In the age of the electronic health record (EHR), there has been a shift in focus toward patient-centric reporting of pathology and radiology results. Radiology reports, in particular, are the most frequently accessed by patients who are commonly met with medical language and abbreviations which limit comprehension. Creating reports which can be effectively communicated to the patient is pivotal in developing a patient-centric model of healthcare to empower an individual’s participation on their health journey. This narrative review explores the evolution and impact of patient-centred radiology reporting, especially in the context of prostate cancer.

A search of the literature was conducted on 24th June 2024 using Embase, Medline and Pubmed. Only original articles pertaining to the utility and creation of patient-centred medical reports were considered, resulting in a review of 32 articles.

Studies reveal that while patients desire timely access to their reports via unfettered access to EHRs, they often struggle with medical terminology and complex report formats. This can hinder their understanding and increase anxiety, highlighting the need for patient-centred reports that are both comprehensible and informative. Research indicates that patient-centred reporting can enhance patient knowledge and engagement. For instance, patient-centred pathology reports for bladder cancer and prostate cancer have shown improvements in patient understanding and recall of disease characteristics. Prototypes of patient-centered radiology reports for prostate cancer, developed with input from patients and specialists, aim to simplify information and improve patient decision-making. Despite these advancements, challenges remain in making reports accessible to diverse patient populations, addressing varying preferences for information detail, and overcoming the complexities of medical vocabulary. Artificial intelligence (AI) presents a promising solution to these challenges by assisting in the creation of structured and simplified reports. AI tools, such as language models and computer-assisted reporting systems, have demonstrated promise in generating clear and accurate patient-centred reports, potentially easing the burden on radiologists and enhancing patient understanding.

The transition to patient-centred radiology reporting, particularly for prostate cancer, represents a critical step towards a more transparent and empowering healthcare model. Leveraging AI to assist in report generation and ensuring that reports are tailored to patient needs can significantly improve communication, understanding, and overall patient satisfaction. Further investigation into the impact of these approaches on patient outcomes and engagement is essential to advancing patient-centric healthcare.