Schnelle Christoph, Clark Justin, Mascord Rachel, Jones Mark A
Institute of Evidence-Based Healthcare, Bond University, Robina, Queensland, Australia.
General Dentist, BMA House, Sydney, New South Wales, Australia.
Ther Clin Risk Manag. 2022 Jul 21;18:721-737. doi: 10.2147/TCRM.S372464. eCollection 2022.
Despite billions of doctor visits worldwide each year, little is known on whether doctors themselves affect patients' physical health after accounting for intervention and confounders such as patients' and doctors' data, hospital effects, nor how strong that doctors' effect is. Knowledge of surgeons' and psychotherapists' effects exists, but not for 102 other medical specialties notwithstanding the importance of such knowledge.
: Randomized controlled trials (RCTs), case-control, and cohort studies including medical doctors except surgeons for any intervention, reporting the proportion of variance in patients' outcomes owing to the doctors (random effects), or the fixed effects of grading doctors by outcomes, after multivariate adjustment. Exclusions: studies of <15 doctors or solely reporting doctors' effects for known variables.
Medline, Embase, PsycINFO, inception to June 2020. Manual search for papers referring/referred to by resulting studies.
Using Newcastle-Ottawa scale.
Despite all medical interventions bar surgery being eligible, only thirty cohort papers were found, covering 36,239 doctors, with 10 specialties, 21 interventions, 60 outcomes (17 unique). Studies reported doctors' effects by grading doctors from best to worst, or by diversely calculating the doctor-attributed percentage of patients' outcome variation, ie the intra-class correlation coefficient (ICC). Sixteen studies presented fixed effects, 18 random effects, and 3 another approach. No RCTs found. Thirteen studies reported exceptionally good and/or poor performers with confidence intervals wholly outside the average performance. ICC range 0 to 33%, mean 3.9%. Highly diverse reporting, meta-analysis therefore not applicable.
Doctors, on their own, can affect patients' physical health for many interventions and outcomes. Effects range from negligible to substantial, even after accounting for all known variables. Many published cohorts may reveal valuable information by reanalyzing their data for doctors' effects. Positive and negative doctor outliers appear regularly. Therefore, it can matter which doctor is chosen.
尽管全球每年有数十亿人次看医生,但在考虑干预措施以及患者和医生数据、医院效应等混杂因素后,医生自身是否会影响患者的身体健康,以及这种影响有多强,目前所知甚少。虽然对外科医生和心理治疗师的影响已有了解,但尽管此类知识很重要,对于其他102个医学专科的影响却尚无相关研究。
随机对照试验(RCT)、病例对照研究和队列研究,纳入除外科医生之外的从事任何干预措施的医生,报告经多变量调整后患者结局中因医生因素导致的方差比例(随机效应),或根据结局对医生进行分级的固定效应。排除标准:医生人数少于15人的研究,或仅报告已知变量的医生效应的研究。
检索Medline、Embase、PsycINFO,检索时间从建库至2020年6月。手动检索所得研究引用或被引用的论文。
采用纽卡斯尔-渥太华量表。
尽管除手术外的所有医疗干预措施均符合纳入标准,但仅找到30篇队列研究论文,涵盖36,239名医生,涉及10个专科、21种干预措施、60种结局(其中17种为独特结局)。研究通过将医生从最佳到最差进行分级,或通过不同方式计算患者结局变异中归因于医生的百分比,即组内相关系数(ICC),来报告医生的效应。16项研究呈现固定效应,18项呈现随机效应,3项采用其他方法。未找到RCT研究。13项研究报告了表现异常出色和/或异常糟糕的医生,其置信区间完全超出平均表现范围。ICC范围为0至33%,平均为3.9%。报告方式高度多样,因此不适用荟萃分析。
对于许多干预措施和结局而言,医生自身会影响患者的身体健康。即使在考虑所有已知变量后,其影响范围从微不足道到相当显著。许多已发表的队列研究通过重新分析其数据以了解医生效应,可能会揭示有价值的信息。表现出色和糟糕的医生异常情况经常出现。因此,选择哪位医生可能很重要。