Development and validation of a coding framework to identify severe acute toxicity from systemic anti-cancer therapy using hospital administrative data

2022 ◽  
Vol 77 ◽  
pp. 102096
Author(s):  
Jemma M. Boyle ◽  
Thomas E. Cowling ◽  
Angela Kuryba ◽  
Nicola S. Fearnhead ◽  
Jan van der Meulen ◽  
...  
Keyword(s):  
Cancer Therapy ◽  
Acute Toxicity ◽  
Administrative Data ◽  
Anti Cancer ◽  
Hospital Administrative ◽  
Development And Validation ◽  
Hospital Administrative Data

scholarly journals Establishing a composite neonatal adverse outcome indicator using English hospital administrative data

2018 ◽  
Vol 104 (5) ◽  
pp. F502-F509 ◽  
Author(s):  
Hannah Ellin Knight ◽  
Sam J Oddie ◽  
Katie L Harron ◽  
Harriet K Aughey ◽  
Jan H van der Meulen ◽  
...  
Keyword(s):  
Data Quality ◽  
Predictive Validity ◽  
Administrative Data ◽  
Adverse Outcome ◽  
First Year ◽  
Risk Of Death ◽  
Outcome Indicator ◽  
Hospital Administrative ◽  
First Year Of Life ◽  
Hospital Administrative Data

ObjectiveWe adapted a composite neonatal adverse outcome indicator (NAOI), originally derived in Australia, and assessed its feasibility and validity as an outcome indicator in English administrative hospital data.DesignWe used Hospital Episode Statistics (HES) data containing information infants born in the English National Health Service (NHS) between 1 April 2014 and 31 March 2015. The Australian NAOI was mapped to diagnoses and procedure codes used within HES and modified to reflect data quality and neonatal health concerns in England. To investigate the concurrent validity of the English NAOI (E-NAOI), rates of NAOI components were compared with population-based studies. To investigate the predictive validity of the E-NAOI, rates of readmission and death in the first year of life were calculated for infants with and without E-NAOI components.ResultsThe analysis included 484 007 (81%) of the 600 963 eligible babies born during the timeframe. 114/148 NHS trusts passed data quality checks and were included in the analysis. The modified E-NAOI included 23 components (16 diagnoses and 7 procedures). Among liveborn infants, 5.4% had at least one E-NAOI component recorded before discharge. Among newborns discharged alive, the E-NAOI was associated with a significantly higher risk of death (0.81% vs 0.05%; p<0.001) and overnight hospital readmission (15.7% vs 7.1%; p<0.001) in the first year of life.ConclusionsA composite NAOI can be derived from English hospital administrative data. This E-NAOI demonstrates good concurrent and predictive validity in the first year of life. It is a cost-effective way to monitor neonatal outcomes.

scholarly journals How Reliable Are Administrative Data for Capturing Stroke Patients and Their Care

2016 ◽  
Vol 6 (3) ◽  
pp. 96-106 ◽  
Author(s):  
Joan Porter ◽  
Luke Mondor ◽  
Moira K. Kapral ◽  
Jiming Fang ◽  
Ruth E. Hall
Keyword(s):  
Ischemic Stroke ◽  
Administrative Data ◽  
Stroke Risk ◽  
Billing Data ◽  
Stroke Risk Factors ◽  
Physician Billing ◽  
Stroke Type ◽  
Hospital Administrative ◽  
Kappa Agreement ◽  
Hospital Administrative Data

Background/Aims: The reliability of diagnostic coding of acute stroke and transient ischemic attack (TIA) in administrative data is uncertain. The purpose of this study is to determine the agreement between administrative data sources and chart audit for the identification of stroke type, stroke risk factors, and the use of hospital-based diagnostic procedures in patients with stroke or TIA. Methods: Medical charts for a population-based sample of patients (n = 14,508) with ischemic stroke, intracerebral hemorrhage (ICH), or TIA discharged from inpatient and emergency departments (ED) in Ontario, Canada, between April 1, 2012 and March 31, 2013, were audited by trained abstractors. Audited data were linked and compared with hospital administrative data and physician billing data. The positive predictive value (PPV) of hospital administrative data and kappa agreement for the reporting of stroke type were calculated. Kappa agreement was also determined for stroke risk factors and for select stroke-related procedures. Results: The PPV for stroke type in inpatient administrative data ranged from 89.5% (95% CI 88.0-91.0) for TIA, 91.9% (95% CI 90.2-93.5) for ICH, and 97.3% (95% CI 96.9-97.7) for ischemic stroke. For ED administrative data, PPV varied from 78.8% (95% CI 76.3-81.2) for ischemic, 86.3% (95% CI 76.8-95.7) for ICH, and 95.3% (95% CI 94.6-96.0) for TIA. The chance-corrected agreement between the audited and administrative data was good for atrial fibrillation (k = 0.60) and very good for diabetes (k = 0.86). Hospital administrative data combined with physician billing data more than doubled the observed agreement for carotid imaging (k = 0.65) and echocardiography (k = 0.66) compared to hospital administrative data alone. Conclusions: Inpatient and ED administrative data were found to be reliable in the reporting of the International Classification of Diagnosis, 10th revision, Canada (ICD-10-CA)-coded ischemic stroke, ICH and TIA, and for the recording of atrial fibrillation and diabetes. The combination of physician billing data with hospital administrative data greatly improved the capture of some diagnostic services provided to inpatients.

Identifying Communication-Impaired Pediatric Patients Using Detailed Hospital Administrative Data

2016 ◽  
Vol 6 (8) ◽  
pp. 456-467
Author(s):  
D. L. Hill ◽  
K. W. Carroll ◽  
D. Dai ◽  
J. A. Faerber ◽  
S. L. Dougherty ◽  
...  
Keyword(s):  
Administrative Data ◽  
Pediatric Patients ◽  
Hospital Administrative ◽  
Hospital Administrative Data

Does parental report of insurance status agree with hospital administrative data for children presenting to the ED?

2006 ◽  
Vol 24 (7) ◽  
pp. 890-892
Author(s):  
Mark I. Neuman ◽  
Michael S. Radeos ◽  
Anthony Yang ◽  
James A. Gordon ◽  
Carlos A. Camargo
Keyword(s):  
Administrative Data ◽  
Insurance Status ◽  
Parental Report ◽  
Hospital Administrative ◽  
Hospital Administrative Data

Identifying Increased Risk of Readmission and In-hospital Mortality Using Hospital Administrative Data

Medical Care ◽  
2017 ◽  
Vol 55 (7) ◽  
pp. 698-705 ◽  
Author(s):  
Brian J. Moore ◽  
Susan White ◽  
Raynard Washington ◽  
Natalia Coenen ◽  
Anne Elixhauser
Keyword(s):  
Hospital Mortality ◽  
Administrative Data ◽  
Increased Risk ◽  
Hospital Administrative ◽  
Hospital Administrative Data
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