Usher Institute, University of Edinburgh, Edinburgh, UK.
School of Health and Social Care. Edinburgh Napier University, Edinburgh, UK.
BMC Med Res Methodol. 2021 Feb 10;21(1):31. doi: 10.1186/s12874-021-01219-8.
Scale-up BP was a quasi-experimental implementation study, following a successful randomised controlled trial of the roll-out of telemonitoring in primary care across Lothian, Scotland. Our primary objective was to assess the effect of telemonitoring on blood pressure (BP) control using routinely collected data. Telemonitored systolic and diastolic BP were compared with surgery BP measurements from patients not using telemonitoring (comparator patients). The statistical analysis and interpretation of findings was challenging due to the broad range of biases potentially influencing the results, including differences in the frequency of readings, 'white coat effect', end digit preference, and missing data.
Four different statistical methods were employed in order to minimise the impact of these biases on the comparison between telemonitoring and comparator groups. These methods were "standardisation with stratification", "standardisation with matching", "regression adjustment for propensity score" and "random coefficient modelling". The first three methods standardised the groups so that all participants provided exactly two measurements at baseline and 6-12 months follow-up prior to analysis. The fourth analysis used linear mixed modelling based on all available data.
The standardisation with stratification analysis showed a significantly lower systolic BP in telemonitoring patients at 6-12 months follow-up (-4.06, 95% CI -6.30 to -1.82, p < 0.001) for patients with systolic BP below 135 at baseline. For the standardisation with matching and regression adjustment for propensity score analyses, systolic BP was significantly lower overall (- 5.96, 95% CI -8.36 to - 3.55 , p < 0.001) and (- 3.73, 95% CI- 5.34 to - 2.13, p < 0.001) respectively, even after assuming that - 5 of the difference was due to 'white coat effect'. For the random coefficient modelling, the improvement in systolic BP was estimated to be -3.37 (95% CI -5.41 to -1.33 , p < 0.001) after 1 year.
The four analyses provide additional evidence for the effectiveness of telemonitoring in controlling BP in routine primary care. The random coefficient analysis is particularly recommended due to its ability to utilise all available data. However, adjusting for the complex array of biases was difficult. Researchers should appreciate the potential for bias in implementation studies and seek to acquire a detailed understanding of the study context in order to design appropriate analytical approaches.
Scale-up BP 是一项准实验实施研究，在苏格兰洛锡安成功开展了一项针对初级保健中远程监测的随机对照试验之后进行。我们的主要目的是使用常规收集的数据评估远程监测对血压（BP）控制的影响。与未使用远程监测的手术 BP 测量值（对照组患者）相比，比较了远程监测的收缩压和舒张压。由于可能影响结果的各种偏差，包括读数频率、“白大衣效应”、尾数偏好和缺失数据的差异，因此统计分析和结果解释具有挑战性。
为了尽量减少这些偏差对远程监测组和对照组之间比较的影响，我们采用了四种不同的统计方法。这些方法包括“标准化分层”、“标准化匹配”、“倾向评分回归调整”和“随机系数建模”。前三种方法使两组标准化，以便所有参与者在基线和 6-12 个月随访时均提供两次测量，然后再进行分析。第四种分析使用基于所有可用数据的线性混合模型。
标准化分层分析显示，基线收缩压低于 135 的患者在 6-12 个月随访时，远程监测组的收缩压明显更低（-4.06，95%置信区间-6.30 至-1.82，p<0.001）。对于标准化匹配和倾向评分回归调整分析，收缩压总体上显著降低（-5.96，95%置信区间-8.36 至-3.55，p<0.001）和（-3.73，95%置信区间-5.34 至-2.13，p<0.001），即使假设其中 5 个差值是由于“白大衣效应”。对于随机系数建模，估计收缩压在 1 年后的改善为-3.37（95%置信区间-5.41 至-1.33，p<0.001）。
这四项分析为远程监测在常规初级保健中控制血压的有效性提供了额外的证据。由于其能够利用所有可用数据，因此特别推荐使用随机系数分析。然而，调整复杂的偏差数组是困难的。研究人员应该意识到实施研究中存在潜在的偏差，并努力深入了解研究背景，以便设计适当的分析方法。
