在资源有限的环境中，针对证据为基础的实践进行关注健康公平的经济评估缺乏指导，特别是在人员时间利用方面。研究者必须在低接触、对成本数据的非干扰性收集需求与优先亚群体服务数据需求之间取得平衡。本研究在波士顿都会区的四个联邦合格医疗中心（FQHCs）内进行了一项初步研究，探究了一个综合筛查干预措施的实施情况，包括社会健康决策决定因素筛查和结直肠癌筛查。通过采访FQHC工作人员（包括临床医生，人口健康人员和社区健康工作者）以及对数据完整性进行评估，定性评估了人员成本收集的方法，包括被动（自动）和主动（非自动，需要人员时间和精力）数据收集以及三种可替代的关于自报时间利用的措辞。被动数据收集方法执行简单，没有缺失数据，但错过了在计划会议之外进行的实施和干预活动。使用电子表格进行主动成本数据收集时，当应用于已以此方式跟踪的护理过程时，对用户来说相对简单，并产生准确的时间利用数据。然而对于不常见的任务，以及当任务分散在多个会议中进行时，使用电子表格更具挑战性。关于典型而非特定时期的时间利用问题，以及关于典型患者的问题，能够提供最可靠和可操作的数据。尽管如此，即使最好的问题在时间利用估计方面仍然存在显著的变异性。参与者指出，对公平研究感兴趣的患者特征，包括使用的语言、有害的社会健康决定因素以及与贫困或精神健康有关的问题，都对这种变异性有很大贡献。被动收集的时间利用数据是负担最轻的，在研究工作中应尽可能使用，但应通过定性评估确保数据准确地反映出工作量。当工作流程已通过主动数据收集进行跟踪时，这也是强大的数据收集方法。当问题询问"典型"任务和特定类型的患者时，自报时间利用将更加准确。©2023. BioMed Central Ltd.

There is little guidance for conducting health equity-focused economic evaluations of evidence-based practices in resource-constrained settings, particularly with respect to staff time use. Investigators must balance the need for low-touch, non-disruptive cost data collection with the need for data on providing services to priority subpopulations.This investigation took place within a pilot study examining the implementation of a bundled screening intervention combining screening for social determinants of health and colorectal cancer at four federally qualified health centers (FQHCs) in the Boston metropolitan area. Methods for collecting data on personnel costs for implementation and intervention activities, including passive (automatic) and active (non-automatic, requiring staff time and effort) data collection, as well as three alternate wordings for self-reporting time-use, were evaluated qualitatively using data collected through interviews with FQHC staff (including clinicians, population health staff, and community health workers) and assessments of data completeness.Passive data collection methods were simple to execute and resulted in no missing data, but missed implementation and intervention activities that took place outside planned meetings. Active cost data collection using spreadsheets was simple for users when applied to care processes already tracked in this fashion and yielded accurate time use data. However, for tasks where this was not typical, and when tasks were broken up over multiple sessions, spreadsheets were more challenging to use. Questions asking about time use for a typical rather than specific time period, and for typical patients, yielded the most reliable and actionable data. Still, even the best-performing question had substantial variability in time use estimates. Participants noted that patient characteristics of interest for equity-focused research, including language spoken, adverse social determinants of health, and issues related to poverty or mental health, all contributed significantly to this variability.Passively collected time use data are the least burdensome and should be pursued in research efforts when possible, but should be accompanied by qualitative assessments to ensure the data are an accurate reflection of effort. When workflows are already tracked by active data collection, these are also strong data collection methods. Self-reported time use will be most accurate when questions inquire about "typical" tasks and specific types of patients.© 2023. BioMed Central Ltd.