{"http:\/\/dx.doi.org\/10.14288\/1.0435770":{"http:\/\/vivoweb.org\/ontology\/core#departmentOrSchool":[{"value":"Medicine, Faculty of","type":"literal","lang":"en"},{"value":"Non UBC","type":"literal","lang":"en"},{"value":"Pediatrics, Department of","type":"literal","lang":"en"}],"http:\/\/www.europeana.eu\/schemas\/edm\/dataProvider":[{"value":"DSpace","type":"literal","lang":"en"}],"https:\/\/open.library.ubc.ca\/terms#identifierCitation":[{"value":"Allergy, Asthma & Clinical Immunology. 2023 May 28;19(1):46","type":"literal","lang":"en"}],"https:\/\/open.library.ubc.ca\/terms#rightsCopyright":[{"value":"The Author(s)","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/creator":[{"value":"Stirton, Hannah","type":"literal","lang":"en"},{"value":"Kosowan, Leanne","type":"literal","lang":"en"},{"value":"Abrams, Elissa M.","type":"literal","lang":"en"},{"value":"Protudjer, Jennifer L. P.","type":"literal","lang":"en"},{"value":"Queenan, John","type":"literal","lang":"en"},{"value":"Singer, Alexander","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/issued":[{"value":"2023-09-07T21:20:05Z","type":"literal","lang":"en"},{"value":"2023-05-28","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/description":[{"value":"To validate case definitions for eczema using primary care Electronic Medical Record (EMR) data from the Canadian Primary Care Sentential Surveillance Network (CPCSSN).\r\n                This study used EMR data from 1,574 primary care providers in seven Canadian provinces, representing 689,301 patients. Using a subset of patient records seven medical students or family medicine residents created a reference set of 1,772 patients. A total of 23 clinician-informed case definitions were validated against the reference. We assessed agreement using sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV) and overall accuracy. The case definitions with the best agreement statistics were deployed to estimate the prevalence of eczema in the CPCSSN.\r\n                Case definition 1 had the highest SE (92.1%,85.0-96.5) but a lower SP (88.5%,86.7\u201390.1) and PPV (36.6%,33.1\u201340.3). Case definition 7 was the most specific case definition with a SP (99.8%, 99.4\u2013100) and PPV (84.2%,61.2\u201394.7) but low SE (15.8%,9.3\u201324.5). Case definition 17 had a SE (75.3%, 65.7\u201383.3), SP (93.8%, 91.5\u201394.3) and PPV 43.7% (38.3\u201349.2). When we applied the most specific and most sensitive case definitions, we estimate the prevalence of eczema to be between 0.8 and 15.1%. Case definition 17 suggests an eczema prevalence estimate of 8.2% (8.08\u20138.21%).\r\n                We validated EMR-based eczema case definitions to estimate the prevalence of clinician-documented eczema. Future studies may choose to apply one or more of these definitions\u2019 dependent on their studies objectives to inform disease surveillance as well as explore burden of illness or interventions related to eczema care in Canada.","type":"literal","lang":"en"}],"http:\/\/www.europeana.eu\/schemas\/edm\/aggregatedCHO":[{"value":"https:\/\/circle.library.ubc.ca\/rest\/handle\/2429\/85871?expand=metadata","type":"literal","lang":"en"}],"http:\/\/www.w3.org\/2009\/08\/skos-reference\/skos.html#note":[{"value":"R E S E A R C H Open Access\u00a9 The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article\u2019s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article\u2019s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:\/\/creativecommons.org\/licenses\/by\/4.0\/. The Creative Commons Public Domain Dedication waiver (http:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.Stirton et al. Allergy, Asthma & Clinical Immunology           (2023) 19:46 https:\/\/doi.org\/10.1186\/s13223-023-00785-4Allergy, Asthma & Clinical Immunology*Correspondence:Alexander Singeralexander.singer@umanitoba.ca1Division of Dermatology, Department of Medicine, University of Toronto, Toronto, ON, Canada2Department of Family Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada3Department of Pediatrics, Section of Allergy and Clinical Immunology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada4Department of Pediatrics, Division of Allergy and Immunology, University of British Columbia, Vancouver, BC, Canada5Department of Pediatrics and Child Health, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada6Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden7Department of Family Medicine, Queens University, Kingston, Ontario, CanadaAbstractBackground To validate case definitions for eczema using primary care Electronic Medical Record (EMR) data from the Canadian Primary Care Sentential Surveillance Network (CPCSSN).Methods This study used EMR data from 1,574 primary care providers in seven Canadian provinces, representing 689,301 patients. Using a subset of patient records seven medical students or family medicine residents created a reference set of 1,772 patients. A total of 23 clinician-informed case definitions were validated against the reference. We assessed agreement using sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV) and overall accuracy. The case definitions with the best agreement statistics were deployed to estimate the prevalence of eczema in the CPCSSN.Results Case definition 1 had the highest SE (92.1%,85.0-96.5) but a lower SP (88.5%,86.7\u201390.1) and PPV (36.6%,33.1\u201340.3). Case definition 7 was the most specific case definition with a SP (99.8%, 99.4\u2013100) and PPV (84.2%,61.2\u201394.7) but low SE (15.8%,9.3\u201324.5). Case definition 17 had a SE (75.3%, 65.7\u201383.3), SP (93.8%, 91.5\u201394.3) and PPV 43.7% (38.3\u201349.2). When we applied the most specific and most sensitive case definitions, we estimate the prevalence of eczema to be between 0.8 and 15.1%. Case definition 17 suggests an eczema prevalence estimate of 8.2% (8.08\u20138.21%).Conclusions We validated EMR-based eczema case definitions to estimate the prevalence of clinician-documented eczema. Future studies may choose to apply one or more of these definitions\u2019 dependent on their studies objectives to inform disease surveillance as well as explore burden of illness or interventions related to eczema care in Canada.Keywords Eczema, Primary Health Care, Electronic Health RecordsValidation of a primary care electronic medical records case definition for eczema: retrospective cross-sectional studyHannah Stirton1,2, Leanne Kosowan2, Elissa M Abrams3,4, Jennifer LP Protudjer5,6, John Queenan7 and Alexander Singer2*Page 2 of 11Stirton et al. Allergy, Asthma & Clinical Immunology           (2023) 19:46 BackgroundEczema (atopic dermatitis) is a common inflammatory skin disease characterized by intense pruritus, xerosis and recurrent eczematous lesions [1]. The prevalence of eczema is increasing globally making it the most burden-some skin disorder worldwide [2\u20136]. The pathophysiol-ogy of eczema involves complex interactions between genetics and the immune system interacting with envi-ronmental and infectious agents [7]. Eczema is the ini-tial step in the \u201catopic triad\u201d (i.e. a person with eczema, asthma and allergic rhinitis). Having eczema increases the risk of having other atopic conditions such as asthma and allergic rhinitis [7]. There is also a known association between eczema and food allergy [7] as well as several non-atopic conditions including depression, anxiety, and attention deficit hyperactivity disorder (ADHD) [5, 6, 8]. Risk factors for developing eczema include a family his-tory of atopy, female sex, Black race, and high socioeco-nomic status [1, 7, 9\u201314]. A worldwide study found that eczema affects approximately 5\u201320% of children [15]. While traditionally thought of as a childhood disease, recent evidence suggests eczema in adults is common [13, 16, 17].There are several features of eczema that make its epi-demiology challenging to study, such as non-standardized nomenclature, variable morphology and heterogenous skin lesion distribution [12]. Thus far, most research on eczema has largely relied on survey data. Due to the com-plexity and diversity of this disease the true prevalence of eczema may be over- or underestimated. Application of a validated case definition to large representative datasets can provide primary care provider diagnosed prevalence estimates that can increase our current understand-ing of risk factors and comorbidities of eczema. Several prior studies have attempted to use Hanifin\u2019s and Raja-kin\u2019s criteria and\/or the UK Working Group criteria for diagnosing atopic dermatitis [18\u201321]. Previous litera-ture [18\u201321] has focused on specific ICD-9 codes within a specific cohort of patients. Building on this work we test and validate possible definitions of eczema using both specific and less specific diagnostic coding applied to data derived from 11 different Canadian primary care EMRs. We aimed to include definitions that would range from being highly specific but potentially less sensitive, to highly sensitive and less specific.MethodsStudy designWe conducted a retrospective cross-sectional study to develop and validate an EMR-based case definition for eczema. Using EMR medical record review we created a reference set for validation. Case definitions were applied within a pan-Canadian representative patient population [22]. We used the checklist of reporting criteria for vali-dation studies [23].SettingThis study used de-identified EMR data from 1,574 pri-mary care providers participating in the Canadian Pri-mary Care Sentinel Surveillance Network (CPCSSN). These family physicians, nurse practitioners and com-munity pediatricians are located across seven Canadian provinces, British Columbia, Alberta, Manitoba, Ontario, Quebec, Nova Scotia, and Newfoundland and Labrador. There were 11 EMR vendors represented in this data extract.Data sourcesThe CPCSSN generates a pan-Canadian repository using EMR data extracted and processed from each provincial network. CPCSSN captures longitudinal primary care EMR data representing > 1,800,000 Canadians. Data are included for all patients that attend an appointment with a consenting provider. Patients do have the option to opt-out of CPCSSN upon request. The data in the CPCSSN repository is processed using computerized coding and cleaning algorithms [24\u201326]. During the data cleaning process, invalid entries are deleted, and the data are stan-dardized to map prescribed medications to Anatomical Therapeutic Chemical (ATC) Classification codes, labo-ratory variable names to Logical Observation Identifiers Names and Codes (LOINC) codes, and medical diag-noses to International Classification of Disease, ninth edition, clinical modification (ICD-9-CM) codes. The repository includes both structured data fields as well as short-text fields with diagnoses, medications, allergies, and risk factors. Regionally some provincial networks hold free-text encounter notes. A de-identification pro-cess is applied to all free text to render the data anony-mized. This study accessed the billing, health condition (problem list), encounter diagnosis, medication, allergy, patient, and provider tables from the CPCSSN reposi-tory as well as free-text data from the Manitoba regional network.ParticipantsWe utilized EMR records for active patients, defined as those with at least one appointment between January 1, 2017, and December 31, 2019 [27]. There were 689,301 active patients in CPCSSN with health records from inception of the EMR to December 31, 2019.Reference datasetWe created a sub-set of CPCSSN patient records for medical records review. Medical record review was per-formed by seven medical students and family medi-cine residents. Medical students\/residents reviewed Page 3 of 11Stirton et al. Allergy, Asthma & Clinical Immunology           (2023) 19:46 encounter notes and clinician free-text entries in the health condition, billing, encounter diagnosis tables for patients with an ICD-9-CM code 691 (atopic dermatitis and related conditions), or 692 (contact dermatitis and other eczema) in the EMR (n = 358,560 encounter notes, 2,292 free-text entries) to create a positive reference set. Medical students\/residents reviewed an additional 27,630 randomly selected records to create a negative ref-erence set. This created a reference set of 2,484 patients (Fig.\u00a01). The reference standard used for algorithm devel-opment assigned each patient as positive, negative or unsure for a diagnosis of eczema [21]. Two students\/residents reviewed each set of records, and discrepancies between the students\/residents were reviewed by a family Fig. 1 Flow diagram for creation of the eczema reference set from the Canadian Primary Care Research Network (CPCSSN) Page 4 of 11Stirton et al. Allergy, Asthma & Clinical Immunology           (2023) 19:46 physician or allergist. There were 51 patients excluded due to an inability to differentiate between eczema and other rashes using eczema diagnostic criteria [21], and another 661 patients removed because they did not have an appointment in the previous two years [27]. Our final reference set had 1,772 patients (101 positive, and 1,671 negative) (Fig.\u00a01). Studies from the US have suggested a prevalence rate of 7% [12, 13, 16] we therefore randomly excluded 275 patients producing our validation set of 1,496 (101 positive, 1,395 negative). We included data on each patient including province, age, and sex. Patient age was calculated at the index date of December 31, 2019. To create a test data set we matched positive and nega-tive cases at a 1:3 ratio using province, sex and age creat-ing a dataset of 408 patients (101 positive, 307 negative) (Fig.\u00a01).Case definitionsCase definitions were developed by clinicians and researchers to include ICD-9-CM and ATC codes found in the health condition, billing, encounter diagnoses and medication tables (Table 1). Case definitions were informed by diagnostic criteria [21], and previous case validation studies [18\u201320]. ICD-9-CM 691.8 is specific for eczema. However, some providers may use the code 692.9 (contact dermatitis and other eczema, unspecific cause) [18] or less specific codes (691 (atopic dermati-tis and related conditions), 692 (contact dermatitis and other eczema)) with or without sub-codes. Diagnostic criteria and previous studies suggest an association with atopic conditions and allergy [18\u201321]. We assessed the health conditions, billing and encounter diagnosis tables for indications of asthma (ICD-9-CM 493) [25], or rhini-tis\/hay fever (ICD-9-CM 472, 477) [26]. Within the EMR, primary care providers can indicate with short-text if the patient has an allergy. We applied a previously validated algorithm to identify patients with documentation of an allergy in the EMR [26, 27]. Allergy documentation in the EMR may reference a specific allergy such as a drug, food, stinging insect, vaccine, environment, or other allergy [26, 27]. We assessed prescriptions for topical eczema medications (ATC: D07, D02A, D11AH) [28].Statistical analysisWe assessed agreement between each of the case defini-tions and the two reference sets (test and validation) with several metrics including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy. The equations for these metrics are presented below. PPVTPTP+FP SensitivityTPTP+FN NPVTNTN+FN SpecificityTNTN+FP AccuracyTP+TNTP+FP+FN+TNTP: true positive, FP: false positive, FN: false negative, FP: false positive The prevalence and 95% confidence limits were com-puted using an exact binomial test. We assessed asso-ciations between case definition capture and patient characteristics including age, sex, atopic comorbidities and medication using chi-square, and t-test. Significance was assessed at 0.05. Statistical analyses were conducted using SAS V9.4 (SAS Institute Inc, Cary, NC).ResultsThe final reference set included positive and negative cases from the following Canadian provinces: Brit-ish Columbia, Alberta, Manitoba, Ontario, Quebec. In the test set there were 101 positive and 307 negative patients matched using province, sex and age. Positive and negative cases were not significantly different based on, urban or rural location (0.6287), or annual visit fre-quency (0.8366). We assessed the agreement between our reference set and twenty-three case definitions (Table 1). Eczema-specific ICD-9-CM codes 691.8 and 692.9 had low sensitivity and high specificity. Case definition 7 (ICD-9-CM 691.8) had a sensitivity 15.8% and specific-ity 100% (Table\u00a02). ICD-9-CM 691.8 or 692.9 (case defi-nition 13) had a sensitivity 59.4%, and specificity 94.1%. Inclusion of related but less specific codes demonstrated an overall improvement in capture. Case definition 1 included all related ICD-9-CM codes with a sensitivity 92.1%, specificity 91.9%, PPV 78.8% and NPV 97.2%. Case definitions 14 and 17 saw improvements in specificity (93.8% and 93.8%) and PPV (82.1% and 80.0%) compared to case definition 1\u00a0(Table 2). Incorporating medications that can be used to treat eczema and related atopic con-ditions did not improve agreement.In the validation set there were 101 positive and 1395 negative patients representing an eczema prevalence of 6.8%. Positive cases were significantly more likely to be female compared to male (0.0076). However, urban vs. rural residency (0.4427), age (0.89) or annual visit fre-quency (0.365) were not significantly different. Case definition 7 (ICD-9-CM 691.8) had a strong specificity 99.8% and PPV 84.2% but low sensitivity 15.8%. All other case definitions had a low PPV including case definition 13 (ICD-9-CM 691.8, 692.9) with a PPV of 41.4%. Case Page 5 of 11Stirton et al. Allergy, Asthma & Clinical Immunology           (2023) 19:46 Case definition DescriptionCase definition 1 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM code starting with 691.xx or 692.xxCase definition 1b \u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM code 691 or 692Case definition 2 \u2265 1 health condition for 3-digit ICD-9-CM code 691, 692OR\u2265 2 billing\/Encounter Diagnosis for 3-digit ICD-9-CM code 691, 692Case definition 3 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM code starting with 691.xx or 692.xxOR\u2265 1 medication for ATC code starting with D07, D02A, D11AHCase definition 4 \u2265 1 health condition for ICD-9-CM code starting with 691.xx, 692.xxOR\u2265 2 billing encounter diagnosis for ICD-9-CM starting with 691.xx, 692.xxOR\u2265 1 medication for ATC code starting with D07, D02A, D11AHCase definition 5 \u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM 691Case definition 6 \u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM 692Case definition 7 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8Case definition 8 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8OR\u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM 691, 692Case definition 9 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8OR\u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM 691, 692AND\u2265 1 medication for ATC code starting with D07, D02A, D11AHCase definition 10 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8OR\u2265 1 medication for ATC code starting with D07, D02A, D11AHCase definition 11 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8 or 692.9OR\u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM 691, 692AND\u2265 1 medication for ATC code starting with D07, D02A, D11AHCase definition 12 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8 or 692.9OR\u2265 1 medication for ATC code starting with D07, D02A, D11AHCase definition 13 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8 or 692.9Case definition 14 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8 or 692.9OR\u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM 691 or 692Case definition 15 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM code starting with 691.xx or 692.xxAND\u2265 1 health condition, billing or encounter diagnosis for atopy condition ICD-9-CM starting with 493.xx (asthma) or 472.xx\/477.xx (rhinitis\/hay fever)OR\u2265 1 allergy documented in the allergy table of the EMRCase definition 16 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM code starting with 691.xx or 692.xxAND\u2265 1 health condition, billing or encounter diagnosis for atopy condition ICD-9-CM starting with 493.xx (asthma) or 472.xx\/477.xx (rhinitis\/hay fever)OR\u2265 1 food allergy documented in the allergy table of the EMRCase definition 17 \u2265 1 health condition for 3-digit ICD-9-CM code 691 or 692OR\u2265 2 billing\/Encounter Diagnosis for 3-digit ICD-9-CM code 691 or 692OR\u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8 or 692.9Table 1 EMR-based Case Definitions for Identification of EczemaPage 6 of 11Stirton et al. Allergy, Asthma & Clinical Immunology           (2023) 19:46 definition 1 had a sensitivity 92.1%, specificity 88.5%, PPV 36.6%, NPV 99.4% and accuracy 88.7%. Case definition 14 and 17 demonstrated slight decreases in sensitivity (86.1%, 75.3%) but increases in specificity (89.5%, 93.0%), PPV (37.3%, 43.7%), and accuracy (89.3%, 91.8%)\u00a0 (Table 3). Incorporating medications that can be used to treat eczema and related atopic conditions did not improve our case definitions.Within the CPCSSN dataset of 689,301 active patients, the estimated prevalence of eczema ranged from 0.8% (0.79\u20130.83%) in our most specific definition to 15.1% (15.05\u201315.22%) in our most liberal definition (Table\u00a0 4). Case definition 17 estimates a lifetime prevalence of 8.2% Case definition DescriptionCase definition 18 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8 or 692.9OR\u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM code starting with 691.xx or 692.xxAND\u2265 1 health condition, billing or encounter diagnosis for atopy condition ICD-9-CM starting with 493.xx (asthma) or 472.xx\/477.xx (rhinitis\/hay fever)OR\u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM code starting with 691.xx or 692.xxAND\u2265 1 allergy documented in the allergy table of the EMRCase definition 19 \u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM code 691 or 692AND\u2265 1 health condition, billing or encounter diagnosis for atopy condition ICD-9-CM starting with 493.xx (asthma), or 472.xx\/477.xx (rhinitis\/hay fever)OR\u2265 1 allergy documented in the allergy table of the EMRCase definition 20 \u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM code 691 or 692AND\u2265 1 health condition, billing or encounter diagnosis for atopy condition ICD-9-CM starting with 493.xx (asthma), or 472.xx\/477.xx (rhinitis\/hay fever)OR\u2265 1 food allergy documented in the allergy table of the EMRCase definition 21 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8 or 692.9OR\u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM code 691 or 692AND\u2265 1 health condition, billing or encounter diagnosis for atopy condition ICD-9-CM starting with 493.xx (asthma), or 472.xx\/477.xx (rhinitis\/hay fever)OR\u2265 1 allergy documented in the allergy table of the EMRCase definition 22 \u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM code 691 or 692AND\u2265 1 health condition, billing or encounter diagnosis for atopy condition ICD-9-CM starting with 493.xx (asthma), or 472.xx\/477.xx (rhinitis\/hay fever)OR\u2265 1 allergy documented in the allergy table of the EMROR\u2265 1 medication for ATC code starting with D07, D02A, D11AHCase definition 23 \u2265 1 health condition, billing or encounter diagnosis for ICD-9-CM 691.8 or 692.9OR\u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM code 691 or 692AND\u2265 1 health condition, billing or encounter diagnosis for atopy condition ICD-9-CM starting with 493.xx (asthma), or 472.xx\/477.xx (rhinitis\/hay fever)OR\u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM code 691 or 692AND\u2265 1 allergy documented in the allergy table of the EMROR\u2265 1 health condition, billing or encounter diagnosis for 3-digit ICD-9-CM code 691 or 692AND\u2265 1 medication for ATC code starting with D07, D02A, D11AHTable 1 (continued) Page 7 of 11Stirton et al. Allergy, Asthma & Clinical Immunology           (2023) 19:46 (8.08\u20138.21%). Inclusion of atopic conditions and medica-tions (case definition 23) suggested a prevalence of 9.8% (9.71\u20139.85%). Application of the case definitions with the strongest metrics suggests patients captured were significantly more likely to be female, prescribed a medi-cation that can treat eczema and have asthma or rhinitis (Table\u00a04). Interestingly, patients with eczema in case defi-nition 7, 13 or 17 were less likely to have an allergy docu-mented in the EMR.DiscussionWe validated case definitions for eczema in the CPCSSN repository of primary care patients. Using the EMR-based case definitions suggests a prevalence of eczema between 0.8 and 15.1% comparable to prior study esti-mates [12, 13, 16, 29]. Multiple US surveys suggest the adult prevalence of eczema to be 7.0% [12, 13, 16, 30, 31]. In our study case definition 17 suggests a slightly higher lifetime prevalence of 8.2%.Table 2 Validation of Eczema Case Definitions in the Test Dataset n = 408Case DefinitionTrue PositiveTrue NegativeFalse NegativeFalse PositiveSE SP PPV NPV ACC1 93 282 8 25 92.1 (85.0, 96.5)91.9 (88.2, 94.7) 78.8 (71.8, 84.5) 97.2 (94.8, 98.6) 91.9 (88.8, 94.4)1b 28 305 73 2 27.7 (19.3, 37.5)99.4 (97.7, 99.9) 93.3 (77.3, 98.3) 80.7 (78.7, 82.5) 81.6 (77.5, 85.3)2 16 305 85 2 15.8 (9.3, 24.5) 99.4 (97.7, 99.9) 88.9 (65.2, 97.2) 78.2 (76.7,79.6)78.7 (74.4, 82.6)3 50 269 51 38 49.5 (39.4, 59.6)87.6 (83.4, 91.1) 56.8 (47.9, 65.3) 84.1 (81.2, 86.5) 78.2 (73.9, 82.1)4 42 269 59 38 41.6 (31.9, 51.8)87.6 (83.4, 91.1) 52.5 (43.1, 61.7) 82.0 (79.4, 84.4) 76.2 (71.8, 80.3)5 19 306 82 1 18.8 (11.7, 27.8)99.7 (98.2, 100) 95.0 (72.0, 99.3) 78.9 (77.3, 80.4) 79.7 (75.4, 83.5)6 14 306 87 1 13.9 (7.8, 22.2) 99.7 (98.2, 100) 93.3 (65.1, 99.1) 77.9 (76.5, 79.2) 78.4 (74.1, 82.3)7 16 307 85 0 15.8 (9.3, 24.5) 100 (98.8, 100) 100 78.3 (76.9, 79.7) 79.2 (74.9, 83.0)8 44 305 57 2 43.6 (33.7, 53.8)99.4 (97.7, 99.9) 95.7 (84.5, 98.9) 84.3 (81.8, 86.4) 85.5 (81.8, 88.8)9 25 305 76 2 24.8 (16.7, 34.3)99.4 (97.7, 99.9) 24.8 (20.6, 29.2) 80.1 (78.2, 81.8) 80.9 (76.7, 84.6)10 43 269 58 38 42.6 (32.8, 52.8)87.6 (83.4, 91.1) 53.1 (43.8, 62.2) 82.3 (79.6, 84.7) 76.5 (72.1, 80.5)11 69 288 32 19 68.3 (58.3, 77.2)93.8 (90.5, 96.2) 78.4 (69.7, 85.1) 90.0 (87.1, 92.3) 87.5 (83.9, 90.6)12 67 257 34 50 66.3 (56.3, 75.4)83.7 (79.1, 87.7) 57.3 (50.1, 64.2) 88.3 (85.1, 90.9) 79.4 (75.2, 83.2)13 60 289 41 18 59.4 (49.2, 69.1)94.1 (90.9, 96.5) 76.9 (67.4, 84.3) 87.6 (84.8, 89.9) 85.5 (81.8, 88.8)14 87 288 14 19 86.1 (77.8, 92.2)93.8 (90.5, 96.2) 82.1 (74.6, 87.7) 95.4 (92.7, 97.1) 91.9 (88.8, 94.4)15 27 301 74 6 26.7 (18.4, 36.5)98.1 (95.8, 99.3) 81.8 (65.7, 91.4) 80.3 (78.3, 82.1) 80.4 (76.2, 84.1)16 23 301 78 6 22.8 (15.0, 32.2)98.1 (95.8, 99.3) 79.3 (61.6, 90.2) 79.4 (77.6, 81.1) 79.4 (75.2, 83.2)17 76 288 25 19 75.3 (65.7, 83.3)93.8 (90.5, 96.2) 80.0 (71.8, 86.3) 92.0 (89.1, 94.2) 89.2 (85.8, 92.1)18 70 286 31 21 69.3 (59.3, 78.1)93.2 (89.7, 95.7) 76.9 (68.4, 83.7) 90.2 (87.3, 92.5) 87.3 (83.6, 90.3)19 11 306 90 1 10.9 (5.6, 18.7) 99.7 (98.2, 100) 91.7 (59.0, 98.8) 77.3 (76.1, 78.5) 77.7 (73.3, 81.6)20 9 306 92 1 8.9 (4.2, 16.2) 99.7 (98.2, 100) 90.0 (53.6, 98.6) 76.9 (75.8, 78.0) 77.2 (72.8, 81.2)21 70 288 31 19 69.3 (59.3, 78.1)93.8 (90.5, 96.2) 78.7 (70.1, 85.3) 90.3 (87.4, 92.6) 87.8 (84.2, 90.8)22 44 305 57 2 43.6 (33.7, 53.8)99.4 (97.7, 99.9) 95.7 (84.5, 98.9) 84.3 (81.8, 86.4) 85.5 (81.8, 88.8)23 77 288 24 19 76.2 (66.7, 84.1)93.8 (90.5, 96.2) 80.2 (72.1, 86.4) 92.3 (89.4, 94.5) 89.5 (86.1, 92.3)Page 8 of 11Stirton et al. Allergy, Asthma & Clinical Immunology           (2023) 19:46 Overall, the case definitions performed well in the test set of matched patients with case definitions 1, 11, 14, 17 and 23 demonstrating metrics over 70%. As anticipated the specificity (100%) and PPV (100%) was high in case definition 7 (eczema specific ICD-9-CM 691.8) but the sensitivity was low (15.8%). When we included both ICD-9-CM 691.8 or 692.9 (case definition 13) the specificity and PPV dropped slightly (94.1% and 76.9%, respectively) with a moderate increase in sensitivity (59.4%). Similar to Hsu and colleagues, we found that patients with 692.9 have eczema [18].When we tested our case definitions in the validation set the PPV of each definition decreased. The most spe-cific definition (case definition 7) had a specificity 99.8% and PPV 84.2%, with a sensitivity of 15.8%. The use of ICD-9-CM 691.8 alone was able to identify patients who have eczema according to our reference set. However, as suggested by Hsu and colleagues the use of 691.8 is overly restrictive and underestimates the prevalence of eczema Table 3 Validation of Eczema Case Definitions in the Validation Dataset n = 1495Case DefinitionTrue PositiveTrue NegativeFalse NegativeFalse PositiveSE SP PPV NPV ACC1 93 1234 8 161 92.1 (85.0, 96.5)88.5 (86.7, 90.1) 36.6 (33.1, 40.3) 99.4 (98.8, 99.7) 88.7 (87.0, 90.3)1b 28 1328 73 67 27.7 (19.3, 37.5)95.2 (93.9, 96.3) 29.5 (22.0, 38.2) 94.8 (94.2, 95.4) 90.6 (89.1, 92.1)2 16 1379 85 16 15.8 (9.3, 24.5) 98.9 (98.1, 99.3) 50.0 (34.0, 66.0) 94.2 (93.7, 94.6) 93.3 (91.9, 94.5)3 50 1165 51 230 49.5 (39.4, 59.6)83.5 (81.5, 85.4) 17.9 (14.7, 21.5) 95.8 (95.0, 96.5) 81.2 (79.1, 83.2)4 42 1190 59 205 41.6 (31.9, 51.8)85.3 (83.3, 87.1) 17.0 (13.6, 21.1) 95.3 (94.5, 96.0) 82.4 (80.3, 84.3)5 19 1361 82 34 18.8 (11.7, 27.8)97.6 (96.6, 98.3) 35.9 (24.9, 48.6) 94.3 (93.8, 94.8) 92.3 (90.8, 93.6)6 14 1359 87 36 13.9 (7.8, 22.2) 97.4 (96.5, 98.2) 28.0 (17.8, 41.1) 94.0 (93.5, 94.4) 91.8 (90.3, 93.1)7 16 1392 85 3 15.8 (9.3, 24.5) 99.8 (99.4, 100) 84.2 (61.2, 94.7) 94.3 (93.8, 94.7) 94.1 (92.8, 95.3)8 44 1325 57 70 43.6 (33.7, 53.8)95.1 (93.8, 96.1) 38.6 (31.4, 46.4) 96.0 (95.2, 96.6) 91.7 (90.2, 93.0)9 25 1360 76 35 24.8 (16.7, 34.3)97.5 (96.5, 98.3) 41.7 (30.8, 53.4) 94.7 (94.1, 95.2) 92.6 (91.1, 93.9)10 43 1197 58 198 42.6 (32.8, 52.8)85.8 (83.9, 87.6) 17.8 (14.3, 22.0) 95.4 (94.6, 96.1) 82.9 (80.9, 84.8)11 69 1282 32 113 68.3 (58.3, 77.2)91.9 (90.3, 93.3) 37.9 (32.9, 43.2) 97.6 (96.8, 98.2) 90.3 (88.7, 91.8)12 67 1147 34 248 66.3 (56.3, 75.4)82.2 (80.1, 84.2) 21.3 (18.4, 24.4) 97.1 (96.2, 97.8) 81.2 (79.1, 83.1)13 60 1310 41 85 59.4 (49.2, 69.1)93.9 (92.5, 95.1) 41.4 (35.2, 47.8) 97.0 (96.2, 97.6) 91.6 (90.1, 92.9)14 87 1249 14 146 86.1 (77.8, 92.2)89.5 (87.8, 91.1) 37.3 (33.4, 41.5) 99.0 (98.2, 99.3) 89.3 (87.6, 90.8)15 27 1347 74 48 26.7 (18.4, 36.5)96.6 (95.5, 97.5) 36.0 (26.9, 46.3) 94.8 (94.2, 95.4) 91.8 (90.3, 93.2)16 23 1355 78 40 22.8 (15.0, 32.2)97.1 (96.1, 97.9) 36.5 (26.4, 48.0) 94.6 (94.0, 95.1) 92.1 (90.6, 93.4)17 76 1297 25 98 75.3 (65.7, 83.3)93.0 (91.5, 94.3) 43.7 (38.3, 49.2) 98.1 (97.4, 98.7) 91.8 (90.3, 93.1)18 70 1283 31 112 69.3 (59.3, 78.1)92.0 (90.4, 93.3) 38.5 (33.4, 43.8) 97.6 (96.9, 98.2) 90.4 (88.8, 91.9)19 11 1368 90 27 10.9 (5.6, 18.7) 98.1 (97.2, 98.7) 29.0 (17.2, 44.4) 93.8 (93.4, 94.2) 92.2 (90.7, 93.5)20 9 1374 92 21 8.9 (4.2, 16.2) 98.5 (97.7, 99.1) 30.0 (16.8,47.7)93.7 (93.4, 94.1) 92.5 (91.0, 93.7)21 70 1285 31 110 69.3 (59.3, 78.1)92.1 (90.6, 93.5) 38.9 (33.8, 44.3) 97.6 (96.9, 98.2) 90.6 (89.0, 92.0)22 44 1325 57 70 43.6 (33.7, 53.8)95.0 (93.7, 96.1) 38.6 (31.4, 46.4) 95.9 (95.1, 96.5) 91.5 (90.0, 92.9)23 77 1263 24 132 76.2 (66.7, 84.1)90.5 (88.9, 92.0) 36.8 (32.4, 41.5) 98.1 (97.4, 98.7) 89.6 (87.9, 91.1)Page 9 of 11Stirton et al. Allergy, Asthma & Clinical Immunology           (2023) 19:46 [18]. Previously studies using specific ICD-9-CM codes also reported low sensitivity [18, 19] and\/or PPV [18]. Low sensitivity from 4-digit ICD-9-CM codes (691.8 and 692.9) likely resulted from frequent use of less specific 3-digit ICD-9-CM codes. Reliance on 4-digit codes may exclude billing data from provincial systems that only require 3-digit codes. Case definitions 14 and 17 used eczema-specific as well as 3-digit ICD-9-CM codes.When we compared overall metrics, case definition 17, despite low PPV (43.7%) was able to maintain higher specificity (93.0%) and sensitivity (75.3%). Although the sensitivity was lower then reported by case definition 1 (92.1%) and 14 (86.1%) overall case definition 17 found substantially less false positives. Contrary to Hsu and colleagues we found that requiring multiple occurrences of less specific ICD-9-CM codes improved performance [18]. The addition of related atopic conditions and medi-cations to our case definition did not substantially change sensitivity (76.2%), specificity (90.5%), or PPV (36.8%).Depending on a study\u2019s objectives, researchers may require application of one or more of the above-described case definitions. For example, a clinical trial would require a definition with high specificity, whereas for epidemiological studies definitions with a more bal-anced sensitivity and specificity and high accuracy would be preferred. Case definition 1 or 17 may be useful for epidemiology and surveillance efforts. Unconfirmed diagnoses could be related to a lack of formal criteria as well as provider uncertainty in making the official diag-nosis for the purpose of billing [18]. Case definition 1 and 17 will include some false positives and is likely inclusive of some patients with ill-defined eczematous disorders or non-atopic dermatosis conditions. However, the esti-mated prevalence of case definition 17 (8.2%), is similar to previous literature [12, 13, 16]. Reliance on diagnos-tic information are much simpler and more transferable than those requiring medications or atopic diagnoses. Additionally, simpler definitions may be more desirable given known variations in data quality [44, 45] and pro-vider and system factors such as EMR capabilities or pro-vincial billing code requirements.The validity and utility of the case definitions can be further supported by the characteristics of the patients captured. Independent of the case definition applied we found evidence that patients captured by one of these case definitions are experiencing or had experi-enced some form of atopic or non-atopic dermatoid condition. In all case definitions there was significant increases in diagnosis of other atopic conditions includ-ing asthma, and rhinitis consistent with other literature [1, 19, 26, 32\u221243]. Although patients with eczema did not have higher rates of food allergy, a previous study using CPSCNN data also noted lower then expected allergy prevalence suggesting incomplete documentation of allergy in primary care EMRs [26]. While we cannot discern if medications are prescribed for the treatment of eczema specifically, patients meeting criteria received more eczema related medications.LimitationsOne of the key limitations is that we relied on primary care provider documentation in EMR, which could both overestimate or underestimate eczema prevalence due to variation in provider coding, missing diagnoses, and incomplete documentation. Clinicians use EMR systems for clinical purposes and may not be concerned with the use of specific ICD-9-CM codes for secondary pur-poses. For example, the ICD-9-CM code 692 includes the Table 4 Application of the Strongest Eczema Case Definitions to the CPCSSN Repository N = 689,301 patientsCase definition Prevalence n(%, 95%CI)Female patient, n(%)Patient age, mean(SD)Eczema medi-cation n (%)Patients with an allergy n (%)Patients with asthma n(%)Patients with rhini-tis n(%)Case definition 1 104,354 (15.1%, 15.05\u201315.22%)65,085 (62.4%) 53.9 (19.9) 27,885 (26.7%) 14,948 (14.3%) 18,973 (18.2%)11,151 (10.7%)Case definition 7 5569 (0.8%, 0.79\u20130.83%) 3479 (62.5%) 48.9 (20.3) 1620 (29.1%) 447 (8.0%) 1228 (22.1%) 786 (14.1%)Case definition 13 28,762 (4.2%, 4.13\u20134.22%)18,240 (63.4%) 51.9 (20.0) 8452 (29.4%) 2892 (10.1%) 5426 (18.9%) 4208 (14.6%)Case definition 14 97,980 (14.2%, 14.13\u201314.3%)61,258 (62.5%) 53.9 (19.9) 26,301 (26.8%) 14,260 (14.6%) 17,998 (18.4%)10,429 (10.6%)Case definition 17 56,171 (8.2%, 8.08\u20138.21%)35,434 (63.1%) 53.4 (20.1) 15,275 (27.2%) 7504 (13.4%) 11,007 (19.6%)7167 (12.8%)Case definition 23 67,416 (9.8%, 9.71\u20139.85%)42,467 (63.0%) 52.3 (20.0) 26,301 (39.0%) [1]14,260 (21.2%)117,998 (26.7%)110,429 (15.5%)1Patients not captured in an eczema case definition584,538 (84.8%) 322,481 (55.2%) 52.0 (19.3) 55,506 (9.5%) 84,878 (14.5%) 64,811 (11.1%) 31,863 (5.5%)1medication, allergy, asthma and rhinitis diagnosis are included in the case definitionBoldface font indicated the variable was significant at p-value > 0.0595%CI: 95% confidence intervalsPage 10 of 11Stirton et al. Allergy, Asthma & Clinical Immunology           (2023) 19:46 term \u2018eczema,\u2019 but also contains multiple branch points that refer to contact dermatitis from a variety of sources including detergents, chemicals, drugs and medicines, among others. Furthermore, within typical medical prac-tice, eczema may refer to atopic dermatitis or non-atopic dermatoses. CPCSSN includes only primary care EMR data and does not represent specialist visits. Future stud-ies linking this dataset to representative cohorts of aller-gist and dermatologist could be helpful to improve the certainty and accuracy of our prevalence estimates.ConclusionsApplication of a validated EMR-based case definition for eczema can improve health surveillance of this increas-ingly prevalent condition. Future research should explore the burden of illness, trends and interventions related to eczema care using these validated case definitions.AcknowledgementsWe would like to acknowledge William Peeler for assistance in data acquisition and pre-processing of the data for this study.Authors\u2019 contributionsHannah Stirton, Leanne Kosowan and Alexander Singer conceptualized this study. Leanne Kosowan and Alexander Singer acquired the data for this study. Leanne Kosowan analyzed the data. Hannah Stirton, Leanne Kosowan and Alexander Singer assisted with data interpretation. Hannah Stirton and Leanne Kosowan drafted the manuscript. All authors have made substantial contributions to manuscript revisions. All authors approve the final version of the manuscript for submission.FundingThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.Availability of Data and MaterialsDatasets generated and\/or analysed during the current study are not publicly available due to the confidential nature of data governed by the PHIA legislation but are available from the corresponding author on reasonable request and with the appropriate approvals.DeclarationsEthics approval and consent to participateThis study was approved by the Health Research Ethics Board at the University of Manitoba.Consent for publicationNot applicable.Competing InterestsEMA is an employee of Public Health Agency of Canada (PHAC) but the views expressed in this manuscript are her own and not that of PHAC. 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