title: Improving performance with clinical decision support.
abstract: BACKGROUND
  CADU/CIS (Clinical and Administrative Decision-support Utility and Clinical Information System) is a clinical decision-support workstation that allows large volumes of clinical information systems data to be analyzed in a timely and user-friendly fashion. CARE PROCESS MEASUREMENT: For any given disease, subgroups of patients are identified, and automated, customized "clinical pathways" are generated. For each subgroup, the best practice norms for use of test and therapies are identified. Practice style variations are then compared to outcomes to focus inquiry on decisions that significantly affect outcomes.
  
  
  METHODS
  INTESTINAL OBSTRUCTION: Graduate Health Systems, a multisite integrated provider in the Philadelphia area, has used CADU/CIS to improve quality problems, reduce treatment-intensity variations, and improve clinical participation in care process evaluation and decision making. A task force selected intestinal obstruction without hernia as its first study because of the related high-volume and high-morbidity complications. Use of a ten-step method for clinical performance improvement showed that the intravenous administration of unnecessary fluids to 104 patients with intestinal obstruction induced congestive heart failure (CHF) in 5 patients. Task force members and other practicing physicians are now developing guidelines and other interventions aimed at fluid use. Indeed, the task force used CADU/CIS to identify an additional 250 patients in one year whose conditions were complicated by CHF.
  
  
  CONCLUSIONS
  A clinical decision support tool can be instrumental in detecting problems with important clinical and economic implications, identifying their important underlying causes, tracking the associated tests and therapies, and monitoring interventions.
authors.affiliation: Care Management Science Corporation, Philadelphia, USA. dbrailer@comscience.com
authors.forename: D J
authors.initials: DJ
authors.lastname: Brailer
authors.forename: S
authors.initials: S
authors.lastname: Goldfarb
authors.forename: M
authors.initials: M
authors.lastname: Horgan
authors.forename: F
authors.initials: F
authors.lastname: Katz
authors.forename: R A
authors.initials: RA
authors.lastname: Paulus
authors.forename: K
authors.initials: K
authors.lastname: Zakrewski
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002408:Catheters, Indwelling / Q000009:adverse effects; D003195:Computer Communication Networks; D003363:Cost Control; D019091:Critical Pathways; D003625:Data Collection; D003658:Decision Making, Computer-Assisted; D003936:Diagnosis, Computer-Assisted; D005069:Evaluation Studies as Topic; D005260:Female; D006302:Health Services Research; D006751:Hospital Information Systems; D006785:Hospitals, University / Q000458:organization & administration / Q000592:standards*; D006801:Humans; D007239:Infections / Q000628:therapy; D007255:Information Services; D015143:Philadelphia; D017064:Process Assessment, Health Care; D018570:Risk Assessment; D018511:Systems Integration; D013813:Therapy, Computer-Assisted; D014481:United States