Dr. Rushika Fernandopulle, chief innovation officer of One Medical, a tech-enabled primary-care company, recommended health systems and digital health companies sign long-term deals. He said his most successful partnerships with health systems as a digital health entrepreneur have been 10-year relationships.
“Both sides need that commitment,” Fernandopulle said. “We as the innovators need to get the funding and reassure partners we’re not going away.”
Murphy said Geisinger has developed a platform to help manage chronic conditions that uses AI, remote patient monitoring and patient-generated data technologies developed by external partners. She said the organization doesn’t want to be a software company and would rather partner. However, the partnerships must be mutually beneficial.
5. Finding talent is a barrier to transformation
Whether it’s a health system, insurer or a digital health company, panelists agreed the biggest challenge is finding talent, particularly as health systems tackle digital transformation initiatives.
Khan, the first-ever chief digital officer at Mayo Clinic, went from leading a team of 200 staffers to 700 since she started in 2019. Yet, finding people remains a huge challenge. “We’re competing with technology companies for talent,” she said.
Providence, based in suburban Seattle, competes with Microsoft and Amazon for talent, said B.J. Moore, the health system’s chief information officer. To solve this problem, it has hired engineers in India.
“Three years ago we had zero Providence employees outside the U.S. and now we have 550 engineers in India,” Moore said. “We have a 24/7 engineering cycle. While we’re asleep in the U.S., they’re engineering in India and vice versa.”
Amid clinician burnout, Providence’s chief people officer, Greg Till, said flexibility is how health systems will engage and retain employees. Health systems need to give employees what they need where they want it and when they want it. He said Providence uses data to better understand employees.
“We have gathered a lot of data over the last two to three years and can predict with 95% accuracy where our staffing needs are going to be three to six months out,” Till said. “We can pinpoint the effectiveness of our interventions—whether it’s caregiver rounding, additional pay schemes or more flexibility—based on attrition at the unit level, caregiver function level and we’re perfecting it at the patient level.”