Health economic evaluations potentially provide valuable information to clinicians, health care administrators, and policy makers regarding the financial implications of decisions about the care of patients. The highest quality research should be used to inform decisions that have direct impact on the access to care and the outcome of treatment. However, economic analyses are often complex and use research methods which are relatively unfamiliar to clinicians. Furthermore, health economic data have substantial national, regional, and institutional variability, which can limit the external validity of the results of a study. Therefore, minimum guidelines that aim to standardise the quality and transparency of reporting health economic research have been developed, and instruments are available to assist in the assessment of its quality and the interpretation of results. The purpose of this editorial is to discuss the principal types of health economic studies, to review the most common instruments for judging the quality of these studies and to describe current reporting guidelines. Recommendations for the submission of these types of studies to The Bone & Joint Journal are provided. Cite this article: Bone Joint J 2016;98-B:147–51

The OpenAI chatbot ChatGPT is an artificial intelligence (AI) application that uses state-of-the-art language processing AI. It can perform a vast number of tasks, from writing poetry and explaining complex quantum mechanics, to translating language and writing research articles with a human-like understanding and legitimacy. Since its initial release to the public in November 2022, ChatGPT has garnered considerable attention due to its ability to mimic the patterns of human language, and it has attracted billion-dollar investments from Microsoft and PricewaterhouseCoopers. The scope of ChatGPT and other large language models appears infinite, but there are several important limitations. This editorial provides an introduction to the basic functionality of ChatGPT and other large language models, their current applications and limitations, and the associated implications for clinical practice and research.

Cite this article: Bone Joint J 2023;105-B(6):587–589.

Research into COVID-19 has been rapid in response to the dynamic global situation, which has resulted in heterogeneity of methodology and the communication of information. Adherence to reporting standards would improve the quality of evidence presented in future studies, and may ensure that findings could be interpreted in the context of the wider literature. The COVID-19 pandemic remains a dynamic situation, requiring continued assessment of the disease incidence and monitoring for the emergence of viral variants and their transmissibility, virulence, and susceptibility to vaccine-induced immunity. More work is needed to assess the long-term impact of COVID-19 infection on patients who sustain a hip fracture. The International Multicentre Project Auditing COVID-19 in Trauma & Orthopaedics (IMPACT) formed the largest multicentre collaborative audit conducted in orthopaedics in order to provide an emergency response to a global pandemic, but this was in the context of many vital established audit services being disrupted at an early stage, and it is crucial that these resources are protected during future health crises. Rapid data-sharing between regions should be developed, with wider adoption of the revised 2022 Fragility Fracture Network Minimum Common Data Set for Hip Fracture Audit, and a pragmatic approach to information governance processes in order to facilitate cooperation and meta-audit. This editorial aims to: 1) identify issues related to COVID-19 that require further research; 2) suggest reporting standards for studies of COVID-19 and other communicable diseases; 3) consider the requirement of new risk scores for hip fracture patients; and 4) present the lessons learned from IMPACT in order to inform future collaborative studies.

Cite this article: Bone Joint Res 2022;11(6):342–345.