Developing clinical informatics to support direct care and population health management: the VIEWER story

Abstract: Electronic health records (EHRs) provide comprehensive patient data which could be better used to enhance informed decision-making, resource allocation, and coordinated care, thereby optimising healthcare delivery. However, in mental healthcare, critical information, such as on risk factors, precipitants, and treatment responses, is often embedded in unstructured text, limiting the ability to automate at scale measures to identify and prioritise local populations and patients, which potentially hinders timely prevention and intervention. We describe the development and proof-of-concept implementation of VIEWER, a clinical informatics platform designed to enhance direct patient care and population health management by improving the accessibility and usability of EHR data. We further outline strategies that were employed in this work to foster informatics innovation through interdisciplinary and cross-organisational collaboration to support integrated, personalised care, and detail how these advancements were piloted and implemented within a large UK mental health National Health Service Foundation Trust to improve patient outcomes at an individual patient, clinician, clinical team, and organisational level.

An Analytical Overview of the VIEWER Initiative in Mental Health Clinical Informatics

In light of the complex challenges faced by mental health services within the United Kingdom's National Health Service (NHS), the paper titled "Developing clinical informatics to support direct care and population health management: the VIEWER story" presents the development and implementation of a clinical informatics platform named VIEWER. This platform is designed to enhance both direct patient care and population health management by optimizing the use of Electronic Health Records (EHRs) to deliver integrated and personalized mental health services.

The VIEWER initiative was undertaken against a backdrop of longstanding challenges in the mental healthcare domain, marked by disparities in access, quality, and integration between mental and physical health services, compounded by resource constraints. The authors argue that conventional approaches focusing on crisis intervention are disproportionately consuming resources without addressing broader systemic issues. For this reason, the paper advocates for the adoption of Integrated Care Systems (ICS) that prioritize prevention, deploy coordinated health services, and address social determinants of health (SDOH) within a population health management (PHM) framework.

The VIEWER Platform’s Architecture and Implementation

VIEWER leverages cutting-edge natural language processing (NLP) and visual analytics to extract meaningful insights from the unstructured text of EHRs, significantly enhancing the ability to use clinical data for patient care and research. Originally developed by the South London and Maudsley NHS Foundation Trust, the platform integrates open-source tools, such as CogStack, to enable complex data analysis, facilitating efficient information retrieval and real-time visualization.

The platform supports clinical decision-making at three hierarchical levels:

1. Population-Level Insights: VIEWER provides comprehensive demographic visualizations which support healthcare providers in identifying areas with discrepancies in mental health incidence and service provision. For instance, visualizations reveal geographic patterns of psychosis incidence, crucial for aligning health services with community needs.

2. Pathway-Level Analysis: By visualizing caseload data with respect to clinical pathways, VIEWER aims to uphold adherence to care standards and promote equitable healthcare access. This is exemplified in the management of non-affective psychosis patients, where discharges to primary care trigger checks for adherence to NICE guidelines.

3. Individual Patient Management: VIEWER offers a streamlined interface for clinicians to access summaries of individual patient records, including medication timelines and physical health trends. This functionality significantly reduces the time required for clinical evaluations and supports evidence-based decision-making.

Theoretical and Practical Implications

The paper emphasizes the potential of VIEWER to transform mental health service delivery models from reactive approaches to proactive, population-centered strategies. The platform’s adaptability to varying clinical demands due to its modular design positions it as a robust tool for future healthcare innovations amidst evolving NHS policies.

The authors acknowledge certain challenges inherent to wider platform adoption across diverse NHS settings. These challenges include the need for considerable technical and financial resources, potential disparities in digital literacy among health professionals, and the complexities of integrating data across varying healthcare systems. Despite these hurdles, the VIEWER initiative provides a promising model for using advanced informatics to enhance PHM in mental health care settings.

Looking Forward

While this paper focuses on a proof-of-concept pilot within the NHS framework, it suggests that expanding similar initiatives requires cross-organizational collaboration to overcome barriers related to data standardization and digital adoption. It also highlights the need for integrating more extensive data points from across healthcare systems, such as primary care and emergency services, to provide comprehensive insights into patient journeys.

In conclusion, the VIEWER program exemplifies the integration of clinical informatics in enhancing mental healthcare delivery. This initiative underscores the potential for collaborative, data-driven healthcare models to improve outcomes and serve as a benchmark for future developments in clinical decision support systems across mental health services.