We consider a shift in pain medicine delivery systems from the conventional, body-part-based approach to one anchored in intricate, real-world pain experience and holistic profiles of patient function. Utilizing the largest biomedical dataset to date (n = 34,337), we unearth four unique, biologically-based pain profiles that cut across medical specialties: pain interference, depression, medical pain, and anxiety, each representing different facets of functional impairment. Importantly, these profiles do not specifically align with variables believed to be important to the standard pain evaluation, namely painful body part, pain intensity, sex, or BMI. Correlations with individual-level clinical histories (137 medication categories, 1,425 clinician-assigned diagnostic codes, and 757 lifestyle and behavioral phenotypes) reveal that our pain profiles are largely associated with clinical variables and treatments of modifiable, chronic diseases, rather than with specific body parts. Across profiles, notable differences include opioids being associated only with the pain interference profile, while antidepressants linked to the three complimentary profiles. We further provide evidence that our pain profiles offer valuable, additional insights into patients' wellbeing that are not captured by the body-part framework, and make recommendations for how our pain profiles might sculpt the future design of healthcare delivery systems.