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How health data can improve MSK-care member experience

Here’s how payers can harness the power of data to bring more effective — and timely — musculoskeletal (MSK) care to their members.

4-minute read

MSK ailments are all-too-common conditions that comprise some of the costliest sources of annual health care spend.1 Consider the following:

  • What if there was a way to catch MSK ailments early on in their progress to make a far greater impact in both patient outcome and payer value?
  • What if you could easily compare potential treatment paths for these complex conditions, or better spot big-picture trends in MSK treatment as they emerge?
  • What if there were a way to do all 3 of these things at once, using the exact same raw information for each of these vital endeavors?

Fortunately, there is a way to do all these things, resulting in better member experience and higher payer ROI. It all comes down to data. But we’re not talking about simply digging through a pile of numbers and haphazardly casting about for patterns. We’re advocating for a system of data analytics that synthesizes disparate health and social information and triggers real and impactful action.

Here’s what such a system might look like for payers willing to aim higher for their members.

Using data to address MSK issues early on

There are numerous signs of early MSK issues, such as stiff joints, poor sleep, muscle aches and pain that worsens with movement.2 These signs are a driving force behind everyday visits to one’s primary care provider or a specialist to which the patient has been referred. If treated promptly, these symptoms can head off far worse diagnoses down the line. They are often noted in patients’ records but rarely synthesized into a picture of an emerging ailment.

Capturing patient data across various providers’ charts, tests and labs at scale is only possible with sophisticated data analytics. These analytics can precisely predict and prioritize charts most likely to contain unreported MSK diagnosis codes.

For example, if a patient comes to their doctor complaining of low back pain, it may seem prudent and cost-saving to recommend a conservative course of action for the time being. This may include icing the area, performing certain stretches or seeing a physical therapist for a few weeks. And if data analysis suggests that this member fits a profile of patients who later go on to require back surgery, the right course of action may be to, for example, order an MRI right away or immediately begin anti-inflammatory injections.

The Optum® Specialist Management Solutions (SMS) program does exactly that. By using predictive algorithms to identify patients on a potential path to surgery for an MSK ailment, we can help guide them to the most fitting care. This may mean guiding them to high-value sites of care for the intended surgery or helping them find a more conservative approach to pain management.

Deploying data analytics removes much of the guesswork of treating emerging patients whose symptoms could just as easily indicate a condition likely to resolve on its own as one that will only improve with significant intervention. Best of all, this approach also makes it easier to identify these ailments early on, when treatment tends to yield better outcomes and higher savings, and to help ensure that members are referred to the highest-quality sites of care.

Using data to guide appropriate, evidence-based care

A more conservative care approach can help members avoid invasive procedures that may not have the desired effect. It can also help payers better manage health care costs even while delivering more appropriate treatment to members. Yet there are often instances in which a different treatment path is better suited to a member’s needs. A steady regimen of physical therapy may be less invasive or costly than surgery, but if it doesn’t result in the meaningful improvement of a member’s condition, it’s simply delaying the path to more effective care.

How can the most fitting approach be found? Health data and analytics can simplify such decisions via a close reading of previous outcomes. With utilization management programs, data can be used to identify an expected duration of care for patients pursuing a more conservative treatment path. This helps to signal when it’s time to move on to other methods if an improvement has not yet been observed. In addition, this data can also be used to ease the administrative burden on providers by identifying those who consistently pursue appropriate and high-value treatment, exempting them from the need for prior authorization.

Using data to ease friction in patient navigation

There may be no greater frustration for members than facing obstacles in getting the right treatment plan in place. This may include being referred to a specialist who turns out to be out of network or being asked to travel long distances to a medical center that specializes in their condition. Faced with such an obstacle-ridden path to treatment, many patients miss out on meaningfully improved outcomes.3

But data analytics can be used to fuel programs that locate members who need an accessible second opinion, such as via virtual appointments with expert physicians. The result for patients is less frustration and friction as they shift between their provider’s office to other care sites. And given the ubiquitous recommendations for multimodal treatment approaches in MSK conditions,4 this streamlining effect is likely to make a big impact.

When payers put patient data to work, they unlock a powerful ability to improve member experience, significantly ramp up health outcomes, and reach new heights in value in an area of medicine that has historically proven costly. And all it takes is making better use of what’s already there: the invaluable insights hiding within those thousands of electronic patient records waiting to be deployed on behalf of patients and payers alike.

Learn about Optum Musculoskeletal Solutions for Health Plans.


  1. Dieleman JL, Cao J, Chapin A, et al. US health care spending by payer and health condition, 1996-2016. JAMA. 2020; 323(9):863–884.
  2. Cleveland Clinic. Musculoskeletal pain. Accessed October 16, 2023.
  3. Mathematica. New studies reveal that fragmented care persists despite efforts to improve primary care and care delivery. Accessed October 16, 2023.
  4. El-Tallawy SN, Nalamasu R, Salem GI, et al. Management of musculoskeletal pain: an update with emphasis on chronic musculoskeletal pain. Pain and Therapy. 2021; 10:181–209