COAs have been used in medicine for decades, but they have only recently been getting attention from researchers and policymakers. COAs are assessments of patient outcomes that can be directly linked to healthcare providers and their treatment. For example, one common COA is a measurement of cholesterol levels before and after starting a drug treatment regimen. The idea behind these measures is that they can provide real-world evidence about how well treatments work outside of clinical trials.
COAs provide real-world evidence
COAs provide real-world evidence. Self-reported data are notoriously unreliable and may be biased by the patient’s illness, willingness to report symptoms, or even the presence of a caregiver who is helping the patient fill out the forms. COAs are instead collected from patients using standardized tools and validated by clinicians who have been trained in their use.
They also avoid any potential for bias since they’re based on objective clinical outcomes that users like self-reported data can’t manipulate often. For example, according to clinical trial expert Medable, its eCOA software says, “Up level Clinical Outcome Assessments and arm your studies with real-time data.”
COA measures can map to PROs
Clinical Outcome Assessments (COAs) can measure patient-reported outcomes (PROs). PROs are patient-reported assessments of health status, such as physical functioning, pain, and quality of life. In contrast to traditional measures that focus on disease severity or the degree of dysfunction related to a condition, PROs assess how conditions affect patients’ ability to perform daily tasks or maintain their quality of life.
COA measures can be valuable to patients and providers
Of course, no one is perfect. You all make mistakes, and even the best of you can miss important details. That’s why clinical outcome assessments (COAs), which measure what actually happens in real-world situations, provide a more realistic view of health care than patient-reported outcomes (PROs).
For example: Imagine you go to the doctor for treatment for your diabetes, and he tells you that his PROs show that he has been doing an excellent job managing your condition—even though it hasn’t improved at all! In short, he’s lying through his teeth—his data is inaccurate because he didn’t count things like how many times you passed out or needed emergency care due to complications from diabetes (which aren’t easy things to measure).
A COA would give a much better idea of how well this doctor was doing compared with other doctors who have similar patients but take time out of their day to collect accurate data on their patients’ experiences rather than just relying on the word of their patients themselves.
COA measures are useful in healthcare policy discussions
COAs are useful in healthcare policy discussions because they can be used to measure the impact of care delivery and policy changes. The same is true for new technologies. For example, COA results can help you see if your program is helping patients or if it’s making things worse.
COAs are an important part of evidence-based care, and they can be an important tool for healthcare policy discussions. They provide real-world evidence that can be used to improve the quality of care and outcomes for patients.