Validity of routinely collected data in identifying hip fractures at a major tertiary hospital in Australia

Trinh, Lieu Thi Thuy; Achat, Helen M; Loh, Sze Ming; Pascoe, R.; Assareh, Hassan; Stubbs, Joanne M.; Guevarra, Veth

doi:10.1177/1833358317721305

Cited by 6 publications

(7 citation statements)

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“…Keeping in mind that it was assessed by central recoders with their own potential biases, the overall quality of coding in our study was moderate, with significant variations between comorbidities (online supplementary table). Other studies for various specific indications such as venous thromboembolism,24 25 arrhythmia,26 stroke,27 hypersensitivity reactions,28 bone metastases,29 glaucoma,30 hip fractures,31 hidradenitis suppurativa,32 acute kidney injury,33 overdoses34 and sepsis19 35 have also found average validity, with significant variations between studies for the same condition 19 27 36. Under the French hospital payment system, patients with comorbidities are associated with higher payments to compensate for the higher burden of care, which may have favoured NPV over PPV and sensitivity over specificity.…”

Section: Discussionmentioning

confidence: 99%

Effect of data validation audit on hospital mortality ranking and pay for performance

et al. 2018

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BackgroundQuality improvement and epidemiology studies often rely on database codes to measure performance or impact of adjusted risk factors, but how validity issues can bias those estimates is seldom quantified.ObjectivesTo evaluate whether and how much interhospital administrative coding variations influence a typical performance measure (adjusted mortality) and potential incentives based on it.DesignNational cross-sectional study comparing hospital mortality ranking and simulated pay-for-performance incentives before/after recoding discharge abstracts using medical records.SettingTwenty-four public and private hospitals located in FranceParticipantsAll inpatient stays from the 78 deadliest diagnosis-related groups over 1 year.InterventionsElixhauser and Charlson comorbidities were derived, and mortality ratios were computed for each hospital. Thirty random stays per hospital were then recoded by two central reviewers and used in a Bayesian hierarchical model to estimate hospital-specific and comorbidity-specific predictive values. Simulations then estimated shifts in adjusted mortality and proportion of incentives that would be unfairly distributed by a typical pay-for-performance programme in this situation.Main outcome measuresPositive and negative predictive values of routine coding of comorbidities in hospital databases, variations in hospitals’ mortality league table and proportion of unfair incentives.ResultsA total of 70 402 hospital discharge abstracts were analysed, of which 715 were recoded from full medical records. Hospital comorbidity-level positive predictive values ranged from 64.4% to 96.4% and negative ones from 88.0% to 99.9%. Using Elixhauser comorbidities for adjustment, 70.3% of hospitals changed position in the mortality league table after correction, which added up to a mean 6.5% (SD 3.6) of a total pay-for-performance budget being allocated to the wrong hospitals. Using Charlson, 61.5% of hospitals changed position, with 7.3% (SD 4.0) budget misallocation.ConclusionsVariations in administrative data coding can bias mortality comparisons and budget allocation across hospitals. Such heterogeneity in data validity may be corrected using a centralised coding strategy from a random sample of observations.

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Section: Discussionmentioning

confidence: 99%

Effect of data validation audit on hospital mortality ranking and pay for performance

et al. 2018

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“…Our study is the first in Victoria to investigate hip fracture incidence and mortality using real-world administrative data. Limitations common with other administrative data studies include possible under-reporting of hip fractures [ 19 ], differential recording of diagnoses and admission sources, incomplete medical records, wrong dates of admission, discharge, and deaths. Data quality were maximized with regular Australian Government data integrity audits [ 45 ] and the quality of ICD-10-AM coding in Victorian hospitals was previously validated [ 46 ].…”

Section: Discussionmentioning

confidence: 99%

“…Patients aged 50 years or above and admitted to a public or private hospital for hip fracture (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification [ICD-10-AM] S72.0-S72.2) [ 7 , 17 - 19 ] and discharged between 1 July 2012 and 30 June 2018 were included. A previous Australian study demonstrated the sensitivity of hip fracture ascertainment from routinely collected administrative data was around 95% and the positive predictive value was above 70% [ 19 ]. Our study only looked at the first hip fractures and removed any patients with any previous history of hip fractures in the past 6 years.…”

Section: Methodsmentioning

confidence: 99%

Hip fracture incidence and post-fracture mortality in Victoria, Australia: a state-wide cohort study

et al. 2023

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Summary Hip fractures are a major public health concern. Number of hip fractures cases increased by 20% from 2012 to 2018. Factors associated with post-fracture mortality included men, those who are frail, living in a non-metropolitan region, or residing in a residential aged care facility. Our results are useful for planning healthcare interventions. Purpose Hip fractures are a major public health concern in Australia. Data on hip fracture incidence and mortality are needed to plan and evaluate healthcare interventions. The aims of the study were to investigate (1) the time-trend in absolute number and incidence of first hip fractures, and (2) factors associated with mortality following first hip fractures in Victoria, Australia. Methods A state-wide cohort study of all patients aged $$\ge$$ ≥ 50 years admitted to a Victorian hospital for first hip fracture between July 2012 and June 2018. Annual age-standardized incidence rates were calculated using population data from Australian Bureau of Statistics. Multivariate negative binomial regression was used to investigate factors associated with post-fracture mortality. Results Overall, 31,578 patients had a first hip fracture, of whom two-thirds were women and 47% were $$\ge$$ ≥ 85 years old. Absolute annual numbers of first hip fractures increased by 20%. There was no significant change in age- and sex-adjusted incidence. In total, 8% died within 30 days and 25% within 1 year. Factors associated with 30-day mortality included age (≥ 85 years old versus 50–64 years old, mortality rate ratio [MRR] 8.05, 95% confidence interval [CI] 5.86–11.33), men (MRR 2.11, 95% CI 1.88–2.37), higher Hospital Frailty Risk Scores (high frailty versus no frailty, MRR 3.46, 95% CI 2.66–4.50), admission from a residential aged care facility (RACF) (MRR 2.28, 95% CI 1.85–2.82), and residing in a non-metropolitan region (MRR 1.22, 95% CI 1.09–1.38). The same factors were associated with 1-year mortality. Conclusion The absolute increase in hip fractures highlights the need for interventions to reduce fracture risk, especially for those at higher risk of post-fracture mortality, including men and those who are frail, living in a non-metropolitan region, or residing in a RACF.

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“…Hip fracture is a major clinical event that almost always requires hospitalisation and is generally accurately coded. [17][18][19] The diagnosis codes to identify hip fracture are subject to local clinical practice; the sites will use their own standard or validated algorithms for identifying hip fracture. The algorithms for hip fracture used by each site, and positive predictive values where available, are provided in table 2.…”

Section: Outcome Assessmentmentioning

confidence: 99%

Global epidemiology of hip fractures: a study protocol using a common analytical platform among multiple countries

et al. 2021

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IntroductionHip fractures are associated with a high burden of morbidity and mortality. Globally, there is wide variation in the incidence of hip fracture in people aged 50 years and older. Longitudinal and cross-geographical comparisons of health data can provide insights on aetiology, risk factors, and healthcare practices. However, systematic reviews of studies that use different methods and study periods do not permit direct comparison across geographical regions. Thus, the objective of this study is to investigate global secular trends in hip fracture incidence, mortality and use of postfracture pharmacological treatment across Asia, Oceania, North and South America, and Western and Northern Europe using a unified methodology applied to health records.Methods and analysisThis retrospective cohort study will use a common protocol and an analytical common data model approach to examine incidence of hip fracture across population-based databases in different geographical regions and healthcare settings. The study period will be from 2005 to 2018 subject to data availability in study sites. Patients aged 50 years and older and hospitalised due to hip fracture during the study period will be included. The primary outcome will be expressed as the annual incidence of hip fracture. Secondary outcomes will be the pharmacological treatment rate and mortality within 12 months following initial hip fracture by year. For the primary outcome, crude and standardised incidence of hip fracture will be reported. Linear regression will be used to test for time trends in the annual incidence. For secondary outcomes, the crude mortality and standardised mortality incidence will be reported.Ethics and disseminationEach participating site will follow the relevant local ethics and regulatory frameworks for study approval. The results of the study will be submitted for peer-reviewed scientific publications and presented at scientific conferences.

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Validity of routinely collected data in identifying hip fractures at a major tertiary hospital in Australia

Abstract: When it is not practical to use the algorithm for regular monitoring of HFs, using PD by admission to estimate total HFs and PD by episode in combination with a procedure code to estimate HFs with surgery can produce robust estimations.

Cited by 6 publications

References 13 publications

Effect of data validation audit on hospital mortality ranking and pay for performance

Effect of data validation audit on hospital mortality ranking and pay for performance

Hip fracture incidence and post-fracture mortality in Victoria, Australia: a state-wide cohort study

Global epidemiology of hip fractures: a study protocol using a common analytical platform among multiple countries

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