Health
Health & Life Sciences: How InterWorks can help solve your data challenges
At InterWorks, we have a wealth of experience supporting HLS (Healthcare and Life Sciences) organisations in creating efficient, compliant, and open data structures. With over 425 clients worldwide, including more than 40 hospitals, we bring deep industry knowledge and proven expertise to every engagement.
The impact and realities of data for HLS
Navigating Fragmented Data in the Health and Life Sciences Ecosystem
Challenge: Health and life sciences data comes from many sources—like EHRs, clinical trials, and monitoring devices making it difficult to keep data accurate and consistent.
Leveraging Unstructured Health Data for Real-World Evidence and Analytics
Challenge: Real-world data is often unstructured and hard to integrate with clinical trial data. Linking and analyzing diverse data types—structured, unstructured, genomic, and phenotypic—poses technical and organizational challenges.
Meeting Emerging Data Security and Privacy Demands in Health and Life Sciences
Challenge: Health data is highly sensitive and regulated, GXP compliance and data governance is essential to ensure the organization is meeting patient outcome targets.
Solution: Design practical, phased data programs that are grounded in real-world impact and make AI transformation achievable.
Services
Data Integration & ETL Services
Data Integration: Aggregating data from disparate systems (EHRs, LIMS, clinical trial data, IoT health devices, CRM, financial systems, etc.) to create a unified, accessible dataset.
ETL (Extract, Transform, Load) Services: Automating the extraction, transformation, and loading of data to facilitate seamless integration into BI platforms. This is essential for aggregating clinical, operational, and financial data to enable comprehensive analysis.
AI & ML Integration
Implementing AI and ML algorithms to automate decision-making, identify hidden patterns, and generate insights from large, complex datasets. AI can help detect patterns in patient behavior or predict the likelihood of certain diseases.
Natural Language Processing (NLP): Using NLP to extract insights from unstructured data such as physician notes, clinical records, research papers, and other text-based information that isn't captured in traditional databases.
Clinical Decision Support Systems (CDSS): Implementing AI-powered tools that help clinicians make real-time, data-driven decisions based on patient history, lab results, and predictive models.
Training & Change Management
Helping organizations implement BI solutions successfully by managing the transition and fostering a culture of data-driven decision-making.
Patient & Drug Journey Analytics
Patient Journey Mapping: Analyzing and visualizing the entire patient journey (from diagnosis to treatment to recovery) to identify gaps, bottlenecks, and opportunities for improvement in patient care.
Drug Lifecycle Analytics: Tracking the lifecycle of pharmaceutical products from development to market launch, sales, and post-market surveillance, ensuring that drug development processes are optimized and compliant with regulations.
Cloud Solutions & Scalability
Setting up cloud-based BI solutions to allow healthcare and life sciences companies to scale their data and analytics capabilities as their needs grow. Cloud solutions provide flexibility, lower upfront costs, and enhance collaboration.
Solutions
Federated Data Access Governance Review
Provide expert guidance on how to manage and standardize data access across multiple systems and use cases. Ensure that all data access—regardless of how or where it's used—follows a consistent model for authentication and authorization.
Cloud Data Platform Setup
Quickly launch a high-performing Cloud Data Warehouse using proven best practices. We’ll handle the setup, optimize performance, and support adoption—so you can get the most value from your data and pipelines right away.
Decision-Making Framework Assessment
A practical, non-technical guide to help your team turn business questions into data-driven insights. We’ll train them to build and test analytical hypotheses, with a focus on health and life sciences (HLS) data.
Unstructured Data Integration
Design and build a pipeline to extract, transform, and validate semi-structured and unstructured data—making it ready for use in your systems.
Resources
Crucial to understanding the people and population of the UK on a number of levels, NHS England developed the PAPI (person and population information) team to help develop insight and analytics in this area.
- Tableau Desktop
- Tableau Cloud
Advocating for the unification of the region’s health and social care services, GMHSCP made the jump to a formally devolved program in April 2016, allowing control of public services to rest in local hands.
- Tableau Desktop
- Tableau Cloud
Learn how Asthma Australia implemented a customer experience framework, with a single view of the customer to enable personalised engagement and journeys.
- Power BI
In today’s digital age, data is the most valuable asset we have to understand our world and the effects our decisions have on it. With our increasing reliance on data, it’s imperative that companies maintain good data governance principles.
- White Paper
For 20+ years, we’ve helped organizations bring order to complexity.
Let’s build the trust, clarity and control your data needs to fuel confident decisions and scale with purpose.
