真实场景下放射诊断报告审核耗时与人力资源管理关系初探

Preliminary Study on the Relationship between Real-Scene Time Consuming Radiological Diagnostic Re⁃ports Review and Managing Human Resources

目的 依据大数据分析各层级医生审核放射诊断报告耗时、8小时工作时间段内有效工时占比,为放射科临床工作精细化管理提供客观依据。方法 记录真实场景下每份诊断报告审核耗时,采用方差分析进行差异比较。结果 审核DR、CT和MR总体平均每份报告耗时254秒,按检查类型分别统计审核每份报告耗时:DR 77秒、CT 297秒、MR 325秒。不同亚专业组、检查类型各层级医生审核耗时差异均有统计学意义(P<0.001)。审核腹部组报告耗时最长,固定亚专业组的高年资医生审核报告耗时短于在亚专业组间轮转的中青年医生。8小时工作时间段内有效工时占比平均为54%,合理提高8小时内工作效率,能节省人力资源、缩短患者等待诊断报告时间。结论 依据大型教学医院放射科真实工作场景的大数据分类统计结果,可推广用于各级综合医院和专科医院放射科日常临床工作精细化管理和人力资源估算。

Objective Based on the big data to investigate the time spent by radiologists at each levels reviewing di⁃agnostic radiology reports and the proportion of effective working hours within an 8-hour workday in order to pro⁃vide an objective basis for the refined management of clinical work in radiology departments.Methods The time spent reviewing each diagnostic report in real-world scenarios was recorded,and analysis of variance was used to com⁃pare differences.Results The overal average time required to review 1 report for DR,CT,and MR was 254 seconds,while the time required to review 1 report by examination type was 77 seconds for DR,297 seconds for CT,and 325 seconds for MR.The average time spent reviewing a report by different subspecialty groups and examination typies each levels of radiologists varied,which differences are satistical(P<0.001).The longest time spent by the abdominal group,the time spent by senior radiologists in a fixed subspecialty group was shorter than that spent by attending radiologists who rotated among subspecialty groups.The average percentage of effective working hours within the 8-hour working period is 54%.Reasonably improving the working efficiency within 8 hours can save hu⁃man resources and shorten the waiting time of patients for diagnosis reports.Conclusion Based on the results of big data classification and statistics of actual work scenarios in the radiology departments of large medical schools,the results can be applied to daily work refinement management and human resource estimation in radiology depart⁃ments of general hospitals and specialists of all levels.