How employers can raise the standard of care for their employees

In health care, most research shows no clear correlation between price and quality. When it comes to perceptions, whether you believe expensive care is better is mostly a function of how generous your insurance coverage is. For example, a recent study in HBR found that those with rich or comprehensive coverage tend to believe expensive providers are better, while people with more cost exposure believe the opposite. This confusion drives up cost in some cases and makes patients’ health outcomes worse.

Today, too much variation exists in provider quality – which exacerbates this issue. For example, Morgan Health and Embold Health found wide variation in medication adherence and cesarean delivery (C-section) among providers within a geography, translating into variation in both health outcomes and cost.

Self-insured employers are well-positioned to drive change, as they determine which providers are included in their plan’s networks and decide how to share price and quality information with employees. According to a survey Morgan Health recently conducted of U.S. employers in partnership with the consultancy X4, many employers are starting to embrace a more comprehensive view of quality improvement among their employees.

However, what they often don’t know is how to assess data on the quality of individual physicians or of care facilities. This lack of visibility has compounded the country’s $935 billion health care waste problem, which ultimately leaves millions of families paying equivalent to the cost of a small car each year for their health care.

These findings underscore employers’ need for common standards to assess care quality, and an understanding of how quality drives appropriate additional spending versus cost savings.

The field of orthopedics has straightforward quality measures, and thus serves as a useful case study of how price and quality are inversely correlated. For both spine care and orthopedic joint care, costly surgeries are more likely to happen when seeing low-performing providers. In contrast, high-performing clinicians tend to be more conservative in recommending surgery and use physical therapy and other non-surgical interventions to achieve good functional outcomes for their patients.

As an example, hip or knee replacements are often unnecessary and should only be done after other less severe treatment options are performed. According to Embold’s analytics and dataset which represents more than 200 million covered lives and evaluates over 400K doctors nationwide, patients with insurance coverage who see low-performing providers are nearly 16 times more likely to have this procedure before completing conservative therapy for new arthritis, compared to if they had seen a high-performing one (28.2% vs 1.8%).

This is also the case with neck surgeries, where other less severe treatment options that don’t require surgery are often recommended or considered first. We see a common trend like other orthopedic surgeries: when members see low-performing providers, they are nearly 56 times more likely compared to high-performing providers to have a neck surgery before trying conservative therapy for a year (22.3% vs 0.4%).

These trends are also highly prevalent in non-surgical specialties as well. For example, when patients see a low-performing pulmonologist, they are nearly 5 times more likely to have an unnecessary breathing test, compared to if they had seen a low-performing provider (35.8% vs 7.4%). These tests add costs and redundancy to our health care system, and negatively impact employers’ benefit spend.

Related: This summer, rural health clinics get a boost from CMS to improve quality of care

These data only make a difference if people can see them and act upon them. Most health plan provider directories, which some members use for finding care sites, typically use black-box algorithms that incorporate some quality measures alongside cost measures. The health plans that manage these provider guides benefit from members choosing less expensive providers, so cost considerations tend to drive filtering more than quality.

The effort to make these data more transparent and actionable has a demonstrable impact on costs and outcomes, as well as on narrowing health literacy gaps – a trifecta of improvements that make consumers more confident in their health care choices and improve the efficiency of employer-sponsored health care.

It’s past time to make this shift. Employers and employees just need the right tools to do it.