Use of administrative data to find substandard care: validation of the complications screening program.
OBJECTIVE
The use of administrative data to identify inpatient complications is technically feasible and inexpensive but unproven as a quality measure. Our objective was to validate whether a screening method that uses data from standard hospital discharge abstracts identifies complications of care and potential quality problems.


METHODS
This was a case-control study with structured implicit physician reviews.


METHODS
Acute-care hospitals in California and Connecticut in 1994.


METHODS
The study included 1,025 Medicare beneficiaries greater than 265 years of age.


METHODS
Using administrative data, we stratified acute-care hospitals by observed-to-expected complication rates and randomly selected hospitals within each state. We randomly selected cases flagged with 1 of 17 surgical complications and 6 medical complications. We randomly selected controls from unflagged cases.


METHODS
Peer-review organization physicians' judgments about the presence of the flagged complication and potential quality-of-care problems.


RESULTS
Physicians confirmed flagged complications in 68.4% of surgical and 27.2% of medical cases. They identified potential quality problems in 29.5% of flagged surgical and 15.7% of medical cases but in only 2.1% of surgical and medical controls. The rate of physician-identified potential quality problems among flagged cases exceeded 25% in 9 surgical screens and 1 medical screen. Reviewers noted several potentially mitigating circumstances that affected their judgments about quality, including factors related to the patients' illness, the complexity of the case, and technical difficulties that clinicians encountered.


CONCLUSIONS
For some types of complications, screening administrative data may offer an efficient approach for identifying potentially problematic cases for physician review. Understanding the basis for physicians' judgments about quality requires more investigation.
Weingart
S N
SN
Beth Israel Deaconess Medical Center, Department of Medicine, Harvard Medical School, Charles A Dana Research Institute, and the Harvard-Thorndike Library, Boston, Massachusetts 02215, USA. saul_weingart@caregroup.harvard.edu
Iezzoni
L I
LI
Davis
R B
RB
Palmer
R H
RH
Cahalane
M
M
Hamel
M B
MB
Mukamal
K
K
Phillips
R S
RS
Davies
D T
DT
Banks
N J
NJ
D000368:Aged; D002140:California; D016022:Case-Control Studies; D003237:Connecticut; D005260:Female; D006761:Hospitals / Q000592:standards*; D006801:Humans; D007049:Iatrogenic Disease; D007902:Length of Stay; D008297:Male; D008485:Medical Audit / Q000379:methods*; D008499:Medical Records / Q000145:classification*; D006278:Medicare; D010351:Patient Discharge; D011183:Postoperative Complications / Q000453:epidemiology; D011366:Professional Review Organizations; D019984:Quality Indicators, Health Care / Q000145:classification*; D015203:Reproducibility of Results; D014481:United States