Telehealth is now firmly established as a key form of care delivery in most practices and hospitals, with many organizations now shifting from program implementation or expansion to optimization. Indeed, Sage’s recently released report on telehealth in 2023 notes that 41% of hospitals and 35% of practices are now in optimization mode — more than double the number just getting started with their programs.
As virtual care leaders aim to take their programs to the next level, developing confident telehealth staff that have the skills and support they need to be successful will be key.
All too often, though, virtual care feedback loops and performance evaluations fall short.
Feedback is painfully delayed and infrequent, expectations are unclear and staff are evaluated based on only a fraction of their interactions.
This has largely been a resourcing issue: Managers can only manually audit so many calls, so only a fraction are considered; and with so little data to draw upon, evaluations are generalized and don’t take into account long-term trends. Meanwhile, few teams have time for constant refresher trainings, so quality standards slip.
To offer patients the best experience and feel confident in their work, staff need regular, timely feedback and individualized coaching that takes into account all of their interactions. And while that once sounded like a pipe dream, new developments in AI and conversation intelligence have made QA and feedback on 100% of calls as simple as a few clicks.
Here’s a quick look at how AI can seamlessly fit into your 2023 virtual care workflow by offering staff the timely, comprehensive feedback they need to do their best work.
Feedback and call scoring in real time
One way that AI and conversation intelligence tools can be used to improve virtual care is by providing real-time quality assurance (QA) based on an organization’s best practices checklist. These tools use natural language processing and machine learning algorithms to analyze calls and offer insight into the content and tone of the conversation.
When trained on an organization’s unique protocols and QA standards or industry best practices, conversation intelligence tools can automatically evaluate virtual care calls as they happen to see whether staff members are following proper protocols and addressing key topics.This is particularly useful in virtual care settings since all interactions can be captured digitally and it’s not always possible for managers to observe interactions in person and provide real-time feedback.
Along with highlighting key steps to follow, questions to ask or topics requiring special attention during calls, these tools can score the quality of a call as soon as it ends, giving staff immediate feedback on their performance and advice on how to improve next time.
By providing feedback in real time, these tools can give staff a sense of how they are performing during the call and allow them to adjust their approach as needed, gently ensuring compliance while reinforcing training and best practices. Rather than waiting until the end of a shift (or, more realistically, until the end of the quarter or at annual reviews) to receive feedback, staff can get instant feedback and guidance as they work.
For example, if a staff member is overlooking required screening questions or deviating from protocols, the conversation intelligence tool can alert them and suggest areas for improvement. This can help to ensure that all virtual care interactions are meeting an organization’s compliance and quality standards, without requiring managers to manually audit hours upon hours of recordings.
These tools can even be used to dynamically generate additional resources for staff to review after the call (like call notes and key topics discussed) or potentially share with patients (like virtual therapy session notes, action items and more), further leveling up their expertise and confidence that they’re delivering the best possible care.
Comprehensive reporting and individualized coaching
This data can also be used retrospectively to identify areas where staff are consistently struggling or excelling, giving managers the insights they need to build contextual, data-backed performance evaluations and offer targeted feedback and coaching.
Evaluations need no longer be based on only a fraction of calls. Instead, since QA is done automatically and on every call, managers can use conversation intelligence to easily spot trends across thousands of calls and get a once-unthinkable view into staff performance on both a team and individual level.
With these insights in hand, managers are able to build nuanced and focused training plans that meet staff where they are. Instead of one-size-fits-all modules, managers can tailor training and coaching to individual staff members, helping them level up their expertise and confidence while also demonstrating that the organization is committed to their continued growth.
These tools and insights can also be used to reward the good work of top-performing staff and learn from their example. Managers can even identify best practices of top performers and implement them throughout the organization, refining quality standards across the organization.
This creates a positive feedback loop that drives continuous improvement and ensures key talent get the kudos and career growth opportunities they deserve.
By using these tools to support staff development and recognize top-performers, organizations can create a positive culture of excellence and ensure that their staff are delivering the best possible care to their patients.
Bottom line: AI gives virtual care managers superpowers
By using AI to provide comprehensive QA on 100% of calls and give staff real-time feedback virtual care leaders can improve their staff’s performance, grow their careers, build hyper-personalized coaching plans and ultimately create a better patient experience.
What once seemed impossible is now only a few clicks away. If you’re ready to go beyond simply sustaining your virtual care program and begin optimizing it for the best possible patient and staff experience, AI-powered feedback and performance evaluation can be a huge difference-maker.
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