Evidence map›Paper›PMID 22995224›Full record

ArticleBMC health services research2012

Hospital discharge diagnostic and procedure codes for upper gastro-intestinal cancer: how accurate are they?

Efty Stavrou, Nicole Pesa, Sallie-Anne Pearson

Abstract readValidation Study
In one paragraph

Article in BMC health services research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. The accuracy of administrative data in identifying pulmonary metastases: a population-based study in Northern Italy.European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation (ECP) · 2026
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  9. Assessing the accuracy of the International Classification of Diseases codes to identify abusive head trauma: a feasibility study.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2015
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Efty StavrouAdult Cancer Program, Prince of Wales Clinical School, Lowy Cancer Research Centre, University of New South Wales, Sydney, NSW, Australia. efty.stavrou@unsw.edu.au
Nicole Pesa
Sallie-Anne Pearson

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPopulation-level health administrative datasets such as hospital discharge data are used increasingly to evaluate health services and outcomes of care. However information about the accuracy of Australian discharge data in identifying cancer, associated procedures and comorbidity is limited. The Admitted Patients Data Collection (APDC) is a census of inpatient hospital discharges in the state of New South Wales (NSW). Our aim was to assess the accuracy of the APDC in identifying upper gastro-intestinal (upper GI) cancer cases, procedures for associated curative resection and comorbidities at the time of admission compared to data abstracted from medical records (the 'gold standard').

methodsWe reviewed the medical records of 240 patients with an incident upper GI cancer diagnosis derived from a clinical database in one NSW area health service from July 2006 to June 2007. Extracted case record data was matched to APDC discharge data to determine sensitivity, positive predictive value (PPV) and agreement between the two data sources (κ-coefficient).

resultsThe accuracy of the APDC diagnostic codes in identifying site-specific incident cancer ranged from 80-95% sensitivity. This was comparable to the accuracy of APDC procedure codes in identifying curative resection for upper GI cancer. PPV ranged from 42-80% for cancer diagnosis and 56-93% for curative surgery. Agreement between the data sources was >0.72 for most cancer diagnoses and curative resections. However, APDC discharge data was less accurate in reporting common comorbidities - for each condition, sensitivity ranged from 9-70%, whilst agreement ranged from κ = 0.64 for diabetes down to κ < 0.01 for gastro-oesophageal reflux disorder.

conclusionsIdentifying incident cases of upper GI cancer and curative resection from hospital administrative data is satisfactory but under-ascertained. Linkage of multiple population-health datasets is advisable to maximise case ascertainment and minimise false-positives. Consideration must be given when utilising hospital discharge data alone for generating comorbidity indices, as disease burden at the time of admission is under-reported.

Indexed as

Gastrointestinal NeoplasmsInternational Classification of DiseasesOutcome and Process Assessment, Health CareUpper Gastrointestinal TractAgedComorbidityFemaleHealth Services ResearchHumansIncidenceMaleMedical Record LinkageMiddle AgedNew South WalesPatient DischargePredictive Value of Tests

Identifiers

PMID22995224
PMCPMC3506480

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.