scholarly journals Exploring the implications of the new ICD-10-CM classification system for injury surveillance: analysis of dually coded data from two medical centres

2021 ◽  
Vol 27 (S1) ◽  
pp. i19-i26
Author(s):  
Eduard A Poltavskiy ◽  
Susan H Fenton ◽  
Oluseun Atolagbe ◽  
Banafsheh Sadeghi ◽  
Heejung Bang ◽  
...  
Keyword(s):  
Classification System ◽  
Motor Vehicle ◽  
International Classification Of Diseases ◽  
Injury Surveillance ◽  
The Other ◽  
Trauma Centres ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Surveillance Analysis

IntroductionExternal cause of injury matrices is used to classify mechanisms/causes of injuries for surveillance and research. Little is known about the performance of the Centers for Disease Control and Prevention’s new external cause of injury matrix for Clinical Modification of the 10th Revision of the International Classification of Diseases (ICD-10-CM), compared with the ICD-9-CM version.MethodsDually coded (ICD-9-CM and ICD-10-CM) administrative data were obtained from two major academic trauma centres. Injury-related cases were identified and categorised by mechanism/cause and manner/intent. Comparability ratios (CR) were used to estimate the net impact of changing from ICD-9-CM to ICD-10-CM on the number of cases classified to each mechanism/cause category. Chamberlain’s percent positive agreements (PPA) were calculated and McNemar’s test was used to assess the significance of observed classification differences.ResultsOf 4832 and 5211 dual-coded records from the two centres, 632 and 520 with injury-related principal diagnoses and external cause codes in both ICD-9-CM and ICD-10-CM were identified. CRs for the mechanisms/causes with at least 20 records ranged from 0.85 to 1.9 at one centre and from 0.97 to 1.07 at the other. Among these mechanisms/causes, PPAs ranged from 33% for ‘other transport’ to 94% for poisoning at one centre, and from 75% for ‘other transport’ to 100% for fires/burns at the other centre. Case assignment differed significantly for falls, motor vehicle traffic, other transport, and ‘struck by/against’ injuries at one centre, and for ‘other pedal cyclist’ at the other centre.ConclusionSwitching to ICD-10-CM and the new external cause of injury matrix may affect injury surveillance and research, especially for certain mechanisms/causes.

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 Experiences with Coding using ICD-11: “The Codes Paint a Clearer Picture”

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Catherine Eastwood ◽  
Danielle Southern ◽  
Alicia Boxill ◽  
Malgorzata Maciszewski ◽  
Hude Quan ◽  
...  
Keyword(s):  
Classification System ◽  
International Classification Of Diseases ◽  
Large Field ◽  
Coding System ◽  
High Performing ◽  
Electronic Survey ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
User Friendly

IntroductionA high performing health data classification system requires clear, comprehensive code descriptions and user-friendly coding tools for effective coding. Coding specialists have essential specialized knowledge to contribute to the development and functionality of the 11th version of International Classification of Diseases (ICD-11) that will be released in June of 2018. Objectives and ApproachThe objective was to evaluate coding specialists’ experience of coding using ICD-11 for complete inpatient hospital charts. Mixed methods were employed for a survey and interviews. As part of a large field trial, 6 certified coding specialists underwent training to use the ICD-11 Beta Draft browser and ICD-11 Coding Tool. The coding team completed multiple coding exercises and coded over 60 charts each prior to evaluation of their experience. An electronic survey was used to evaluate ICD-11 knowledge, comprehension, and application of the coding training. Interviews explored the coders’ experience of learning and using the ICD-11 classification system. ResultsThe coding team (3 to 10 years of experience) received 14 hours classroom training and 5-10 hours per week of coding practice over 3 months. After training, perceived confidence in coding with ICD-11 was satisfactory; moderate (n=4), high (n=1), and low (n=1). Coding short scenarios was the most useful resource (n=6) and lack of guidelines was the most frustrating. Learning ICD-11 was deemed moderately (n=2) to somewhat (n=3) difficult but each coder described satisfaction in learning the new system. From the interviews, coders expressed liking the ability to more fully describe health conditions and hospital harms with code clusters. “The codes paint a clearer picture of what happened than with ICD-10”. With practice they achieved speed with the coding tools. Conclusion/ImplicationsCoding specialists learned and proficiently used the Beta Version of ICD-11 coding system with moderate perceived confidence. New ICD-11 codes and clustering functions allowed for more complete description of health scenarios and enhanced coder satisfaction.

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.

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