CCD Health

How to Improve Patient Outcomes with Machine Learning [report inside]

Download CCD Health’s report on how machine learning can improve your patient outcomes, including better patient care and decreasing your overhead costs.


In 2021, there were reportedly close to 11,000 outpatient medical centers in the United States. Whether large multi-state systems or individual, independent clinics all face the same two challenges: decreasing overhead costs and improving Patient Care.

How imaging centers handle patient interactions can affect both goals. Patient Care means more than just being polite to your patients or providing service with a (virtual) smile. It is about delivering the utmost Patient Experience, from the first interaction through their treatment to post-visit follow-ups. Still, as an outpatient imaging center, you must protect your revenue generation engine—your Patient Care.

Medical companies lose billions of dollars each year due to missed appointments. In fact, one 2017 study found that no-shows cost the U.S. healthcare system more than $150 billion a year, and individual physicians an average of $200 for every 60-minute appointment. Year after year, that stacks up to an unimaginable amount of lost revenue.

Throughout our research, the CCD Business Intelligence Department was concerned with three aspects of patient no-shows in medical centers: identifying the leading causes of patient no-shows, pinpointing the most at-risk patients and time slots for missed appointments, and developing an action plan that can diminish no-show rates among patients.

We have compiled our findings into a report to shed light on the impact of patient no-shows. By downloading the report, you’ll learn about:

  • COVID-19’s impact on imaging center scheduling
  • The cost of patient no-shows across medical centers
  • Leading indicators of missed appointments
  • Best practices to lower no-show rates at imaging centers
  • Next steps for your patient care

Download your report: How to Improve Patient Outcomes with Machine Learning

In this whitepaper, you’ll learn:

  • How to leverage Machine Learning to minimize the impact of patient no-shows on Business outcomes and Patient Care.
  • Best practices to lower no-show rates at imaging centers.

To get a sneak peek of the report, keep reading.

Modern-day outpatient imaging operations

Your scheduling process can significantly impact if, when, and how patients show up to your facilities. And in the age of COVID-19, every interaction’s impact is amplified. Medical centers saw a significant drop in scheduling throughout 2020, uniquely impacting each imaging modality service.

Some imaging modalities, such as chest X-rays and CT scans, are commonly used for diagnosing and managing COVID-19 patients. Still, modalities like mammography have seen significant drops in scheduling and patient volumes since the beginning of COVID-19.

Now more than ever, business efficiency and patient satisfaction are crucial elements of your operations and long-term continuity. Even when 100% of your patients attend their scheduled appointments, your outpatient imaging organization must ensure that you’re fully utilizing your equipment and employees.

Inefficient use of healthcare facilities and resources can severely impact your profitability and business outcomes due to improper scheduling, especially given the high patient no-show rates pervasive in the radiology industry.

At CCD, our patient scheduling expertise within outpatient imaging has allowed us to explore and identify solutions to optimize the patient scheduling process and minimize patient no-

shows. To do this, the Business Intelligence department leveraged machine learning techniques to ensure that you can maximize revenue without sacrificing your Patient Experience.

The impact of patient no-shows

There’s no doubt that our lives grow more hectic and busy with each passing week.

While managing personal and professional responsibilities, meetings, reservations, and appointments are often missed or forgotten. Your patients’ lives are complex and unique, yet this impact is costly and wasteful for outpatient imaging centers across the healthcare industry.

In healthcare, patient no-shows and missed medical appointments without prior notice are prevalent. As Patient Care and medical centers’ efficiency increases, it’s essential to understand

the explicit and implicit impact of missed patient appointments. When a patient misses a medical appointment, three core elements of a medical center are impacted:

  • Revenue is left uncaptured
  • Resources and staff are left underutilized and idle
  • Patients receive delayed care

Yet as machine learning, analytics and technology continue to develop, it’s hard

to believe that such an expensive problem persists. Because of this, the team at CCD developed and deployed a three-stage research plan to identify and prevent patient no-shows for healthcare providers and outpatient imaging centers.

Improving patient experiences with CCD Health

We hope you find the report helpful as you work to improve both patient experiences and your business operations. If you have any further questions, please reach out to CCD Health.

As a leading healthcare contact center for outpatient healthcare providers, we offer exceptional patient and customer experience. Our team of over 1,000 patient care specialists works as an extension of your practice, taking tasks off your staff’s plate and assisting patients where needed.

Download your report: How to Improve Patient Outcomes with Machine Learning

In this whitepaper, you’ll learn:

  • How to leverage Machine Learning to minimize the impact of patient no-shows on Business outcomes and Patient Care.
  • Best practices to lower no-show rates at imaging centers.

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