Welcome to the Digital Health revolution

From digital health to learning health systems: four approaches to using data for digital health design

Digital health technologies, powered by digital data, provide an opportunity to improve the efficacy and efficiency of health systems at large. However, little is known about different approaches to the use of data for digital health design, or about their possible relations to system-level dynamics. In this contribution, we identify four existing approaches to the use of data for digital health design, namely the silent, the overt, the data-enabled, and the convergent. After characterising the approaches, we provide real-life examples of each. Furthermore, we compare the approaches in terms of selected desirable characteristics of the design process, highlighting relative advantages and disadvantages. Finally, we reflect on the system-level relevance of the differentiation between the approaches and point towards future research directions. Overall, the contribution provides researchers and practitioners with a broad conceptual framework to examine data-related challenges and opportunities in digital health design.

Digital maturity and its determinants in General Practice: A cross-sectional study in 20 countries

Background

The extent to which digital technologies are employed to promote the delivery of high-quality healthcare is known as Digital Maturity. Individual and systemic digital maturity are both necessary to ensure a successful, scalable and sustainable digital transformation in healthcare. However, digital maturity in primary care has been scarcely evaluated.

Objectives

This study assessed the digital maturity in General Practice (GP) globally and evaluated its association with participants' demographic characteristics, practice characteristics and features of Electronic Health Records (EHRs) use.

Methods

GPs across 20 countries completed an online questionnaire between June and September 2020. Demographic data, practice characteristics, and features of EHRs use were collected. Digital maturity was evaluated through a framework based on usage, resources and abilities (divided in this study in its collective and individual components), interoperability, general evaluation methods and impact of digital technologies. Each dimension was rated as 1 or 0. The digital maturity score was calculated as the sum of the six dimensions and ranged between 0 to 6 (maximum digital maturity). Multivariable linear regression was used to model the total score, while multivariable logistic regression was used to model the probability of meeting each dimension of the score.

Results

One thousand six hundred GPs (61% female, 68% Europeans) participated. GPs had a median digital maturity of 4 (P25-P75: 3-5). Positive associations with digital maturity were found with: male gender [B = 0.18 (95% CI 0.01; 0.36)], use of EHRs for longer periods [B = 0.45 (95% CI 0.35; 0.54)] and higher frequencies of access to EHRs [B = 0.33 (95% CI 0.17; 0.48)]. Practicing in a rural setting was negatively associated with digital maturity [B = -0.25 (95%CI -0.43; -0.08)]. Usage (90%) was the most acknowledged dimension while interoperability (47%) and use of best practice general evaluation methods (28%) were the least. Shorter durations of EHRs use were negatively associated with all digital maturity dimensions (aOR from 0.09 to 0.77).

Conclusion

Our study demonstrated notable factors that impact digital maturity and exposed discrepancies in digital transformation across healthcare settings. It provides guidance for policymakers to develop more efficacious interventions to hasten the digital transformation of General Practice.

Message applications in the doctor-patient relationship as a stressor

OBJECTIVE:

The aim of this study was to assess the use of smartphones’ messaging apps as a stressor affecting the well-being of gynecologists who use this tool to communicate with patients.

METHODS:

A cross-sectional study was conducted with gynecologists who use message applications to communicate with patients. Participants answered the WhatsApp Stress Scale, Oldenburg Burnout Inventory, and the techno-stress questionnaire. The population sample consisted of gynecologists and obstetricians selected by convenience.

RESULTS:

Physicians who spent more time using WhatsApp to communicate with patients had higher levels of stress (p=0.010), Burnout (p<0.001), and techno-invasion score (p<0.05).

CONCLUSIONS:

A positive association was found between the high frequency of WhatsApp usage for communication with patients and doctor's Burnout and stress, negatively influencing professional's well-being.