Does radiofrequency ablation procedural data improve the accuracy of identifying atrial fibrillation recurrence?

Radiofrequency ablation (RFA) using the CARTO 3D mapping system is a common approach for pulmonary vein isolation to treat atrial fibrillation (AF). Linkage between CARTO procedural data and patients' electronical health records (EHR) provides an opportunity to identify the ablation-related parameters that would predict AF recurrence. The objective of this study is to assess the incremental accuracy of RFA procedural data to predict post-ablation AF recurrence using machine learning model. Procedural data generated during RFA procedure were downloaded from CARTONET and linked to deidentified Mercy Health EHR data. Data were divided into train (70%) and test (30%) data for model development and validation. Automate machine learning (AutoML) was used to predict 1 year AF recurrence, defined as a composite of repeat ablation, electrical cardioversion, and AF hospitalization. At first, AutoML model only included Patients' demographic and clinical characteristics. Second, an AutoML model with procedural variables and demographical/clinical variables was developed. Area under receiver operating characteristic curve (AUROC) and net reclassification improvement (NRI) were used to compare model performances using test data. Among 306 patients, 67 (21.9%) patients experienced 1-year AF recurrence. AUROC increased from 0.66 to 0.78 after adding procedural data in the AutoML model based on test data. For patients with AF recurrence, NRI was 32% for model with procedural data. Nine of 10 important predictive features were CARTO procedural data. From CARTO procedural data, patients with lower contact force in right inferior site, long ablation duration, and low number of left inferior and right roof lesions had a higher risk of AF recurrence. Patients with persistent AF were more likely to have AF recurrence. The machine learning model with procedural data better predicted 1-year AF recurrence than the model without procedural data. The model could be used for identification of patients with high risk of AF recurrence post ablation.

Insurer costs of COVID-19 by disease severity and duration.

OBJECTIVES: To analyze US commercial insurance payments associated with COVID-19 as a function of severity and duration of disease. STUDY DESIGN: Retrospective database analysis. METHODS: Patients with COVID-19 between April 1, 2020, and June 30, 2021, in the Merative MarketScan Commercial database were identified and stratified as having asymptomatic, mild, moderate (with and without lower respiratory disease), or severe/critical (S/C) disease based on the severity of the acute COVID-19 infection. Duration of disease (DOD) was estimated for all patients. Patients with DOD longer than 12 weeks were defined as having post-COVID-19 condition (PCC). Outcomes were all-cause payments (ACP) and disease-specific payments (DSP) for the entire DOD. Variables included demographic and comorbidities at the time of acute disease. Adjusted payments by disease severity were estimated using generalized linear models (γ distribution with log link). RESULTS: A total of 738,339 patients were included (374,401 asymptomatic, 156,220 mild, 180,213 moderate, and 27,505 S/C cases). DSP increased from $217 (95% CI, $214-221) for asymptomatic cases to $2744 (95% CI, $2678-$2811) for moderate cases with lower respiratory disease and $28,250 (95% CI, $26,963-$29,538) for S/C cases. ACP increased from $505 (95% CI, $497-$512) for asymptomatic cases to $46,538 (95% CI, $44,096-$48,979) for S/C cases. The DSP and ACP further increased by $50,736 (95% CI, $45,337-$56,136) and $94,839 (95% CI, $88,029-$101,649), respectively, in S/C cases with PCC vs a DOD of fewer than 4 weeks. CONCLUSIONS: COVID-19 payments for S/C cases were more than 10-fold greater than those of moderate cases and further increased by nearly $95,000 in S/C cases with PCC vs a DOD of fewer than 4 weeks.

Health care costs of COVID-19 vs influenza and pneumonia.

OBJECTIVES: To estimate payments for the treatment of COVID-19 compared with that of influenza or viral pneumonia (IP), from the perspective of the US payer. STUDY DESIGN: Retrospective cohort analysis. METHODS: Patients with COVID-19 during the period from October 1, 2020, to February 1, 2021, or IP during the period from October 1, 2018, to February 1, 2019, in the IBM MarketScan databases were identified. The index was defined as the date of the first COVID-19 or IP diagnosis. Patients with COVID-19 were stratified by severity. Variables for all patients included demographics and comorbidities at the time of index and duration of disease. IP and COVID-19 cohorts were matched using propensity scores, and inflation-adjusted all-cause payments (ACP), and disease-specific payments (DSP) for IP vs COVID-19 were estimated using generalized linear models. RESULTS: Matched cohorts included 6332 Medicare (female, 58.5%; mean [SD] age, 75.3 [7.6] years), and 397,532 commercially insured patients (female, 57.6%; mean [SD] age, 34.7 [16.7] years). ACP and DSP were significantly higher in the COVID-19 cohort vs IP cohort. Payments for severe/critical COVID-19 were significantly greater than those for IP, with adjusted marginal incremental DSP and ACP of $24,852 (95% CI, $21,573-$28,132) and $50,325 (95% CI, $43,932-$56,718), respectively. IP was significantly less expensive than moderate COVID-19 for commercial payers but not Medicare. IP was more expensive than mild COVID-19 for all payers. CONCLUSIONS: Payments associated with severe/critical COVID-19 significantly exceeded those associated with IP. For Medicare, IP was more expensive than mild or moderate COVID-19. For commercial payers, IP was less expensive than moderate COVID-19 but more expensive than mild COVID-19.

Racial and Health Insurance Differences in Patient Outcomes After Surgical Treatment for Cauda Equina Syndrome: A United States Retrospective Hospital Claims Database Analysis.

STUDY DESIGN: Retrospective database evaluation. OBJECTIVES: To study the association between race, health care insurance, mortality, postoperative visits, and reoperation within a hospital setting in patients with cauda equina syndrome (CES) undergoing surgical intervention. SUMMARY OF BACKGROUND DATA: CES can lead to permanent neurological deficits if the diagnosis is missed or delayed. Evidence of racial or insurance disparities in CES is sparse. MATERIALS AND METHODS: Patients with CES undergoing surgery from 2000 to 2021 were identified from the Premier Health care Database. Six-month postoperative visits and 12-month reoperations within the hospital were compared by race ( i.e ., White, Black, or Other [Asian, Hispanic, or other]) and insurance ( i.e. , Commercial, Medicaid, Medicare, or Other) using Cox proportional hazard regressions; covariates were used in the regression models to control for confounding. Likelihood ratio tests were used to compare model fit. RESULTS: Among 25,024 patients, most were White (76.3%), followed by Other race (15.4% [ 8.8% Asian, 7.3% Hispanic, and 83.9% other]) and Black (8.3%). Models with race and insurance combined provided the best fit for estimating the risk of visits to any setting of care and reoperations. White Medicaid patients had the strongest association with a higher risk of 6-month visits to any setting of care versus White patients with commercial insurance (HR: 1.36 (1.26,1.47)). Being Black with Medicare had a strong association with a higher risk of 12-month reoperations versus White commercial patients (HR: 1.43 (1.10,1.85)). Having Medicaid versus Commercial insurance was strongly associated with a higher risk of complication-related (HR: 1.36 (1.21, 1.52)) and ER visits (HR: 2.26 (2.02,2.51)). Medicaid had a significantly higher risk of mortality compared with Commercial patients (HR: 3.19 (1.41,7.20)). CONCLUSIONS: Visits to any setting of care, complication-related, ER visits, reoperation, or mortality within the hospital setting after CES surgical treatment varied by race and insurance. Insurance type had a stronger association with the outcomes than race. LEVEL OF EVIDENCE: Level-III.

Impact of a digital surgical workflow including Digital Device Briefing Tool on morbidity and mortality in a patient population undergoing primary stapled colorectal anastomosis for benign or malignant colorectal disease: protocol for a multicentre prospective cohort study.

INTRODUCTION: With growing emphasis on surgical safety, it appears fundamental to assess the safety of colorectal resection involving primary stapled anastomosis. Surgical stapling devices can considerably foster patient safety in colorectal surgery, but their misuse or malfunction encompass a unique risk of postoperative complications. The Digital Device Briefing Tool (DDBT) is a digital cognitive aid developed to enhance safe use of the Ethicon circular stapling device during colorectal resection. The purpose of this study is to evaluate how a digital operative workflow, including DDBT, compared with routine surgical care, affects morbidity and mortality in patients undergoing left-sided colorectal resection with primary stapled colorectal anastomosis for colorectal cancer or benign disease. METHODS AND ANALYSIS: A multicentre, prospective cohort study will be conducted at five certified academic colorectal centres in Germany. It compares a non-digital with a Johnson & Johnson digital solution (Surgical Process Institute Deutschland (SPI))-guided operative workflow in patients undergoing left hemicolectomy, sigmoidectomy, anterior rectal resection and Hartmann reversal procedure. The sample size is set at 528 cases in total, divided into 3 groups (a non-digital and two SPI-guided workflow cohorts, with and without DDBT) in a ratio of 1:1:1, with 176 patients each. The primary endpoint is a composite outcome comprising the overall rate of surgical complications, including death, during hospitalisation and within the first 30 days after colorectal resection. Secondary endpoints include operating time, length of hospital stay and 30-day hospital readmission rate. ETHICS AND DISSEMINATION: This study will be performed in line with the Declaration of Helsinki. The ethics committee of the Charité-University Medicine Berlin, Germany, approved the study (No: 22-0277-EA2/060/22). Study Investigators will obtain written informed consent from each patient before a patient may participate in this study. The study results will be submitted to an international peer-reviewed journal. TRIAL REGISTRATION NUMBER: DRKS00029682.

Using real-world data from health systems to evaluate the safety and effectiveness of a catheter to treat ischemic ventricular tachycardia.

BACKGROUND: The ThermoCool STSF catheter is used for ablation of ischemic ventricular tachycardia (VT) in routine clinical practice, although outcomes have not been studied and the catheter does not have Food and Drug Administration (FDA) approval for this indication. We used real-world health system data to evaluate its safety and effectiveness for this indication. METHODS: Among patients undergoing ischemic VT ablation with the ThermoCool STSF catheter pooled across two health systems (Mercy Health and Mayo Clinic), the primary safety composite outcome of death, thromboembolic events, and procedural complications within 7 days was compared to a performance goal of 15%, which is twice the expected proportion of the primary composite safety outcome based on prior studies. The exploratory effectiveness outcome of rehospitalization for VT or heart failure or repeat VT ablation at up to 1 year was averaged across health systems among patients treated with the ThermoCool STSF vs. ST catheters. RESULTS: Seventy total patients received ablation for ischemic VT using the ThermoCool STSF catheter. The primary safety composite outcome occurred in 3/70 (4.3%; 90% CI, 1.2-10.7%) patients, meeting the pre-specified performance goal, p = 0.0045. At 1 year, the effectiveness outcome risk difference (STSF-ST) at Mercy was - 0.4% (90% CI: - 25.2%, 24.3%) and at Mayo Clinic was 12.6% (90% CI: - 13.0%, 38.4%); the average risk difference across both institutions was 5.8% (90% CI: - 12.0, 23.7). CONCLUSIONS: The ThermoCool STSF catheter was safe and appeared effective for ischemic VT ablation, supporting continued use of the catheter and informing possible FDA label expansion. Health system data hold promise for real-world safety and effectiveness evaluation of cardiovascular devices.

Integrating real-world data to assess cardiac ablation device outcomes in a multicenter study using the OMOP common data model for regulatory decisions: implementation and evaluation.

The objective of this study is to describe application of the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) to support medical device real-world evaluation in a National Evaluation System for health Technology Coordinating Center (NESTcc) Test-Case involving 2 healthcare systems, Mercy Health and Mayo Clinic. CDM implementation was coordinated across 2 healthcare systems with multiple hospitals to aggregate both medical device data from supply chain databases and patient outcomes and covariates from electronic health record data. Several data quality assurance (QA) analyses were implemented on the OMOP CDM to validate the data extraction, transformation, and load (ETL) process. OMOP CDM-based data of relevant patient encounters were successfully established to support studies for FDA regulatory submissions. QA analyses verified that the data transformation was robust between data sources and OMOP CDM. Our efforts provided useful insights in real-world data integration using OMOP CDM for medical device evaluation coordinated across multiple healthcare systems.

Comparison of Clinical Outcomes of Gripping Surface Technology Staple Reloads versus Standard Staple Reloads Used with Manual Linear Surgical Staplers.

Purpose: Linear surgical staplers reduce rates of surgical adverse events (bleeding, leaks, infections) compared to manual sutures thereby reducing patient risks, surgeon workflow disruption, and healthcare costs. However, further improvements are needed. Ethicon Gripping Surface Technology (GST) reloads, tested and approved by regulatory authorities in combination with powered staplers, may reduce surgical risks through improved tissue grip. While manual staplers are used in some regions due to affordability, clinical data on GST reloads used with manual staplers are unavailable. This study compared surgical adverse event rates of manual staplers with GST vs standard reloads. These data may be used for label changes in China and Latin America. Patients and Methods: Patients undergoing general or thoracic surgery between October 1, 2015 and August 31, 2021 using ECHELON FLEX™ manual staplers with GST or standard reloads were identified from the Premier Healthcare Database. GST reloads were compared to standard reloads for non-inferiority in bleeding and anastomotic leak for general surgery. Secondary outcomes included sepsis for general surgery, and bleeding and prolonged air leak for thoracic surgery. Covariate balancing was performed using stable balancing weights. Results: The general and thoracic surgery cohorts contained 4571 (GST: 2780; standard: 1791) and 814 (GST: 514; standard: 300) patients, respectively. GST reloads were non-inferior to standard reloads for bleeding and anastomotic leak (adjusted cumulative incidence ratio: 1.02 [90% CI: 0.71, 1.45] and 1.03 [90% CI: 0.72, 1.46], respectively) for general surgery. Compared with standard reloads, GST reloads had a similar incidence of sepsis (2.2% vs 2.1%) for general surgery and lower incidences of bleeding (9.5% vs 16.0%) and prolonged air leak (12.6% vs 14.0%,) for thoracic surgery. Conclusion: GST reloads, compared to standard reloads, used with ECHELON FLEX™ manual staplers had comparable perioperative bleeding and anastomotic leak for general surgery, and lower incidences of safety events for thoracic surgery.

Safety and Effectiveness of a Catheter With Contact Force and 6-Hole Irrigation for Ablation of Persistent Atrial Fibrillation in Routine Clinical Practice.

Importance: The ThermoCool SmartTouch catheter (ablation catheter with contact force and 6-hole irrigation [CF-I6]) is approved by the US Food and Drug Administration (FDA) for paroxysmal atrial fibrillation (AF) ablation and used in routine clinical practice for persistent AF ablation, although clinical outcomes for this indication are unknown. There is a need to understand whether data from routine clinical practice can be used to conduct regulatory-grade evaluations and support label expansions. Objective: To use health system data to compare the safety and effectiveness of the CF-I6 catheter for persistent AF ablation with the ThermoCool SmartTouch SurroundFlow catheter (ablation catheter with contact force and 56-hole irrigation [CF-I56]), which is approved by the FDA for this indication. Design, Setting, and Participants: This retrospective, comparative-effectiveness cohort study included patients undergoing catheter ablation for persistent AF at Mercy Health or Mayo Clinic from January 1, 2014, to April 30, 2021, with up to a 1-year follow-up using electronic health record data. Exposures: Use of the CF-I6 or CF-I56 catheter. Main Outcomes and Measures: The primary safety outcome was a composite of death, thromboembolic events, and procedural complications within 7 to 90 days. The exploratory effectiveness outcome was a composite of AF-related hospitalization events after a 90-day blanking period. Propensity score weighting was used to balance baseline covariates. Risk differences were estimated between catheter groups and averaged across the 2 health care systems, testing for noninferiority of the CF-I6 vs the CF-I56 catheter with respect to the safety outcome using 2-sided 90% CIs. Results: Overall, 1450 patients (1034 [71.3%] male; 1397 [96.3%] White) underwent catheter ablation for persistent AF, including 949 at Mercy Health (186 CF-I6 and 763 CF-I56; mean [SD] age, 64.9 [9.2] years) and 501 at Mayo Clinic (337 CF-I6 and 164 CF-I56; mean [SD] age, 63.7 [9.5] years). A total of 798 (55.0%) had been treated with class I or III antiarrhythmic drugs before ablation. The safety outcome (CF-I6 - CF-I56) was similar at both Mercy Health (1.3%; 90% CI, -2.1% to 4.6%) and Mayo Clinic (-3.8%; 90% CI, -11.4% to 3.7%); the mean difference was noninferior, with a mean of 0.5% (90% CI, -2.6% to 3.5%; P < .001). The effectiveness was similar at 12 months between the 2 catheter groups (mean risk difference, -1.8%; 90% CI, -7.3% to 3.7%). Conclusions and Relevance: In this cohort study, the CF-I6 catheter met the prespecified noninferiority safety criterion for persistent AF ablation compared with the CF-I56 catheter, and effectiveness was similar. This study demonstrates the ability of electronic health care system data to enable safety and effectiveness evaluations of medical devices.

Site-specific cancer risk following cobalt exposure via orthopedic implants or in occupational settings: A systematic review and meta-analysis.

In 2020, the European Commission up-classified metal cobalt as Class 1B Carcinogen (presumed to have carcinogenic potential) based primarily on data from rodent inhalation carcinogenicity studies. This up-classification requires an assessment under the Medical Device Regulations of cobalt cancer risk from medical devices. We performed a systematic review and meta-analysis to evaluate site-specific cancer risks with cobalt exposure from either total joint replacement (TJR) or occupational exposure (OC). Results were stratified by exposure type (OC or TJR), exposure level (metal-on-metal (MoM) or non-MoM), follow-up duration (latency period: <5, 5-10 or >10 years), and cancer incidence or mortality (detection bias assessment). From 30 studies (653,104 subjects, average 14.5 years follow-up), the association between TJR/OC and cancer risk was null for 22 of 27 cancer sites, negative for 3 sites, and positive for prostate cancer and myeloma. Significant heterogeneity and large estimate ranges were observed for many cancer sites. No significant increase in estimates was observed by exposure level or follow-up duration. The current evidence, including weak associations, heterogeneity across studies and no increased association with exposure level or follow-up duration, is insufficient to conclude that there exists an increased risk for people exposed to cobalt in TJR/OC of developing site-specific cancers.

Challenges of evaluating and modelling vaccination in emerging infectious diseases.

Outbreaks of emerging pathogens pose unique methodological and practical challenges for the design, implementation, and evaluation of vaccine efficacy trials. Lessons learned from COVID-19 highlight the need for innovative and flexible study design and application to quickly identify promising candidate vaccines. Trial design strategies should be tailored to the dynamics of the specific pathogen, location of the outbreak, and vaccine prototypes, within the regional socioeconomic constraints. Mathematical and statistical models can assist investigators in designing infectious disease clinical trials. We introduce key challenges for planning, evaluating, and modelling vaccine efficacy trials for emerging pathogens.

An integrated benefit-risk assessment of cobalt-containing alloys used in medical devices: Implications for regulatory requirements in the European Union.

In 2017, the European Union (EU) Committee for Risk Assessment (RAC) recommended the classification of metallic cobalt (Co) as Category 1B with respect to its carcinogenic and reproductive hazard potential and Category 2 for mutagenicity but did not evaluate the relevance of these classifications for patients exposed to Co-containing alloys (CoCA) used in medical devices. CoCA are inherently different materials from Co metal from a toxicological perspective and thus require a separate assessment. CoCA are biocompatible materials with a unique combination of properties including strength, durability, and a long history of safe use that make them uniquely suited for use in a wide-range of medical devices. Assessments were performed on relevant preclinical and clinical carcinogenicity and reproductive toxicity data for Co and CoCA to meet the requirements under the EU Medical Device Regulation triggered by the ECHA re-classification (adopted in October 2019 under the 14th Adaptation to Technical Progress to CLP) and to address their relevance to patient safety. The objective of this review is to present an integrated overview of these assessments, a benefit-risk assessment and an examination of potential alternative materials. The data support the conclusion that the exposure to CoCA in medical devices via clinically relevant routes does not represent a hazard for carcinogenicity or reproductive toxicity. Additionally, the risk for the adverse effects that are known to occur with elevated Co concentrations (e.g., cardiomyopathy) are very low for CoCA implant devices (infrequent reports often reflecting a unique catastrophic failure event out of millions of patients) and negligible for CoCA non-implant devices (not measurable/no case reports). In conclusion, the favorable benefit-risk profile also in relation to possible alternatives presented herein strongly support continued use of CoCA in medical devices.

Carcinogenic assessment of cobalt-containing alloys in medical devices or cobalt in occupational settings: A systematic review and meta-analysis of overall cancer risk from published epidemiologic studies.

In 2020, the European Commission up-classified pure cobalt metal to a Category 1B hazard, based primarily on data from rodent inhalation carcinogenicity studies of metallic cobalt. The European Commission review did not evaluate cobalt-containing alloys in medical devices, which have very different properties vs. pure cobalt metal and did not include a systematic epidemiologic review. We performed a systematic review and meta-analysis of published, peer-reviewed epidemiologic studies evaluating the association between overall cancer risk and exposure to orthopedic implants containing cobalt alloys or cobalt particulates in occupational settings. Study-specific estimates were pooled using random-effects models. Analyses included 20 papers on orthopedic implants and 10 occupational cohort papers (~1 million individuals). The meta-analysis summary estimates (95% confidence intervals) for overall cancer risk were 1.00 (0.96-1.04) overall and 0.97 (0.94-1.00) among high-quality studies. Results were also similar in analyses stratified by type of exposure/data sources (occupational cohort, implant registry or database), comparators (general or implant population), cancer incidence or mortality, follow-up duration (latency period), and study precision. In conclusion, meta-analysis found no association between exposure to orthopedic implants containing cobalt alloys or cobalt particulates in occupational settings and overall cancer risk, including an analysis of studies directly comparing metal-on-metal vs. non-metal-on-metal implants.

Measuring problem prescription opioid use among patients receiving long-term opioid analgesic treatment: development and evaluation of an algorithm for use in EHR and claims data.

Objective: Opioid surveillance in response to the opioid epidemic will benefit from scalable, automated algorithms for identifying patients with clinically documented signs of problem prescription opioid use. Existing algorithms lack accuracy. We sought to develop a high-sensitivity, high-specificity classification algorithm based on widely available structured health data to identify patients receiving chronic extended-release/long-acting (ER/LA) therapy with evidence of problem use to support subsequent epidemiologic investigations. Methods: Outpatient medical records of a probability sample of 2,000 Kaiser Permanente Washington patients receiving ≥60 days' supply of ER/LA opioids in a 90-day period from 1 January 2006 to 30 June 2015 were manually reviewed to determine the presence of clinically documented signs of problem use and used as a reference standard for algorithm development. Using 1,400 patients as training data, we constructed candidate predictors from demographic, enrollment, encounter, diagnosis, procedure, and medication data extracted from medical claims records or the equivalent from electronic health record (EHR) systems, and we used adaptive least absolute shrinkage and selection operator (LASSO) regression to develop a model. We evaluated this model in a comparable 600-patient validation set. We compared this model to ICD-9 diagnostic codes for opioid abuse, dependence, and poisoning. This study was registered with ClinicalTrials.gov as study NCT02667262 on 28 January 2016. Results: We operationalized 1,126 potential predictors characterizing patient demographics, procedures, diagnoses, timing, dose, and location of medication dispensing. The final model incorporating 53 predictors had a sensitivity of 0.582 at positive predictive value (PPV) of 0.572. ICD-9 codes for opioid abuse, dependence, and poisoning had a sensitivity of 0.390 at PPV of 0.599 in the same cohort. Conclusions: Scalable methods using widely available structured EHR/claims data to accurately identify problem opioid use among patients receiving long-term ER/LA therapy were unsuccessful. This approach may be useful for identifying patients needing clinical evaluation.

Postmarketing studies program to assess the risks and benefits of long-term use of extended-release/long-acting opioids among chronic pain patients.

Background: Among patients with chronic pain using long-term opioid therapy, the incidence of opioid abuse, addiction, overdose, and associated death are not well quantified. The range of estimates for these adverse outcomes varies drastically and may depend on how they are measured (i.e. study definitions of outcomes) and on patient characteristics and opioid-use factors (e.g. regimen, daily dose).Methods: Based on a review of the literature, the US Food and Drug Administration (FDA) required companies that manufacture and sell extended-release/long-acting (ER/LA) opioids conduct as a postmarketing requirement (PMR) a series of observational studies to estimate the rates of treatment-emergent misuse, abuse, addiction, overdose, and death using validated measures. The companies formed a consortium, the Opioid PMR Consortium (OPC), to conduct the studies.Results: The FDA initially requested four observational studies (a cohort study, a questionnaire validation study, a code validation study, and a doctor-shopping validation study), but in order to achieve the FDA's goals of the 4 studies, OPC and FDA agreed to 10 observational studies (a prospective cohort study, a retrospective database cohort study, three questionnaire validation studies, two code validation studies, and three doctor-shopping validation studies). The studies are continuing through 2020.Conclusions: A series of 10 observational studies was or are being conducted in response to the FDA's postmarketing requirement. All studies have been feasible to conduct, although a validated algorithm for measuring abuse and addiction in databases was not successful.

Using natural language processing of clinical text to enhance identification of opioid-related overdoses in electronic health records data.

PURPOSE: To enhance automated methods for accurately identifying opioid-related overdoses and classifying types of overdose using electronic health record (EHR) databases. METHODS: We developed a natural language processing (NLP) software application to code clinical text documentation of overdose, including identification of intention for self-harm, substances involved, substance abuse, and error in medication usage. Using datasets balanced with cases of suspected overdose and records of individuals at elevated risk for overdose, we developed and validated the application using Kaiser Permanente Northwest data, then tested portability of the application using Kaiser Permanente Washington data. Datasets were chart-reviewed to provide a gold standard for comparison and evaluation of the automated method. RESULTS: The method performed well in identifying overdose (sensitivity = 0.80, specificity = 0.93), intentional overdose (sensitivity = 0.81, specificity = 0.98), and involvement of opioids (excluding heroin, sensitivity = 0.72, specificity = 0.96) and heroin (sensitivity = 0.84, specificity = 1.0). The method performed poorly at identifying adverse drug reactions and overdose due to patient error and fairly at identifying substance abuse in opioid-related unintentional overdose (sensitivity = 0.67, specificity = 0.96). Evaluation using validation datasets yielded significant reductions, in specificity and negative predictive values only, for many classifications mentioned above. However, these measures remained above 0.80, thus, performance observed during development was largely maintained during validation. Similar results were obtained when evaluating portability, although there was a significant reduction in sensitivity for unintentional overdose that was attributed to missing text clinical notes in the database. CONCLUSIONS: Methods that process text clinical notes show promise for improving accuracy and fidelity at identifying and classifying overdoses according to type using EHR data.

Development of an algorithm to identify inpatient opioid-related overdoses and oversedation using electronic data.

PURPOSE: To facilitate surveillance and evaluate interventions addressing opioid-related overdoses, algorithms are needed for use in large health care databases to identify and differentiate community-occurring opioid-related overdoses from inpatient-occurring opioid-related overdose/oversedation. METHODS: Data were from Kaiser Permanente Northwest (KPNW), a large integrated health plan. We iteratively developed and evaluated an algorithm for electronically identifying inpatient overdose/oversedation in KPNW hospitals from 1 January 2008 to 31 December 2014. Chart audits assessed accuracy; data sources included administrative and clinical records. RESULTS: The best-performing algorithm used these rules: (1) Include events with opioids administered in an inpatient setting (including emergency department/urgent care) followed by naloxone administration within 275 hours of continuous inpatient stay; (2) exclude events with electroconvulsive therapy procedure codes; and (3) exclude events in which an opioid was administered prior to hospital discharge and followed by readmission with subsequent naloxone administration. Using this algorithm, we identified 870 suspect inpatient overdose/oversedation events and chart audited a random sample of 235. Of the random sample, 185 (78.7%) were deemed overdoses/oversedation, 37 (15.5%) were not, and 13 (5.5%) were possible cases. The number of hours between time of opioid and naloxone administration did not affect algorithm accuracy. When "possible" overdoses/oversedations were included with confirmed events, overall positive predictive value (PPV) was very good (PPV = 84.0%). Additionally, PPV was reasonable when evaluated specifically for hospital stays with emergency/urgent care admissions (PPV = 77.0%) and excellent for elective surgery admissions (PPV = 97.0%). CONCLUSIONS: Algorithm performance was reasonable for identifying inpatient overdose/oversedation with best performance among elective surgery patients.

Identifying and classifying opioid-related overdoses: A validation study.

PURPOSE: The study aims to develop and validate algorithms to identify and classify opioid overdoses using claims and other coded data, and clinical text extracted from electronic health records using natural language processing (NLP). METHODS: Primary data were derived from Kaiser Permanente Northwest (2008-2014), an integrated health care system (~n > 475 000 unique individuals per year). Data included International Classification of Diseases, Ninth Revision (ICD-9) codes for nonfatal diagnoses, International Classification of Diseases, Tenth Revision (ICD-10) codes for fatal events, clinical notes, and prescription medication records. We assessed sensitivity, specificity, positive predictive value, and negative predictive value for algorithms relative to medical chart review and conducted assessments of algorithm portability in Kaiser Permanente Washington, Tennessee State Medicaid, and Optum. RESULTS: Code-based algorithm performance was excellent for opioid-related overdoses (sensitivity = 97.2%, specificity = 84.6%) and classification of heroin-involved overdoses (sensitivity = 91.8%, specificity = 99.0%). Performance was acceptable for code-based suicide/suicide attempt classifications (sensitivity = 70.7%, specificity = 90.5%); sensitivity improved with NLP (sensitivity = 78.7%, specificity = 91.0%). Performance was acceptable for the code-based substance abuse-involved classification (sensitivity = 75.3%, specificity = 79.5%); sensitivity improved with the NLP-enhanced algorithm (sensitivity = 80.5%, specificity = 76.3%). The opioid-related overdose algorithm performed well across portability assessment sites, with sensitivity greater than 96% and specificity greater than 84%. Cross-site sensitivity for heroin-involved overdose was greater than 87%, specificity greater than or equal to 99%. CONCLUSIONS: Code-based algorithms developed to detect opioid-related overdoses and classify them according to heroin involvement perform well. Algorithms for classifying suicides/attempts and abuse-related opioid overdoses perform adequately for use for research, particularly given the complexity of classifying such overdoses. The NLP-enhanced algorithms for suicides/suicide attempts and abuse-related overdoses perform significantly better than code-based algorithms and are appropriate for use in settings that have data and capacity to use NLP.

Conditional power for assessing population interventions.

AIM: To calculate conditional power in comparative two-period studies with previously observed baseline data. METHOD: Isolate the variability attributable to the yet-to-observed data and modify the standard power formulae. RESULTS: For illustration, we examine rates of opioid overdose before and after a reformulation of one opioid product. The null hypothesis posited no impact of the reformulation, alternative hypotheses posited possible impacts, and ancillary hypotheses posited different secular pre-post changes directly observable in comparators. Conditional power varied with the size of the comparator population and with the assumed pre-post change for the comparator. CONCLUSION: Pre-post designs can be initiated after the baseline period is over. Power calculations that are conditioned on observed baseline data account differently for variability in the baseline and follow-up periods.

Incidence of nonmedical use of OxyContin and other prescription opioid pain relievers before and after the introduction of OxyContin with abuse deterrent properties.

OBJECTIVES: There is an epidemic of nonmedical and extra-medical use opioid abuse, addiction, and overdose. Extended-release oxycodone (OxyContin®), a prescription opioid pain reliever, was reformulated in 2010 to deter its abuse. The aim of this study was to assess changes in the onset of abuse of OxyContin and other opioids among young people and adults after reformulation of OxyContin with abuse-deterrent properties. METHODS: The study population was U.S. residents ≥ 12 years sampled in National Surveys on Drug Use and Health (NSDUH), 2004 to 2015, with subsample of 12-21-year-olds. Nonmedical and extra-medical use is the NSDUH proxy for abuse. Confidential audio-computer-assisted self-interviews were assessed. Age-specific incidence of nonmedical and extra-medical use of OxyContin and other prescription opioids were estimated year by year. Interrupted-time-series and age-period-cohort analyses were analyzed. RESULTS: Interrupted-time-series analysis showed a lower incidence of OxyContin nonmedical and extra-medical use after 2010 reformulation compared to the counterfactual predicted by the trend before 2010. No such difference was seen for other prescription opioids for all ages, although a lower incidence was also observed for other prescription opioids among 12-21-year-olds. Among 12-21-year-olds, a robustly lower incidence was found in 2012 compared to 2010 for OxyContin after holding constant age and cohort effects, whereas no robust difference was observed for other prescription opioids. The results showed 137,500 fewer newly incident cases of OxyContin nonmedical and extra-medical use per year. CONCLUSIONS: This study provides evidence supporting the role of OxyContin reformulation in the reduction of onset of OxyContin nonmedical and extra-medical use.