Acceptance of mHealth among health professionals: a case study on anesthesia practitioners

Abstract

Background: mHealth, the practice of medicine aided by mobile devices is a growing market. Although the offer on Anesthesia applications (Apps) is quite prolific, representative formal assessments on the views of anesthesia practitioners on its use and potential place in daily practice is lacking. This survey aimed thus to cross-assess the Belgian anesthesia population on the use of smartphone Apps and peripherals.

Methods: The survey was exclusively distributed as an online anonymous questionnaire. Sharing took place via hyperlink forwarding by the Belgian Society for Anesthesia and Reanimation (BSAR) and by the Belgian Association for Regional Anesthesia (BARA) to all registered members. The first answer took place on 5 September 2018, the last on 22 January 2019.

Results: Three hundred forty-nine answers were obtained (26.9% corresponding to trainees, 73.1% to specialists). Anesthesiologists were positively confident that Apps and peripherals could help improve anesthesia care (57.0 and 47.9%, respectively, scored 4 or 5, in a scale from 0 to 5). Trainees were significantly more confident than specialists on both mobile Apps (71.2% and 51.8%, respectively; p = 0.001) and peripherals (77.7% and 45.1%, respectively; p = 0.09). The usefulness of Apps and Peripherals was rated 1 or below (on a 0 to 5 scale), respectively, by 9.5 and 14.6% of the total surveyed population, being specialists proportionally less confident in Smartphone peripherals than trainees (p = 0.008). Mobile apps are actively used by a significantly higher proportional number of trainees (67.0% vs. 37.3%, respectively; p = 0.000001). The preferred category of mobile Apps was dose-calculating applications (39.15%), followed by digital books (21. 1%) and Apps for active perioperative monitoring (20.0%).

Conclusions: Belgian Anesthesia practitioners show a global positive attitude towards smartphone Apps and Peripherals, with trainees trending to be more confident than specialists.

Trial registration: ClinicalTrials.gov database Identifier: NCT03750084. Retrospectively registered on 21 November 2018.

Keywords: Anesthesia; Apps; Smartphone application; Smartphone peripherals; mHealth.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1

Subspecialty stacked distribution of responding Anesthesia Specialists (one specialist can be accounted for more than once if he holds multiple subspecialty competences). Percentages represent the total number of surveyees per specific category relative to total number of surveyees

Fig. 2

Apps (left - blue) vs Peripherals (right - orange) - Confidence level (scale: 0 to 5). x axis – Confidence level category, y axis – absolute number of survey answers (“How confident are you that Smartphone Apps can help improve anesthesia care?” / “How confident are you that combining your smartphone with a dedicated monitoring peripheral can help improve anesthesia care?”)

Fig. 3

Apps Confidence level (scale: 0 to 5): Specialists (left) vs Trainees (right). x axis – Confidence level category, y axis – absolute number of survey answers

Fig. 4

Peripherals Confidence level (scale: 0 to 5): Specialists (left) vs. trainees (right). x axis – Confidence level category, y axis – absolute number of survey answers

Fig. 5

Categorization of the most appealing Apps (“Which kind of Apps appeal you the most?”). x axis – App category, y axis – absolute number of survey answers

Fig. 6

Phase in which Smartphone Apps can be more useful (“In which phase of perioperative care can Smartphone Apps be more useful?”). x axis – absolute number of survey answers, y axis – Perioperative phase category

Fig. 7

Phase in which Smartphone Peripherals can be more useful (“In which phase of perioperative care can Smartphone Peripherals be more useful?”). x axis – absolute number of survey answers, y axis – Perioperative phase category

Fig. 8

Wishes for smartphone peripheral device development per monitoring category (“Which peripherals would you like to see developed in the coming future?”). Percentages represent the total number of votes per specific category relative to total number of votes