odds ratios (AORs) with 95% CI of (1) presenting at progressively higher risk group and (2) receiving treatment or active surveillance with intermediate- or high-risk disease, adjusting for sociodemographic and clinical factors. RESULTS: Among 980,889 men (median age 66 years), all AANHPI subgroups with the exception of Thai (AOR = 0.84 [95% CI, 0.58 to 1.21], P > .05), Asian Indian (AOR = 1.12 [95% CI, 1.00 to 1.25], P > .05), and Pakistani (AOR = 1.34 [95% CI, 0.98 to 1.83], P > .05) men had greater odds of presenting at a progressively higher PCa risk group compared with White patients (Chinese AOR = 1.18 [95% CI, 1.11 to 1.25], P < .001; Japanese AOR = 1.36 [95% CI, 1.26 to 1.47], P < .001; Filipino AOR = 1.37 [95% CI, 1.29 to 1.46], P < .001; Korean AOR = 1.32 [95% CI, 1.18 to 1.48], P < .001; Vietnamese AOR = 1.20 [95% CI, 1.07 to 1.35], P = .002; Laotian AOR = 1.60 [95% CI, 1.08 to 2.36], P = .018; Hmong AOR = 4.07 [95% CI, 1.54 to 10.81], P = .005; Kampuchean AOR = 1.55 [95% CI, 1.03 to 2.34], P = .036; Asian Indian or Pakistani AOR = 1.15 [95% CI, 1.07 to 1.24], P < .001; Native Hawaiians AOR = 1.58 [95% CI, 1.38 to 1.80], P < .001; and Pacific Islanders AOR = 1.58 [95% CI, 1.37 to 1.82], P < .001). Additionally, Japanese Americans (AOR = 1.46 [95% CI, 1.09 to 1.97], P = .013) were more likely to receive treatment compared with White patients. CONCLUSION: Our findings suggest that there are differences in PCa risk group at presentation by race or ethnicity among Asian American, Native Hawaiian, and Pacific Islander subgroups and that there exist disparities in treatment patterns. Although AANHPI are often studied as a homogenous group, heterogeneity upon subgroup disaggregation underscores the importance of further study to assess and address barriers to PCa care.

The Oncology Care Model (OCM), launched in 2016 by the Centers for Medicare and Medicaid Services, was the first demonstration of value-based payment in oncology. Although the OCM delivered mixed results in terms of quality of care and total episode costs, the model had no statistically significant impact on remediating racial, ethnic, and socioeconomic disparities among beneficiaries. These deficits have been prominent in other aspects of US healthcare, and as a result, the Institute for Healthcare Improvement has advocated for stakeholders to leverage improvement science, an applied science that focuses on implementing rapid cycles for change, to identify and overcome barriers to health equity. With the announcement of the new Enhancing Oncology Model, a continuation of the OCM’s efforts in introducing value to cancer care for episodes surrounding chemotherapy administration, both policymakers and providers must apply tenets of improvement science and make eliminating disparities in alternative payment models a forefront objective. In this commentary, we discuss previous inequities in alternative payment models, the role that improvement science plays in addressing health-care disparities, and steps that stakeholders can take to maximize equitable outcomes in the Enhancing Oncology Model.

Objective: The objective of this study is to present a cross-sectional analysis of cancer burden in the South Asian Association for Regional Cooperation (SAARC) region and explain unique characteristics of its cancer burden as compared with the rest of the world. Methods and analysis: Using publicly available data from the Global Cancer Observatory (GCO) and the World Bank, we collected cancer statistics and population statistics for Afghanistan, Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, and Sri Lanka from 2017 to 2022. Results: The number of newly diagnosed cases in the region was 1 846 963, representing 9.3% of the incidence worldwide. As defined by the GCO, the crude incidence rate (CIR) (per 100 000) of cancer in SAARC was 97.3 compared with the worldwide rate of 235.5. The crude mortality rate (per 100 000) in SAARC was 63.4, compared with 123.6 globally. However, the mortality to incidence ratio (MIR) (per 100 000) was 0.65, compared with 0.49 globally. Conclusion: Our research highlights SAARC’s unique cancer landscape with low incidence (CIR) and mortality (CMR) but elevated MIR compared with global figures. These findings underscore the need for a united, contextually relevant approach to addressing the burden of cancer in SAARC. In particular, investment in collaborative, tailored cancer care programmes will build the SAARC region’s capacity to address the growing cancer challenge.

American Journal of Public Health (AJPH) from the American Public Health Association (APHA) All Infrastructure Is Health Infrastructure, an article from American Journal of Public Health, Vol 112 Issue 1