scholarly journals A population‐based study to develop juvenile arthritis case definitions for administrative health data using model‐based dynamic classification

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Allison Feely ◽  
Lily SH Lim ◽  
Depeng Jiang ◽  
Lisa M. Lix
Keyword(s):  
Population Based ◽  
Health Data ◽  
Case Definition ◽  
Deterministic Approach ◽  
Deterministic Case ◽  
Dynamic Approach ◽  
Case Definitions ◽  
Classification Approach ◽  
Administrative Health Data ◽  
Model Based

Abstract Background Previous research has shown that chronic disease case definitions constructed using population-based administrative health data may have low accuracy for ascertaining cases of episodic diseases such as rheumatoid arthritis, which are characterized by periods of good health followed by periods of illness. No studies have considered a dynamic approach that uses statistical (i.e., probability) models for repeated measures data to classify individuals into disease, non-disease, and indeterminate categories as an alternative to deterministic (i.e., non-probability) methods that use summary data for case ascertainment. The research objectives were to validate a model-based dynamic classification approach for ascertaining cases of juvenile arthritis (JA) from administrative data, and compare its performance with a deterministic approach for case ascertainment. Methods The study cohort was comprised of JA cases and non-JA controls 16 years or younger identified from a pediatric clinical registry in the Canadian province of Manitoba and born between 1980 and 2002. Registry data were linked to hospital records and physician billing claims up to 2018. Longitudinal discriminant analysis (LoDA) models and dynamic classification were applied to annual healthcare utilization measures. The deterministic case definition was based on JA diagnoses in healthcare use data anytime between birth and age 16 years; it required one hospitalization ever or two physician visits. Case definitions based on model-based dynamic classification and deterministic approaches were assessed on sensitivity, specificity, and positive and negative predictive values (PPV, NPV). Mean time to classification was also measured for the former. Results The cohort included 797 individuals; 386 (48.4 %) were JA cases. A model-based dynamic classification approach using an annual measure of any JA-related healthcare contact had sensitivity = 0.70 and PPV = 0.82. Mean classification time was 9.21 years. The deterministic case definition had sensitivity = 0.91 and PPV = 0.92. Conclusions A model-based dynamic classification approach had lower accuracy for ascertaining JA cases than a deterministic approach. However, the dynamic approach required a shorter duration of time to produce a case definition with acceptable PPV. The choice of methods to construct case definitions and their performance may depend on the characteristics of the chronic disease under investigation.

scholarly journals Model-based methods for case definitions from administrative health data: application to rheumatoid arthritis

BMJ Open ◽  
2017 ◽  
Vol 7 (6) ◽  
pp. e016173 ◽  
Author(s):  
Kristine Kroeker ◽  
Jessica Widdifield ◽  
Saman Muthukumarana ◽  
Depeng Jiang ◽  
Lisa M Lix
Keyword(s):  
Rheumatoid Arthritis ◽  
Health Data ◽  
Case Definitions ◽  
Administrative Health Data ◽  
Model Based ◽  
Data Application

scholarly journals Using Linked Administrative Health Databases for An Obesity Case Definition

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Naomi C Hamm ◽  
Lin Yan ◽  
Lisa M Lix
Keyword(s):  
Primary Care ◽  
Chronic Conditions ◽  
Health Data ◽  
Case Definition ◽  
Income Quintile ◽  
Age Group ◽  
Case Definitions ◽  
Administrative Health Data ◽  
Case Ascertainment ◽  
Primary Care Data

IntroductionCapture of obesity using administrative health data is poor, with many cases being under coded within the data. Linking multiple health data sources may improve case ascertainment and facilitate the use of administrative health data for obesity research and surveillance. Objectives and ApproachThis research aims to determine if using individual-level linked data from multiple sources can improve case ascertainment for obesity in administrative health data. Data from between April 1, 2001 and March 31, 2015 were obtained from the Manitoba Population Data Repository. Eighteen obesity case definitions were developed with different observation times and combinations of diagnosis, procedure, and prescription codes from physician billing claims, hospitalization abstracts, and prescription drug records. Body mass index (BMI) records from primary care data and the Bone Mineral Density (BMD) registry were used for validation. Sensitivity, specificity, and Cohen’s kappa were calculated. ResultsIndividuals with a higher BMI class had more physician visits and were more likely to have comorbidities and obese codes in the administrative health data. A higher BMI class was associated with being in a lower income quintile and the age group 40-59. Overall, the case definitions for obesity had high specificity (0.98-0.99) and low sensitivity (0.005-0.19) when validated using primary care data. Case definitions with obesity codes from multiple databases 3 year prior to and including the index date had the highest sensitivity (0.06-0.19) and kappa (0.04-0.23). Results with the BMD data were similar (specificity: 0.97-0.99; sensitivity: 0.007-0.21). Stratified analyses found agreement measures improved slightly for females, those who had chronic conditions and a later index year, and the age group 40-59. Conclusion / ImplicationsWhen using multiple databases to build a case definition for obesity, sensitivity improves but remains low. Individuals with other chronic conditions and a higher BMI class were more likely to be accurately classified as an obese case.

scholarly journals Recurrent Traumatic Brain Injury Surveillance Using Administrative Health Data: A Bayesian Latent Class Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Oliver Lasry ◽  
Nandini Dendukuri ◽  
Judith Marcoux ◽  
David L. Buckeridge
Keyword(s):  
Measurement Error ◽  
Latent Class ◽  
Severity Index ◽  
Health Data ◽  
Case Definition ◽  
Latent Class Models ◽  
Case Definitions ◽  
Epidemiological Research ◽  
Administrative Health Data ◽  
Injury Burden

Background: The initial injury burden from incident TBI is significantly amplified by recurrent TBI (rTBI). Unfortunately, research assessing the accuracy to conduct rTBI surveillance is not available. Accurate surveillance information on recurrent injuries is needed to justify the allocation of resources to rTBI prevention and to conduct high quality epidemiological research on interventions that mitigate this injury burden. This study evaluates the accuracy of administrative health data (AHD) surveillance case definitions for rTBI and estimates the 1-year rTBI incidence adjusted for measurement error.Methods: A 25% random sample of AHD for Montreal residents from 2000 to 2014 was used in this study. Four widely used TBI surveillance case definitions, based on the International Classification of Disease and on radiological exams of the head, were applied to ascertain suspected rTBI cases. Bayesian latent class models were used to estimate the accuracy of each case definition and the 1-year rTBI measurement-error-adjusted incidence without relying on a gold standard rTBI definition that does not exist, across children (<18 years), adults (18-64 years), and elderly (> =65 years).Results: The adjusted 1-year rTBI incidence was 4.48 (95% CrI 3.42, 6.20) per 100 person-years across all age groups, as opposed to a crude estimate of 8.03 (95% CrI 7.86, 8.21) per 100 person-years. Patients with higher severity index TBI had a significantly higher incidence of rTBI compared to patients with lower severity index TBI. The case definition that identified patients undergoing a radiological examination of the head in the context of any traumatic injury was the most sensitive across children [0.46 (95% CrI 0.33, 0.61)], adults [0.79 (95% CrI 0.64, 0.94)], and elderly [0.87 (95% CrI 0.78, 0.95)]. The most specific case definition was the discharge abstract database in children [0.99 (95% CrI 0.99, 1.00)], and emergency room visits claims in adults/elderly [0.99 (95% CrI 0.99, 0.99)]. Median time to rTBI was the shortest in adults (75 days) and the longest in children (120 days).Conclusion: Conducting accurate surveillance and valid epidemiological research for rTBI using AHD is feasible when measurement error is accounted for.

scholarly journals Validation of a Case Definition for Pediatric Brain Injury Using Administrative Data

2017 ◽  
Vol 44 (2) ◽  
pp. 161-169 ◽  
Author(s):  
Jane McChesney-Corbeil ◽  
Karen Barlow ◽  
Hude Quan ◽  
Guanmin Chen ◽  
Samuel Wiebe ◽  
...  
Keyword(s):  
Brain Injury ◽  
Administrative Data ◽  
Predictive Value ◽  
External Validation ◽  
Secondary Data ◽  
Population Based ◽  
Case Definition ◽  
Case Definitions ◽  
Icd 10 ◽  
Pediatric Tbi

AbstractBackground: Health administrative data are a common population-based data source for traumatic brain injury (TBI) surveillance and research; however, before using these data for surveillance, it is important to develop a validated case definition. The objective of this study was to identify the optimal International Classification of Disease , edition 10 (ICD-10), case definition to ascertain children with TBI in emergency room (ER) or hospital administrative data. We tested multiple case definitions. Methods: Children who visited the ER were identified from the Regional Emergency Department Information System at Alberta Children’s Hospital. Secondary data were collected for children with trauma, musculoskeletal, or central nervous system complaints who visited the ER between October 5, 2005, and June 6, 2007. TBI status was determined based on chart review. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each case definition. Results: Of 6639 patients, 1343 had a TBI. The best case definition was, “1 hospital or 1 ER encounter coded with an ICD-10 code for TBI in 1 year” (sensitivity 69.8% [95% confidence interval (CI), 67.3-72.2], specificity 96.7% [95% CI, 96.2-97.2], PPV 84.2% [95% CI 82.0-86.3], NPV 92.7% [95% CI, 92.0-93.3]). The nonspecific code S09.9 identified >80% of TBI cases in our study. Conclusions: The optimal ICD-10–based case definition for pediatric TBI in this study is valid and should be considered for future pediatric TBI surveillance studies. However, external validation is recommended before use in other jurisdictions, particularly because it is plausible that a larger proportion of patients in our cohort had milder injuries.

scholarly journals Existing comorbidities in people with osteoarthritis: a retrospective analysis of a population-based cohort in Alberta, Canada

BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e033334 ◽  
Author(s):  
Deborah A Marshall ◽  
Xiaoxiao Liu ◽  
Cheryl Barnabe ◽  
Karen Yee ◽  
Peter D Faris ◽  
...  
Keyword(s):  
Cohort Analysis ◽  
Age Groups ◽  
Population Based ◽  
Case Definition ◽  
Chronic Obstructive ◽  
Age Group ◽  
Case Definitions ◽  
Obstructive Pulmonary Disease ◽  
Physician Visits ◽  
Significant Difference

ObjectivesThe purpose of this study is to estimate the prevalence of comorbidities among people with osteoarthritis (OA) using administrative health data.DesignRetrospective cohort analysis.SettingAll residents in the province of Alberta, Canada registered with the Alberta Health Care Insurance Plan population registry.Participants497 362 people with OA as defined by ‘having at least one OA-related hospitalization, or at least two OA-related physician visits or two ambulatory care visits within two years’.Primary outcome measuresWe selected eight comorbidities based on literature review, clinical consultation and the availability of validated case definitions to estimate their frequencies at the time of diagnosis of OA. Sex-stratified age-standardised prevalence rates per 1000 population of eight clinically relevant comorbidities were calculated using direct standardisation with 95% CIs. We applied χ2 tests of independence with a Bonferroni correction to compare the percentage of comorbid conditions in each age group.Results54.6% (n=2 71 794) of people meeting the OA case definition had at least one of the eight selected comorbidities. Females had a significantly higher rate of comorbidities compared with males (standardised rates ratio=1.26, 95% CI 1.25 to 1.28). Depression, chronic obstructive pulmonary disease (COPD) and hypertension were the most prevalent in both females and males after age-standardisation, with 40% of all cases having any combination of these comorbidities. We observed a significant difference in the percentage of comorbidities among age groups, illustrated by the youngest age group (<45 years) having the highest percentage of cases with depression (24.6%), compared with a frequency of 16.1% in those >65 years.ConclusionsOur findings highlight the high frequency of comorbidity in people with OA, with depression having the highest age-standardised prevalence rate. Comorbidities differentially affect females, and vary by age. These factors should inform healthcare programme and delivery.

Definitions of medication-overuse headache in population-based studies and their implications on prevalence estimates: A systematic review

Cephalalgia ◽  
2013 ◽  
Vol 34 (6) ◽  
pp. 409-425 ◽  
Author(s):  
Maria L Westergaard ◽  
Ebba Holme Hansen ◽  
Charlotte Glümer ◽  
Jes Olesen ◽  
Rigmor H Jensen
Keyword(s):  
Medication Overuse ◽  
Medication Overuse Headache ◽  
Large Population ◽  
Population Based ◽  
Case Definition ◽  
Practical Case ◽  
Case Definitions ◽  
Wide Range ◽  
Concurrent Medication ◽  
Over Time

Background Case definitions of medication-overuse headache (MOH) in population-based research have changed over time. This study aims to review MOH prevalence reports with respect to these changes, and to propose a practical case definition for future studies based on the ICHD-3 beta. Methods A systematic literature search was conducted to identify MOH prevalence studies. Findings were summarized according to diagnostic criteria. Results Twenty-seven studies were included. The commonly used case definition for MOH was headache ≥15 days/month with concurrent medication overuse ≥3 months. There were varying definitions for what was considered as overuse. Studies that all used ICHD-2 criteria showed a wide range of prevalence among adults: 0.5%–7.2%. Conclusions There are limits to comparing prevalence of MOH across studies and over time. The wide range of reported prevalence might not only be due to changing criteria, but also the diversity of countries now publishing data. The criterion “headache occurring on ≥15 days per month” with concurrent medication overuse can be applied in population-based studies. However, the new requirement that a respondent must have “a preexisting headache disorder” has not been previously validated. Exclusion of other headache diagnoses by expert evaluation and ancillary examinations is not feasible in large population-based studies.

Development and validation of a case definition for epilepsy for use with administrative health data

2012 ◽  
Vol 102 (3) ◽  
pp. 173-179 ◽  
Author(s):  
Aylin Y. Reid ◽  
Christine St.Germaine-Smith ◽  
Mingfu Liu ◽  
Shahnaz Sadiq ◽  
Hude Quan ◽  
...  
Keyword(s):  
Health Data ◽  
Case Definition ◽  
Administrative Health Data ◽  
Development And Validation

Systemic Autoimmune Rheumatic Disease Prevalence in Canada: Updated Analyses Across 7 Provinces

2014 ◽  
Vol 41 (4) ◽  
pp. 673-679 ◽  
Author(s):  
Laurel Broten ◽  
J. Antonio Aviña-Zubieta ◽  
Diane Lacaille ◽  
Lawrence Joseph ◽  
John G. Hanly ◽  
...  
Keyword(s):  
Rheumatic Disease ◽  
Lupus Erythematosus ◽  
Latent Class ◽  
Population Based ◽  
Case Definition ◽  
Case Definitions ◽  
Autoimmune Rheumatic Disease ◽  
Primary Sjögren Syndrome ◽  
Physician Billing ◽  
Systemic Autoimmune Rheumatic Disease

Objective.To estimate systemic autoimmune rheumatic disease (SARD) prevalence across 7 Canadian provinces using population-based administrative data evaluating both regional variations and the effects of age and sex.Methods.Using provincial physician billing and hospitalization data, cases of SARD (systemic lupus erythematosus, scleroderma, primary Sjögren syndrome, polymyositis/dermatomyositis) were ascertained. Three case definitions (rheumatology billing, 2-code physician billing, and hospital diagnosis) were combined to derive a SARD prevalence estimate for each province, categorized by age, sex, and rural/urban status. A hierarchical Bayesian latent class regression model was fit to account for the imperfect sensitivity and specificity of each case definition. The model also provided sensitivity estimates of different case definition approaches.Results.Prevalence estimates for overall SARD ranged between 2 and 5 cases per 1000 residents across provinces. Similar demographic trends were evident across provinces, with greater prevalence in women and in persons over 45 years old. SARD prevalence in women over 45 was close to 1%. Overall sensitivity was poor, but estimates for each of the 3 case definitions improved within older populations and were slightly higher for men compared to women.Conclusion.Our results are consistent with previous estimates and other North American findings, and provide results from coast to coast, as well as useful information about the degree of regional and demographic variations that can be seen within a single country. Our work demonstrates the usefulness of using multiple data sources, adjusting for the error in each, and providing estimates of the sensitivity of different case definition approaches.

Sarcoidosis incidence and prevalence: a nationwide register-based assessment in Sweden

2016 ◽  
Vol 48 (6) ◽  
pp. 1690-1699 ◽  
Author(s):  
Elizabeth V. Arkema ◽  
Johan Grunewald ◽  
Susanna Kullberg ◽  
Anders Eklund ◽  
Johan Askling
Keyword(s):  
Population Based ◽  
Education Level ◽  
Case Definition ◽  
Case Definitions ◽  
Swedish Population ◽  
Individual Level ◽  
Level Data ◽  
National Patient ◽  
History Of ◽  
Dispensing Data

Our objective was to estimate the contemporary incidence and prevalence of sarcoidosis using Swedish population-based register data.Adults with any sarcoidosis-coded visit were identified from the National Patient Register (hospitalisations 1964–2013 and outpatient care 2001–2013). Demographic and medication dispensing data were retrieved from national registers. We estimated the prevalence of sarcoidosis in 2013 overall and by county of residence. The incidence of sarcoidosis during 2003–2012 was estimated by sex, age, education level and year of diagnosis. Case definitions were varied to test their robustness.More than 16 000 individuals had a history of sarcoidosis in 2013. When defined as two or more sarcoidosis-coded visits, the prevalence was 160 per 100 000. Using different definitions, the prevalence ranged from 152 (requiring a specialist visit) to 215 per 100 000 (only one visit required). The highest prevalence was observed in northern less densely populated counties. The incidence was 11.5 per 100 000 per year and varied by −10% to +30% depending on case definition. The incidence peaked in males aged 30–50 years and in females aged 50–60 years, but did not differ by education level and was stable over time.This study represents the largest epidemiological investigation of sarcoidosis using population-based individual-level data. Age at diagnosis in men was 10 years younger than in women and geographical variation was observed.

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