What’s next in hospital digitization? A Delphi-based scenario study

IntroductionThe second iteration of the National Early Warning Score (NEWS2) has been widely adopted for predicting patient deterioration in healthcare settings using routinely collected physiological observations. The use of NEWS2 has been shown to reduce in-hospital mortality, but it has limited accuracy in the prediction of clinically important outcomes, especially over longer time periods. The increasing implementation of digital patient observations and health records presents an opportunity to investigate whether the addition of individual patient characteristics and information about their care-setting, would improve the predictive accuracy of the score.Methods and analysisThis protocol describes the work to determine whether the performance of the current NEWS2 system could be improved by the use of additional variables. The project has been designed after an extensive scoping review of existing literature on NEWS2 and an exploration of retrospective cohort data in The Newcastle upon Tyne Hospitals NHS Foundation Trust, with input from key clinical stakeholders.Ethics and disseminationThe project has received competitive funding following peer-review, from the NIHR Newcastle Biomedical Research Centre as an Interdisciplinary Research Award. Ethical approval has been requested. Findings are expected to be produced by June 2025, and will be disseminated at symposia, conferences and in journal publications.Strengths and limitations of this studyStrengths-This work highlights the importance of investigating the use of additional clinical variables to those used in NEWS2, in the development of a new early warning score-The study design was informed by an evidence synthesis of the literatureLimitations-Some retrospective data sets may be of low quality and/or incomplete-External validation will be needed to test algorithm generalisability

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Forecasting the future of smart hospitals: findings from a real-time delphi study

Jovy-Klein,

Stead,

Salge

et al. 2024

BMC Health Serv Res

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Background In concert with other digital technologies, artificial intelligence (AI) is shaping the vision of smart hospitals. The transformation into smart hospitals, however, is all but trivial due to the lack of financial and human resources, digital skills, and supporting policies. Thus, the extent to which the vision of smart hospitals will eventually become reality is uncertain. In this context, our study provides a multidimensional conceptualization of the immediate future of smart hospitals to 2042. Methods This study employs an iterative mixed-methods approach, including expert workshops and a Delphi study. We conducted a real-time Delphi study to forecast the evolution of smart hospitals in 5-year steps from 2027 to 2042. A total of 39 experts in healthcare, artificial intelligence, and management participated. Results Our understanding of a technology-enabled smart hospital in this study includes four dimensions: artificial intelligence (AI), sustainability, ecosystems, and human-centeredness. Our findings underscore the critical need to address the shortage of hospital staff and general practitioners that models predict will peak by 2032. Additionally, our results show a significant shift to individualized medicine and home care. This shift indicates that smart hospitals are expected to leverage AI and digital technologies to tailor care to each patient. Furthermore, the roles and responsibilities of hospital staff will undergo significant changes. Healthcare personnel will have to adapt to new technologies that facilitate more efficient workflows and improve patient engagement in evolving healthcare environments. The results of our study suggest a shift in care to individualized medicine and home care, with corresponding changes in the roles and responsibilities of hospital staff who will employ new technologies. Conclusions The findings from our real-time Delphi study suggest that the vision of smart hospitals is gradually becoming reality over the next 20 years. Advancements in artificial intelligence should enhance operational efficiency and patient-centric care, while facilitating the integration of sustainability practices and fostering collaborative ecosystems. However, addressing challenges such as staff shortages, ethical considerations, and the need for robust digital skills will be essential. A deep pool of expert healthcare practitioners, clear ethical guidelines, and robust digital skills are essential to fully realize this vision and ensure that smart hospitals can meet the evolving needs of healthcare delivery.

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What’s next in hospital digitization? A Delphi-based scenario study

Cited by 3 publications

References 105 publications

How digital technologies and AI contribute to achieving the health-related SDGs

How digital technologies and AI contribute to achieving the health-related SDGs

Algorithm Refinement of the National Early Warning Score 2 (NEWS2): Study Protocol

Forecasting the future of smart hospitals: findings from a real-time delphi study

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