Heald Brandie, Rybicki Lisa, Clements Diane, Marquard Jessica, Mester Jessica, Noss Ryan, Nardini Monica, Polk Jill, Psensky Brittany, Rigelsky Christina, Schreiber Allison, Shealy Amy, Smith Marissa, Eng Charis
Center for Personalized Genetic Healthcare, Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH, USA.
Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA.
NPJ Genom Med. 2016 May 11;1:16010. doi: 10.1038/npjgenmed.2016.10. eCollection 2016.
With genomics influencing clinical decisions, genetics professionals are exponentially called upon as part of multidisciplinary care. Increasing demand for genetic counselling, a limited workforce, necessitates practices improve efficiency. We hypothesised that distinct differences in clinical workload exist between various disciplines of genetic counselling, complicating practice standardisation and patient volume expectations. We thus sought to objectively define and assess workload among various specialties of genetic counselling. Twelve genetic counsellors (GCs), representing 9.3 clinical FTE, in general or specialty (cancer, cardiovascular or prenatal) services at an academic health system developed a data collection tool for assessing time and complexity. Over a 6-week period, the data were recorded for 583 patient visits (136 general and 447 specialty) and analysed comparing general versus specialty GCs. Variables were compared with hierarchical linear models for ordinal or continuous data and hierarchical logistic models for binary data. General GCs completed more pre- and post-visit activities (=0.011) and spent more time (=0.009) per case. General GCs reported greater case discussion with other providers (<0.001), literature review (=0.026), exploring testing options (=0.041), electronic medical record review (=0.040), insurance preauthorization (=0.05) and fielding patient inquiries (=0.003). Lesser redundancy in referral indication was observed by general GCs. GCs in general practice carry a higher pre- and post-visit workload compared with GCs in specialty practices. General GCs may require lower patient volumes than specialty GCs to allow time for additional pre- and post-visit activities. Non-clinical activities should be transferred to support staff.
随着基因组学影响临床决策,遗传学专业人员作为多学科护理的一部分被大量需求。对遗传咨询的需求不断增加,而劳动力有限,这就要求实践提高效率。我们假设遗传咨询的各个学科之间临床工作量存在明显差异,这使得实践标准化和患者数量预期变得复杂。因此,我们试图客观地定义和评估遗传咨询各专业的工作量。在一个学术健康系统中,12名遗传咨询师(GCs),代表9.3个临床全时当量,从事普通或专科(癌症、心血管或产前)服务,他们开发了一种数据收集工具来评估时间和复杂性。在6周的时间里,记录了583次患者就诊的数据(136次普通就诊和447次专科就诊),并对普通GCs和专科GCs进行了比较分析。对于有序或连续数据,使用分层线性模型比较变量;对于二元数据,使用分层逻辑模型比较变量。普通GCs完成了更多的就诊前和就诊后活动(P=0.011),每个病例花费的时间更多(P=0.009)。普通GCs报告与其他提供者进行了更多的病例讨论(P<0.001)、文献综述(P=0.026)、探索检测选项(P=0.041)、电子病历审查(P=0.04)、保险预授权(P=0.05)和处理患者咨询(P=0.003)。普通GCs观察到转诊指征的冗余较少。与专科实践中的GCs相比,普通实践中的GCs在就诊前和就诊后的工作量更高。普通GCs可能比专科GCs需要更低患者数量,以便有时间进行额外的就诊前和就诊后活动。非临床活动应转移给辅助人员。