Breast cancer teams: the impact of constitution, new cancer workload, and methods of operation on their effectiveness

Br J Cancer. 2003 Jul 7;89(1):15-22. doi: 10.1038/sj.bjc.6601073.

Abstract

National guidance and clinical guidelines recommended multidisciplinary teams (MDTs) for cancer services in order to bring specialists in relevant disciplines together, ensure clinical decisions are fully informed, and to coordinate care effectively. However, the effectiveness of cancer teams was not previously evaluated systematically. A random sample of 72 breast cancer teams in England was studied (548 members in six core disciplines), stratified by region and caseload. Information about team constitution, processes, effectiveness, clinical performance, and members' mental well-being was gathered using appropriate instruments. Two input variables, team workload (P=0.009) and the proportion of breast care nurses (P=0.003), positively predicted overall clinical performance in multivariate analysis using a two-stage regression model. There were significant correlations between individual team inputs, team composition variables, and clinical performance. Some disciplines consistently perceived their team's effectiveness differently from the mean. Teams with shared leadership of their clinical decision-making were most effective. The mental well-being of team members appeared significantly better than in previous studies of cancer clinicians, the NHS, and the general population. This study established that team composition, working methods, and workloads are related to measures of effectiveness, including the quality of clinical care.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Attitude of Health Personnel
  • Breast Neoplasms / therapy*
  • Decision Making
  • Female
  • Humans
  • Interprofessional Relations
  • Leadership
  • Male
  • Middle Aged
  • Nurse Clinicians
  • Outcome and Process Assessment, Health Care
  • Patient Care Team*
  • Quality of Health Care
  • Referral and Consultation*
  • Regression Analysis
  • Workload*