Sarcopenia Is Recognized as an Independent Condition by an International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) Code

2016 ◽  
Vol 17 (8) ◽  
pp. 675-677 ◽  
Author(s):  
Li Cao ◽  
John E. Morley
Keyword(s):  
International Classification ◽  
Independent Condition ◽  
International Classification Of Disease ◽  
Icd 10

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 Validating International Classification of Disease 10th revision algorithms for identifying influenza and respiratory syncytial virus hospitalizations

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Mackenzie A Hamilton ◽  
Andrew Calzavara ◽  
Scott D Emerson ◽  
Jeffrey C Kwong
Keyword(s):  
Respiratory Syncytial Virus ◽  
Administrative Data ◽  
Predictive Value ◽  
Hospitalized Patients ◽  
International Classification ◽  
Health Administrative Data ◽  
International Classification Of Disease ◽  
Icd 10 ◽  
Syncytial Virus

Objective: Routinely collected health administrative data can be used to efficiently assess disease burden in large populations, but it is important to evaluate the validity of these data. The objective of this study was to develop and validate International Classification of Disease 10PthP revision (ICD -10) algorithms that identify laboratory-confirmed influenza or laboratory-confirmed respiratory syncytial virus (RSV) hospitalizations using population-based health administrative data from Ontario, Canada. Study Design and Setting: Influenza and RSV laboratory data from the 2014-15 through to 2017-18 respiratory virus seasons were obtained from the Ontario Laboratories Information System (OLIS) and were linked to hospital discharge abstract data to generate influenza and RSV reference cohorts. These reference cohorts were used to assess the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the ICD-10 algorithms. To minimize misclassification in future studies, we prioritized specificity and PPV in selecting top-performing algorithms. Results: 83,638 and 61,117 hospitalized patients were included in the influenza and RSV reference cohorts, respectively. The best influenza algorithm had a sensitivity of 73% (95% CI 72% to 74%), specificity of 99% (95% CI 99% to 99%), PPV of 94% (95% CI 94% to 95%), and NPV of 94% (95% CI 94% to 95%). The best RSV algorithm had a sensitivity of 69% (95% CI 68% to 70%), specificity of 99% (95% CI 99% to 99%), PPV of 91% (95% CI 90% to 91%) and NPV of 97% (95% CI 97% to 97%). Conclusion: We identified two highly specific algorithms that best ascertain patients hospitalized with influenza or RSV. These algorithms may be applied to hospitalized patients if data on laboratory tests are not available, and will thereby improve the power of future epidemiologic studies of influenza, RSV, and potentially other severe acute respiratory infections.

A Strategic Plan for Integrating ICD-10 in Your Practice and Workflow

2015 ◽  
pp. e91-e98 ◽  
Author(s):  
Sue Bowman ◽  
Risë Marie Cleland ◽  
Stuart Staggs
Keyword(s):  
United States ◽  
Strategic Plan ◽  
The United States ◽  
Training Needs ◽  
International Classification ◽  
Diagnosis Code ◽  
International Classification Of Disease ◽  
Challenges And Opportunities ◽  
Icd 10

The adoption of the International Classification of Disease (ICD) 10th Revision (ICD-10) diagnosis code set in the United States has been legislatively delayed several times with the most recent date for implementation set for October 1, 2015. The transition from ICD-9 to ICD-10 will be a major undertaking that will require a substantial amount of planning. In the following article, we outline the steps to develop and implement a strategic plan for the transition to the new code set, identify training needs throughout the practice, and review the challenges and opportunities associated with the transition to ICD-10.

scholarly journals Gambaran Pengetahuan dan Keterampilan Dokter tentang Pengisian Penyebab Kematian Medis (Medical Cause of Death) Berdasarkan Standar ICD-10 di RS Tersier di Bandung

2019 ◽  
Vol 8 (2) ◽  
pp. 325
Author(s):  
Noverika Windasari ◽  
Nur Adibah ◽  
Chevi Sayusman
Keyword(s):  
Cause Of Death ◽  
International Classification ◽  
International Classification Of Disease ◽  
Terminal Events ◽  
Icd 10

Penyebab kematian medis perlu dicantumkan pada setiap rekam medis pasien yang meninggal. Dokter di Rumah Sakit berperan penting dalam menentukan sebab kematian medis (medical cause of death). Tujuan penelitian adalah untuk menilai pengetahuan dan keterampilan dokter tentang cara penulisan penyebab kematian medis (medical cause of death) pada rekam medis di RS Tersier di Bandung yang sesuai dengan standar WHO International Classification of Disease (ICD) 10. Penelitian ini berupa studi deskriptif analitik dengan memberikan kuesioner pada dokter klinis di suatu RS Tersier di Bandung untuk menilai pengetahuan dan keterampilan dokter tentang cara penulisan penyebab kematian medis (medical cause of death) dan kesesuaiannya dengan standar WHO ICD-10. Dari total 928 orang dokter klinis, didapatkan 90 sampel. Sampel mewakili setiap departemen/bagian yang terlibat langsung pembuatan penyebab kematian medis di suatu RS Tersier di Bandung. Hasil penelitian ini menunjukkan 58,1% dokter yang memahami tentang cara penulisan penyebab kematian medis yang benar, sedangkan 41,9% belum memahami secara teori. Keterampilan dokter dalam mengisi penyebab kematian medis yang benar dan lengkap sebesar 20,7%, sedangkan 23,3% mengisi penyebab kematian medis dengan benar namun tidak lengkap. Sebanyak 75,4% mengisi penyebab kematian yang salah, terutama karena menuliskan kondisi akhir sebelum kematian (terminal events). Masih separuh dokter (58,1%) mengetahui cara penulisan penyebab kematian medis yang benar sesuai standar WHO ICD-10. Tingkat keterampilan dalam mengisi penyebab kematian medis yang lengkap, masih sangat rendah (20,7%).

scholarly journals Acute and transient psychotic disorders in a rapidly developing country, State of Qatar

Medicina ◽  
2006 ◽  
Vol 43 (7) ◽  
pp. 575 ◽  
Author(s):  
Taher Shaltout ◽  
Abdulbari Bener ◽  
Majid Al Abdullah ◽  
Zahra Al Mujalli ◽  
Hany Shaltout
Keyword(s):  
Psychotic Disorders ◽  
Early Adulthood ◽  
Study Data ◽  
International Classification ◽  
International Classification Of Disease ◽  
Significant Difference ◽  
Icd 10 ◽  
Lower Incidence Rate ◽  
Interesting Area

Background. Little is known about acute and transient psychotic disorders, which is a diagnostic group, introduced with International Classification of Disease, 10th revision. It is an interesting area of research receiving a lot of attention. Objective. The aim of the study was to find the incidence of acute and transient psychotic disorders in the population and determine its sociodemographic features in the State of Qatar. Design. This is a retrospective descriptive study. Setting. The study was conducted in the Department of Psychiatry of the Rumaillah Hospital, Hamad Medical Corporation, Doha, Qatar. Methods. All Qatari, non-Qatari Arabs, and expatriate patients who were hospitalized with psychotic disorders in the inpatient wards or treated in the outpatient clinics of the Department of Psychiatry over a 7-year period were enrolled in the study. Data were collected from the medical records of patients. The study was conducted from August 1, 1996, to January 1, 2004, amongst the patients with acute and transient psychotic disorders. The diagnostic classification of definite psychotic disorders was made in accordance with criteria based on the International Classification of Disease, 10th revision (ICD-10). Results. A total of 174 patients were treated during a 7-year period. Among them, 69% were males and 31% females. No cases were found in children aged less than 15 years. The highest frequency (43.7%) was found in the early adulthood (16–29 years of age). The incidence of acute and transient psychotic disorders was higher in the expatriates (66.7%). More than half (63.8%) of the patients were employed. Most of the cases (35.6%) had acute schizophrenia-like psychotic disorders (F23.2). There was no statistically significant difference in the frequency of acute and transient psychotic disorders between males and females, Qatari and non-Qatari Arabs, and single and married. Conclusion. The study found markedly lower incidence rate of acute and transient psychotic disorders in females than males. The highest frequency was found in the early adulthood (16–29 years). No cases were found in children aged less than 15 years. It is important to find ways to promote healthier lifestyles in this population in order to prevent the onset of psychotic disorders.

scholarly journals Coding reliability and agreement of international classification of disease, 10th revision (ICD-10) codes in emergency department data

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Mingkai Peng ◽  
Cathy Eastwood ◽  
Alicia Boxill ◽  
Rachel Joy Jolley ◽  
Laura Rutherford ◽  
...  
Keyword(s):  
Emergency Department ◽  
Emergency Departments ◽  
International Classification ◽  
Main Diagnosis ◽  
International Classification Of Disease ◽  
Diagnostic Codes ◽  
Clinical Encounters ◽  
Diagnosis Codes ◽  
Icd 10

Introduction: Administrative health data from the emergency department (ED) play important roles in understanding health needs of the public and reasons for health care resource use. International Classification of Disease (ICD) diagnostic codes have been widely used for code reasons of clinical encounters for administrative purposes in EDs. Objective: The purpose of the study is to examine the coding agreement and reliability of ICD diagnosis codes in ED through auditing the routinely collected data. Methods: We randomly sampled 1 percent of records (n=1636) between October and December from 11 emergency departments in Alberta, Canada. Auditors were employed to review the same chart and independently assign main diagnosis codes. We assessed coding agreement and reliability through comparison of codes assigned by auditors and hospital coders using the proportion of agreement and Cohen’s kappa. Error analysis was conducted to review diagnosis codes with disagreement and categorized them into six groups. Results: Overall, the agreement was 86.5% and 82.2% at 3 and 4 digits levels respectively, and reliability was 0.86 and 0.82 respectively. Variation of agreement and reliability were identified across different emergency departments. The major two categories of coding discrepancy were the use of different codes for the same condition (23.6%) and the use of codes at different levels of specificity (20.9%). Conclusions: Diagnosis codes in emergency department show high agreement and reliability. More strict coding guidelines regarding the use of unspecified codes are needed to enhance coding consistency.

scholarly journals Validation of the International Classification of Disease 10th Revision Codes for Kidney Transplant Rejection and Failure

2020 ◽  
Vol 7 ◽  
pp. 205435812097739
Author(s):  
David Massicotte-Azarniouch ◽  
Manish M. Sood ◽  
Dean A. Fergusson ◽  
Greg A. Knoll
Keyword(s):  
Kidney Transplant ◽  
Chart Review ◽  
Transplant Rejection ◽  
Graft Loss ◽  
International Classification ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
International Classification Of Disease ◽  
Icd 10

Background: Clinical research requires that diagnostic codes captured from routinely collected health administrative data accurately identify individuals with a disease. Objective: In this study, we validated the International Classification of Disease 10th Revision (ICD-10) definition for kidney transplant rejection (T86.100) and for kidney transplant failure (T86.101). Design: Retrospective cohort study. Setting: A large, regional transplantation center in Ontario, Canada. Patients: All adult kidney transplant recipients from 2002 to 2018. Measurements: Chart review was undertaken to identify the first occurrence of biopsy-confirmed rejection and graft loss for all participants. For each observation, we determined the first date a single ICD-10 code T86.100 or T86.101 was recorded as a hospital encounter discharge diagnosis. Methods: Using chart review as the gold standard, we determined the sensitivity, specificity, and positive predictive value (PPV) for the ICD-10 codes T86.100 and T86.101. Results: Our study population comprised of 1,258 kidney transplant recipients. The prevalence of rejection and death-censored graft loss were 15.6 and 9.1%, respectively. For the ICD-10 rejection code (T86.100), sensitivity was 72.9% (95% confidence interval [CI], 66.6-79.2), specificity 97.5% (96.5-98.4), and PPV 83.8% (78.3-89.4). For the ICD-10 graft loss code (T86.101), sensitivity was 21.2% (95% CI, 13.2-29.3), specificity 86.3% (84.3-88.3), and PPV 11.7% (7.0-16.4). Limitations: Single-center study which may limit generalizability of our findings. Conclusions: A single ICD-10 code for kidney transplant rejection (T86.100) was present in 84% of true kidney transplant rejections and is an accurate way of identifying kidney transplant recipients with rejection using administrative health data. The ICD-10 code for graft failure (T86.101) performed poorly and should not be used for administrative health research.

scholarly journals Improving the coding and classification of ambulance data through the application of International Classification of Disease 10th revision

2014 ◽  
Vol 38 (1) ◽  
pp. 70 ◽  
Author(s):  
Kate Cantwell ◽  
Amee Morgans ◽  
Karen Smith ◽  
Michael Livingston ◽  
Paul Dietze
Keyword(s):  
Large Datasets ◽  
International Classification ◽  
Ambulance Service ◽  
Assessment Data ◽  
Case Definitions ◽  
Relative Ease ◽  
Fine Grained ◽  
International Classification Of Disease ◽  
Icd 10

Objectives This paper aims to examine whether an adaptation of the International Classification of Disease (ICD) coding system can be applied retrospectively to final paramedic assessment data in an ambulance dataset with a view to developing more fine-grained, clinically relevant case definitions than are available through point-of-call data. Methods Over 1.2 million case records were extracted from the Ambulance Victoria data warehouse. Data fields included dispatch code, cause (CN) and final primary assessment (FPA). Each FPA was converted to an ICD-10-AM code using word matching or best fit. ICD-10-AM codes were then converted into Major Diagnostic Categories (MDC). CN was aligned with the ICD-10-AM codes for external cause of morbidity and mortality. Results The most accurate results were obtained when ICD-10-AM codes were assigned using information from both FPA and CN. Comparison of cases coded as unconscious at point-of-call with the associated paramedic assessment highlighted the extra clinical detail obtained when paramedic assessment data are used. Conclusions Ambulance paramedic assessment data can be aligned with ICD-10-AM and MDC with relative ease, allowing retrospective coding of large datasets. Coding of ambulance data using ICD-10-AM allows for comparison of not only ambulance service users but also with other population groups. What is known about the topic? There is no reliable and standard coding and categorising system for paramedic assessment data contained in ambulance service databases. What does this paper add? This study demonstrates that ambulance paramedic assessment data can be aligned with ICD-10-AM and MDC with relative ease, allowing retrospective coding of large datasets. Representation of ambulance case types using ICD-10-AM-coded information obtained after paramedic assessment is more fine grained and clinically relevant than point-of-call data, which uses caller information before ambulance attendance. What are the implications for practitioners? This paper describes a model of coding using an internationally recognised standard coding and categorising system to support analysis of paramedic assessment. Ambulance data coded using ICD-10-AM allows for reliable reporting and comparison within the prehospital setting and across the healthcare industry.

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