scholarly journals Accuracy of ICD-10 Diagnostic Codes to Identify COVID-19 Among Hospitalized Patients

2021 ◽  
Author(s):  
Ankeet S. Bhatt ◽  
Erin E. McElrath ◽  
Brian L. Claggett ◽  
Deepak L. Bhatt ◽  
Dale S. Adler ◽  
...  
Keyword(s):  
Hospitalized Patients ◽  
Diagnostic Codes ◽  
Icd 10

scholarly journals Development of an Electronic Algorithm to Target Outpatient Antimicrobial Stewardship Efforts for Acute Bronchitis

2020 ◽  
Vol 41 (S1) ◽  
pp. s32-s32
Author(s):  
Ebbing Lautenbach ◽  
Keith Hamilton ◽  
Robert Grundmeier ◽  
Melinda Neuhauser ◽  
Lauri Hicks ◽  
...  
Keyword(s):  
Antimicrobial Stewardship ◽  
Predictive Value ◽  
Gold Standard ◽  
Chart Review ◽  
Acute Bronchitis ◽  
Antibiotic Use ◽  
Antibiotic Prescribing ◽  
Diagnostic Codes ◽  
Icd 10 ◽  
The Impact

Background: Antibiotic resistance has increased at alarming rates, driven predominantly by antibiotic overuse. Although most antibiotic use occurs in outpatients, antimicrobial stewardship programs have primarily focused on inpatient settings. A major challenge for outpatient stewardship is the lack of accurate and accessible electronic data to target interventions. We sought to develop and validate an electronic algorithm to identify inappropriate antibiotic use for outpatients with acute bronchitis. Methods: This study was conducted within the University of Pennsylvania Health System (UPHS). We used ICD-10 diagnostic codes to identify encounters for acute bronchitis at any outpatient UPHS practice between March 15, 2017, and March 14, 2018. Exclusion criteria included underlying immunocompromising condition, other comorbidity influencing the need for antibiotics (eg, emphysema), or ICD-10 code at the same visit for a concurrent infection (eg, sinusitis). We randomly selected 300 (150 from academic practices and 150 from nonacademic practices) eligible subjects for detailed chart abstraction that assessed patient demographics and practice and prescriber characteristics. Appropriateness of antibiotic use based on chart review served as the gold standard for assessment of the electronic algorithm. Because antibiotic use is not indicated for this study population, appropriateness was assessed based upon whether an antibiotic was prescribed or not. Results: Of 300 subjects, median age was 61 years (interquartile range, 50–68), 62% were women, 74% were seen in internal medicine (vs family medicine) practices, and 75% were seen by a physician (vs an advanced practice provider). On chart review, 167 (56%) subjects received an antibiotic. Of these subjects, 1 had documented concern for pertussis and 4 had excluding conditions for which there were no ICD-10 codes. One received an antibiotic prescription for a planned dental procedure. Thus, based on chart review, 161 (54%) subjects received antibiotics inappropriately. Using the electronic algorithm based on diagnostic codes, underlying and concurrent conditions, and prescribing data, the number of subjects with inappropriate prescribing was 170 (56%) because 3 subjects had antibiotic prescribing not noted based on chart review. The test characteristics of the electronic algorithm (compared to gold standard chart review) for identification of inappropriate antibiotic prescribing were the following: sensitivity, 100% (161 of 161); specificity, 94% (130 of 139); positive predictive value, 95% (161 of 170); and negative predictive value, 100% (130 of 130). Conclusions: For outpatients with acute bronchitis, an electronic algorithm for identification of inappropriate antibiotic prescribing is highly accurate. This algorithm could be used to efficiently assess prescribing among practices and individual clinicians. The impact of interventions based on this algorithm should be tested in future studies.Funding: NoneDisclosures: None

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 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.

scholarly journals The incidence of Human Herpesvirus in preschool children: problems and solutions

2020 ◽  
Vol 19 (4) ◽  
pp. 50-53
Author(s):  
A. V. Permyakova ◽  
A. Y. Deryusheva
Keyword(s):  
Preschool Children ◽  
Infectious Mononucleosis ◽  
Cytomegalovirus Infection ◽  
Human Herpesvirus ◽  
Hospitalized Patients ◽  
Herpes Viruses ◽  
Problems And Solutions ◽  
Icd 10 ◽  
Perm Krai ◽  
The City

The results of the study of the registered morbidity caused by herpes viruses (HHV) type 4, 5, 6 in preschool children in a large industrial region are presented. Materials and methods. The information on the registered incidence of acute forms of HHV-4, 5, 6 infections in hospitals and clinics in Perm and Perm Krai in 2015—2018 was studied. The following nosologies were taken into account according to ICD-10: В 27.0, В 27.1, В 27.8, В 25., В 25., К 11., К 77.0, В 08.2. 13 452 outpatient cases of infections caused by HHV 4, 5, 6 children 1—6 years old were analyzed, of which in the city of Perm — 6330, in the Perm Krai — 7122, hospitalized — 1171 people. Results. The incidence of hospitalized patients in 92.0% of cases is represented by infectious mononucleosis. The outpatient incidence of HHV 4, 5, 6 infections in 80.6% of cases is represented by non-mononucleous cytomegalovirus diseases, the proportion of which exceeds those in hospitalized patients by 16 times. Conclusions. The analysis of the registered morbidity caused by HHV 4,5,6 in children 1—6 years old in the city of Perm revealed a significant pediatric problem consisting in incorrectness and overdiagnosis of cytomegalovirus infection.

scholarly journals ICD-10 codes are a valid tool for identification of pneumonia in hospitalized patients aged ⩾65 years

2007 ◽  
Vol 136 (2) ◽  
pp. 232-240 ◽  
Author(s):  
S. A. SKULL ◽  
R. M. ANDREWS ◽  
G. B. BYRNES ◽  
D. A. CAMPBELL ◽  
T. M. NOLAN ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Medical Record ◽  
Chest Radiograph ◽  
Predictive Value ◽  
Hospitalized Patients ◽  
Radiology Reports ◽  
Cohort Design ◽  
Icd 10 ◽  
Symptoms And Signs

SUMMARYThis study examines the validity of using ICD-10 codes to identify hospitalized pneumonia cases. Using a case-cohort design, subjects were randomly selected from monthly cohorts of patients aged ⩾65 years discharged from April 2000 to March 2002 from two large tertiary Australian hospitals. Cases had ICD-10-AM codes J10–J18 (pneumonia); the cohort sample was randomly selected from all discharges, frequency matched to cases by month. Codes were validated against three comparators: medical record notation of pneumonia, chest radiograph (CXR) report and both. Notation of pneumonia was determined for 5098/5101 eligible patients, and CXR reports reviewed for 3349/3464 (97%) patients with a CXR. Coding performed best against notation of pneumonia: kappa 0·95, sensitivity 97·8% (95% CI 97·1–98·3), specificity 96·9% (95% CI 96·2–97·5), positive predictive value (PPV) 96·2% (95% CI 95·4–97·0) and negative predictive value (NPV) 98·2% (95% CI 97·6–98·6). When medical record notation of pneumonia is used as the standard, ICD-10 codes are a valid method for retrospective ascertainment of hospitalized pneumonia cases and appear superior to use of complexes of symptoms and signs, or radiology reports.

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 Syndromic Surveillance of Emergency Department Visits for Acute Adverse Effects of Marijuana, Tri-County Health Department, Colorado, 2016-2017

2019 ◽  
Vol 134 (2) ◽  
pp. 132-140 ◽  
Author(s):  
Grace E. Marx ◽  
Yushiuan Chen ◽  
Michele Askenazi ◽  
Bernadette A. Albanese
Keyword(s):  
Emergency Department ◽  
Adverse Effects ◽  
Medical Records ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Marijuana Use ◽  
Emergency Department Visits ◽  
Diagnostic Codes ◽  
Icd 10 ◽  
Ed Visits

Objectives: In Colorado, legalization of recreational marijuana in 2014 increased public access to marijuana and might also have led to an increase in emergency department (ED) visits. We examined the validity of using syndromic surveillance data to detect marijuana-associated ED visits by comparing the performance of surveillance queries with physician-reviewed medical records. Methods: We developed queries of combinations of marijuana-specific International Classification of Diseases, Tenth Revision (ICD-10) diagnostic codes or keywords. We applied these queries to ED visit data submitted through the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE) syndromic surveillance system at 3 hospitals during 2016-2017. One physician reviewed the medical records of ED visits identified by ≥1 query and calculated the positive predictive value (PPV) of each query. We defined cases of acute adverse effects of marijuana (AAEM) as determined by the ED provider’s clinical impression during the visit. Results: Of 44 942 total ED visits, ESSENCE queries detected 453 (1%) as potential AAEM cases; a review of 422 (93%) medical records identified 188 (45%) true AAEM cases. Queries using ICD-10 diagnostic codes or keywords in the triage note identified all true AAEM cases; PPV varied by hospital from 36% to 64%. Of the 188 true AAEM cases, 109 (58%) were among men and 178 (95%) reported intentional use of marijuana. Compared with noncases of AAEM, cases were significantly more likely to be among non-Colorado residents than among Colorado residents and were significantly more likely to report edible marijuana use rather than smoked marijuana use ( P < .001). Conclusions: ICD-10 diagnostic codes and triage note keyword queries in ESSENCE, validated by medical record review, can be used to track ED visits for AAEM.

scholarly journals Accuracy of Administrative Data for the Coding of Acute Stroke and TIAs

2016 ◽  
Vol 43 (6) ◽  
pp. 765-773 ◽  
Author(s):  
Ruth Hall ◽  
Luke Mondor ◽  
Joan Porter ◽  
Jiming Fang ◽  
Moira K. Kapral
Keyword(s):  
Ischemic Stroke ◽  
Acute Stroke ◽  
Administrative Data ◽  
Data Validation ◽  
Reference Standard ◽  
Stroke Registry ◽  
Diagnostic Codes ◽  
Icd 10 ◽  
Stroke Type ◽  
Ischemic Attack

AbstractObjective: Administrative data validation is essential for identifying biases and misclassification in research. The objective of this study was to determine the accuracy of diagnostic codes for acute stroke and transient ischemic attack (TIA) using the Ontario Stroke Registry (OSR) as the reference standard. Methods: We identified stroke and TIA events in inpatient and emergency department (ED) administrative data from eight regional stroke centres in Ontario, Canada, from April of 2006 through March of 2008 using ICD–10–CA codes for subarachnoid haemorrhage (I60, excluding I60.8), intracerebral haemorrhage (I61), ischemic (H34.1 and I63, excluding I63.6), unable to determine stroke (I64), and TIA (H34.0 and G45, excluding G45.4). We linked administrative data to the Ontario Stroke Registry and calculated sensitivity and positive predictive value (PPV). Results:: We identified 5,270 inpatient and 4,411 ED events from the administrative data. Inpatient administrative data had an overall sensitivity of 82.2% (95% confidence interval [CI95%]=81.0, 83.3) and a PPV of 68.8% (CI95%=67.5, 70.0) for the diagnosis of stroke, with notable differences observed by stroke type. Sensitivity for ischemic stroke increased from 66.5 to 79.6% with inclusion of I64. The sensitivity and PPV of ED administrative data for diagnosis of stroke were 56.8% (CI95%=54.8, 58.7) and 59.1% (CI95%=57.1, 61.1), respectively. For all stroke types, accuracy was greater in the inpatient data than in the ED data. Conclusion: The accuracy of stroke identification based on administrative data from stroke centres may be improved by including I64 in ischemic stroke type, and by considering only inpatient data.

Sign in / Sign up

Export Citation Format

Share Document