Dean Schillinger

Common mental health conditions (CMHCs) such as depression and anxiety often co-occur with noncommunicable diseases (NCDs) like hypertension and diabetes,

Population health initiatives often rely on cold outreach to close gaps in preventive care, such as overdue screenings or immunizations. Tailoring messages to diverse patient populations remains challenging, as traditional A/B testing requires large sample sizes to test only two alternative messages. With increasing availability of large language models (LLMs), programs can utilize tiered testing among both LLM and manual human agents, presenting the dilemma of identifying which patients need different levels of human support to cost-effectively engage large populations. Using microsimulations, we compared both the statistical power and false positive rates of A/B testing and Sequential Multiple Assignment Randomized Trials (SMART) for developing personalized communications across multiple effect sizes and sample sizes. SMART showed better cost-effectiveness and net benefit across all scenarios, but superior power for detecting heterogeneous treatment effects (HTEs) only in later randomization stages, when populations were more homogeneous and subtle differences drove engagement differences.

Background: Patient engagement with secure messaging (SM) via digital patient portals has been associated with improved diabetes outcomes, including increased patient satisfaction and better glycemic control. Yet, disparities in SM uptake exist among older patients and racial and ethnic underserved groups. Care partners (family members or friends) may provide a means for mitigating these disparities; however, it remains unclear whether and to what extent care partners might enhance SM use. Objective: We aim to examine whether SM use differs among older patients with diabetes based on the involvement of care partner proxies. Methods: This is a substudy of the ECLIPPSE (Employing Computational Linguistics to Improve Patient-Provider Secure Emails) project, a cohort study taking place in a large, fully integrated health care delivery system with an established digital patient portal serving over 4 million patients. Participants included patients with type 2 diabetes aged ≥50 years, newly registered on the patient portal, who sent ≥1 English-language message to their clinician between July 1, 2006, and December 31, 2015. Proxy SM was identified by having a registered proxy. To identify nonregistered proxies, a computational linguistics algorithm was applied to detect words and phrases more likely to appear in proxy messages compared to patient-authored messages. The primary outcome was the annual volume of secure messages (sent or received); secondary outcomes were the length of time to the first SM sent by patient or proxy and the number of annual SM exchanges (unique message topics generating ≥1 reply). Results: The mean age of the cohort (N=7659) at this study’s start was 61 (SD 7.16) years; 75% (n=5573) were married, 15% (n=1089) identified as Black, 10% (n=747) Chinese, 12% (n=905) Filipino, 13% (n=999) Latino, and 30% (n=2225) White. Further, 49% (n=3782) of patients used a proxy to some extent. Compared to nonproxy users, proxy users were older (P<.001), had lower educational attainment (P<.001), and had more comorbidities (P<.001). Adjusting for patient sociodemographic and clinical characteristics, proxy users had greater annual SM volume (20.7, 95% CI 20.2-21.2 vs 10.9, 95% CI 10.7-11.2; P<.001), shorter time to SM initiation (hazard ratio vs nonusers: 1.30, 95% CI 1.24-1.37; P<.001), and more annual SM exchanges (6.0, 95% CI 5.8-6.1 vs 2.9, 95% CI 2.9-3.0, P<.001). Differences in SM engagement by proxy status were similar across patient levels of education, and racial and ethnic groups. Conclusions: Among a cohort of older patients with diabetes, proxy SM involvement was independently associated with earlier initiation and increased intensity of messaging, although it did not appear to mitigate existing disparities in SM. These findings suggest care partners can enhance patient-clinician telecommunication in diabetes care. Future studies should examine the effect of care partners’ SM involvement on diabetes-related quality of care and clinical outcomes.

Importance: Sugar-sweetened beverage (SSB) taxes are promoted as key policies to reduce cardiometabolic diseases and other conditions, but comprehensive analyses of SSB taxes in the US have been difficult because of the absence of sufficiently large data samples and methods limitations.Objective: To estimate changes in SSB prices and purchases following SSB taxes in 5 large US cities.Design, Setting, and Participants: In this cross-sectional study with an augmented synthetic control analysis, changes in prices and purchases of SSBs were estimated following SSB tax implementation in Boulder, Colorado; Philadelphia, Pennsylvania; Oakland, California; Seattle, Washington; and San Francisco, California. Changes in SSB prices (in US dollars) and purchases (volume in ounces) in these cities in the 2 years following tax implementation were estimated and compared with control groups constructed from other cities. Changes in adjacent, untaxed areas were assessed to detect any increase in cross-border purchases. Data used for this analysis spanned from January 1, 2012, to February 29, 2020, and were analyzed between June 1, 2022, and September 29, 2023.Main Outcomes and Measures: The main outcomes were the changes in SSB prices and volume purchased.Results: Using nutritional information, 5500 unique universal product codes were classified as SSBs, according to tax designations. The sample included 26 338 stores—496 located in treated localities, 1340 in bordering localities, and 24 502 in the donor pool. Prices of SSBs increased by an average of 33.1% (95% CI, 14.0% to 52.2%; P < .001) during the 2 years following tax implementation, corresponding to an average price increase of 1.3¢ per oz and a 92% tax pass-through rate from distributors to consumers. SSB purchases declined in total volume by an average of 33.0% (95% CI, −2.2% to −63.8%; P = .04) following tax implementation, corresponding to a −1.00 price elasticity of demand. The observed price increase and corresponding volume decrease immediately followed tax implementation, and both outcomes were sustained in the months thereafter. No evidence of increased cross-border purchases following tax implementation was found.Conclusions and Relevance: In this cross-sectional study, SSB taxes led to substantial, consistent declines in SSB purchases across 5 taxed cities following price increases associated with those taxes. Scaling SSB taxes nationally could yield substantial public health benefits.

Authors of this Viewpoint discuss the recent “pause” of the NIH Common Fund’s research program that was designed to study the communication of science and the possible detrimental effect of not addressing scientific misinformation and disinformation.

Introduction: We carried out a two-phase, qualitative evaluation of a novel public health campaign to promote COVID-19 vaccination among youth and young adults of color (YOC), called Survival Pending Revolution. The campaign, commissioned by California's Department of Public Health, was created by YOC spoken word artists, under the direction of the organization, Youth Speaks.Methods: In phase 1, we describe the communication attributes of the campaign's nine video-poems, coded the content of the pieces, and applied thematic analysis to describe the themes conveyed. In phase 2, we carried out a comparative health communication study to assess the content's potential value. We exposed a sample of the target audience (YOC) to the content of Survival Pending Revolution and a widely viewed comparator campaign (The Conversation). Using a focus group, we solicited participants' views using a semi-structured approach. Using thematic analysis, we summarized the reactions that arose when participants reflected on the attributes of each campaign.Results: Findings from phase 1 reveal how engaging YOC artists who embrace Youth Speaks' philosophy of harnessing “life as primary text” resulted in content that is aligned with critical communication theory, focusing on structural determinants of health, including themes of overcoming oppressive systems, health and social inequities, and medical discrimination and mistrust. Findings from phase 2 reveal that this arts-based campaign based on such critical communication theory, when compared to a more traditional campaign, promotes message salience, fosters emotional engagement, and provides a form of validation among historically oppressed groups such that they may be more open to, and potentially act on, the COVID-19 vaccination communications to which they are exposed.Discussion: As an example of critical communication, the Survival Pending Revolution campaign encourages health-promoting behavioral decisions while calling out the structural determinants of health that shape risks of exposure and constrain free choice. Engaging uniquely gifted members of marginalized populations as creators and messengers of campaigns lead to content that is aligned with a critical communication approach, whose goal is to aid disparity populations in both resisting and navigating systems that continue to locate them on the margins of society. Our evaluation of this campaign suggests that it represents a promising formative and interventional approach to engendering trust in public health messaging and promoting health equity.

BACKGROUND Patient engagement with secure messaging (SM) via digital patient portals has been associated with improved diabetes outcomes, including increased patient satisfaction and better glycemic control. Yet, disparities in SM uptake exist among older patients and racial and ethnic underserved groups. Care partners (family members or friends) may provide a means for mitigating these disparities; however, it remains unclear whether and to what extent care partners might enhance SM use. OBJECTIVE We aim to examine whether SM use differs among older patients with diabetes based on the involvement of care partner proxies. METHODS This is a substudy of the ECLIPPSE (Employing Computational Linguistics to Improve Patient-Provider Secure Emails) project, a cohort study taking place in a large, fully integrated health care delivery system with an established digital patient portal serving over 4 million patients. Participants included patients with type 2 diabetes aged ≥50 years, newly registered on the patient portal, who sent ≥1 English-language message to their clinician between July 1, 2006, and December 31, 2015. Proxy SM was identified by having a registered proxy. To identify nonregistered proxies, a computational linguistics algorithm was applied to detect words and phrases more likely to appear in proxy messages compared to patient-authored messages. The primary outcome was the annual volume of secure messages (sent or received); secondary outcomes were the length of time to the first SM sent by patient or proxy and the number of annual SM exchanges (unique message topics generating ≥1 reply). RESULTS The mean age of the cohort (N=7659) at this study’s start was 61 (SD 7.16) years; 75% (n=5573) were married, 15% (n=1089) identified as Black, 10% (n=747) Chinese, 12% (n=905) Filipino, 13% (n=999) Latino, and 30% (n=2225) White. Further, 49% (n=3782) of patients used a proxy to some extent. Compared to nonproxy users, proxy users were older (P<.001), had lower educational attainment (P<.001), and had more comorbidities (P<.001). Adjusting for patient sociodemographic and clinical characteristics, proxy users had greater annual SM volume (20.7, 95% CI 20.2-21.2 vs 10.9, 95% CI 10.7-11.2; P<.001), shorter time to SM initiation (hazard ratio vs nonusers: 1.30, 95% CI 1.24-1.37; P<.001), and more annual SM exchanges (6.0, 95% CI 5.8-6.1 vs 2.9, 95% CI 2.9-3.0, P<.001). Differences in SM engagement by proxy status were similar across patient levels of education, and racial and ethnic groups. CONCLUSIONS Among a cohort of older patients with diabetes, proxy SM involvement was independently associated with earlier initiation and increased intensity of messaging, although it did not appear to mitigate existing disparities in SM. These findings suggest care partners can enhance patient-clinician telecommunication in diabetes care. Future studies should examine the effect of care partners’ SM involvement on diabetes-related quality of care and clinical outcomes.

Background: While a 2021 federal commission recommended that the United States government levy a sugar-sweetened beverage (SSB) tax to improve diabetes prevention and control efforts, evidence is limited regarding the longer-term impacts of SSB taxes on SSB purchases, health outcomes, costs, and cost-effectiveness. This study estimates the impact and cost-effectiveness of an SSB tax levied in Oakland, California. Methods and findings: An SSB tax ($0.01/oz) was implemented on July 1, 2017, in Oakland. The main sample of sales data included 11,627 beverage products, 316 stores, and 172,985,767 product-store-month observations. The main analysis, a longitudinal quasi-experimental difference-in-differences approach, compared changes in beverage purchases at stores in Oakland versus Richmond, California (a nontaxed comparator in the same market area) before and 30 months after tax implementation (through December 31, 2019). Additional estimates used synthetic control methods with comparator stores in Los Angeles, California. Estimates were inputted into a closed-cohort microsimulation model to estimate quality-adjusted life years (QALYs) and societal costs (in Oakland) from 6 SSB-associated disease outcomes. In the main analysis, SSB purchases declined by 26.8% (95% CI −39.0 to −14.7, p < 0.001) in Oakland after tax implementation, compared with Richmond. There were no detectable changes in purchases of untaxed beverages or sweet snacks or purchases in border areas surrounding cities. In the synthetic control analysis, declines in SSB purchases were similar to the main analysis (−22.4%, 95% CI −41.7% to −3.0%, p = 0.04). The estimated changes in SSB purchases, when translated into declines in consumption, would be expected to accrue QALYs (94 per 10,000 residents) and significant societal cost savings (>$100,000 per 10,000 residents) over 10 years, with greater gains over a lifetime horizon. Study limitations include a lack of SSB consumption data and use of sales data primarily from chain stores. Conclusions: An SSB tax levied in Oakland was associated with a substantial decline in volume of SSBs purchased, an association that was sustained more than 2 years after tax implementation. Our study suggests that SSB taxes are effective policy instruments for improving health and generating significant cost savings for society.

The etiology of type 2 diabetes is rooted in a myriad of factors and exposures at individual, community, and societal levels, many of which also affect the control of type 1 and type 2 diabetes. Not only do such factors impact risk and treatment at the time of diagnosis but they also can accumulate biologically from preconception, in utero, and across the life course. These factors include inadequate nutritional quality, poor access to physical activity resources, chronic stress (e.g., adverse childhood experiences, racism, and poverty), and exposures to environmental toxins. The National Clinical Care Commission (NCCC) concluded that the diabetes epidemic cannot be treated solely as a biomedical problem but must also be treated as a societal problem that requires an all-of-government approach. The NCCC determined that it is critical to design, leverage, and coordinate federal policies and programs to foster social and environmental conditions that facilitate the prevention and treatment of diabetes. This article reviews the rationale, scientific evidence base, and content of the NCCC’s population-wide recommendations that address food systems; consumption of water over sugar-sweetened beverages; food and beverage labeling; marketing and advertising; workplace, ambient, and built environments; and research. Recommendations relate to specific federal policies, programs, agencies, and departments, including the U.S. Department of Agriculture, the Food and Drug Administration, the Federal Trade Commission, the Department of Housing and Urban Development, the Environmental Protection Agency, and others. These population-level recommendations are transformative. By recommending health-in-all-policies and an equity-based approach to governance, the NCCC Report to Congress has the potential to contribute to meaningful change across the diabetes continuum and beyond. Adopting these recommendations could significantly reduce diabetes incidence, complications, costs, and inequities. Substantial political resolve will be needed to translate recommendations into policy. Engagement by diverse members of the diabetes stakeholder community will be critical to such efforts.

Electronic patient portals (web-based platforms providing patients immediate access to their health records) are a popular channel that are increasingly available for patients' and providers' communication using secure messaging (SM). These exchanges offer an unprecedented possibility of employing computational linguistics to estimate patients’ health literacy (HL) as well as providers’ language complexity. This chapter describes the NLM-funded ECLIPPSE project and discusses various approaches employed to develop the HL and language complexity measures, the results to date. ECLIPPSE represents an interdisciplinary effort that brought together primary care clinicians with computational linguistics, computers, communication, and health services scientists to harness online SMs exchanged between the patients and the providers to 1) create an automated and valid patient Literacy Profile (LP) that characterizes a patients’ HL, 2) develop an automated and valid physicians’ Complexity Profile (CP) to determine their SMs linguistic complexity, 3) assess whether physicians tailor their SM responses to accommodate limited HL patients communication needs, and 4) design a CP-based automated aid that provides clinicians with real-time feedback to curtail their SMs complexity. Herein, the progress related to Aims 1 and 2 is reported. During the course of LP and CP development, several natural language processing (NLP) tools measuring different language aspects were used and various challenges encountered. To enable successful implementation, solutions were devised for challenges related to data mining, analyses related to NLP and machine learning (ML), and interdisciplinary collaboration. Ultimately, patients’ self-reported HL, physician linguistic complexity, and patients’ HL rated by experts scores were used to train and evaluate ML classification models for building the patients’ LP and physicians’ CP. The ability to rapidly assess patients’ HL at scale could improve clinical care and population health among diverse populations, and determining whether physicians’ CP can be modified to mitigate the untoward effects of limited patient HL is of interest to healthcare delivery systems focused on promoting health equity. This research can reduce HL-related disparities in healthcare by supporting the health systems and healthcare organizations in becoming “health literate”.