{"id":21104,"date":"2025-02-19T14:28:39","date_gmt":"2025-02-19T20:28:39","guid":{"rendered":"https:\/\/www.bbrown.com\/?post_type=insight&p=12462"},"modified":"2025-04-09T22:31:12","modified_gmt":"2025-04-10T03:31:12","slug":"when-will-innovation-lead-to-progress-2","status":"publish","type":"insight","link":"https:\/\/www.bbrown.com\/us\/insight\/when-will-innovation-lead-to-progress-2\/","title":{"rendered":"When Will Innovation Lead to Progress? | A Data-Driven Approach to Performance Measurement of Health-Focused Point Solutions"},"content":{"rendered":"

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Employee Benefits<\/p>\n

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\n When Will Innovation Lead to Progress? | A Data-Driven Approach to Performance Measurement of Health-Focused Point Solutions\n <\/h1>\n\t\n <\/div>[vc_column_text css=””]More than 125 companies market diabetes management programs to employers, and more than 75 additional companies offer musculoskeletal programs.1 <\/sup>While value statements vary, these and other point solution vendors claim they can achieve savings in medical, pharmacy and disability claims and improve clinical outcomes. They provide case studies, white papers and published research papers. Some vendors have also commissioned third parties to review their methods for calculating savings.<\/p>\n

How can an employer objectively validate these claims? Unfortunately, independent researchers have yet to publish the results of randomized trials, while organizations like The Peterson Health Technology Institute have published studies questioning the benefits of many of these programs.2<\/sup><\/p>\n

Asking The Right Questions<\/h3>\n

In the meantime, employers need to use their own data to see if the \u201cinnovative\u201d programs marketed by these vendors have resulted in progress. Among the questions employers should ask:<\/p>\n

Is the solution reaching the target population?<\/h4>\n

For example, say an employer offers a diabetes management vendor program. What percentage of members with Type 2 diabetes engage with it? Are prediabetics slowing their progression to a diagnosis of diabetes? Are there subgroups of employees that are not engaging with the solution? If so, are differences in engagement rates based on social determinants of health, job site, union status, salary band, etc.? Answers suggest opportunities for different communication strategies.<\/p>\n

What are the characteristics of members engaging with the program?<\/h4>\n

A Brown & Brown custom analysis found that 97% of people engaging with one employer\u2019s virtual Musculoskeletal (MSK) program had not used traditional physical therapy in the year prior, and only 60% faced a claim with an MSK diagnosis. In other words, the virtual MSK program was attracting a new group of people who had yet to incur significant MSK costs. Perhaps the virtual MSK program will avoid future costs, but there was no reduction in MSK or physical therapy claims in the near term.<\/p>\n

Is there evidence that the use of the program is growing?<\/h4>\n

How many new members engage with the program over time? Ideally, there will be a \u201cwater cooler effect,\u201d meaning that employees who use a program will pass their positive impressions to their colleagues. If a program enrolls spouses and dependents, is growth observed in those sections of the population?<\/p>\n

Do we see a reduction in medical and pharmacy claims for the enrolled population that can be attributed to the program?<\/h4>\n

Too often, vendors will attempt to calculate savings based on avoided utilization and expense, using projected direct cost avoidance calculations. Here is a typical scenario: an MSK solution implemented by an employer last year may result in fewer knee replacement surgeries in the future. It will then take several years of data for employers to verify and compare projected versus actual savings (if any), particularly given employee turnover.<\/p>\n

A proper claims analysis typically requires a data warehouse where medical and pharmacy claims can be linked to program participant data at the member level, providing a holistic view of care. With this integrated data, employers can see differences in utilization rates and costs between cohorts, e.g., those that use the program and those with similar demographics or health profiles that do not. Risk adjusting between the participant and non-participant populations will enable a more complete analysis. Alternatively, employers can look at utilization and costs before and after program introduction.<\/p>\n

Getting Some Answers<\/h3>\n

Employers should not be fooled or dazzled by vendors\u2019 claims about the effectiveness or return of these programs. Instead, they should develop a data-driven approach to measure performance on objective terms:<\/p>\n