RAND Corporation, 4570 Fifth Avenue, Suite 600, Pittsburgh, PA, USA.
Severyn Group, Ashburn, VA, USA.
J Gen Intern Med. 2019 Feb;34(2):243-249. doi: 10.1007/s11606-018-4725-y. Epub 2018 Nov 16.
Public reports on healthcare quality typically include complex data. To lower the cognitive burden of interpreting these data, some report designers create summary, or roll-up, measures combining multiple indicators of quality into one score. Little is known about how the availability of roll-ups affects clinician choice.
To determine how presenting quality scores at different levels of aggregation affects patients' clinician choices.
We conducted a simulated clinician-choice experiment, randomizing participants to three versions of a public reporting website and comparing their clinician choices. One version aggregated all clinician-level quality measures into roll-ups, the second provided disaggregated (drill-down) scores only, and the third offered both roll-ups and drill-downs.
Five hundred fifty panelists drawn from a probability-based Internet panel.
We assessed the amount of effort participants exerted by tracking the length of time spent on the website and the number of concrete actions taken on the website (e.g., clicking items). We evaluated decision quality by measuring whether participants selected a clinician who performed more poorly than others and incongruence between participants' stated preferences for dimensions of quality and their chosen clinician's performance on those dimensions.
Participants seeing drill-downs alone (mean = 14.9) or with roll-ups (mean = 19.2) took more actions than those who saw roll-ups alone (mean = 10.5) (ps < 0.05). However, participants seeing only drill-downs made poorer choices than those who saw roll-ups alone or with drill-downs. More participants seeing drill-downs chose a clinician who was outperformed (36.3% versus 23.4% [roll-up] and 25.6% [drill-down + roll-up], ps < 0.05) and made choices incongruent with stated preferences (51.2% versus 45.6% [roll-up] and 47.5% [drill-down + roll-up], ps < 0.05). The distinction between roll-up and drill-down was somewhat stronger for sicker participants.
Our results suggest that roll-ups in healthcare quality reports, alone or as a complement to drill-downs, can help patients make better decisions for themselves.
公共卫生质量报告通常包含复杂的数据。为了降低解读这些数据的认知负担，一些报告设计者创建了汇总或汇总指标，将多个质量指标合并为一个分数。对于汇总指标的可用性如何影响临床医生的选择，知之甚少。
确定以不同聚合级别呈现质量评分如何影响患者的临床医生选择。
我们进行了一项模拟临床医生选择实验，将参与者随机分配到三个公共报告网站版本，并比较他们的临床医生选择。一个版本将所有临床医生级别的质量指标汇总到汇总指标中，第二个仅提供明细（向下钻取）分数，第三个则提供汇总指标和明细（向下钻取）。
从基于概率的互联网面板中抽取的 550 名小组成员。
我们通过跟踪在网站上花费的时间长度和在网站上采取的具体操作（例如点击项目）来评估参与者付出的努力量。我们通过衡量参与者是否选择了表现不如其他医生的医生，以及参与者对质量维度的陈述偏好与他们选择的医生在这些维度上的表现之间的不一致性，来评估决策质量。
仅查看明细（平均值=14.9）或与汇总指标一起查看（平均值=19.2）的参与者比仅查看汇总指标的参与者（平均值=10.5）采取了更多的操作（p<0.05）。然而，仅查看明细的参与者做出的选择比仅查看汇总指标或同时查看明细和汇总指标的参与者更差。更多看到明细的参与者选择了表现不佳的医生（36.3%比 23.4%[汇总指标]和 25.6%[明细+汇总指标]，p<0.05），并且做出了与陈述偏好不一致的选择（51.2%比 45.6%[汇总指标]和 47.5%[明细+汇总指标]，p<0.05）。汇总指标和明细之间的区别对于病情较重的患者更为明显。
我们的结果表明，医疗质量报告中的汇总指标，单独使用或作为明细的补充，可以帮助患者为自己做出更好的决策。
