Toward the Measure of Credibility of Hospital Administrative Datasets in the Context of DRG Classification

2019 ◽  
pp. 289-296 ◽  
Author(s):  
Diana Pimenta ◽  
Julio Souza ◽  
Ismael Caballero ◽  
Alberto Freitas
Keyword(s):  
Hospital Administrative ◽  
Administrative Datasets

scholarly journals Costs of Hospitalisation Due to Stroke: Linked Registry and Administrative Clinical Costing Study

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Joosup Kim
Keyword(s):  
Length Of Stay ◽  
Disease Burden ◽  
Linear Regression Analysis ◽  
Quality Data ◽  
Clinical Registry ◽  
Costing Study ◽  
Multivariable Linear Regression Analysis ◽  
Hospital Administrative ◽  
Mean Cost ◽  
Administrative Datasets

IntroductionRoutine clinical costing of hospital care provided for a representative sample of patients informs a national price for hospital reimbursement according to the diagnosis related group of a patient. These clinical costing data are available for linkage as part of hospital administrative datasets. Objectives and ApproachThe Australian Stroke Clinical Registry (AuSCR) is a national data collection program used to monitor the quality of care provided to patients who have been hospitalised with a clinical diagnosis of stroke or transient ischaemic attack (TIA). For the Stroke123 project, registrants from the Australian Stroke Clinical Registry in 2009-2013 were linked to hospital administrative datasets in four states (Victoria, Queensland, New South Wales and Western Australia). Clinical costing data were obtained for the cohort in Queensland only. Using these clinical costing data, we aimed to determine the costs of hospitalisations according to clinical and demographic characteristics of patients. Reliability of clinical costing data were tested by assessing the association with disease burden and length of stay using multivariable linear regression analysis. ResultsOf the 5522 patient episodes (from 23 hospitals), clinical costing data were available for 3909 (71%, from 22 hospitals). Patients with clinical costing data were more often aged <65 years (30% vs 24%, p<0.001) and more often male (56% vs 49%, p<0.001) than those without these data. Mean cost of an episode was $12,129. Episodes of intracerebral haemorrhage had a mean cost of $18,315, which was greater than the mean costs of ischaemic stroke ($13,925), TIA ($5,247) and undetermined stroke ($8,996). Greater costs were associated with greater disease burden according to the Charlson Comorbidity Index (p<0.001) and length of stay (p<0.001). Conclusion / ImplicationsIntegration of clinical quality data and costs will enable more holistic assessment and monitoring of the effects of quality improvement initiatives and therapeutic advances.

Effect of change in coding rules on recording diabetes in hospital administrative datasets

2016 ◽  
Vol 94 ◽  
pp. 182-190 ◽  
Author(s):  
Hassan Assareh ◽  
Helen M. Achat ◽  
Veth M. Guevarra ◽  
Joanne M. Stubbs
Keyword(s):  
Hospital Administrative ◽  
Coding Rules ◽  
Administrative Datasets

Estimating Incidence Rate of Hospital-Treated Self-Harm in Hong Kong Using Capture–Recapture Approach

Crisis ◽  
2018 ◽  
Vol 39 (3) ◽  
pp. 205-217
Author(s):  
Chi Leung Kwok ◽  
Paul S. F. Yip
Keyword(s):  
Hong Kong ◽  
Incidence Rate ◽  
Surveillance System ◽  
Public Hospitals ◽  
Medical Attention ◽  
Capture Recapture ◽  
Self Harm ◽  
Data Source ◽  
Hospital Administrative ◽  
Administrative Datasets

Abstract. Background: A surveillance system for self-harm has not been established in Hong Kong. The existing data source has an unknown degree of underreporting, and therefore a capture–recapture method has been proposed to correct for the incompleteness. Aims: To assess the underestimation of the incidence of self-harm cases presenting to hospital in Hong Kong using a capture and recapture method. Method: Two different yet overlapping hospital administrative datasets of self-harm were obtained from all public hospitals in Hong Kong. From 2002 to 2011, 59,473 distinct episodes involving 36,411 patients were identified. A capture–recapture model considering heterogeneous capture probabilities was applied to estimate the number of self-harm episodes. Results: The estimated number of self-harm incidence was 79,923, equally shared by females and males. Cases of self-harm by females were more likely to be ascertained than those by males. The estimated annual incidence rate of self-harm in Hong Kong from 2002 to 2011 ranged from 96.4 in 2010 to 132.7 in 2002. Limitations: The proposed method does not include patients who required no medical attention and those where the patient consulted private doctors. Conclusion: The capture–recapture model is a useful method for adjusting the underestimation of self-harm cases from existing databases when surveillance system is not available and to reveal some hidden patterns.

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 Challenges of using asthma admission rates as a measure of primary care quality in children: An international comparison

2021 ◽  
pp. 135581962110127
Author(s):  
Irina Lut ◽  
Kate Lewis ◽  
Linda Wijlaars ◽  
Ruth Gilbert ◽  
Tiffany Fitzpatrick ◽  
...  
Keyword(s):  
Primary Care ◽  
Hospital Admission ◽  
Hospital Admissions ◽  
Underlying Disease ◽  
Primary Diagnosis ◽  
Care Quality ◽  
Attendance Rates ◽  
Admission Rates ◽  
Primary Care Quality ◽  
Hospital Administrative

Objectives To demonstrate the challenges of interpreting cross-country comparisons of paediatric asthma hospital admission rates as an indicator of primary care quality. Methods We used hospital administrative data from >10 million children aged 6–15 years, resident in Austria, England, Finland, Iceland, Ontario (Canada), Sweden or Victoria (Australia) between 2008 and 2015. Asthma hospital admission and emergency department (ED) attendance rates were compared between countries using Poisson regression models, adjusted for age and sex. Results Hospital admission rates for asthma per 1000 child-years varied eight-fold across jurisdictions. Admission rates were 3.5 times higher when admissions with asthma recorded as any diagnosis were considered, compared with admissions with asthma as the primary diagnosis. Iceland had the lowest asthma admission rates; however, when ED attendance rates were considered, Sweden had the lowest rate of asthma hospital contacts. Conclusions The large variations in childhood hospital admission rates for asthma based on the whole child population reflect differing definitions, admission thresholds and underlying disease prevalence rather than primary care quality. Asthma hospital admissions among children diagnosed with asthma is a more meaningful indicator for inter-country comparisons of primary care quality.

scholarly journals Sociodemographic associations of geographic variation in paediatric tonsillectomy and adenoidectomy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Aimy H. L. Tran ◽  
Danny Liew ◽  
Rosemary S. C. Horne ◽  
Joanne Rimmer ◽  
Gillian M. Nixon
Keyword(s):  
Geographic Variation ◽  
Language Proficiency ◽  
Regression Models ◽  
English Language ◽  
Population Analysis ◽  
English Language Proficiency ◽  
The State ◽  
The Public ◽  
Factors Associated ◽  
Administrative Datasets

AbstractGeographic variation of paediatric tonsillectomy, with or without adenoidectomy, (A/T) has been described since the 1930s until today but no studies have investigated the factors associated with this variation. This study described the geographical distribution of paediatric A/T across the state of Victoria, Australia, and investigated area-level factors associated with this variation. We used linked administrative datasets capturing all paediatric A/T performed between 2010 and 2015 in Victoria. Surgery data were collapsed by patient residence to the level of Local Government Area. Regression models were used to investigate the association between likelihood of surgery and area-level factors. We found a 10.2-fold difference in A/T rates across the state, with areas of higher rates more in regional than metropolitan areas. Area-level factors associated with geographic variation of A/T were percentage of children aged 5–9 years (IRR 1.07, 95%CI 1.01–1.14, P = 0.03) and low English language proficiency (IRR 0.95, 95% CI 0.90–0.99, P = 0.03). In a sub-population analysis of surgeries in the public sector, these factors were low maternal educational attainment (IRR 1.09, 95% CI 1.02–1.16, P < 0.001) and surgical waiting time (IRR 0.99635 95% CI 0.99273–0.99997, P = 0.048). Identifying areas of focus for improvement and factors associated with geographic variation will assist in improving equitable provision of paediatric A/T and decrease variability within regions.

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.

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