Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee, Berlin, Germany.
Department of Health Sciences, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, the Netherlands.
PLoS One. 2018 Apr 3;13(4):e0194128. doi: 10.1371/journal.pone.0194128. eCollection 2018.
Diagnosing the causes of low back pain is a challenging task, prone to errors. A novel approach to increase diagnostic accuracy in medical decision making is collective intelligence, which refers to the ability of groups to outperform individual decision makers in solving problems. We investigated whether combining the independent ratings of chiropractors, chiropractic radiologists and medical radiologists can improve diagnostic accuracy when interpreting diagnostic images of the lumbosacral spine. Evaluations were obtained from two previously published studies: study 1 consisted of 13 raters independently rating 300 lumbosacral radiographs; study 2 consisted of 14 raters independently rating 100 lumbosacral magnetic resonance images. In both studies, raters evaluated the presence of "abnormalities", which are indicators of a serious health risk and warrant immediate further examination. We combined independent decisions of raters using a majority rule which takes as final diagnosis the decision of the majority of the group. We compared the performance of the majority rule to the performance of single raters. Our results show that with increasing group size (i.e., increasing the number of independent decisions) both sensitivity and specificity increased in both data-sets, with groups consistently outperforming single raters. These results were found for radiographs and MR image reading alike. Our findings suggest that combining independent ratings can improve the accuracy of lumbosacral diagnostic image reading.
诊断腰痛的病因是一项具有挑战性的任务,容易出现错误。一种提高医学决策诊断准确性的新方法是集体智慧,它是指群体在解决问题方面优于个体决策者的能力。我们研究了在解释腰骶部脊柱诊断图像时,将脊椎按摩师、脊椎放射科医生和放射科医生的独立评估结果相结合是否可以提高诊断准确性。评估结果来自两项先前发表的研究:研究 1 由 13 名评估者独立评估了 300 张腰骶部射线照片;研究 2 由 14 名评估者独立评估了 100 张腰骶部磁共振图像。在这两项研究中,评估者评估了“异常”的存在,这是严重健康风险的指标,需要立即进一步检查。我们使用多数规则结合评估者的独立决策,该规则将多数组的决策作为最终诊断。我们将多数规则的性能与单个评估者的性能进行了比较。结果表明,随着群体规模的增加(即增加独立决策的数量),两个数据集的敏感性和特异性都有所提高,群体的表现始终优于单个评估者。X 光片和磁共振成像阅读的结果都是如此。我们的研究结果表明,结合独立评估可以提高腰骶部诊断图像阅读的准确性。