Understanding Health Care Workers' Attitudes and Preferences Toward Digital Patient Monitoring Platforms: Cross-Country Survey Study

Abstract

Background: The integration of digital health tools into the routines of health care workers (HCWs) holds potential to enhance health care delivery. In particular, digital tools for patient data monitoring allow HCWs to quickly access patient health information and detect early warning signs of potential issues. However, while interest in these tools, such as telemedicine and mobile health, has rapidly grown in recent years, limited research has explored HCWs' attitudes toward digital innovations or their feature preferences.

Objective: This study aims to (1) assess HCWs' attitudes toward digital health tools for patient data monitoring, (2) identify socioeconomic factors influencing these attitudes, (3) determine HCWs' preferences for features of a novel digital health platform for patient data monitoring, and (4) examine whether HCWs' baseline attitudes impact their feature preferences.

Methods: This study uses an integrated approach combining item response theory (IRT) and discrete choice experiment to evaluate the attitudes and preferences of HCWs. Data come from a web conjoint survey distributed to an international cohort of HCWs across the following 4 European countries: Spain, Albania, Bulgaria, and Greece.

Results: Survey respondents comprise 260 HCWs from the 4 countries. The findings indicate that HCWs generally hold a positive attitude toward technological devices (all the IRT coefficients are statistically significant with P<.05). Socioeconomic characteristics, including factors such as gender (P=0.05), professional role (P=0.01), and educational background (P=0.01), significantly influence these attitudes. Results show that highly educated female HCWs are those who are mostly inclined to use technologies. In addition, the specific features of a digital health platform for patient data monitoring highly impact HCWs' willingness to incorporate such a tool into their daily practice (all coefficients related to the attributes' effects in the models for the discrete choice experiment results are significant (all P=0.01 except the data looking attribute which has P=0.03) . The findings suggest that an ideal digital health platform for patient data monitoring should offer intuitive graphs, comparative statistics against standards, and include patients' family clinical history. In addition, health workers should receive instructor-led group training to effectively use the platform.

Conclusions: This study shows that health workers generally support the use of digital health tools, which have the potential to improve health care efficiency and patient outcomes through enhanced monitoring and timely interventions. To facilitate adoption, policymakers should strengthen infrastructure, enact supportive legislation, and tailor interventions for groups less inclined to use these tools. Aligning digital health platform features with HCW preferences is crucial, as it directly impacts HCWs' willingness to integrate these tools into daily routines, ultimately benefiting patients. Future research should examine additional factors influencing HCW adoption and address organizational and infrastructural barriers to optimize implementation of digital health platform and improve patient care.

Keywords: discrete choice experiments; health care workers; health technology; preferences; survey study.

Figure 1.. The determinants of the individual attitude toward using technology in the working activities, daily habits, and both. The figure reports estimates regarding the linear regression coefficient, together with their corresponding 95% CIs, in the 3 different models. EHR: electronic health record.

Figure 2.. Discrete choice experiment results: odds ratios and corresponding 95% CIs of 3 conditional logit models.

Figure 3.. Discrete choice experiment results: ideal characteristics of the web platform.