Brief Summary: As part of UCLA Health's commitment to developing a premier integrated health system built on a foundation of physician-led, team-based primary care, the Department of Medicine (DOM) recently implemented a new performance based incentive plan called the Primary Care Clinical Excellence (PCCE) Incentive Plan. This incentive plan was developed to motivate providers to improve health maintenance screening rates. The UCLA Health DOM Quality team is leading the implementation and evaluation of this new incentive plan across our primary care network. In addition, the DOM Quality team has partnered with the UCLA Anderson School of Management to study the most efficacious ways to frame and communicate performance based incentives. Understanding the factors that motivate physicians to deliver the highest quality primary care will provide pivotal insights into the successful implementation of performance based programs nationwide. The investigators believe that physicians who receive communication built on behavioral principles will demonstrate more motivation towards and success at meeting national primary care screening guidelines.

Detailed Description: Currently, UCLA Health has 42 primary care clinics staffed with approximately 205 PCP's serving more than 300,000 patients. In order to improve health maintenance screening rates associated with the performance based program, the investigators will use a communication strategy that leverages behavioral principles to motivate providers to improve health maintenance screening rates. The investigators will implement a three-arm experimental communication campaign that includes monthly messages. The communication strategy will utilize behavioral change theory (particularly social comparison and recognition) to improve physician performance in health maintenance quality metrics. This study will primarily focus on one quality domain of the PCCE incentive program-Clinical Quality. Two further quality domains of the PCCE incentive program will serve as exploratory measures: Patient Experience and Professional Participation. For the primary outcome measure and high-priority secondary outcome measures, the investigators will first evaluate whether the combination of arms 2 and 3 differs from arm 1 in terms of the measures listed in the Outcome Measures section. If this comparison is statistically significant, the investigators will next compare arms 1 vs 2. and then, if also significant, the investigators will compare arms 1 vs 3 and 2 vs 3. For the 1 vs 3 and 2 vs 3 comparisons, we will use a Holm-Bonferroni p-value correction. These comparisons of treatment arms will be performed at the patient level using a mixed effects regression model, including random physician and clinic effects to account for clustering of patients. Control variables include (1) patient baseline order rates (or completion rates depending on the outcome measure) in July-October 2019, (2) patient characteristics (age, gender, comorbidity, insurance plan, zip code), and (3) physician characteristics (gender, race, years practiced, years at UCLA Health). Unless otherwise specified, p-values less than 0.05 will be considered statistically significant.