– Dr. R. Todd Reilly, Dovel Technologies
At the HIMSS Precision Medicine Summit this summer there was a lot of discussion about the desire to move toward a more distributed model of care delivery. Distributed care is about decentralizing healthcare services – moving basic monitoring and diagnostic tests to the patient instead of requiring the patient to constantly come into a doctor’s office. This can be done inside patient homes or at hyper-local centers. This includes the concepts of telehealth and pharmacy quick clinics. This practice allows highly-trained providers to stay focused on more complex cases rather than administering routine care.
Distributed care is becoming a reality thanks to wide consumer Internet connectivity, availability of IoT devices (and the infrastructure to support them), and electronic record sharing. But the health system is not set up perfectly to enable the desired wide adoption of distributed care. There are a number of hurdles to overcome. These include:
- Technical issues – collecting, managing, aggregating, analyzing, securing data
- Data sharing – cultural resistance, legal and intellectual property issues, standard formats
- Participant engagement – defining who owns and controls the data
- Trust – transparency, consent, privacy, security
- Health justice – for everyone to contribute everyone must benefit
- Cost – insurance must reimburse distributed care, understanding investment vs short term cost
A key element to overcoming these hurdles is a commitment to integration. Technology providers need to ensure that their solutions will work with a variety of other vendor solutions. There is no place for vendor lock-in in a distributed system of care. IT professionals have to understand how to make this integration work for their environment as well as the health ecosystem as a whole. It’s a complex process, but with buy-in across the care spectrum it can be done.
There needs to be better integration of laboratory and research data, as well as related clinical decision support tools, within the Electronic Health Record. This need encompasses the development of Application Program Interface tools to facilitate data access and integration as well as development of support tools (especially those incorporating Natural Language Processing and pattern recognition) to facilitate clinical decision-making.
Of course, having the technology available is not the full answer. Today, there is a significant shortage of genetic counselors and practicing clinicians with sufficient training to interpret precision health data. Beyond that, there is the cultural barrier of moving away from the current, linear model of care delivery, in which translational, clinical, and public health research each feed into patient care without any significant data integration or collaboration.
Data integration can be a critical enabler of more effective and individualized patient care. In this approach, technology-enabled data integration provides access to the breadth of information needed to more fully address the needs, risks, and benefits of all stakeholders. Additionally, technology-driven innovation incentivizes the emergence of new partnerships between health stakeholders, which will be critical for overcoming cultural barriers.
Much of the infrastructure necessary for distributed care exists today. What we need are new applications that work both on the existing infrastructure and with existing workflows. A willingness to share data and open up systems is also critical. The good news is the right applications can help drive this user acceptance and sharing.