Using Data to Fix Your “No-Show” Problem

May 15, 2023

In today’s technology-driven world, the way that healthcare is managed and delivered is evolving at a rapid pace. There is more and more data being created every minute. But without a solid plan and a means of collecting and understanding all this data, hospitals and clinics can fall behind larger health systems. It isn’t a question of whether it is necessary to grow and change. The question is how quickly an organization can understand all the moving pieces and make effective decisions based on data. In this whitepaper, we will be discussing two applications of data analytics in healthcare systems and how they can drive gains in efficiency for organizations and better outcomes for patients.


The first application has to do with scheduling of patients and providers. This may seem like a mundane and straightforward topic, but we rarely find that to be the case in the real world. How do you know if your providers and support staff are operating at full capacity? While there is no perfect algorithm that can account for every possible variable, developing a model for an ideal system provides essential clarity and a valuable measuring tool. Depending on the organization, a provider’s capacity may be measured in daily number of patients, operations, daily patient-hours, etc. The ideal number may be different for each location, department, or even each specific provider. Once this goal is established, you can use the data that is already being collected to monitor the expectations vs. actual results. Using data analytics, progress can be calculated and communicated efficiently and objectively.


The second application builds off what we have just discussed in the previous paragraph. One of the biggest burdens on any healthcare provider is the impact of “no-shows”. When a patient does not come to a scheduled appointment, the provider and facility are incurring the same costs as they would if the patient was present. But there is no billable activity generated to offset these expenses. It is estimated that “no-shows” generate a $150B annual cost to the healthcare industry. This assessment is obviously coming from the financial perspective of the organization. Let’s not forget the consequences for the patient.


According to the American Hospital Association, approximately 45% of Americans are living with one or more chronic health conditions. Regular and proper care is vital to maximize quality of life for these patients. Missed appointments can result in additional complications and incomplete information for providers. Around 2.5% of the population drives almost 25% of all healthcare costs worldwide. This high-risk cohort represents the top priority for any health organization. Using data and aggregated patient information, it’s possible to determine which appointments represent a high risk of “no-show”. Once these are identified, decision-makers can determine appropriate interventions and alternative ways to improve the chances of positive outcomes for both the organization and the patient.


The healthcare industry is a complex system that is constantly changing. “Going with your gut” as an executive or administrator will only get you so far. Strategic analysis of existing information will yield valuable insight and a deeper understanding of any organization. Without knowing your numbers, it’s nearly impossible to improve them. The purpose of this whitepaper is to provide ideas that can spark change in any organization. If the data exists, then it should be used to improve operational efficiency and drive better patient outcomes.