Abstract
Background
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.
Methods
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.
Results
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.
Conclusions
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.
An Introduction to R Statistical Computing for Horticultural Science
