How your revenue Cycle Management effects Patient Payment and surprise billing

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How a practice’s revenue cycle management can impact patient payments and the likelihood of surprise billing situations.
Chris Hutson, product line director at Availity, discusses how a practice’s revenue cycle management can affect patient payments and the probability of surprise billing scenarios.
Hyper-personalized digital interventions improve outcomes

Such are the results of a clinical study published in the Journal of Medical Internet Research (JMIR) Diabetes. This retrospective cohort study examined data from 998 people with Type 2 diabetes who used a digital health platform.

Key findings of the research include:
- statistical support for the idea that promoting sustained behavior change can significantly improve patient outcomes;
- evidence highlighting the need for a hyper-personalized approach to digital health.
Study findings
The study examined the effect of digital engagement on monthly average blood glucose levels during a patient’s first year of managing diabetes on a digital platform.

- engaged users, defined as those who rarely or never used additional features of the digital health application but who measured their blood glucose;
- highly engaged users, defined as those who consistently used the application to tag and track mealtimes, food intake, exercise, mood, and location alongside their blood glucose readings.
Researchers found that highly engaged users showed statistically significant improvements during the initial period (13 %) compared with engaged users (9 %).

Key takeaways for physicians
What insights should providers take from these findings?
First, the research offers encouragement for providers under pressure to improve outcomes. Clinicians can advise patients daily on healthy habits, yet what happens once patients leave the exam room?

The JMIR study suggests that providers can better support patients beyond the office visit by offering access to digital tools that promote continuous self-management, thereby fostering healthier behaviors and improved outcomes.
However, simply providing an app is not enough. According to the JMIR research, achieving sustained behavior change requires understanding how people change, what triggers those changes, and what helps those changes persist.

Healthcare often relies on demographically derived personas, grouping people by region, age, sex, or other variables to deliver “personalized” content. While this is a useful starting point, truly supporting behavior change demands deeper recognition of each person’s unique shifts and growth.

The promise of hyper-personalized interventions

The study indicates that digital solutions accounting for intrapersonal change can drive sustained behavior modification that meaningfully improves health outcomes. Many people with chronic conditions already feel overwhelmed, and many physicians feel overburdened. Digital health tools can ease some of these pressures for both parties and help achieve better results.
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