The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With an Acute Myocardial Infarction
Open accessAbstract
Background— A model using administrative claims data that is suitable for profiling hospital performance for acute myocardial infarction would be useful in quality assessment and improvement efforts. We sought to develop a hierarchical regression model using Medicare claims data that produces hospital risk-standardized 30-day mortality rates and to validate the hospital estimates against those derived from a medical record model. Methods and Results— For hospital estimates derived from claims data, we developed a derivation model using 140 120 cases discharged from 4664 hospitals in 1998. For the comparison of models from claims data and medical record data, we used the Cooperative Cardiovascular Project database. To determine the stability of the model over time, we used annual Medicare cohorts discharged in 1995, 1997, and 1999–2001. The final model included 27 variables and had an area under the receiver operating characteristic curve of 0.71. In a comparison of the risk-standardized hospital mortality rates from the claims model with those of the medical record model, the correlation coefficient was 0.90 (SE=0.003). The slope of the weighted regression line was 0.95 (SE=0.007), and the intercept was 0.008 (SE=0.001), both indicating strong agreement of the hospital estimates between the 2 data sources. The median difference between the claims-based hospital risk-standardized mortality rates and the chart-based rates was <0.001 (25th and 75th percentiles, −0.003 and 0.003). The performance of the model was stable over time. Conclusions— This administrative claims-based model for profiling hospitals performs consistently over several years and produces estimates of risk-standardized mortality that are good surrogates for estimates from a medical record model.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Donabedian, A. (1988) · JAMA · doi:10.1001/jama.260.12.1743 · Cited by 5,895
Cited by
Krumholz, H. M., Merrill, A. R., Schone, E. M., Schreiner, G. C., Chen, J., Bradley, E. H., Wang, Y., Wang, Y., Lin, Z., Straube, B. M., et al. (2009) · Circulation: Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.109.883256 · Cited by 580
Self-citationWhich Patients and Where: A Qualitative Study of Patient Transfers from Community Hospitals
Bosk, E. A., Veinot, T., & Iwashyna, T. J. (2011) · Medical Care · doi:10.1097/mlr.0b013e31820fb71b · Cited by 138
Tabak, Y. P., Sun, X., Nunez, C. M., & Johannes, R. S. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-001790 · Cited by 107
Fleischmann-Struzek, C., Thomas-Rüddel, D. O., Schettler, A., Schwarzkopf, D., Stacke, A., Seymour, C. W., Haas, C., Dennler, U., & Reinhart, K. (2018) · PLOS ONE · doi:10.1371/journal.pone.0198847 · Cited by 95
Association between a hospital's rate of cardiac arrest incidence and cardiac arrest survival
Chen, L. M. (2013) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2013.1026 · Cited by 88
Metadata
- Authors
- Krumholz, H. M., Wang, Y., Mattera, J. A., Wang, Y., Han, L. F., Ingber, M. J., Roman, S., & Normand, S.-L. T.
- Venue
- Circulation
- Published
- 2006-04-04
- Volume
- 113
- Issue
- 13
- Pages
- 1683-1692
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- OpenAlex
- W2064951857
- Cited by
- 492
- References
- 1
- FWCI
- 40.83
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With an Acute Myocardial Infarction. https://app.cochat.ai/papers/10.1161/circulationaha.105.611186
- The paper
- Krumholz, H. M., Wang, Y., Mattera, J. A., Wang, Y., Han, L. F., Ingber, M. J., Roman, S., & Normand, S.-L. T. (2006). An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With an Acute Myocardial Infarction. Circulation. https://doi.org/10.1161/circulationaha.105.611186
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.