Related Experiment Videos
Accuracy of hospital report cards based on administrative data
Laurent G Glance1, Andrew W Dick, Turner M Osler
1Department of Anesthesiology, University of Rochester School of Medicine, 601 Elmwood Avenue, Box 601, Rochester, NY 14642, USA.
Insights
Administrative data without date stamps can misclassify hospital quality. Using condition present at admission (CPAA) modifiers improves accuracy, but requires further validation for reliable health quality report cards.
Area of Science:
- Health Services Research
- Health Informatics
- Quality Improvement
Background:
- Publicly available health quality report cards often rely on administrative data.
- Administrative data lack date stamps, making it difficult to distinguish pre-existing conditions from post-admission complications.
- This can lead to misclassification of hospital performance, potentially labeling low-quality providers as average or high-performing.
Purpose of the Study:
- To assess the impact of condition present at admission (CPAA) modifiers on hospital quality assessment using administrative data.
- To determine if CPAA modifiers, acting as date stamps, improve the accuracy of hospital quality report cards.
Main Methods:
- Retrospective cohort study of 648,866 inpatient admissions (1998-2000) for procedures like CABG, PTCA, CEA, AAA repair, THR, AMI, and stroke.
- Utilized the California State Inpatient Database with CPAA modifiers.
- Compared risk adjustment models: 'date stamp' (using CPAA) vs. 'no date stamp' (ignoring CPAA) to assess hospital quality.
Main Results:
- Significant discrepancies in low-performance hospital identification between 'date stamp' and 'no date stamp' models for CABG, PTCA, THR, and AMI.
- For instance, 40% of CABG hospitals identified as low-performance by 'date stamp' models were not by 'no date stamp' models.
- CPAA modifier inclusion had a minor impact on quality assessment for AAA repair, stroke, and CEA.
Conclusions:
- Routine administrative data without date stamp information may lead to misidentification of hospital quality outliers.
- The CPAA modifier shows potential for improving the accuracy of hospital quality assessments.
- Further validation of the CPAA modifier is necessary before implementing date-stamped administrative data for health quality report cards.
Context:
Many of the publicly available health quality report cards are based on administrative data. ICD-9-CM codes in administrative data are not date stamped to distinguish between medical conditions present at the time of hospital admission and complications, which occur after hospital admission. Treating complications as preexisting conditions gives poor-performing hospitals "credit" for their complications and may cause some hospitals that are delivering low-quality care to be misclassified as average- or high-performing hospitals.
Objective:
To determine whether hospital quality assessment based on administrative data is impacted by the inclusion of condition present at admission (CPAA) modifiers in administrative data as a date stamp indicator.
Design, Setting, And Patients:
Retrospective cohort study based on 648,866 inpatient admissions between 1998 and 2000 for coronary artery bypass graft (CABG) surgery, coronary angioplasty (PTCA), carotid endarterectomy (CEA), abdominal aortic aneurysm (AAA) repair, total hip replacement (THR), acute MI (AMI), and stroke using the California State Inpatient Database which includes CPAA modifiers. Hierarchical logistic regression was used to create separate condition-specific risk adjustment models. For each study population, one model was constructed using only secondary diagnoses present at admission based on the CPAA modifier: "date stamp" model. The second model was constructed using all secondary diagnoses, ignoring the information present in the CPAA modifier: the "no date stamp model." Hospital quality was assessed separately using the "date stamp" and the "no date stamp" risk-adjustment models.
Results:
Forty percent of the CABG hospitals, 33 percent of the PTCA hospitals, 40 percent of the THR hospitals, and 33 percent of the AMI hospitals identified as low-performance hospitals by the "date stamp" models were not classified as low-performance hospitals by the "no date stamp" models. Fifty percent of the CABG hospitals, 33 percent of the PTCA hospitals, 50 percent of the CEA hospitals, and 36 percent of the AMI hospitals identified as low-performance hospitals by the "no date stamp" models were not identified as low-performance hospitals by the "date stamp" models. The inclusion of the CPAA modifier had a minor impact on hospital quality assessment for AAA repair, stroke, and CEA.
Conclusion:
This study supports the hypothesis that the use of routine administrative data without date stamp information to construct hospital quality report cards may result in the mis-identification of hospital quality outliers. However, the CPAA modifier will need to be further validated before date stamped administrative data can be used as the basis for health quality report cards.
Related Concept Videos
Data Reporting and Recording
Types of Records II: Educational and Administrative Records
Introduction to Documentation and Reporting
Nursing documentation records essential information and details regarding a patient's care and treatment in written or electronic form. It is a critical aspect of nursing practice that involves documenting assessments, interventions, outcomes, and other relevant details about a patient's health status.
Documentation maps the patient's health journey by creating a comprehensive and precise...
Types of Reports II: Incident or Occurrence Report
Purposes:
In the healthcare industry, reports play a crucial role in documenting incidents within an agency. The primary objective of these reports is to ensure patient safety, uphold the...
Purpose of Health Records I
Here's a breakdown of how health records serve these purposes:
Health Information Technology and Healthcare Information System
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include: