Genetic testing behavior and reporting patterns in electronic medical records for physicians trained in a primary care specialty or subspecialty

Precision Medicine Landscape of Genomic Testing for Patients With Cancer in the National Institutes of Health All of Us Database Using Informatics Approaches

PURPOSE

The rapid growth of biomedical data ecosystems has catalyzed research for oncology and precision medicine. We leverage federal cloud-based precision medicine databases and tools to better understand the current landscape of precision medicine and genomic testing for patients with cancer.

METHODS

Retrospective observational study of genomic testing for patients with cancer in the National Institutes of Health All of Us Research Program, with the cancer cohort defined as having at least two documented or reported cancer diagnoses.

RESULTS

There were 5,678 (1.8%) All of Us participants in the cancer cohort, with a significant difference between cancer status by age category, sex, race, and ethnicity (P < .001 for all). There were 295 (5.2%) patients with cancer who received genomic testing compared with 6,734 (2.2%) of noncancer patients, with 752 genomic tests commonly focused on gene mutations (primarily pharmacogenomics), molecular pathology, or clinical cytogenetic reports.

CONCLUSION

Although not yet ubiquitous, diverse clinical genomic analyses in oncology can set the stage to grow the practice of precision medicine by integrating research patient data repositories, cancer data ecosystems, and biomedical informatics.

Interpretation and management of genetic test results by Canadian family physicians: a multiple choice survey of performance

Family physicians (FPs) will encounter genetic concerns within community practice. To determine how FPs compare to genetic counselors (GCs), a cross-sectional survey was distributed to Canadian FPs and GCs in 2019. The survey assessed risk analysis, counseling, and management of genetic information. FPs performed less well than GCs on each survey question and scenario (p < 0.05). Average overall survey scores for FPs were lower than GCs (62% vs. 93%, p < 0.001). Additional genetic training for FPs may help avoid potential harm.

Delivering genomic medicine in the United Kingdom National Health Service: a systematic review and narrative synthesis

PURPOSE

We sought to assess the readiness of the United Kingdom (UK) National Health Service to implement a Genomic Medicine Service. We conducted a systematic literature review to identify what is known about factors related to the implementation of genomic medicine in routine health care and to draw out the implications for the UK and other settings.

METHODS

Relevant studies were identified in Web of Science and PubMed from their date of inception to April 2018. The review included primary research studies using quantitative, qualitative, or mixed methods, and systematic reviews. A narrative synthesis was conducted.

RESULTS

Fifty-five studies met our inclusion criteria. The majority of studies reviewed were conducted in the United States. We identified four domains: (1) systems, (2) training and workforce needs, (3) professional attitudes and values, and (4) the role of patients and the public.

CONCLUSION

Mainstreaming genomic medicine into routine clinical practice requires actions at each level of the health-care system. Our synthesis emphasized the organizational, social, and cultural implications of reforming practice, highlighting that demonstration of clinical utility and cost-effectiveness, attending to the compatibility of genomic medicine with clinical principles, and involving and engaging patients are key to successful implementation.

A Q-Probes Study Involving Utilization of Free Prostate-Specific Antigen, Factor V Leiden, and Hepatitis A Serology Tests

Context.—

Managing the utilization of laboratory tests is an important quality improvement activity that adds value to health care.

Objective.—

To examine utilization of 3 laboratory tests and identify factors that impact performance.

Design.—

Test utilization performance was evaluated by determining the frequency with which appropriate preconditions for testing were met. This included 30 testing episodes each involving (1) free prostate-specific antigen (PSA) when total PSA was within an appropriate interpretable range, (2) total anti–hepatitis A virus antibody when previous anti–hepatitis A virus antibody results were either negative or not done, and (3) factor V Leiden mutation when a previous result was not already available. Participants also provided information regarding some of their utilization policies and procedures for these 3 tests.

Results.—

The overall frequency with which testing criteria were met was 20.6% (163 of 790), 91.5% (649 of 709), and 95.2% (799 of 839) for free PSA, anti–hepatitis A virus antibody, and factor V Leiden, respectively. Utilization review was infrequent and done by 20.7% (6 of 29) of participants for factor V Leiden, 3.6% (1 of 28) for anti–hepatitis A virus antibody, and 3.6% (1 of 28) for free PSA. No practice or demographic characteristics were significantly associated with utilization performance for any test.

Conclusions.—

Utilization review was infrequent for the 3 tests examined. Variable amounts of unnecessary testing were observed for all tests, most frequently for free PSA, for which reporting results carried the added risk of diagnostic error from misinterpretation of results.

Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record

OBJECTIVE

Clinical informatics researchers depend on the availability of high-quality data from the electronic health record (EHR) to design and implement new methods and systems for clinical practice and research. However, these data are frequently unavailable or present in a format that requires substantial revision. This article reports the results of a review of informatics literature published from 2010 to 2016 that addresses these issues by identifying categories of data content that might be included or revised in the EHR.

MATERIALS AND METHODS

We used an iterative review process on 1,215 biomedical informatics research articles. We placed them into generic categories, reviewed and refined the categories, and then assigned additional articles, for a total of three iterations.

RESULTS

Our process identified eight categories of data content issues: Adverse Events, Clinician Cognitive Processes, Data Standards Creation and Data Communication, Genomics, Medication List Data Capture, Patient Preferences, Patient-reported Data, and Phenotyping.

DISCUSSION

These categories summarize discussions in biomedical informatics literature that concern data content issues restricting clinical informatics research. These barriers to research result from data that are either absent from the EHR or are inadequate (e.g., in narrative text form) for the downstream applications of the data. In light of these categories, we discuss changes to EHR data storage that should be considered in the redesign of EHRs, to promote continued innovation in clinical informatics.

CONCLUSION

Based on published literature of clinical informaticians' reuse of EHR data, we characterize eight types of data content that, if included in the next generation of EHRs, would find immediate application in advanced informatics tools and techniques.

Assessing the readiness of precision medicine interoperabilty: An exploratory study of the National Institutes of Health genetic testing registry

BACKGROUND

  Precision medicine involves three major innovations currently taking place in healthcare:  electronic health records, genomics, and big data.  A major challenge for healthcare providers, however, is understanding the readiness for practical application of initiatives like precision medicine.

OBJECTIVE

  To better understand the current state and challenges of precision medicine interoperability using a national genetic testing registry as a starting point, placed in the context of established interoperability formats.

METHODS

  We performed an exploratory analysis of the National Institutes of Health Genetic Testing Registry.  Relevant standards included Health Level Seven International Version 3 Implementation Guide for Family History, the Human Genome Organization Gene Nomenclature Committee (HGNC) database, and Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT).  We analyzed the distribution of genetic testing laboratories, genetic test characteristics, and standardized genome/clinical code mappings, stratified by laboratory setting.

RESULTS

There were a total of 25472 genetic tests from 240 laboratories testing for approximately 3632 distinct genes.  Most tests focused on diagnosis, mutation confirmation, and/or risk assessment of germline mutations that could be passed to offspring.  Genes were successfully mapped to all HGNC identifiers, but less than half of tests mapped to SNOMED CT codes, highlighting significant gaps when linking genetic tests to standardized clinical codes that explain the medical motivations behind test ordering.  Conclusion:  While precision medicine could potentially transform healthcare, successful practical and clinical application will first require the comprehensive and responsible adoption of interoperable standards, terminologies, and formats across all aspects of the precision medicine pipeline.

Sex-specific patterns and differences in dementia and Alzheimer's disease using informatics approaches

The National Institutes of Health Office of Research on Women's Health recently highlighted the critical need for explicitly addressing sex differences in biomedical research, including Alzheimer's disease and dementia. The purpose of our study was to perform a sex-stratified analysis of cognitive impairment using diverse medical, clinical, and genetic factors of unprecedented scale and scope by applying informatics approaches to three large Alzheimer's databases. Analyses suggested females were 1.5 times more likely than males to have a documented diagnosis of probable Alzheimer's disease, and several other factors fell along sex-specific lines and were possibly associated with severity of cognitive impairment.

Implementing and Improving Automated Electronic Tumor Molecular Profiling

Oncology practice increasingly requires the use of molecular profiling of tumors to inform the use of targeted therapeutics. However, many oncologists use third-party laboratories to perform tumor genomic testing, and these laboratories may not have electronic interfaces with the provider's electronic medical record (EMR) system. The resultant reporting mechanisms, such as plain-paper faxing, can reduce report fidelity, slow down reporting procedures for a physician's practice, and make reports less accessible. Vanderbilt University Medical Center and its genomic laboratory testing partner have collaborated to create an automated electronic reporting system that incorporates genetic testing results directly into the clinical EMR. This system was iteratively tested, and causes of failure were discovered and addressed. Most errors were attributable to data entry or typographical errors that made reports unable to be linked to the correct patient in the EMR. By providing direct feedback to providers, we were able to significantly decrease the rate of transmission errors (from 6.29% to 3.84%; P < .001). The results and lessons of 1 year of using the system and transmitting 832 tumor genomic testing reports are reported.

Closing the gap between knowledge and clinical application: challenges for genomic translation

Despite early predictions and rapid progress in research, the introduction of personal genomics into clinical practice has been slow. Several factors contribute to this translational gap between knowledge and clinical application. The evidence available to support genetic test use is often limited, and implementation of new testing programs can be challenging. In addition, the heterogeneity of genomic risk information points to the need for strategies to select and deliver the information most appropriate for particular clinical needs. Accomplishing these tasks also requires recognition that some expectations for personal genomics are unrealistic, notably expectations concerning the clinical utility of genomic risk assessment for common complex diseases. Efforts are needed to improve the body of evidence addressing clinical outcomes for genomics, apply implementation science to personal genomics, and develop realistic goals for genomic risk assessment. In addition, translational research should emphasize the broader benefits of genomic knowledge, including applications of genomic research that provide clinical benefit outside the context of personal genomic risk.

Supporting interoperability of genetic data with LOINC

Electronic reporting of genetic testing results is increasing, but they are often represented in diverse formats and naming conventions. Logical Observation Identifiers Names and Codes (LOINC) is a vocabulary standard that provides universal identifiers for laboratory tests and clinical observations. In genetics, LOINC provides codes to improve interoperability in the midst of reporting style transition, including codes for cytogenetic or mutation analysis tests, specific chromosomal alteration or mutation testing, and fully structured discrete genetic test reporting. LOINC terms follow the recommendations and nomenclature of other standards such as the Human Genome Organization Gene Nomenclature Committee's terminology for gene names. In addition to the narrative text they report now, we recommend that laboratories always report as discrete variables chromosome analysis results, genetic variation(s) found, and genetic variation(s) tested for. By adopting and implementing data standards like LOINC, information systems can help care providers and researchers unlock the potential of genetic information for delivering more personalized care.

How the electronic health record will change the future of health care

Genetic testing is expected to play a critical role in patient care in the near future. Advances in genomic research have the potential to impact medicine in very tangible and direct ways, from carrier screening to disease diagnosis and prognosis to targeted treatments and personalized medicine. However, numerous barriers to widespread adoption of genetic testing continue to exist, and health information technology will be a critical means of addressing these challenges. Electronic health records (EHRs) are a digital replacement for the traditional paper-based patient chart designed to improve the quality of patient care. EHRs have become increasingly essential to managing the wealth of existing clinical information that now includes genetic information extracted from the patient genome. The EHR is capable of changing health care in the future by transforming the way physicians use genomic information in the practice of medicine.