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Why Telemedicine Success Measurements Fall Short


Health-tech KOL Janae Sharp talks to experts about the telemedicine metrics problem and possible solutions.

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Healthcare organizations must use the right metrics to measure the success of telemedicine programs. Image has been altered. Licensed from goir — stock.adobe.com.

Telemedicine is one key way to bring care closer to patient needs. Healthy life changes in the home have massive effects on patient outcomes, alleviating some of the circumstances that physicians and payers cannot control but for which they are still held financially liable. Social circumstances and access to care have a huge impact on someone’s potential to heal. A lack of specialists and limited access to care in rural areas mean some patients drive hours to treatment. But developing a telemedicine program and measuring its value is a data science challenge.

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Measuring the success of a program based on adoption is a mistake. Some programs simply drive more usage without adding value to health outcomes. Patients and providers need to benefit. Because there are so many different ways to measure telemedicine, specific outcome goals need to be determined by a health system. If you want to deliver better behavioral health care to a rural underserved area, that will require different benchmarks than an initiative designed to identify stroke victims quickly. The sheer volume of options means analytics don’t transfer across different systems.

Recently, Health Catalyst, a company that uses technology to unify healthcare data, held their annual conference, drawing health IT leaders, technologists and traditional data science experts. Many of the tools people showed interest in were directed toward setting up better analytics and making health data useful for improving care.

However, the diversity of need and types of data mean we are not all measuring the same thing. One of the difficulties with collaborative models and startups in the digital and healthcare analytics space is that, despite the shared goal of improving healthcare access, we are not all on the same page.

Analyzing a Telemedicine Success Story

Lyle Berkowitz, M.D., chief medical officer of the telehealth company MD Live, sat down with me at lunch and discussed what he believes is important in developing telemedicine programs. “We use multiple analytics to assess quality, satisfaction and efficiency of the telehealth care we deliver to our patients,” he told me. “We review these daily to help determine where to prioritize product changes, how updates impact our system and which providers or staff might need additional coaching.”

Berkowitz also discussed the challenges of treating patients who live in remote areas or are otherwise unable to regularly see a physician. “To reach patients who don’t have the financial resources or bandwidth to have regular medical care, we need to improve access to care,” he said. “Many health systems have options to provide care remotely, but adoption of telemedicine programs remains consistently low or is reported with measures that don’t actually improve health outcomes.”

An example: If a health system reports fantastic adoption but measures every text message from patients to providers as evidence, then their reporting isn’t valuable.

Healthcare providers need to account for people who don’t want to go to the doctor. This virtualization can provide for patients that have barriers due to cost, time and distance. The combination of automation and virtualization that telemedicine offers allows for better patient care delivered to more patients for each doctor.

MD Live uses analytics to actively improve the patient experience. They use reviews to make measures that matter over simple adoption, distributing post-visit surveys that produce satisfaction metrics. The company reviews each case in which a patient was unhappy and attempts to remediate the situation as necessary. Those statistics also guide MD Live in developing product and service improvements to enhance the telemedicine program at large.

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At that point, things “get interesting,” Berkowitz said. MD Live uses machine learning to analyze visit recordings, building a score based on that information and patient satisfaction and demographic data. The resultant score enables the telemedicine company to predict which patients might have a problematic experience — and how to prevent that.

No National Standard for Telemedicine Success

However, replicating the work of MD Live on a national level isn’t a simple proposition. The debate surrounding virtual primary care is key to improving health outcomes, but there are so many solutions, and none has yet emerged as a clear market leader in the heavily regulated healthcare industry. Regulation is evolving more slowly than telemedicine options.

Sarah Sossong, principal at Flare Capital Partners, spoke to me about her experiences with developing some of the national quality measurement framework for telemedicine. “There are so many different ways to measure what is important and what brings value to a health system,” she said.

No matter what your system is, value-based adoption of a program is key. While providing access to care remotely is important, if a health system is simply providing a healthcare system call-in for searches or is driving volume without adding better medical care, the program doesn’t add value.

“The incentive alignment of adoption, value and payment is inconsistent,” Sossong explained, “since reimbursement rates are as inconsistent as what different health systems will code as a telemedicine healthcare encounter. I don’t think we will make progress in the space until they have parity. Currently, not every program has the adoption it needs. But the adoption itself isn’t enough. We need high-value adoption.”

In a field with huge amounts of variety, goal-oriented analytics are key. If the No. 1 focus of a telemedicine program is adoption of the program, the analytics can be misleading. Maybe a department will show a huge increase in usage, but it is driven by two providers, meaning adoption of tools like messaging, digital tools and virtual visits should be addressed broadly.

Sossong talked about the step-by-step processes of developing national tools for measurement and driving better value in individual programs. One of the most difficult parts of this process is a lack of parity. We want care that improves patient outcomes, and physicians want to be paid for the work they do. The other challenge is that we have a lack of common metrics. This insight mirrors the criticism from Berkowitz. In our market, if one health system reports success but measures every text message to a patient, while the other system only measures video encounters, how do we determine what “works” and drive the best program through adoption?

>> READ: How Telemedicine Helps Victims Heal After Tragedies

A patient encounter should not have the same reimbursement as a text message. According to Sossong, “because there is no standard for telehealth measurement, if we want to compare Mass General’s telehealth to Cleveland Clinic’s, to Miami’s, we’re stuck — because we don’t really have common metrics.”

Value is inherently difficult to measure for payers and providers given the current state of telemedicine. Even in reducing readmission or urgent care or telepsychology visits, there are so many permutations for which the return on investment for a behavioral health visit might be zero.

Designing a Better Telemedicine Program

Part of the challenge of streamlining value measurement is that that not every program is designed with specific health metrics in mind. I spoke with Rachel Dixon, who developed a telepsychiatry program with Colorado Access and now works with companies to develop successful telemedicine programs, about this lack of conscientious program design.

“It is more effective to think of telemedicine as a vehicle or tool, rather than the solution itself,” Dixon told me. “Shift the question from, ‘How am I going to prove telemedicine works?’ to, ‘Which KPI/metric do I think telemedicine can help me improve?’ Start by analyzing the problem, not the solution.”

Telemedicine analytics need to combine automated and virtual care, and the metrics for designing those programs should be goal-focused. For example, health systems can start by running their own reports to identify the shift in primary care at their organizations in the past decade — many have seen most “low-complexity urgent issues” shift away to urgent care — and consider whether a telehealth partner is the answer to competing in this area.

Throughout the telemedicine industry, the focus on improving analytics in order to serve healthcare is the priority. Quality metrics improvement and measurement consistency will improve telemedicine and overall patient outcomes.

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