A systematic review of validated methods to capture acute bronchospasm using administrative or claims data

Comparative Effectiveness of Mepolizumab, Benralizumab, and Dupilumab among Patients with Difficult-to-Control Asthma: A Multicenter Retrospective Propensity-matched Analysis

Rationale: The comparative effectiveness of biologic agents used as add-on therapy in the management of difficult-to-control asthma is unclear. Objective: To compare the effectiveness of dupilumab, mepolizumab, and benralizumab among patients with difficult-to-control asthma. Methods: Retrospective multicenter cohort study of adult patients with difficult-to-control asthma starting treatment with dupilumab, mepolizumab, or benralizumab as documented in a multicenter electronic health record and claims-based database between October 19, 2018, and September 30, 2022. Propensity-score matching was used to minimize bias from nonrandomized treatment assignment; a prespecified α-level was set at 0.017 to account for three primary comparisons. The exposure of interest was the new initiation of dupilumab, benralizumab, or mepolizumab treatment. The primary outcome was the rate of asthma exacerbations in the 1 year after initiation of biologic therapy modeled using a negative binomial approach. Results: Among 893,668 patients with asthma who were prescribed an inhaled corticosteroid and were ⩾12 years old (65% female; mean age, 49 yr), 3,943 started dupilumab, 1,902 started benralizumab, and 2,012 started mepolizumab, all without an alternative indication for biologic therapy. After matching, there were 1,805 patients in each group for comparisons between dupilumab and benralizumab, 1,865 for comparisons between dupilumab and mepolizumab, and 1,721 for comparisons between mepolizumab and benralizumab. For all pairwise comparisons, covariates were well balanced after matching (all standardized mean differences <0.1). Patients who initiated dupilumab had a significantly lower rate of asthma exacerbations (1.07 per year) compared with benralizumab (1.47 per year), with a rate ratio (RR) of 0.73 (95% confidence interval, 0.63-0.85), and also had a significantly lower rate of asthma exacerbations compared with mepolizumab (1.04 per year vs. 1.45 per year), with an RR of 0.72 (0.62-0.84). There was no statistically significant difference in the rate of asthma exacerbations between mepolizumab (1.40 per year) and benralizumab (1.41 per year), with an RR of 1.00 (0.85-1.17). Conclusions: In patients with difficult-to-control asthma who had newly initiated biologic therapy, dupilumab was associated with a decreased rate of asthma exacerbations in the 1 year after initiation compared with mepolizumab or benralizumab.

Development and Validation of a Model to Identify Alzheimer's Disease and Related Syndromes in Administrative Data

BACKGROUND

Administrative data are used in the field of Alzheimer's Disease and Related Syndromes (ADRS), however their performance to identify ADRS is unknown.

OBJECTIVE

i) To develop and validate a model to identify ADRS prevalent cases in French administrative data (SNDS), ii) to identify factors associated with false negatives.

METHODS

Retrospective cohort of subjects ≥ 65 years, living in South-Western France, who attended a memory clinic between April and December 2013. Gold standard for ADRS diagnosis was the memory clinic specialized diagnosis. Memory clinics' data were matched to administrative data (drug reimbursements, diagnoses during hospitalizations, registration with costly chronic conditions). Prediction models were developed for 1-year and 3-year periods of administrative data using multivariable logistic regression models. Overall model performance, discrimination, and calibration were estimated and corrected for optimism by resampling. Youden index was used to define ADRS positivity and to estimate sensitivity, specificity, positive predictive and negative probabilities. Factors associated with false negatives were identified using multivariable logistic regressions.

RESULTS

3360 subjects were studied, 52% diagnosed with ADRS by memory clinics. Prediction model based on age, all-cause hospitalization, registration with ADRS as a chronic condition, number of anti-dementia drugs, mention of ADRS during hospitalizations had good discriminative performance (c-statistic: 0.814, sensitivity: 76.0%, specificity: 74.2% for 2013 data). 419 false negatives (24.0%) were younger, had more often ADRS types other than Alzheimer's disease, moderate forms of ADRS, recent diagnosis, and suffered from other comorbidities than true positives.

CONCLUSION

Administrative data presented acceptable performance for detecting ADRS. External validation studies should be encouraged.

The validity of diagnostic algorithms to identify asthma patients in healthcare administrative databases: a systematic literature review

OBJECTIVES

To review the available evidence supporting the validity of algorithms to identify asthma patients in healthcare administrative databases.

METHODS

A systematic literature search was conducted on multiple databases from inception to March 2020 to identify studies that reported the validity of case-finding asthma algorithms applied to healthcare administrative data. Following an initial screening of abstracts, two investigators independently assessed the full text of studies which met the pre-determined eligibility criteria. Data on study population and algorithm characteristics were extracted. A revised version of the Quality Assessment of Diagnostic Accuracy Studies tool was used to evaluate the risk of bias and generalizability of studies.

RESULTS

A total of 20 studies met the eligibility criteria. Algorithms which incorporated ≥1 diagnostic code for asthma over a 1-year period appeared to be valid in both adult and pediatric populations (sensitivity ≥ 85%; specificity ≥ 89%; PPV ≥ 70%). The validity was enhanced when: (1) the time frame to capture asthma cases was increased to two years; (2) ≥2 asthma diagnostic codes were considered; and (3) when diagnoses were recorded by a pulmonologist. Algorithms which integrated pharmacy claims data appeared to correctly identify asthma patients; however, the extent to which asthma medications can improve the validity remains unclear. The quality of several studies was high, although disease progression bias and biases related to self-reported data was observed in some studies.

CONCLUSIONS

Healthcare administrative databases are adequate sources to identify asthma patients. More restrictive definitions based on both asthma diagnoses and asthma medications may enhance validity, although further research is required to confirm this hypothesis.

Identifying Asthma Exacerbation-Related Emergency Department Visit Using Electronic Medical Record and Claims Data

Background  Asthma exacerbation leading to emergency department (ED) visit is prevalent, an indicator of poor control of asthma, and is a potentially preventable clinical outcome.

Objective  We propose to utilize multiple data elements available in electronic medical records (EMRs) and claims database to create separate algorithms with high validity for clinical and research purposes to identify asthma exacerbation-related ED visit among the general population.

Methods  We performed a retrospective study with inclusion criteria of patients aged 4 to 40 years, a visit to Geisinger ED from January 1, 2006, to October 28, 2013, with asthma on their problem list. Different electronic data elements including chief complaints, vitals, season, smoking, medication use, and discharge diagnoses were obtained to create the algorithm. A stratified random sample was generated to select the charts for review. Chart review was performed to classify patients with asthma-related ED visit, that is, the gold standard. Two reviewers performed the chart review and validation was done on a small subset.

Results  There were 966 eligible ED visits in the EMR sample and 731 in the claims sample. Agreement between reviewers was 95.45% and kappa statistic was 0.91. Mean age of the EMR sample was 22 years, and mostly white (93%). Multiple models conventionally used in studies were evaluated and the final model chosen included principal diagnosis, bronchodilator, and steroid use for both algorithms, chief complaints for EMR, and secondary diagnosis for claims. Area under the curve was 0.93 (95% confidence interval: 0.91–0.94) and 0.94 (0.93–0.96), respectively, for EMR and claims data, with positive predictive value of > 94%. The algorithms are visually presented using nomograms.

Conclusion  We were able to develop two separate algorithms for EMR and claims to identify asthma exacerbation-related ED visit with excellent diagnostic ability and varying discrimination threshold for clinical and research purposes.

Classifying Chronic Lower Respiratory Disease Events in Epidemiologic Cohort Studies

RATIONALE

One in 12 adults has chronic obstructive pulmonary disease or asthma. Acute exacerbations of these chronic lower respiratory diseases (CLRDs) are a major cause of morbidity and mortality. Valid approaches to classifying cases and exacerbations in the general population are needed to facilitate prevention research.

OBJECTIVES

To assess the feasibility, reproducibility, and performance of a protocol to identify CLRD cases and exacerbations triggering emergency department (ED) visits or hospitalizations in cohorts of patients derived from general populations of adults.

METHODS

A protocol was developed to classify CLRD cases and severe exacerbations on the basis of review of medical records. ED and inpatient medical records were ascertained prospectively in the Hispanic Community Health Study/Study of Latinos, and inpatient records were retrospectively identified by administrative codes in the Multi-Ethnic Study of Atherosclerosis. "Probable" exacerbations were defined as a physician's diagnosis of CLRD with acute respiratory symptoms. "Highly probable" exacerbations additionally required systemic corticosteroid therapy, and "definite" exacerbations required airflow limitation or evidence of CLRD on imaging studies. Adjudicated results were compared with CLRD cases identified by spirometry and self-report, and with an administrative definition of exacerbations.

MEASUREMENTS AND MAIN RESULTS

Protocol-based classification was completed independently by two physicians for 216 medical records (56 ED visits and 61 hospitalizations in the Hispanic Community Health Study/Study of Latinos; 99 hospitalizations in the Multi-Ethnic Study of Atherosclerosis). Reviewer disagreement occurred in 2-5% of cases and 4-8% of exacerbations. Eighty-nine percent of records were confirmed as at least probable CLRD cases. Fifty-six percent of confirmed CLRD cases had airflow limitation on the basis of baseline study spirometry. Of records that described CLRD as the primary discharge diagnosis code, an acute exacerbation was confirmed as at least probable for 96% and as highly probable or definite for 77%. Only 50% of records with CLRD as a secondary code were confirmed, although such records accounted for over half of all confirmed exacerbations.

CONCLUSIONS

CLRD cases and severe exacerbations without preceding documentation of airflow limitation are identified frequently in population-based cohorts of persons. A primary discharge diagnosis of CLRD is specific but insensitive for defining exacerbations. Protocol-based classification of medical records may be appropriate to supplement and to validate identification of CLRD cases and exacerbations in general population studies. Clinical trials registered with www.clinicaltrials.gov (NCT00005487 and NCT02060344).

Validation of asthma recording in electronic health records: a systematic review

Objective

To describe the methods used to validate asthma diagnoses in electronic health records and summarize the results of the validation studies.

Background

Electronic health records are increasingly being used for research on asthma to inform health services and health policy. Validation of the recording of asthma diagnoses in electronic health records is essential to use these databases for credible epidemiological asthma research.

Methods

We searched EMBASE and MEDLINE databases for studies that validated asthma diagnoses detected in electronic health records up to October 2016. Two reviewers independently assessed the full text against the predetermined inclusion criteria. Key data including author, year, data source, case definitions, reference standard, and validation statistics (including sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) were summarized in two tables.

Results

Thirteen studies met the inclusion criteria. Most studies demonstrated a high validity using at least one case definition (PPV >80%). Ten studies used a manual validation as the reference standard; each had at least one case definition with a PPV of at least 63%, up to 100%. We also found two studies using a second independent database to validate asthma diagnoses. The PPVs of the best performing case definitions ranged from 46% to 58%. We found one study which used a questionnaire as the reference standard to validate a database case definition; the PPV of the case definition algorithm in this study was 89%.

Conclusion

Attaining high PPVs (>80%) is possible using each of the discussed validation methods. Identifying asthma cases in electronic health records is possible with high sensitivity, specificity or PPV, by combining multiple data sources, or by focusing on specific test measures. Studies testing a range of case definitions show wide variation in the validity of each definition, suggesting this may be important for obtaining asthma definitions with optimal validity.

Validation of asthma recording in electronic health records: protocol for a systematic review

BACKGROUND

Asthma is a common, heterogeneous disease with significant morbidity and mortality worldwide. It can be difficult to define in epidemiological studies using electronic health records as the diagnosis is based on non-specific respiratory symptoms and spirometry, neither of which are routinely registered. Electronic health records can nonetheless be valuable to study the epidemiology, management, healthcare use and control of asthma. For health databases to be useful sources of information, asthma diagnoses should ideally be validated. The primary objectives are to provide an overview of the methods used to validate asthma diagnoses in electronic health records and summarise the results of the validation studies.

METHODS

EMBASE and MEDLINE will be systematically searched for appropriate search terms. The searches will cover all studies in these databases up to October 2016 with no start date and will yield studies that have validated algorithms or codes for the diagnosis of asthma in electronic health records. At least one test validation measure (sensitivity, specificity, positive predictive value, negative predictive value or other) is necessary for inclusion. In addition, we require the validated algorithms to be compared with an external golden standard, such as a manual review, a questionnaire or an independent second database. We will summarise key data including author, year of publication, country, time period, date, data source, population, case characteristics, clinical events, algorithms, gold standard and validation statistics in a uniform table.

ETHICS AND DISSEMINATION

This study is a synthesis of previously published studies and, therefore, no ethical approval is required. The results will be submitted to a peer-reviewed journal for publication. Results from this systematic review can be used to study outcome research on asthma and can be used to identify case definitions for asthma.

PROSPERO REGISTRATION NUMBER

CRD42016041798.

Use of laboratory and administrative data to understand the potential impact of human parainfluenza virus 4 on cases of bronchiolitis, croup, and pneumonia in Alberta, Canada

Background

Human Parainfluenza Virus (hPIV) causes severe respiratory illness in infants and adults. Our study describes the association of hPIV1–4 with bronchiolitis, croup, and pneumonia using retrospective laboratory, administrative and public health data. Due to issues including the historic lack of hPIV4 in some commercial respiratory virus panels, the description of the impact of hPIV4 on croup, bronchiolitis, and pneumonia at population levels has often been limited. This study will use routine clinical laboratory data, and administrative data to provide a preliminary description of the impact of hPIV4 on these diseases in our population.

Methods

A three year cohort of patients positive for hPIV was linked with data from physician visits and hospital admissions to define cases and hospitalization status. International Classification of Disease (ICD-9) codes were used to determine if cases had croup, bronchiolitis, and pneumonia. We also looked at differences in hospitalization status, age and gender among hPIV1–4. All statistical analysis was done using SPSS (Version 19.0.0, IBM Corp© 2010) and Graphpad Prism V6 (GraphPad Software, Inc., 2012).

Results

Only hPIV1 and hPIV4 specimens had positivity rates greater than 5 % of all specimens sent for respiratory virus panel testing. hPIV1 exhibited a biennial pattern while the pattern for hPIV3 was less interpretable due to lower positivity rates. Circulation patterns for hPIV2 and hPIV4 were not assessed due to the low positivity rates of theses specimens. From 2010 to 2013, there were 2300 hPIV cases with hPIV3 (46 %) being the most common, followed by hPIV1 (27 %), hPIV4 (16 %) and hPIV2 (11 %). The median age was 2 years for all hPIV types. Males were slightly greater than females for hPIV1 and hPIV2, with an equal distribution for hPIV3 and slightly more females than males for hPIV4. hPIV1 and hPIV2 had the highest or proportion of croup while hPIV3 and hPIV4 had the highest proportion of pneumonia. Within hPIV4 cases, distributions of diseases were; pneumonia (21 %, 95 % CI 17.1–25.7), bronchiolitis (18 %, 95 % CI 14.3–22.5), croup (2 %, 95 % CI 0.8–3.9), mixed illness of any of pneumonia, bronchiolitis or croup (4 %, 95 % CI 2.5–7.0) or other respiratory diseases (54 %, 95 % CI 49.1–59.6).

Conclusions

We used laboratory and administrative data to undertake a descriptive analysis of the association of hPIV1–4 with croup, bronchiolitis and pneumonia. hPIV4 appears to be more associated more with bronchiolitis and pneumonia and less with croup in our population.

Validation of chronic obstructive pulmonary disease (COPD) diagnoses in healthcare databases: a systematic review protocol

INTRODUCTION

Healthcare databases are useful sources to investigate the epidemiology of chronic obstructive pulmonary disease (COPD), to assess longitudinal outcomes in patients with COPD, and to develop disease management strategies. However, in order to constitute a reliable source for research, healthcare databases need to be validated. The aim of this protocol is to perform the first systematic review of studies reporting the validation of codes related to COPD diagnoses in healthcare databases.

METHODS AND ANALYSIS

MEDLINE, EMBASE, Web of Science and the Cochrane Library databases will be searched using appropriate search strategies. Studies that evaluated the validity of COPD codes (such as the International Classification of Diseases 9th Revision and 10th Revision system; the Real codes system or the International Classification of Primary Care) in healthcare databases will be included. Inclusion criteria will be: (1) the presence of a reference standard case definition for COPD; (2) the presence of at least one test measure (eg, sensitivity, positive predictive values, etc); and (3) the use of a healthcare database (including administrative claims databases, electronic healthcare databases or COPD registries) as a data source. Pairs of reviewers will independently abstract data using standardised forms and will assess quality using a checklist based on the Standards for Reporting of Diagnostic accuracy (STARD) criteria. This systematic review protocol has been produced in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P) 2015 statement.

ETHICS AND DISSEMINATION

Ethics approval is not required. Results of this study will be submitted to a peer-reviewed journal for publication. The results from this systematic review will be used for outcome research on COPD and will serve as a guide to identify appropriate case definitions of COPD, and reference standards, for researchers involved in validating healthcare databases.

TRIAL REGISTRATION NUMBER

CRD42015029204.