scholarly journals P135: Administrative codes for heat illness: a validation study in Ontario, Canada

CJEM ◽  
2020 ◽  
Vol 22 (S1) ◽  
pp. S113-S113
Author(s):  
H. Baassiri ◽  
T. Varghese ◽  
M. Columbus ◽  
K. Clemens ◽  
J. Yan
Keyword(s):  
Gold Standard ◽  
Heat Stroke ◽  
Heat Exposure ◽  
Sample Size Calculation ◽  
Physical Exertion ◽  
International Classification Of Diseases ◽  
Administrative Database ◽  
Heat Illness ◽  
Predictive Values ◽  
Icd 10

Introduction: Extreme heat events due to climate change are becoming increasingly frequent and severe, and may have an impact on human health. Administrative database studies using International Classification of Diseases 10th revision codes (ICD-10) are powerful tools to measure the burden of acute heat illness (AHI) in Canada. We aimed to assess the validity of the coding algorithm for emergency department (ED) encounters for AHI in our region. Methods: Two independent reviewers retrospectively abstracted data from 507 medical records of patients presenting at two EDs in Ontario between May-September 2015-2018. The Gold Standard definition of an AHI is chart-documented heat exposure with a heat related complaint, such as syncope while working outdoors on a hot day. To determine ICD coding algorithm positive predictive value (PPV), records that were previously coded as ICD-10 heat illnesses were compared to the Gold Standard for AHI. To determine sensitivity (Sn), specificity (Sp) and negative predictive values (NPV), the Gold Standard was compared to randomly selected records. A total of 326,702 ED visits were included in study period with 208 having an ICD-10 code related to heat illness. Sample size calculation demonstrated a need to manually review 62 previously coded heat illnesses and 931 random cases, of which 50 and 474 have been reviewed, respectively. In both abstractions, 20% of cases underwent a blinded duplicate review. Results: In our review of 474 random records, 2 cases were identified as AHI but without an appropriate ICD-10 code, 445 were not AHIs, and no cases had been identified as having an AHI ICD-10 inappropriately applied. In our review of 50 previously coded heat illnesses, 34 were found to be appropriately coded and 16 inappropriately coded, as AHI ICD-10. Average patient age and gender of heat illness vs non-heat illness ED presentations were 32 and 48 years of age and 49% and 64% male, respectively. The leading complaint in AHI was heat stroke/exhaustion (39%), followed by headaches (15%), dizziness (9%), shortness of breath (9%) and syncope/presyncope (6%). 76% of all heat illness presentations presented following a period of physical exertion. Conclusion: Final calculation of Sn, Sp, PPV, NPV for the algorithm will occur upon completion of the review. Preliminary results suggest that ICD-10 coding for AHI may be applied correctly in the ED. This study will help to determine if administrative data can accurately be used to measure the burden of heat illness in Canada.

scholarly journals Suicidal and self-harm presentations to Emergency Departments: The challenges of identification through diagnostic codes and presenting complaints

2019 ◽  
Vol 49 (1) ◽  
pp. 38-46 ◽  
Author(s):  
Jerneja Sveticic ◽  
Nicholas CJ Stapelberg ◽  
Kathryn Turner
Keyword(s):  
Suicidal Ideation ◽  
Gold Standard ◽  
Emergency Departments ◽  
Policy Development ◽  
Suicide Attempts ◽  
Predictive Values ◽  
Diagnostic Codes ◽  
Icd 10 ◽  
Self Harm ◽  
Low Sensitivity

Background: The accuracy of data on suicide-related presentations to Emergency Departments (EDs) has implications for the provision of care and policy development, yet research on its validity is scarce. Objective: To test the reliability of allocation of ICD-10 codes assigned to suicide and self-related presentations to EDs in Queensland, Australia. Method: All presentations due to suicide attempts, non-suicidal self-injury (NSSI) and suicidal ideation between 1 July 2017 and 31 December 2017 were reviewed. The number of presentations identified through relevant ICD-10-AM codes and presenting complaints in the Emergency Department Information System were compared to those identified through an application of an evolutionary algorithm and medical record review (gold standard). Results: A total of 2540 relevant presentations were identified through the gold standard methodology. Great heterogeneity of ICD-10-AM codes and presenting complaints was observed for suicide attempts (40 diagnostic codes and 27 presenting complaints), NSSI (27 and 16, respectively) and suicidal ideation (38 and 34, respectively). Relevant ICD codes applied as primary or secondary diagnosis had very low sensitivity in detecting cases of suicide attempts (18.7%), NSSI (38.5%) and suicidal ideation (42.3%). A combination of ICD-10-AM code and a relevant presenting complaint increased specificity, however substantially reduced specificity and positive predictive values for all types of presentations. ED data showed bias in detecting higher percentages of suicide attempts by Indigenous persons (10.1% vs. 6.9%) or by cutting (28.1% vs. 10.3%), and NSSI by female presenters (76.4% vs. 67.4%). Conclusion: Suicidal and self-harm presentations are grossly under-enumerated in ED datasets and should be used with caution until a more standardised approach to their formulation and recording is implemented.

scholarly journals Validity of ICD-10-CM codes for determination of diabetes type for persons with youth-onset type 1 and type 2 diabetes

2019 ◽  
Vol 7 (1) ◽  
pp. e000547 ◽  
Author(s):  
Gloria C Chi ◽  
Xia Li ◽  
Sara Y Tartof ◽  
Jeff M Slezak ◽  
Corinna Koebnick ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Predictive Value ◽  
Gold Standard ◽  
Characteristic Curve ◽  
Diabetes Type ◽  
Predictive Values ◽  
Icd 10

ObjectiveDiagnosis codes might be used for diabetes surveillance if they accurately distinguish diabetes type. We assessed the validity ofInternational Classification of Disease, 10th Revision, Clinical Modification(ICD-10-CM) codes to discriminate between type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) among health plan members with youth-onset (diagnosis age <20 years) diabetes.Research design and methods. Diabetes case identification and abstraction of diabetes type was done as part of the SEARCH for Diabetes in Youth Study. The gold standard for diabetes type is the physician-assigned diabetes type documented in patients’ medical records. Using all healthcare encounters with ICD-10-CM codes for diabetes, we summarized codes within each encounter and determined diabetes type using percent of encounters classified as T2DM. We chose 50% as the threshold from a receiver operating characteristic curve because this threshold yielded the largest Youden’s index. Persons with ≥50% T2DM-coded encounters were classified as having T2DM. Otherwise, persons were classified as having T1DM. We calculated sensitivity, specificity, positive and negative predictive values, and accuracy overall and by demographic characteristics.ResultsAccording to the gold standard, 1911 persons had T1DM and 652 persons had T2DM (mean age (SD): 19.1 (6.5) years). We obtained 90.6% (95% CI 88.4% to 92.9%) sensitivity, 96.3% (95% CI 95.4% to 97.1%) specificity, 89.3% (95% CI 86.9% to 91.6%) positive predictive value, 96.8% (95% CI 96.0% to 97.6%) negative predictive value, and 94.8% (95% CI 94.0% to 95.7%) accuracy for discriminating T2DM from T1DM.ConclusionsICD-10-CM codes can accurately classify diabetes type for persons with youth-onset diabetes, showing promise for rapid, cost-efficient diabetes surveillance.

scholarly journals Diagnostic Accuracy of Health Care Administrative Diagnosis Codes to Identify Nontuberculous Mycobacteria Disease: A Systematic Review

2021 ◽  
Vol 8 (5) ◽  
Author(s):  
Carlos Mejia-Chew ◽  
Lauren Yaeger ◽  
Kevin Montes ◽  
Thomas C Bailey ◽  
Margaret A Olsen
Keyword(s):  
Health Care ◽  
Diagnostic Accuracy ◽  
Administrative Data ◽  
International Classification Of Diseases ◽  
Administrative Database ◽  
Cochrane Central Register ◽  
Predictive Values ◽  
Diagnosis Codes ◽  
Database Research ◽  
Classification Of Diseases

Abstract Background Health care administrative database research frequently uses standard medical codes to identify diagnoses or procedures. The aim of this review was to establish the diagnostic accuracy of codes used in administrative data research to identify nontuberculous mycobacterial (NTM) disease, including lung disease (NTMLD). Methods We searched Ovid Medline, Embase, Scopus, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov from inception to April 2019. We included studies assessing the diagnostic accuracy of International Classification of Diseases, 9th edition, Clinical Modification (ICD-9-CM) diagnosis codes to identify NTM disease and NTMLD. Studies were independently assessed by 2 researchers, and the Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess bias and quality. Results We identified 5549 unique citations. Of the 96 full-text articles reviewed, 7 eligible studies of moderate quality (3730 participants) were included in our review. The diagnostic accuracy of ICD-9-CM diagnosis codes to identify NTM disease varied widely across studies, with positive predictive values ranging from 38.2% to 100% and sensitivity ranging from 21% to 93%. For NTMLD, 4 studies reported diagnostic accuracy, with positive predictive values ranging from 57% to 64.6% and sensitivity ranging from 21% to 26.9%. Conclusions Diagnostic accuracy measures of codes used in health care administrative data to identify patients with NTM varied across studies. Overall the positive predictive value of ICD-9-CM diagnosis codes alone is good, but the sensitivity is low; this method is likely to underestimate case numbers, reflecting the current limitations of coding systems to capture NTM diagnoses.

scholarly journals P057 THE ACCURACY OF INCISIONAL HERNIA CODES IN ADMINISTRATIVE DATA: A VALIDATION STUDY

2021 ◽  
Vol 108 (Supplement_8) ◽  
Author(s):  
Arturo Rios-Diaz ◽  
Jesse Y. Hsu ◽  
Robyn Broach ◽  
Bradford Bormann ◽  
John Fischer
Keyword(s):  
Abdominal Surgery ◽  
Incisional Hernia ◽  
Predictive Value ◽  
Large Scale ◽  
False Negative ◽  
International Classification Of Diseases ◽  
Administrative Databases ◽  
Administrative Database ◽  
Icd 10 ◽  
Sensitivity Specificity

Abstract Aim Administrative databases contain valuable information for studying incisional hernia (IH) following intra-abdominal procedures at a large scale. We assessed the validity of billing codes for the identification of IH in patients following abdominal surgery. Material and Methods Using International Classification of Diseases, Ninth and Tenth Revision, Clinical Modification (ICD-9-CM and ICD-10-CM), a random sample of 1,000 patients who underwent abdominal operations between 2006-2020 within a large health system-wide administrative database and ≥1 year of follow-up were screened for eligibility. Validation of IH codes was performed using the electronic medical record as reference. Validity metrics of interest included sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy. Patient factors associated with false positive (FP) and false negative (FN) were also explored within univariate and multivariate analyses. Results 759 patients were included. The sensitivity of IH codes was 94.7% (CI 91.4 – 97.0), specificity was 94.9% (CI 92.6 – 96.7), PPV was 84.4% (CI 78.5 – 88.9), NPV was 98.4 (CI 97.4 – 99.0), accuracy was 94.9% (CI 93.0 – 96.3). Within adjusted analyses, patients admitted to a non-surgical service (relative to patients admitted to surgical services; OR 4.46 [95% CI 1.06-18.66]; p = 0.04) were associated with FP; whereas every one-year increase in age was associated with a 5.0% (95% CI 1.0%-10.0%) increase in FN (p = 0.03). Conclusions We have validated the use of ICD-9-CM and ICD-10-CM codes for accurately identifying IH following abdominal surgery. This method yields &gt;94% for key validity measures.

Without Warning: Worker Deaths From Heat 2014–2016

2018 ◽  
Vol 28 (2) ◽  
pp. 344-357 ◽  
Author(s):  
Cora Roelofs
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Heat Stroke ◽  
Heat Exposure ◽  
Heat Index ◽  
Heat Illness ◽  
National Weather Service ◽  
Illness Prevention ◽  
Surveillance And Response ◽  
Weather Service

Worker deaths from heat exposure are unlike heat deaths in the general population; workers tend to be outside in variable temperatures and younger than sixty-five years. Climate change will increase the frequency, duration, and variability of hot temperatures. Public health warning systems, such as the Heat Index of the National Weather Service, do not generally account for workers' greater likelihood of exposure to direct sunlight or exertion. Only 28% of the 79 worker heat-related fatalities during 2014–2016 occurred on days when the National Weather Service warning would have included the possibility of fatal heat stroke. Common heat illness prevention advice ignores workers' lack of control over their ability to rest and seek cooler temperatures. Additionally, acclimatization, or phased-in work in the heat, may be less useful given temperature variability under climate change. Workers' vulnerability and context of heat exposure should inform public health surveillance and response to prevent heat illness and death.

scholarly journals Accuracy of ICD-10-CM coding for physical child abuse in a paediatric level I trauma centre

2021 ◽  
Vol 27 (Suppl 1) ◽  
pp. i71-i74
Author(s):  
Holly Hughes Garza ◽  
Karen E Piper ◽  
Amanda N Barczyk ◽  
Adriana Pérez ◽  
Karla A Lawson
Keyword(s):  
Child Abuse ◽  
Physical Abuse ◽  
Child Protection ◽  
International Classification Of Diseases ◽  
Trauma Centre ◽  
Child Physical Abuse ◽  
Physical Child Abuse ◽  
Predictive Values ◽  
Icd 10 ◽  
Level I

This retrospective study examined the accuracy of the International Classification of Diseases, Clinical Modification (ICD-10-CM) coding for physical child abuse among patients less than 18 years of age who were evaluated due to concern for physical abuse by a multidisciplinary child protection team (MCPT) during 2016–2017 (N=312) in a paediatric level I trauma centre. Sensitivity, specificity, predictive values and diagnostic OR for ICD-10-CM coding were calculated and stratified by admission status, using as a reference standard the abuse determination of the MCPT recorded in a hospital registry. Among inpatients, child physical abuse coding sensitivity was 55.6% (95% CI 41.4% to 69.1%) and specificity was 78.6% (95% CI 59.0% to 91.7%), with diagnostic OR of 4.58 (95% CI 1.64 to 12.70). Among outpatients, sensitivity was 22.2% (95% CI 15.5% to 30.2%) and specificity was 86.3% (95% CI 77.7% to 92.5%), with diagnostic OR of 1.80 (95% CI 0.89 to 3.64). Use of ICD-10-CM coded data sets alone for surveillance may significantly underestimate the occurrence of physical child abuse.

scholarly journals Heat-Associated Mortality in a Hot Climate

2020 ◽  
Vol 135 (5) ◽  
pp. 631-639
Author(s):  
Sally Ann Iverson ◽  
Aaron Gettel ◽  
Carla P. Bezold ◽  
Kate Goodin ◽  
Benita McKinney ◽  
...  
Keyword(s):  
Sonoran Desert ◽  
Surveillance System ◽  
Heat Stroke ◽  
Heat Exposure ◽  
International Classification Of Diseases ◽  
Maricopa County ◽  
Hot Climate ◽  
Location Of Death ◽  
Populations At Risk ◽  
Classification Of Diseases

Objectives Maricopa County, Arizona (2017 population about 4.3 million), is located in the Sonoran Desert. In 2005, the Maricopa County Department of Public Health (MCDPH) established a heat-associated mortality surveillance system that captures data on circumstances of death for Maricopa County residents and visitors. We analyzed 2006-2016 surveillance system data to understand the characteristics and circumstances of heat-associated deaths. Methods We classified heat-associated deaths based on International Classification of Diseases, Tenth Revision codes (X30, T67.X, and P81.0) and phrases (heat exposure, environ, exhaustion, sun, heat stress, heat stroke, or hyperthermia) in part I or part II of the death certificate. We summarized data on decedents’ demographic characteristics, years lived in Arizona, location of death (indoors vs outdoors), presence and functionality of air conditioning, and whether the decedent had been homeless. We examined significant associations between variables by using the Pearson χ2 tests and logistic regression. Results During 2006-2016, MCDPH recorded data on 920 heat-associated deaths, 912 of which included location of injury. Of 565 (62%) heat-associated deaths that occurred outdoors, 458 (81%) were among male decedents and 243 (43%) were among decedents aged 20-49. Of 347 (38%) heat-associated deaths that occurred indoors, 201 (58%) were among decedents aged ≥65. Non-Arizona residents were 5 times as likely as Arizona residents to have a heat-associated death outdoors ( P < .001). Of 727 decedents with data on duration of Arizona residency, 438 (60%) had resided in Arizona ≥20 years. Conclusions Ongoing evaluation of interventions that target populations at risk for both outdoor and indoor heat-associated deaths can further inform refinement of the surveillance system and identify best practices to prevent heat-associated deaths.

A Guide to Coding and Billing for the Audiological Management of Patients Receiving Ototoxic Medical Treatments

2019 ◽  
Vol 4 (5) ◽  
pp. 936-946
Author(s):  
Dawn Konrad-Martin ◽  
Neela Swanson ◽  
Angela Garinis
Keyword(s):  
Otoacoustic Emissions ◽  
Best Practice ◽  
Private Insurance ◽  
Monitoring Program ◽  
Current Method ◽  
International Classification Of Diseases ◽  
Ethical Practice ◽  
Party Payer ◽  
High Frequency Audiometry ◽  
Icd 10

Purpose Improved medical care leading to increased survivorship among patients with cancer and infectious diseases has created a need for ototoxicity monitoring programs nationwide. The goal of this report is to promote effective and standardized coding and 3rd-party payer billing practices for the audiological management of symptomatic ototoxicity. Method The approach was to compile the relevant International Classification of Diseases, 10th Revision (ICD-10-CM) codes and Current Procedural Terminology (CPT; American Medical Association) codes and explain their use for obtaining reimbursement from Medicare, Medicaid, and private insurance. Results Each claim submitted to a payer for reimbursement of ototoxicity monitoring must include both ICD-10-CM codes to report the patient's diagnosis and CPT codes to report the services provided by the audiologist. Results address the general 3rd-party payer guidelines for ototoxicity monitoring and ICD-10-CM and CPT coding principles and provide illustrative examples. There is no “stand-alone” CPT code for high-frequency audiometry, an important test for ototoxicity monitoring. The current method of adding a –22 modifier to a standard audiometry code and then submitting a letter rationalizing why the test was done has inconsistent outcomes and is time intensive for the clinician. Similarly, some clinicians report difficulty getting reimbursed for detailed otoacoustic emissions testing in the context of ototoxicity monitoring. Conclusions Ethical practice, not reimbursement, must guide clinical practice. However, appropriate billing and coding resulting in 3rd-party reimbursement for audiology services rendered is critical for maintaining an effective ototoxicity monitoring program. Many 3rd-party payers reimburse for these services. For any CPT code, payment patterns vary widely within and across 3rd-party payers. Standardizing coding and billing practices as well as advocacy including letters from audiology national organizations may be necessary to help resolve these issues of coding and coverage in order to support best practice recommendations for ototoxicity monitoring.

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.

ICD10Net: An Artificial Intelligence Algorithm with Medical Background Conducts ICD-10-CM Coding Task with Outstanding Performance (Preprint)

2019 ◽  
Author(s):  
Chin Lin ◽  
Yu-Sheng Lou ◽  
Chia-Cheng Lee ◽  
Chia-Jung Hsu ◽  
Ding-Chung Wu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
General Hospital ◽  
Pearson Correlation ◽  
Model Performance ◽  
International Classification Of Diseases ◽  
Free Text ◽  
Daily Work ◽  
Medical Background ◽  
Icd 10 ◽  
F Measure

BACKGROUND An artificial intelligence-based algorithm has shown a powerful ability for coding the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) in discharge notes. However, its performance still requires improvement compared with human experts. The major disadvantage of the previous algorithm is its lack of understanding medical terminologies. OBJECTIVE We propose some methods based on human-learning process and conduct a series of experiments to validate their improvements. METHODS We compared two data sources for training the word-embedding model: English Wikipedia and PubMed journal abstracts. Moreover, the fixed, changeable, and double-channel embedding tables were used to test their performance. Some additional tricks were also applied to improve accuracy. We used these methods to identify the three-chapter-level ICD-10-CM diagnosis codes in a set of discharge notes. Subsequently, 94,483-labeled discharge notes from June 1, 2015 to June 30, 2017 were used from the Tri-Service General Hospital in Taipei, Taiwan. To evaluate performance, 24,762 discharge notes from July 1, 2017 to December 31, 2017, from the same hospital were used. Moreover, 74,324 additional discharge notes collected from other seven hospitals were also tested. The F-measure is the major global measure of effectiveness. RESULTS In understanding medical terminologies, the PubMed-embedding model (Pearson correlation = 0.60/0.57) shows a better performance compared with the Wikipedia-embedding model (Pearson correlation = 0.35/0.31). In the accuracy of ICD-10-CM coding, the changeable model both used the PubMed- and Wikipedia-embedding model has the highest testing mean F-measure (0.7311 and 0.6639 in Tri-Service General Hospital and other seven hospitals, respectively). Moreover, a proposed method called a hybrid sampling method, an augmentation trick to avoid algorithms identifying negative terms, was found to additionally improve the model performance. CONCLUSIONS The proposed model architecture and training method is named as ICD10Net, which is the first expert level model practically applied to daily work. This model can also be applied in unstructured information extraction from free-text medical writing. We have developed a web app to demonstrate our work (https://linchin.ndmctsgh.edu.tw/app/ICD10/).

Sign in / Sign up

Export Citation Format

Share Document