scholarly journals Linking administrative data sets of inpatient infectious diseases diagnoses in far North Queensland: a cohort profile

BMJ Open ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. e034845
Author(s):  
Damon P Eisen ◽  
Emma S McBryde ◽  
Luke Vasanthakumar ◽  
Matthew Murray ◽  
Miriam Harings ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Relational Database ◽  
Query Language ◽  
Chronic Renal Disease ◽  
Data Extraction ◽  
Clinical Information ◽  
International Classification Of Diseases ◽  
Data Sets ◽  
Classification Of Diseases ◽  
Hospital Administrative

PurposeTo design a linked hospital database using administrative and clinical information to describe associations that predict infectious diseases outcomes, including long-term mortality.ParticipantsA retrospective cohort of Townsville Hospital inpatients discharged with an International Classification of Diseases and Related Health Problems 10th Revision Australian Modification code for an infectious disease between 1 January 2006 and 31 December 2016 was assembled. This used linked anonymised data from: hospital administrative sources, diagnostic pathology, pharmacy dispensing, public health and the National Death Registry. A Created Study ID was used as the central identifier to provide associations between the cohort patients and the subsets of granular data which were processed into a relational database. A web-based interface was constructed to allow data extraction and evaluation to be performed using editable Structured Query Language.Findings to dateThe database has linked information on 41 367 patients with 378 487 admissions and 1 869 239 diagnostic/procedure codes. Scripts used to create the database contents generated over 24 000 000 database rows from the supplied data. Nearly 15% of the cohort was identified as Aboriginal or Torres Strait Islanders. Invasive staphylococcal, pneumococcal and Group A streptococcal infections and influenza were common in this cohort. The most common comorbidities were smoking (43.95%), diabetes (24.73%), chronic renal disease (17.93%), cancer (16.45%) and chronic pulmonary disease (12.42%). Mortality over the 11-year period was 20%.Future plansThis complex relational database reutilising hospital information describes a cohort from a single tropical Australian hospital of inpatients with infectious diseases. In future analyses, we plan to explore analyses of risks, clinical outcomes, healthcare costs and antimicrobial side effects in site and organism specific infections.

scholarly journals Potential of Minimally Invasive Tissue Sampling for Attributing Specific Causes of Childhood Deaths in South Africa: A Pilot, Epidemiological Study

2019 ◽  
Vol 69 (Supplement_4) ◽  
pp. S361-S373 ◽  
Author(s):  
Richard Chawana ◽  
Vicky Baillie ◽  
Alane Izu ◽  
Fatima Solomon ◽  
Quique Bassat ◽  
...  
Keyword(s):  
Minimally Invasive ◽  
Diarrheal Disease ◽  
Respiratory Infections ◽  
Clinical Information ◽  
International Classification Of Diseases ◽  
Community Acquired Pneumonia ◽  
Microbial Culture ◽  
Tissue Sampling ◽  
Classification Of Diseases ◽  
Syncytial Virus

Abstract Background Current estimates for causes of childhood deaths are mainly premised on modeling of vital registration and limited verbal autopsy data and generally only characterize the underlying cause of death (CoD). We investigated the potential of minimally invasive tissue sampling (MITS) for ascertaining the underlying and immediate CoD in children 1 month to 14 years of age. Methods MITS included postmortem tissue biopsies of brain, liver, and lung for histopathology examination; microbial culture of blood, cerebrospinal fluid (CSF), liver, and lung samples; and molecular microbial testing on blood, CSF, lung, and rectal swabs. Each case was individually adjudicated for underlying, antecedent, and immediate CoD by an international multidisciplinary team of medical experts and coded using the International Classification of Diseases, Tenth Revision (ICD-10). Results An underlying CoD was determined for 99% of 127 cases, leading causes being congenital malformations (18.9%), complications of prematurity (14.2%), human immunodeficiency virus/AIDS (12.6%), diarrheal disease (8.7%), acute respiratory infections (7.9%), injuries (7.9%), and malignancies (7.1%). The main immediate CoD was pneumonia, sepsis, and diarrhea in 33.9%, 19.7%, and 10.2% of cases, respectively. Infection-related deaths were either an underlying or immediate CoD in 78.0% of cases. Community-acquired pneumonia deaths (n = 32) were attributed to respiratory syncytial virus (21.9%), Pneumocystis jirovecii (18.8%), cytomegalovirus (15.6%), Klebsiella pneumoniae (15.6%), and Streptococcus pneumoniae (12.5%). Seventy-one percent of 24 sepsis deaths were hospital-acquired, mainly due to Acinetobacter baumannii (47.1%) and K. pneumoniae (35.3%). Sixty-two percent of cases were malnourished. Conclusions MITS, coupled with antemortem clinical information, provides detailed insight into causes of childhood deaths that could be informative for prioritization of strategies aimed at reducing under-5 mortality.

scholarly journals Utility of ICD Codes for Stress Cardiomyopathy in Hospital Administrative Databases: What Do They Signify?

2019 ◽  
pp. 160-163
Author(s):  
Anusha G Bhat ◽  
Kevin White ◽  
Kyle Gobeil ◽  
Tara Lagu ◽  
Peter K Lindenauer ◽  
...  
Keyword(s):  
Chart Review ◽  
Clinical Manifestations ◽  
International Classification Of Diseases ◽  
Stress Cardiomyopathy ◽  
Administrative Databases ◽  
Classification Of Diseases ◽  
Icd Codes ◽  
Hospital Administrative ◽  
New Diagnosis

Prior studies of stress cardiomyopathy (SCM) have used International Classification of Diseases (ICD) codes to identify patients in administrative databases without evaluating the validity of these codes. Between 2010 and 2016, we identified 592 patients discharged with a first known principal or secondary ICD code for SCM in our medical system. On chart review, 580 charts had a diagnosis of SCM (positive predictive value 98%; 95% CI: 96.4-98.8), although 38 (6.4%) did not have active clinical manifestations of SCM during the hospitalization. Moreover, only 66.8% underwent cardiac catheterization and 91.5% underwent echocardiography. These findings suggest that, although all but a few hospitalized patients with an ICD code for SCM had a diagnosis of SCM, some of these were chronic cases, and numerous patients with a new diagnosis of SCM did not undergo a complete diagnostic workup. Researchers should be mindful of these limitations in future studies involving administrative databases.

Correlations Between Physician and Hospital Stroke Thrombectomy Volumes and Outcomes: A Nationwide Analysis

Stroke ◽  
2021 ◽  
Author(s):  
Laura K. Stein ◽  
J Mocco ◽  
Johanna Fifi ◽  
Nathalie Jette ◽  
Stanley Tuhrim ◽  
...  
Keyword(s):  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Inpatient Rehabilitation ◽  
International Classification Of Diseases ◽  
Data Sets ◽  
Medicare Beneficiaries ◽  
Inpatient Mortality ◽  
Discharge Disposition ◽  
Good Outcome ◽  
Classification Of Diseases

Background and Purpose: Despite the Joint Commission’s certification requirement of ≥15 stroke thrombectomy (ST) cases per center and proceduralist annually, the relationship between ST case volumes and outcomes is uncertain. We sought to determine whether a proceduralist or hospital volume threshold exists that is associated with better outcomes among Medicare beneficiaries. Methods: Retrospective cohort study using validated International Classification of Diseases, Tenth Revision , Clinical Modification codes to identify admissions with acute ischemic stroke and treatment with ST. We used de-identified, national 100% inpatient Medicare data sets from January 1, 2016, to December 31, 2017 for US individuals aged ≥65 years. We calculated total procedures by proceduralist and hospital. We performed adjusted logistic regression of total cases as a predictor of inpatient mortality, good outcome (defined by dichotomized discharge disposition of inpatient rehabilitation or better), and 30-day readmission. We adjusted for sex, age, Charlson Comorbidity Index, availability of neurocritical care, teaching hospital status, socioeconomic status, 2-year stroke volume, and urban versus rural hospital location. We dichotomized case numbers incrementally to determine a volume threshold for better outcomes. Results: Thirteen thousand three hundred thirty-five patients were treated with ST by 2754 proceduralists at 641 hospitals. For every 10 more proceduralist cases, patients had 4% lower adjusted odds of inpatient mortality (adjusted odds ratio, 0.96 [95% CI, 0.95–0.98], P <0.0001) and 3% greater adjusted odds of good outcome (adjusted odds ratio, 1.03 [95% CI, 1.02–1.04], P <0.0001). For every 10 more hospital cases, patients had 2% lower odds of inpatient mortality (adjusted odds ratio, 0.98 [95% CI, 0.98–0.99], P =0.0003) and 2% greater odds of good outcome (adjusted odds ratio, 1.02 [95% CI, 1.01–1.02], P <0.0001). With increasing volumes, there were higher odds of better outcomes. Conclusions: Nationally, higher proceduralist and hospital ST case volumes were associated with reduced inpatient mortality and better outcome. These data support volume requirements in guidelines for ST training and certification.

Comparing ICD-10 external cause codes for pedal cyclists with self-reported crash details

2017 ◽  
Vol 24 (2) ◽  
pp. 157-160 ◽  
Author(s):  
Ben Beck ◽  
Christina L Ekegren ◽  
Peter Cameron ◽  
Mark Stevenson ◽  
Rodney Judson ◽  
...  
Keyword(s):  
Administrative Data ◽  
International Classification Of Diseases ◽  
Coding System ◽  
Event Information ◽  
Injury Event ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Hospital Administrative ◽  
Crash Characteristics

Accurate coding of injury event information is critical in developing targeted injury prevention strategies. However, little is known about the validity of the most universally used coding system, the International Classification of Diseases (ICD-10), in characterising crash counterparts in pedal cycling events. This study aimed to determine the agreement between hospital-coded ICD-10-AM (Australian modification) external cause codes with self-reported crash characteristics in a sample of pedal cyclists admitted to hospital following bicycle crashes. Interview responses from 141 injured cyclists were mapped to a single ICD-10-AM external cause code for comparison with ICD-10-AM external cause codes from hospital administrative data. The percentage of agreement was 77.3% with a κ value of 0.68 (95% CI 0.61 to 0.77), indicating substantial agreement. Nevertheless, studies reliant on ICD-10 codes from administrative data should consider the 23% level of disagreement when characterising crash counterparts in cycling crashes.

Novelties in the ongoing 11th revision of the International Classification of Diseases

2014 ◽  
Vol 155 (39) ◽  
pp. 1535-1537
Author(s):  
Balázs Babarczy
Keyword(s):  
Development Process ◽  
Level Structure ◽  
Clinical Information ◽  
World Health Organisation ◽  
International Classification Of Diseases ◽  
International Classification ◽  
World Health ◽  
Classification Of Diseases ◽  
High Level

The development of the 11th revision of the International Classification of Diseases has been underway since 2007. The World Health Organisation, its coordinator, currently schedules the completion to 2017. The novel classification system has a similar high-level structure than the 10th revision of the International Classification of Diseases, while the entities are significantly more detailed and contain more parameters. The development process aims at the harmonisation of the 11th revision definitions with the codes of other information technology systems, potentially allowing the statistical use of far more clinical information than at present. Meanwhile, this complex development process is confronted at several difficulties. The developers are awaiting the comments of all professionals concerning the Beta-version of the system, available on the Internet. Orv. Hetil., 2014, 155(39), 1535–1537.

scholarly journals Development of the Canadian Emergency Department Diagnosis Shortlist

CJEM ◽  
2010 ◽  
Vol 12 (04) ◽  
pp. 311-319 ◽  
Author(s):  
Bernard Unger ◽  
Marc Afilalo ◽  
Jean François Boivin ◽  
Michael Bullard ◽  
Eric Grafstein ◽  
...  
Keyword(s):  
Emergency Department ◽  
International Classification Of Diseases ◽  
University Teaching ◽  
Data Sets ◽  
Modified Delphi ◽  
Classification Of Diseases ◽  
Chief Complaints ◽  
Icd 10 ◽  
The Creation ◽  
Standardized Parameters

ABSTRACTObjective:Managers of emergency departments (EDs), governments and researchers would benefit from reliable data sets that characterize use of EDs. Although Canadian ED lists for chief complaints and triage acuity exist, no such list exists for diagnosis classification. This study was aimed at developing a standardized Canadian Emergency Department Diagnosis Shortlist (CED-DxS), as a subset of the full International Classification of Diseases, 10th revision, with Canadian Enhancement (ICD-10-CA).Methods:Emergency physicians from across Canada participated in the revision of the ICD-10-CA through 2 rounds of the modified Delphi method. We randomly assigned chapters from the ICD-10-CA (approximately 3000 diagnoses) to reviewers, who rated the importance of including each diagnosis in the ED-specific diagnosis list. If 80% or more of the reviewers agreed on the importance of a diagnosis, it was retained for the final revision. The retained diagnoses were further aggregated and adjusted, thus creating the CED-DxS.Results:Of the 83 reviewers, 76% were emergency medicine (EM)–trained physicians with an average of 12 years of experience in EM, and 92% were affiliated with a university teaching hospital. The modified Delphi process and further adjustments resulted in the creation of the CED-DxS, containing 837 items. The chapter with the largest number of retained diagnoses was injury and poisoning (n= 292), followed by gastrointestinal (n= 59), musculoskeletal (n= 55) and infectious disease (n= 42). Chapters with the lowest number retained were neoplasm (n= 18) and pregnancy (n= 12).Conclusion:We report the creation of the uniform CED-DxS, tailored for Canadian EDs. The addition of ED diagnoses to existing standardized parameters for the ED will contribute to homogeneity of data across the country.

Maximising the value of hospital administrative datasets

2010 ◽  
Vol 34 (2) ◽  
pp. 216 ◽  
Author(s):  
Shyamala G. Nadathur
Keyword(s):  
Administrative Data ◽  
Performance Monitoring ◽  
International Classification Of Diseases ◽  
Audit And Feedback ◽  
Management Tools ◽  
Classification Of Diseases ◽  
Diagnostic Related Groups ◽  
Data Collections ◽  
Hospital Administrative ◽  
Administrative Datasets

Mandatory and standardised administrative data collections are prevalent in the largely public-funded acute sector. In these systems the data collections are used for financial, performance monitoring and reporting purposes. This paper comments on the infrastructure and standards that have been established to support data collection activities, audit and feedback. The routine, local and research uses of these datasets are described using examples from Australian and international literature. The advantages of hospital administrative datasets and opportunities for improvement are discussed under the following headings: accessibility, standardisation, coverage, completeness, cost of obtaining clinical data, recorded Diagnostic Related Groups and International Classification of Diseases codes, linkage and connectivity. In an era of diminishing resources better utilisation of these datasets should be encouraged. Increased study and scrutiny will enhance transparency and help identify issues in the collections. As electronic information systems are increasingly embraced, administrative data collections need to be managed as valuable assets and powerful operational and patient management tools.

scholarly journals Occult Blood in Feces Is Associated With an Increased Risk of Ischemic Stroke and Myocardial Infarction: A Nationwide Population Study

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jung Min Moon ◽  
Hyun Jung Lee ◽  
Kyungdo Han ◽  
Da Hye Kim ◽  
Seung Wook Hong ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Ischemic Stroke ◽  
Cardiovascular Diseases ◽  
Clinical Information ◽  
Occult Blood ◽  
International Classification Of Diseases ◽  
Crc Screening ◽  
Increased Risk ◽  
Classification Of Diseases ◽  
Positive Population

Background Although occult hemoglobin in feces is universally valued as a screening tool for colorectal cancer (CRC), only few studies investigated the clinical meaning of fecal immunochemical test (FIT) in other diseases. We evaluated the clinical utility of FIT in patients with cardiovascular diseases (namely, ischemic stroke and myocardial infarction [MI]). Methods and Results Using the National Health Insurance database, participants (aged >50 years) with CRC screening records from 2009 to 2012 were screened and followed up. Subjects with a history of cardiovascular diseases and CRC were excluded. Ischemic stroke, MI, and other comorbidities were defined by International Classification of Diseases, Tenth Revision ( ICD‐10 ), codes. Age, sex, smoking, alcohol consumption, regular exercise, diabetes mellitus, hypertension, dyslipidemia, and body mass index were adjusted in a multivariate analysis. A total of 6 277 446 subjects were eligible for analysis. During the mean 6.79 years of follow‐up, 168 570 participants developed ischemic stroke, 105 983 developed MI, and 11 253 deaths were observed. A multivariate‐adjusted model revealed that the risk of ischemic stroke was higher in the FIT‐positive population (adjusted hazard ratio [HR], 1.09; 95% CI, 1.07–1.11). Similarly, FIT‐positive subjects were at an increased risk of MI (adjusted HR, 1.09; 95% CI, 1.06–1.12). Moreover, increased all‐cause mortality was observed in the FIT‐positive population (adjusted HR, 1.15; 95% CI, 1.07–1.23). The increased risk remained consistent in the stratified analysis on anemia and CRC status. Conclusions Positive FIT findings were associated with ischemic stroke, MI, and mortality. Occult blood in feces may offer more clinical information than its well‐known conventional role in CRC screening.

scholarly journals Improving the performance of big data databases

2019 ◽  
Vol 4 (2) ◽  
pp. 206-220
Author(s):  
Dashne Raouf Arif ◽  
Nzar Abdulqadir Ali
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Query Language ◽  
Database Management System ◽  
Data Sets ◽  
Relational Database Management System ◽  
Nosql Database ◽  
Sql Database ◽  
Performance Results ◽  
Relational Database Management

Real-time monitoring systems utilize two types of database, they are relational databases such as MySQL and non-relational databases such as MongoDB. A relational database management system (RDBMS) stores data in a structured format using rows and columns. It is relational because the values of the tables are connected. A non-relational database is a database that does not adopt the relational structure given by traditional. In recent years, this class of databases has also been referred to as Not only SQL (NoSQL).  This paper discusses many comparisons that have been conducted on the execution time performance of types of databases (SQL and NoSQL). In SQL (Structured Query Language) databases different algorithms are used for inserting and updating data, such as indexing, bulk insert and multiple updating. However, in NoSQL different algorithms are used for inserting and updating operations such as default-indexing, batch insert, multiple updating and pipeline aggregation. As a result, firstly compared with related papers, this paper shows that the performance of both SQL and NoSQL can be improved. Secondly, performance can be dramatically improved for inserting and updating operations in the NoSQL database compared to the SQL database. To demonstrate the performance of the different algorithms for entering and updating data in SQL and NoSQL, this paper focuses on a different number of data sets and different performance results. The SQL part of the paper is conducted on 50,000 records to 3,000,000 records, while the NoSQL part of the paper is conducted on 50,000 to 16,000,000 documents (2GB) for NoSQL. In SQL, three million records are inserted within 606.53 seconds, while in NoSQL this number of documents is inserted within 67.87 seconds. For updating data, in SQL 300,000 records are updated within 271.17 seconds, while for NoSQL this number of documents is updated within just 46.02 seconds.  

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