Kevin Keenahan, is the Chief Product Officer at Net Health and co-founder of Tissue Analytics, Inc., acquired by Net Health in 2020.
Net Health’s mission is to harness data for human health. They offer EHR software and predictive, actionable analytics for medical specialties, including rehab therapy, wound care, home health and hospice and employee health. Their solutions are trusted in over 23,000 facilities across the continuum of care, including the nation’s leading hospitals, skilled nursing facilities, senior living facilities, home health and hospice agencies and outpatient clinics.
Could you share the genesis story of how you got involved in wound care, and how this resulted from your graduate studies at John Hopkins University?
Back in 2013, I started my Master’s at the Johns Hopkins Center for Bioengineering Innovation and Design (CBID), which is an incredible program that gives young engineers the chance to rotate through different clinical settings at the Johns Hopkins Hospital. I was fortunate enough to see chronic and acute wound care during these rotations and found the space fascinating, which led me to spend more dedicated time in the wound center at Hopkins.
Through that experience, I realized there was a lack of innovation in the wound care industry, with most wound care treatments relying on outdated methods and technologies to assess efficacy. I saw this as an opportunity to use my engineering training to create a solution for wound care management that would facilitate better data collection and improve chronic wound outcomes, leading me to found Tissue Analytics in 2014.
Tissue Analytics, Inc., was then acquired by Net Health in 2020. Could you share some details about this moment in time and why you chose to be acquired?
Net Health® Tissue Analytics uses machine learning to analyze wound images and automatically measure healing. The acquisition was highly strategic for us because it gave us an opportunity to expand our reach and provided access to a much larger dataset for us to apply to our machine learning methods. Joining forces with Net Health also allowed us to leverage their established position in the market and access its network of healthcare providers, in addition to strengthening their inpatient wound care business.
How does Net Health use machine learning for wound tracking?
Net Health’s algorithms analyze millions of images in seconds to automatically measure a wound’s size and colorimetric composition. It’s 90% more accurate than manual, ruler-based measurements, which have a 40% error rate. This capability leads to a more objective story of healing to drive better patient care and outcomes. This technology is the foundation of our mobile wound imaging and analytics solution, which uses artificial intelligence combined with a smartphone to measure, characterize and analyze a chronic wound more accurately. Using the data collected in the wound imaging process, it also predicts whether a pressure injury is at risk for deterioration, a particularly important feature for hospitals that get penalized for hospital-acquired pressure injuries.
Why is precise tracking of wound size so important in healthcare?
There are a few reasons. Precise tracking enables clinicians to monitor the healing progress of a wound over time, make effective treatment decisions and estimate healing times. By regularly measuring the wound, providers can determine if the wound is healing as expected or if there are any signs of stalled healing. This helps providers make informed decisions about the right course of treatment and adjust these care plans as necessary. By providing a common foundation of healing to the entire care team, everyone including the patient now has an objective measure of progress that is shared across providers as well as care settings.
What other types of analytics can be offered for wound care?
In our wound care EHR product, Net Health® Wound Care, we can offer powerful predictions around amputation risk and total wound healing time. In addition, we offer a missed visit prediction indicator that flags patients at risk for missing a visit. This enables wound care providers to intervene, whether they help communicate with the patient directly or double-book to ensure they don’t lose revenue or time spent providing care.
Net Health goes beyond wound analytics, what other types of services are offered?
We also offer EHRs for full spectrum of rehab professionals, which include physical and occupational therapists and speech language pathologists. Our rehab therapy EHRs serve private practice clinics, hospital therapy units, hospital outpatient clinics, skilled nursing facilities and assisted living communities. Our outpatient and private practice EHR comes with a patient engagement suite, which helps clinics market their services and engage their patients through digital interactive tools and an automated digital intake process.
In your opinion, why is the adoption of AI in healthcare so important?
AI has the potential to improve the accuracy and efficiency of healthcare operations, from diagnosis and treatment to the automation of administrative tasks. Algorithms can analyze vast amounts of data and identify patterns that would be difficult or impossible for humans to detect, enabling more accurate diagnoses, more personalized treatment plans, and better resource allocation. It can even help to reduce healthcare costs by streamlining processes and reducing the need for manual labor. It can also help to improve patient outcomes by enabling earlier diagnosis and treatment, reducing the risk of complications, and facilitating more personalized care. For example, AI-powered wound care management platforms can help healthcare providers to track wound healing progress more accurately, identify potential complications, and adjust treatment plans accordingly. Healthcare providers can improve patient outcomes, reduce costs, and stay at the forefront of technological innovation in the field with AI, so adoption is crucial if you have not already utilized it.
Do you see a future for generative AI in healthcare?
Absolutely. AI can help to improve the accuracy and speed of diagnosis, leading to better outcomes for patients. Generative AI can analyze a patient's medical history, genetic data, and other factors to automate the documentation process while simultaneously predicting which treatments are most likely to be effective for that individual.
Tissue Analytics originally had the vision of transforming the smartphone into a sophisticated imaging and diagnostic platform for chronic wounds, to redefine how wound care is delivered. Could you share how your vision has evolved over time?
Following the acquisition by Net Health, Tissue Analytics has continued to develop its wound care management platform, while also integrating its technology into Net Health's broader suite of healthcare solutions. This has enabled Tissue Analytics to expand its capabilities and include functionality for predicting the deterioration of pressure injuries in the hospital setting and automatically capturing wounds that wrap around patients’ limbs, which we call circumferential imaging. Moving forward, the product will continue to innovate with a focus on identification, prevention, and management of chronic wound conditions through advanced analytics solutions in all care settings.
Is there anything else that you would like to share about Net Health?
Net Health has a strong focus on the specialized needs of healthcare providers. This focus enables Net Health to deliver tailored solutions that are specifically designed to meet the unique needs of providers, rather than offering a one-size-fits-all approach. This understanding of specialized clinical workflows puts us in a unique position to seamlessly gather the most impactful, high-quality data and develop cutting edge AI tools that will ultimately help us move the entire industry forward.
Thank you for the great interview, readers who wish to learn more should visit Net Health.
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