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Accuracy of administrative data to assess comorbidity in patients with heart disease. an Australian perspective
Powell H, Lim LL, Heller RF.. Journal of clinical epidemiology, 2001-07-01
Topic: Health services, long-term care and technology
The objective of this study was to determine the accuracy of administrative data (by use of hospital discharge codes) for measuring comorbidity in patients with heart disease. One thousand seven hundred and sixty-five medical records of subjects admitted to hospital for AMI, unstable angina, angina pectoris, chronic IHD or heart failure were reviewed. The number and types of comorbidities were determined from the medical records (regarded as the "gold standard"). These were compared with the 10 discharge codes obtained from the hospital administrative records (referred to as the "administrative data"). The rate of false-negative and false-positive comorbidity diagnoses were determined. Twenty of the 21 comorbidities studied were underreported in the administrative data. For these 20 comorbidities, the median false-negative rate was 49.5% and ranged from 11% for diabetes to 100% for dementia. False-positive rates were low, less than 1.5%, except for chronic arrythmia (4.8%) and hypertension (4.2%). Mean percent agreement was high, ranging from 88% for hypertension to 100% for AIDS/HIV. Administrative data based on hospital discharge codes consistently underestimate the presence of comorbid conditions in our population. This has implications for administrators when estimating mortality, length of stay and disability. Researchers also need to be aware when using administrative data based on hospital discharge codes to assess subject's comorbidities that they may be widely underreported.
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APA 7th
Powell, H., Lim, L. L., & Heller, R. F. (2001). Accuracy of administrative data to assess comorbidity in patients with heart disease. an Australian perspective. Journal of clinical epidemiology. https://doi.org/10.1016/s0895-4356(00)00364-4
Vancouver
Powell H, Lim LL, Heller RF. Accuracy of administrative data to assess comorbidity in patients with heart disease. an Australian perspective. Journal of clinical epidemiology. 2001. doi:10.1016/s0895-4356(00)00364-4. PMID: 11438409.
BibTeX
@article{powell2001-11438409,
author = {Powell, H. and Lim, L. L. and Heller, R. F.},
title = {{Accuracy of administrative data to assess comorbidity in patients with heart disease. an Australian perspective}},
journal = {Journal of clinical epidemiology},
year = {2001},
doi = {10.1016/s0895-4356(00)00364-4},
pmid = {11438409},
url = {https://doi.org/10.1016/s0895-4356(00)00364-4}
}
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Key findings
- These were compared with the 10 discharge codes obtained from the hospital administrative records (referred to as the "administrative data").
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Study details
- Effect size49.5%; 1.5%; 4.8%
- Evidence strengthLow
How this study scored 40/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, studied in people and randomized / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multicenter collaboration, so those were left out: it earned 23 of the 58 points we could judge it on, which is 40 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Journal of clinical epidemiology) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 2001 — older than 20 years, still counted |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomized / blinded | 0 / 2 | No randomization or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multicenter collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 11438409) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 23 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 23 of the 58 points we could judge it on is 40 out of 100. |
| Total | 40 / 100 | — |
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