Choudhry 2018.

Study characteristics
Methods	Effect of a remotely delivered tailored multicomponent approach to enhance medication taking for patients with hyperlipidemia, hypertension, and diabetes: the STIC2IT cluster randomized clinical trial Clustered RCT (14 clusters and 250 providers), conducted in 1) This trial was conducted at Atrius Health, a large multi specialty medical group, Newton, Massachusetts. Remotely delivered tailored multicomponent intervention. 2) Intervention conducted by a staff clinical pharmacist. In United States of America. 2 arms: 1) Control (usual care) (control arm) and 2) Intervention (telephone consultation by pharmacist) (intervention arm)
Participants	Control arm N: 242 Intervention arm N: 246, NA, NA Diabetes type: 4 Mean age: 59.80 ± 9.60 % Male: 54.85 Longest follow‐up: 12 months
Interventions	Control arm: (usual care) Intervention arm: (telephone consultation by pharmacist) 1) Case management 2) Facilitated relay of clinical information 3) Promotion of self‐management 4) Patient reminders
Outcomes	Glycated haemoglobin
Funding source	This research was supported by a grant from the National Heart, Lung, and Blood Institute to Brigham and Women’s Hospital (R01 HL 117918)
Notes	—
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Low risk	From supplemental file: within the resultant 4 blocks, practices were then randomised in a 1:1 ratio to intervention or control using a random number generator.
Allocation concealment (selection bias)	Low risk	Cluster‐RCT. Randomisation occurred at the level of the primary care practice sites.
Provider's baseline characteristics (selection bias)	Unclear risk	No comparison done between groups, but they did block randomisation (unlikely that an imbalance happen). Quote: "Because the practice sites differ from each other, simple cluster randomization may have resulted in imbalances in patient or provider factors that could potentially bias outcome assessment. Therefore, we categorized the practice sites based on their size (i.e., small or large, based on the number of patients receiving care at each site) and whether clinical pharmacists at the sites offered disease management counseling directly to patients (i.e., yes or no). Within the resultant 4 blocks, practices were then randomized in a 1:1 ratio to intervention or control using a random number generator."
Patient's baseline characteristics (selection bias)	Low risk	Table 1 note: Standardised mean differences between intervention and control for age and race/ethnicity were greater than 0.1. Text: Intervention patients were slightly older and less likely to be of white race/ethnicity.
Patient's baseline outcomes (selection bias)	Low risk	Table 1. HbA1c data reported at baseline. Table note: Standardised mean differences between intervention and control for age and race/ethnicity were greater than 0.1; otherwise, there were no significant differences between treatment arms.
Incomplete outcome data (attrition bias)	Unclear risk	Number of lost not reported. Outcomes were evaluated using intention‐to‐treat principles and multiple imputation for missing values. We used electronic health record data to evaluate clinical outcomes, and any missing or inaccurate data, even if non differential, would have biased treatment effects to the null.
Blinding of participants and personnel (performance bias) and of outcome assessors (detection bias)	Low risk	HbA1c was objectively assessed.
Selective reporting (reporting bias)	Unclear risk	Prospectively registered protocol. Do not report diastolic blood pressure for patients with hypertension in the paper. All other outcomes match.
Risk of contamination (other bias)	Low risk	Clustered‐RCT. We chose to use cluster‐randomisation at the practice level to minimise contamination by clinical pharmacist and primary care clinician.
Other bias	High risk	From the supplemental file, some major changes to the protocol were done: 1) Changing randomisation process from the level of the physician to the level of the practice site. 2) Increasing the number of patients included in the study has increased from 2000 to 3000, as this is roughly the number of eligible patients at our practice sites. 3) Changing the enrollment number target from 3000 to 4,080 patients to reflect findings from the first few months of enrollment.