Before clinical AI touches a patient, someone has to prove it actually works — on the real population, across subgroups, under edge cases, and not just on the slide that sold it. That is what rigorous, independent validation does, and it is increasingly required by the FDA, by customers, and by your own risk posture. Taction Software provides healthcare AI evaluation and validation: clinical accuracy, bias and fairness, robustness, and clinical-workflow validation, to recognized reporting standards. Our value here is independence — when we validate a model, the finding is honest, including the inconvenient ones. This pairs naturally with our FDA SaMD compliance, healthcare MLOps, and clinical decision support work. Schedule a Healthcare AI Validation Strategy Workshop (Free 60-Min) → (NDA-protected) Independent validation positioning · healthcare AI & clinical evaluation experience · HIPAA + BAA · FDA SaMD awareness Why Rigorous Healthcare AI Evaluation Matters Patient Safety Implications A clinical model that is wrong in the wrong way can harm patients. Validation is how you find that out before deployment, not after. FDA SaMD Validation Requirements Regulated AI requires documented verification and validation. We provide the technical V&V; the regulatory strategy is led with your regulatory advisors — see our FDA SaMD compliance practice. Bias Risk in Healthcare AI Healthcare AI can underperform for some demographic groups in ways that are invisible without subgroup testing. Fairness evaluation surfaces it so it can be addressed. Real-World Performance vs. Lab Performance Models that look excellent in development often degrade on real-world data and workflows. Validation closes the gap between the demo and the deployment. Our Healthcare AI Evaluation Capabilities Clinical Accuracy Validation Sensitivity, specificity, PPV, and NPV, calibration testing, and subgroup performance analysis — measuring not just whether the model is accurate, but where and for whom. Bias & Fairness Testing Demographic subgroup analysis, fairness metrics, and mitigation strategy so disparities are detected and addressed rather than shipped. Robustness Testing Adversarial testing, out-of-distribution detection, and edge-case analysis so you know how the model behaves when reality is messy. Clinical Workflow Validation Workflow integration testing, clinical outcome studies, and provider adoption analysis — validating the model in the workflow, not just in isolation. (Clinical outcome and pivotal studies are designed and analyzed with the appropriate qualified clinical and research partners.) FDA-Aligned Validation Pre-submission V&V, pivotal study design support, and real-world performance monitoring (via our MLOps work) — the validation evidence an FDA pathway needs, with the submission led by your regulatory advisors. Use Cases We Validate We validate clinical decision support models (see our CDS work), AI medical imaging (see our DICOM AI imaging pipeline work), AI medical scribes (see our AI medical scribe work), clinical NLP (see our clinical NLP work), and risk stratification models — including models we did not build. Validation Framework Standards We validate to recognized standards: the FDA SaMD validation framework, TRIPOD (transparent reporting of prediction models, with its AI extension), CLAIM (the checklist for AI in medical imaging), and STARD (diagnostic accuracy studies) — so your validation is credible to regulators, customers, and reviewers. Independent Validation for AI Buyers If you are buying or deploying someone else’s AI, independence is everything: validating vendor claims against real evidence, pre-procurement AI evaluation before you commit, and post-deployment audit to confirm it still performs. Because we are independent of the vendor, our assessment is in your interest, not the seller’s. Engagement Options We work in four common shapes: pre-deployment validation, FDA pre-submission validation, ongoing performance monitoring, and independent third-party validation — all on our healthcare AI and custom healthcare software foundation. Schedule a Healthcare AI Validation Strategy Workshop (Free 60-Min) → Frequently Asked Questions How rigorous does validation need to be? It scales with risk and purpose. A model that informs a high-stakes clinical decision or pursues FDA clearance needs the full battery — accuracy, calibration, subgroup, fairness, robustness, and workflow validation to formal standards. A lower-risk internal tool needs less. We right-size the rigor to the model’s risk rather than over- or under-validating. FDA validation vs internal validation? FDA validation is formal, documented, and tied to a regulatory framework and submission; internal validation is what you do for your own confidence and customer trust. They share methods but differ in rigor and documentation. We provide the technical validation either way, and for FDA, the evidence package your regulatory advisors carry into the submission. Independent validation cost? It depends on the model, the use case, and the standards required, so we scope it to your situation rather than quoting a flat number. For buyers, independent validation is typically a small fraction of the AI investment it protects — cheap insurance against deploying something that does not perform. Validation timeline? A focused pre-deployment validation can run a few weeks; a full FDA-aligned validation with clinical studies runs considerably longer. We set the timeline against your driver — procurement deadline, deployment date, or submission schedule — and tell you honestly what rigor fits the time available. Schedule a Healthcare AI Validation Strategy Workshop (Free 60-Min) → Reviewed by Taction Software’s healthcare AI evaluation team. ISO 27001-certified information security management. We are an independent validator; PHI used in validation is handled under a signed BAA. Validation informs deployment decisions and is paired with clinician oversight; it does not by itself make a model safe to use unsupervised. See our data security practice.

Most healthcare AI initiatives do not fail at the model — they fail at operations. Getting a model into production, watching it for drift, retraining it safely, and proving what ran when are where clinical AI either matures or quietly degrades. And in healthcare the stakes are patient safety and compliance, not just uptime. Taction Software builds healthcare MLOps: HIPAA-compliant deployment, monitoring and drift detection, FDA-aware retraining pipelines, and the experiment tracking and versioning that make clinical AI reproducible and auditable. Schedule a Healthcare MLOps Maturity Assessment (Free 60-Min) → (NDA-protected) MLOps engineering credentials · healthcare AI specialist team · HIPAA + BAA · FDA SaMD awareness Why Healthcare MLOps Is Different Clinical Validation Requirements Healthcare models cannot ship or change on engineering metrics alone — clinical validation gates deployment and retraining, which general MLOps does not account for. HIPAA & Compliance Constraints PHI in training and inference imposes constraints on data handling, environments, and logging that ordinary MLOps pipelines ignore — see our HIPAA-compliant development and data security practices. Auditability & Explainability You have to be able to show what model produced a given output, on what data, and why — auditability is a first-class requirement, not an afterthought. Production Quality Stakes (Patient Safety) When a model affects care, silent degradation is a safety issue. Monitoring and clinician oversight are non-negotiable, not nice-to-haves. Our Healthcare MLOps Capabilities Model Deployment Containerized deployment, inference serving (TorchServe, BentoML, KServe), edge and mobile deployment, and multi-region deployment for reliable, scalable serving. Monitoring & Observability Performance monitoring, drift detection (data and concept drift), clinical outcome monitoring, and audit logging so degradation and PHI access are both visible. Retraining Pipelines Continuous-learning pipelines, FDA PCCP-aligned retraining, and drift-triggered retraining — updating models within controlled, validated guardrails rather than ad hoc, connecting to our LLM fine-tuning work. Experiment Tracking & Reproducibility MLflow / Weights & Biases, reproducible training, and model versioning so any model in production can be traced, reproduced, and rolled back. MLOps for FDA SaMD For regulated models, we run operations that fit the FDA framework: PCCP-aligned operations, real-world performance monitoring, and algorithm change protocol execution — so changes happen within a pre-authorized envelope. See our FDA SaMD compliance practice (where the regulatory strategy is led with your regulatory advisors). Common Healthcare MLOps Stack We work across stacks: cloud-native (AWS SageMaker, Azure ML, Vertex AI) — see our cloud comparison for healthcare — self-hosted (Kubeflow, MLflow, BentoML) for control and on-premises needs, and hybrid. We choose based on your cloud footprint, compliance, and scale rather than a fixed stack. MLOps Maturity Assessment Framework We assess and advance organizations through the maturity levels: Level 0 (manual), Level 1 (ML pipeline automation), Level 2 (CI/CD for ML), and Level 3 (full MLOps) — meeting you where you are and building the path forward rather than imposing more than you need. Engagement Options We work in three common shapes: a greenfield MLOps build, an MLOps maturity uplift of an existing setup, and a specific MLOps component build (deployment, monitoring, or retraining) — all on our healthcare AI and custom healthcare software foundation. Robust MLOps pairs naturally with AI evaluation and validation, which we also provide. Schedule a Healthcare MLOps Maturity Assessment (Free 60-Min) → Frequently Asked Questions How does healthcare MLOps differ? General MLOps optimizes for reliable, scalable model operations; healthcare MLOps adds clinical validation gates, HIPAA constraints on data and environments, strong auditability and explainability, and patient-safety-grade monitoring. The pipeline has to satisfy clinical and compliance requirements, not just engineering ones. FDA PCCP impact on retraining? For FDA-regulated models, retraining must stay within the Predetermined Change Control Plan — the changes and validation you pre-defined. We build retraining pipelines that enforce the PCCP’s boundaries and document changes for the algorithm change protocol, so updates remain compliant. The regulatory strategy itself is led with your regulatory advisors. Drift detection approaches? We monitor for data drift (inputs shifting from training distribution) and concept drift (the input-output relationship changing), using statistical monitoring and, where it matters most, clinical-outcome monitoring. Detected drift can trigger alerts and, within guardrails, retraining — so accuracy is caught slipping rather than discovered by users. Cost considerations? MLOps cost is driven by your serving volume, infrastructure choices (cloud-managed vs self-hosted), and monitoring depth. We size it to your needs and maturity target, and a maturity assessment usually finds the highest-leverage investments first. See our healthcare AI implementation cost guide for broader context. Schedule a Healthcare MLOps Maturity Assessment (Free 60-Min) → Reviewed by Taction Software’s healthcare AI and ML engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA, and clinical-facing models are operated with monitoring and clinician oversight.

Fine-tuning is the right tool when you need a model to adopt your specialty’s terminology, your documentation style, or a specific reasoning pattern — things retrieval alone cannot give you. But it is also easy to do badly, and in healthcare the cost of a confidently wrong model is high. Taction Software fine-tunes and domain-adapts LLMs for healthcare: base-model selection, PEFT/LoRA and full fine-tuning, rigorous clinical data curation and PHI handling, and the evaluation that proves the model is actually better — deployed in the cloud or on-premises. The first question is usually fine-tuning vs RAG, and often the answer is both. For the retrieval side, see our healthcare RAG implementation practice; this page is about adapting the model itself. Schedule a Healthcare LLM Fine-Tuning Strategy Workshop → (NDA-protected) LLM engineering credentials · healthcare AI specialist team · HIPAA + BAA When Fine-Tuning Beats RAG Specialty Terminology Adaptation When a model needs to natively understand and produce your specialty’s terminology and conventions, fine-tuning bakes that in rather than retrieving it each time. Documentation Style Replication To match a specific documentation style or house format consistently, fine-tuning shapes the model’s output in a way prompting and retrieval struggle to. Reasoning Pattern Customization When you need the model to follow a particular clinical reasoning or structuring pattern, fine-tuning adapts how it thinks, not just what it knows. Performance & Latency Requirements A smaller fine-tuned model can hit accuracy and latency targets more cheaply at scale than a large general model with a heavy prompt. Our Fine-Tuning Capabilities Base Model Selection Open-source foundations (Llama, Mistral, Mixtral), healthcare-specific foundation models, and commercial models with fine-tuning APIs — chosen for your accuracy, cost, deployment, and licensing needs. Fine-Tuning Approaches Full fine-tuning, LoRA / QLoRA, PEFT techniques, and instruction tuning — matched to your data volume, budget, and the degree of adaptation you need. Healthcare Data Curation Clinical document selection, PHI handling in training data (de-identification and BAA-governed handling so PHI is never mishandled), synthetic data generation, and quality filtering — because fine-tuning quality is mostly data quality. Built on our clinical NLP work. Evaluation Framework Healthcare-specific benchmarks, clinical accuracy validation against expert-reviewed references, bias and fairness testing, and production performance monitoring — so you can prove the fine-tuned model is genuinely better and safe to use, with clinician oversight where outputs affect care. Specialty Fine-Tuning Use Cases We fine-tune for behavioral health documentation (see our behavioral health software work), specialty coding (cardiology, orthopedics), specialty clinical summarization, and specialty diagnostic reasoning — each adapting the model to a domain general models handle only roughly. Fine-Tuning vs Alternatives Fine-Tuning vs RAG Fine-tuning changes how the model behaves (style, terminology, reasoning); RAG changes what it knows (current, citable knowledge). For evolving knowledge, RAG; for ingrained behavior, fine-tuning. Fine-Tuning vs Prompt Engineering Prompt engineering is the cheapest, fastest lever and often enough; fine-tuning is worth it when prompting cannot reliably get the behavior, or when latency and cost at scale favor a smaller adapted model. When to Combine Approaches The strongest systems often combine all three: a fine-tuned model for behavior, RAG for knowledge, and careful prompting — we design the right mix rather than forcing one. Deployment Options We deploy in the cloud under a BAA, on-premises for data sovereignty (see our on-prem LLM work), or hybrid — matched to your compliance and cost needs, consistent with our HIPAA-compliant development and data security practices. Cost & Timeline Typical phase ranges; your number depends on model, data, and approach (LoRA/PEFT is far cheaper than full fine-tuning): See our healthcare AI implementation cost guide for broader AI cost context; we give a firmer estimate after the workshop. Schedule a Healthcare LLM Fine-Tuning Strategy Workshop → Frequently Asked Questions LLM provider vs open-source fine-tuning? Commercial fine-tuning APIs are fast and managed but keep you on that provider and its terms; open-source fine-tuning (Llama, Mistral) gives full control, on-premises capability, and often lower long-run inference cost, at the cost of more engineering. We choose based on your control, deployment, and cost needs rather than defaulting either way. How much training data do we need? It depends on the goal. Instruction tuning for a specific behavior can work with a few hundred to a few thousand high-quality examples; broad domain adaptation needs substantially more. Quality and representativeness matter more than raw volume — we assess your data and tell you honestly whether you have enough or need synthetic augmentation. Cost of GPU infrastructure? It depends heavily on model size and approach: LoRA/QLoRA and PEFT train on far less GPU than full fine-tuning, and you can rent cloud GPUs rather than buy. We size the infrastructure to your model and approach and model the cost up front, including whether owned hardware makes sense for ongoing work. Continuous fine-tuning approach? For models that should keep improving, we set up a pipeline to periodically retrain on new, curated data with re-evaluation and guardrails before promotion — connecting to MLOps practices so updates are controlled, validated, and reversible rather than ad hoc. Schedule a Healthcare LLM Fine-Tuning Strategy Workshop → Reviewed by Taction Software’s healthcare AI and ML engineering team. ISO 27001-certified information security management. Training data containing PHI is handled under a signed BAA, and clinical-facing models are validated with clinician oversight. See our broader healthcare AI solutions.

Smile CDR — the enterprise platform from Smile Digital Health, built on the open-source HAPI FHIR foundation — is one of the most capable enterprise FHIR servers available, used by major health systems and payers. But its power is in its configurability, and configuring it well (resources, profiles, modules, terminology, interceptors, and scale) takes specialist FHIR engineering. Taction Software implements, extends, and tunes Smile CDR: server configuration, module setup, custom extensions, and performance at scale. We are your implementation partner for Smile CDR; the platform is licensed from Smile Digital Health. For managed cloud FHIR alternatives, see our Azure API for FHIR and AWS HealthLake practices. Schedule a Smile CDR Implementation Strategy Call → (NDA-protected) HAPI FHIR & Smile CDR specialist team · FHIR R4 expertise · HIPAA + BAA When Smile CDR Is the Right Choice Enterprise FHIR Server Requirements Smile CDR fits when you need an enterprise-grade FHIR server with commercial support, rather than building and supporting one yourself. Self-Hosted FHIR Deployment When you need to self-host — for data sovereignty, control, or architecture reasons — Smile CDR supports running in your own environment. Open-Source HAPI FHIR Foundation Because it builds on HAPI FHIR, you get the maturity and extensibility of the leading open-source FHIR implementation with enterprise capabilities on top. Modular Capabilities Architecture Smile CDR’s modular design lets you enable the capabilities you need — terminology, interoperability, MDM, and more — rather than a monolith. Our Smile CDR Implementation Capabilities FHIR Server Configuration Resource type configuration, custom profile implementation, search parameter configuration, and subscription implementation so the server matches your data and integration needs — on our FHIR API development foundation. Module Configuration The terminology module, the Cures Act / interoperability module, the CARIN Blue Button module, and MDM (patient matching / master data management) — configured to your use cases, supporting our CMS interoperability compliance work. Custom Extensions Custom resource types, custom operations, and interceptor development using the HAPI/Smile extensibility model for behavior the platform does not provide out of the box. Performance & Scale Tuning High-volume configuration, database tuning, and caching strategy so the server performs at your data volume and query load. Smile CDR vs Alternatives Smile CDR vs Azure FHIR Azure’s FHIR service is fully managed and cloud-native; Smile CDR offers self-hosting and deep configurability with commercial support. The choice follows your control, hosting, and cloud preferences. Smile CDR vs AWS HealthLake AWS HealthLake is managed with built-in ML; Smile CDR gives you a configurable, self-hostable enterprise FHIR platform. Again, managed-cloud versus configurable-enterprise is the deciding axis. Smile CDR vs Open-Source HAPI FHIR Direct Running HAPI FHIR directly is free but you build and support everything; Smile CDR adds enterprise modules, support, and tooling on top of HAPI. The trade is licensing cost versus the engineering and operational burden of going fully DIY. Common Use Cases We implement Smile CDR as an enterprise FHIR data platform, for Cures Act compliance for payers (CARIN and interoperability modules), for clinical data aggregation, and as a research data platform — all on our custom healthcare software foundation. Engagement Options We work in four common shapes: an initial Smile CDR deployment, custom module development, performance optimization, and migration to or from Smile CDR. Schedule a Smile CDR Implementation Strategy Call → Frequently Asked Questions Smile CDR vs HAPI FHIR direct? Smile CDR is built on HAPI FHIR and adds enterprise modules (terminology, interoperability, MDM), tooling, and commercial support. Running HAPI directly is free and fully under your control, but you build and maintain everything yourself. Smile makes sense when the enterprise capabilities and support are worth the license; direct HAPI when you have the engineering depth and want no licensing. Self-hosted vs managed Smile? Smile CDR can run self-hosted in your environment or in a managed arrangement. Self-hosting maximizes control and data sovereignty; managed reduces operational burden. We help you choose based on your compliance, control, and operations preferences, and implement either. Performance at scale? At high volume, performance depends on configuration, database design, and caching. We tune resource indexing, search parameters, database, and caching, and load-test against your expected volume so the platform stays responsive as data and traffic grow. Cost considerations? There are two cost layers: Smile’s commercial licensing (set by Smile Digital Health and confirmed with them) and the implementation and operations cost. We scope the implementation; the licensing is separate. Against fully self-built HAPI, you trade license cost for far less engineering and operational burden — we help you weigh that honestly. Schedule a Smile CDR Implementation Strategy Call → Reviewed by Taction Software’s healthcare integration and FHIR engineering team. ISO 27001-certified information security management. We are an independent implementation partner; Smile CDR is licensed from Smile Digital Health. PHI is handled under a signed BAA — see our data security practice.

Particle Health gives products a way to pull a patient’s longitudinal record from across disconnected providers through national data networks — powerful for care coordination, risk adjustment, and onboarding, but only as good as the integration around it. Identity resolution, FHIR data mapping, and resilient retrieval all take real engineering. Taction Software implements and integrates Particle Health for health-tech vendors: clinical data retrieval workflows, FHIR R4 mapping, patient identity resolution, and production operations. We are your integration partner for Particle, not Particle itself. For neighboring options, see our Redox and 1upHealth integration practices. Schedule a Particle Health Implementation Strategy Call → (NDA-protected) FHIR specialist team · clinical data aggregation experience · HIPAA + BAA When Particle Health Is the Right Choice Clinical Data Aggregation Use Cases Particle is a strong fit when you need to assemble a patient’s records from many sources you are not directly connected to, via national networks. Member Onboarding With Historical Records When onboarding a member or patient and you want their historical clinical record from the start, network-based retrieval brings it in without per-provider integration. Care Coordination Across Disconnected Providers For coordinating care across providers who do not share an EHR, Particle’s network reach surfaces records that would otherwise be invisible. Specialty Use Cases vs. Redox or 1upHealth Particle’s niche is network-based record retrieval, which is different from Redox‘s broad EHR connectivity or 1upHealth‘s FHIR data platform. The right tool follows your use case, and some stacks combine more than one. Our Particle Implementation Capabilities Clinical Data Retrieval Workflows We build the query, retrieval, and processing workflows that turn Particle responses into usable clinical data in your product. FHIR R4 Data Model Mapping We map retrieved data into your FHIR R4 model so it fits cleanly with the rest of your system — on our FHIR API development foundation. Patient Identity Resolution We implement demographic matching and identity resolution so retrieved records are correctly associated with the right patient. Error Handling & Retry Logic We build robust error handling, retry, and partial-result handling so network variability does not break your workflow. Particle vs Alternatives Particle vs Redox (Different Use Cases) Redox focuses on broad EHR connectivity and interface management; Particle focuses on retrieving records across networks. They solve different problems and can be complementary. Particle vs 1upHealth 1upHealth centers on a FHIR data platform and payer/aggregation use cases; Particle centers on network-based record retrieval. The choice follows your data model and where the records live. Particle vs Direct EHR Integration Direct integration gives deep, specific access to a known EHR; Particle gives broad reach across many providers without per-EHR builds. Depth versus breadth, as with most integration decisions. Common Use Cases We build care coordination apps, risk-adjustment workflows (pulling records to support compliant HCC capture, complementing our value-based care work), prior-authorization documentation (gathering supporting records, see our prior authorization automation work), and provider onboarding workflows. Implementation Approach Use Case Validation We validate the use case and confirm Particle is the right fit. Particle Sandbox Implementation We build and validate against Particle’s sandbox. Production Deployment We deploy to production with the identity, mapping, and error handling in place. Monitoring & Operations We build monitoring and support operations so retrieval stays healthy at scale. Engagement Options We work in three common shapes: an initial Particle implementation, a migration to or from another aggregator, and Particle optimization and scaling — all on our custom healthcare software foundation. Schedule a Particle Health Implementation Strategy Call → Frequently Asked Questions Particle vs other clinical aggregators? Particle’s strength is network-based retrieval of records across many disconnected providers, where Redox emphasizes EHR connectivity and 1upHealth emphasizes a FHIR data platform. The right choice depends on whether your problem is reaching many providers, integrating specific EHRs, or managing FHIR data — and we help you match tool to use case rather than defaulting to one. Performance at scale? Network-based retrieval performance depends on the networks and the volume of queries, so we architect with appropriate concurrency, caching of retrieved data, and asynchronous patterns, and we monitor it in production so it holds up as your volume grows. Data freshness? Network-retrieved records reflect what participating sources have shared, so freshness varies by source. We design workflows that account for that — for example, retrieving on a schedule or on demand at the right moments — so your product uses appropriately current data. Integration with our existing FHIR architecture? We map Particle data into your existing FHIR R4 model and resources so it integrates with the rest of your system rather than sitting in a silo, consistent with our data security and HIPAA-compliant development practices. Schedule a Particle Health Implementation Strategy Call → Reviewed by Taction Software’s healthcare integration engineering team. ISO 27001-certified information security management. We are an independent integration partner. PHI is handled under a signed BAA.

If your customers run Cerner — now Oracle Health — building a clean, listed integration is the way to reach them, and it takes Cerner-specific SMART on FHIR and API engineering to do well. Cerner’s developer program, Cerner Code (the Cerner Open Developer Experience, CODE), sits under Oracle Health today, and its direction is evolving with Oracle’s investment. Taction Software builds Cerner-integrated apps end to end: SMART on FHIR development, Cerner FHIR API integration, the Cerner-specific patterns, and support through marketplace listing. As with any EHR, the roles matter: we are your development partner for Cerner-integrated apps, not Oracle Health. Listing and program terms are set by Oracle Health and require your own program relationship — we build the software and help you navigate the process. For the platform comparison, see our Epic vs Cerner vs athenahealth page and Cerner vs Epic article. Schedule a Cerner / Oracle Health Integration Strategy Call → (NDA-protected) Cerner / Oracle Health integration experience · FHIR specialist team · SMART on FHIR expertise · HIPAA + BAA Cerner Code in the Oracle Era What’s Changed Post-Acquisition Since Oracle acquired Cerner, the developer program and platform have continued under Oracle Health, with Oracle’s resources and roadmap now shaping their evolution. Cerner Code Platform Evolution The Cerner Code / Open Developer Experience continues to provide the APIs and sandbox for building Cerner-integrated apps, and the branding and tooling are evolving under Oracle Health. Oracle Health Strategy Direction Oracle has signaled significant investment in the platform, and some buyers weigh the evolving roadmap as part of their decision — a real but not inherently negative consideration we help you think through. Our Cerner Integration Capabilities SMART on FHIR for Cerner EHR-launched apps, patient-launched apps, and Cerner-specific extensions on the SMART on FHIR standard — on our FHIR API development foundation. Cerner FHIR API Integration USCDI resource coverage, Cerner-specific resources, and bulk data so your app reads and writes what it needs through Cerner’s FHIR APIs. Cerner Open Engine Integration HL7 v2 integration (via our HL7 practice), CCL reporting (Cerner Command Language), and mPages integration for the clinician workflow. Marketplace & Distribution Support through Cerner Code listing, Oracle Health marketplace inclusion, and the strategic partnership path — preparing the technical artifacts and working with you through the process. Common Use Cases We Build We build clinical decision support apps (see our clinical decision support work), patient engagement apps (via our patient portal practice), analytics apps (via our healthcare data analytics work), and specialty workflow apps — all on our custom healthcare software foundation. Development Process Sandbox Access & Setup We set up against Cerner’s sandbox and developer environment. FHIR Resource Mapping We map your data model to Cerner’s FHIR resources and APIs. Integration Testing We test the integration thoroughly against Cerner’s environment. Marketplace Submission We prepare and support the marketplace submission for listing. Combined Cerner + Epic Strategy Many vendors need both. We design a multi-EHR app architecture that reuses logic across EHRs on a shared SMART on FHIR core, with EHR-specific customization layered on top — so you build once and adapt per platform rather than building twice. See our Epic App Orchard / Connection Hub work for the Epic side. Schedule a Cerner / Oracle Health Integration Strategy Call → Frequently Asked Questions How does Cerner Code differ from Epic App Orchard? Both are EHR developer programs built around SMART on FHIR, but they differ in APIs, tooling, listing process, and program terms, and Cerner’s now sits under Oracle Health. The good news is that a well-architected SMART on FHIR app shares a large common core across both; we handle the platform-specific differences. Oracle acquisition impact on developer program? The program continues under Oracle Health with Oracle’s backing, and the tooling and branding are evolving. For most vendors the practical impact is that you build to the current Oracle Health developer platform and stay attentive to roadmap changes — which we help you track. Multi-EHR strategy? We architect a shared SMART on FHIR core that maximizes reuse across Cerner, Epic, and other FHIR-capable EHRs, then add per-EHR customization. That keeps your engineering investment efficient while still meeting each platform’s specifics and listing requirements. Distribution without marketplace listing? It is sometimes possible depending on the integration and the customer’s policies, but a marketplace listing eases procurement and trust for Cerner-using customers. We help you decide between listing and a direct integration based on your go-to-market and target accounts. Schedule a Cerner / Oracle Health Integration Strategy Call → Reviewed by Taction Software’s healthcare integration engineering team. ISO 27001-certified information security management. We are an independent development partner, not Oracle Health; program and listing terms are set by Oracle Health. PHI is handled under a signed BAA — see our data security practice.

If your customers run Epic, building a clean, listed Epic integration is one of the most effective ways to reach and sell to them. Epic’s developer ecosystem — historically App Orchard, now organized as Connection Hub with the Showroom marketplace — is the channel, and getting an app through it takes real SMART on FHIR and Epic-specific engineering. Taction Software builds Epic-integrated apps end to end: SMART on FHIR development, Epic FHIR API integration, the Epic-specific patterns, and support through submission and listing. To be clear about roles: we are your development partner for Epic-integrated apps, not Epic. Listing, certification decisions, and program terms are Epic’s, and they require your own Epic program relationship — we build the software and help you navigate the process. For Epic integration more broadly, see our Epic EHR integration practice and Epic integration guide. Schedule an Epic App Strategy Workshop (Free 60-Min) → (NDA-protected) Epic integration experience · FHIR specialist team · SMART on FHIR expertise · HIPAA + BAA Why Epic Marketplace Distribution Matters Reach Epic’s Large Patient Base Epic holds records for a very large share of US patients — Epic has cited figures in the hundreds of millions — so a listed Epic app reaches an enormous installed base through one channel. Streamlined Health System Procurement A listed, pre-vetted app is far easier for an Epic-using health system to evaluate and buy than an unknown integration, shortening procurement. Pre-Approved Integration Pattern Building to Epic’s supported integration patterns means you are working within an approved, repeatable model rather than fighting the EHR. Our Epic Development Capabilities SMART on FHIR App Development EHR-launched apps, patient-launched apps, and standalone apps built on the SMART on FHIR standard — on our FHIR API development foundation. Epic FHIR API Integration USCDI resource coverage, Epic-specific resources, and bulk data export so your app reads and writes the data it needs through Epic’s APIs. App Submission & Certification Support through App Orchard submission, Connection Hub listing, and Showroom inclusion — preparing the technical artifacts and working with you through Epic’s process. Epic-Specific Integration Patterns Hyperspace embedded apps (in the clinician workflow), MyChart integration (patient-facing, via our patient portal work), and Care Everywhere integration for record exchange. Epic Marketplace Tiers & Strategy We help you choose the right route — App Orchard Direct, Connection Hub, Showroom / Workshop, or open-API listed — based on your product, customers, and the relationship you want with Epic. The naming has evolved, and we keep you oriented to the current structure. Common Use Cases We Build We build clinical decision support apps (see our clinical decision support work), patient engagement apps, care coordination apps, specialty practice apps, and AI/ML integration apps (via our healthcare AI work) — all on our custom healthcare software foundation. Epic App Development Process Use Case Validation We validate the use case and the integration approach before building. Sandbox Development We build against Epic’s sandbox / on-FHIR test resources. Testing Environment Certification We move through Epic’s testing-environment validation toward certification. Pilot Customer Validation We validate with a real Epic-using pilot customer to prove fit before broad release. Marketplace Submission We prepare and support the marketplace submission for Connection Hub / Showroom listing. Timeline & Investment Typical ranges, with the listing timeline also dependent on Epic’s process: We give a firmer estimate of the development scope after the strategy workshop. Schedule an Epic App Strategy Workshop (Free 60-Min) → Frequently Asked Questions Difference between App Orchard / Connection Hub / Showroom? They are stages of the same evolving ecosystem. App Orchard was Epic’s original developer program and marketplace; Epic has reorganized this into Connection Hub (the developer program and listing) with Showroom as the marketplace customers browse. The terms still circulate together, so we keep you aligned to Epic’s current structure and choose the right route for your product. Epic certification cost? Epic sets its own program fees and terms, and they depend on your arrangement and tier — we do not control or quote them, and you will establish them directly with Epic. What we scope is the development cost to build and ready your app; the Epic program costs are separate and confirmed with Epic. Can we sell without Epic listing? Sometimes, depending on the integration and the customer’s policies, but a listing materially eases procurement and trust for Epic-using customers and is often expected. We help you weigh listing against a direct integration based on your go-to-market. Multi-EHR strategy? Building to SMART on FHIR gives you a strong foundation that extends beyond Epic to other FHIR-capable EHRs, so we architect for portability where a multi-EHR strategy matters, then handle the Epic-specific layer for the Epic channel. Schedule an Epic App Strategy Workshop (Free 60-Min) → Reviewed by Taction Software’s healthcare integration engineering team. ISO 27001-certified information security management. We are an independent development partner, not Epic; Epic sets program and listing terms. PHI is handled under a signed BAA — see our data security practice.

HHS has set out cybersecurity expectations for healthcare in its Healthcare and Public Health Cybersecurity Performance Goals — a set of Essential and Enhanced goals that increasingly define what “good enough” security looks like for hospitals and health systems. They are voluntary today, but the direction of travel is toward mandatory minimums with potential Medicare implications, which makes getting ahead of them a smart move now. Taction Software helps you implement the technical controls behind the CPGs and produce the assessment, roadmap, and documentation to demonstrate where you stand. We provide the security engineering and assessment; the regulatory determination of what applies to your organization rests with your compliance and security leadership, with whom we work. For broader assessment work, see our healthcare security audit and HIPAA risk assessment practices. Schedule a CPG Compliance Assessment (Free 60-Min) → (NDA-protected) Healthcare cybersecurity specialists · NIST CSF expertise · HIPAA Security Rule program experience · ISO 27001-certified What HHS CPGs Require Essential Goals A baseline set of practices every healthcare organization is expected to have — the fundamentals that block the most common attacks. Enhanced Goals A more advanced tier for organizations maturing beyond the baseline toward stronger resilience. Voluntary vs. Mandatory Pathway The CPGs are currently voluntary guidance. HHS has signaled intent to move toward mandatory minimum requirements, and has proposed strengthening the HIPAA Security Rule, so treating the CPGs as a preview of future obligations is prudent. Your compliance team confirms what currently binds you. Medicare Reimbursement Implications There have been proposals to tie healthcare cybersecurity requirements to Medicare participation. These are evolving rather than settled, so we help you prepare for the trajectory without overstating what is in force today. Essential Goals We Implement Mitigate Known Vulnerabilities Patch management and vulnerability scanning so known weaknesses are found and closed on a cadence — complementing our penetration testing work. Implement Phishing Defense Email security controls and support for user training, since phishing remains the top entry point. Strong Authentication MFA implementation and privileged access management so credentials alone do not open the door. Asset Inventory & Network Segmentation Asset management and network-segmentation architecture so you know what you have and a breach cannot move freely — drawing on our data security practice. Enhanced Goals We Implement For organizations going further: advanced identity management, cyber resilience and recovery (backup, recovery, and tested incident response), third-party risk management, and building a cybersecurity mindset and skills across the organization. Our CPG Compliance Methodology Current-State Assessment We assess your existing security posture against the CPG practices. Gap Analysis Against CPGs We identify exactly where you fall short of the Essential and Enhanced goals. Implementation Roadmap We build a prioritized roadmap, sequencing the highest-risk gaps first. Engineering Work to Close Gaps We do the technical work — segmentation, MFA/PAM, patching and scanning programs, logging, recovery — to close the gaps, drawing on our software modernization and security practices. Documentation & Reporting We produce the documentation that demonstrates your posture for leadership, boards, and any future attestation. Combined CPG + Other Compliance The CPGs overlap with frameworks you may already maintain, and we map controls across them to avoid duplicate work: CPGs + the HIPAA Security Rule (see our HIPAA consulting and HIPAA-compliant development practices) and CPGs + NIST CSF, plus any other frameworks your organization holds. Medicare & Funding Implications We help you weigh the hospital reimbursement impact as requirements evolve, the benefits of voluntary adoption now (real risk reduction and readiness for whatever becomes mandatory), and the enforcement trajectory — without treating proposals as settled law. The honest summary: the bar is rising, and early movers carry less risk. Schedule a CPG Compliance Assessment (Free 60-Min) → Frequently Asked Questions Are CPGs mandatory yet? As of now they are voluntary guidance. HHS has signaled a move toward mandatory minimum requirements and has proposed strengthening the HIPAA Security Rule, with potential ties to Medicare under discussion. So they are not universally mandatory today, but the trajectory points toward enforcement — which is why preparing now is the low-risk choice. Confirm your current obligations with your compliance team. Cost of compliance? It depends entirely on your current maturity. An organization with solid security may have modest gaps; one starting further back has more to do. We assess first and give a roadmap with scoped cost, so you invest against real gaps rather than a generic checklist. HIPAA Security Rule sufficiency? Meeting the HIPAA Security Rule does not automatically satisfy all the CPGs. The Security Rule is risk-based and flexible, while the CPGs are more specific and prescriptive, and the proposed Security Rule update would raise the bar further. We map where your HIPAA program already covers CPGs and where additional work is needed. Reporting requirements? Formal reporting expectations are still taking shape as the requirements evolve. We build the documentation and evidence now so that whatever attestation or reporting is ultimately required, you can produce it without scrambling. Schedule a CPG Compliance Assessment (Free 60-Min) → Reviewed by Taction Software’s healthcare security engineering team. ISO 27001-certified information security management. We provide security engineering and assessment; regulatory determinations rest with your compliance leadership. PHI is handled under a signed BAA.

If your software diagnoses, treats, or drives clinical decisions, it may be a regulated medical device — and the FDA pathway is expensive, multi-year, and unforgiving of shortcuts. Taction Software builds Software as a Medical Device to the engineering standard the FDA expects: a quality-managed design-controls process, IEC 62304 software lifecycle, ISO 14971 risk management, premarket cybersecurity, and the verification, validation, and documentation that support a submission — including AI/ML SaMD with a Predetermined Change Control Plan. One thing to be clear about: we are your software engineering partner for regulated development, not an FDA regulatory consultancy or law firm. We build the compliant software and engineering evidence; your regulatory strategy and the FDA submission are led by you and your regulatory advisors, with whom we work closely. For decision-support products specifically, see our clinical decision support practice. Schedule an FDA SaMD Pathway Strategy Workshop (Free 60-Min) → (NDA-protected) Regulated-software engineering specialists · ISO 13485 QMS experience · IEC 62304 lifecycle · healthcare engineering credentials When Your Software Triggers FDA Regulation Definition of SaMD Software as a Medical Device is software intended for a medical purpose that performs that purpose without being part of a hardware device. Intended use is what determines it. Clinical Decision Support Carve-Out (Cures Act §3060) Some clinical decision support is excluded from device regulation when it meets the statutory non-device CDS criteria — including that the clinician can independently review the basis for the recommendation. Whether your CDS qualifies is a determination to confirm with your regulatory advisors; we design with the distinction in mind. Wellness vs. Medical Device General-wellness software intended to maintain a healthy lifestyle generally falls outside device regulation, while software making medical claims does not. The line is in the intended use and claims. Class I, II, III Determination Devices are classified by risk — Class I (low), II (moderate), III (high) — which drives the pathway and the evidence required. FDA Pathways We Support 510(k) Premarket Notification Predicate device strategy, substantial-equivalence documentation, and support through the FDA review process for devices that can demonstrate equivalence to a legally marketed predicate. De Novo Pathway For a novel device without a predicate, with risk-based classification and special controls for low-to-moderate-risk innovations. PMA (Premarket Approval) For Class III devices, the most rigorous pathway, typically with clinical-trial requirements and the strongest evidence burden. AI/ML SaMD With PCCP A Predetermined Change Control Plan, continuous-learning model management, and real-world performance monitoring so AI/ML devices can evolve within a pre-authorized envelope rather than re-submitting for every change — built on our healthcare AI work. Our FDA SaMD Engineering Methodology Quality Management System (ISO 13485 / QMSR) We engineer within a quality management system aligned to ISO 13485, consistent with the FDA’s Quality Management System Regulation (QMSR), which harmonized 21 CFR 820 with ISO 13485 effective February 2026. Design Controls (21 CFR 820) We follow design controls — inputs, outputs, reviews, verification, validation, and a design history file — as the backbone of regulated development. Software Lifecycle (IEC 62304) We develop to IEC 62304, the medical-device software lifecycle standard, with the rigor scaled to your software’s safety classification. Risk Management (ISO 14971) We apply ISO 14971 risk management throughout, so hazards are identified, controlled, and traced. Cybersecurity (FDA Premarket Cybersecurity Guidance) We build to FDA premarket cybersecurity expectations (including the “cyber device” requirements under FD&C Act §524B), with an SBOM and security testing — drawing on our penetration testing and security audit practices. AI/ML-Specific FDA Considerations We handle the AI/ML specifics: PCCP authoring, the choice between a locked algorithm and continuous learning, the algorithm change protocol that defines permitted changes, and real-world performance monitoring — the framework that lets an AI device improve safely within FDA’s expectations. Cost & Timeline These are typical industry ranges and vary widely by device, evidence needs, and pathway; the regulatory fees, regulatory-consultant, and clinical-trial costs are separate from our engineering scope: We give a firmer estimate of the engineering scope after the pathway workshop. Combined FDA + HIPAA + Quality Management FDA, HIPAA, and quality-management obligations overlap, and a stacked compliance strategy with shared documentation and audit crosswalks avoids doing the same work three times — connecting to our HIPAA-compliant development and data security practices. Schedule an FDA SaMD Pathway Strategy Workshop (Free 60-Min) → Frequently Asked Questions Does our product require FDA clearance? It depends on intended use and claims. Software with a medical purpose generally is regulated; general-wellness software and CDS that meets the Cures Act non-device criteria generally are not. This is a determination to confirm with your regulatory advisors — we help you understand where your product likely sits and design accordingly, but the regulatory call is theirs. 510(k) vs De Novo decision? If a suitable predicate device exists, 510(k) via substantial equivalence is usually faster; if your device is genuinely novel with no predicate, De Novo is the route for low-to-moderate risk. We help frame the engineering and evidence for either, and your regulatory advisors confirm the strategy. AI/ML continuous learning approval path? The current approach is a Predetermined Change Control Plan: you define, up front, the changes the model may undergo and how they will be validated and monitored, so the device can update within that authorized envelope. We author the PCCP engineering and build the monitoring; the submission strategy is led with your regulatory advisors. Pre-Submission meeting strategy? An FDA Pre-Submission (Q-Sub) is a valuable way to align with the FDA on your pathway, predicate, and evidence before you invest fully. We prepare the technical and engineering content that supports a strong Pre-Sub, working alongside your regulatory team who manage the FDA interaction. Schedule an FDA SaMD Pathway Strategy Workshop (Free 60-Min) → Reviewed by Taction Software’s regulated-software engineering team. ISO 27001-certified information security management. We provide regulated-software engineering and documentation, not regulatory or legal services; FDA strategy and submission are led with your regulatory advisors. PHI is handled under a signed BAA.

The information blocking rule has changed the default in healthcare from “share when required” to “share unless an exception applies” — and getting it wrong now carries real penalties. The hard part is rarely wanting to comply; it is operationalizing the rule, applying the eight exceptions correctly, and documenting the decisions. Taction Software provides the technical and workflow side of information blocking compliance: practice discovery, exception-framework implementation, technical access and API design, and the documentation tooling that supports your compliance posture. An important boundary: information blocking is a legal and regulatory matter, and this is implementation support, not legal advice. We work alongside your compliance team and counsel, who make the legal determinations. For the broader context, see our overview of 21st Century Cures Act compliance. Schedule an Info Blocking Compliance Assessment (Free 45-Min) → (NDA-protected) Healthcare regulatory implementation experience · ONC rule specialist team · HIPAA + BAA What the Info Blocking Rule Prohibits Definition of “Information Blocking” Broadly, a practice by a regulated actor that is likely to interfere with the access, exchange, or use of electronic health information (EHI), except as required by law or covered by an exception. Who Is Subject (Actors Defined) Three actor types: health care providers, health IT developers of certified health IT, and health information networks and exchanges (HINs/HIEs). Penalty Framework Health IT developers, HINs, and HIEs can face OIG civil monetary penalties of up to $1 million per violation. Health care providers are subject to separate “disincentives” established by a later rule (tied to federal program participation rather than CMPs). The specifics of how these apply to you are a legal determination for your counsel. The 8 Exceptions The rule defines eight exceptions in two groups. We help you implement the technical and workflow conditions each requires; whether a given practice qualifies is a legal call. Exceptions for Not Fulfilling a Request (5) Exceptions for the Manner of Fulfilling a Request (3) Our Info Blocking Compliance Approach Practice Discovery & Gap Assessment We inventory your data-sharing practices and identify where information blocking risk exists. Exception Framework Implementation We implement the technical and operational conditions your relied-upon exceptions require. Policy & Procedure Development We help develop the supporting policies and procedures, in coordination with your compliance team and counsel. Technical Workflow Design We design the access, API, and request-handling workflows so sharing is the default and exceptions are applied deliberately — built on our FHIR API development work. Training & Documentation We build the documentation and support the training so decisions are recorded and defensible. Info Blocking for Different Actors Healthcare Providers Providers must make EHI available and handle access requests without practices that interfere — with the right exceptions applied. Related: our ONC certification and CMS interoperability work. Health IT Developers Developers of certified health IT must not design or operate products in ways that block information, and must support standardized access (e.g., APIs). HIEs / HINs Networks and exchanges must not impose practices that interfere with exchange across their participants. Common Practices That Trigger Info Blocking Concern The recurring risk areas: data access fees that do not meet the Fees exception, information withholding without a valid exception, API throttling that impedes access, and onerous patient workflows that effectively block patient access. We assess each against the rule. Enforcement & Penalty Risk Enforcement is active. Developers, HINs, and HIEs face OIG civil monetary penalties (up to $1 million per violation), and providers face disincentives under the separate provider rule. Enforcement actions have begun under these frameworks; rather than cite specific cases that may be mischaracterized, we focus on reducing your risk to the point where enforcement is not a concern. Your counsel advises on legal exposure. Frequently Asked Questions Can we still charge for some data access? Sometimes. The Fees exception permits certain fees that meet its conditions, but it does not cover things that must be provided without special charge, such as a patient’s access to their own EHI. Whether a specific fee qualifies is a legal determination; we build the workflows and documentation to support fees that your counsel confirms are permissible. What about competitor data requests? The rule is specifically concerned with anti-competitive withholding, so declining a legitimate request simply because the requester is a competitor is risky. The Licensing and Content-and-Manner exceptions govern how you may respond on reasonable terms. We implement compliant request-handling; the legal line on a given request is for your counsel. Documentation requirements? Documentation is central, because exception reliance has to be demonstrable. We build the tooling to record your practices, the exceptions relied upon, and the basis for decisions, so you can show your reasoning if questioned. How to handle patient consent? Patient access to their own EHI generally must be fulfilled, while the Privacy exception governs situations where law or required consent applies. We build consent and access workflows consistent with that, in line with our data security and HIPAA-compliant development practices, with your counsel confirming the legal treatment. Schedule an Info Blocking Compliance Assessment (Free 45-Min) → Reviewed by Taction Software’s healthcare regulatory implementation team. ISO 27001-certified information security management. This is technical and workflow implementation support, not legal advice; legal determinations rest with your compliance team and counsel. PHI is handled under a signed BAA.