Personalized medicine in a community health system: the NorthShore experience.

Genomic and personalized medicine implementation efforts have largely centered on specialty care in tertiary health systems. There are few examples of fully integrated care systems that span the healthcare continuum. In 2014, NorthShore University HealthSystem launched the Center for Personalized Medicine to catalyze the delivery of personalized medicine. Successful implementation required the development of a scalable family history collection tool, the Genetic and Wellness Assessment (GWA) and Breast Health Assessment (BHA) tools; integrated pharmacogenomics programming; educational programming; electronic medical record integration; and robust clinical decision support tools. To date, more than 225,000 patients have been screened for increased hereditary conditions, such as cancer risk, through these tools in primary care. More than 35,000 patients completed clinical genetic testing following GWA or BHA completion. An innovative program trained more than 100 primary care providers in genomic medicine, activated with clinical decision support and access to patient genetic counseling services and digital healthcare tools. The development of a novel bioinformatics platform (FLYPE) enabled the incorporation of genomics data into electronic medical records. To date, over 4,000 patients have been identified to have a pathogenic or likely pathogenic variant in a gene with medical management implications. Over 33,000 patients have clinical pharmacogenomics data incorporated into the electronic health record supported by clinical decision support tools. This manuscript describes the evolution, strategy, and successful multispecialty partnerships aligned with health system leadership that enabled the implementation of a comprehensive personalized medicine program with measurable patient outcomes through a genomics-enabled learning health system model that utilizes implementation science frameworks.

Utility of Polygenic Scores for Differentiating Diabetes Diagnosis Among Patients With Atypical Phenotypes of Diabetes.

CONTEXT: Misclassification of diabetes type occurs in people with atypical presentations of type 1 diabetes (T1D) or type 2 diabetes (T2D). Although current clinical guidelines suggest clinical variables and treatment response as ways to help differentiate diabetes type, they remain insufficient for people with atypical presentations. OBJECTIVE: This work aimed to assess the clinical utility of 2 polygenic scores (PGSs) in differentiating between T1D and T2D. METHODS: Patients diagnosed with diabetes in the UK Biobank were studied (N = 41 787), including 464 (1%) and 15 923 (38%) who met the criteria for classic T1D and T2D, respectively, and 25 400 (61%) atypical diabetes. The validity of 2 published PGSs for T1D (PGST1D) and T2D (PGST2D) in differentiating classic T1D or T2D was assessed using C statistic. The utility of genetic probability for T1D based on PGSs (GenProb-T1D) was evaluated in atypical diabetes patients. RESULTS: The joint performance of PGST1D and PGST2D for differentiating classic T1D or T2D was outstanding (C statistic = 0.91), significantly higher than that of PGST1D alone (0.88) and PGST2D alone (0.70), both P less than .001. Using an optimal cutoff of GenProb-T1D, 23% of patients with atypical diabetes had a higher probability of T1D and its validity was independently supported by clinical presentations that are characteristic of T1D. CONCLUSION: PGST1D and PGST2D can be used to discriminate classic T1D and T2D and have potential clinical utility for differentiating these 2 types of diseases among patients with atypical diabetes.

Safe Transitions and Congregate Living in the Age of COVID-19: A Retrospective Cohort Study.

BACKGROUND: COVID-19 represents a grave risk to residents in skilled nursing facilities (SNFs). OBJECTIVE: To determine whether establishment of an appropriate-use committee was associated with a reduction in SNF utilization. DESIGNS, SETTING, AND PARTICIPANTS: Retrospective cohort study at NorthShore University HealthSystem, a multihospital integrated health system in northern Illinois. Participants were patients hospitalized from March 19, 2019, to July 16, 2020. INTERVENTION: Creation of a multidisciplinary committee to assess appropriateness of discharge to SNF following hospitalization. MAIN OUTCOME AND MEASURES: Primary outcome was total discharges to SNFs. Secondary outcomes were new discharges to SNFs, readmissions, length of stay (LOS), and COVID-19 incidence following discharge. RESULTS: Matched populations pre and post intervention were each 4424 patients. Post intervention, there was a relative reduction in total SNF discharges of 49.7% (odds ratio [OR], 0.42; 95% CI, 0.38-0.47) and in new SNF discharges of 66.9% (OR, 0.29; 95% CI, 0.25-0.34). Differences in readmissions and LOS were not statistically significant. For patients discharged to a SNF, 2.99% (95% CI, 1.59%-4.39%) developed COVID-19 within 30 days, compared with 0.26% (95% CI, 0.29%-0.93%) of patients discharged to other settings (P < .001). CONCLUSION: Implementing a review committee to assess for appropriateness of SNF use after a hospitalization during the COVID-19 pandemic is highly effective. There was no negative impact on safety or efficiency of hospital care, and reduced SNF use likely prevented several cases of COVID-19. This model could serve as a template for other hospitals to reduce the risks of COVID-19 in SNFs and as part of a value-based care strategy.

Primary Care Physician Experiences with Integrated Population-Scale Genetic Testing: A Mixed-Methods Assessment.

The scalable delivery of genomic medicine requires collaboration between genetics and non-genetics providers. Thus, it is essential to investigate and address the perceived value of and barriers to incorporating genetic testing into the clinical practice of primary care providers (PCPs). We used a mixed-methods approach of qualitative interviews and surveys to explore the experience of PCPs involved in the pilot DNA-10K population genetic testing program. Similar to previous research, PCPs reported low confidence with tasks related to ordering, interpreting and managing the results of genetic tests, and identified the need for additional education. PCPs endorsed high levels of utility for patients and their families but noted logistical challenges to incorporating genetic testing into their practice. Overall PCPs were not familiar with the United States' Genetic Information Nondiscrimination Act and they expressed high levels of concern for patient data privacy and potential insurance discrimination. This PCP feedback led to the development and implementation of several processes to improve the PCP experience with the DNA-10K program. These results contribute to the knowledge base regarding genomic implementation using a mixed provider model and may be beneficial for institutions developing similar clinical programs.

Pharmacogenomics: Prescribing Precisely.

Pharmacogenomics (PGx) is a powerful tool that can predict increased risks of adverse effects and sub-therapeutic response to medications. This article establishes the core principles necessary for a primary care provider to meaningfully and prudently use PGx testing. Key topics include in which patients PGx testing should be considered, how PGx tests are ordered, how the results are translated into clinical recommendations, and what further advancements are likely in the near future. This will provide clinicians with a foundational knowledge of PGx that can allow incorporation of this tool into their practice or support further personal investigation.

Overt expression of AP-1 reduces alpha myosin heavy chain expression and contributes to heart failure from chronic volume overload.

Reduced expression of alpha-MHC plays a significant role in cardiac contractile dysfunction from hemodynamic overload. Previously, Pur proteins and YY1 have been shown to play a role in alpha-MHC repression during heart failure induced by pressure overload and by spontaneous hypertension, respectively. This was not observed in volume-overload-induced heart failure, suggesting additional regulatory mechanisms for alpha-MHC repression. The present study was performed to identify volume overload responsive transcription factors involved in alpha-MHC gene regulation. DNA binding activity of several transcription factors was evaluated in a functionally characterized rat model of heart failure induced by aorto-caval shunt. After 10 weeks of shunt, severe LV dilatation and reduced LV function were accompanied by increased expression of ANF and beta-MHC, and decreased expression of alpha-MHC. This was associated with dramatic (10-fold) activation of AP-1 together with increased expression of c-fos and c-jun. AP-1 activation was not observed following 4 weeks of shunt when cardiac function was preserved. In cultured cardiomyocytes, induction of AP-1 by PMA attenuated alpha-MHC mRNA by 60%. Transient transfection assays mapped PMA responsive sequence to -582 to -588 bp of alpha-MHC promoter. Deletion or mutation of these nucleotides had minimal effect on basal promoter activity but played a dominant role in PMA-mediated repression of alpha-MHC promoter activity. Over-expression of c-fos and c-jun in cardiomyocytes inhibited alpha-MHC promoter activity in a concentration dependent manner. Data suggest a repressive role of AP-1 in alpha-MHC expression and its possible involvement in the transition from compensatory hypertrophy to heart failure in chronic volume overload.