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Vision Use Cases
sphin-X aims to provide a platform that takes the healthcare system to a new level through improved data exchange. sphin-X does not primarily stand for the implementation of a specific use case, but provides scope for a wide range of conceivable applications. The following use cases are currently being discussed in the support group and should serve as inspiration at this point:
Integration of clinical data sets for efficient study planning
Existing medical data from healthcare and findings from research form the basis for planning future clinical trials. The collection and use of the required data is very time-consuming and in some cases not possible, as the data is distributed across many systems and institutions and is not technically and semantically interoperable or quality-assured. sphin-X could provide a central platform that gives data users quick and easy access to existing medical data. Available medical datasets are uniformly described, cataloged, technically and semantically interoperable, and quality-assured. The data can be used securely and in compliance with data protection regulations via standardized interfaces. The introduction of such a platform can simplify and accelerate study planning and protocol development.
Patient matching
There is currently a lack of effective patient matching for clinical trials in the healthcare sector. There is no central platform that connects study sponsors, patients and healthcare providers to efficiently identify potential study participants and find suitable studies for patients. sphin-X could offer a solution here by providing a central web service for clinical studies. This would make it easier for doctors to find patients to participate in the study.
Consent management
There is currently no standardized consent management for the automatic transfer of health data between service providers. The lack of standardization leads to higher costs and lower documentation quality. Principal investigators are also less willing to participate in clinical trials. sphin-X could provide standardized consent management by automatically transferring health data between the patient record (EHR) of a practice management system and a study database (EDC). The introduction of indication-specific documentation standards can reduce costs, improve quality and increase the willingness of principal investigators to participate in clinical trials.
Master data management
There is currently no standardized semantic and syntactic description of participants, services and assets in the healthcare sector. Different players in the healthcare sector use different data formats and structures. This makes interoperability and data exchange more difficult. sphin-X could be the basis for a standardized solution that makes it possible to describe master file data uniformly across different use cases and thus ensure smooth communication and collaboration in the healthcare sector.
CO2 footprint
There is currently no standardized calculation and no easy access to or exchange of CO2 footprint data in the healthcare sector. This makes it difficult to ensure the transparency of CO2 emissions along the value and supply chains and to optimize the CO2 footprint of health care products. sphin-X could establish standardized methods and measurement procedures for calculating the CO2 footprint of products in the healthcare sector. It could provide a secure and accessible data platform where this CO2 footprint data can be stored and shared. As an example, this use case shows that the joint development of standards enables cost-efficient compliance with future regulatory requirements in various areas.
Central platform for pharmacovigilance processes
Current pharmacovigilance processes are often not efficient due to the high administrative effort involved. Side effect reports are rarely recorded by doctors and existing drug interactions are not always recognized. sphin-X could enable simple recording (e.g. by scanning the QR code on the product packaging) and the creation of a database containing information on medicines, CYP involvement and existing side effects. An algorithm could be used to identify new DDIs or warn patients in their electronic patient file (ePA) or for the attending physician when prescribing. The consistent streamlining of the process through digitalized recording of adverse drug reaction reports would allow improved detection of drug interactions. This use case could also enable central PV services such as free text field monitoring or the direct connection of the database to the regulator’s systems.
Data repository for diagnosed image data
Healthcare stakeholders often collect image data in clinical trials that cannot be used and reimbursed efficiently due to the lack of a central platform for aggregating and using this data. sphin-X could create a repository for image data from various imaging procedures. By consolidating this data in a central system, health care companies, clinicians and other stakeholders could use this data efficiently and remunerate it accordingly. This would promote collaboration, knowledge transfer and AI training in pharmaceutical research and thus enable improved utilization and monetary value creation of image data from clinical studies.
Genotyping of the CYP isoenzymes
Patients often know nothing about their individual drug metabolism, which can lead to over- or underdosing. At the same time, the pharmaceutical industry lacks access to relevant genome data to improve drug safety. sphin-X could enable patients to confidentially report the side effects of a drug to a pharmaceutical company and have their CYP-450 enzymes genotyped. This would allow them to find out whether they metabolize the drug quickly or slowly and whether they are possibly over- or underdosing. The information could be made available to the patient and the pharmaceutical company could receive the genotyping in a pseudonymized form for research purposes. In this way, sphin-X would contribute to improving patient counseling and support pharmaceutical research by providing access to relevant genome data.