A New Era for EHR Data
A new study published in the latest issue of the Royal College of Physicians’ Future Healthcare Journal introduces PICTURE, an innovative data platform designed to convert routine electronic health record (EHR) data into actionable clinical intelligence, without requiring specialist analysts or advanced coding expertise.
The platform was developed by a multidisciplinary team at Great Ormond Street Hospital (GOSH), specifically within their DRIVE (Data Research, Innovation and Virtual Environments) unit, in collaboration with University College London (UCL) and Roche. This partnership represents a significant milestone in NHS-led digital innovation, bridging the gap between raw data collection and real-world clinical application.
The platform addresses one of the most persistent challenges in modern healthcare: while vast quantities of patient data are captured daily through EHR systems, much of this information remains underutilised due to technical barriers, fragmented systems, and limited analytical capacity within frontline clinical teams.
Unlocking the Value of Routine Data
Healthcare systems across the UK and globally have invested heavily in digitising patient records. However, extracting meaningful insights from those records typically requires data scientists, bespoke dashboards, or external analytics teams. This creates bottlenecks and limits the ability of clinicians to rapidly identify trends, monitor performance, or implement quality improvement initiatives.
PICTURE has been developed to bridge that gap. According to the study, the platform enables clinicians and healthcare managers to transform routinely collected EHR data into structured, interpretable outputs that can support clinical decision-making and service evaluation.
Crucially, the system is designed for accessibility. Users do not need programming knowledge or complex data manipulation skills. Instead, the platform automates much of the data transformation process, allowing healthcare professionals to generate insights directly from their existing data infrastructure.
Moving from Data Collection to Clinical Intelligence
The concept underpinning PICTURE reflects a broader shift in healthcare digital transformation: moving beyond data storage toward real-time intelligence generation.
EHR systems were originally introduced to improve documentation and streamline administrative processes. Over time, they have evolved into repositories of rich clinical information, including laboratory results, diagnostic codes, prescribing data, observations, and outcomes. However, in many institutions, these datasets remain siloed or difficult to interrogate without technical support.
The study outlines how PICTURE integrates structured EHR data and applies automated logic to produce outputs that are clinically meaningful. This may include:
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Identifying patterns in patient flow to reduce bottlenecks.
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Highlighting variation in care delivery across different wards or teams.
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Surfacing opportunities for quality improvement (QI) through real-time monitoring.
Supporting Quality Improvement and Service Redesign
One of the key potential applications of PICTURE is in QI initiatives. Healthcare providers increasingly rely on data to measure performance, reduce unwarranted variation, and optimise resource allocation. Yet many frontline teams struggle to access timely analytics without formal data requests that can take weeks to process.
The study suggests that platforms like PICTURE could enable clinicians to independently explore service-level questions, such as admission patterns, length of stay metrics, or clinical pathway outcomes. This may accelerate local improvement projects and reduce reliance on overstretched informatics departments.
In an era of constrained healthcare budgets and workforce pressures, tools that streamline analysis and reduce administrative burden are likely to attract significant attention from hospital leaders and policymakers.
Democratising Healthcare Analytics
A notable aspect of the PICTURE platform is its focus on democratising access to data. Healthcare analytics has traditionally been the domain of specialised professionals. While this ensures methodological rigour, it can create distance between those generating insights and those delivering care.
By making data interrogation more intuitive, PICTURE aligns with a growing movement toward clinician-led analytics. This approach recognises that healthcare professionals are often best positioned to interpret patterns within the context of real-world clinical practice.
However, the study also emphasises the importance of governance, data quality, and responsible use. Automated data platforms must operate within strict information governance frameworks to ensure patient confidentiality and compliance with regulatory standards like GDPR.
The Broader Digital Health Context
The introduction of PICTURE comes amid wider efforts to modernise NHS data systems and improve interoperability across care settings. National strategies increasingly prioritise digital maturity, predictive analytics, and real-time performance monitoring.
Platforms that can extract value from routine EHR data without requiring additional specialist staffing may play an important role in advancing these goals. At the same time, experts caution that technology alone is not a solution. Successful implementation depends on clinician engagement, training, and a cultural acceptance of data-informed practice.
