scholarly journals WikiMedMap: Expanding the Phenotyping Mapping Toolbox Using Wikipedia

2019 ◽  
Author(s):  
Lina Sulieman ◽  
Patrick Wu ◽  
Joshua C. Denny ◽  
Lisa Bastarache
Keyword(s):  
International Classification Of Diseases ◽  
Mendelian Inheritance ◽  
Medical Subject Headings ◽  
Phenotypic Data ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Conventional Mapping ◽  
The Uk ◽  
Omim Database

AbstractResearchers utilizing phenotypic data from diverse sources require matching of phenotypes to standard clinical vocabularies. Mapping phenotypes to vocabulary can be difficult, as existing tools are often incomplete, can be difficult to access, and can be cumbersome to use, especially for non-experts. We created WikiMedMap as a simple tool that leverages Wikipedia and maps phenotype strings to standard clinical vocabularies. We assessed WikiMedMap by mapping phenotype strings from questionnaires in the UK Biobank and from Mendelian diseases in Online Mendelian Inheritance in Man (OMIM) database to eight vocabularies: International Classification of Diseases, Ninth Revision (ICD-9), ICD-10, ICD-O, Medical Subject Headings (MeSH), OMIM, Disease Database, and MedlinePlus. WikiMedMap outperformed conventional mapping tools in finding potential matches for phenotype strings. We envision WikiMedMap as a technique that complements existing and established tools to map strings to clinical vocabularies that usually do not coexist in one source.

scholarly journals Developing and Evaluating Mappings of ICD-10 and ICD-10-CM Codes to PheCodes

2018 ◽  
Author(s):  
Patrick Wu ◽  
Aliya Gifford ◽  
Xiangrui Meng ◽  
Xue Li ◽  
Harry Campbell ◽  
...  
Keyword(s):  
Medical Center ◽  
Association Studies ◽  
International Classification Of Diseases ◽  
Snomed Ct ◽  
Unified Medical Language System ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
The Uk ◽  
Systematized Nomenclature Of Medicine

AbstractBackgroundThe PheCode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) in the electronic health record (EHR).ObjectiveHere, we present our work on the development and evaluation of maps from ICD-10 and ICD-10-CM codes to PheCodes.MethodsWe mapped ICD-10 and ICD-10-CM codes to PheCodes using a number of methods and resources, such as concept relationships and explicit mappings from the Unified Medical Language System (UMLS), Observational Health Data Sciences and Informatics (OHDSI), Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT), and National Library of Medicine (NLM). We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM→PheCode map by investigating phenotype reproducibility and conducting a PheWAS.ResultsWe mapped >75% of ICD-10-CM and ICD-10 codes to PheCodes. Of the unique codes observed in the VUMC (ICD-10-CM) and UKBB (ICD-10) cohorts, >90% were mapped to PheCodes. We observed 70-75% reproducibility for chronic diseases and <10% for an acute disease. A PheWAS with a lipoprotein(a) (LPA) genetic variant, rs10455872, using the ICD-9-CM and ICD-10-CM maps replicated two genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P < .001, OR = 1.60 vs. ICD-10-CM: P < .001, OR = 1.60) and with chronic ischemic heart disease (ICD-9-CM: P < .001, OR = 1.5 vs. ICD-10-CM: P < .001, OR = 1.47).ConclusionsThis study introduces the initial “beta” versions of ICD-10 and ICD-10-CM to PheCode maps that will enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for high-throughput PheWAS in the EHR.

scholarly journals Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation

10.2196/14325 ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. e14325 ◽  
Author(s):  
Patrick Wu ◽  
Aliya Gifford ◽  
Xiangrui Meng ◽  
Xue Li ◽  
Harry Campbell ◽  
...  
Keyword(s):  
Medical Center ◽  
Association Studies ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Initial Evaluation ◽  
Unified Medical Language System ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
The Uk

Background The phecode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) using the electronic health record (EHR). Objective The goal of this paper was to develop and perform an initial evaluation of maps from the International Classification of Diseases, 10th Revision (ICD-10) and the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes to phecodes. Methods We mapped ICD-10 and ICD-10-CM codes to phecodes using a number of methods and resources, such as concept relationships and explicit mappings from the Centers for Medicare & Medicaid Services, the Unified Medical Language System, Observational Health Data Sciences and Informatics, Systematized Nomenclature of Medicine-Clinical Terms, and the National Library of Medicine. We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM phecode map by investigating phenotype reproducibility and conducting a PheWAS. Results We mapped >75% of ICD-10 and ICD-10-CM codes to phecodes. Of the unique codes observed in the UKBB (ICD-10) and VUMC (ICD-10-CM) cohorts, >90% were mapped to phecodes. We observed 70-75% reproducibility for chronic diseases and <10% for an acute disease for phenotypes sourced from the ICD-10-CM phecode map. Using the ICD-9-CM and ICD-10-CM maps, we conducted a PheWAS with a Lipoprotein(a) genetic variant, rs10455872, which replicated two known genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P<.001; odds ratio (OR) 1.60 [95% CI 1.43-1.80] vs ICD-10-CM: P<.001; OR 1.60 [95% CI 1.43-1.80]) and chronic ischemic heart disease (ICD-9-CM: P<.001; OR 1.56 [95% CI 1.35-1.79] vs ICD-10-CM: P<.001; OR 1.47 [95% CI 1.22-1.77]). Conclusions This study introduces the beta versions of ICD-10 and ICD-10-CM to phecode maps that enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for PheWAS in the EHR.

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.

scholarly journals Neue Terminologie für Sprachentwicklungsstörungen?

2021 ◽  
Author(s):  
K. Neumann ◽  
B. Arnold ◽  
A. Baumann ◽  
C. Bohr ◽  
H. A. Euler ◽  
...  
Keyword(s):  
International Classification Of Diseases ◽  
International Classification ◽  
International Classification Of Disease ◽  
Diagnostik Und Therapie ◽  
Classification Of Diseases ◽  
Icd 10

Zusammenfassung Hintergrund Sprachtherapeutisch-linguistische Fachkreise empfehlen die Anpassung einer von einem internationalen Konsortium empfohlenen Änderung der Nomenklatur für Sprachstörungen im Kindesalter, insbesondere für Sprachentwicklungsstörungen (SES), auch für den deutschsprachigen Raum. Fragestellung Ist eine solche Änderung in der Terminologie aus ärztlicher und psychologischer Sicht sinnvoll? Material und Methode Kritische Abwägung der Argumente für und gegen eine Nomenklaturänderung aus medizinischer und psychologischer Sicht eines Fachgesellschaften- und Leitliniengremiums. Ergebnisse Die ICD-10-GM (Internationale statistische Klassifikation der Krankheiten und verwandter Gesundheitsprobleme, 10. Revision, German Modification) und eine S2k-Leitlinie unterteilen SES in umschriebene SES (USES) und SES assoziiert mit anderen Erkrankungen (Komorbiditäten). Die USES- wie auch die künftige SES-Definition der ICD-11 (International Classification of Diseases 11th Revision) fordern den Ausschluss von Sinnesbehinderungen, neurologischen Erkrankungen und einer bedeutsamen intellektuellen Einschränkung. Diese Definition erscheint weit genug, um leichtere nonverbale Einschränkungen einzuschließen, birgt nicht die Gefahr, Kindern Sprach- und weitere Therapien vorzuenthalten und erkennt das ICD(International Classification of Disease)-Kriterium, nach dem der Sprachentwicklungsstand eines Kindes bedeutsam unter der Altersnorm und unterhalb des seinem Intelligenzalter angemessenen Niveaus liegen soll, an. Die intendierte Ersetzung des Komorbiditäten-Begriffs durch verursachende Faktoren, Risikofaktoren und Begleiterscheinungen könnte die Unterlassung einer dezidierten medizinischen Differenzialdiagnostik bedeuten. Schlussfolgerungen Die vorgeschlagene Terminologie birgt die Gefahr, ätiologisch bedeutsame Klassifikationen und differenzialdiagnostische Grenzen zu verwischen und auf wertvolles ärztliches und psychologisches Fachwissen in Diagnostik und Therapie sprachlicher Störungen im Kindesalter zu verzichten.

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.

Impact of ICD-9 to ICD-10 Coding Transition on Prevalence Trends in Neurology

2021 ◽  
Vol 11 (5) ◽  
pp. e612-e619
Author(s):  
Ali G. Hamedani ◽  
Leah Blank ◽  
Dylan P. Thibault ◽  
Allison W. Willis
Keyword(s):  
Time Series ◽  
Status Epilepticus ◽  
Interrupted Time Series ◽  
International Classification Of Diseases ◽  
Disease Prevalence ◽  
Rate Of Change ◽  
International Classification ◽  
Classification Of Diseases ◽  
Icd 10

ObjectiveTo determine the effect of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) coding transition on the point prevalence and longitudinal trends of 16 neurologic diagnoses.MethodsWe used 2014–2017 data from the National Inpatient Sample to identify hospitalizations with one of 16 common neurologic diagnoses. We used published ICD-9-CM codes to identify hospitalizations from January 1, 2014, to September 30, 2015, and used the Agency for Healthcare Research and Quality's MapIt tool to convert them to equivalent ICD-10-CM codes for October 1, 2015–December 31, 2017. We compared the prevalence of each diagnosis before vs after the ICD coding transition using logistic regression and used interrupted time series regression to model the longitudinal change in disease prevalence across time.ResultsThe average monthly prevalence of subarachnoid hemorrhage was stable before the coding transition (average monthly increase of 4.32 admissions, 99.7% confidence interval [CI]: −8.38 to 17.01) but increased after the coding transition (average monthly increase of 24.32 admissions, 99.7% CI: 15.71–32.93). Otherwise, there were no significant differences in the longitudinal rate of change in disease prevalence over time between ICD-9-CM and ICD-10-CM. Six of 16 neurologic diagnoses (37.5%) experienced significant changes in cross-sectional prevalence during the coding transition, most notably for status epilepticus (odds ratio 0.30, 99.7% CI: 0.26–0.34).ConclusionsThe transition from ICD-9-CM to ICD-10-CM coding affects prevalence estimates for status epilepticus and other neurologic disorders, a potential source of bias for future longitudinal neurologic studies. Studies should limit to 1 coding system or use interrupted time series models to adjust for changes in coding patterns until new neurology-specific ICD-9 to ICD-10 conversion maps can be developed.

Validation of ICD-10 codes shows intracranial venous thrombosis incidence to be higher than previously reported

2018 ◽  
Vol 49 (1) ◽  
pp. 58-61 ◽  
Author(s):  
Joel D Handley ◽  
Hedley CA Emsley
Keyword(s):  
Positive Predictive Value ◽  
Cerebral Infarction ◽  
Venous Thrombosis ◽  
Cerebral Venous Thrombosis ◽  
International Classification Of Diseases ◽  
Coding System ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
In Pregnancy

Background: Intracranial venous thrombosis (ICVT) accounts for around 0.5% of all stroke cases. There have been no previously published studies of the International Classification of Diseases, Tenth Edition (ICD-10) validation for the identification of ICVT admissions in adults. Objective: The aims of this study were to validate and quantify the performance of the ICD-10 coding system for identifying cases of ICVT in adults and to derive an estimate of incidence. Method: Administrative data were collected for all patients admitted to a regional neurosciences centre over a 5-year period. We searched for the following ICD-10 codes at any position: G08.X (intracranial and intraspinal phlebitis and thrombophlebitis), I67.6 (non-pyogenic thrombosis of intracranial venous system), I63.6 (cerebral infarction due to cerebral venous thrombosis, non-pyogenic), O22.5 (cerebral venous thrombosis in pregnancy) and O87.3 (cerebral venous thrombosis in the puerperium). Results: Sixty-five admissions were identified by at least one of the relevant ICD-10 codes. The overall positive predictive value (PPV) for confirmed ICVT from all of the admissions combined was 92.3% (60 out of 65) with the results for each code as follows: G08.X 91.5% (54 of 59), O22.5 100% (4 of 4), I67.6 100% (1 of 1), I63.6 100% (1 of 1) and O87.3 100% (1 of 1). There were 40 unique cases of ICVT over a 5-year period giving an annual incidence of ICVT of 5 per million. Conclusions: All codes gave a high PPV. Implications for practice: As demonstrated in previous studies, the incidence of ICVT may be higher than previously thought.

scholarly journals Adverse drug events identified in hospitalized patients in Brazil by International Classification of Diseases (ICD-10) code listings

2018 ◽  
Vol 34 (12) ◽  
Author(s):  
Ana Cristina Martins ◽  
Fabíola Giordani ◽  
Lusiele Guaraldo ◽  
Gianni Tognoni ◽  
Suely Rozenfeld
Keyword(s):  
Public Health ◽  
Adverse Drug Events ◽  
International Classification Of Diseases ◽  
Hospitalized Patients ◽  
International Classification ◽  
Administrative Databases ◽  
National Database ◽  
Classification Of Diseases ◽  
Icd 10

Studies of adverse drug events (ADEs) are important in order not to jeopardize the positive impact of pharmacotherapy. These events have substantial impact on the population morbidity profiles, and increasing health system operating costs. Administrative databases are an important source of information for public health purposes and for identifying ADEs. In order to contribute to learning about ADE in hospitalized patients, this study examined the potential of applying ICD-10 (10th revision of the International Classification of Diseases) codes to a national database of the public health care system (SIH-SUS). The study comprised retrospective assessment of ADEs in the SIH-SUS administrative database, from 2008 to 2012. For this, a list of ICD-10 codes relating to ADEs was built. This list was built up by examining lists drawn up by other authors identified by bibliographic search in the MEDLINE and LILACS and consultations with experts. In Brazil, 55,604,537 hospital admissions were recorded in the SIH-SUS, between 2008 and 2012, of which 273,440 (0.49%) were related to at least one ADE. The proportions and rates seem to hold constant over the study period. Fourteen out of 20 most frequent ADEs were identified in codes relating to mental disorders. Intoxications figure as the second most frequently recorded group of ADEs in the SIH-SUS, comprising 76,866 hospitalizations. Monitoring of ADEs in administrative databases using ICD-10 codes is feasible, even in countries with information systems under construction, and can be an innovative tool to complement drug surveillance strategies in place in Brazil, as well as in others countries.

scholarly journals Epidemiological Profile of Intracerebral Hemorrhage during a 10-Year Period in a Southern Brazilian Region

2018 ◽  
Vol 37 (01) ◽  
pp. 7-12
Author(s):  
Timóteo Almeida ◽  
Fernanda Almeida ◽  
Luidia Giacomini ◽  
Andressa Niederauer ◽  
Anna Cho ◽  
...  
Keyword(s):  
Surgical Treatment ◽  
Intracerebral Hemorrhage ◽  
Epidemiological Data ◽  
International Classification Of Diseases ◽  
Spontaneous Intracerebral Hemorrhage ◽  
Anticoagulant Drugs ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Epidemiological Profile

Objective Spontaneous intracerebral hemorrhage is responsible for 20% of all cases of cerebrovascular accidents, which might lead to functional disabilities and death. There are few epidemiological data on spontaneous intracerebral hemorrhage in Brazil, and more specifically in the southern region of the country. Methods We reviewed data of 221 patients with intracerebral hemorrhage who attended our department between January of 2004 and December of 2013 and were registered as I61 and I62 according to the 10th edition of the International Classification of Diseases and Related Health Problems (ICD-10). Results From the 221 cases, 53.8% were male, and the median age was 63 years old. Arterial hypertension was reported in 62.4% of the patients. Surgical treatment was performed in 28.9% of all cases and pneumonia affected 19.9%. In 73.4% of the cases, the patients died or were severely disabled at discharge. We found an association of heart disease, coagulopathies, chronic kidney disease, anticoagulant drugs use, surgical treatment, and pneumonia with a poorer outcome. Conclusion The present study describes the epidemiological profile of intracerebral hemorrhage in a southern Brazilian population during a 10-year period.

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