Development and evaluation of a mobile patient application to enhance medical-dental integration for the treatment of periodontitis and diabetes.

Introduction: People around the world are increasingly affected by multimorbidity, where conditions in different medical specialties can correlate in complex ways. This increases the relevance of multidisciplinary integrated care pathways. Modern software solutions provide vast opportunities to enhance information exchange between patients and various healthcare professionals, thereby improving patient-centered and inter-professional care. This paper describes the development and validation of a mobile patient application which exploits Patient Reported Outcomes to enhance patient-centered medical-dental integration with a focus on integrated management of periodontitis and diabetes.

Methods: This study was part of a multidisciplinary project for enhancement of medical-dental integration. The Intervention Mapping Protocol was supplemented by the RAND/UCLA Appropriateness Method, including literature reviews, focus group discussions and a Delphi panel in cooperation with various stakeholders. A mobile application was developed in close collaboration with patients, physicians and dentists. The usability of the application's core components was validated in two medical and two dental practices using the System Usability Scale (SUS).

Results: 39 questions were identified to provide relevant patient-reported information which can be collected via a mobile application to enhance integrated management of periodontitis and diabetes. Usability testing of the application's core components (14 questions) among 137 participants in medical and dental practices indicated a good SUS score of 77.88 (±12.17).

Discussion: The systematically developed mobile application offers the potential to provide physicians and dentists with treatment-relevant information to enhance medical-dental integration, thereby reducing the workload of medical staff, improving the quality of routinely collected data, and enabling automated data processing. This unique, novel, and validated approach can serve as an open framework for the development and evaluation of interdisciplinary healthcare software.