Guideline-Based Cardiovascular Risk Assessment Delivered by an mHealth App: Development Study

Abstract

Background: Identifying high-risk individuals is crucial for preventing cardiovascular diseases (CVDs). Currently, risk assessment is mostly performed by physicians. Mobile health apps could help decouple the determination of risk from medical resources by allowing unrestricted self-assessment. The respective test results need to be interpretable for laypersons.

Objective: Together with a patient organization, we aimed to design a digital risk calculator that allows people to individually assess and optimize their CVD risk. The risk calculator was integrated into the mobile health app HerzFit, which provides the respective background information.

Methods: To cover a broad spectrum of individuals for both primary and secondary prevention, we integrated the respective scores (Framingham 10-year CVD, Systematic Coronary Risk Evaluation 2, Systematic Coronary Risk Evaluation 2 in Older Persons, and Secondary Manifestations Of Arterial Disease) into a single risk calculator that was recalibrated for the German population. In primary prevention, an individual's heart age is estimated, which gives the user an easy-to-understand metric for assessing cardiac health. For secondary prevention, the risk of recurrence was assessed. In addition, a comparison of expected to mean and optimal risk levels was determined. The risk calculator is available free of charge. Data safety is ensured by processing the data locally on the users' smartphones.

Results: Offering a risk calculator to the general population requires the use of multiple instruments, as each provides only a limited spectrum in terms of age and risk distribution. The integration of 4 internationally recommended scores allows risk calculation in individuals aged 30 to 90 years with and without CVD. Such integration requires recalibration and harmonization to provide consistent and plausible estimates. In the first 14 months after the launch, the HerzFit calculator was downloaded more than 96,000 times, indicating great demand. Public information campaigns proved effective in publicizing the risk calculator and contributed significantly to download numbers.

Conclusions: The HerzFit calculator provides CVD risk assessment for the general population. The public demonstrated great demand for such a risk calculator as it was downloaded up to 10,000 times per month, depending on campaigns creating awareness for the instrument.

Keywords: HerzFit; cardiovascular disease; cardiovascular risk assessment; mHealth app; mobile health app; mobile phone; prevention; public information campaigns; risk calculator.

Figure 1

Correlation of age and 10-year risk of cardiovascular disease for different personas. This figure demonstrates the correlation between age and 10-year risk of cardiovascular disease for unhealthy, average, and healthy personas for Framingham Risk Score (FRS), Systematic Coronary Risk Evaluation 2 (SCORE2), and SCORE2–Older Persons (SCORE2-OP) in their respective age ranges used in the HerzFit risk calculator. Healthy persona: male, nonsmoker, nondiabetic, systolic blood pressure (SBP) 125 mm Hg, no blood pressure (BP) treatment, total cholesterol (TC) 170 mg/dL, and high-density lipoprotein cholesterol (HDL-C) 70 mg/dL. Average persona: male, nonsmoker, nondiabetic, SBP 130 mm Hg, no BP treatment, TC 200 mg/dL, and HDL-C 50 mg/dL. Unhealthy persona: male, smoker, nondiabetic, SBP 155 mm Hg, no BP treatment, TC 250 mg/dL, and HDL-C 40 mg/dL.

Figure 2

Correlation of age and heart age in the HerzFit risk calculator. This figure demonstrates the correlation of real age and heart age for unhealthy, average, and healthy individual personas for Framingham Risk Score (FRS), Systematic Coronary Risk Evaluation 2 (SCORE2), and SCORE2–Older Persons (SCORE2-OP) in their respective age ranges used in the HerzFit risk calculator. Healthy persona: male, nonsmoker, nondiabetic, systolic blood pressure (SBP) 125 mm Hg, no blood pressure (BP) treatment, total cholesterol (TC) 170 mg/dL, and high-density lipoprotein cholesterol (HDL-C) 70 mg/dL. Average persona: male, nonsmoker, nondiabetic, SBP 130 mm Hg, no BP treatment, TC 200 mg/dL, and HDL-C 50 mg/dL. Unhealthy persona: male, smoker, nondiabetic, SBP 155 mm Hg, no BP treatment, TC 250 mg/dL, and HDL-C 40 mg/dL.

Figure 3

Presentation of heart age and risk in primary and secondary prevention. For individuals without cardiovascular disease, the HerzFit calculator estimates an individual’s heart age. The 10-year risk of recurrent events was estimated for people with established cardiovascular disease. In addition, the individual risk is compared with the mean and optimal risk. The screenshots were translated from German.

Figure 4

The effect of different risk profiles on heart age. This figure shows the effects of cardiovascular risk factors on heart age. Although a healthy man aged 45 years has a heart age of 37 years, and an average man of the same age has a heart age of 45 years, an unhealthy man of the same age can already have a heart age of 69 years. Healthy persona: nonsmoker, nondiabetic, systolic blood pressure (SBP) 125 mm Hg, no blood pressure (BP) treatment, total cholesterol (TC) 170 mg/dL, and high-density lipoprotein cholesterol (HDL-C) 70 mg/dL. Average persona: nonsmoker, nondiabetic, SBP 130 mm Hg, no BP treatment, TC 200 mg/dL, and HDL-C 50 mg/dL. Unhealthy persona: smoker, nondiabetic, SBP 155 mm Hg, no BP treatment, TC 250 mg/dL, and HDL-C 40 mg/dL.

Figure 5

HerzFit downloads from April 2022 to June 2023. Since its release in April 2022, the HerzFit app and risk calculator have been downloaded more than 96,000 times. The orange curve represents the total number of downloads. The green and blue curves mark the downloads per day on iOS and Android devices, respectively. In addition to a continuous increase in the total download numbers, repeated peaks in daily downloads were evident. This finding could be correlated with previous marketing campaigns and events.