Leveraging principles of behavioural economics to encourage patient engagement with population health screening programmes

Abstract

Cardiovascular disease is a leading cause of morbidity and mortality worldwide. We leveraged behavioural economics principles to encourage screening for cardiovascular disease risk factors. In a pilot, 60 high-risk patients were offered a complimentary home BP monitor and a lipid test through more convenient means (local lab, home phlebotomy, or self-test), along with financial incentives. Of these, 43.3% submitted the required BP readings, compared with 30.0% in a historical control group; 30.0% completed the lipid panel, versus 18.1% historically. While these results suggest that convenience and incentives can increase participation, over half of participants still did not complete the screenings, indicating a need for additional strategies to fully engage at-risk populations.

Introduction

Cardiovascular disease is a leading cause of morbidity and mortality,¹ and modifiable risk factors often go unrecognised.^{2 3} Increasing engagement in screening programmes is important to achieve reductions in risk. Insights from behavioural economics suggest strategies that help to align short-term choices with long-term health goals.⁴ We describe an effort leveraging behavioural economics concepts to improve participation in blood pressure (BP) and cholesterol monitoring for individuals at elevated cardiovascular risk. We tested two related interventions, comparing participation rates between interventions and with historical controls.

Methods

Between September 2023 and March 2024, we piloted two programmes to encourage BP measurement and lipid testing. Participants came from three primary care practices and were identified through the Electronic Health Record (EHR). Eligible participants had systolic BP≥140 mm Hg on their two most recent checks (both within the past 12 months) and had at least one of: (1) Atherosclerotic Cardiovascular Disease (ASCVD) diagnosis or 10-year risk ≥10%,⁵ (2) diabetes diagnosis, (3) most recent Low-Density Lipoprotein (LDL)≥190 mg/dL. Randomisation between Pilots 1 and 2 was 2:1.

Both pilots incorporated behavioural economics principles to maximise the likelihood of engagement (table 1), and all messages were automated to enhance the sustainability of our approach. Participants received messages introducing them to the programme and verifying their home address to send a complementary BP monitor. Participants in both pilots were asked to send in twice daily BP readings for three consecutive days; they received text reminders. For lipid testing, Pilot 1 participants received a printed laboratory order and information on how to complete a test at either (1) a local laboratory of their choice or (2) a home phlebotomy visit. Pilot 2 participants received a home lipid test kit to collect a dried spot blood sample that was shipped to the laboratory. All participants were offered US$200 in incentives for completing the activities. They were considered to have completed the BP screening if they sent in at least three readings. Historical controls came from two prior studies—BP Pal⁶ and Missing Lipids⁷—in which participants were asked to complete BP checks and lipid testing, respectively, in the traditional manner (coming into the clinic). Completion rates were compared with historical controls using χ² tests.

Table 1. Behavioural science principles used in design.

Principle	Definition	Study implementation
Behavioural economics	The study of the psychological factors which influence how people make decisions, and how these decisions deviate from the implied rational approach.	The overarching discipline from which the principles below are drawn.
Status quo bias	The preference for maintaining one’s current situation or choosing inaction over action.	Opt-out language in messages—framing participation in the programme as the default choice.
Present bias	The tendency to give stronger weight to payoffs that are closer to the present time.11	Leveraged the dynamic of immediate rewards by (1) mailing a free BP monitor at enrolment and (2) providing a portion of US$200 incentive as soon as the participant agreed to participate. Effort reduction: BP measurement: mailed home monitor. Lipid testing: Pilot 1: given choice to complete phlebotomy at a local laboratory or have a phlebotomist come into home. Pilot 2: home self-test kit.
Norms of reciprocity	If you treat people nicely they will likely do the same.12	In addition to receiving a home BP monitor with enrolment, participants received a handwritten note welcoming them to the programme.
Social accountability	People try harder when they know their actions are observed by others.13	Let patients know that we will share updates with their PCP. Encouraged patients to tell a friend or family member about their goals and ask them to check-in.
Fresh starts	Individuals are more likely to engage when they perceive a blank slate and new opportunities.14	Framed the programme as a fresh start for patients who have been unable to lower their BP and cholesterol previously. Encouraged patients who were less engaged in sending BP data to view each reminder as a fresh start and provided them with additional days to meet the minimum BP requirement if needed.
Incentives	Something which motivates an individual to perform an action.	Provided a financial incentive, split as unconditional (after agreeing to participate, prior to any action) and conditional (contingent on completing the BP check and lipid panel).

BPblood pressurePCPPrimary care provider

Results

A total of 60 participants were enrolled and randomly assigned to Pilot 1 (n=40) or Pilot 2 (n=20), among which the mean (SD) age was 65.4 (9.5); 35 (58.3%) were men and 25 (41.7%) were women; and 47 (78.3%) self-identified as white and 9 (15.0%) as black. The mean (SD) baseline systolic BP was 151.5 (11.3) mm Hg and diastolic BP was 84.5 (10.0) mm Hg. The mean (SD) time since the last lipid panel was 1.9 (0.9) years.

26 (43.3%) participants completed the BP check, including 17 (42.5%) participants in Pilot 1 and 9 (45.0%) participants in Pilot 2 (figure 1). In the BP Pal study, 30.0% (45/150) of participants completed the in-person BP check (p=0.07).

Figure 1. Completion rates across both pilots and for historical data. ^aPilot 1 and 2 participants were considered to have completed the home BP check if they submitted three or more home BP readings. BP Pal required an in-office BP check. ^bPilot 1 participants were offered phlebotomy at a local laboratory of their choice or a home phlebotomy service; all 12 patients who completed testing opted for a laboratory-based draw. Pilot 2 participants completed a home self-test using a kit and providing a dried-spot blood sample. Missing Lipids required an office-based laboratory visit. BP, blood pressure.

18 (30.0%) participants completed the lipid panel, including 12 (30.0%) participants in Pilot 1 and 6 (30.0%) participants in Pilot 2. In Missing Lipids, 18.1% (73/404) of participants completed the laboratory-based lipid panel (p=0.03).

Discussion

We leveraged strategies to increase motivation and decrease barriers to test methods of increasing uptake of cardiovascular health screening activities. We observed a 45–65% relative increase in the rate of engagement with these activities when compared with studies in which patients were asked to complete similar tasks in person. This improvement, while promising, still left most individuals unscreened despite generous incentives.

A variety of patient-facing behavioural nudges have been tested to promote uptake of screening activities for diseases such as cancer and diabetes,8,10 but there is limited literature on strategies to promote cardiovascular health screening. Our findings demonstrate the challenges of increasing engagement with population health screening programmes, even when applying many of the levers of behavioural science. Despite offering significant financial incentives and increasing convenience by bringing activities into the home, fewer than half of participants completed either task. Our target population may have been harder to engage, given that we selected for a higher risk group. The scalability of our approach was enhanced by the use of automated messaging but limited by expense, which may not be easily replicated elsewhere. Future work should (1) look at which components of our multipronged strategy were most cost-effective, (2) qualitatively explore the differential responses to our approach and (3) assess whether a more adaptive outreach strategy (eg, considering preferences for mode, timing or content of outreach) improves responses.