Incidence and prevalence of MS in children

Neurology ◽  
2018 ◽  
Vol 91 (17) ◽  
pp. e1579-e1590 ◽  
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.

scholarly journals Establishing the Incidence and Prevalence of Multiple Sclerosis in Saskatchewan

2018 ◽  
Vol 45 (3) ◽  
pp. 295-303 ◽  
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.

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

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.

scholarly journals How do we enhance linked administrative data based chronic disease surveillance in Canada? Results of an environmental scan.

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Raquel Duchen ◽  
Lisa Lix ◽  
Kim Reimer ◽  
Jessica Widdifield ◽  
Debra Butt ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Administrative Data ◽  
Disease Surveillance ◽  
Grey Literature ◽  
Case Definition ◽  
Case Definitions ◽  
Standard Case ◽  
Environmental Scan ◽  
Mesh Terms ◽  
Linked Administrative Data

IntroductionThe Canadian Chronic Disease Surveillance System (CCDSS) is a collaboration of provincial and territorial surveillance systems which generates estimates of chronic diseases using linked population-level administrative health databases and standard case definitions. We conducted an environmental scan of administrative data validation studies and identified opportunities for CCDSS case definition enhancement. Objectives and ApproachThe purpose of this project is to develop a methodology for and conduct an environmental scan, identifying opportunities for enhancing the CCDSS. This multifaceted approach consists of the following elements: 1) key informant interviews and stakeholder consultations to identify new and existing priority conditions for updating/validating within the CCDSS, and new areas of conceptual and methodological relevance for administrative data disease surveillance, 2) a systematic literature review of PubMed, Ovid and Embase from 2013-2017 using MeSH terms and a librarian peer-reviewed search strategy, and 3) a review of the grey literature. ResultsKey stakeholders identified the following priorities for validation work and/or case definition enhancement: diabetes, mood and anxiety disorders, schizophrenia, obesity, hypertension, chronic obstructive pulmonary disease, osteoarthritis, stroke, early-onset dementia, rheumatoid arthritis and gout. Scientific and grey literature reviews of validation work for these conditions examined the following concepts/methods: 1) evaluating validity of disease-specific case definitions over time, and in different ages, sub-populations and settings, 2) defining incidence versus prevalence using linked administrative data, 3) determining opportunities and constraints of using linked administrative data to conduct surveillance on diseases that are chronic versus episodic in nature and defining active versus lifetime prevalence, and 4) assessing the feasibility of using new sources of data for linkage to enhance case definition validity. Conclusion/ImplicationsUtilization of linked administrative databases for chronic disease surveillance has expanded across many jurisdictions since the inception of the CCDSS. As disease estimates generated in this manner are increasingly being relied upon by policy makers working to enhance public health, the methodological opportunities and constraints identified here require consideration.

scholarly journals Population-based data sources for chronic disease surveillance

2008 ◽  
Vol 29 (1) ◽  
pp. 31-38 ◽  
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.

P549CIED infection risk score validation using US health claims data

EP Europace ◽  
2020 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
F Z Ahmed ◽  
C Blomstrom Lundqvist ◽  
H Bloom ◽  
C Cooper ◽  
C Ellis ◽  
...  
Keyword(s):  
Risk Score ◽  
Predictive Value ◽  
Claims Data ◽  
Frailty Model ◽  
Infection Risk ◽  
Health Claims ◽  
Validation Dataset ◽  
Data Set ◽  
Device Infection ◽  
Health Claims Data

Abstract Funding Acknowledgements This work was supported by Medtronic Background/Introduction: The increasing number of cardiac implantable electronic device (CIED) infections has led to increased interest in the identification of patients who may benefit from additional infection prevention measures. Purpose The purpose of this evaluation was to validate the predictive value of the Prevention of Arrhythmia Device Infection Trial (PADIT) risk score to identify patients at increased risk of CIED infection using a U.S. health claims data set. Methods A retrospective analysis using the Optum® Clinformatics® claims database was conducted to create a dataset of index procedures which either did or did not result in an infection.  The study population included both commercial and Medicare Advantage patients aged ≥18 years with at least one record of a CIED procedure between January 2011 and September 2014.  Major CIED infections, defined as an infection associated with system removal, invasive procedure without system removal, or death attributable to infection, were identified through diagnosis and procedure codes.  The dataset was randomized (stratified by PADIT score, which included prior procedures, age, depressed renal function, immunocompromised, and procedure type) into a Development Dataset (60%) and a Validation dataset (40%).  A frailty model allowing multiple procedures per patient was fit using the Development Dataset, with PADIT score as the only predictor, excluding patients with prior infection. Prior CIED infection, which was not available in the original PADIT data, was examined for additional predictive value. Results The data extraction resulted in a dataset of 53,554 index procedures among 51,583 patients, with 30,950 patients randomized to the Development Dataset.  The distribution of procedures was pacemakers (52%), ICD (20%), CRT (12%), and Revision/Upgrade (16%), while prior procedures were none (62%), 1 (37%), and 2 (1%). Among patients with no history of prior CIED infection, the frailty model showed that a 1 unit increase in the PADIT score predicts higher infection risk (20%) in the U.S. claims data set (Table 1). Prior CIED infection was associated with strong additional predictive value (HR 4.77, p < 0.0001) after adjusting for PADIT score. Conclusion In the largest external validation of a CIED risk score, the PADIT risk score predicts increased CIED infection risk, identifying higher risk patients that can benefit from targeted interventions to reduce the risk of CIED infection. Prior CIED infection brings additional predictive value to the PADIT score.

Predictive Value of Clinical Diagnostic Codes for the CDC Case Definition of Pelvic Inflammatory Disease (PID)

2003 ◽  
Vol 30 (11) ◽  
pp. 866-870 ◽  
Author(s):  
SYLVIE RATELLE ◽  
DEBORAH YOKOE ◽  
CHRISTINA BLEJAN ◽  
MICHAEL WHELAN ◽  
YUREN TANG ◽  
...  
Keyword(s):  
Pelvic Inflammatory Disease ◽  
Inflammatory Disease ◽  
Predictive Value ◽  
Case Definition ◽  
Diagnostic Codes ◽  
Clinical Diagnostic ◽  
Definition Of

scholarly journals ‘What about the dads?’ Linking fathers and children in administrative data: A systematic scoping review

2022 ◽  
Vol 9 (1) ◽  
pp. 205395172110692
Author(s):  
Irina Lut ◽  
Katie Harron ◽  
Pia Hardelid ◽  
Margaret O’Brien ◽  
Jenny Woodman
Keyword(s):  
Child Health ◽  
Administrative Data ◽  
Scoping Review ◽  
Paternal Involvement ◽  
Personal Identification ◽  
Health Claims ◽  
Address Data ◽  
Health Claims Data ◽  
Health And Development ◽  
The Impact

Research has shown that paternal involvement positively impacts on child health and development. We aimed to develop a conceptual model of dimensions of fatherhood, identify and categorise methods used for linking fathers with their children in administrative data, and map these methods onto the dimensions of fatherhood. We carried out a systematic scoping review to create a conceptual framework of paternal involvement and identify studies exploring the impact of paternal exposures on child health and development outcomes using administrative data. We identified four methods that have been used globally to link fathers and children in administrative data based on family or household identifiers using address data, identifiable information about the father on the child's birth registration, health claims data, and Personal Identification Numbers. We did not identify direct measures of paternal involvement but mapping linkage methods to the framework highlighted possible proxies. The addition of paternal National Health Service numbers to birth notifications presents a way forward in the advancement of fatherhood research using administrative data sources.

Case Definitions for Paediatric AIDS: The Zambian Experience

1993 ◽  
Vol 4 (2) ◽  
pp. 83-85 ◽  
Author(s):  
C Chintu ◽  
A Malek ◽  
M Nyumbu ◽  
C Luo ◽  
J Masona ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Predictive Value ◽  
Clinical Case ◽  
Case Definition ◽  
World Health ◽  
Who Criteria ◽  
Number Of Patients ◽  
Definition Of ◽  
Hiv 1 ◽  
Clinical Case Definition

For the purpose of surveillance of the acquired immunodeficiency syndrome (AIDS) in developing countries, the World Health Organization (WHO) has recommended criteria for the clinical case definition of AIDS in adults and children. In a preliminary examination of children in Zambia a number of patients with obvious AIDS did not fit the published WHO case definition for paediatric AIDS. Based on this the Zambia National AIDS Surveillance Committee designed local criteria for the clinical case definition of paediatric AIDS. We compared the Zambian criteria with the WHO criteria for the diagnosis of paediatric AIDS by studying 134 consecutively admitted children to one of the paediatric wards at the University Teaching Hospital in Lusaka. Twenty-nine of the patients were HIV-1 seropositive and 105 were HIV-1 seronegative. Among the 29 HIV-seropositive patients, the Zambian criteria identified 23, and the WHO criteria identified 20 children as having AIDS. The 105 HIV-seronegative children were classified as having AIDS in 9 cases by the Zambian criteria and in 38 cases by the WHO criteria. These results give the Zambian criteria for the diagnosis of AIDS a sensitivity of 79.3%, a specificity of 91.4% and a positive predictive value of 86.8% compared to a sensitivity of 69%, specificity of 64% and a positive predictive value of 38% for the WHO criteria. The current WHO criteria are inadequate for the diagnosis of paediatric AIDS. The need to refine the WHO criteria for the diagnosis of paediatric AIDS is discussed.

Biomarker validation of a new case definition of menstrual cycleassociated syndrome (MCAS) Opinion Paper

2020 ◽  
Vol 19 ◽  
Author(s):  
Chutima Roomruangwong ◽  
Michael Maes
Keyword(s):  
Menstrual Cycle ◽  
Drug Targets ◽  
False Negative ◽  
Follicular Development ◽  
Case Definition ◽  
Antioxidant Defenses ◽  
Paraoxonase 1 ◽  
Case Definitions ◽  
Chemokine Production ◽  
Definition Of

: There are different case definitions of premenstrual syndrome, one proposed by the American College of Obstetricians and Gynecologists (ACOG) and another based on the Daily Record of Severity of Problems (DRSP) scores. Here we review our recent findings indicating that the gold-standard methods to assess PMS, including ACOG, induce a high degree of false-negative findings. We propose a new case definition of the menstrual cycle-associated syndrome (MCAS), which is characterized by increased DRSP scores during the menstrual cycle and by symptom increases the week prior to the menses. The MCAS case definition was externally validated by diverse biomarkers including plasma levels of progesterone and estradiol, chemokines (e.g. CCL2, CCL5 and CCL11), epidermal growth factor, hydroperoxides, paraoxonase 1 activity and complement C4. These biomarkers as well as IgA responses to Gram-negative bacteria are significantly associated with the DRSP and its subdomains including depression, anxiety, and physiosomatic (fatigue, pain) symptoms. In conclusion, we propose, to a) use the MCAS diagnosis as an indicant of menstrual cycle-related symptoms; and b) examine the associations of the time series in the DRSP and its subdomains and those in biomarkers including distributed lag models. Aberrations in the uterine-chemokine-brain-axis underpin the pathophysiology of MCAS whereby suboptimal pre-ovulatory follicular development coupled with a relative corpus luteum insufficiency may drive increased chemokine production, lowered antioxidant defenses, neuro-oxidative stress pathways, and increased bacterial translocation. As such, we have delineated new drug targets for the treatment of MCAS. This opinion paper reviews new possible treatments that should be trialed in MCAS.

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