Chart validation of inpatient ICD-9-CM administrative diagnosis codes for acute myocardial infarction (AMI) among intravenous immune globulin (IGIV) users in the Sentinel Distributed Database

A scoping review of the methodological approaches used in retrospective chart reviews to validate adverse event rates in administrative data

Patient safety is a key quality issue for health systems. Healthcare acquired adverse events (AEs) compromise safety and quality; therefore, their reporting and monitoring is a patient safety priority. Although administrative datasets are potentially efficient tools for monitoring rates of AEs, concerns remain over the accuracy of their data. Chart review validation studies are required to explore the potential of administrative data to inform research and health policy. This review aims to present an overview of the methodological approaches and strategies used to validate rates of AEs in administrative data through chart review. This review was conducted in line with the Joanna Briggs Institute methodological framework for scoping reviews. Through database searches, 1054 sources were identified, imported into Covidence, and screened against the inclusion criteria. Articles that validated rates of AEs in administrative data through chart review were included. Data were extracted, exported to Microsoft Excel, arranged into a charting table, and presented in a tabular and descriptive format. Fifty-six studies were included. Most sources reported on surgical AEs; however, other medical specialties were also explored. Chart reviews were used in all studies; however, few agreed on terminology for the study design. Various methodological approaches and sampling strategies were used. Some studies used the Global Trigger Tool, a two-stage chart review method, whilst others used alternative single-, two-stage, or unclear approaches. The sources used samples of flagged charts (n = 24), flagged and random charts (n = 11), and random charts (n = 21). Most studies reported poor or moderate accuracy of AE rates. Some studies reported good accuracy of AE recording which highlights the potential of using administrative data for research purposes. This review highlights the potential for administrative data to provide information on AE rates and improve patient safety and healthcare quality. Nonetheless, further work is warranted to ensure that administrative data are accurate. The variation of methodological approaches taken, and sampling techniques used demonstrate a lack of consensus on best practice; therefore, further clarity and consensus are necessary to develop a more systematic approach to chart reviewing.

Risk of Arterial and Venous Thrombotic Events Among Patients with COVID-19: A Multi-National Collaboration of Regulatory Agencies from Canada, Europe, and United States

Purpose

Few studies have examined how the absolute risk of thromboembolism with COVID-19 has evolved over time across different countries. Researchers from the European Medicines Agency, Health Canada, and the United States (US) Food and Drug Administration established a collaboration to evaluate the absolute risk of arterial (ATE) and venous thromboembolism (VTE) in the 90 days after diagnosis of COVID-19 in the ambulatory (eg, outpatient, emergency department, nursing facility) setting from seven countries across North America (Canada, US) and Europe (England, Germany, Italy, Netherlands, and Spain) within periods before and during COVID-19 vaccine availability.

Patients and Methods

We conducted cohort studies of patients initially diagnosed with COVID-19 in the ambulatory setting from the seven specified countries. Patients were followed for 90 days after COVID-19 diagnosis. The primary outcomes were ATE and VTE over 90 days from diagnosis date. We measured country-level estimates of 90-day absolute risk (with 95% confidence intervals) of ATE and VTE.

Results

The seven cohorts included 1,061,565 patients initially diagnosed with COVID-19 in the ambulatory setting before COVID-19 vaccines were available (through November 2020). The 90-day absolute risk of ATE during this period ranged from 0.11% (0.09-0.13%) in Canada to 1.01% (0.97-1.05%) in the US, and the 90-day absolute risk of VTE ranged from 0.23% (0.21-0.26%) in Canada to 0.84% (0.80-0.89%) in England. The seven cohorts included 3,544,062 patients with COVID-19 during vaccine availability (beginning December 2020). The 90-day absolute risk of ATE during this period ranged from 0.06% (0.06-0.07%) in England to 1.04% (1.01-1.06%) in the US, and the 90-day absolute risk of VTE ranged from 0.25% (0.24-0.26%) in England to 1.02% (0.99-1.04%) in the US.

Conclusion

There was heterogeneity by country in 90-day absolute risk of ATE and VTE after ambulatory COVID-19 diagnosis both before and during COVID-19 vaccine availability.

Validity of Routine Health Data To Identify Safety Outcomes of Interest For Covid-19 Vaccines and Therapeutics in the Context of the Emerging Pandemic: A Comprehensive Literature Review

Introduction

Regulatory guidance encourages transparent reporting of information on the quality and validity of electronic health record data being used to generate real-world benefit-risk evidence for vaccines and therapeutics. We aimed to provide an overview of the availability of validated diagnostic algorithms for selected safety endpoints for Coronavirus disease 2019 (COVID-19) vaccines and therapeutics in the context of the emerging pandemic prior to December 2020.

Methods

We reviewed the literature up to December 2020 to identify validation studies for various safety events of interest, including myocardial infarction, arrhythmia, myocarditis, acute cardiac injury, vasculitis/vasculopathy, venous thromboembolism, stroke, respiratory distress syndrome (RDS), pneumonitis, cytokine release syndrome (CRS), multiple organ dysfunction syndrome, and renal failure. We included studies published between 2015 and 2020 that were considered high quality assessed with QUADAS and that reported positive predictive values (PPVs).

Results

Out of 43 identified studies, we found that diagnostic algorithms for cardiovascular outcomes were supported by the highest number of validation studies (n=17). Accurate algorithms are available for myocardial infarction (median PPV 80%; IQR 22%), arrhythmia (PPV range >70%), venous thromboembolism (median PPV: 73%) and ischaemic stroke (PPV range ≥85%). We found a lack of validation studies for less common respiratory and cardiac safety outcomes of interest (eg, pneumonitis and myocarditis), as well as for COVID-specific complications (CRS, RDS).

Conclusion

There is a need for better understanding of barriers to conducting validation studies, including data governance restrictions. Regulatory guidance should promote embedding validation within real-world EHR research used for decision-making.

Validation of a Case Definition to Identify Patients Diagnosed With Cardiovascular Disease in Canadian Primary Care Practices

Background

Cardiovascular disease (CVD) is a leading cause of death globally. This study validates a primary care-based electronic medical record case definition for CVD.

Methods

This retrospective, cross-sectional study explores electronic medical record data from 1574 primary care providers participating in the Canadian Primary Care Sentinel Surveillance Network. A reference standard was created by reviewing medical records of a subset of patients in this network (n = 2017) for coronary artery disease (CAD), cerebrovascular disease (CeVD), and peripheral vascular disease (PVD). Together, these data produced a CVD reference. We applied validated case definitions to an active patient population (≥ 1 visit between January 1, 2018 and December 31, 2019) to estimate prevalence using the exact binomial test (N = 689,301). Descriptive statistics, χ² tests, and t tests characterized patients with vs without CVD.

Results

The optimal CVD Case Definition 2 had a sensitivity of 68.5% (95% Confidence Interval [CI]: 61.6%-74.8%), a specificity of 97.8% (95% CI: 97.0%-98.4%), a positive predictive value of 77.7% (95% CI: 71.6%-82.7%), and a negative predictive value of 96.5% (95% CI: 95.8%-97.1%). Included in this CVD definition was a strong CAD case definition with sensitivity of 91.6% (95% CI: 84.6%-96.1%), specificity of 98.3% (95% CI: 97.6%-98.8%), a PPV of 74.8% (95% CI: 67.8%-80.7%), and an NPV of 99.5% (95% CI: 99.1%-99.7%). This CVD definition also included CeVD and PVD case definitions with low sensitivity (77.6% and 36.6%) but high specificity (98.6% and 99.0%). The estimated prevalence of CVD among primary care patients is 11.2% (95% CI, 11.1%-11.3%; n = 77,064); the majority had CAD (6.4%).

Conclusions

This study validated a definition of CVD and its component parts-CAD, CeVD, and PVD. Understanding the prevalence and disease burden for patients with CVD within primary care settings can improve prevention and disease management.

Risk of admission to hospital with arterial or venous thromboembolism among patients diagnosed in the ambulatory setting with covid-19 compared with influenza: retrospective cohort study

Objective

To measure the 90 day risk of arterial thromboembolism and venous thromboembolism among patients diagnosed with covid-19 in the ambulatory (ie, outpatient, emergency department, or institutional) setting during periods before and during covid-19 vaccine availability and compare results to patients with ambulatory diagnosed influenza.

Design

Retrospective cohort study.

Setting

Four integrated health systems and two national health insurers in the US Food and Drug Administration's Sentinel System.

Participants

Patients with ambulatory diagnosed covid-19 when vaccines were unavailable in the US (period 1, 1 April-30 November 2020; n=272 065) and when vaccines were available in the US (period 2, 1 December 2020-31 May 2021; n=342 103), and patients with ambulatory diagnosed influenza (1 October 2018-30 April 2019; n=118 618).

Main outcome measures

Arterial thromboembolism (hospital diagnosis of acute myocardial infarction or ischemic stroke) and venous thromboembolism (hospital diagnosis of acute deep venous thrombosis or pulmonary embolism) within 90 days after ambulatory covid-19 or influenza diagnosis. We developed propensity scores to account for differences between the cohorts and used weighted Cox regression to estimate adjusted hazard ratios of outcomes with 95% confidence intervals for covid-19 during periods 1 and 2 versus influenza.

Results

90 day absolute risk of arterial thromboembolism with covid-19 was 1.01% (95% confidence interval 0.97% to 1.05%) during period 1, 1.06% (1.03% to 1.10%) during period 2, and with influenza was 0.45% (0.41% to 0.49%). The risk of arterial thromboembolism was higher for patients with covid-19 during period 1 (adjusted hazard ratio 1.53 (95% confidence interval 1.38 to 1.69)) and period 2 (1.69 (1.53 to 1.86)) than for patients with influenza. 90 day absolute risk of venous thromboembolism with covid-19 was 0.73% (0.70% to 0.77%) during period 1, 0.88% (0.84 to 0.91%) during period 2, and with influenza was 0.18% (0.16% to 0.21%). Risk of venous thromboembolism was higher with covid-19 during period 1 (adjusted hazard ratio 2.86 (2.46 to 3.32)) and period 2 (3.56 (3.08 to 4.12)) than with influenza.

Conclusions

Patients diagnosed with covid-19 in the ambulatory setting had a higher 90 day risk of admission to hospital with arterial thromboembolism and venous thromboembolism both before and after covid-19 vaccine availability compared with patients with influenza.

New cardiovascular events in the convalescent period among survivors of SARS-CoV-2 infection

BACKGROUND

Patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may have an increased risk of acute cardiovascular events in the convalescent period.

AIMS

To determine whether patients with SARS-CoV-2 infection have an increased risk of cardiovascular events during the convalescent period.

METHODS

We analyzed 10,691 hospitalized adult pneumonia patients with SARS-CoV-2 infection and contemporary matched controls of pneumonia patients without SARS-CoV-2 infection. The risk of new cardiovascular events following >30 days pneumonia admission (convalescent period) was ascertained using Cox proportional hazards regression analysis to adjust for potential confounders.

RESULTS

Among 10,691 pneumonia patients with SARS-CoV-2 infection, 697 patients (5.8%; 95% CI, 5.4-6.2%) developed new cardiovascular events (median time interval of 218 days post pneumonia admission; interquartile range Q1 = 117 days, Q3 = 313 days). The risk of new cardiovascular events was not significantly higher among pneumonia patients with SARS-CoV-2 infection compared with those with pneumonia without SARS-CoV-2 infection (hazard ratio (HR), 0.90, 95% CI, 0.80-1.02) after adjustment for potential confounders. In addition, no significant difference in the rate of a new ischemic stroke (HR, 0.84; 95% CI, 0.70-1.02) or ischemic heart disease (HR, 1.00; 95% CI, 0.87-1.15) was observed between the pneumonia patients with and without SARS-CoV-2 infection.

CONCLUSION

Our study suggests that new cardiovascular events rate in the convalescent period among pneumonia patients with SARS-CoV-2 infection was not significantly higher than the rate seen with other pneumonias.

Large-scale evidence generation and evaluation across a network of databases for type 2 diabetes mellitus (LEGEND-T2DM): a protocol for a series of multinational, real-world comparative cardiovascular effectiveness and safety studies

INTRODUCTION

Therapeutic options for type 2 diabetes mellitus (T2DM) have expanded over the last decade with the emergence of cardioprotective novel agents, but without such data for older drugs, leaving a critical gap in our understanding of the relative effects of T2DM agents on cardiovascular risk.

METHODS AND ANALYSIS

The large-scale evidence generations across a network of databases for T2DM (LEGEND-T2DM) initiative is a series of systematic, large-scale, multinational, real-world comparative cardiovascular effectiveness and safety studies of all four major second-line anti-hyperglycaemic agents, including sodium-glucose co-transporter-2 inhibitor, glucagon-like peptide-1 receptor agonist, dipeptidyl peptidase-4 inhibitor and sulfonylureas. LEGEND-T2DM will leverage the Observational Health Data Sciences and Informatics (OHDSI) community that provides access to a global network of administrative claims and electronic health record data sources, representing 190 million patients in the USA and about 50 million internationally. LEGEND-T2DM will identify all adult, patients with T2DM who newly initiate a traditionally second-line T2DM agent. Using an active comparator, new-user cohort design, LEGEND-T2DM will execute all pairwise class-versus-class and drug-versus-drug comparisons in each data source, producing extensive study diagnostics that assess reliability and generalisability through cohort balance and equipoise to examine the relative risk of cardiovascular and safety outcomes. The primary cardiovascular outcomes include a composite of major adverse cardiovascular events and a series of safety outcomes. The study will pursue data-driven, large-scale propensity adjustment for measured confounding, a large set of negative control outcome experiments to address unmeasured and systematic bias.

ETHICS AND DISSEMINATION

The study ensures data safety through a federated analytic approach and follows research best practices, including prespecification and full disclosure of results. LEGEND-T2DM is dedicated to open science and transparency and will publicly share all analytic code from reproducible cohort definitions through turn-key software, enabling other research groups to leverage our methods, data and results to verify and extend our findings.

Cardiogenic shock complicating non-ST-segment elevation myocardial infarction: An 18-year study

OBJECTIVE

To evaluate the epidemiology and outcomes of non-ST-segment-elevation myocardial infarction-cardiogenic shock (NSTEMI-CS) in the United States.

METHODS

Adult (>18 years) NSTEMI-CS admissions were identified using the National Inpatient Sample (2000-2017) and classified by tertiles of admission year (2000-2005, 2006-2011 and 2012-2017). Outcomes of interest included temporal trends of prevalence and in-hospital mortality, use of cardiac procedures, in-hospital mortality, hospitalization costs, and length of stay.

RESULTS

In over 7.3 million NSTEMI admissions, CS was noted in 189,155 (2.6%). NSTEMI-CS increased from 1.5% in 2000 to 3.6% in 2017 (adjusted odds ratio 2.03 [95% confidence interval 1.97-2.09]; P < .001). Rates of non-cardiac organ failure and cardiac arrest increased during the study period. Between 2000 and 2017, coronary angiography (43.9%-63.9%), early coronary angiography (13.6%-25.6%), percutaneous coronary intervention (14.8%-31.6%), and coronary artery bypass grafting use (19.0%-25.8%) increased (P < .001). Over the study period, the use of intra-aortic balloon pump remained stable (28.6%-28.8%), and both percutaneous left ventricular assist devices (0%-9.1%) and extra-corporeal membrane oxygenation (0.1%-1.6%) increased (all P < .001). In hospital mortality decreased from 50.2% in 2000 to 32.3% in 2017 (adjusted odds ratio 0.27 [95% confidence interval 0.25-0.29]; P < .001). During the 18-year period, hospital lengths of stay decreased, and hospitalization costs increased.

CONCLUSIONS

In the United States, prevalence of CS in NSTEMI has increased 2-fold between 2000 and 2017, while in-hospital mortality has decreased during the study period. Use of coronary angiography and percutaneous coronary intervention increased during the study period.

COVID-19 is associated with higher risk of venous thrombosis, but not arterial thrombosis, compared with influenza: Insights from a large US cohort

Introduction

Infection with SARS-CoV-2 is typically compared with influenza to contextualize its health risks. SARS-CoV-2 has been linked with coagulation disturbances including arterial thrombosis, leading to considerable interest in antithrombotic therapy for Coronavirus Disease 2019 (COVID-19). However, the independent thromboembolic risk of SARS-CoV-2 infection compared with influenza remains incompletely understood. We evaluated the adjusted risks of thromboembolic events after a diagnosis of COVID-19 compared with influenza in a large retrospective cohort.

Methods

We used a US-based electronic health record (EHR) dataset linked with insurance claims to identify adults diagnosed with COVID-19 between April 1, 2020 and October 31, 2020. We identified influenza patients diagnosed between October 1, 2018 and April 31, 2019. Primary outcomes [venous composite of pulmonary embolism (PE) and acute deep vein thrombosis (DVT); arterial composite of ischemic stroke and myocardial infarction (MI)] and secondary outcomes were assessed 90 days post-diagnosis. Propensity scores (PS) were calculated using demographic, clinical, and medication variables. PS-adjusted hazard ratios (HRs) were calculated using Cox proportional hazards regression.

Results

There were 417,975 COVID-19 patients (median age 57y, 61% women), and 345,934 influenza patients (median age 47y, 66% women). Compared with influenza, patients with COVID-19 had higher venous thromboembolic risk (HR 1.53, 95% CI 1.38–1.70), but not arterial thromboembolic risk (HR 1.02, 95% CI 0.95–1.10). Secondary analyses demonstrated similar risk for ischemic stroke (HR 1.11, 95% CI 0.98–1.25) and MI (HR 0.93, 95% CI 0.85–1.03) and higher risk for DVT (HR 1.36, 95% CI 1.19–1.56) and PE (HR 1.82, 95% CI 1.57–2.10) in patients with COVID-19.

Conclusion

In a large retrospective US cohort, COVID-19 was independently associated with higher 90-day risk for venous thrombosis, but not arterial thrombosis, as compared with influenza. These findings may inform crucial knowledge gaps regarding the specific thromboembolic risks of COVID-19.

Validation Study of Algorithms to Identify Malignant Tumors and Serious Infections in a Japanese Administrative Healthcare Database

BACKGROUND

This retrospective observational study validated case-finding algorithms for malignant tumors and serious infections in a Japanese administrative healthcare database.

METHODS

Random samples of possible cases of each disease (January 2015-January 2018) from two hospitals participating in the Medical Data Vision Co., Ltd. (MDV) database were identified using combinations of ICD-10 diagnostic codes and other procedural/billing codes. For each disease, two physicians identified true cases among the random samples of possible cases by medical record review; a third physician made the final decision in cases where the two physicians disagreed. The accuracy of case-finding algorithms was assessed using positive predictive value (PPV) and sensitivity.

RESULTS

There were 2,940 possible cases of malignant tumor; 180 were randomly selected and 108 were identified as true cases after medical record review. One case-finding algorithm gave a high PPV (64.1%) without substantial loss in sensitivity (90.7%) and included ICD-10 codes for malignancy and photographing/imaging. There were 3,559 possible cases of serious infection; 200 were randomly selected and 167 were identified as true cases after medical record review. Two case-finding algorithms gave a high PPV (85.6%) with no loss in sensitivity (100%). Both case-finding algorithms included the relevant diagnostic code and immunological infection test/other related test and, of these, one also included pathological diagnosis within 1 month of hospitalization.

CONCLUSIONS

The case-finding algorithms in this study showed good PPV and sensitivity for identification of cases of malignant tumors and serious infections from an administrative healthcare database in Japan.

COVID-19 is associated with higher risk of venous thrombosis, but not arterial thrombosis, compared with influenza: Insights from a large US cohort

Introduction

Infection with SARS-CoV-2 is typically compared with influenza to contextualize its health risks. SARS-CoV-2 has been linked with coagulation disturbances including arterial thrombosis, leading to considerable interest in antithrombotic therapy for Coronavirus Disease 2019 (COVID-19). However, the independent thromboembolic risk of SARS-CoV-2 infection compared with influenza remains incompletely understood. We evaluated the adjusted risks of thromboembolic events after a diagnosis of COVID-19 compared with influenza in a large retrospective cohort.

Methods

We used a US-based electronic health record (EHR) dataset linked with insurance claims to identify adults diagnosed with COVID-19 between April 1, 2020 and October 31, 2020. We identified influenza patients diagnosed between October 1, 2018 and April 31, 2019. Primary outcomes [venous composite of pulmonary embolism (PE) and acute deep vein thrombosis (DVT); arterial composite of ischemic stroke and myocardial infarction (MI)] and secondary outcomes were assessed 90 days post-diagnosis. Propensity scores (PS) were calculated using demographic, clinical, and medication variables. PS-adjusted hazard ratios (HRs) were calculated using Cox proportional hazards regression.

Results

There were 417,975 COVID-19 patients (median age 57y, 61% women), and 345,934 influenza patients (median age 47y, 66% women). Compared with influenza, patients with COVID-19 had higher venous thromboembolic risk (HR 1.53, 95% CI 1.38–1.70), but not arterial thromboembolic risk (HR 1.02, 95% CI 0.95–1.10). Secondary analyses demonstrated similar risk for ischemic stroke (HR 1.11, 95% CI 0.98–1.25) and MI (HR 0.93, 95% CI 0.85–1.03) and higher risk for DVT (HR 1.36, 95% CI 1.19–1.56) and PE (HR 1.82, 95% CI 1.57–2.10) in patients with COVID-19.

Conclusion

In a large retrospective US cohort, COVID-19 was independently associated with higher 90-day risk for venous thrombosis, but not arterial thrombosis, as compared with influenza. These findings may inform crucial knowledge gaps regarding the specific thromboembolic risks of COVID-19.

Tofacitinib Treatment Safety in Moderate to Severe Ulcerative Colitis: Comparison of Observational Population Cohort Data From the IBM MarketScan® Administrative Claims Database With Tofacitinib Trial Data

BACKGROUND

Tofacitinib is an oral, small molecule Janus kinase inhibitor for the treatment of ulcerative colitis (UC). We aimed to estimate the overall incidence of safety events in patients with UC in a real-life population cohort for comparison with the tofacitinib UC clinical trial program.

METHODS

Clinical trial-like criteria were applied to an IBM MarketScan® claims database population-based cohort (n = 22,967) of patients with UC (October 2010 to September 2015) to identify a UC trial-like cohort treated with tumor necrosis factor inhibitors (TNFi; n = 6366) to compare with the tofacitinib UC clinical trial cohort (n = 1157).

RESULTS

Incidence rates (events per 100 patient-years; [95% confidence interval]) in the UC trial-like cohort were as follows: serious infections, 3.33 (2.73-4.02); opportunistic infections (OIs; excluding herpes zoster [HZ]), 1.45 (1.06-1.93); HZ, 1.77 (1.34-2.29); malignancies (excluding nonmelanoma skin cancer [NMSC]), 0.63 (0.43-0.90); NMSC, 1.69 (1.35-2.10); major adverse cardiovascular events (MACE), 0.51 (0.31-0.79); pulmonary embolism (PE), 0.54 (0.30-0.89); deep vein thrombosis (DVT), 1.41 (1.00-1.93); and gastrointestinal perforations, 0.31 (0.16-0.54). Compared with the UC trial-like cohort, tofacitinib-treated patients had numerically lower incidence rates for serious infections (1.75 [1.27-2.36]), OIs (excluding HZ; 0.16 [0.04-0.42]), NMSC (0.78 [0.47-1.22]), PE (0.16 [0.04-0.41]), and DVT (0.04 [0.00-0.23]), and a higher rate for HZ (3.57 [2.84-4.43]); rates for malignancies (excluding NMSC), MACE, and gastrointestinal perforations were similar.

CONCLUSIONS

When acknowledging limitations of comparing claims data with controlled clinical trial data, incidence rates for HZ among TNFi-treated patients in the UC trial-like cohort were lower than in the tofacitinib UC clinical trial cohort; rates for serious infections, OIs, NMSC, PE, and DVT were numerically higher.

CLINICALTRIALS.GOV

NCT00787202, NCT01465763, NCT01458951, NCT01458574, NCT01470612.

Acute myocardial infarction: Development and application of an ICD-10-CM-based algorithm to a large U.S. healthcare claims-based database

Background

Healthcare administrative claims data hold value for monitoring drug safety and assessing drug effectiveness. The U.S. Food and Drug Administration Biologics Effectiveness and Safety Initiative (BEST) is expanding its analytical capacity by developing claims-based definitions—referred to as algorithms—for populations and outcomes of interest. Acute myocardial infarction (AMI) was of interest due to its potential association with select biologics and the lack of an externally validated International Classification of Diseases, 10^th Revision, Clinical Modification (ICD-10-CM) algorithm.

Objective

Develop and apply an ICD-10-CM-based algorithm in a U.S. administrative claims database to identify and characterize AMI populations.

Methods

A comprehensive literature review was conducted to identify validated AMI algorithms. Building on prior published methodology and consistent application of ICD-9-CM codes, an ICD-10-CM algorithm was developed via forward-backward mapping using General Equivalence Mappings and refined with clinical input. An AMI population was then identified in the IBM^® MarketScan^® Research Databases and characterized using descriptive statistics.

Results and discussion

Between 2014–2017, 2.83–3.16 individuals/1,000 enrollees/year received ≥1 AMI diagnosis in any healthcare setting. The 2015 transition to ICD-10-CM did not result in a substantial change in the proportion of patients identified. Average patient age at first AMI diagnosis was 64.9 years, and 61.4% of individuals were male. Unspecified chest pain, hypertension, and coronary atherosclerosis of native coronary vessel/artery were most commonly reported within one day of AMI diagnosis. Electrocardiograms were the most common medical procedure and beta-blockers were the most commonly ordered cardiac medication in the one day before to 14 days following AMI diagnosis. The mean length of inpatient stay was 5.6 days (median 3 days; standard deviation 7.9 days). Findings from this ICD-10-CM-based AMI study were internally consistent with ICD-9-CM-based findings and externally consistent with ICD-9-CM-based studies, suggesting that this algorithm is ready for validation in future studies.

Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review

Background

Electronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research.

Objective

This review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions.

Methods

A scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines.

Results

A total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule–based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance.

Conclusions

Recognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed.

Using Medicare Claims to Identify Acute Clinical Events Following Implantation of Leadless Pacemakers

Background

There is heightened interest in how real-world data (RWD) can be used to supplement or replace traditional mechanisms for collecting clinical information. A critical component in evaluating utility of RWD is assessing the validity and reliability of event measurement. Only two studies have validated Medicare claims with physician-adjudicated data collected in a clinical study and none in the pacemaker patient population. This study compares events identified in physician-adjudicated clinical registry data collected in the Micra Post-Approval Registry (PAR) with events identified via Medicare administrative claims in the Micra Coverage with Evidence (CED) Study.

Methods

Patients who were dually enrolled in the Micra CED and the Micra PAR between March 9, 2017 and December 1, 2017 were included in the validation analysis. All patients intended to be implanted with a Micra device were eligible for participation in the Micra PAR. All Medicare fee-for-service beneficiaries implanted with a Micra device who met the 12-month continuous enrollment criteria were included in the Micra CED. We compared the count of acute (30-day) complications identified in the Medicare claims and the physician-adjudicated PAR data to assess agreement between data sources.

Results

There were 230 patients dually enrolled in the Micra CED and Micra PAR studies during the study period. Overall, there were 17 acute events reported in either the Micra CED or the Micra PAR, with 95% agreement in the identification of events and absence of events between studies. Study disagreement between events reported in either study varied: arteriovenous fistula (50%), pulmonary embolism (67%), hemorrhage/hematoma (75%), and deep vein thrombosis (100%). Among physician-adjudicated events, there was no disagreement between the Micra CED and Micra PAR studies in any event type.

Conclusion

Findings from this study demonstrate high agreement in event identification between Medicare claims data and registries for patients implanted with Micra leadless pacemakers.

Validation of a claims-based algorithm identifying eligible study subjects in the ADAPTABLE pragmatic clinical trial

Objective

Validate an algorithm that uses administrative claims data to identify eligible study subjects for the ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness) pragmatic clinical trial (PCT).

Materials and methods

This study used medical records from a random sample of patients identified as eligible for the ADAPTABLE trial. The inclusion criteria for ADAPTABLE were a history of acute myocardial infarction (AMI) or percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG), or other coronary artery disease (CAD), plus at least one of several risk-enrichment factors. Exclusion criteria included a history of bleeding disorders or aspirin allergy. Using a claims-based algorithm, based on International Classification of Diseases, 9th Edition, Clinical Modification (ICD-9-CM) and 10th Edition (ICD-10) codes and Current Procedural Terminology (CPT) codes, we identified patients eligible for the PCT. The primary outcome was the positive predictive value (PPV) of the identification algorithm: the proportion of sampled patients whose medical records confirmed their ADAPTABLE study eligibility. Exact 95% confidence limits for binomial random variables were calculated for the PPV estimates.

Results

Of the 185 patients whose medical records were reviewed, 168 (90.8%; 95% Confidence Interval: 85.7%, 94.6%) were confirmed study eligible. This proportion did not differ between patients identified with codes for AMI and patients identified with codes for PCI or CABG.

Conclusion

The estimated PPV was similar to those in claims-based identification of drug safety surveillance events, indicating that administrative claims data can accurately identify study-eligible subjects for pragmatic clinical trials.