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

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.

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Establishing the Incidence and Prevalence of Multiple Sclerosis in Saskatchewan

Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques ◽

10.1017/cjn.2017.301 ◽

2018 ◽

Vol 45 (3) ◽

pp. 295-303 ◽

Cited By ~ 20

Author(s):

Lina H. Al-Sakran ◽

Ruth Ann Marrie ◽

David F. Blackburn ◽

Katherine B. Knox ◽

Charity D. Evans

Keyword(s):

Multiple Sclerosis ◽

Administrative Data ◽

Predictive Value ◽

Disease Surveillance ◽

Population Based ◽

Case Definition ◽

Case Definitions ◽

Health Administrative Data ◽

Disease Surveillance System ◽

Definition Of

AbstractObjective: To validate a case definition of multiple sclerosis (MS) using health administrative data and to provide the first province-wide estimates of MS incidence and prevalence for Saskatchewan, Canada. Methods: We used population-based health administrative data between January 1, 1996 and December 31, 2015 to identify individuals with MS using two potential case definitions: (1) ≥3 hospital, physician, or prescription claims (Marrie definition); (2) ≥1 hospitalization or ≥5 physician claims within 2 years (Canadian Chronic Disease Surveillance System [CCDSS] definition). We validated the case definitions using diagnoses from medical records (n=400) as the gold standard. Results: The Marrie definition had a sensitivity of 99.5% (95% confidence interval [CI] 92.3-99.2), specificity of 98.5% (95% CI 97.3-100.0), positive predictive value (PPV) of 99.5% (95% CI 97.2-100.0), and negative predictive value (NPV) of 97.5% (95% CI 94.4-99.2). The CCDSS definition had a sensitivity of 91.0% (95% CI 81.2-94.6), specificity of 99.0% (95% CI 96.4-99.9), PPV of 98.9% (95% CI 96.1-99.9), and NPV of 91.7% (95% CI 87.2-95.0). Using the more sensitive Marrie definition, the average annual adjusted incidence per 100,000 between 2001 and 2013 was 16.5 (95% CI 15.8-17.2), and the age- and sex-standardized prevalence of MS in Saskatchewan in 2013 was 313.6 per 100,000 (95% CI 303.0-324.3). Over the study period, incidence remained stable while prevalence increased slightly. Conclusion: We confirm Saskatchewan has one of the highest rates of MS in the world. Similar to other regions in Canada, incidence has remained stable while prevalence has gradually increased.

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Improving an Administrative Case Definition for Longitudinal Surveillance of Sickle Cell Disease

Public Health Reports ◽

10.1177/0033354919839072 ◽

2019 ◽

Vol 134 (3) ◽

pp. 274-281 ◽

Cited By ~ 7

Author(s):

Angela B. Snyder ◽

Mei Zhou ◽

Rodney Theodore ◽

Maa-Ohui Quarmyne ◽

James Eckman ◽

...

Keyword(s):

Sickle Cell Disease ◽

Sickle Cell ◽

Predictive Value ◽

International Classification Of Diseases ◽

Population Based ◽

Case Definition ◽

Surveillance Systems ◽

Cell Disease ◽

Case Definitions ◽

Sensitivity Specificity

Objective: Several states are building infrastructure and data collection methods for longitudinal, population-based surveillance systems for selected hemoglobinopathies. The objective of our study was to improve an administrative case definition for sickle cell disease (SCD) to aid in longitudinal surveillance. Methods: We collected data from 3 administrative data sets (2004-2008) on 1998 patients aged 0-21 in Georgia who had ≥1 encounter in which an SCD International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code was recorded, and we compared these data with data from a laboratory and medical record review. We assessed performance (sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) of case definitions that differed by number and type of SCD-coded encounters; addition of SCD-associated treatments, procedures, and complications; and length of surveillance (1 vs 5 years). We identified correct diagnoses for patients who were incorrectly coded as having SCD. Results: The SCD case definition of ≥3 SCD-coded encounters in 5 years simplified and substantially improved the sensitivity (96.0% vs 85.8%) and NPV (68.2% vs 38.2%) of the original administrative case definition developed for 5-year, state-based surveillance (≥2 encounters in 5 years and ≥1 encounter for an SCD-related treatment, procedure, or complication), while maintaining a similar PPV (97.4% vs 97.4%) and specificity (76.5% vs 79.0%). Conclusions: This study supports an administrative case definition that specifies ≥3 ICD-9-CM–coded encounters to identify SCD with a high degree of accuracy in pediatric patients. This case definition can be used to help establish longitudinal SCD surveillance systems.

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Development and Validation of an Administrative Case Definition for Inflammatory Bowel Diseases

Canadian Journal of Gastroenterology ◽

10.1155/2012/278495 ◽

2012 ◽

Vol 26 (10) ◽

pp. 711-717 ◽

Cited By ~ 60

Author(s):

Ali Rezaie ◽

Hude Quan ◽

Richard N Fedorak ◽

Remo Panaccione ◽

Robert J Hilsden

Keyword(s):

Ambulatory Care ◽

Classification System ◽

Predictive Value ◽

Population Based ◽

Case Definition ◽

Administrative Databases ◽

Case Definitions ◽

Health Region ◽

System Database ◽

Inflammatory Bowel

BACKGROUND: A population-based database of inflammatory bowel disease (IBD) patients is invaluable to explore and monitor the epidemiology and outcome of the disease. In this context, an accurate and validated population-based case definition for IBD becomes critical for researchers and health care providers.METHODS: IBD and non-IBD individuals were identified through an endoscopy database in a western Canadian health region (Calgary Health Region, Calgary, Alberta). Subsequently, using a novel algorithm, a series of case definitions were developed to capture IBD cases in the administrative databases. In the second stage of the study, the criteria were validated in the Capital Health Region (Edmonton, Alberta).RESULTS: A total of 150 IBD case definitions were developed using 1399 IBD patients and 15,439 controls in the development phase. In the validation phase, 318,382 endoscopic procedures were searched and 5201 IBD patients were identified. After consideration of sensitivity, specificity and temporal stability of each validated case definition, a diagnosis of IBD was assigned to individuals who experienced at least two hospitalizations or had four physician claims, or two medical contacts in the Ambulatory Care Classification System database with an IBD diagnostic code within a two-year period (specificity 99.8%; sensitivity 83.4%; positive predictive value 97.4%; negative predictive value 98.5%). An alternative case definition was developed for regions without access to the Ambulatory Care Classification System database. A novel scoring system was developed that detected Crohn disease and ulcerative colitis patients with a specificity of >99% and a sensitivity of 99.1% and 86.3%, respectively.CONCLUSION: Through a robust methodology, a reproducible set of criteria to capture IBD patients through administrative databases was developed. The methodology may be used to develop similar administrative definitions for chronic diseases.

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Developing and Validating an Algorithm to Identify Incident Chronic Dialysis Patients Using Administrative Data

10.20944/preprints202005.0101.v1 ◽

2020 ◽

Author(s):

Dino Gibertoni ◽

Claudio Voci ◽

Marica Iommi ◽

Benedetta D'Ercole ◽

Marcora Mandreoli ◽

...

Keyword(s):

Positive Predictive Value ◽

Administrative Data ◽

Predictive Value ◽

Healthcare Providers ◽

High Sensitivity ◽

Case Definition ◽

Chronic Dialysis ◽

Administrative Databases ◽

Dialysis Patients ◽

Case Definitions

Background: Administrative healthcare databases are widespread and are often standardized with regard to their content and data coding, thus they can be used also as data sources for surveillance and epidemiological research. Chronic dialysis requires patients to frequently access hospital and clinic services, causing a heavy burden to healthcare providers. This also means that these patients are routinely tracked on administrative databases, yet very few case definitions for their identification are currently available. The aim of this study was to develop two algorithms derived from administrative data for identifying incident chronic dialysis patients and test their validity compared to the reference standard of the regional dialysis registry. Methods: The algorithms are based on data retrieved from hospital discharge records (HDR) and ambulatory specialty visits (ASV) to identify incident chronic dialysis patients in an Italian region. Subjects are included if they have at least one event in the HDR or ASV databases based on the ICD9-CM dialysis-related diagnosis or procedure codes in the study period. Exclusion criteria comprise non-residents, prevalent cases, or patients undergoing temporary dialysis, and are evaluated only on ASV data by the first algorithm, on both ASV and HDR data by the second algorithm. We validated the algorithms against the Emilia-Romagna regional dialysis registry by searching for incident patients in 2014. Results: Algorithm 1 identified 680 patients and algorithm 2 identified 676 initiating dialysis in 2014, compared to 625 patients included in the regional dialysis registry. Sensitivity for the two algorithms was respectively 90.8% and 88.4%, positive predictive value 84.0% and 82.0%, and percentage agreement was 77.4% and 74.1%. Conclusions: These results suggest that administrative data have high sensitivity and positive predictive value for the identification of incident chronic dialysis patients. Algorithm 1, which showed the higher accuracy and has a simpler case definition, can be used in place of regional dialysis registries when they are not present or sufficiently developed in a region, or to improve the accuracy and timeliness of existing registries.

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Incidence and prevalence of MS in children

Neurology ◽

10.1212/wnl.0000000000006395 ◽

2018 ◽

Vol 91 (17) ◽

pp. e1579-e1590 ◽

Cited By ~ 11

Author(s):

Ruth Ann Marrie ◽

Julia O'Mahony ◽

Colleen Maxwell ◽

Vicki Ling ◽

E. Ann Yeh ◽

...

Keyword(s):

Administrative Data ◽

Predictive Value ◽

Disease Surveillance ◽

Pediatric Population ◽

Case Definition ◽

Health Claims ◽

Healthy Children ◽

Case Definitions ◽

Health Claims Data ◽

Definition Of

ObjectiveTo validate a case definition of multiple sclerosis (MS) in the pediatric population using administrative (health claims) data, and to estimate the incidence and prevalence of MS in the pediatric population for Ontario, Canada.MethodsWe used population-based administrative data to identify persons aged ≤18 years with MS. We assessed the performance of multiple administrative case definitions using a clinical reference cohort including children with MS, children with monophasic demyelinating syndromes, and healthy children; we report sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We applied 2 preferred case definitions to estimate the incidence and prevalence of MS from 2003 to 2014.ResultsThe Canadian Chronic Disease Surveillance System definition of ≥1 hospitalization or ≥5 physician claims for MS within 2 years had a sensitivity of 81.1%, specificity of 100%, PPV of 100%, and NPV of 86%. The Marrie definition of ≥3 hospital or physician claims for MS ever had a sensitivity of 89.2%, specificity of 100%, PPV of 100%, and NPV of 91.5%. Depending on the administrative case definition used, in 2014, the annual age-standardized annual incidence of MS in the pediatric population ranged from 0.99 to 1.24 per 100,000 population, and the age-standardized prevalence ranged from 4.03 to 6.8 per 100,000 population. The prevalence of MS rose over time.ConclusionAdministrative data provide a feasible, valid means of estimating the incidence and prevalence of MS in the pediatric population. MS prevalence in the Ontario pediatric population is among the highest reported in pediatric populations worldwide.

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Population-based data sources for chronic disease surveillance

Chronic Diseases in Canada ◽

10.24095/hpcdp.29.1.04 ◽

2008 ◽

Vol 29 (1) ◽

pp. 31-38 ◽

Cited By ~ 15

Author(s):

L.M. Lix ◽

M.S. Yogendran ◽

S. Shaw ◽

C. Burchill ◽

C. Metge ◽

...

Keyword(s):

Chronic Disease ◽

Survey Data ◽

Administrative Data ◽

Disease Surveillance ◽

Canadian Community Health Survey ◽

Population Based ◽

Case Definition ◽

Data Sources ◽

Case Definitions ◽

Disease Case

This study estimated agreement between population-based administrative and survey data for ascertaining cases of arthritis, asthma, diabetes, heart disease, hypertension and stroke. Chronic disease case definitions that varied by data source, number of years and number of diagnosis or prescription drug codes were constructed from Manitoba's administrative data. These data were linked to the Canadian Community Health Survey. Agreement between the two data sources, estimated by the κ coefficient, was calculated for each case definition, and differences were tested. Socio-demographic and comorbidity variables associated with agreement were tested using weighted logistic regression. Agreement was strongest for diabetes and hypertension and lowest for arthritis. The case definition elements that contributed to the highest agreement between the two population-based data sources varied across the chronic diseases. Low agreement between administrative and survey data is likely to occur for conditions that are difficult to diagnose, but will be mediated by individual socio-demographic and health status characteristics. Construction of a chronic disease case definition from administrative data should be accompanied by a justification for the choice of each of its elements.

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Estimating the incidence of first-episode psychosis using population-based health administrative data to inform early psychosis intervention services

Psychological Medicine ◽

10.1017/s0033291718002933 ◽

2018 ◽

Vol 49 (12) ◽

pp. 2091-2099 ◽

Cited By ~ 8

Author(s):

Kelly K. Anderson ◽

Ross Norman ◽

Arlene G. MacDougall ◽

Jordan Edwards ◽

Lena Palaniyappan ◽

...

Keyword(s):

Psychotic Disorder ◽

Administrative Data ◽

Catchment Area ◽

Population Based ◽

First Episode Psychosis ◽

Case Definition ◽

First Episode ◽

Affective Psychosis ◽

Health Administrative Data ◽

Episode Psychosis

AbstractBackgroundDiscrepancies between population-based estimates of the incidence of psychotic disorder and the treated incidence reported by early psychosis intervention (EPI) programs suggest additional cases may be receiving services elsewhere in the health system. Our objective was to estimate the incidence of non-affective psychotic disorder in the catchment area of an EPI program, and compare this to EPI-treated incidence estimates.MethodsWe constructed a retrospective cohort (1997–2015) of incident cases of non-affective psychosis aged 16–50 years in an EPI program catchment using population-based linked health administrative data. Cases were identified by either one hospitalization or two outpatient physician billings within a 12-month period with a diagnosis of non-affective psychosis. We estimated the cumulative incidence and EPI-treated incidence of non-affective psychosis using denominator data from the census. We also estimated the incidence of first-episode psychosis (people who would meet the case definition for an EPI program) using a novel approach.ResultsOur case definition identified 3245 cases of incident non-affective psychosis over the 17-year period. We estimate that the incidence of first-episode non-affective psychosis in the program catchment area is 33.3 per 100 000 per year (95% CI 31.4–35.1), which is more than twice as high as the EPI-treated incidence of 18.8 per 100 000 per year (95% CI 17.4–20.3).ConclusionsCase ascertainment strategies limited to specialized psychiatric services may substantially underestimate the incidence of non-affective psychotic disorders, relative to population-based estimates. Accurate information on the epidemiology of first-episode psychosis will enable us to more effectively resource EPI services and evaluate their coverage.

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Validating International Classification of Disease 10th revision algorithms for identifying influenza and respiratory syncytial virus hospitalizations

University of Toronto Journal of Public Health ◽

10.33137/utjph.v2i2.37000 ◽

2021 ◽

Vol 2 (2) ◽

Author(s):

Mackenzie A Hamilton ◽

Andrew Calzavara ◽

Scott D Emerson ◽

Jeffrey C Kwong

Keyword(s):

Respiratory Syncytial Virus ◽

Administrative Data ◽

Predictive Value ◽

Hospitalized Patients ◽

International Classification ◽

Health Administrative Data ◽

International Classification Of Disease ◽

Icd 10 ◽

Syncytial Virus

Objective: Routinely collected health administrative data can be used to efficiently assess disease burden in large populations, but it is important to evaluate the validity of these data. The objective of this study was to develop and validate International Classification of Disease 10PthP revision (ICD -10) algorithms that identify laboratory-confirmed influenza or laboratory-confirmed respiratory syncytial virus (RSV) hospitalizations using population-based health administrative data from Ontario, Canada. Study Design and Setting: Influenza and RSV laboratory data from the 2014-15 through to 2017-18 respiratory virus seasons were obtained from the Ontario Laboratories Information System (OLIS) and were linked to hospital discharge abstract data to generate influenza and RSV reference cohorts. These reference cohorts were used to assess the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the ICD-10 algorithms. To minimize misclassification in future studies, we prioritized specificity and PPV in selecting top-performing algorithms. Results: 83,638 and 61,117 hospitalized patients were included in the influenza and RSV reference cohorts, respectively. The best influenza algorithm had a sensitivity of 73% (95% CI 72% to 74%), specificity of 99% (95% CI 99% to 99%), PPV of 94% (95% CI 94% to 95%), and NPV of 94% (95% CI 94% to 95%). The best RSV algorithm had a sensitivity of 69% (95% CI 68% to 70%), specificity of 99% (95% CI 99% to 99%), PPV of 91% (95% CI 90% to 91%) and NPV of 97% (95% CI 97% to 97%). Conclusion: We identified two highly specific algorithms that best ascertain patients hospitalized with influenza or RSV. These algorithms may be applied to hospitalized patients if data on laboratory tests are not available, and will thereby improve the power of future epidemiologic studies of influenza, RSV, and potentially other severe acute respiratory infections.

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Young Adults With Traumatic Brain Injury in Long-Term Care Homes: A Population-Based Study

Brain Impairment ◽

10.1375/brim.11.1.31 ◽

2010 ◽

Vol 11 (1) ◽

pp. 31-36 ◽

Cited By ~ 13

Author(s):

Angela Colantonio ◽

Dana Howse ◽

Jigisha Patel

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Long Term Care ◽

Secondary Data ◽

Population Based ◽

Care Homes ◽

Care Needs ◽

Cross Sectional ◽

Term Care

AbstractThe aim of this research was to identify the number and characteristics of adults under the age of 65 with a diagnosis of traumatic brain injury (TBI) living in long-term care homes (nursing homes, homes for the aged and charitable homes) in Ontario, Canada. Methods: The study used a cross-sectional design. Secondary data analysis of a comprehensive provincial database of long-term care homes was conducted. Results: Of the 399 residents coded as having a TBI, 154 were < 65 years of age. Virtually all residents were limited in personal care and required assistance for eating (94.2%), toileting (92.2%) and dressing (99.4%). A large percentage also required care for challenging behaviours, while care needs due to substance abuse was common among 12.3% of TBI residents. Conclusion: As similar research in Australia has found, young persons in long-term care homes in Ontario, Canada, have high level personal health needs, however the appropriateness of this environment is questionable.

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

BMJ Open ◽

10.1136/bmjopen-2019-033334 ◽

2019 ◽

Vol 9 (11) ◽

pp. e033334 ◽

Cited By ~ 4

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.

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