Hargraves 2012.

Study characteristics
Methods	Community health workers assisting patients with diabetes in self‐management Clustered RCT (12 clusters and NR providers), conducted in 1) Six pairs of community health centres were randomly assigned to employ community health workers (CHWs) on healthcare teams. 2) The intervention involved 2 phases. The first phase, called the Collaborative, sponsored highly structured improvement interventions that focused on quality improvement activities. The goal of the second phase was to assess the impact of adding specially trained CHWs to a subset of the CHCs’ health care teams to address diabetes disparities. In United States of America. 2 arms: 1. Control (ongoing Collaborative intervention) (control arm) and 2. Intervention (ongoing Collaborative intervention with Community Health Workers) (intervention arm)
Participants	Control arm N: 921 Intervention arm N: 494, NA, NA Diabetes type: 2 Mean age: 53.34 ± 9.05 % Male: 48.04 Longest follow‐up: 13 months
Interventions	Control arm: (ongoing Collaborative intervention) Intervention arm: (ongoing Collaborative intervention with Community Health Workers) 1) Case management 2) Team change 3) Patient education 4) Promotion of self‐management
Outcomes	Hypertension control
Funding source	Disclosure of funding: Robert Wood Johnson Foundation (RWJF), Finding Answers: Disparities Research for Change
Notes	—
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Not reported. Matched 6 pairs of CHCs based on baseline performance in the Collaborative intervention (Phase 1), volume of patients, racial/ethnic diversity, and geographic location, and randomly assigned each health centre to either control or intervention status.
Allocation concealment (selection bias)	Low risk	Clustered RCT.
Provider's baseline characteristics (selection bias)	High risk	No table. In general, the intervention and control health centres were significantly different in terms of the profile of patient demographic variables, except for patients’ sex, and thus our analyses have adjusted for them. Some community health centres are staffed with dieticians while others are not; likewise, some CHCs have pharmacies with federal pricing, thus providing medication at low or no cost for the uninsured.
Patient's baseline characteristics (selection bias)	Low risk	Table 1 shows patient characteristics of patient age, sex and ethnicity, along with insurance status. There were a higher percent of non‐Hispanic white patients (53% vs 35%) enrolled in the intervention CHCs. The average age of our intervention centres was 54.9 (SD = 13.0), an average of about 2 years older than the control group, P < .001.
Patient's baseline outcomes (selection bias)	High risk	Table 4. The number of patients with HbA1c below 7, LDL below 100 and blood pressure below 130/80 is significantly different between some ethnic groups at baseline or before intervention (see comments b and c in the legend).
Incomplete outcome data (attrition bias)	High risk	In Table 4, they have data for 750 out of 921 in the control arm (18.6% missing) and 445 out of 494 in the intervention arm (9.9% missing). Numbers unbalanced. No flow chart. Reasons for loss not reported.
Blinding of participants and personnel (performance bias) and of outcome assessors (detection bias)	Low risk	All outcomes were objectively measured (HbA1c, SBP, DBP and LDL)
Selective reporting (reporting bias)	Unclear risk	No registered protocol. They only report the number of patients at target and not their mean level for HbA1c, LDL and blood pressure. In the methods, they state: "we examined change in performance for several measures... including ... systolic blood pressure", but they reported the number of patients below a blood pressure of 130/80.
Risk of contamination (other bias)	High risk	Clustered RCT but all health centres participating in this CHW demonstration project participated in the first 12 months of a statewide diabetes health disparities collaborative (the Collaborative), which sponsored highly structured improvement interventions that focused on quality improvement activities using PDSA cycles to improve care effectiveness for a cohort of patients with diabetes cared for by a primary care provider and support team. This intervention included pre‐work on leading change and data collection; development of a patient registry; monthly conference calls; three 1‐day team training sessions; monthly progress and data reports; and practice redesign coaching.
Other bias	Low risk	None identified.