Error message

  • Strict warning: Declaration of biblio_handler_citation::init() should be compatible with views_handler::init(&$view, &$options) in require_once() (line 2 of /home/www/chspr/sites/all/modules/biblio/views/
  • Warning: htmlspecialchars() expects parameter 1 to be string, array given in check_plain() (line 1545 of /home/www/chspr/includes/

Using population-based data to enhance clinical practice guideline development

Using population-based data to enhance clinical practice guideline development

Medical careMed.Care, Volume 37, Issue 6 Suppl, UNITED STATES, p.JS254 - 63 (1999)
Journal Article

OBJECTIVES: Working with the College of Physicians and Surgeons of Manitoba, and using tonsillectomies as a basis of inquiry, MCHPE examined surgical rates and patterns of practice. This project had three major aims: to review whether current patterns of delivery provide optimal care; to enhance the development of clinical guidelines; and to inform and influence physician practice. RESEARCH DESIGN: Both a population-based method of inquiry (which permits comparisons across population groups) and a provider-based approach (which offers insights into differences in the nature of care offered by different types of hospitals and physicians) were used. MEASURES: Synergies between these two approaches offered useful insight into aspects of quality and efficiency of care. RESULTS: Consistent with other jurisdictions, there was a high degree of variability across regions. However, there were also a number of surprising findings, including high rates of surgery in females, in older children, and among residents of rural areas. Data analysis raised a number of quality-of-care issues related to small caseload volumes, performance of procedures in very young children, and patterns of postoperative care in rural hospitals. The analyses provided impetus for addressing these issues in the guideline and suggested that the target audience for intervention should be rural physicians rather than urban specialists. CONCLUSIONS: This project demonstrated that data analysis can provide a powerful adjunct to the development and implementation of clinical practice guidelines.