Genetically guided precision medicine clinical decision support tools: a systematic review.

OBJECTIVES: Patient care using genetics presents complex challenges. Clinical decision support (CDS) tools are a potential solution because they provide patient-specific risk assessments and/or recommendations at the point of care. This systematic review evaluated the literature on CDS systems which have been implemented to support genetically guided precision medicine (GPM). MATERIALS AND METHODS: A comprehensive search was conducted in MEDLINE and Embase, encompassing January 1, 2011-March 14, 2023. The review included primary English peer-reviewed research articles studying humans, focused on the use of computers to guide clinical decision-making and delivering genetically guided, patient-specific assessments, and/or recommendations to healthcare providers and/or patients. RESULTS: The search yielded 3832 unique articles. After screening, 41 articles were identified that met the inclusion criteria. Alerts and reminders were the most common form of CDS used. About 27 systems were integrated with the electronic health record; 2 of those used standards-based approaches for genomic data transfer. Three studies used a framework to analyze the implementation strategy. DISCUSSION: Findings include limited use of standards-based approaches for genomic data transfer, system evaluations that do not employ formal frameworks, and inconsistencies in the methodologies used to assess genetic CDS systems and their impact on patient outcomes. CONCLUSION: We recommend that future research on CDS system implementation for genetically GPM should focus on implementing more CDS systems, utilization of standards-based approaches, user-centered design, exploration of alternative forms of CDS interventions, and use of formal frameworks to systematically evaluate genetic CDS systems and their effects on patient care.

Genomics in nephrology: identifying informatics opportunities to improve diagnosis of genetic kidney disorders using a human-centered design approach.

BACKGROUND: Genomic kidney conditions often have a long lag between onset of symptoms and diagnosis. To design a real time genetic diagnosis process that meets the needs of nephrologists, we need to understand the current state, barriers, and facilitators nephrologists and other clinicians who treat kidney conditions experience, and identify areas of opportunity for improvement and innovation. METHODS: Qualitative in-depth interviews were conducted with nephrologists and internists from 7 health systems. Rapid analysis identified themes in the interviews. These were used to develop service blueprints and process maps depicting the current state of genetic diagnosis of kidney disease. RESULTS: Themes from the interviews included the importance of trustworthy resources, guidance on how to order tests, and clarity on what to do with results. Barriers included lack of knowledge, lack of access, and complexity surrounding the case and disease. Facilitators included good user experience, straightforward diagnoses, and support from colleagues. DISCUSSION: The current state of diagnosis of kidney diseases with genetic etiology is suboptimal, with information gaps, complexity of genetic testing processes, and heterogeneity of disease impeding efficiency and leading to poor outcomes. This study highlights opportunities for improvement and innovation to address these barriers and empower nephrologists and other clinicians who treat kidney conditions to access and use real time genetic information.

Using implementation science to develop a familial hypercholesterolemia screening program in primary care: The CARE-FH study.

BACKGROUND: We designed the Collaborative Approach to Reach Everyone with familial hypercholesterolemia (CARE-FH) clinical trial to improve FH screening in primary care and facilitate guideline-based care. OBJECTIVE: The goal was to incorporate perspectives from end-users (healthcare system leaders, primary care clinicians, cardiologists, genetic counselors, nurses, and clinic staff) and improve translation of screening guidance into practice. METHODS: We partnered with end-users to sequentially define the current state of FH screening, assess acceptability, feasibility, and appropriateness of implementing an FH screening program, and select clinically actionable strategies at the patient-, clinician-, and system-level to be deployed as a package in the CARE-FH clinical trial. Methods informed by implementation science and human centered design included: contextual inquiries, surveys, and deliberative engagement sessions. RESULTS: Screening for FH occurred rarely in primary care, and then only after a cardiovascular event or sometimes due to a family history of high cholesterol or early heart attack. Surveys suggested FH screening in primary care was acceptable, appropriate, and feasible. Reported and observed barriers to screening include insufficient time at patient encounters to screen, cost and convenience of testing for patients, and knowledge regarding causes of dyslipidemia. Facilitators included clear guidance on screening criteria and new therapies to treat FH. These results led to the development of multilevel strategies that were presented to end-users, modified, and then pilot tested in one primary care clinic. CONCLUSIONS: A refined implementation strategy package for FH screening was created with a goal of improving FH awareness, identification, and initiation of guideline-based care. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/study/NCT05284513?id=NCT05284513&rank=1 Unique Identifier: NCT05284513.

Enabling the clinical application of artificial intelligence in genomics: a perspective of the AMIA Genomics and Translational Bioinformatics Workgroup.

OBJECTIVE: Given the importance AI in genomics and its potential impact on human health, the American Medical Informatics Association-Genomics and Translational Biomedical Informatics (GenTBI) Workgroup developed this assessment of factors that can further enable the clinical application of AI in this space. PROCESS: A list of relevant factors was developed through GenTBI workgroup discussions in multiple in-person and online meetings, along with review of pertinent publications. This list was then summarized and reviewed to achieve consensus among the group members. CONCLUSIONS: Substantial informatics research and development are needed to fully realize the clinical potential of such technologies. The development of larger datasets is crucial to emulating the success AI is achieving in other domains. It is important that AI methods do not exacerbate existing socio-economic, racial, and ethnic disparities. Genomic data standards are critical to effectively scale such technologies across institutions. With so much uncertainty, complexity and novelty in genomics and medicine, and with an evolving regulatory environment, the current focus should be on using these technologies in an interface with clinicians that emphasizes the value each brings to clinical decision-making.

Should secondary pharmacogenomic variants be actively screened and reported when diagnostic genome-wide sequencing is performed in a child?

This white paper was prepared by the Global Alliance for Genomics and Health Regulatory and Ethics Work Stream's Pediatric Task Team to review and provide perspective with respect to ethical, legal, and social issues regarding the return of secondary pharmacogenomic variants in children who have a serious disease or developmental disorder and are undergoing exome or genome sequencing to identify a genetic cause of their condition. We discuss actively searching for and reporting pharmacogenetic/genomic variants in pediatric patients, different methods of returning secondary pharmacogenomic findings to the patient/parents and/or treating clinicians, maintaining these data in the patient's health record over time, decision supports to assist using pharmacogenetic results in future treatment decisions, and sharing information in public databases to improve the clinical interpretation of pharmacogenetic variants identified in other children. We conclude by presenting a series of points to consider for clinicians and policymakers regarding whether, and under what circumstances, routine screening and return of pharmacogenomic variants unrelated to the indications for testing is appropriate in children who are undergoing genome-wide sequencing to assist in the diagnosis of a suspected genetic disease.

Evaluation of Malignant Hyperthermia Features in Patients with Pathogenic or Likely Pathogenic RYR1 Variants Disclosed through a Population Genomic Screening Program.

BACKGROUND: Malignant hyperthermia (MH) susceptibility is a heritable musculoskeletal disorder that can present as a potentially fatal hypermetabolic response to triggering anesthesia agents. Genomic screening for variants in MH-associated genes RYR1 and CACNA1S provides an opportunity to prevent morbidity and mortality. There are limited outcomes data from disclosing variants in RYR1, the most common MH susceptibility gene, in unselected populations. The authors sought to identify the rate of MH features or fulminant episodes after triggering agent exposure in an unselected population undergoing genomic screening including actionable RYR1 variants. METHODS: The MyCode Community Health Initiative by Geisinger (USA) is an electronic health record-linked biobank that discloses pathogenic and likely pathogenic variants in clinically actionable genes to patient-participants. Available electronic anesthesia and ambulatory records for participants with actionable RYR1 results returned through December 2020 were evaluated for pertinent findings via double-coded chart reviews and reconciliation. Descriptive statistics for observed phenotypes were calculated. RESULTS: One hundred fifty-two participants had an actionable RYR1 variant disclosed during the study period. None had previous documented genetic testing for MH susceptibility; one had previous contracture testing diagnosing MH susceptibility. Sixty-eight participants (44.7%) had anesthesia records documenting triggering agent exposure during at least one procedure. None received dantrolene treatment or had documented muscle rigidity, myoglobinuria, hyperkalemia, elevated creatine kinase, severe myalgia, or tea-colored urine. Of 120 possibly MH-related findings (postoperative intensive care unit admissions, hyperthermia, arterial blood gas evaluation, hypercapnia, or tachycardia), 112 (93.3%) were deemed unlikely to be MH events; 8 (6.7%) had insufficient records to determine etiology. CONCLUSIONS: Results demonstrate a low frequency of classic intraanesthetic hypermetabolic phenotypes in an unselected population with actionable RYR1 variants. Further research on the actionability of screening for MH susceptibility in unselected populations, including economic impact, predictors of MH episodes, and expanded clinical phenotypes, is necessary.

Testing and Management of Iron Overload After Genetic Screening-Identified Hemochromatosis.

Importance: HFE gene-associated hereditary hemochromatosis type 1 (HH1) is underdiagnosed, resulting in missed opportunities for preventing morbidity and mortality. Objective: To assess whether screening for p.Cys282Tyr homozygosity is associated with recognition and management of asymptomatic iron overload. Design, Setting, and Participants: This cross-sectional study obtained data from the Geisinger MyCode Community Health Initiative, a biobank of biological samples and linked electronic health record data from a rural, integrated health care system. Participants included those who received a p.Cys282Tyr homozygous result via genomic screening (MyCode identified), had previously diagnosed HH1 (clinically identified), and those negative for p.Cys282Tyr homozygosity between 2017 and 2018. Data were analyzed from April 2020 to August 2023. Exposure: Disclosure of a p.Cys282Tyr homozygous result. Main Outcomes and Measures: Postdisclosure management and HFE-associated phenotypes in MyCode-identified participants were analyzed. Rates of HFE-associated phenotypes in MyCode-identified participants were compared with those of clinically identified participants. Relevant laboratory values and rates of laboratory iron overload among participants negative for p.Cys282Tyr homozygosity were compared with those of MyCode-identified participants. Results: A total of 86 601 participants had available exome sequences at the time of analysis, of whom 52 994 (61.4%) were assigned female at birth, and the median (IQR) age was 62.0 (47.0-73.0) years. HFE p.Cys282Tyr homozygosity was disclosed to 201 participants, of whom 57 (28.4%) had a prior clinical HH1 diagnosis, leaving 144 participants who learned of their status through screening. There were 86 300 individuals negative for p.Cys282Tyr homozygosity. After result disclosure, among MyCode-identified participants, 99 (68.8%) had a recommended laboratory test and 36 (69.2%) with laboratory or liver biopsy evidence of iron overload began phlebotomy or chelation. Fifty-three (36.8%) had iron overload; rates of laboratory iron overload were higher in MyCode-identified participants than participants negative for p.Cys282Tyr homozygosity (females: 34.1% vs 2.1%, P < .001; males: 39.0% vs 2.9%, P < .001). Iron overload (females: 34.1% vs 79.3%, P < .001; males: 40.7% vs 67.9%, P = .02) and some liver-associated phenotypes were observed at lower frequencies in MyCode-identified participants compared with clinically identified individuals. Conclusions and Relevance: Results of this cross-sectional study showed the ability of genomic screening to identify undiagnosed iron overload and encourage relevant management, suggesting the potential benefit of population screening for HFE p.Cys282Tyr homozygosity. Further studies are needed to examine the implications of genomic screening for health outcomes and cost-effectiveness.

Prospective, multi-site study of healthcare utilization after actionable monogenic findings from clinical sequencing.

As large-scale genomic screening becomes increasingly prevalent, understanding the influence of actionable results on healthcare utilization is key to estimating the potential long-term clinical impact. The eMERGE network sequenced individuals for actionable genes in multiple genetic conditions and returned results to individuals, providers, and the electronic health record. Differences in recommended health services (laboratory, imaging, and procedural testing) delivered within 12 months of return were compared among individuals with pathogenic or likely pathogenic (P/LP) findings to matched individuals with negative findings before and after return of results. Of 16,218 adults, 477 unselected individuals were found to have a monogenic risk for arrhythmia (n = 95), breast cancer (n = 96), cardiomyopathy (n = 95), colorectal cancer (n = 105), or familial hypercholesterolemia (n = 86). Individuals with P/LP results more frequently received services after return (43.8%) compared to before return (25.6%) of results and compared to individuals with negative findings (24.9%; p < 0.0001). The annual cost of qualifying healthcare services increased from an average of $162 before return to $343 after return of results among the P/LP group (p < 0.0001); differences in the negative group were non-significant. The mean difference-in-differences was $149 (p < 0.0001), which describes the increased cost within the P/LP group corrected for cost changes in the negative group. When stratified by individual conditions, significant cost differences were observed for arrhythmia, breast cancer, and cardiomyopathy. In conclusion, less than half of individuals received billed health services after monogenic return, which modestly increased healthcare costs for payors in the year following return.

Low adenoma burden in unselected patients with a pathogenic APC variant.

PURPOSE: Genomic screening can improve clinical outcomes, but presentation of individuals with risk for polyposis identified via genomic screening is unknown. To inform assessment of clinical utility of genomic screening for polyposis risk, clinical presentation of individuals in an unselected health care system cohort with an APC pathogenic or likely pathogenic (P/LP) variant causative of familial adenomatous polyposis are described. METHODS: Electronic health records of individuals with an APC P/LP variant identified via the MyCode program (MyCode APC+) were reviewed to assess adenoma burden and compare it among individuals with a clinical diagnosis of familial adenomatous polyposis and matched variant-negative controls. RESULTS: The prevalence of APC P/LP variants in this health care cohort is estimated to be 1 in 2800. Twenty-four MyCode APC+ individuals were identified during the study period. Median age at result disclosure was 53 years. Rate of clinical polyposis was 8%. Two of six participants with a classic region variant and none of those with an attenuated region variant had polyposis. MyCode APC+ participants did not differ from controls in cumulative adenoma count. CONCLUSION: APC P/LP variant prevalence estimate in the MyCode cohort is higher than prior published prevalence rates. Individuals with APC P/LP variants identified via genomic screening had a low adenoma burden.

Yield of Familial Hypercholesterolemia Genetic and Phenotypic Diagnoses After Electronic Health Record and Genomic Data Screening.

Background Data mining of electronic health records to identify patients suspected of familial hypercholesterolemia (FH) has been limited by absence of both phenotypic and genomic data in the same cohort. Methods and Results Using the Geisinger MyCode Community Health Initiative cohort (n=130 257), we ran 2 screening algorithms (Mayo Clinic [Mayo] and flag, identify, network, deliver [FIND] FH) to determine FH genetic and phenotypic diagnostic yields. With 29 243 excluded by Mayo (for secondary causes of hypercholesterolemia, no lipid value in electronic health records), 52 034 excluded by FIND FH (insufficient data to run the model), and 187 excluded for prior FH diagnosis, a final cohort of 59 729 participants was created. Genetic diagnosis was based on presence of a pathogenic or likely pathogenic variant in FH genes. Charts from 180 variant-negative participants (60 controls, 120 identified by FIND FH and Mayo) were reviewed to calculate Dutch Lipid Clinic Network scores; a score ≥5 defined probable phenotypic FH. Mayo flagged 10 415 subjects; 194 (1.9%) had a pathogenic or likely pathogenic FH variant. FIND FH flagged 573; 34 (5.9%) had a pathogenic or likely pathogenic variant, giving a net yield from both of 197 out of 280 (70%). Confirmation of a phenotypic diagnosis was constrained by lack of electronic health record data on physical findings or family history. Phenotypic FH by chart review was present by Mayo and/or FIND FH in 13 out of 120 versus 2 out of 60 not flagged by either (P<0.09). Conclusions Applying 2 recognized FH screening algorithms to the Geisinger MyCode Community Health Initiative identified 70% of those with a pathogenic or likely pathogenic FH variant. Phenotypic diagnosis was rarely achievable due to missing data.

Population Genomic Screening for Three Common Hereditary Conditions : A Cost-Effectiveness Analysis.

BACKGROUND: The cost-effectiveness of screening the U.S. population for Centers for Disease Control and Prevention (CDC) Tier 1 genomic conditions is unknown. OBJECTIVE: To estimate the cost-effectiveness of simultaneous genomic screening for Lynch syndrome (LS), hereditary breast and ovarian cancer syndrome (HBOC), and familial hypercholesterolemia (FH). DESIGN: Decision analytic Markov model. DATA SOURCES: Published literature. TARGET POPULATION: Separate age-based cohorts (ages 20 to 60 years at time of screening) of racially and ethnically representative U.S. adults. TIME HORIZON: Lifetime. PERSPECTIVE: U.S. health care payer. INTERVENTION: Population genomic screening using clinical sequencing with a restricted panel of high-evidence genes, cascade testing of first-degree relatives, and recommended preventive interventions for identified probands. OUTCOME MEASURES: Incident breast, ovarian, and colorectal cancer cases; incident cardiovascular events; quality-adjusted survival; and costs. RESULTS OF BASE-CASE ANALYSIS: Screening 100 000 unselected 30-year-olds resulted in 101 (95% uncertainty interval [UI], 77 to 127) fewer overall cancer cases and 15 (95% UI, 4 to 28) fewer cardiovascular events and an increase of 495 quality-adjusted life-years (QALYs) (95% UI, 401 to 757) at an incremental cost of $33.9 million (95% UI, $27.0 million to $41.1 million). The incremental cost-effectiveness ratio was $68 600 per QALY gained (95% UI, $41 800 to $88 900). RESULTS OF SENSITIVITY ANALYSIS: Screening 30-, 40-, and 50-year-old cohorts was cost-effective in 99%, 88%, and 19% of probabilistic simulations, respectively, at a $100 000-per-QALY threshold. The test costs at which screening 30-, 40-, and 50-year-olds reached the $100 000-per-QALY threshold were $413, $290, and $166, respectively. Variant prevalence and adherence to preventive interventions were also highly influential parameters. LIMITATIONS: Population averages for model inputs, which were derived predominantly from European populations, vary across ancestries and health care environments. CONCLUSION: Population genomic screening with a restricted panel of high-evidence genes associated with 3 CDC Tier 1 conditions is likely to be cost-effective in U.S. adults younger than 40 years if the testing cost is relatively low and probands have access to preventive interventions. PRIMARY FUNDING SOURCE: National Human Genome Research Institute.

Designing implementation strategies to improve identification, cascade testing, and management of families with familial hypercholesterolemia: An intervention mapping approach.

Introduction: Familial hypercholesterolemia (FH) is a common inherited cholesterol disorder that, without early intervention, leads to premature cardiovascular disease. Multilevel strategies that target all components of FH care including identification, cascade testing, and management are needed to address gaps that exist in FH care. We utilized intervention mapping, a systematic implementation science approach, to identify and match strategies to existing barriers and develop programs to improve FH care. Methods: Data were collected utilizing two methods: a scoping review of published literature, related to any component of FH care, and a parallel mixed method study using interviews and surveys. The scientific literature was searched using key words including "barriers" or "facilitators" and "familial hypercholesterolemia" from inception to December 1, 2021. The parallel mixed method study recruited individuals and families with FH to participate in either dyadic interviews (N = 11 dyads/22 individuals) or online surveys (N = 98 respondents). Data generated from the scoping review, dyadic interviews, and online surveys were used in the 6-step intervention mapping process. Steps 1-3 included a needs assessment, development of program outcomes and creation of evidence-based implementation strategies. Steps 4-6 included program development, implementation, and evaluation of implementation strategies. Results: In steps 1-3, a needs assessment found barriers to FH care included underdiagnosis of the condition which led to suboptimal management due to a myriad of determinants including knowledge gaps, negative attitudes, and risk misperceptions by individuals with FH and clinicians. Literature review highlighted barriers to FH care at the health system level, notably the relative lack of genetic testing resources and infrastructure needed to support FH diagnosis and treatment. Examples of strategies to overcome identified barriers included development of multidisciplinary care teams and educational programs. In steps 4-6, an NHLBI-funded study, the Collaborative Approach to Reach Everyone with FH (CARE-FH), deployed strategies that focused on improving identification of FH in primary care settings. The CARE-FH study is used as an example to describe program development, implementation, and evaluation techniques of implementation strategies. Conclusion: The development and deployment of evidence-based implementation strategies that address barriers to FH care are important next steps to improve identification, cascade testing, and management.

Familial Hypercholesterolemia in the Electronic Medical Records and Genomics Network: Prevalence, Penetrance, Cardiovascular Risk, and Outcomes After Return of Results.

BACKGROUND: The implications of secondary findings detected in large-scale sequencing projects remain uncertain. We assessed prevalence and penetrance of pathogenic familial hypercholesterolemia (FH) variants, their association with coronary heart disease (CHD), and 1-year outcomes following return of results in phase III of the electronic medical records and genomics network. METHODS: Adult participants (n=18 544) at 7 sites were enrolled in a prospective cohort study to assess the clinical impact of returning results from targeted sequencing of 68 actionable genes, including LDLR, APOB, and PCSK9. FH variant prevalence and penetrance (defined as low-density lipoprotein cholesterol >155 mg/dL) were estimated after excluding participants enrolled on the basis of hypercholesterolemia. Multivariable logistic regression was used to estimate the odds of CHD compared to age- and sex-matched controls without FH-associated variants. Process (eg, referral to a specialist or ordering new tests), intermediate (eg, new diagnosis of FH), and clinical (eg, treatment modification) outcomes within 1 year after return of results were ascertained by electronic health record review. RESULTS: The prevalence of FH-associated pathogenic variants was 1 in 188 (69 of 13,019 unselected participants). Penetrance was 87.5%. The presence of an FH variant was associated with CHD (odds ratio, 3.02 [2.00-4.53]) and premature CHD (odds ratio, 3.68 [2.34-5.78]). At least 1 outcome occurred in 92% of participants; 44% received a new diagnosis of FH and 26% had treatment modified following return of results. CONCLUSIONS: In a multisite cohort of electronic health record-linked biobanks, monogenic FH was prevalent, penetrant, and associated with presence of CHD. Nearly half of participants with an FH-associated variant received a new diagnosis of FH and a quarter had treatment modified after return of results. These results highlight the potential utility of sequencing electronic health record-linked biobanks to detect FH.

A picture is worth a thousand words: advancing the use of visualization tools in implementation science through process mapping and matrix heat mapping.

BACKGROUND: Identifying key determinants is crucial for improving program implementation and achieving long-term sustainment within healthcare organizations. Organizational-level complexity and heterogeneity across multiple stakeholders can complicate our understanding of program implementation. We describe two data visualization methods used to operationalize implementation success and to consolidate and select implementation factors for further analysis. METHODS: We used a combination of process mapping and matrix heat mapping to systematically synthesize and visualize qualitative data from 66 stakeholder interviews across nine healthcare organizations, to characterize universal tumor screening programs of all newly diagnosed colorectal and endometrial cancers and understand the influence of contextual factors on implementation. We constructed visual representations of protocols to compare processes and score process optimization components. We also used color-coded matrices to systematically code, summarize, and consolidate contextual data using factors from the Consolidated Framework for Implementation Research (CFIR). Combined scores were visualized in a final data matrix heat map. RESULTS: Nineteen process maps were created to visually represent each protocol. Process maps identified the following gaps and inefficiencies: inconsistent execution of the protocol, no routine reflex testing, inconsistent referrals after a positive screen, no evidence of data tracking, and a lack of quality assurance measures. These barriers in patient care helped us define five process optimization components and used these to quantify program optimization on a scale from 0 (no program) to 5 (optimized), representing the degree to which a program is implemented and optimally maintained. Combined scores within the final data matrix heat map revealed patterns of contextual factors across optimized programs, non-optimized programs, and organizations with no program. CONCLUSIONS: Process mapping provided an efficient method to visually compare processes including patient flow, provider interactions, and process gaps and inefficiencies across sites, thereby measuring implementation success via optimization scores. Matrix heat mapping proved useful for data visualization and consolidation, resulting in a summary matrix for cross-site comparisons and selection of relevant CFIR factors. Combining these tools enabled a systematic and transparent approach to understanding complex organizational heterogeneity prior to formal coincidence analysis, introducing a stepwise approach to data consolidation and factor selection.

Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network.

The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using electronic health records (EHRs). Based on scientific merit and predicted difficulty, eMERGE selected six existing phenotypes to enhance with NLP. We assessed performance, portability, and ease of use. We summarized lessons learned by: (1) challenges; (2) best practices to address challenges based on existing evidence and/or eMERGE experience; and (3) opportunities for future research. Adding NLP resulted in improved, or the same, precision and/or recall for all but one algorithm. Portability, phenotyping workflow/process, and technology were major themes. With NLP, development and validation took longer. Besides portability of NLP technology and algorithm replicability, factors to ensure success include privacy protection, technical infrastructure setup, intellectual property agreement, and efficient communication. Workflow improvements can improve communication and reduce implementation time. NLP performance varied mainly due to clinical document heterogeneity; therefore, we suggest using semi-structured notes, comprehensive documentation, and customization options. NLP portability is possible with improved phenotype algorithm performance, but careful planning and architecture of the algorithms is essential to support local customizations.

Making inroads to precision medicine for the treatment of autoimmune diseases: Harnessing genomic studies to better diagnose and treat complex disorders.

Precision Medicine is an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle. Autoimmune diseases are those in which the body's natural defense system loses discriminating power between its own cells and foreign cells, causing the body to mistakenly attack healthy tissues. These conditions are very heterogeneous in their presentation and therefore difficult to diagnose and treat. Achieving precision medicine in autoimmune diseases has been challenging due to the complex etiologies of these conditions, involving an interplay between genetic, epigenetic, and environmental factors. However, recent technological and computational advances in molecular profiling have helped identify patient subtypes and molecular pathways which can be used to improve diagnostics and therapeutics. This review discusses the current understanding of the disease mechanisms, heterogeneity, and pathogenic autoantigens in autoimmune diseases gained from genomic and transcriptomic studies and highlights how these findings can be applied to better understand disease heterogeneity in the context of disease diagnostics and therapeutics.

Population-based screening of newborns: Findings from the newborn screening expansion study (part two).

Rapid advances in genomic technologies to screen, diagnose, and treat newborns will significantly increase the number of conditions in newborn screening (NBS). We previously identified four factors that delay and/or complicate NBS expansion: 1) variability in screening panels persists; 2) the short duration of pilots limits information about interventions and health outcomes; 3) recent recommended uniform screening panel (RUSP) additions are expanding the definition of NBS; and 4) the RUSP nomination and evidence review process has capacity constraints. In this paper, we developed a use case for each factor and suggested how model(s) could be used to evaluate changes and improvements. The literature on models was reviewed from a range of disciplines including system sciences, management, artificial intelligence, and machine learning. The results from our analysis highlighted that there is at least one model which could be applied to each of the four factors that has delayed and/or complicate NBS expansion. In conclusion, our paper supports the use of modeling to address the four challenges in the expansion of NBS.