Validation of a model of gross motor function for children with cerebral palsy.

BACKGROUND AND PURPOSE: Development of gross motor function in children with cerebral palsy (CP) has not been documented. The purposes of this study were to examine a model of gross motor function in children with CP and to apply the model to construct gross motor function curves for each of the 5 levels of the Gross Motor Function Classification System (GMFCS). SUBJECTS: A stratified sample of 586 children with CP, 1 to 12 years of age, who reside in Ontario, Canada, and are known to rehabilitation centers participated. METHODS: Subjects were classified using the GMFCS, and gross motor function was measured with the Gross Motor Function Measure (GMFM). Four models were examined to construct curves that described the nonlinear relationship between age and gross motor function. RESULTS: The model in which both the limit parameter (maximum GMFM score) and the rate parameter (rate at which the maximum GMFM score is approached) vary for each GMFCS level explained 83% of the variation in GMFM scores. The predicted maximum GMFM scores differed among the 5 curves (level I=96.8, level II=89.3, level III=61.3, level IV=36.1, and level V=12.9). The rate at which children at level II approached their maximum GMFM score was slower than the rates for levels I and III. The correlation between GMFCS levels and GMFM scores was (.91. Logistic regression, used to estimate the probability that children with CP are able to achieve gross motor milestones based on their GMFM total scores, suggests that distinctions between GMFCS levels are clinically meaningful. CONCLUSION AND DISCUSSION: Classification of children with CP based on functional abilities and limitations is predictive of gross motor function, whereas age alone is a poor predictor. Evaluation of gross motor function of children with CP by comparison with children of the same age and GMFCS level has implications for decision making and interpretation of intervention outcomes.

Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review.

CONTEXT: Many computer software developers and vendors claim that their systems can directly improve clinical decisions. As for other health care interventions, such claims should be based on careful trials that assess their effects on clinical performance and, preferably, patient outcomes. OBJECTIVE: To systematically review controlled clinical trials assessing the effects of computer-based clinical decision support systems (CDSSs) on physician performance and patient outcomes. DATA SOURCES: We updated earlier reviews covering 1974 to 1992 by searching the MEDLINE, EMBASE, INSPEC, SCISEARCH, and the Cochrane Library bibliographic databases from 1992 to March 1998. Reference lists and conference proceedings were reviewed and evaluators of CDSSs were contacted. STUDY SELECTION: Studies were included if they involved the use of a CDSS in a clinical setting by a health care practitioner and assessed the effects of the system prospectively with a concurrent control. DATA EXTRACTION: The validity of each relevant study (scored from 0-10) was evaluated in duplicate. Data on setting, subjects, computer systems, and outcomes were abstracted and a power analysis was done on studies with negative findings. DATA SYNTHESIS: A total of 68 controlled trials met our criteria, 40 of which were published since 1992. Quality scores ranged from 2 to 10, with more recent trials rating higher (mean, 7.7) than earlier studies (mean, 6.4) (P<.001). Effects on physician performance were assessed in 65 studies and 43 found a benefit (66%). These included 9 of 15 studies on drug dosing systems, 1 of 5 studies on diagnostic aids, 14 of 19 preventive care systems, and 19 of 26 studies evaluating CDSSs for other medical care. Six of 14 studies assessing patient outcomes found a benefit. Of the remaining 8 studies, only 3 had a power of greater than 80% to detect a clinically important effect. CONCLUSIONS: Published studies of CDSSs are increasing rapidly, and their quality is improving. The CDSSs can enhance clinical performance for drug dosing, preventive care, and other aspects of medical care, but not convincingly for diagnosis. The effects of CDSSs on patient outcomes have been insufficiently studied.