Citations

AbstractBackground Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM).Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms.Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility.Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.

Abstract Objective Clinicians’ ability to use and interpret genetic information depends upon how those data are displayed in electronic health records (EHRs). There is a critical need to develop systems to effectively display genetic information in EHRs and augment clinical decision support (CDS). Materials and Methods The National Institutes of Health (NIH)-sponsored Clinical Sequencing Exploratory Research and Electronic Medical Records & Genomics EHR Working Groups conducted a multiphase, iterative process involving working group discussions and 2 surveys in order to determine how genetic and genomic information are currently displayed in EHRs, envision optimal uses for different types of genetic or genomic information, and prioritize areas for EHR improvement. Results There is substantial heterogeneity in how genetic information enters and is documented in EHR systems. Most institutions indicated that genetic information was displayed in multiple locations in their EHRs. Among surveyed institutions, genetic information enters the EHR through multiple laboratory sources and through clinician notes. For laboratory-based data, the source laboratory was the main determinant of the location of genetic information in the EHR. The highest priority recommendation was to address the need to implement CDS mechanisms and content for decision support for medically actionable genetic information. Conclusion Heterogeneity of genetic information flow and importance of source laboratory, rather than clinical content, as a determinant of information representation are major barriers to using genetic information optimally in patient care. Greater effort to develop interoperable systems to receive and consistently display genetic and/or genomic information and alert clinicians to genomic-dependent improvements to clinical care is recommended.

Altruism is a well-established reason underlying research participation. Less is known about altruism in adolescent-parent decision-making about clinical trials enrolling healthy adolescents. This qualitative investigation focused on identifying spontaneous statements of altruism within adolescent-parent (dyadic) discussions of participation in a hypothetical phase I clinical trial related to adolescent sexual health. Content analysis revealed several response patterns to each other’s altruistic reasoning. Across 70 adolescent-parent dyads in which adolescents were 14 to 17 years of age and 91% of their parents were mothers, a majority (61%) of dyadic discussions included a statement reflecting altruism. Parents responded to adolescents’ statements of altruism more frequently than adolescents responded to parents’ statements. Responses included: expresses concern, reiterates altruistic reasoning, agrees with altruistic reasoning, and adds to/expands altruistic reasoning. Since an altruistic perspective was often balanced with concerns about risk or study procedures, researchers cannot assume that altruism will directly lead to study participation. Optimizing the informed consent process for early phase clinical trials involving healthy adolescents may include supporting parents to have conversations with their adolescents which will enhance their capacity to consider all aspects of trial participation.

Introduction Primary spinal osteosarcomas are rare and aggressive neoplasms with poor outcomes. Enneking appropriate, en bloc resection is recommended for appendicular osteosarcomas. Obtaining even marginal margins is technically demanding in the spine, resulting in significant morbidity and possible functional sacrifice. The aim of this study was to identify prognostic variables on local recurrence and mortality, in surgically treated patients diagnosed with a primary osteosarcoma of the spine. Methods A multicenter ambispective database of surgically treated patients with primary spine osteosarcomas was developed by the AOSpine knowledge forum tumor. Patient demographic, diagnosis, treatment, perioperative morbidity, local recurrence, and cross-sectional survival data were collected. Tumors were classified according to Enneking principles and analyzed in the following two cohorts: Enneking appropriate (EA) and Enneking inappropriate (EI). EA was defined by the final pathology margin matching the Enneking recommended surgical margin and EI by not matching. Prognostic variables including age, previous spine tumor operation, biopsy type, spine level, tumor size, and chemotherapy timing were analyzed in reference to local recurrence and survival. Results Between 1987 and 2012, 57 patients (31 females and 26 males) underwent surgical treatment for a primary spinal osteosarcoma at a mean age of 36 ± 16 years. Patients were followed for a mean period of 3.4 ± 3.5 years (range, 0.5 days–14.3 years). Median survival for the entire cohort was 6.7 years postoperative. Overall, 24 (42%) patients died and 17 (30%) patients suffered a local recurrence, 10 (59%) of which died. Overall, 28 (52%) patients underwent EA resection while 26 (48%) patients were treated by EI resection. Median survival for patients with EA was 6.8 years postoperative, whereas median survival for EI patients was 3.7 years postoperatively ( p = 0.062). EI patients were at a higher risk of local recurrence than EA patients ( p = 0.002). Patient age, previous spine tumor operation, tumor size, spine level, and chemotherapy timing did not significantly influence recurrence and survival. Conclusion Osteosarcoma of the spine presents a significant challenge and most patients die from their disease in spite of aggressive surgery. There is a significant decrease in recurrence with en bloc resection when compared with intralesional resection.