Measuring resource use in the ICU with computerized therapeutic intervention scoring system-based data.
OBJECTIVE
In this era of health-care reform, there is increasing need to monitor and control health-care resource consumption. This requires the development of measurement tools that are practical, uniform, reproducible, and of sufficient detail to allow comparison among institutions, among select groups of patients, and among individual patients. We explored the feasibility of generating an index of resource use based on the Therapeutic Intervention Scoring System (TISS) from hospital electronic billing data. Such an index is potentially comparable across institutions, allows assessment of care at many levels, is well understood by clinicians, and captures many of the resources relevant to the ICU.


METHODS
We developed an automated mapping of the hospital billing database into the different items of TISS and generated computerized active TISS scores on 1,372 ICU days. The computerized score was then validated by comparison to prospectively gathered active TISS scores by trained data collectors.


METHODS
Eight ICUs within a university teaching institution.


METHODS
We studied 1,229 general medical and surgical ICU patients.


METHODS
None.


RESULTS
Active TISS scores ranged from 0 to 31 points. The two scores were well correlated (R2=0.53) and highly calibrated (as assessed by regression of active TISS on mean computerized active TISS [R2=0.85]). The scores were identical on 756 days (55.6%) and differed by < or = 3 TISS points on an additional 387 (28.2%) days. Interreliability assessment suggested substantial agreement (kappa statistic=0.71). The discriminatory power of the computerized score to identify different levels of ICU resource use was excellent as assessed by area under the receiver operating characteristics curves at four threshold points (0.91, 0.87, 0.89, and 0.88). Performance of the computerized score was similar across medical, coronary, and surgical ICU patient groups.


CONCLUSIONS
An automated algorithm can reproduce valid TISS scores from standard hospital billing data, allowing comparison of patients and groups of patients in order to better understand ICU resource use.
Clermont
G
G
Health Delivery and Systems Evaluation Team, Department of Anesthesiology and Critical Care Medicine, University of Pittsburgh, PA 15213, USA.
Angus
D C
DC
Linde-Zwirble
W T
WT
Lave
J R
JR
Pinsky
M R
MR
D000066:Accounting; D000465:Algorithms; D019540:Area Under Curve; D002138:Calibration; D003422:Critical Care / Q000458:organization & administration / Q000706:statistics & numerical data*; D003628:Database Management Systems; D016002:Discriminant Analysis; D005240:Feasibility Studies; D005260:Female; D018166:Health Care Reform; D006295:Health Resources / Q000706:statistics & numerical data*; D006751:Hospital Information Systems; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D017064:Process Assessment, Health Care; D011446:Prospective Studies; D012372:ROC Curve; D012044:Regression Analysis; D015203:Reproducibility of Results; D012121:Respiration, Artificial; D012680:Sensitivity and Specificity; D012986:Software Validation; D014662:Vasoconstrictor Agents / Q000627:therapeutic use; D014665:Vasodilator Agents / Q000627:therapeutic use
D014662:Vasoconstrictor Agents; D014665:Vasodilator Agents