Solving the 5 Core Data Infrastructure Problems in Diagnostics
Diagnostics and research companies are actively managing a difficult combination of fragmented legacy platforms, intense regulatory compliance pressure, and isolated internal artificial intelligence initiatives. The transition to advanced technical systems and smooth digital experiences is accelerating rapidly. However, enterprise data architecture often struggles to keep pace.
If your organization is scaling up its testing volume or expanding its digital footprint, the infrastructure decisions you make today will dictate your operational agility for years. Addressing these foundational data issues early is a reliable way to secure high testing volumes and superior clinical adoption rates.
This article details the five core technical obstacles slowing down the diagnostics sector. Furthermore, it outlines exactly how Sigma Software Group helps engineering teams resolve them, drawing on our extensive global experience in healthcare software solutions.
1. Legacy Platform Modernization and Data Security
Operating core revenue systems on outdated technology creates immediate operational risks. Large enterprise diagnostic platforms often rely heavily on legacy frameworks where older languages like PHP, Laravel, and AngularJS remain active in core systems. These environments typically feature multiple data stores that lack a unified patient, clinic, or business data layer. Because this data remains deeply fragmented, artificial intelligence simply cannot be embedded into clinical workflows to assist with diagnostics, treatment recommendations, or revenue optimization. Furthermore, operating without enterprise Data Security Posture Management across these fragmented systems constitutes a massive operational risk. Without Data Security Posture Management, organizations lack centralized visibility into where regulated data lives, how it moves, and who accesses it.
Our Engineering Solution
- Modernize legacy applications, including PHP, Laravel, and AngularJS systems, into highly scalable, cloud-native platforms.
- Build unified data migration and consistency architectures to connect fragmented patient and clinic records into a single source of truth.
- Embed artificial intelligence directly into diagnostic and clinic workflow systems once the unified data foundation is established.
- Implement rigorous enterprise Data Security Posture Management to deliver comprehensive data discovery.
- Map exact data flows, triage security risks automatically, and permanently remediate over-privileged access to sensitive regulated data.
Sigma Software Group operates with 2,600 engineers across 15 countries and maintains strict ISO 27001 certification. We possess the exact security framework required to execute these complex data unifications safely. We have previously migrated the Siemens Healthineers CT scanner data processing infrastructure from on-premise systems to the cloud, maintaining full Digital Imaging and Communications in Medicine compliance and clinical data integrity throughout the engagement.
2. Clinical Workflows and Digital Experience Design
Innovators providing complex genetic testing require smooth digital interfaces and portable electronic medical records to scale their operations effectively. Laborious paper-based workflows at obstetrics and gynecology clinics severely disrupt the patient experience and slow down testing cycles. Companies need a seamless digital experience for clinicians and patients across diverse care settings and socioeconomic contexts. When diagnostics companies lack portable electronic medical records, care transfer becomes incredibly difficult. Furthermore, significant backend services, data processing pipelines, and interface development are required to manage these workflows efficiently.
Our Engineering Solution
- Engineer the complete digital experience layer, encompassing both clinician-facing portals and patient applications.
- Execute paper workflow digitization directly at clinic sites to replace manual entry.
- Build highly secure, portable electronic medical record architectures that allow patient data to move safely between different care settings.
- Engineer powerful backend services and data processing pipelines capable of handling large volumes of complex genetic test data without performance degradation.
Through our full-stack product engineering capability, we build interfaces that physicians and patients actually find easy to use. Our successful delivery of the AstraZeneca RITA patient platform serves as direct evidence of our ability to engineer clinician and patient-facing healthcare products from the ground up.
Explore Sigma Software’s Healthcare Software Development Services
3. Compliance, Quality Assurance, and Preclinical Data
Deploying laboratory systems requires intense software quality assurance across multiple products. In highly regulated, compliance-focused environments, organizations struggle with implementing and configuring complex laboratory information systems. This is particularly true for specialty platforms like mTilda, HistoTrac, and Soft HLA. Additionally, deploying and customizing Health Level Seven interfaces is a major operational focus. Preclinical contract research organizations also face incredibly strict regulatory guidelines. These preclinical environments often need strict Good Laboratory Practice compliance engineering, along with automated data capture from lab instruments.
Our Engineering Solution
- Provide dedicated software quality assurance engineering capacity across your entire diagnostic product portfolio.
- Implement and configure complex Laboratory Information Management Systems, including specialty platforms like mTilda, HistoTrac, and Soft HLA.
- Deploy, configure, and troubleshoot Health Level Seven interfaces.
- Automate instrument data capture to eliminate manual transcription errors and guarantee Good Laboratory Practice compliance.
- Deliver custom project tracking dashboards and secure collaboration portals for clinical study data.
Because we are fully ISO 13485 certified and highly experienced in Health Insurance Portability and Accountability Act aligned delivery practices, we can guarantee compliance. Our direct experience delivering the Formpipe Life Science Quality Management System proves our capability to operate securely within these highly restricted regulatory frameworks.
4. Productizing Diagnostic Artificial Intelligence
Many diagnostic organizations possess brilliant internal artificial intelligence initiatives for test interpretation analytics. Sadly, these powerful tools remain functionally isolated because they are not productized or accessible externally via Application Programming Interfaces or Software Development Kits. Consequently, there is no published clinical workflow automation for test ordering, results delivery, or insights delivery. Research and clinical study data is incredibly rich, but process automation is entirely absent. When artificial intelligence is not properly productized, clinicians simply cannot access the diagnostic insights within their existing software ecosystem.
Our Engineering Solution
- Develop an artificial intelligence productization layer using custom Application Programming Interfaces and Software Development Kits.
- Securely expose internal analytical models directly to external clinical workflow tools.
- Automate the entire testing lifecycle, including test ordering, results delivery, and analytics distribution.
- Construct clinical study data pipelines to make research data operationally useful at a massive scale.
- Build custom integration layers connecting laboratory results directly to hospital electronic health record systems.
Turning internal analytics into a production clinical workflow service is a core technical competency. Our specific work engineering the AstraZeneca RITA platform serves as direct evidence of our ability to turn an internal artificial intelligence capability into a production clinical workflow service.
5. Medical Imaging Cloud Migration
Legacy magnetic resonance imaging organizations and hardware-first imaging companies frequently face significant limitations with software and cloud capability. Massive imaging data sets remain housed entirely on-premise. Relying on this aging infrastructure eventually restricts analytical capabilities and prevents the implementation of a modern data platform. Migrating this infrastructure requires highly specialized handling. The primary concern is ensuring that Digital Imaging and Communications in Medicine compliance is never compromised during the transition.
Our Engineering Solution
- Safely migrate massive on-premise imaging data and associated processing systems to highly scalable cloud environments.
- Implement modern data platforms specifically tailored to handle large medical files efficiently.
- Engineer strict, compliant data pipelines to ensure clinical data integrity is maintained at all times during the transit process.
- Maintain strict and verifiable adherence to Digital Imaging and Communications in Medicine standards across all new cloud infrastructure.
We apply the exact cloud migration and data engineering approach we successfully delivered for Siemens Healthineers. By leveraging this proven methodology, we move your on-premise imaging infrastructure to the cloud while strictly maintaining all industry compliance standards and clinical data integrity.
Is your data infrastructure slowing you down?
The diagnostics companies that get ahead of legacy modernization and artificial intelligence productization early are the exact ones that will secure the highest testing volumes.
If your team is currently working through decisions around legacy migrations, Laboratory Information Management Systems implementation, or workflow integration, Sigma Software Group is ready to help. We bring the scale, the certifications, and the direct healthcare software experience necessary to execute these projects flawlessly.
Let us map out your path forward. Contact us to schedule a free diagnostic consultation. We will discuss your current architecture and outline a governed, scalable strategy.
Want to see what this looks like in practice? Let’s talk.
Let’s talk about your unique workflows and design a custom digital health solution that supports outcome-based care, improves population health, and aligns with value-based reimbursement models.
Whether you’re navigating HEDIS metrics, improving care coordination, or optimizing performance-based contracts, we can help.
Build Your Custom Implementation Plan
Your implementation plan includes integrations, MVP timelines, and long-term support strategies. We build your value-based care solution around real workflows, compliance requirements, and measurable outcome goals.
Launch and Optimize for Outcome-Based Development
Our solutions combine predictive analytics, AI-driven clinical insights, and secure, interoperable data flows. Whether you need compliance tools, shared savings tracking, or a care coordination engine, we align it with your quality metrics, reimbursement goals, and care delivery model.
Ready to Improve Outcomes with Custom Value-Based Solutions?
We design and build custom software for value-based healthcare, built around your data, workflows, and objectives. Whether you need to unify data, support attribution, or track performance across contracts—we’re here to build what works.
Custom Software for Aesthetic Clinics: Overcoming Digital Growth Challenges
3 AI Execution Gaps Slowing Down Medical Distribution
Resolving Fragmented Clinical Data in Biotech
The 7 Core IT Engineering Bottlenecks in Clinical Stage Biotech (And How to Resolve Them)
Where AI Actually Works in Biotech: Clinical Trials, Genomics, and Drug Discovery
CMS LEAD Model Explained: Strategy, Risk & Readiness Checklist
Stay in the loop with everything you need to know.