scholarly journals Comparison of Three Information Sources for Smoking Information in Electronic Health Records

2016 ◽  
Vol 15 ◽  
pp. CIN.S40604 ◽  
Author(s):  
Liwei Wang ◽  
Xiaoyang Ruan ◽  
Ping Yang ◽  
Hongfang Liu
Keyword(s):  
Language Processing ◽  
Smoking Status ◽  
International Classification Of Diseases ◽  
Structured Data ◽  
Narrative Text ◽  
Data Sources ◽  
Related Information ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Sensitivity Specificity

Objective The primary aim was to compare independent and joint performance of retrieving smoking status through different sources, including narrative text processed by natural language processing (NLP), patient-provided information (PPI), and diagnosis codes (ie, International Classification of Diseases, Ninth Revision [ICD-9]). We also compared the performance of retrieving smoking strength information (ie, heavy/light smoker) from narrative text and PPL Materials and Methods Our study leveraged an existing lung cancer cohort for smoking status, amount, and strength information, which was manually chart-reviewed. On the NLP side, smoking-related electronic medical record (EMR) data were retrieved first. A pattern-based smoking information extraction module was then implemented to extract smoking-related information. After that, heuristic rules were used to obtain smoking status-related information. Smoking information was also obtained from structured data sources based on diagnosis codes and PPI. Sensitivity, specificity, and accuracy were measured using patients with coverage (ie, the proportion of patients whose smoking status/strength can be effectively determined). Results NLP alone has the best overall performance for smoking status extraction (patient coverage: 0.88; sensitivity: 0.97; specificity: 0.70; accuracy: 0.88); combining PPI with NLP further improved patient coverage to 0.96. ICD-9 does not provide additional improvement to NLP and its combination with PPI. For smoking strength, combining NLP with PPI has slight improvement over NLP alone. Conclusion These findings suggest that narrative text could serve as a more reliable and comprehensive source for obtaining smoking-related information than structured data sources. PPI, the readily available structured data, could be used as a complementary source for more comprehensive patient coverage.

scholarly journals Association Between Diagnosis Code Expansion and Changes in 30‐Day Risk‐Adjusted Outcomes for Cardiovascular Diseases

2021 ◽  
Author(s):  
Lauren Gilstrap ◽  
Rishi K. Wadhera ◽  
Andrea M. Austin ◽  
Stephen Kearing ◽  
Karen E. Joynt Maddox ◽  
...  
Keyword(s):  
Logistic Regression ◽  
International Classification Of Diseases ◽  
Fee For Service ◽  
Readmission Rates ◽  
Difference In Differences ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Changes In Risk ◽  
The Impact

BACKGROUND In January 2011, Centers for Medicare and Medicaid Services expanded the number of inpatient diagnosis codes from 9 to 25, which may influence comorbidity counts and risk‐adjusted outcome rates for studies spanning January 2011. This study examines the association between (1) limiting versus not limiting diagnosis codes after 2011, (2) using inpatient‐only versus inpatient and outpatient data, and (3) using logistic regression versus the Centers for Medicare and Medicaid Services risk‐standardized methodology and changes in risk‐adjusted outcomes. METHODS AND RESULTS Using 100% Medicare inpatient and outpatient files between January 2009 and December 2013, we created 2 cohorts of fee‐for‐service beneficiaries aged ≥65 years. The acute myocardial infarction cohort and the heart failure cohort had 578 728 and 1 595 069 hospitalizations, respectively. We calculate comorbidities using (1) inpatient‐only limited diagnoses, (2) inpatient‐only unlimited diagnoses, (3) inpatient and outpatient limited diagnoses, and (4) inpatient and outpatient unlimited diagnoses. Across both cohorts, International Classification of Diseases, Ninth Revision ( ICD‐9 ) diagnoses and hierarchical condition categories increased after 2011. When outpatient data were included, there were no significant differences in risk‐adjusted readmission rates using logistic regression or the Centers for Medicare and Medicaid Services risk standardization. A difference‐in‐differences analysis of risk‐adjusted readmission trends before versus after 2011 found that no significant differences between limited and unlimited models for either cohort. CONCLUSIONS For studies that span 2011, researchers should consider limiting the number of inpatient diagnosis codes to 9 and/or including outpatient data to minimize the impact of the code expansion on comorbidity counts. However, the 2011 code expansion does not appear to significantly affect risk‐adjusted readmission rate estimates using either logistic or risk‐standardization models or when using or excluding outpatient data.

scholarly journals Use of Diagnosis Codes and/or Wound Culture Results for Surveillance of Surgical Site Infection after Mastectomy and Breast Reconstruction

2010 ◽  
Vol 31 (05) ◽  
pp. 544-547 ◽  
Author(s):  
Margaret A. Olsen ◽  
Victoria J. Fraser
Keyword(s):  
Surgical Site Infection ◽  
Claims Data ◽  
Breast Surgery ◽  
International Classification Of Diseases ◽  
Site Infection ◽  
Wound Culture ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Major Breast

We compared surveillance of surgical site infection (SSI) after major breast surgery by using a combination of International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes and microbiology-based surveillance. The sensitivity of the coding algorithm for identification of SSI was 87.5%, and the sensitivity of wound culture for identification of SSI was 78.1%. Our results suggest that SSI surveillance can be reliably performed using claims data.

scholarly journals The risk of asthma is increased among women with polycystic ovary syndrome: a twin study

2019 ◽  
Vol 5 (3) ◽  
pp. 00018-2018 ◽  
Author(s):  
Louise Zierau ◽  
Howraman Meteran ◽  
Vibeke Backer ◽  
Svend Lindenberg ◽  
Axel Skytthe ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Polycystic Ovary Syndrome ◽  
Polycystic Ovary ◽  
Smoking Status ◽  
International Classification Of Diseases ◽  
Ovary Syndrome ◽  
Classification Of Diseases ◽  
National Patient ◽  
The Individual ◽  
Danish Twin

BackgroundRecent registry studies have demonstrated a higher prevalence of asthma among women with polycystic ovary syndrome (PCOS). We aimed to assess the association and heritability of PCOS and asthma in a Danish twin cohort.MethodsData for 32 382 female twins from the Danish Twin Registry were included. Twins with PCOS were identified by searching the Danish National Patient Registry for International Classification of Diseases-10 code E28.2. Asthma was diagnosed by questionnaires.Results103 (0.3%) women had a PCOS diagnosis. The risk of asthma was increased among women with PCOS compared with women without (18% versus 9%, respectively; OR 2.11 (95% CI 1.13–3.96); p=0.02). After adjustment for age, body mass index, alcohol consumption and smoking status, the risk of asthma was still increased, but was no longer statistically significant (OR 1.54 (95% CI 0.75–3.17); p=0.24). Variance components analysis showed that shared environmental factors explained 49% (95% CI 24–68%) and unique environmental factors explained 51% (95% CI 32–76%) of the susceptibility to PCOS. For asthma, 44% (95% CI 28–61%) of the variance was explained by genetic factors, whereas 25% (95% CI 11–38%) was ascribable to shared environmental factors and 31% (95% CI 26–36%) to unique environmental factors.ConclusionThe risk of asthma is twice as high among female twins with PCOS. The individual susceptibility to PCOS is mainly due to environmental factors and not genetics.

The prevalence of localised scleroderma in childhood assessed in the administrative claims data from the United States

2018 ◽  
Vol 4 (1) ◽  
pp. 77-78
Author(s):  
Timothy Beukelman ◽  
Fenglong Xie ◽  
Ivan Foeldvari
Keyword(s):  
United States ◽  
Systemic Sclerosis ◽  
Claims Data ◽  
International Classification Of Diseases ◽  
The United States ◽  
Administrative Claims ◽  
Administrative Claims Data ◽  
Diagnosis Codes ◽  
Classification Of Diseases

Juvenile localised scleroderma is believed an orphan autoimmune disease, which occurs 10 times more often than systemic sclerosis in childhood and is believed to have a prevalence of 1 per 100,000 children. To gain data regarding the prevalence of juvenile localised scleroderma, we assessed the administrative claims data in the United States using the International Classification of Diseases, Ninth Revision diagnosis codes. We found an estimated prevalence in each year ranging from 3.2 to 3.6 per 10,000 children. This estimate is significantly higher as found in previous studies.

scholarly journals Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings

Antibiotics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 536
Author(s):  
George Germanos ◽  
Patrick Light ◽  
Roger Zoorob ◽  
Jason Salemi ◽  
Fareed Khan ◽  
...  
Keyword(s):  
Urinary Tract ◽  
Urinary Tract Infections ◽  
Chart Review ◽  
International Classification Of Diseases ◽  
Primary Care Settings ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Tract Infections ◽  
Outpatient Settings

Objective: To validate the use of electronic algorithms based on International Classification of Diseases (ICD)-10 codes to identify outpatient visits for urinary tract infections (UTI), one of the most common reasons for antibiotic prescriptions. Methods: ICD-10 symptom codes (e.g., dysuria) alone or in addition to UTI diagnosis codes plus prescription of a UTI-relevant antibiotic were used to identify outpatient UTI visits. Chart review (gold standard) was performed by two reviewers to confirm diagnosis of UTI. The positive predictive value (PPV) that the visit was for UTI (based on chart review) was calculated for three different ICD-10 code algorithms using (1) symptoms only, (2) diagnosis only, or (3) both. Results: Of the 1087 visits analyzed, symptom codes only had the lowest PPV for UTI (PPV = 55.4%; 95%CI: 49.3–61.5%). Diagnosis codes alone resulted in a PPV of 85% (PPV = 84.9%; 95%CI: 81.1–88.2%). The highest PPV was obtained by using both symptom and diagnosis codes together to identify visits with UTI (PPV = 96.3%; 95%CI: 94.5–97.9%). Conclusions: ICD-10 diagnosis codes with or without symptom codes reliably identify UTI visits; symptom codes alone are not reliable. ICD-10 based algorithms are a valid method to study UTIs in primary care settings.

Is Splenectomy after Trauma an Endangered Species?

2008 ◽  
Vol 74 (5) ◽  
pp. 410-412
Author(s):  
Brian G. Harbrecht ◽  
Glen A. Franklin ◽  
Frank B. Miller ◽  
J. David Richardson
Keyword(s):  
Nonoperative Management ◽  
Cancer Staging ◽  
International Classification Of Diseases ◽  
Neoplastic Disease ◽  
Splenic Trauma ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Trauma Injury ◽  
Laparoscopic Techniques ◽  
Medical Indications

Nonoperative management of splenic trauma is now the most common treatment modality for splenic injuries and splenectomy has almost disappeared in some trauma centers. Splenectomy for cancer staging is infrequently performed suggesting that the indications for splenectomy continue to evolve. We evaluated a state database to assess a communitywide experience with splenic surgery. International Classification of Diseases, 9th Revision, Clinical Modification diagnosis codes were used to determine the indication for splenic surgery. Indications for splenic surgery were listed as trauma (injury codes), medical (hematological diseases, neoplasms, or procedures in which the spleen might be removed contiguously like distal pancreatectomy), or incidental (noncontiguous procedures). Splenectomies for medical indications (n = 607, 43%) were more common than splenectomies for trauma (n = 518, 37%) or incidental splenectomies (n = 276, 20%). Splenectomy for medical reasons was associated with hematologic disease in 56 per cent, neoplastic disease in 34 per cent, and other diagnoses in 10 per cent of cases. Incidental splenectomies were most commonly associated with operations on the esophagus/stomach (32%) and colon (30%). Mortality rate and length of stay were greatest for incidental (14.4 ± 0.9 days, 10.9% mortality) compared with trauma (11.0 ± 0.5 days, 7.7% mortality) or medical (9.7 ± 0.4 days, 4.8% mortality) splenectomies (all P < 0.05 versus incidental). Our results suggest that in the era of nonoperative management of splenic injuries, medical indications now represent the most common reason for splenectomy. As laparoscopic techniques for elective splenectomy become more common, the changing indication for splenectomy has important ramifications for surgical education and training.

scholarly journals Impact of ICD10 and secular changes on electronic medical record rheumatoid arthritis algorithms

Rheumatology ◽  
2020 ◽  
Vol 59 (12) ◽  
pp. 3759-3766 ◽  
Author(s):  
Sicong Huang ◽  
Jie Huang ◽  
Tianrun Cai ◽  
Kumar P Dahal ◽  
Andrew Cagan ◽  
...  
Keyword(s):  
Language Processing ◽  
Gold Standard ◽  
International Classification Of Diseases ◽  
Data Mart ◽  
Classification Of Diseases ◽  
Icd Codes ◽  
Rule Based Approach ◽  
Citrullinated Peptide ◽  
Better Than

Abstract Objective The objective of this study was to compare the performance of an RA algorithm developed and trained in 2010 utilizing natural language processing and machine learning, using updated data containing ICD10, new RA treatments, and a new electronic medical records (EMR) system. Methods We extracted data from subjects with ≥1 RA International Classification of Diseases (ICD) codes from the EMR of two large academic centres to create a data mart. Gold standard RA cases were identified from reviewing a random 200 subjects from the data mart, and a random 100 subjects who only have RA ICD10 codes. We compared the performance of the following algorithms using the original 2010 data with updated data: (i) a published 2010 RA algorithm; (ii) updated algorithm, incorporating ICD10 RA codes and new DMARDs; and (iii) published algorithm using ICD codes only, ICD RA code ≥3. Results The gold standard RA cases had mean age 65.5 years, 78.7% female, 74.1% RF or antibodies to cyclic citrullinated peptide (anti-CCP) positive. The positive predictive value (PPV) for ≥3 RA ICD was 54%, compared with 56% in 2010. At a specificity of 95%, the PPV of the 2010 algorithm and the updated version were both 91%, compared with 94% (95% CI: 91, 96%) in 2010. In subjects with ICD10 data only, the PPV for the updated 2010 RA algorithm was 93%. Conclusion The 2010 RA algorithm validated with the updated data with similar performance characteristics as the 2010 data. While the 2010 algorithm continued to perform better than the rule-based approach, the PPV of the latter also remained stable over time.

Assessing the prevalence of juvenile systemic sclerosis in childhood using administrative claims data from the United States

2018 ◽  
Vol 3 (2) ◽  
pp. 189-190 ◽  
Author(s):  
Timothy Beukelman ◽  
Fenglong Xie ◽  
Ivan Foeldvari
Keyword(s):  
United States ◽  
Systemic Sclerosis ◽  
Claims Data ◽  
International Classification Of Diseases ◽  
The United States ◽  
Administrative Claims ◽  
Administrative Claims Data ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Juvenile Systemic Sclerosis

Juvenile systemic sclerosis is a very rare orphan disease. To date, only one publication has estimated the prevalence of juvenile systemic sclerosis using a survey of specialized physicians. We conducted a study of administrative claims data in the United States using the International Classification of Diseases, Ninth Revision diagnosis codes and found a prevalence of approximately 3 per 1,000,000 children. This estimate will inform the planning of prospective studies.

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