Jarman B
Br Med J (Clin Res Ed). 1984 Dec 8;289(6458):1587-92. doi: 10.1136/bmj.289.6458.1587.
Underprivileged areas were identified by weighting several census variables that relate to social conditions, by using weights determined by means of a questionnaire sent to one in 10 of the general practitioners in the United Kingdom. The weighted variables were added (after statistical manipulation) to give a score for each of the 9265 electoral wards in England and Wales. Blank ward maps were sent to general practitioners in five family practitioner committee areas and they were asked to shade the wards according to the degree to which the population increased their workload or the pressure on their services. Maps of these same areas were then prepared by using the calculated scores with the cut off points between the worst, the intermediate, and the best areas as on those used by the general practitioners. The two sets of maps were then compared to determine how well the maps that were based on scores agreed with the general practitioners' maps showing their assessment of the variation of workload in their areas. Overall, 6.3% of the wards differed in shading in any way between the two sets of maps. In the three areas where the general practitioners shaded complete wards and did not report having difficulties with shading only 1.2% of the wards differed. It may be possible to use these "underprivileged area" scores to indicate where problems occur for general practitioners and to extend this work to other primary health care workers.
通过对若干与社会状况相关的人口普查变量进行加权,利用向英国十分之一的全科医生发送调查问卷所确定的权重,来确定贫困地区。对这些加权变量进行(统计处理后)相加,得出英格兰和威尔士9265个选区各自的分数。空白的选区地图被发送给五个家庭医生委员会地区的全科医生,要求他们根据当地居民增加其工作量或对其服务造成压力的程度,给选区上色。然后,利用计算得出的分数绘制这些相同地区的地图,划分最差、中等和最佳地区的临界点与全科医生所用的相同。接着比较这两组地图,以确定基于分数绘制的地图与全科医生展示其对所在地区工作量变化评估的地图的吻合程度。总体而言,两组地图中任何方式下上色不同的选区占6.3%。在全科医生给整个选区上色且未报告上色困难的三个地区,只有1.2%的选区不同。或许可以利用这些“贫困地区”分数来表明全科医生面临问题的地点,并将这项工作扩展到其他初级卫生保健工作者。