Musculoskeletal (MSK) pain has overtaken mental health issues as the number one reason why people take time off work in United States. MSK conditions are the leading contributor to disability, with low back pain being the single leading cause. The problem is quite widespread. About 1 in 3 Adults in US experience MSK pain, with 170 million annual visits just for low back pain. It is estimated that 1/3rd of visits to primary care physician (PCP) offices are due to MSK conditions.

Where you start in the episode of care affects your outcome. The care strategy each member receives for any MSK condition is predicated upon which door they walk into.

In our fragmented system of care, it is all over the place. Orthopedic surgeons often believe they can fix the problem on an operating room table. Physical therapists believe they can fix it with their hands. Most recently available data suggests 37% visits for MSK issues are made to primary care offices, compared with 31% to surgical specialists and 16.5% to medical specialists.

The current care delivery system is not designed to provide the ‘right’ treatment quickly to people with MSK pain. People are also not provided the tools to take good decisions about who they should see ‘first’ for their condition between PCP (primary care physician), physical therapist, occupational therapist, a podiatrist, a chiropractor, Physiatrist or a pain medicine.

It is true that early identification of MSK pain and improved managed of those at risk of severe disabling can save severe discomfort for members and significant downstream costs for employers and health plans. It is also important to make sure that people in all risk categories are triaged faster to the right treatment pathways.

Prognostic stratified care model can deliver on this promise for a broader range of common MSK pain presentations.

PROGNOSTIC STRATIFIED MODEL OF CARE

Traditionally, patients have 1-2 visits with a PCP or specialist, possibly have x-rays or other imaging, and/or receive prescriptions for medications.  Very often, after this is done for majority of MSK conditions, the patient is then referred to PT. This passive and misguided approach adds unnecessary delay, cause de-conditioning and is counter-productive to recovery.

In contrast, prognostic stratified model of care starts with a digital assistant that presents smart questions presented to members electronically, when they first experience the pain. The questions screen for multiple things including – symptoms, red flags and prognostic factors for risk categorization.

For sinister problems such as Cauda Equina, Metastatic Cancer ‘Red Flags’ etc, the system catches serious warning signs from the point of contact, reducing the timeline between someone deciding they need help and the time they receive clinical advice. To reduce complexity, the prognostic factors associated with outcome of an episode of pain can be generic in nature regardless of the location of pain. Research suggests that patients with different MSK pain presentations (eg, back, neck, knee, shoulder, or multisite pain) share common prognostic factors.

The outcome of this process is a) risk categorization and b) suggestions for next step, an evidence-based care in-app or in-person based on risk category and c) clear explanation of costs for different treatment options.

The risk categorization is based on the member’s risk of a poor outcome (low, medium, high). The system aims to ensure that members with common musculoskeletal conditions receive the right treatments at the earliest opportunity. Aligning interventions to risk category reduces treatment variability and improves adherence to best practice. The typical treatment options for members at low risk include advice and education and avoidance of MSK investigations such as imaging and specialist referrals (where possible). The typical treatment options for members at medium risk, in addition to the low-risk options, include physical therapy (virtual or in-person) and consider investigations where necessary. Physical therapy is a productive and cost-effective means of treating most musculoskeletal pain, and if used as a treatment option prior to visiting a primary care physician or a specialist, can help patients avoid X-rays, MRIs, opioids and surgery – saving them both time and money in the long run.

The typical treatment options for members at high risk, in addition to the medium- and low-risk options, includes referral to specialist services (eg, orthopedics, rheumatology, and pain clinics); imaging; and/or behavioral health support.

It is important to know that this model allows for a clinician to intervene and override – vary from the defined protocol as necessary. The primary patient-reported clinical outcome is pain intensity, measured regularly over the course of treatment, as well as 3-6 months after treatment.

In addition, secondary clinical outcomes specific to body-site (for example KOOS for knee pain, SPADI for shoulder pain) are measured.

The variance and outcomes are fed back to the model for continuous improvement.

In short, the prognostic stratified model of care for musculoskeletal conditions uses machine learning and clinical expertise to identify red flags, and segment individuals into low-, medium-, and high-risk subgroups, and match these subgroups to recommended clinical management options. This approach reduces time to care, empower your people to make better care decisions and is cost-effective compared to usual fragmented model of care experienced by them.

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