Carlos Bezos Daleske

Patient experience is no longer a "soft" metric. When measured rigorously, it becomes a crucial source of information for redesigning healthcare processes. This is accomplished through two key types of patient-reported data: PREMs and PROMs. PREMs (Patient-Reported Experience Measures): These collect data on a patient's experience with the healthcare system, focusing on areas like accessibility, care coordination, treatment understanding, and patient participation. Unlike traditional satisfaction surveys, PREMs provide comparable data that helps pinpoint specific bottlenecks, errors, or inefficiencies within a process. PROMs (Patient-Reported Outcome Measures): These collect clinical results directly from the patient's perspective. They measure things like symptom severity, physical function, and quality of life. The NHS in England has demonstrated that integrating both PREMs and PROMs into process redesign improves patient adherence to treatment, reduces costs, and optimizes clinical outcomes. The Power of Data Integration By combining PREMs, PROMs, clinical data, and sociodemographic information with Artificial Intelligence (AI), we can create powerful tools for managing healthcare, improving quality, and controlling costs. This comprehensive approach transforms subjective patient feedback into actionable insights, driving significant improvements across the entire healthcare system.