Marija Radic and Agnes Vosen, Fraunhofer IMW, Germany
Objectives
There are increasing burdens on the health sector, both through rising healthcare cost and skills shortage. Data-based solutions have the potential to alleviate some of this burden. Especially clinical decision support systems (CDSS) as data-based healthcare services incorporating AI have the potential to improve care while reducing healthcare costs at the same time. In the research project MED2ICIN, a CDSS for chronic inflammatory bowel diseases (IBD) has been developed which consists of a decision support system for the clinician on the one hand and a patient app for improved data sovereignty and patient involvement on the other hand. The aim of the qualitative study is to determine the potential value of the CDSS in terms of increasing benefits and reducing cost.
Methods
We conduct semi-structured interviews with 12 gastroenterologists from different university clinics in Germany. After an initial explanation of the eHealth solution, we discuss the potential of the solution with regards to cost, time expenditure and quality of care. The experts are stratified in terms of their experience ranging from assistant doctors to specialists and senior specialists.
Results
The CDSS consists of different modules. In the interviews we discuss the potential of the overall solution as well as the potential of individual modules of the solution. The results show that the overall solution can lead to improvements in all three dimensions. It appears that the individual modules have different effect strengths in the individual dimensions: Most modules are expected to increase in the quality of care. The interviews also suggest a reduction in the time spent on many tasks. The possibility of saving costs is also immanent, depending on the module. Discussion The results show that physicians appreciate the support of a CDSS. Our qualitative study also shows that the CDSS has the potential to increase quality of care and realize cost and time savings. In a next step, we plan to validate the results based on a quantitative health economic study. There are increasing burdens on the health sector, both through rising healthcare cost and skills shortage. Data-based solutions have the potential to alleviate some of this burden. Especially clinical decision support systems (CDSS) as data-based healthcare services incorporating AI have the potential to improve care while reducing healthcare costs at the same time. In the research project MED2ICIN, a CDSS for chronic inflammatory bowel diseases (IBD) has been developed which consists of a decision support system for the clinician on the one hand and a patient app for improved data sovereignty and patient involvement on the other hand. The aim of the qualitative study is to determine the potential value of the CDSS in terms of increasing benefits and reducing cost. Methods We conduct semi-structured interviews with 12 gastroenterologists from different university clinics in Germany. After an initial explanation of the eHealth solution, we discuss the potential of the solution with regards to cost, time expenditure and quality of care. The experts are stratified in terms of their experience ranging from assistant doctors to specialists and senior specialists. Results The CDSS consists of different modules. In the interviews we discuss the potential of the overall solution as well as the potential of individual modules of the solution. The results show that the overall solution can lead to improvements in all three dimensions. It appears that the individual modules have different effect strengths in the individual dimensions: Most modules are expected to increase in the quality of care. The interviews also suggest a reduction in the time spent on many tasks. The possibility of saving costs is also immanent, depending on the module.
Discussion
The results show that physicians appreciate the support of a CDSS. Our qualitative study also shows that the CDSS has the potential to increase quality of care and realize cost and time savings. In a next step, we plan to validate the results based on a quantitative health economic study.