Cancer tracking system improves timeliness of liver cancer care at a Veterans Hospital: A comparison of cohorts before and after implementation of an automated care coordination tool

Deploying a national clinical text processing infrastructure

OBJECTIVES

Clinical text processing offers a promising avenue for improving multiple aspects of healthcare, though operational deployment remains a substantial challenge. This case report details the implementation of a national clinical text processing infrastructure within the Department of Veterans Affairs (VA).

METHODS

Two foundational use cases, cancer case management and suicide and overdose prevention, illustrate how text processing can be practically implemented at scale for diverse clinical applications using shared services.

RESULTS

Insights from these use cases underline both commonalities and differences, providing a replicable model for future text processing applications.

CONCLUSIONS

This project enables more efficient initiation, testing, and future deployment of text processing models, streamlining the integration of these use cases into healthcare operations. This project implementation is in a large integrated health delivery system in the United States, but we expect the lessons learned to be relevant to any health system, including smaller local and regional health systems in the United States.

The future of hepatology

The field of hepatology has made impressive progress over its ~75 years of existence. Advances in understanding liver function and its dysregulation in disease, genetic determinants of disease, antiviral therapy, and transplantation have transformed the lives of patients. However, there are still significant challenges that require ongoing creativity and discipline, particularly with the emergence of fatty liver diseases, as well as managing autoimmune disease, cancer, and liver disease in children. Diagnostic advances are urgently needed to accelerate risk stratification and efficient testing of new agents with greater precision in enriched populations. Integrated, holistic care models should be extended beyond liver cancer to diseases like NAFLD with systemic manifestations or extrahepatic comorbidities such as cardiovascular disease, diabetes, addiction, and depressive disorders. To meet the growing burden of asymptomatic liver disease, the workforce will need to be expanded by incorporating more advanced practice providers and educating other specialists. The training of future hepatologists will benefit from incorporating emerging skills in data management, artificial intelligence, and precision medicine. Continued investment in basic and translational science is crucial for further progress. The challenges ahead are significant, but with collective effort, the field of hepatology will continue to make progress and overcome obstacles.