Conjoint analysis is a method used to elicit patient and community preferences for healthcare. It allows for the estimation of the relative importance of different aspects of care, the trade-offs between these aspects, and the total satisfaction or utility derived from healthcare services. This technique has been successfully applied in various areas of healthcare, including the delivery of health services, priority setting, outcome measures, treatment decisions, and evaluating alternatives in randomized controlled trials. It can also help in establishing patients' preferences in the doctor-patient relationship. The method involves identifying characteristics of healthcare services, assigning levels to these characteristics, creating scenarios, eliciting preferences through ranking, rating, or discrete choices, and analyzing the data using regression techniques. In the orthodontic study, conjoint analysis was used to determine the trade-offs individuals were willing to make between location of treatment and waiting time. The results showed that patients preferred local clinics over hospital clinics and were willing to wait extra time for local appointments. Despite its potential, there are methodological issues that need further consideration, such as the sensitivity of results to the method of setting discrete choices, handling inconsistent responders, and modeling the benefit function. The application of conjoint analysis in healthcare has shown promise, but further research is needed to address these issues. The NHS faces challenges in modernizing healthcare services, including the need for more flexible training and working practices, ensuring that doctors do not use time dealing with patients who could be treated safely by other healthcare staff. Professionals are ready to change and have already done so, and NHS organizations need to listen to their staff, who know where systems go wrong. More flexible working and training are long overdue, along with proper training for multidisciplinary working. Innovation needs to be encouraged, and entrepreneurial clinicians should be supported.Conjoint analysis is a method used to elicit patient and community preferences for healthcare. It allows for the estimation of the relative importance of different aspects of care, the trade-offs between these aspects, and the total satisfaction or utility derived from healthcare services. This technique has been successfully applied in various areas of healthcare, including the delivery of health services, priority setting, outcome measures, treatment decisions, and evaluating alternatives in randomized controlled trials. It can also help in establishing patients' preferences in the doctor-patient relationship. The method involves identifying characteristics of healthcare services, assigning levels to these characteristics, creating scenarios, eliciting preferences through ranking, rating, or discrete choices, and analyzing the data using regression techniques. In the orthodontic study, conjoint analysis was used to determine the trade-offs individuals were willing to make between location of treatment and waiting time. The results showed that patients preferred local clinics over hospital clinics and were willing to wait extra time for local appointments. Despite its potential, there are methodological issues that need further consideration, such as the sensitivity of results to the method of setting discrete choices, handling inconsistent responders, and modeling the benefit function. The application of conjoint analysis in healthcare has shown promise, but further research is needed to address these issues. The NHS faces challenges in modernizing healthcare services, including the need for more flexible training and working practices, ensuring that doctors do not use time dealing with patients who could be treated safely by other healthcare staff. Professionals are ready to change and have already done so, and NHS organizations need to listen to their staff, who know where systems go wrong. More flexible working and training are long overdue, along with proper training for multidisciplinary working. Innovation needs to be encouraged, and entrepreneurial clinicians should be supported.