Comparing a Digital Health Check With Traditional Nurse-Led Health Examinations Among Long-Term Unemployed Individuals: Comparison Study

Abstract

Background: A digital health check can be used to screen health behavior risks in the population, help health care professionals with standardized risk estimation for their patients, and motivate a patient to change unhealthy behaviors. Long-term unemployed individuals comprise a particular subgroup with an increased risk of lifestyle-related diseases. Objective: This study aims to investigate the clinical utility of a general digital health examination, the STAR Duodecim Health Check and Coaching Program (STAR), which was developed in Finland, in the targeted screening of long-term unemployed individuals. For this purpose, we compared health challenges identified by a digital health check with those identified by a nurse during a face-to-face health check for unemployed individuals. Methods: In this comparison study, 49 unemployed participants attending a health check were recruited from two Finnish primary health care centers. The participants used STAR and attended a nurse’s health check. Data were collected by surveys with multiple-choice and open-ended questions from the participants, nurses, and a study assistant who observed the session. The nurses were asked to name the three most significant health challenges for each participant. These health challenges were categorized into health challenges corresponding to STAR and these were compared with each other. Percentages of agreement between STAR and nurses were calculated. Sensitivity and specificity, as well as Cohen κ with P values and CIs, were computed for agreement. Results: STAR identified a total of 365 health challenges, an average of 7.4 (SD 2.5) health challenges per participant (n=49). The nurses named a total of 160 health challenges (n=47). In 53% (95% CI 38.1-67.9; n=25) of cases, STAR identified all categorized health challenges named by nurses. In 64% (95% CI 48.5-77.3; n=30) of cases, STAR identified at least 2/3 of the health challenges identified by nurses. Cohen κ was 0.877 (P<.001) for alcohol, indicating almost perfect agreement, and 0.440 (P<.001) for smoking and 0.457 (P=.001) for cholesterol, indicating moderate agreement. STAR left a total of 89 health challenges, an average of 1.8 (SD 1.1) per participant, uncategorized because STAR lacked an answer to the question or questions required for the classification of a certain health challenge. The participants did not always add information on their blood pressure (n=36, 74%), cholesterol (n=22, 45%), and waist circumference (n=15, 31%). Conclusions: In conclusion, STAR identified most of the health challenges identified by nurses but missed some essential ones. Participants did not have information on measurements, such as blood pressure and cholesterol values, which are pivotal to STAR in assessing cardiovascular risks. Using the tool for screening or as a part of a traditional health check with necessary measurements and dialog with health care professionals may improve the risk assessments and streamline the health checks of unemployed individuals.