scholarly journals Development of the Canadian Emergency Department Diagnosis Shortlist

CJEM ◽  
2010 ◽  
Vol 12 (04) ◽  
pp. 311-319 ◽  
Author(s):  
Bernard Unger ◽  
Marc Afilalo ◽  
Jean François Boivin ◽  
Michael Bullard ◽  
Eric Grafstein ◽  
...  
Keyword(s):  
Emergency Department ◽  
International Classification Of Diseases ◽  
University Teaching ◽  
Data Sets ◽  
Modified Delphi ◽  
Classification Of Diseases ◽  
Chief Complaints ◽  
Icd 10 ◽  
The Creation ◽  
Standardized Parameters

ABSTRACTObjective:Managers of emergency departments (EDs), governments and researchers would benefit from reliable data sets that characterize use of EDs. Although Canadian ED lists for chief complaints and triage acuity exist, no such list exists for diagnosis classification. This study was aimed at developing a standardized Canadian Emergency Department Diagnosis Shortlist (CED-DxS), as a subset of the full International Classification of Diseases, 10th revision, with Canadian Enhancement (ICD-10-CA).Methods:Emergency physicians from across Canada participated in the revision of the ICD-10-CA through 2 rounds of the modified Delphi method. We randomly assigned chapters from the ICD-10-CA (approximately 3000 diagnoses) to reviewers, who rated the importance of including each diagnosis in the ED-specific diagnosis list. If 80% or more of the reviewers agreed on the importance of a diagnosis, it was retained for the final revision. The retained diagnoses were further aggregated and adjusted, thus creating the CED-DxS.Results:Of the 83 reviewers, 76% were emergency medicine (EM)–trained physicians with an average of 12 years of experience in EM, and 92% were affiliated with a university teaching hospital. The modified Delphi process and further adjustments resulted in the creation of the CED-DxS, containing 837 items. The chapter with the largest number of retained diagnoses was injury and poisoning (n= 292), followed by gastrointestinal (n= 59), musculoskeletal (n= 55) and infectious disease (n= 42). Chapters with the lowest number retained were neoplasm (n= 18) and pregnancy (n= 12).Conclusion:We report the creation of the uniform CED-DxS, tailored for Canadian EDs. The addition of ED diagnoses to existing standardized parameters for the ED will contribute to homogeneity of data across the country.

scholarly journals Validation of ICD-10-CM codes for injuries complicating pregnancy, childbirth and the puerperium: a medical record review

2021 ◽  
Vol 27 (Suppl 1) ◽  
pp. i9-i12
Author(s):  
Anna Hansen ◽  
Dana Quesinberry ◽  
Peter Akpunonu ◽  
Julia Martin ◽  
Svetla Slavova
Keyword(s):  
Emergency Department ◽  
Medical Record ◽  
International Classification Of Diseases ◽  
Medical Record Review ◽  
Full Sample ◽  
Emergency Department Data ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Record Review

IntroductionThe purpose of this study was to estimate the positive predictive value (PPV) of International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes for injury, poisoning, physical or sexual assault complicating pregnancy, childbirth and the puerperium (PCP) to capture injury encounters within both hospital and emergency department claims data.MethodsA medical record review was conducted on a sample (n=157) of inpatient and emergency department claims from one Kentucky healthcare system from 2015 to 2017, with any diagnosis in the ICD-10-CM range O9A.2-O9A.4. Study clinicians reviewed medical records for the sampled cases and used an abstraction form to collect information on documented presence of injury and PCP complications. The study estimated the PPVs and the 95% CIs of O9A.2-O9A.4 codes for (1) capturing injuries and (2) capturing injuries complicating PCP.ResultsThe estimated PPV for the codes O9A.2-O9A.4 to identify injury in the full sample was 79.6% (95% CI 73.3% to 85.9%) and the PPV for capturing injuries complicating PCP was 72.0% (95% CI 65.0% to 79.0%). The estimated PPV for an inpatient principal diagnosis O9A.2-O9A.4 to capture injuries was 90.7% (95% CI 82.0% to 99.4%) and the PPV for capturing injuries complicating PCP was 88.4% (95% CI 78.4% to 98.4%). The estimated PPV for any mention of O9A.2-O9A.4 in emergency department data to capture injuries was 95.2% (95% CI 90.6% to 99.9%) and the PPV for capturing injuries complicating PCP was 81.0% (95% CI 72.4% to 89.5%).DiscussionThe O9A.2-O9A.4 codes captured high percentage true injury cases among pregnant and puerperal women.

scholarly journals Defining indicators for drug overdose emergency department visits and hospitalisations in ICD-10-CM coded discharge data

2021 ◽  
Vol 27 (Suppl 1) ◽  
pp. i56-i61 ◽  
Author(s):  
Alana Vivolo-Kantor ◽  
Emilia Pasalic ◽  
Stephen Liu ◽  
Pedro D Martinez ◽  
Robert Matthew Gladden
Keyword(s):  
Emergency Department ◽  
Drug Overdose ◽  
International Classification Of Diseases ◽  
Case Definition ◽  
Emergency Department Visits ◽  
Health Departments ◽  
Discharge Data ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Key Aspects

IntroductionThe drug overdose epidemic has worsened over the past decade; however, efforts have been made to better understand and track nonfatal overdoses using various data sources including emergency department and hospital admission data from billing and discharge files.Methods and findingsThe Centers for Disease Control and Prevention (CDC) has developed surveillance case definition guidance using standardised discharge diagnosis codes for public health practitioners and epidemiologists using lessons learnt from CDC’s funded recipients and the Council for State and Territorial Epidemiologists (CSTE) International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) Drug Poisoning Indicators Workgroup and General Injury ICD-10-CM Workgroup. CDC’s guidance was informed by health departments and CSTE’s workgroups and included several key aspects for assessing drug overdose in emergency department and hospitalisation discharge data. These include: (1) searching all diagnosis fields to identify drug overdose cases; (2) estimating drug overdose incidence using visits for initial encounter but excluding subsequent encounters and sequelae; (3) excluding underdosing and adverse effects from drug overdose incidence indicators; and (4) using codes T36–T50 for overdose surveillance. CDC’s guidance also suggests analysing intent separately for ICD-10-CM coding.ConclusionsCDC’s guidance provides health departments a key tool to better monitor drug overdoses in their community. The implementation and validation of this standardised guidance across all CDC-funded health departments will be key to ensuring consistent and accurate reporting across all entities.

scholarly journals Identification of work-related injury emergency department visits using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes

2021 ◽  
Vol 27 (Suppl 1) ◽  
pp. i3-i8
Author(s):  
Ashley M Bush ◽  
Terry L Bunn ◽  
Madison Liford
Keyword(s):  
Emergency Department ◽  
International Classification Of Diseases ◽  
Injury Surveillance ◽  
Discharge Data ◽  
Work Related ◽  
Work Related Injury ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Ed Visits

IntroductionEmergency department (ED) visit discharge data are a less explored population-based data source used to identify work-related injuries. When using discharge data, work-relatedness is often determined by the expected payer of workers’ compensation (WC). In October 2015, healthcare discharge data coding systems transitioned to the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM). ICD-10-CM’s structure offers potential new work-related codes to enhance work-related injury surveillance. This study identified work-related ED visits using relevant ICD-10-CM work-related injury codes. Cases identified using this method were compared with those identified using the WC expected payer approach.MethodsState ED visit discharge data (2016–2019) were analysed using the CDC’s discharge data surveillance definition. Injuries were identified using a diagnosis code or an external cause-of-injury code in any field. Injuries were assessed by mechanism and expected payer. Literature searches and manual review of ICD-10-CM codes were conducted to identify possible work-related injury codes. Descriptive statistics were performed and assessed by expected payer.ResultsWC was billed for 87 361 injury ED visits from 2016 to 2019. Falls were the most frequent injury mechanism. The 246 ICD-10-CM work-related codes identified 36% more work-related ED injury visits than using WC as the expected payer alone.ConclusionThis study identified potential ICD-10-CM codes to expand occupational injury surveillance using discharge data beyond the traditional WC expected payer approach. Further studies are needed to validate the work-related injury codes and support the development of a work-related injury surveillance case definition.

scholarly journals National rates of non-fatal emergency department visits and hospitalisations due to fall-related injuries in older adults 2010–2014 and 2016: transitioning from ICD-9-CM to ICD-10-CM

2021 ◽  
Vol 27 (S1) ◽  
pp. i75-i78
Author(s):  
Briana L Moreland ◽  
Elizabeth R Burns ◽  
Yara K Haddad
Keyword(s):  
Emergency Department ◽  
International Classification Of Diseases ◽  
Emergency Department Visits ◽  
Injury Rates ◽  
Fall Injury ◽  
The Us ◽  
Before And After ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Ed Visits

BackgroundThis study describes rates of non-fatal fall-injury emergency department (ED) visits and hospitalisations before and after the US 2015 transition from the 9th to 10th revision of the International Classification of Diseases, Clinical Modification (ICD-9-CM to ICD-10-CM).MethodsED visit and hospitalisation data for adults aged 65+ years were obtained from the 2010–2016 Healthcare Cost and Utilisation Project. Differences in fall injury rates between 2010 and 2014 (before transition), and 2014 and 2016 (before and after transition) were analysed using t-tests.ResultsFor ED visits, rates did not differ significantly between 2014 and 2016 (4288 vs 4318 per 100 000, respectively). Hospitalisation rates were lower in 2014 (1232 per 100 000) compared with 2016 (1281 per 100 000).ConclusionIncreased rates of fall-related hospitalisations could be an artefact of the transition or may reflect an increase in the rate of fall-related hospitalisations. Analyses of fall-related hospitalisations across the transition should be interpreted cautiously.

scholarly journals Incidence of Congenital Fetal Malformation Abnormalities in Tribhuban University, Teaching Hospital, Kathmandu, Nepal: a Hospital Based Study

2021 ◽  
Vol 3 (1) ◽  
pp. 30-33
Author(s):  
Sunita Bajracharya ◽  
Deepak Rajbhandari ◽  
Binaya Gurung ◽  
Asma Rana
Keyword(s):  
Birth Defects ◽  
Teaching Hospital ◽  
International Classification Of Diseases ◽  
University Teaching ◽  
Fetal Malformation ◽  
Institute Of Medicine ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
A Prospective Study ◽  
First Year Of Life

Background : Birth defects are defined as abnormalities of structure or function, which are present at birth. Major birth defects are abnormalities that lead to developmental or physical disabilities or require medical or surgical treatment and they're the leading cause of death in the first year of life. The objective of this study is to find the incidence of congenital abnormalities in this institution. Methods: This was a prospective study conducted in Institute of  Medicine, Maharajgunj Medical Campus, Tribhuwan  University Teaching Hospital  from 14th April 2015 to 11th  Feb ,2016 . All the delivered babies in this hospital during the study period were included. All the birth cases of gross congenital fetal malformation were identified and carefully studied and were classified according to the International Classification of diseases (ICD-10). Results: Total number of congenital fetal malformation abnormalities (CMF) delivered during this period was 94 (1.13%) in total 8300 birth /7868 live birth. CMF were categorized as, Musculoskeletal - 25.55%, CNS - 17.02%, Gastrointestinal -13.33%, Renal 14.25%, Cardiac -10.63%,  Respiratory -10.6%, craniofacial -  9.57%, Genitouriary - 8.51%,  and Miscellaneous - 9.57%. Conclusion: Birth abnormalities incompatible to life needs to be timely diagnosed and terminated, whereas as those compatible to life should be given a chance to be born and cared thereafter. All the mothers who have, had previous malformed babies must undergo preconceptional counseling, before planning next pregnancy in order to avoid recurrent mishap.  

scholarly journals ICD-10-CM–Based Definitions for Emergency Department Opioid Poisoning Surveillance: Electronic Health Record Case Confirmation Study

2020 ◽  
Vol 135 (2) ◽  
pp. 262-269
Author(s):  
Svetla Slavova ◽  
Dana Quesinberry ◽  
Julia F. Costich ◽  
Emilia Pasalic ◽  
Pedro Martinez ◽  
...  
Keyword(s):  
Emergency Department ◽  
Drug Testing ◽  
International Classification Of Diseases ◽  
Case Definitions ◽  
Health Care Networks ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Ed Visits ◽  
Representative Samples

Objectives: Valid opioid poisoning morbidity definitions are essential to the accuracy of national surveillance. The goal of our study was to estimate the positive predictive value (PPV) of case definitions identifying emergency department (ED) visits for heroin or other opioid poisonings, using billing records with International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes. Methods: We examined billing records for ED visits from 4 health care networks (12 EDs) from October 2015 through December 2016. We conducted medical record reviews of representative samples to estimate the PPVs and 95% confidence intervals (CIs) of (1) first-listed heroin poisoning diagnoses (n = 398), (2) secondary heroin poisoning diagnoses (n = 102), (3) first-listed other opioid poisoning diagnoses (n = 452), and (4) secondary other opioid poisoning diagnoses (n = 103). Results: First-listed heroin poisoning diagnoses had an estimated PPV of 93.2% (95% CI, 90.0%-96.3%), higher than secondary heroin poisoning diagnoses (76.5%; 95% CI, 68.1%-84.8%). Among other opioid poisoning diagnoses, the estimated PPV was 79.4% (95% CI, 75.7%-83.1%) for first-listed diagnoses and 67.0% (95% CI, 57.8%-76.2%) for secondary diagnoses. Naloxone was administered in 867 of 1055 (82.2%) cases; 254 patients received multiple doses. One-third of all patients had a previous drug poisoning. Drug testing was ordered in only 354 cases. Conclusions: The study findings suggest that heroin or other opioid poisoning surveillance definitions that include multiple diagnoses (first-listed and secondary) would identify a high percentage of true-positive cases.

scholarly journals Pterygia are indicators of an increased risk of developing cutaneous melanomas

2017 ◽  
Vol 102 (4) ◽  
pp. 496-501 ◽  
Author(s):  
Julie M Crewe ◽  
Tim Threlfall ◽  
Antony Clark ◽  
Paul G Sanfilippo ◽  
David A Mackey
Keyword(s):  
International Classification Of Diseases ◽  
Data Sets ◽  
Care Providers ◽  
Health Administrative Data ◽  
Increased Risk ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
History Of ◽  
Incident Rate

AimTo investigate whether pterygium is an indicator of an increased risk of cutaneous melanoma (CM).MethodsA matched-cohort study, using linked health administrative data sets to identify all hospital-treated pterygium in Western Australia (WA) between 1979 and 2014. We identified pterygium cases from hospital diagnosis and/or procedure International Classification of Diseases 9th revision (ICD-9) and 10th revision (ICD-10) codes and matched cases by age, sex and residential postcode to WA Electoral Roll controls with no known history of pterygium. Both cohorts were linked to the WA Cancer Registry and the WA Deaths Registry.Results23 625 people had pterygium treatment (64% male) in WA hospitals. The median age for pterygium diagnosis and/or treatment was 49 years (range 14–96). There were significantly more CM cases in the pterygium cohort compared with the control cohort (1083 vs 874; p<0.001). In a logistic regression analysis, there was a 24% increase in the odds of developing a CM in the pterygium cohort, compared with controls, after controlling for other predictors (OR 1.24, 95% CI 1.1 to 1.4). The incident rate ratio (IRR) of a malignant CM diagnosis was 20% greater in people who had treatment for a pterygium compared with controls (IRR 1.2, 95% CI 1.0 to 1.4).ConclusionThe presence of a pterygium indicates a significantly increased risk of developing a CM. Eye care providers who see patients with developing pterygia should advise these patients of this increased risk and recommend regular skin surveillance.

scholarly journals A Classificacao Internacional de Doencas, a Familia de Classificacoes Internacionais, a CID-11 e a Sindrome Pos-Poliomielite

2013 ◽  
Vol 71 (9A) ◽  
pp. 3-10 ◽  
Author(s):  
Ruy Laurenti ◽  
Heloisa Brunow Ventura Di Nubila ◽  
Abrahao Augusto Joviniano Quadros ◽  
Monica Tilli Reis Pessoa Conde ◽  
Acary Souza Bulle Oliveira
Keyword(s):  
Reference Group ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
The Creation

The first International Classification of Diseases (ICD) was approved in 1893 and since then it has been periodically reviewed. The last, 10th revision (ICD-10), was approved in 1989. Since 1989, it was possible to update from ICD revisions, which did not happen before. The next revision (ICD-11) would probably be published in 2015. In 1989, mechanisms were established to update ICD-10, through the creation of the Morbidity Reference Group (MbRG) in 1997 and the Update and Revision Committee (URC) in 2000. The Morbidity Reference Group (MbRG) was created in 2007 to discuss in more detail the issues to update morbidity. A specific code in ICD was not included in the revision of ICD-10 in 1989 for the post-polio syndrome (PPS). However, the ICD new code G14 for PPS was included in ICD-10 since 2010.

Angststörungen – von der ICD-10 zur ICD-11

2020 ◽  
pp. 1-5
Author(s):  
Timo D. Vloet ◽  
Marcel Romanos
Keyword(s):  
Mental Disorders ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Classification Of Diseases ◽  
Icd 10

Zusammenfassung. Hintergrund: Nach 12 Jahren Entwicklung wird die 11. Version der International Classification of Diseases (ICD-11) von der Weltgesundheitsorganisation (WHO) im Januar 2022 in Kraft treten. Methodik: Im Rahmen eines selektiven Übersichtsartikels werden die Veränderungen im Hinblick auf die Klassifikation von Angststörungen von der ICD-10 zur ICD-11 zusammenfassend dargestellt. Ergebnis: Die diagnostischen Kriterien der generalisierten Angststörung, Agoraphobie und spezifischen Phobien werden angepasst. Die ICD-11 wird auf Basis einer Lebenszeitachse neu organisiert, sodass die kindesaltersspezifischen Kategorien der ICD-10 aufgelöst werden. Die Trennungsangststörung und der selektive Mutismus werden damit den „regulären“ Angststörungen zugeordnet und können zukünftig auch im Erwachsenenalter diagnostiziert werden. Neu ist ebenso, dass verschiedene Symptomdimensionen der Angst ohne kategoriale Diagnose verschlüsselt werden können. Diskussion: Die Veränderungen im Bereich der Angsterkrankungen umfassen verschiedene Aspekte und sind in der Gesamtschau nicht unerheblich. Positiv zu bewerten ist die Einführung einer Lebenszeitachse und Parallelisierung mit dem Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Schlussfolgerungen: Die entwicklungsbezogene Neuorganisation in der ICD-11 wird auch eine verstärkte längsschnittliche Betrachtung von Angststörungen in der Klinik sowie Forschung zur Folge haben. Damit rückt insbesondere die Präventionsforschung weiter in den Fokus.

Depression

2017 ◽  
Author(s):  
Philip Cowen
Keyword(s):  
International Classification Of Diseases ◽  
Behavioural Therapy ◽  
Historical Background ◽  
Cognitive Behavioural ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Diagnosis And Classification ◽  
Modern Experience ◽  
Symptoms And Signs

This chapter discusses the symptomatology, diagnosis, and classification of depression. It begins with a brief historical background on depression, tracing its origins to the classical term ‘melancholia’ that describes symptoms and signs now associated with modern concepts of the condition. It then considers the phenomenology of the modern experience of depression, its diagnosis in the operational scheme of ICD-10 (International Classification of Diseases, tenth edition), and current classificatory schemes. It looks at the symptoms needed to meet the criteria for ‘depressive episode’ in ICD-10, as well as clinical features of depression with ‘melancholic’ features or ‘somatic depression’ in ICD-10. It also presents an outline of the clinical assessment of an episode of depression before concluding with an overview of issues that need to be taken into account when addressing approaches to treatment, including cognitive behavioural therapy and the administration of antidepressants.

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