Digital transformation represents an organisational re-wiring to create value for the organisation and its consumers via innovative business models.

All EMR solutions will continue to be shaped by technological innovation and changing healthcare demands. A solution’s long-term success will depend on quickly and cost-effectively supporting new value opportunities presented by advances in technology, science, and service delivery models.
AI and Machine Learning (ML), for example, present realistic and affordable options to enhance the quality and outcomes of care interventions. In fact, it is hard to imagine an enterprise-scale EMR solution without AI capabilities in two years’ time.
Generative AI solutions already help care professionals consolidate, synthesise, and summarise patient record data to improve the efficiency and precision of care planning and interventions. ML examples include predictive analysis, such as identifying patients at a higher risk of readmission, developing conditions, or unexpected deterioration.
Integrating interoperability standards, such as Fast Healthcare Interoperability Resources (FHIR), will also become crucial. These facilitate the sharing of structured, coded, and actionable patient information across health and social care services. This is particularly important in enhancing the efficiency and effectiveness of care transitions and collaborative decision-making across large geographies or populations.
Enterprise EMR solutions will also evolve to provide genomic capabilities relating to test orders and results and, importantly, pharmacogenomic decision support to guide and inform the correct and appropriate use of medications for each individual. This understanding, combined with EMR technology, has the potential to transform care outcomes on a scale similar to the introduction of antibiotics.
The term ‘digital transformation’ is hard to escape. But what does this mean for healthcare services adopting an EMR solution?
