All Articles Healthcare Providers Specialty care models must lead in managing complex patients

Specialty care models must lead in managing complex patients

Specialty care teams supported by technology can offer continuous, individualized care plans that improve patient outcomes and reduce health care costs.

4 min read

HealthcareProviders

Jigsaw with few pieces to fit, on green background.

Getty Images

According to research by the CDC, more than half of US adults — and a staggering 79% of older Americans — live with multiple chronic conditions.

Although this patient group accounts for a disproportionate share of health care utilization and costs, including an estimated 64% of all clinician visits and 93% of Medicare spending, they routinely experience worse health and lower quality of life.

The root of this disconnect is structural. Over three-quarters of primary care physicians are now employed by health systems or other corporate entities. Despite expectations that this shift will yield stronger care infrastructure and world-class instruments, the model frequently falls short for those managing interrelated conditions.

Even the best generalist care, by nature, is organized around time-constrained, episodic visits that struggle to work in concert. Treating multiple chronic conditions hinges on true whole-person care, driven by real-time support across the various clinical, social and logistical conditions that affect a person’s health.

To actually improve outcomes for patients with multiple chronic conditions while also controlling costs, specialty care models must move to the forefront — not as a referral, but as the true conductor of coordinated care journeys.

Why generalist care can fail complex patients

Consider a patient with kidney disease who separately sees a primary care physician, a cardiologist, an endocrinologist and a nephrologist. Each provider may act appropriately within their specialty, but risks compound quickly without oversight into how these decisions interact.

For instance, prescribing a hypertension medication that inadvertently harms kidney function can accelerate disease progression. This type of error is often overlooked without a comprehensive medication reconciliation.

When that same patient receives support from a specialty care team, however, disease management extends holistically. For example, if the patient has complex diabetes management concerns, the care team will coordinate endocrinology appointments and incorporate those insights into the broader kidney care plan.

The same logic can apply to individuals living with diabetes. Considering 1 in 3 adults with diabetes may also live with chronic kidney disease, specialty care for patients with diabetes should include ongoing coordination with a nephrologist to monitor kidney function, or an optometrist for diabetic retinopathy.

It’s the active management of one chronic condition that empowers improved outcomes across the patient’s broader health profile.

Continuing to route complex patients through generalist structures not designed to handle the logistical demands of managing multiple chronic conditions will only amplify costly downstream consequences, from avoidable disease progression to preventable hospitalizations.

How technology will define the future of specialty care

A defining strength of specialty care models is their ability to use technology to easily extend care beyond a single visit.

Machine-learning solutions already play a key role in coordinating treatment. With support from predictive analytics rooted in disease-specific indicators, specialty care teams can design individualized care plans and deploy targeted interventions continuously over time.

Critically, these timely, actionable clinical insights need to be shared directly with the patient’s primary care provider to ensure all clinicians are aligned on the most current understanding of the patient. If a specialty care team is the orchestra conductor, technology creates the score that allows the entire symphony of providers to play in time and in harmony. For patients, this coordination translates into more proactive care decisions as clinicians surface, share and act on status changes before they escalate into acute events.

Looking ahead, AI and machine learning offer additional opportunities to engage patients between visits. The use of AI to generate prompts around appointments, diet or medication adherence can offer timely guidance to encourage action at key moments and support follow-through on treatment plans.

This might involve texting a patient with kidney disease that their blood pressure medication is ready for pickup and offering help with transportation, or reminding a patient with diabetes to schedule an appointment to complete required bloodwork before an upcoming checkup.

Coordinated care must become America’s new standard

Improving outcomes for patients with multiple chronic conditions requires more than the status quo. To better support Americans and reverse the unsustainable rise in US health care spending, we need a structural shift that moves beyond siloed, fragmented care.

It’s time to let specialty care step forward to conduct — so every provider plays their part, and every patient gets the treatment they deserve.

Opinions expressed by SmartBrief contributors are their own.

_______________

Subscribe to SmartBrief for Health Care Leaders, one of our more than 30 health care publications.