Digital Healthcare Innovations and Idea Management

Abstract

The COVID-19 pandemic has triggered a paradigm shift –it is also referred to as the sense of urgency —for accelerating digital healthcare and well-being innovations, although not all new innovations are directly related to COVID-19. Many of the topical innovations have to do with new findings related to artificial intelligence (AI) solutions. For example, scanning healthcare images for the signs of additional conditions or AI-powered mental health apps, the innovation that combines health data with a personalized remote neurofeedback training to improve sleep or an app that enables at-home hormone monitoring in real-time (Springwise, 2022). These are just few digital healthcare innovations which have been launched recently. The AI business platform model is virtually in affluence with the cloud SaaS model –it concerns AI solutions that can work together on the top layer of other digital systems (Mishra & Tripathi, 2021). One of the key questions is whether the growth in public-private funding followed these changes, and how web-based idea management systems (IMS) may support the ongoing digital healthcare innovations.A digital healthcare innovation ecosystem has been researched by many researchers and has been highlighted as a very important one. Several studies have underscored its significance (Asi & Williams, 2018; Benedict & Schlieter, 2015; Bhavnani et al., 2017).Research has also examined various aspects of its development and implementation (Chae, 2019; Cheng et al., 2021; Craig et al., 2020). The role of technology and innovation in enhancing healthcare outcomes has been a focus of many investigations (Cripsi et al., 2019; Gjellebæk et al.,2020; Han et al.,2021). Furthermore, the integration of digital solutions in healthcare systems has been explored extensively (Iyawa et al., 2017; Javaid & Khan, 2021; Kraus et al., 2021). Scholars have also looked into the challenges and opportunities within this ecosystem (Petrakaki et al., 2021; Walsh & Rumsfeld, 2017; Abasi et al., 2021). The impact of digital health innovations on patient care and healthcare delivery has been well-documented (Bygstad & Øvrelid, 2020; Kuo, 2011; Laurenza et al., 2018). Additional research has provided insights into the strategic and operational aspects of digital healthcare ecosystems (Raghupathi & Kesh, 2009; Serbanati et al., 2011; Kouroubali et al., 2021). Studies have also addressed the economic and policy implications (Nimmagadda et al., 2019; Oderanti et al., 2021; Ramadi & Srinivasan, 2021). The evolution and future prospects of digital healthcare innovation continue to be a vital area of study (Regan et al., 2009; Segers & Gaile-Sarakne, 2021).However, in this paper the authors will try to link it with a web-based idea management system potential. Web-based idea management systems (IMS) fall in line with the growing importance of information communication technologies, the spread of open innovation and co-innovation, etc. Especially systems based on the Internet during COVID-19 have become important tools in all sectors. Plus, over the last few years the changes related to digital healthcare have taken place and now in this context the questions have been raised. How could they be linked with a web-based IMS? What are digital healthcare innovation demands and funding trends?Digital healthcare tendencies were researched in previous research (Bhavnani, 2017; Chae, 2019), but in this paper, the authors will concentrate on the COVID-19 period that was the time of changes in healthcare. Previous studies have laid a foundation by examining various digital healthcare trends and their impact on the industry. These earlier works provided valuable insights into the gradual integration of technology in healthcare systems. However, the unprecedented global pandemic brought about rapid andsignificant shifts in how healthcare services are delivered and accessed. This paper aims to explore these specific changes, highlighting the acceleration of digital healthcare adoption during the COVID-19 period and analyzing its implications for the future of healthcare delivery.The application and demand of digital healthcare have been well researched (Andersen et al., 2019; Bennion et al., 2017; Ding et al., 2019; Safi et al., 2018). Previous studies have provided comprehensive insights into the growth and integration of digitalhealthcare solutions (Oborn & Pilosof, 2021; Chang et al., 2021; Safi et al., 2018). Additionally, these works have highlighted the increasing adoption and the benefits of digital healthcare technologies (Balcombe & De Leo. , 2021; Curfman et al., 2021; Hospodková et al., 2021). Several researchers have emphasized various aspects of digital healthcare demand and implementation (Cremers-Pijpers et al., 2021; Dykgraaf et al., 2021; Keasberry et al., 2017). Further studies have explored patient engagement andtechnology acceptance in digital health (Kursīte et al., 2022; Lai et al., 2021; Nikkou et al., 2020). However, in this case, the authors will focus on very specific aspects of digital healthcare to address current gaps in the literature.