Considering end-to-end workflow when building health tech solutions
The digital tools meant to streamline care often do the opposite. Instead of simplifying workflows, they introduce friction, forcing clinicians to toggle between multiple platforms, reenter data, and manage a flood of inbox messages.
To reverse this trend, experts stress the importance of understanding clinical workflows before building software. Layering point solutions over broken processes doesn’t solve problems in the long-term, particularly when clinicians are apt to reject any solution that doesn’t seamlessly integrate into their existing workflow. Developers cannot think about their solutions’ capabilities in isolation but must look at the overall workflow of the clinician who might use the tool and how that tool fits into the end-to-end workflow.
What does digital health tech ROI look like?
Experts suggest both solution developer vendors and healthcare system buyers review health tech solutions against three potential metrics of ROI: financial, quality, and experience.
1. Financial: Balancing the high cost of AI with specific benefits
Since it is unlikely that many (if any) healthcare organizations are looking to rip and replace their entire tech stack to start over and build the ideal modern workflow, it’s important for digital health tech companies to offer solutions that “play nice” with incumbent technology, like major EHRs, while still offering something that differentiates them from features native to the existing tech. Meanwhile, it’s important for healthcare organizations to build on their existing technology foundations with a critical eye toward cost and benefits, especially when it comes to relatively expensive agentic AI technology.
Narrow agentic AI point solutions may only offer small value opportunities for the cost. Experts recommend healthcare organizations and developers partner on AI solutions that can increase efficiency to affect some or even one of the following ROI metrics:
- Growing panel sizes without increasing burnout.
- Establishing tighter connections between patients and their care teams to influence referrals and care coordination.
- Decreasing total medical spend.
2. Quality: Determining how to quantify patient outcomes
Theoretically, improved patient outcomes is the ultimate ROI for any solution. Organizations and solution developers need to determine the right metrics to judge if technology tools are supporting that overall goal in relation to their particular mission or patient population. Measurable ROI metrics that tie to improved outcomes could include:
- Improving unwanted care variation.
- Reducing instances of overprescribing.
- Lowering the number of unnecessary procedures.
3. Experience: Clinician satisfaction with workflow drives adoption
Positive clinician user experience is challenging to quantify, despite it being one of the top three drivers of digital health platform adoption. Clinician satisfaction tends to increase with solutions that align to their point-of-care needs and integrate directly into workflow and decrease with the more windows they have to open and the more clicks they have to make. A well-integrated tool will help reduce cognitive burden to allow more time for a more traditional patient visit experience.
In addition to overall usage and adoption numbers, experience ROI can mostly be judged by clinician-reported satisfaction metrics, including:
- Time saved and ease of use.
- Speed to decision.
The ongoing role of digital health tech at the point of care
When digital health technology innovators partner with health systems early to co-design workflows that solve real clinical problems, they open the door to moving beyond "cool tech" to essential infrastructure that has the potential to reshape the point of care for better outcomes, less burnout, and overall improvement in ROI. Learn more in the whitepaper.
