scholarly journals Performance of Cancer Recurrence Algorithms After Coding Scheme Switch From International Classification of Diseases 9th Revision to International Classification of Diseases 10th Revision

2019 ◽  
pp. 1-9 ◽  
Author(s):  
Nikki M. Carroll ◽  
Debra P. Ritzwoller ◽  
Matthew P. Banegas ◽  
Maureen O’Keeffe-Rosetti ◽  
Angel M. Cronin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Performance Measures ◽  
Cancer Recurrence ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Receiver Operating Curve ◽  
Classification Of Diseases ◽  
The Impact ◽  
Receiver Operating

PURPOSE We previously developed and validated informatic algorithms that used International Classification of Diseases 9th revision (ICD9)–based diagnostic and procedure codes to detect the presence and timing of cancer recurrence (the RECUR Algorithms). In 2015, ICD10 replaced ICD9 as the worldwide coding standard. To understand the impact of this transition, we evaluated the performance of the RECUR Algorithms after incorporating ICD10 codes. METHODS Using publicly available translation tables along with clinician and other expertise, we updated the algorithms to include ICD10 codes as additional input variables. We evaluated the performance of the algorithms using gold standard recurrence measures associated with a contemporary cohort of patients with stage I to III breast, colorectal, and lung (excluding IIIB) cancer and derived performance measures, including the area under the receiver operating curve, average absolute prediction error, and correct classification rate. These values were compared with the performance measures derived from the validation of the original algorithms. RESULTS A total of 659 colorectal, 280 lung, and 2,053 breast cancer cases were identified. Area under the receiver operating curve derived from the updated algorithms was 89.0% (95% CI, 82.3% to 95.7%), 88.9% (95% CI, 79.3% to 98.2%), and 80.5% (95% CI, 72.8% to 88.2%) for the colorectal, lung, and breast cancer algorithms, respectively. Average absolute prediction errors for recurrence timing were 2.7 (SE, 11.3%), 2.4 (SE, 10.4%), and 5.6 months (SE, 21.8%), respectively, and timing estimates were within 6 months of actual recurrence for more than 80% of colorectal, more than 90% of lung, and more than 50% of breast cancer cases using the updated algorithm. CONCLUSION Performance measures derived from the updated and original algorithms had overlapping confidence intervals, suggesting that the ICD9 to ICD10 transition did not affect the RECUR Algorithm performance.

scholarly journals Estimated Burden of Methicillin-Resistant Staphylococcus aureus in California Hospitals after Changes to Administrative Codes, 2005–2010

2013 ◽  
Vol 34 (11) ◽  
pp. 1218-1221 ◽  
Author(s):  
David M. Tehrani ◽  
Chenghua Cao ◽  
Homin Kwark ◽  
Susan S. Huang
Keyword(s):  
Staphylococcus Aureus ◽  
Methicillin Resistant Staphylococcus Aureus ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Methicillin Resistant ◽  
Classification Of Diseases ◽  
The Impact

We assess the impact of revised International Classification of Diseases, Ninth Revision, codes on methicillin-resistant Staphylococcus aureus burden in California hospitals. Codes were rapidly adopted, demonstrating new capture of colonization and continued relatively stable capture of infections. Nevertheless, despite new colonization codes, coded data demonstrated poor retention between serial hospitalizations.

scholarly journals A narrative review of the impact of the transition to ICD-10 and ICD-10-CM/PCS

JAMIA Open ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 126-131 ◽  
Author(s):  
Sheila V Kusnoor ◽  
Mallory N Blasingame ◽  
Annette M Williams ◽  
Spencer J DesAutels ◽  
Jing Su ◽  
...  
Keyword(s):  
United States ◽  
International Classification Of Diseases ◽  
The United States ◽  
International Classification ◽  
Morbidity And Mortality ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
The Impact ◽  
Mortality Surveillance

Abstract Objectives The United States transitioned to the tenth version of the International Classification of Diseases (ICD) system (ICD-10) for mortality coding in 1999 and to the International Classification of Diseases, Clinical Modification and Procedure Coding System (ICD-10-CM/PCS) on October 1, 2015. The purpose of this study was to conduct a narrative literature review to better understand the impact of the implementation of ICD-10/ICD-10-CM/PCS. Materials and Methods We searched English-language articles in PubMed, Web of Science, and Business Source Complete and reviewed websites of relevant professional associations, government agencies, research groups, and ICD-10 news aggregators to identify literature on the impact of the ICD-10/ICD-10-CM/PCS transition. We used Google to search for additional gray literature and used handsearching of the references of the most on-target articles to help ensure comprehensiveness. Results Impact areas reported in the literature include: productivity and staffing, costs, reimbursement, coding accuracy, mapping between ICD versions, morbidity and mortality surveillance, and patient care. With the exception of morbidity and mortality surveillance, quantitative studies describing the actual impact of the ICD-10/ICD-10-CM/PCS implementation were limited and much of the literature was based on the ICD-10-CM/PCS transition rather than the earlier conversion to ICD-10 for mortality coding. Discussion This study revealed several gaps in the literature that limit the ability to draw reliable conclusions about the overall impact, positive or negative, of moving to ICD-10/ICD-10-CM/PCS in the United States. Conclusion These knowledge gaps present an opportunity for future research and knowledge sharing and will be important to consider when planning for ICD-11.

Development and Use of Natural Language Processing for Identification of Distant Cancer Recurrence and Sites of Distant Recurrence Using Unstructured Electronic Health Record Data

2021 ◽  
pp. 469-478
Author(s):  
Yasmin H. Karimi ◽  
Douglas W. Blayney ◽  
Allison W. Kurian ◽  
Jeanne Shen ◽  
Rikiya Yamashita ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Language Processing ◽  
Large Scale ◽  
Cancer Recurrence ◽  
International Classification Of Diseases ◽  
Distant Recurrence ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Classification Of Diseases

PURPOSE Large-scale analysis of real-world evidence is often limited to structured data fields that do not contain reliable information on recurrence status and disease sites. In this report, we describe a natural language processing (NLP) framework that uses data from free-text, unstructured reports to classify recurrence status and sites of recurrence for patients with breast and hepatocellular carcinomas (HCC). METHODS Using two cohorts of breast cancer and HCC cases, we validated the ability of a previously developed NLP model to distinguish between no recurrence, local recurrence, and distant recurrence, based on clinician notes, radiology reports, and pathology reports compared with manual curation. A second NLP model was trained and validated to identify sites of recurrence. We compared the ability of each NLP model to identify the presence, timing, and site of recurrence, when compared against manual chart review and International Classification of Diseases coding. RESULTS A total of 1,273 patients were included in the development and validation of the two models. The NLP model for recurrence detects distant recurrence with an area under the curve of 0.98 (95% CI, 0.96 to 0.99) and 0.95 (95% CI, 0.88 to 0.98) in breast and HCC cohorts, respectively. The mean accuracy of the NLP model for detecting any site of distant recurrence was 0.9 for breast cancer and 0.83 for HCC. The NLP model for recurrence identified a larger proportion of patients with distant recurrence in a breast cancer database (11.1%) compared with International Classification of Diseases coding (2.31%). CONCLUSION We developed two NLP models to identify distant cancer recurrence, timing of recurrence, and sites of recurrence based on unstructured electronic health record data. These models can be used to perform large-scale retrospective studies in oncology.

scholarly journals Leveraging unstructured data to identify hereditary angioedema patients in electronic medical records

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Emily S. Brouwer ◽  
Emily W. Bratton ◽  
Aimee M. Near ◽  
Lynn Sanders ◽  
Christina D. Mack
Keyword(s):  
Hereditary Angioedema ◽  
Retrospective Studies ◽  
False Positive Rate ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Unstructured Data ◽  
Diagnostic Coding ◽  
Classification Of Diseases ◽  
The Impact

Abstract Background The epidemiologic impact of hereditary angioedema (HAE) is difficult to quantify, due to misclassification in retrospective studies resulting from non-specific diagnostic coding. The aim of this study was to identify cohorts of patients with HAE-1/2 by evaluating structured and unstructured data in a US ambulatory electronic medical record (EMR) database. Methods A retrospective feasibility study was performed using the GE Centricity EMR Database (2006–2017). Patients with ≥ 1 diagnosis code for HAE-1/2 (International Classification of Diseases, Ninth Revision, Clinical Modification 277.6 or International Classification of Diseases, Tenth Revision, Clinical Modification D84.1) and/or ≥ 1 physician note regarding HAE-1/2 and ≥ 6 months’ data before and after the earliest code or note (index date) were included. Two mutually exclusive cohorts were created: probable HAE (≥ 2 codes or ≥ 2 notes on separate days) and suspected HAE (only 1 code or note). The impact of manually reviewing physician notes on cohort formation was assessed, and demographic and clinical characteristics of the 2 final cohorts were described. Results Initially, 1691 patients were identified: 190 and 1501 in the probable and suspected HAE cohorts, respectively. After physician note review, the confirmed HAE cohort comprised 254 patients and the suspected HAE cohort decreased to 1299 patients; 138 patients were determined not to have HAE and were excluded. The overall false-positive rate for the initial algorithms was 8.2%. Across final cohorts, the median age was 50 years and > 60% of patients were female. HAE-specific prescriptions were identified for 31% and 2% of the confirmed and suspected HAE cohorts, respectively. Conclusions Unstructured EMR data can provide valuable information for identifying patients with HAE-1/2. Further research is needed to develop algorithms for more representative HAE cohorts in retrospective studies.

scholarly journals The International Classification of Impairments, Disabilities, and Handicaps: A Mental Health Perspective

1995 ◽  
Vol 7 (1) ◽  
pp. 3-7
Author(s):  
Karen Ritchie
Keyword(s):  
Mental Health ◽  
International Classification Of Diseases ◽  
International Classification ◽  
World Health ◽  
Important Place ◽  
The World ◽  
Classification Of Diseases ◽  
Health Organization ◽  
The Impact

The International Classification of Impairments, Disabilities, and Handicaps (the ICIDH) was developed in the 1970s as an extension of the World Health Organization's International Classification of Diseases (ICD). It was developed principally to meet the criticisms of ICD users who thought that the ICD (a) did not sufficiently cover the impact of a given disease on an individual and the society in which he or she lived, and (b) was unable to describe the heterogeneity of the clinical expression of a disorder and the disorder's variable evolution in different individuals and societies. The ICIDH was first published by the World Health Organization (WHO) in 1980 and is currently undergoing its first major revision. In this revision process, psychiatry is being given an important place in response to complaints of users that the ICIDH presently has limited application in the mental health field. In a brief discussion here, I would like to describe the role of the ICIDH in relation to mental health—and to psychogeriatrics in particular—drawing on a number of debates in which I have been involved over the past few years.

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.

Störungen durch Substanzgebrauch und abhängige Verhaltensweisen in der ICD-11

2020 ◽  
pp. 1-8
Author(s):  
Nicolas Arnaud ◽  
Rainer Thomasius
Keyword(s):  
International Classification Of Diseases ◽  
International Classification ◽  
Classification Of Diseases

Zusammenfassung. Der Beitrag informiert über die Eingliederung der Suchtstörungen in die 11. Auflage der International Classification of Diseases (ICD-11) der Weltgesundheitsorganisation (WHO). Die Revision der ICD soll einem gewandelten Verständnis der Suchtstörungen und deren Diagnostik Rechnung tragen und die klinische Anwendbarkeit vereinfachen. Im Bereich der substanzbezogenen und nicht substanzbezogenen Störungen sind gegenüber der Vorgängerversion erhebliche Neuerungen eingeführt worden. Die wichtigsten Änderungen betreffen ein erweitertes Angebot an Stoffklassen, deutliche (vereinfachende) Anpassungen in den konzeptuellen und diagnostischen Leitlinien der substanzbezogenen Störungsbilder und insbesondere der „Abhängigkeit“, sowie die Einführung der Kategorie der „abhängigen Verhaltensweisen“ und damit verbunden die Zuordnung der „Glücksspielstörung“ zu den Suchtstörungen sowie die Aufnahme der neuen (bildschirmbezogenen) „Spielstörung“. Zudem findet eine Erweiterung der diagnostischen Optionen für frühe, präklinische Phänotypen der Suchtstörungen („Episodisch Schädlicher Gebrauch“) erstmals Eingang in den ICD-Katalog. Im vorliegenden Beitrag werden die Änderungen Episodisch schädlicher Gebrauch für den Bereich der Suchtstörungen aus kinder- und jugendpsychiatrischer Sicht zusammenfassend dargestellt und diskutiert.

Zusatzklassifikation zur Kennzeichnung von Personen ohne akute Beschwerden oder Krankheiten)

1968 ◽  
Vol 07 (03) ◽  
pp. 141-151 ◽  
Author(s):  
H. Fassl
Keyword(s):  
International Classification Of Diseases ◽  
International Classification ◽  
Classification Of Diseases

In Krankenprotokollen finden sieb, nicht selten Angaben über den Patienten, die nicht mehr als Diagnosen anzusprechen sind. Dennoch sollten diese Feststellungen nicht verworfen werden, da sie wichtige Informationen darstellen. In der vorliegenden Arbeit wird (dem Vorschlag der Weltgesundheitsorganisation folgend) eine sog. Y-Klassifikation vorgestellt, mittels derer Feststellungen bei Personen ohne akute Klagen oder. Erkrankungen verschlüsselt werden können (z. B. Zustand nach einer Krankheit oder Verletzung, Verdacht auf eine Krankheit, Nachsorgemaßnahmen, prophylaktische Maßnahmen usw.). Der Entwurf folgt der Systematik der ICD (International Classification of Diseases) und kann dazu benutzt werden, gewisse Lücken darin zu überbrücken.

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