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Background Although alert fatigue is blamed for high override rates in contemporary clinical decision support systems, the concept of alert fatigue is poorly defined. We tested hypotheses arising from two possible alert fatigue mechanisms: (A) cognitive overload associated with amount of work, complexity of work, and effort distinguishing informative from uninformative alerts, and (B) desensitization from repeated exposure to the same alert over time. Methods Retrospective cohort study using electronic health record data (both drug alerts and clinical practice reminders) from January 2010 through June 2013 from 112 ambulatory primary care clinicians. The cognitive overload hypotheses were that alert acceptance would be lower with higher workload (number of encounters, number of patients), higher work complexity (patient comorbidity, alerts per encounter), and more alerts low in informational value (repeated alerts for the same patient in the same year). The desensitization hypothesis was that, for newly deployed alerts, acceptance rates would decline after an initial peak. Results On average, one-quarter of drug alerts received by a primary care clinician, and one-third of clinical reminders, were repeats for the same patient within the same year. Alert acceptance was associated with work complexity and repeated alerts, but not with the amount of work. Likelihood of reminder acceptance dropped by 30% for each additional reminder received per encounter, and by 10% for each five percentage point increase in proportion of repeated reminders. The newly deployed reminders did not show a pattern of declining response rates over time, which would have been consistent with desensitization. Interestingly, nurse practitioners were 4 times as likely to accept drug alerts as physicians. Conclusions Clinicians became less likely to accept alerts as they received more of them, particularly more repeated alerts. There was no evidence of an effect of workload per se, or of desensitization over time for a newly deployed alert. Reducing within-patient repeats may be a promising target for reducing alert overrides and alert fatigue.

Background Patients, clinicians, researchers and payers are seeking to understand the value of using genomic information (as reflected by genotyping, sequencing, family history or other data) to inform clinical decision-making. However, challenges exist to widespread clinical implementation of genomic medicine, a prerequisite for developing evidence of its real-world utility. Methods To address these challenges, the National Institutes of Health-funded IGNITE (Implementing GeNomics In pracTicE; www.ignite-genomics.org ) Network, comprised of six projects and a coordinating center, was established in 2013 to support the development, investigation and dissemination of genomic medicine practice models that seamlessly integrate genomic data into the electronic health record and that deploy tools for point of care decision making. IGNITE site projects are aligned in their purpose of testing these models, but individual projects vary in scope and design, including exploring genetic markers for disease risk prediction and prevention, developing tools for using family history data, incorporating pharmacogenomic data into clinical care, refining disease diagnosis using sequence-based mutation discovery, and creating novel educational approaches. Results This paper describes the IGNITE Network and member projects, including network structure, collaborative initiatives, clinical decision support strategies, methods for return of genomic test results, and educational initiatives for patients and providers. Clinical and outcomes data from individual sites and network-wide projects are anticipated to begin being published over the next few years. Conclusions The IGNITE Network is an innovative series of projects and pilot demonstrations aiming to enhance translation of validated actionable genomic information into clinical settings and develop and use measures of outcome in response to genome-based clinical interventions using a pragmatic framework to provide early data and proofs of concept on the utility of these interventions. Through these efforts and collaboration with other stakeholders, IGNITE is poised to have a significant impact on the acceleration of genomic information into medical practice.

Following publication of the original article [1], the authors reported that the article erroneously stated that Dr. Ancker was affiliated with the Tehran University of Medical Sciences. Dr. Ancker is not affiliated with that institution.

We surveyed 488 primary care providers in community and academic practices in New York City in the period 2014-16 about their views on genetic testing for chronic diseases. The majority of the providers, most of whom were current or recent physicians in training, had had formal genetics education and had positive views of the utility of genetic testing. However, they felt unprepared to work with patients at high risk for genetic conditions and were not confident about interpreting test results. Many were concerned that genetic testing might lead to insurance discrimination and lacked trust in companies that offer genetic tests. These findings point to some of the attitudes and knowledge gaps among the providers that should be considered in the clinical implementation of genomic medicine for chronic conditions. Enhanced training, guidelines, clinical tools, and awareness of patient protections might support the effective adoption of genomic medicine by primary care providers.

BACKGROUND Electronic patient portals give patients access to information from their electronic health record and the ability to message their providers. These tools are becoming more widely used and are expected to promote patient engagement with health care. OBJECTIVE To quantify portal usage and explore potential differences in adoption and use according to patients' socioeconomic and clinical characteristics in a network of federally qualified health centers serving New York City and neighboring counties. DESIGN Retrospective analysis of data from portal and electronic health records. PARTICIPANTS 74,368 adult patients seen between April 2008 and April 2010. MAIN MEASURES Odds of receiving an access code to the portal, activating the account, and using the portal more than once KEY RESULTS Over the 2 years of the study, 16% of patients (n = 11,903) received an access code. Of these, 60% (n = 7138) activated the account, and 49% (n = 5791) used the account two or more times. Patients with chronic conditions were more likely to receive an access code and to become repeat users. In addition, the odds of receiving an access code were significantly higher for whites, women, younger patients, English speakers, and the insured. The odds of repeat portal use, among those with activated accounts, increased with white race, English language, and private insurance or Medicaid compared to no insurance. Racial disparities were small but persisted in models that controlled for language, insurance, and health status. CONCLUSIONS We found good early rates of adoption and use of an electronic patient portal during the first 2 years of its deployment among a predominantly low-income population, especially among patients with chronic diseases. Disparities in access to and usage of the portal were evident but were smaller than those reported recently in other populations. Continued efforts will be needed to ensure that portals are usable for and used by disadvantaged groups so that all patients benefit equally from these technologies.

Purpose African ancestry (AA) individuals are inadequately included in translational genomics research, limiting generalizability of findings and benefits of genomic discoveries for populations already facing disproportionately poor health outcomes. We aimed to determine the impact of stakeholder-engaged strategies on recruitment and retention of AA adult patients into a clinical trial testing them for renal risk variants nearly exclusive to AAs. Methods Our academic–clinical–community team developed ten key strategies that recognize AAs' barriers and facilitators for participation. Using electronic health records (EHRs), we identified potentially eligible patients. Recruiters reached out through letters, phone calls, and at medical visits. Results Of 5481 AA patients reached, 51% were ineligible, 37% enrolled, 4% declined, 7% were undecided when enrollment finished. We retained 93% at 3-month and 88% at 12-month follow-up. Those enrolled are more likely female, seen at community sites, and reached through active strategies, than those who declined. Those retained are more likely female, health-literate, and older. While many patients have low income, low clinician trust, and perceive racism in health care, none of these attributes correlate with retention. Conclusion With robust stakeholder engagement, recruiters from patients’ communities, and active approaches, we successfully recruited and retained AA patients into a genomic clinical trial.

Electronic health records (EHRs) have great potential to serve as a catalyst for more effective coordination between public health departments and primary care providers (PCP) in maintaining healthy communities. As a system for documenting patient health data, EHRs can be harnessed to improve public health surveillance for communicable and chronic illnesses. EHRs facilitate clinical alerts informed by public health goals that guide primary care physicians in real time in their diagnosis and treatment of patients. As health departments reassess their public health agendas, the use of EHRs to facilitate this agenda in primary care settings should be considered. PCPs and EHR vendors, in turn, will need to configure their EHR systems and practice workflows to align with public health priorities as these agendas include increased involvement of primary care providers in addressing public health concerns.

A critical gap in the adoption of genomic medicine into medical practice is the need for the rigorous evaluation of the utility of genomic medicine interventions. The Implementing Genomics in Practice Pragmatic Trials Network (IGNITE PTN) was formed in 2018 to measure the clinical utility and cost-effectiveness of genomic medicine interventions, to assess approaches for real-world application of genomic medicine in diverse clinical settings, and to produce generalizable knowledge on clinical trials using genomic interventions. Five clinical sites and a coordinating center evaluated trial proposals and developed working groups to enable their implementation. Two pragmatic clinical trials (PCTs) have been initiated, one evaluating genetic risk APOL1 variants in African Americans in the management of their hypertension, and the other to evaluate the use of pharmacogenetic testing for medications to manage acute and chronic pain as well as depression. IGNITE PTN is a network that carries out PCTs in genomic medicine; it is focused on diversity and inclusion of underrepresented minority trial participants; it uses electronic health records and clinical decision support to deliver the interventions. IGNITE PTN will develop the evidence to support (or oppose) the adoption of genomic medicine interventions by patients, providers, and payers.

Risk variants in the apolipoprotein L1 (APOL1 [OMIM 603743]) gene on chromosome 22 are common in individuals of West African ancestry and confer increased risk of kidney failure for people with African ancestry and hypertension. Whether disclosing APOL1 genetic testing results to patients of African ancestry and their clinicians affects blood pressure, kidney disease screening, or patient behaviors is unknown. To determine the effects of testing and disclosing APOL1 genetic results to patients of African ancestry with hypertension and their clinicians. This pragmatic randomized clinical trial randomly assigned 2050 adults of African ancestry with hypertension and without existing chronic kidney disease in 2 US health care systems from November 1, 2014, through November 28, 2016; the final date of follow-up was January 16, 2018. Patients were randomly assigned to undergo immediate (intervention) or delayed (waiting list control group) APOL1 testing in a 7:1 ratio. Statistical analysis was performed from May 1, 2018, to July 31, 2020. Patients randomly assigned to the intervention group received APOL1 genetic testing results from trained staff; their clinicians received results through clinical decision support in electronic health records. Waiting list control patients received the results after their 12-month follow-up visit. Coprimary outcomes were the change in 3-month systolic blood pressure and 12-month urine kidney disease screening comparing intervention patients with high-risk APOL1 genotypes and those with low-risk APOL1 genotypes. Secondary outcomes compared these outcomes between intervention group patients with high-risk APOL1 genotypes and controls. Exploratory analyses included psychobehavioral factors. Among 2050 randomly assigned patients (1360 women [66%]; mean [SD] age, 53 [10] years), the baseline mean (SD) systolic blood pressure was significantly higher in patients with high-risk APOL1 genotypes vs those with low-risk APOL1 genotypes and controls (137 [21] vs 134 [19] vs 133 [19] mm Hg; P = .003 for high-risk vs low-risk APOL1 genotypes; P = .001 for high-risk APOL1 genotypes vs controls). At 3 months, the mean (SD) change in systolic blood pressure was significantly greater in patients with high-risk APOL1 genotypes vs those with low-risk APOL1 genotypes (6 [18] vs 3 [18] mm Hg; P = .004) and controls (6 [18] vs 3 [19] mm Hg; P = .01). At 12 months, there was a 12% increase in urine kidney disease testing among patients with high-risk APOL1 genotypes (from 39 of 234 [17%] to 68 of 234 [29%]) vs a 6% increase among those with low-risk APOL1 genotypes (from 278 of 1561 [18%] to 377 of 1561 [24%]; P = .10) and a 7% increase among controls (from 33 of 255 [13%] to 50 of 255 [20%]; P = .01). In response to testing, patients with high-risk APOL1 genotypes reported more changes in lifestyle (a subjective measure that included better dietary and exercise habits; 129 of 218 [59%] vs 547 of 1468 [37%]; P < .001) and increased blood pressure medication use (21 of 218 [10%] vs 68 of 1468 [5%]; P = .005) vs those with low-risk APOL1 genotypes; 1631 of 1686 (97%) declared they would get tested again. In this randomized clinical trial, disclosing APOL1 genetic testing results to patients of African ancestry with hypertension and their clinicians was associated with a greater reduction in systolic blood pressure, increased kidney disease screening, and positive self-reported behavior changes in those with high-risk genotypes. ClinicalTrials.gov Identifier: NCT02234063.

Type 2 diabetes plays a major role in racial/ethnic health disparities. We conducted the first study to examine whether multifaceted interventions targeting patients with poorly controlled diabetes (HgbA1c >9%) can reduce racial/ethnic disparities in diabetes control. Among 4595 patients with diabetes at a Federally Qualified Health Center in New York, a higher percentage of blacks (32%) and Hispanics/Latinos (32%) had poorly controlled diabetes than whites (25%) at baseline (prevalence ratio, 1.28; 95% CI, 1.14–1.43; P<0.001). After four years, this percentage was reduced in all groups (blacks, 21%; Hispanics/Latinos, 20%; whites, 20%; P<0.001 for each relative to baseline). Disparities in diabetes control also were significantly reduced (change in disparity relative to whites: blacks, P=0.03; Hispanics/Latinos, P=0.008). In this diverse population, interventions targeting patients with poorly controlled diabetes not only improved diabetes control in all racial/ethnic groups, but significantly reduced disparities. This approach warrants further testing and may help reduce disparities in other populations.