Effects of Social Determinants and Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions.

Context: The present study builds on our prior work that demonstrated an association between pharmacogenetic interactions and 90-day readmission. Objective: Evaluate aggregate contribution of social determinants, comorbidity, and gene-x-drug interactions to moderate 90-day hospital readmission. Study Design and Analysis: Non-concurrent cohort study; Multivariable logistic regression Setting: Hospital/integrated healthcare delivery system in northern Illinois Population Studied: 19,999 adults tracked from 2010 through 2020 who underwent testing with a 13-gene pharmacogenetic panel Outcome Measure: 90-day hospital readmission (primary outcome) Results: Univariate logistic regression analyses demonstrated that strongest associations with 90 day hospital readmissions were the number of medications prescribed within 30 days of a first hospital admission that had Clinical Pharmacogenomics Implementation Consortium (CPIC) guidance (CPIC medications) (5+ CPIC medications, odds ratio (OR) = 7.66, 95% confidence interval 5.45-10.77) (p < 0.0001), major comorbidities (5+ comorbidities, OR 3.36, 2.61-4.32) (p < 0.0001), age (65 + years, OR = 2.35, 1.77-3.12) (p < 0.0001), unemployment (OR = 2.19, 1.88-2.64) (p < 0.0001), Black/African-American race (OR 2.12, 1.47-3.07) (p < 0.0001), median household income (OR = 1.63, 1.03-2.58) (p = 0.035), male gender (OR = 1.47, 1.21-1.80) (p = 0.0001), and one or more gene-x-drug interaction (defined as a prescribed CPIC medication for a patient with a corresponding actionable pharmacogenetic variant) (OR = 1.41, 1.18-1.70). Health insurance was not associated with risk of 90-day readmission. Race, income, employment status, and gene-x-drug interactions were robust in a multivariable logistic regression model. The odds of 90-day readmission for patients with one or more identified gene-x-drug interactions after adjustment for these covariates was attenuated by 10% (OR = 1.31, 1.08-1.59) (p = 0.006). Although the interaction between race and gene-x-drug interactions was not statistically significant, White patients were more likely to have a gene-x-drug interaction (35.2%) than Black/African-American patients (25.9%) who were not readmitted (p < 0.0001). Conclusions: These results highlight the major contribution of social determinants and medical complexity to risk for hospital readmission, and that these determinants may modify the effect of gene-x-drug interactions on rehospitalization risk.

"Everything in One Place": Stakeholder Perceptions of Integrated Medical and Social Care for Diabetes Patients in Western Maryland.

BACKGROUND: Patients with type 2 diabetes frequently have both medical- and health-related social needs that must be addressed for optimal disease management. Growing evidence suggests that intersectoral partnerships between health systems and community-based organizations may effectively support improved health outcomes for patients with diabetes. OBJECTIVE: The purpose of this study was to describe stakeholders' perceptions of the implementation factors associated with a diabetes management program, an intervention involving coordinated clinical and social services supports to address both medical- and health-related social needs. This intervention delivers proactive care alongside community partnerships, and leverages innovative financing mechanisms. DESIGN: Qualitative study with semi-structured interviews. PARTICIPANTS: Study participants included adults (18 years or older) who were patients with diabetes and essential staff (e.g., members of a diabetes care team, health care administrators) and leaders of community-based organizations. APPROACH: We used the Consolidated Framework for Implementation Research (CFIR) to develop a semi-structured interview guide designed to elicit perspectives from patients and essential staff on their experiences within an outpatient center to support patients with chronic conditions (the CCR) as a part of an intervention to improve care for patients with diabetes. KEY RESULTS: Interviews illuminated three key takeaways: (1) team-based care held an important role in promoting accountability across stakeholders motivating patient engagement and positive perceptions, (2) mission-driven alignment across the health care and community sectors was needed to synergize a broad range of efforts, and (3) global payment models allowing for flexible resource allocation can invaluably support the appropriate care being directed where it is needed the most whether medical or social services. CONCLUSIONS: The views and experiences of patient and essential staff stakeholder groups reported here thematically according to CFIR domains may inform the development of other chronic disease interventions that address medical- and health-related social needs in additional settings.

Quality of Care for US Adults With Medicaid Insurance and Type 2 Diabetes in Federally Qualified Health Centers Compared With Other Primary Care Settings.

OBJECTIVE: The objective of this study was to evaluate indicators of diabetes quality of care for US nonelderly, adult Medicaid enrollees with type 2 diabetes and compare federally qualified health centers (FQHCs) versus non-FQHCs. RESEARCH DESIGN AND METHODS: We analyzed diabetes process measures and acute health services utilization with 2012 US fee-for-service and managed care Medicaid claims in all 50 states and DC. We compared FQHC (N=121,977) to non-FQHC patients (N=700,401) using propensity scores to balance covariates and generalized estimating equation models. RESULTS: Overall, laboratory-based process measures occurred more frequently (range, 65.7%-76.6%) than measures requiring specialty referrals (retinal examinations, 33.3%; diabetes education, 3.4%). Compared with non-FQHC patients, FQHC patients had about 3 percentage point lower rates of each process measure, except for higher rates of diabetes education [relative risk=1.09, 95% confidence interval (CI): 1.03-1.16]. FQHC patients had fewer overall [incident rate ratio (IRR)=0.87, 95% CI: 0.86-0.88] and diabetes-related hospitalizations (IRR=0.79, 95% CI: 0.77-0.81), but more overall (IRR=1.06, 95% CI: 1.05-1.07) and diabetes-related emergency department visits (IRR=1.10, 95% CI: 1.08-1.13). CONCLUSIONS: This national analysis identified opportunities to improve diabetes management among Medicaid enrollees with type 2 diabetes, especially for retinal examinations or diabetes education. Overall, we found slightly lower rates of most diabetes care process measures for FQHC patients versus non-FQHC patients. Despite having higher rates of emergency department visits, FQHC patients were significantly less likely to be hospitalized than non-FQHC patients. These findings emphasize the need to identify innovative, effective approaches to improve diabetes care for Medicaid enrollees, especially in FQHC settings.

The Impact of Changes in Medicaid Provider Fees on Provider Participation and Enrollees' Care: a Systematic Literature Review.

BACKGROUND: Changing Medicaid fees is a common approach for states to address budget fluctuations, and many currently set Medicaid physician fees at levels lower than Medicare and private insurers. The Affordable Care Act included a temporary Medicaid fee bump for primary care providers (PCPs) in 2013-2014 that recently led to both an increase and then subsequent decrease in PCP fees in many states. OBJECTIVE: To conduct a systematic literature review on the effects of changing Medicaid fees on provider participation and enrollees' access to care and service use. METHODS: We searched PubMed/Medline and JSTOR and identified 18 studies that assessed the longitudinal impact of provider fee changes in Medicaid on the outcomes of interest. We summarized information on study design, methods, and findings. RESULTS: Seven studies examined the impact of fee changes on provider participation in Medicaid. Of these, three studies found that fee increases were associated with positive effects on providers' likelihood of accepting Medicaid patients or on their Medicaid caseloads. Five studies that examined the impact of fee changes on Medicaid enrollees' access to care found a positive association with one or more access measure, such as having a usual source of care or appointment availability. Lastly, eight of 14 studies that examined service use found positive associations between fee changes and at least one measure of use, such as changes in the probability of enrollees having any visit, the number of visits, and shifts in the site of care toward office-based care; others largely did not find significant associations. CONCLUSIONS: There is mixed evidence on the impact of changing Medicaid fees on provider participation and enrollees' service use; however, increasing fees appears to have more consistent positive effects on access to care. Whether these improvements in access translate into better health outcomes or downstream cost savings are critical questions.

The Impact of Breast Density Notification Laws on Supplemental Breast Imaging and Breast Biopsy.

BACKGROUND: Dense breast tissue increases breast cancer risk and lowers mammography sensitivity, but the value of supplemental imaging for dense breasts remains uncertain. Since 2009, 37 states and Washington DC have passed legislation requiring patient notification about breast density. OBJECTIVE: Examine the effects of state breast density notification laws on use of supplemental breast imaging and breast biopsies. DESIGN: Difference-in-differences analysis of supplemental imaging and biopsies before and after notification laws in 12 states enacting breast density notification laws from 2009 to 2014 and 12 matched control states. Supplemental imaging/biopsy within 6 months following an index mammogram were evaluated during four time periods related to legislation: (1) 6 months before, (2) 0-6 months after, (3) 6-12 months after, and (4) 12-18 months after. PARTICIPANTS: Women ages 40-64 years receiving an initial mammogram in a state that passed a breast density notification law or a control state. INTERVENTION: Mandatory breast density notification following an index mammogram. MAIN MEASURES: Use of breast biopsies and supplemental breast imaging (breast ultrasound, tomosynthesis, magnetic resonance imaging, scintimammography, and thermography), overall and by specific test. KEY RESULTS: Supplemental breast imaging and biopsy increased modestly in states with notification laws and changed minimally in control states. Adjusted rates of supplemental imaging and biopsy within 6 months of mammography before legislation were 8.5% and 3.1%, respectively. Compared with pre-legislation in intervention and control states, legislation was associated with adjusted difference-in-differences estimates of + 1.3% (p < 0.0001) and + 0.4% (p < 0.0001) for supplemental imaging and biopsies, respectively, in the 6-12 months after the law and difference-in-differences estimates of + 3.3% (p < 0.0001) and + 0.8% (p < 0.0001) for supplemental imaging and biopsies, respectively, 12-18 months after the law. CONCLUSIONS: As breast density notification laws are considered, policymakers and clinicians should expect increases in breast imaging/biopsies. Additional research is needed on these laws' effects on cost and patient outcomes.

Financing Diabetes Care in the U.S. Health System: Payment Innovations for Addressing the Medical and Social Determinants of Health.

PURPOSE OF REVIEW: Review innovations in health care financing promoting health system investments in addressing medical and social determinants of health (SDH) for patients with diabetes. RECENT FINDINGS: Particular payment models implemented in the public and private sectors increasingly offer flexibility in health care organizations (HCOs) to allocate resources towards helping patients with diabetes overcome the medical and socio-economic problems driving poor population and individual health. The barriers imposed by the traditional fee-for-service (FFS) payment model to incorporating SDH into health care delivery across the health system are being overcome with new payment approaches rewarding the quality of care provided rather than strictly the volume of health services rendered. Evidence suggests health care financing changes will facilitate the realization of health reform goals to provide the right care to the right people at the right time through the expansion of the role of integrated care teams that can address patients' medical and health-related social needs.

Medicaid Privatization: Has the Invisible Hand Led Us Astray?

Medicaid Privatization: Has the Invisible Hand Led Us Astray? presents timely questions regarding our nation's healthcare safety-net: (1) What are the consequences when states outsource the administration of Medicaid to private organizations with a profit motive?; (2) Can returning administrative responsibility back to state governments restore any losses to quality and equity experienced by previously privatized public programs?; and (3) Is it time to abandon Medicaid managed care altogether for state-operated fee-for-service or other alternative administrative arrangements?

Assessment of unmeasured confounding in the association between perceived discrimination and mental health in a predominantly African American cohort using g-estimation.

BACKGROUND: Perceived discrimination in health care settings can have adverse consequences on mental health in minority groups. However, the association between perceived discrimination and mental health is prone to unmeasured confounding. The study aims to quantitatively evaluate the influence of unmeasured confounding in this association, using g-estimation. METHODS: In a predominantly African American cohort, we applied g-estimation to estimate the association between perceived discrimination and mental health, adjusted and unadjusted for measured confounders. Mental health was measured using clinical diagnoses of anxiety, depression and bipolar disorder. Perceived discrimination was measured as the number of patient-reported discrimination events in health care settings. Measured confounders included demographic, socioeconomic, residential and health characteristics. The influence of confounding was denoted as α1 from g-estimation. We compared α1 for measured and unmeasured confounding. RESULTS: Strong associations between perceived discrimination in health care settings and mental health outcomes were observed. For anxiety, the odds ratio (95% confidence interval) unadjusted and adjusted for measured confounders were 1.30 (1.21, 1.39) and 1.26 (1.17, 1.36), respectively. The α1 for measured confounding was -0.066. Unmeasured confounding with α1=0.200, which was over three times that of measured confounding, corresponds to an odds ratio of 1.12 (1.01, 1.24). Similar results were observed for other mental health outcomes. CONCLUSION: Compared with measured confounding, unmeasured that was three times measured confounding was not enough to explain away the association between perceived discrimination and mental health, suggesting that this association is robust to unmeasured confounding. This study provides a novel framework to quantitatively evaluate unmeasured confounding.

Geographic and Physician-Level Variation in the Use of Hypofractionated Radiation Therapy for Breast Cancer in the U.S.: A Cross-Classified Multilevel Analysis.

Purpose: We aimed to assess geographic and physician-level variation for hypofractionated whole-breast irradiation (HF-WBI) use for early-stage breast cancer patients in the United States. We further evaluated the association between HF-WBI use and demographic factors after accounting for these variations. Methods and Materials: We performed a retrospective study of early-stage breast cancer patients using private employer-sponsored insurance claims from 2008 to 2017. Patients were clustered according to geographic level and by radiation oncologist. Bayesian cross-classified multilevel logistic models were used to examine the geographic heterogeneity and variation of radiation oncologists simultaneously. Intracluster correlation coefficient (ICC) and median odds ratios (MOR) were calculated to quantify the variation at different levels. We also used the cross-classified model to identify patient demographic factors associated with receiving HF-WBI. Results: The study included 79,747 women (74.0%) who received conventionally fractionated whole-breast irradiation (CF-WBI) and 27,999 women (26.0%) who underwent HF-WBI. HF-WBI adoption increased significantly across time (2008-2017). The variation in HF-WBI utilization was attributed mostly to physician-level variability (MOR = 2.59). The variability of HF-WBI utilization across core-based statistical areas (CBSAs) (MOR = 1.55) was found to be the strongest among all geographic classifications. After accounting for variability in both CBSAs and radiation oncologists, age, receiving chemotherapy, and several community-level factors, including distance from home to facility, community education level, and racial composition, were found to be associated with HF-WBI utilization. Conclusion: This study demonstrated geographic and physician-level heterogeneity in the use of HF-WBI among early-stage breast cancer patients. HF-WBI utilization was also found to be associated with patient and community-level characteristics. Given observed physician-level variability, intervention through continuing medical education could help doctors to better understand the advantages of HF-WBI and promote the adoption of HF-WBI in the U.S. Influence of physician-level characteristics on HF-WBI utilization merits further study.

Advancing genomics to improve health equity.

Health equity is the state in which everyone has fair and just opportunities to attain their highest level of health. The field of human genomics has fallen short in increasing health equity, largely because the diversity of the human population has been inadequately reflected among participants of genomics research. This lack of diversity leads to disparities that can have scientific and clinical consequences. Achieving health equity related to genomics will require greater effort in addressing inequities within the field. As part of the commitment of the National Human Genome Research Institute (NHGRI) to advancing health equity, it convened experts in genomics and health equity research to make recommendations and performed a review of current literature to identify the landscape of gaps and opportunities at the interface between human genomics and health equity research. This Perspective describes these findings and examines health equity within the context of human genomics and genomic medicine.

The social vulnerability metric (SVM) as a new tool for public health.

OBJECTIVE: To derive and validate a new ecological measure of the social determinants of health (SDoH), calculable at the zip code or county level. DATA SOURCES AND STUDY SETTING: The most recent releases of secondary, publicly available data were collected from national U.S. health agencies as well as state and city public health departments. STUDY DESIGN: The Social Vulnerability Metric (SVM) was constructed from U.S. zip-code level measures (2018) from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality (2016), COVID-19 vaccination (2021), and emergency department visits for asthma (2018). The SVM was also compared with the existing Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to determine convergent validity and differential predictive validity. DATA COLLECTION/EXTRACTION METHODS: The data were collected directly from published files available to the public online from national U.S. health agencies as well as state and city public health departments. PRINCIPAL FINDINGS: The correlation between SVM scores and national age-adjusted county all-cause mortality was r = 0.68. This correlation demonstrated the SVM's robust validity and outperformed the SVI with an almost four-fold increase in explained variance (46% vs. 12%). The SVM was also highly correlated (r ≥ 0.60) to zip-code level health outcomes for the state of California and city of Chicago. CONCLUSIONS: The SVM offers a measurement tool improving upon the performance of existing SDoH composite measures and has broad applicability to public health that may help in directing future policies and interventions. The SVM provides a single measure of SDoH that better quantifies associations with health outcomes.

The impact of neighborhood disadvantage on colorectal cancer screening among African Americans in Chicago.

Historically, colorectal cancer (CRC) screening rates have been lower among African Americans. Previous studies that have examined the relationship between community characteristics and adherence to CRC screening have generally focused on a single community parameter, making it challenging to evaluate the overall impact of the social and built environment. In this study, we will estimate the overall effect of social and built environment and identify the most important community factors relevant to CRC screening. Data are from the Multiethnic Prevention and Surveillance Study (COMPASS), a longitudinal study among adults in Chicago, collected between May 2013 to March 2020. A total 2,836 African Americans completed the survey. Participants' addresses were geocoded and linked to seven community characteristics (i.e., community safety, community crime, household poverty, community unemployment, housing cost burden, housing vacancies, low food access). A structured questionnaire measured adherence to CRC screening. Weighted quantile sum (WQS) regression was used to evaluate the impact of community disadvantages on CRC screening. When analyzing all community characteristics as a mixture, overall community disadvantage was associated with less adherence to CRC screening even after controlling for individual-level factors. In the adjusted WQS model, unemployment was the most important community characteristic (37.6%), followed by community insecurity (26.1%) and severe housing cost burden (16.3%). Results from this study indicate that successful efforts to improve adherence to CRC screening rates should prioritize individuals living in communities with high rates of insecurity and low socioeconomic status.

Social Vulnerability and Risk of Suicide in US Adults, 2016-2020.

Importance: There were over 45 000 suicides in the US in 2020, making suicide the 12th leading cause of death. If social vulnerability is associated with suicide rates, targeted interventions for at-risk segments of the population may reduce US suicide rates. Objective: To determine the association between social vulnerability and suicide in adults. Design, Setting, and Participants: This cohort study analyzed 2 county-level social vulnerability measures (the Social Vulnerability Index [SVI] and the Social Vulnerability Metric [SVM]) and US Centers for Disease Control and Prevention-reported county-level suicides from 2016 to 2020. Data were analyzed November and December 2022. Exposures: County-level variability in social vulnerability. Main Outcomes and Measures: The primary outcome measure was number of county-level adult suicides from 2016 to 2020, offset by county adult population during those years. The association between social vulnerability (measured using the SVI and the newly created SVM for 2018) and suicide was modeled using a bayesian-censored Poisson regression model to account for the CDC's suppression of county-level suicide counts of less than 10, adjusted for age, racial and ethnic minority, and urban-rural county characteristics. Results: From 2016 to 2020, there were a total of 222 018 suicides in 3141 counties. Comparing the least socially vulnerable (0% to 10%) to the most socially vulnerable (90% to 100%) counties, there was a 56% increase in suicide rate (17.3 per 100 000 persons to 27.0 per 100 000 persons) as measured by the SVI (incidence rate ratio, 1.56; 95% credible interval, 1.51-1.60) and an 82% increase in suicide rate (13.8 per 100 000 persons to 25.1 per 100 000 persons) as measured by the SVM (incidence rate ratio, 1.82; 95% credible interval, 1.72-1.92). Conclusions and Relevance: This cohort study found that social vulnerability had a direct association with risk for adult suicide. Reducing social vulnerability may lead to life-saving reduction in the rate of suicide.

Hypofractionated Radiation Therapy for Breast Cancer: Financial Risk and Expenditures in the United States, 2008 to 2017.

PURPOSE: Rising cancer care expenditures and technological advancement of shorter radiation therapy regimens have drawn significant attention to the use of hypofractionated radiation therapy in clinical care. We examine the costs of hypofractionated whole breast irradiation (HF-WBI) compared with conventional whole breast irradiation (CF-WBI) in the United States and investigate the influences of patient characteristics and commercial insurance on HF-WBI use. METHODS AND MATERIALS: In a retrospective study using private employer-sponsored insurance claims, a pooled cross-sectional evaluation of radiation therapy in patients with commercial insurance was performed from 2008 to 2017. The study population included female patients with early-stage breast cancer treated with lumpectomy and whole breast irradiation. RESULTS: A total of 15,869 women received HF-WBI, and 59,328 received CF-WBI. HF-WBI use increased from 2008 to 2017. Community-level factors such as a higher proportion of college graduates and greater mixed racial composition were associated with increased HF-WBI use. Mean insurer-paid radiation therapy expenditures were significantly lower for HF-WBI versus CF-WBI (adjusted difference, $6375; 95% confidence interval, $6147-$6603). Mean patient out-of-pocket expenditure for HF-WBI was $139 less than that for CF-WBI. Geographic variation existed across the United States in HF-WBI use (range, 9.6%-36.2%), with no consistent relationship between HF-WBI use and corresponding average cost differences between HF-WBI and CF-WBI. CONCLUSIONS: If trends continue, HF-WBI will soon become the dominant form of radiation treatment in the United States. Although HF-WBI represents significant savings to the health care system and individual patients, no evidence indicated that a financial disincentive had slowed adoption of HF-WBI. Therefore, multilevel approaches, including individuals, the community, and health policy, should be used to promote cost-effective cancer care. Innovations to policies on cost-effective radiation therapy treatment might consider non-financial incentives to promote HF-WBI use.

Has Hypofractionated Whole-Breast Radiation Therapy Become the Standard of Care in the United States? An Updated Report from National Cancer Database.

INTRODUCTION/BACKGROUND: We aimed to update the previous evaluation of hypofractionated whole-breast irradiation (HF-WBI) use over time in the United States and factors related to its adoption for patients undergoing a lumpectomy from 2004 to 2016. MATERIALS AND METHODS: Among the patients who underwent a lumpectomy, we identified 688,079 patients with early-stage invasive breast cancer and 248,218 patients with ductal carcinoma in situ in the National Cancer Database from 2004 to 2016. We defined HF-WBI as 2.5 to 3.33 Gy/fraction to the breast and conventional fractionated whole-breast irradiation as 1.8 to 2.0 Gy/fraction. We evaluated the trend of HF-WBI use and examined factors associated with HF-WBI use using logistic regression models. RESULTS: Among invasive cancer patients, the use of HF-WBI increased exponentially from 0.7% in 2004 to 15.6% in 2013 and then to 38.1% in 2016. Among patients with ductal carcinoma in situ, the use of HF-WBI has increased significantly from 0.42% in 2004 to 13.4% in 2013 and then to 34.3% in 2016. Factors found to be associated with HF-WBI use included age, patient geographical location, race/ethnicity, tumor stage, grade, treating facility type, and volume. CONCLUSION: HF-WBI use in the United States has more than doubled from 2013 to 2016. Although its use is close to that of conventional fractionated whole-breast irradiation, HF-WBI is still far from the preferred standard of care in the United States. We identified several patient and facility factors that can impact the uptake of HF-WBI treatment. Microabstract Using the National Cancer Database from 2004 to 2016, we evaluated the trend of hypofractionated whole-breast radiation therapy use and factors associated with use. Use in the United States has more than doubled from 2013 to 2016, but it has not become the standard of care. We identified several patient and facility factors that impact the uptake of hypofractionated whole-breast radiation therapy treatment.

Effect Modification by Social Determinants of Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions within an Integrated U.S. Healthcare System.

The present study builds on our prior work that demonstrated an association between pharmacogenetic interactions and 90-day readmission. In a substantially larger, more diverse study population of 19,999 adults tracked from 2010 through 2020 who underwent testing with a 13-gene pharmacogenetic panel, we included additional covariates to evaluate aggregate contribution of social determinants and medical comorbidity with the presence of identified gene-x-drug interactions to moderate 90-day hospital readmission (primary outcome). Univariate logistic regression analyses demonstrated that strongest associations with 90 day hospital readmissions were the number of medications prescribed within 30 days of a first hospital admission that had Clinical Pharmacogenomics Implementation Consortium (CPIC) guidance (CPIC medications) (5+ CPIC medications, odds ratio (OR) = 7.66, 95% confidence interval 5.45−10.77) (p < 0.0001), major comorbidities (5+ comorbidities, OR 3.36, 2.61−4.32) (p < 0.0001), age (65 + years, OR = 2.35, 1.77−3.12) (p < 0.0001), unemployment (OR = 2.19, 1.88−2.64) (p < 0.0001), Black/African-American race (OR 2.12, 1.47−3.07) (p < 0.0001), median household income (OR = 1.63, 1.03−2.58) (p = 0.035), male gender (OR = 1.47, 1.21−1.80) (p = 0.0001), and one or more gene-x-drug interaction (defined as a prescribed CPIC medication for a patient with a corresponding actionable pharmacogenetic variant) (OR = 1.41, 1.18−1.70). Health insurance was not associated with risk of 90-day readmission. Race, income, employment status, and gene-x-drug interactions were robust in a multivariable logistic regression model. The odds of 90-day readmission for patients with one or more identified gene-x-drug interactions after adjustment for these covariates was attenuated by 10% (OR = 1.31, 1.08−1.59) (p = 0.006). Although the interaction between race and gene-x-drug interactions was not statistically significant, White patients were more likely to have a gene-x-drug interaction (35.2%) than Black/African-American patients (25.9%) who were not readmitted (p < 0.0001). These results highlight the major contribution of social determinants and medical complexity to risk for hospital readmission, and that these determinants may modify the effect of gene-x-drug interactions on rehospitalization risk.

Underrepresented patient views and perceptions of personalized medication treatment through pharmacogenomics.

Within an institutional pharmacogenomics implementation program, we surveyed 463 outpatients completing preemptive pharmacogenomic testing whose genetic results were available to providers for guiding medication treatment. We compared views and experiences from self-reported White and Black patients, including education level as a covariate across analyses. Black patients were less confident about whether their providers made personalized treatment decisions, and overwhelmingly wanted a greater role for their genetic information in clinical care. Both groups similarly reported that providers asked their opinions regarding medication changes, but White patients were more likely (59% vs. 49%, P = 0.005) to discuss the impact of personal/genetic makeup on medication response with providers, and Black patients reported initiating such discussions much less frequently (4% vs. 15%, P = 0.037). Opportunities exist for enhanced communication with underrepresented patients around personalized care. Tailored communication strategies and development of support tools employed in diverse healthcare settings may facilitate pharmacogenomically guided medication treatment that equitably benefits minority patient populations.

Artificial Intelligence Can Cut Costs While Maintaining Accuracy in Colorectal Cancer Genotyping.

Rising cancer care costs impose financial burdens on health systems. Applying artificial intelligence to diagnostic algorithms may reduce testing costs and avoid wasteful therapy-related expenditures. To evaluate the financial and clinical impact of incorporating artificial intelligence-based determination of mismatch repair/microsatellite instability status into the first-line metastatic colorectal carcinoma setting, we developed a deterministic model to compare eight testing strategies: A) next-generation sequencing alone, B) high-sensitivity polymerase chain reaction or immunohistochemistry panel alone, C) high-specificity panel alone, D) high-specificity artificial intelligence alone, E) high-sensitivity artificial intelligence followed by next generation sequencing, F) high-specificity artificial intelligence followed by next-generation sequencing, G) high-sensitivity artificial intelligence and high-sensitivity panel, and H) high-sensitivity artificial intelligence and high-specificity panel. We used a hypothetical, nationally representative, population-based sample of individuals receiving first-line treatment for de novo metastatic colorectal cancer (N = 32,549) in the United States. Model inputs were derived from secondary research (peer-reviewed literature and Medicare data). We estimated the population-level diagnostic costs and clinical implications for each testing strategy. The testing strategy that resulted in the greatest project cost savings (including testing and first-line drug cost) compared to next-generation sequencing alone in newly-diagnosed metastatic colorectal cancer was using high-sensitivity artificial intelligence followed by confirmatory high-specificity polymerase chain reaction or immunohistochemistry panel for patients testing negative by artificial intelligence ($400 million, 12.9%). The high-specificity artificial intelligence-only strategy resulted in the most favorable clinical impact, with 97% diagnostic accuracy in guiding genotype-directed treatment and average time to treatment initiation of less than one day. Artificial intelligence has the potential to reduce both time to treatment initiation and costs in the metastatic colorectal cancer setting without meaningfully sacrificing diagnostic accuracy. We expect the artificial intelligence value proposition to improve in coming years, with increasing diagnostic accuracy and decreasing costs of processing power. To extract maximal value from the technology, health systems should evaluate integrating diagnostic histopathologic artificial intelligence into institutional protocols, perhaps in place of other genotyping methodologies.

Applicability of Pharmacogenomically Guided Medication Treatment during Hospitalization of At-Risk Minority Patients.

Known disparities exist in the availability of pharmacogenomic information for minority populations, amplifying uncertainty around clinical utility for these groups. We conducted a multi-site inpatient pharmacogenomic implementation program among self-identified African-Americans (AA; n = 135) with numerous rehospitalizations (n = 341) from 2017 to 2020 (NIH-funded ACCOuNT project/clinicaltrials.gov#NCT03225820). We evaluated the point-of-care availability of patient pharmacogenomic results to healthcare providers via an electronic clinical decision support tool. Among newly added medications during hospitalizations and at discharge, we examined the most frequently utilized medications with associated pharmacogenomic results. The population was predominantly female (61%) with a mean age of 53 years (range 19-86). On average, six medications were newly prescribed during each individual hospital admission. For 48% of all hospitalizations, clinical pharmacogenomic information was applicable to at least one newly prescribed medication. Most results indicated genomic favorability, although nearly 29% of newly prescribed medications indicated increased genomic caution (increase in toxicity risk/suboptimal response). More than one of every five medications prescribed to AA patients at hospital discharge were associated with cautionary pharmacogenomic results (most commonly pantoprazole/suboptimal antacid effect). Notably, high-risk pharmacogenomic results (genomic contraindication) were exceedingly rare. We conclude that the applicability of pharmacogenomic information during hospitalizations for vulnerable populations at-risk for experiencing health disparities is substantial and warrants continued prospective investigation.

Perceptions of politicization and HPV vaccine policy support.

BACKGROUND: Since its FDA approval in 2006, the Human papillomavirus (HPV) vaccine has been politically-charged, given its association with sexual health among young women and its history of controversial, and largely unsuccessful, legislative mandates. The extent to which perceived politicization is related to public support for the vaccine's use, however, is not clear. We sought to examine the relationship between public perceptions of politicization of the HPV vaccine and public support for HPV vaccine policies. METHODS: We fielded a survey from May-June 2016 using a nationally representative sample of U.S. adults (18-59 years). Among respondents aware of the HPV vaccine (n = 290), we predict support for HPV vaccine policies based on respondents' perceptions of three characteristics of the vaccine's portrayal in public discourse: degree of controversy, certainty of the scientific evidence supporting the vaccine's use, and frequency with which the vaccine appears in political discussion. RESULTS: Respondents who perceived greater certainty about the scientific evidence for the HPV vaccine were more supportive of HPV vaccine policies (p < 0.0001) than respondents who perceived the scientific evidence to be uncertain, after adjusting for respondents' characteristics, including demographics and partisanship. CONCLUSIONS: Public perceptions of the HPV vaccine's politicization, particularly the portrayal of scientific evidence, are associated with receptivity to legislative mandates. POLICY IMPLICATIONS: How the certainty of a body of evidence gets communicated to the public may influence the policy process for a critical cancer prevention intervention.