Development and validation of an electronic health records-based opioid use disorder algorithm by expert clinical adjudication among patients with prescribed opioids.

BACKGROUND: In the US, over 200 lives are lost from opioid overdoses each day. Accurate and prompt diagnosis of opioid use disorders (OUD) may help prevent overdose deaths. However, international classification of disease (ICD) codes for OUD are known to underestimate prevalence, and their specificity and sensitivity are unknown. We developed and validated algorithms to identify OUD in electronic health records (EHR) and examined the validity of OUD ICD codes. METHODS: Through four iterations, we developed EHR-based OUD identification algorithms among patients who were prescribed opioids from 2014 to 2017. The algorithms and OUD ICD codes were validated against 169 independent "gold standard" EHR chart reviews conducted by an expert adjudication panel across four healthcare systems. After using 2014-2020 EHR for validating iteration 1, the experts were advised to use 2014-2017 EHR thereafter. RESULTS: Of the 169 EHR charts, 81 (48%) were reviewed by more than one expert and exhibited 85% expert agreement. The experts identified 54 OUD cases. The experts endorsed all 11 OUD criteria from the Diagnostic and Statistical Manual of Mental Disorders-5, including craving (72%), tolerance (65%), withdrawal (56%), and recurrent use in physically hazardous conditions (50%). The OUD ICD codes had 10% sensitivity and 99% specificity, underscoring large underestimation. In comparison our algorithm identified OUD with 23% sensitivity and 98% specificity. CONCLUSIONS AND RELEVANCE: This is the first study to estimate the validity of OUD ICD codes and develop validated EHR-based OUD identification algorithms. This work will inform future research on early intervention and prevention of OUD.

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.

Fast Healthcare Interoperability Resources (FHIR) as a Meta Model to Integrate Common Data Models: Development of a Tool and Quantitative Validation Study.

BACKGROUND: In a multisite clinical research collaboration, institutions may or may not use the same common data model (CDM) to store clinical data. To overcome this challenge, we proposed to use Health Level 7's Fast Healthcare Interoperability Resources (FHIR) as a meta-CDM-a single standard to represent clinical data. OBJECTIVE: In this study, we aimed to create an open-source application termed the Clinical Asset Mapping Program for FHIR (CAMP FHIR) to efficiently transform clinical data to FHIR for supporting source-agnostic CDM-to-FHIR mapping. METHODS: Mapping with CAMP FHIR involves (1) mapping each source variable to its corresponding FHIR element and (2) mapping each item in the source data's value sets to the corresponding FHIR value set item for variables with strict value sets. To date, CAMP FHIR has been used to transform 108 variables from the Informatics for Integrating Biology & the Bedside (i2b2) and Patient-Centered Outcomes Research Network data models to fields across 7 FHIR resources. It is designed to allow input from any source data model and will support additional FHIR resources in the future. RESULTS: We have used CAMP FHIR to transform data on approximately 23,000 patients with asthma from our institution's i2b2 database. Data quality and integrity were validated against the origin point of the data, our enterprise clinical data warehouse. CONCLUSIONS: We believe that CAMP FHIR can serve as an alternative to implementing new CDMs on a project-by-project basis. Moreover, the use of FHIR as a CDM could support rare data sharing opportunities, such as collaborations between academic medical centers and community hospitals. We anticipate adoption and use of CAMP FHIR to foster sharing of clinical data across institutions for downstream applications in translational research.

Persistently Elevated PTH After Parathyroidectomy at One Year: Experience in a Tertiary Referral Center.

CONTEXT/OBJECTIVE: Increased PTH after successful parathyroid surgery represents a clinical conundrum. We aimed to determine the prevalence of persistently elevated PTH (PePTH) postsurgery, along with predisposing factors. DESIGN: and Setting: Patients ≥ age 18 with parathyroidectomy performed at University of North Carolina Hospitals for primary hyperparathyroidism (PHPT) over a 12-year period were identified from the Carolina Data Warehouse. Clinical and demographic characteristics were collected, transformed, and analyzed. RESULTS: Five hundred seventy patients met initial criteria for PHPT, and of those 407 had postoperative values. One hundred forty-four had laboratory results within 3 to 18 months post operatively. There was no clinical difference between those with and without long-term laboratory follow-up. Presurgery, patients had average calcium of 11 mg/dL and PTH 125.4 pg/mL. Ninety-seven percent of patients had normalized calcium after surgery, but 30% had PePTH, which can be predicted at 3 months. Patients with PePTH (persistent elevation of PTH) after surgery did not differ from those with normalized PTH in terms of sex, age, body mass index, or excised gland weight; presurgery 25-vitamin D was slightly lower, but not abnormal (26 ± 15 vs 36 ± 11). The presurgical PTH was significantly higher (P < 0.001) in those with PePTH (156.5 pg/mL compared with presurgical level of 102.5 in those whose PTH normalized). CONCLUSIONS: Nearly one-third of PHPT patients have elevated PTH levels postsurgery in a tertiary hospital setting. At presentation, patients with PePTH tend to have higher PTH relative to calcium levels. Whether PePTH after surgical treatment of PHPT has pathological consequences is unknown.

Ovicidal Efficacy of Abametapir Against Eggs of Human Head and Body Lice (Anoplura: Pediculidae).

Studies were undertaken to determine the ovicidal efficacy of 5,5'-dimethyl-2,2'-bipyridyl (abametapir) against eggs of both human head and body lice. Head lice eggs of different ages (0-2, 3-5, and 6-8-d-old eggs) were exposed to varying concentrations of abametapir in isopropanol and concentration-dependent response relationships established based on egg hatch. One hundred percent of all abametapir-treated eggs failed to hatch at the 0.74 and 0.55% concentrations, whereas 100% of 6-8-d-old head louse eggs failed to hatch only at the 0.74% concentration. The LC50 value for abametapir varied, depending on the age of the head lice eggs, from ∼0.10% recorded for 0-2-d-old eggs and increasing to ∼0.15% for 6-8-d-old eggs. Abametapir was also evaluated once formulated into a lotion referred to as Xeglyze (0.74% abametapir) and serial dilutions made. Ovicidal efficacies were determined against head lice eggs 0-8-d-old. Results indicated 100% ovicidal activity at the 0.74, 0.55, 0.37, and 0.18% concentrations. Additional studies undertaken using body lice eggs also demonstrated that abametapir was 100% ovicidal against eggs of all ages when evaluated at a concentration of 0.37 and 0.55%. Given that ovicidal activity is a critical component of any effective treatment regime for louse control, the data presented in this study clearly demonstrate the ability of abametapir to inhibit hatching of both head and body louse eggs as assessed in vitro.

Harnessing person-generated health data to accelerate patient-centered outcomes research: the Crohn's and Colitis Foundation of America PCORnet Patient Powered Research Network (CCFA Partners).

The Crohn's and Colitis Foundation of America Partners Patient-Powered Research Network (PPRN) seeks to advance and accelerate comparative effectiveness and translational research in inflammatory bowel diseases (IBDs). Our IBD-focused PCORnet PPRN has been designed to overcome the major obstacles that have limited patient-centered outcomes research in IBD by providing the technical infrastructure, patient governance, and patient-driven functionality needed to: 1) identify, prioritize, and undertake a patient-centered research agenda through sharing person-generated health data; 2) develop and test patient and provider-focused tools that utilize individual patient data to improve health behaviors and inform health care decisions and, ultimately, outcomes; and 3) rapidly disseminate new knowledge to patients, enabling them to improve their health. The Crohn's and Colitis Foundation of America Partners PPRN has fostered the development of a community of citizen scientists in IBD; created a portal that will recruit, retain, and engage members and encourage partnerships with external scientists; and produced an efficient infrastructure for identifying, screening, and contacting network members for participation in research.