1upHealth has become a go-to FHIR platform for payers facing CMS interoperability deadlines and for any organization that needs to aggregate member data across sources. But a platform is only as good as its implementation — the FHIR profiles, the identity resolution, the Cures Act APIs, and the architecture around it all have to be engineered correctly. Taction Software implements and integrates 1upHealth for payers and health-tech companies: Cures Act API implementation, member data aggregation, FHIR profile work, and the custom integration layer around the platform. Schedule a 1upHealth Implementation Strategy Call → (NDA-protected) FHIR specialist team · payer-tech experience · HIPAA + BAA When 1upHealth Is the Right Choice Cures Act Compliance for Payers 1upHealth is especially strong for payers implementing the CMS interoperability APIs on a deadline — see our overview of 21st Century Cures Act compliance and our payer software development practice. Member Data Aggregation Use Cases When you need to aggregate member data across many sources into a longitudinal record, 1upHealth’s FHIR-first model fits well. FHIR-First Architecture If your architecture is FHIR-first, 1upHealth aligns naturally with it, building on our FHIR API development work. Patient Access API Implementation For the Patient Access API specifically, 1upHealth provides a strong foundation to implement against. Our 1upHealth Implementation Capabilities Cures Act API Implementation Patient Access API (CARIN Blue Button), Provider Directory API (Da Vinci PDex), and the Bulk Data API — the CMS-mandated interfaces, implemented to spec. Member Data Aggregation Multi-source FHIR aggregation, patient identity resolution across sources, and longitudinal record building so member data forms one coherent picture. FHIR Custom Profile Implementation US Core profile implementation, Da Vinci and CARIN profile implementation, and custom extensions for data the standard profiles do not cover. Common 1upHealth Use Cases We Build For We build for payer Cures Act compliance, member engagement platforms, care coordination across EHRs, and data aggregation for analytics (connecting to our healthcare data analytics work). 1upHealth vs. Alternatives 1upHealth vs. Redox 1upHealth is FHIR-data-centric and strong for payer and aggregation use cases; Redox is oriented toward broad EHR connectivity across health systems. The right choice follows your primary use case, and some organizations use both. 1upHealth vs. Particle Health Particle Health emphasizes network-based record retrieval, while 1upHealth emphasizes a FHIR data platform and Cures Act APIs. We help you match the platform to your data model. 1upHealth vs. Build Your Own FHIR Server Building your own FHIR server gives maximum control but maximum responsibility. 1upHealth trades some control for speed and managed infrastructure. We help you decide honestly — and build either way. Engagement Options We work in three common shapes: an initial 1upHealth implementation, Cures Act compliance engineering, and 1upHealth plus a custom integration layer for the logic the platform does not cover — all on our custom healthcare software foundation. Schedule a 1upHealth Implementation Strategy Call → Frequently Asked Questions Should we use 1upHealth or build our own? Use 1upHealth when speed to Cures Act compliance and managed FHIR infrastructure matter more than full control; build your own when you need deep control or capabilities a platform will not give you. We give you an honest read on the trade-off and can deliver either path. Can you help with our Cures Act compliance? Yes. We implement the CMS interoperability APIs on 1upHealth — Patient Access (CARIN Blue Button), Provider Directory (Da Vinci PDex), and Bulk Data — and sequence the work against the compliance dates. How do you handle patient identity resolution? We implement identity resolution that matches and merges records for the same patient across sources, so multi-source aggregation produces one accurate longitudinal record rather than fragmented duplicates. What about 1upHealth performance at scale? We architect the integration around the platform — caching, bulk processing, and efficient query patterns — so performance holds up as data volume and member counts grow, and we monitor it in production. Schedule a 1upHealth Implementation Strategy Call → Reviewed by Taction Software’s healthcare integration engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA — see our HIPAA-compliant development and data security practices.

Redox makes EHR integration dramatically easier than building point-to-point interfaces to every health system — but “easier than the alternative” is not the same as “easy.” Mapping your data model to Redox’s, designing event subscriptions, handling errors at scale, and architecting cleanly around the platform still take real integration engineering. Taction Software implements, scales, and optimizes Redox for health-tech vendors and provider organizations: source and destination configuration, data-model mapping, production deployment, and the integration architecture around Redox. Schedule a Redox Integration Strategy Call → (NDA-protected) Redox specialist team · EHR integration credentials · health-tech client work · HIPAA + BAA When You Need Redox Integration Help First Redox Implementation Your first Redox implementation sets patterns you will live with for years. Getting the data-model mapping and architecture right early avoids expensive rework. Scaling Beyond Initial Implementation What worked for the first few connections often strains as you add health systems and data volume. We help you scale Redox cleanly. Migrating to Redox From Direct EHR Integration Moving from a tangle of direct HL7 and FHIR interfaces to Redox is a real migration that benefits from experienced hands. Complex Multi-Source / Multi-Destination Architecture When you are routing data across many sources and destinations, the architecture around Redox becomes the hard part — and the part we specialize in. Our Redox Implementation Capabilities Source & Destination Setup EHR connection configuration, mapping your data model to Redox data models, and an event subscription strategy that captures what you need without drowning in noise. Custom Data Model Implementation Working across the standard data models (PatientAdmin, Clinical Summary, Order, Results), plus custom field mapping and a sound extension strategy for the data those models do not cover cleanly. Production Deployment A real testing strategy, monitoring and alerting, and error handling and recovery so the integration is dependable in production, not just in a demo. Integration Architecture Around Redox Microservice design, idempotency and retry logic, and webhook handling — the engineering that makes Redox robust inside your system, built on our custom healthcare software practice. Common Redox Implementation Challenges We Solve We are most often brought in for data-model mapping edge cases, performance and scaling, error handling at scale, and migration from existing direct EHR integrations — the problems that surface once Redox is past the first happy-path connection. Redox vs. Direct EHR Integration When Redox Is the Right Choice Redox is usually right when you need to connect to many health systems quickly and want to offload the per-EHR connection burden. When Direct Integration Makes More Sense Direct integration — including via our Epic integration work — can make more sense for deep, specific integration with a small number of EHRs, or where you need capabilities beyond what the platform exposes. Hybrid Approaches Often the right answer is hybrid: Redox for breadth, direct integration where depth matters. We help you draw that line deliberately. Redox + Custom Integration Layer Building an Abstraction Layer Above Redox We build an abstraction layer above Redox so your application is insulated from platform specifics and easier to evolve. Multi-Platform Strategy (Redox + Direct) We design multi-platform strategies that combine Redox with direct integration behind one internal interface. Data Lake Integration We route integrated data into your data lake or warehouse for analytics and downstream use. Engagement Options We work in four common shapes: an initial Redox implementation, Redox optimization and scaling, a direct-to-Redox migration, and ongoing Redox operations support. Schedule a Redox Integration Strategy Call → Frequently Asked Questions Should we use Redox or integrate directly? It depends on breadth versus depth. Redox is usually the better choice when you need to connect to many health systems quickly; direct integration can win when you need deep, specific integration with a few EHRs or capabilities beyond the platform. We frequently recommend a hybrid, and we will give you an honest read for your situation. Can you migrate our existing EHR integrations to Redox? Yes. We migrate direct HL7 and FHIR integrations to Redox, mapping your existing data flows onto Redox’s data models, validating parity, and cutting over without losing data continuity. Do you handle Redox onboarding for new health systems? Yes. We manage the configuration and data-model mapping for onboarding new health system connections through Redox, and build the monitoring so you know each connection is healthy. What about Redox vs. 1upHealth vs. Particle? Each platform has a different strength — Redox for broad EHR connectivity, 1upHealth for FHIR-centric data, and Particle Health for network-based record retrieval. The right choice depends on your data needs and connectivity model, and some organizations use more than one. We help you choose and implement, and can build for these alternatives as well. Schedule a Redox Integration Strategy Call → Reviewed by Taction Software’s healthcare integration engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA — see our HIPAA-compliant development and data security practices. For interface-engine work, see our Mirth Connect integration practice.

Utilization management is being forced to modernize on a deadline. The CMS Prior Authorization Final Rule, provider outcry over prior-auth friction, and rising expectations for real-time decisions are pushing payers off legacy UM systems. Taction Software builds custom utilization management software — prior authorization, concurrent and retrospective review, appeals, and the Da Vinci PA APIs — for payers, TPAs, and UM vendors that need to modernize before the rule lands and reduce the friction that providers and members feel. Schedule a UM Software Strategy Workshop → (NDA-protected) Da Vinci PA expertise · FHIR specialist team · payer-tech experience · HIPAA + BAA Why UM Software Is Being Forced to Modernize CMS Prior Authorization Final Rule (Effective 2027) The CMS Interoperability and Prior Authorization Final Rule introduces API and decision-timeframe requirements, with the Prior Authorization API requirement effective in 2027. It is the clearest forcing function UM has seen — see our overview of 21st Century Cures Act compliance. Provider Abrasion & Outcry Prior authorization is the single biggest source of provider friction with payers. Modern UM software that reduces that abrasion is now a competitive and regulatory priority. AI-Enabled UM Capabilities AI can take work off reviewers and speed clear-cut decisions, which is reshaping what a UM platform is expected to do. Real-Time Processing Expectations Providers and members increasingly expect near-real-time decisions, which legacy batch-oriented UM systems cannot deliver. UM Software Capabilities We Build Prior Authorization Workflows Provider submission portals, auto-approval logic for requests that clearly meet criteria, clinical review workflows, and decision support for reviewers — the heart of a modern PA system. Concurrent & Retrospective Review Length-of-stay management, medical necessity review, and discharge planning coordination for inpatient and post-acute oversight. Appeals & Grievances Multi-level appeals workflows, documentation aggregation, and timely-resolution tracking so appeals are handled correctly and within required timeframes. Care Management Integration Case management handoff and high-cost claimant workflows so UM connects to the rest of the plan’s clinical operations. Da Vinci PA API Implementation We implement the Da Vinci prior-authorization API suite that the CMS rule and the market are converging on: Coverage Requirements Discovery (CRD), Documentation Templates and Rules (DTR), Prior Authorization Support (PAS), and the provider EHR integration that makes them usable in the clinician’s workflow — built on our FHIR API development and HL7 work. AI-Enabled UM AI-Assisted Medical Necessity Review We build AI that assists reviewers — surfacing relevant clinical information and flagging where criteria are or are not met. Adverse and denial determinations remain with qualified clinical reviewers; AI assists, it does not autonomously deny. Documentation Summarization for Reviewers We build documentation summarization so reviewers spend less time hunting through records, drawing on our clinical NLP and payer AI work. Auto-Approval Logic with AI We build auto-approval for requests that clearly meet criteria, so straightforward cases clear quickly and reviewers focus on the ones that need judgment. Integration We integrate UM with the rest of the payer stack: core administrative system integration, provider EHR integration via FHIR, member portal integration, and care management system integration, so UM is connected rather than siloed. Engagement Models We work in four common shapes: a custom UM platform for a payer or TPA, UM SaaS product development, Da Vinci PA compliance engineering, and legacy UM modernization (see our software modernization practice). For the broader payer stack, see our payer software development and value-based care work. Schedule a UM Software Strategy Workshop → Frequently Asked Questions Are you ready for the CMS PA Final Rule 2027? Yes. We build the prior-authorization APIs and decision workflows the rule requires, including the Da Vinci PA suite and the Prior Authorization API effective in 2027, and help you sequence the work to be ready ahead of the deadline. Do you implement Da Vinci PA APIs? Yes. We implement Coverage Requirements Discovery (CRD), Documentation Templates and Rules (DTR), and Prior Authorization Support (PAS), with provider EHR integration so they work in the clinician’s workflow. Can you integrate with our existing core admin? Yes. We integrate UM with your existing core administrative / claims system rather than requiring replacement, building the PA, review, and appeals workflows around the core you already run. What about AI-enabled medical necessity? We build AI to assist reviewers — summarizing documentation, surfacing relevant evidence, and auto-approving requests that clearly meet criteria. Denials and adverse determinations stay with qualified clinical reviewers; the AI accelerates the work and supports the decision rather than making it autonomously. Schedule a UM Software Strategy Workshop → Reviewed by Taction Software’s payer technology and healthcare integration engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA — see our HIPAA-compliant development and data security practices.

An accountable care organization has a problem no single EHR solves: it has to operate across many member practices on many different EHRs, aggregate that data into one population view, and manage quality and financial performance against its risk contracts. Taction Software builds custom ACO software — multi-EHR data aggregation, population management, quality reporting, care coordination, and shared-savings financials — for ACO operators and ACO enabler vendors running MSSP, ACO REACH, and commercial programs. ACO software is the entity-specific build. For the broader value-based-care platform view across risk models, see our value-based care software development practice. Schedule an ACO Software Discovery Call → (NDA-protected) ACO domain expertise · CCLF & CMS data experience · multi-EHR integration credentials · HIPAA + BAA What ACO Software Must Do That Generic EHRs Can’t Multi-Site, Multi-EHR Data Integration An ACO’s member practices run different EHRs. The defining ACO software challenge is aggregating all of that into one coherent dataset — something a single EHR cannot do by design. Attribution Across Care Delivery Sites The ACO must know which beneficiaries it is accountable for across every site, and keep that attribution current as data and rosters change. Population-Level Quality & Performance Quality and performance have to be measured across the whole attributed population, not practice by practice. Financial Performance Across Risk Contracts The ACO manages shared-savings and risk performance against CMS and commercial benchmarks — financial tracking generic EHRs do not provide. ACO Software Components We Build Multi-EHR Data Aggregation FHIR-based EHR integration across member practices, a master patient index to resolve identity across systems, and data normalization across sources — built on our FHIR API and HL7 work. This is the foundation everything else depends on. Population Management Patient attribution, risk stratification, care-gap identification, and patient outreach workflows, drawing on our healthcare data analytics. Quality Reporting MIPS APP reporting, MSSP quality reporting, ACO REACH quality reporting, and custom commercial quality — the reporting that determines ACO success. Financial Performance Shared-savings modeling, benchmark-year calculation, and per-beneficiary cost tracking so the ACO can see and manage its position against every contract. Care Coordination Care-team workflows, transition-of-care tracking, and post-acute coordination, connecting to our chronic care management work. ACO Programs Supported We support MSSP (all tracks, BASIC and ENHANCED), ACO REACH, Medicare Advantage ACOs, commercial ACO contracts, and Medicaid ACO programs — accommodating the distinct rules of each. Data Sources We Integrate We bring together everything the ACO needs to see the whole population: CMS CCLF files, member EHRs (multi-vendor), HIE data feeds, payer claims and ERAs, and ADT notifications for real-time event awareness. Engagement Options We work in four common shapes: a custom ACO platform build, ACO enabler SaaS development, an ACO quality-reporting engine, and ACO modernization of an aging platform (see our software modernization practice). For payer-side technology, see our payer software development work. Schedule an ACO Software Discovery Call → Frequently Asked Questions Can you integrate with our member practices’ EHRs? Yes — this is the core of ACO software. We aggregate data across your member practices’ EHRs via FHIR and HL7, resolve patient identity with a master patient index, and normalize it into one population dataset, regardless of how many EHR vendors are in your network. How do you handle CCLF files? We ingest CMS Claim and Claim Line Feed (CCLF) files and combine them with your member-EHR and HIE data, so attribution, quality, and shared-savings calculations run on the full claims-plus-clinical picture rather than claims alone. Do you support ACO REACH quality? Yes. We build ACO REACH quality reporting alongside MSSP (via the APM Performance Pathway) and commercial quality reporting, computing the measures from your aggregated population data. Can you build for ACO enabler vendors? Yes. We build platforms for ACO enabler companies that serve multiple ACOs, with the multi-tenant, multi-program flexibility that requires, as well as custom platforms for individual ACO operators. Schedule an ACO Software Discovery Call → Reviewed by Taction Software’s value-based care and healthcare data engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA — see our HIPAA-compliant development and data security practices.

Value-based care runs on capabilities fee-for-service EHRs were never built to provide — patient attribution, population stratification, quality-measure computation at scale, risk adjustment, and financial performance against multi-payer risk contracts. Taction Software builds custom value-based care software for ACOs, VBC enablers, and risk-bearing organizations: attribution and population management, quality platforms, HCC risk adjustment, and shared-savings and capitation financials — with the CMS data-file and FHIR engineering VBC actually requires. Schedule a VBC Software Discovery Call → (NDA-protected) VBC domain expertise · CMS data file experience (CCLF, RIF) · FHIR & HL7 expertise · HIPAA + BAA Why VBC Needs Different Software Fee-for-Service EHRs Aren’t Built for Risk EHRs are built to document and bill encounters, not to manage a population under risk. VBC organizations consistently hit that wall and need software designed for risk, not visits. Attribution & Population Identification Knowing exactly which patients you are accountable for — and keeping that current across payers — is foundational to VBC and absent from most EHRs. Quality Measure Computation at Scale VBC lives or dies on quality measures computed accurately across the whole attributed population, drawing on data the EHR alone does not hold. Multi-Payer Risk Contract Management VBC organizations operate multiple risk contracts at once, each with its own terms, benchmarks, and reconciliation — which requires purpose-built contract and financial tooling. VBC Software Solutions We Build Attribution & Population Management Patient attribution engines, population stratification, and care-gap identification, drawing on our healthcare data analytics work. Quality Measure Platforms eCQM computation, MIPS / MSSP quality reporting, and custom quality-measure development for commercial contracts. Risk Adjustment & HCC HCC coding workflows, suspecting and validation, and year-over-year RAF optimization, complementing our AI medical coding and payer AI capabilities — done compliantly, supported by documentation. Financial Performance Management Contract modeling, shared-savings calculation, and capitation reconciliation so you can see and manage performance against every risk arrangement. Care Management Workflows Care-plan authoring, care-team coordination, and SDoH integration, connecting to our chronic care management work. VBC Programs Our Software Supports We support Medicare Shared Savings Program (MSSP), ACO REACH (which succeeded the Direct Contracting model), Medicare Advantage, commercial VBC contracts, and Medicaid value-based purchasing — accommodating the rules and benchmarks of each. Data Integration for VBC VBC is a data-integration problem before it is anything else. We ingest claims data (837/835, CCLF, RIF), integrate EHR data via FHIR, consume HIE and ADT feeds via our HL7 integration work, and reconcile payer roster and eligibility — assembling the complete picture an attributed population requires. Quality Reporting APP (APM Performance Pathway) We build reporting through the APM Performance Pathway, the route MSSP ACOs now use for quality reporting. eCQM / MIPS CQM Reporting We compute and report electronic clinical quality measures and MIPS CQMs. (Note: the CMS Web Interface reporting option has been sunset, so we build toward eCQM/CQM digital reporting rather than the retired interface.) Quality Payment Program We support Quality Payment Program reporting requirements for participating organizations. Custom Commercial Quality Reporting We build custom quality reporting for commercial VBC contracts that define their own measures. Engagement Models We work in three common shapes: a custom VBC platform for an ACO or enabler, VBC SaaS product development, and quality-measure engineering — all on our custom healthcare software foundation. For payer-side technology, see our payer software development practice. Schedule a VBC Software Discovery Call → Frequently Asked Questions Can you integrate with our EHR and payers? Yes. We integrate EHR data via FHIR, ingest payer claims files (837/835, CCLF, RIF), consume HIE and ADT feeds, and reconcile payer roster and eligibility, so your VBC platform sees the complete population across sources. Do you handle CCLF files? Yes. CMS Claim and Claim Line Feed (CCLF) files are core to ACO data, and we ingest and process them — along with RIF and standard EDI claims — into your attribution, quality, and financial workflows. How do you handle attribution? We build attribution engines that apply the program’s attribution methodology (MSSP, REACH, commercial) to claims and eligibility data, keep it current as data refreshes, and make the attributed population the basis for quality and financial computation. What about HCC coding workflows? We build HCC risk-adjustment workflows — suspecting, validation, and year-over-year RAF management — done compliantly so conditions captured are supported by documentation, and we can pair this with AI assistance where it helps. Schedule a VBC Software Discovery Call → Reviewed by Taction Software’s value-based care and healthcare data engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA — see our HIPAA-compliant development and data security practices.

Payer technology is one of the highest-stakes, highest-budget corners of healthcare software — claims at scale, member and provider engagement, prior authorization, utilization management, and a wave of CMS interoperability mandates landing on tight deadlines. Taction Software builds custom payer software for health plans, TPAs, PBMs, and payer-tech vendors: member and provider platforms, claims and adjudication, prior authorization and UM, and Cures Act / CMS interoperability APIs — with deep X12 EDI and FHIR engineering. For AI-specific payer capabilities — risk models, claims AI, automation — see our payer AI work. This page covers the broader payer software build. Schedule a Payer Software Discovery Call → (NDA-protected) Payer-tech experience · X12 EDI expertise · FHIR & Cures Act specialist · HIPAA + BAA Payer Software Solutions We Build Member Engagement Platforms Member portals, mobile apps (via our mobile app development practice), cost transparency tools, and the Patient Access API (CARIN Blue Button) that the CMS rules require. Provider Engagement Platforms Provider portals, the Provider Directory API (Da Vinci PDex), network management, and credentialing — the provider-facing side of the plan. Claims Processing & Adjudication EDI 837/835 processing, claims adjudication engines, and fraud detection — the operational core, built on our HL7 and integration engineering. Prior Authorization PA workflow automation, the Da Vinci CRD, DTR, and PAS APIs, and provider submission portals — increasingly mandated and increasingly automated. Utilization Management UM workflow, medical necessity determination, and appeals management for the clinical-review side of the plan. Cures Act / CMS Interoperability Compliance Patient Access API (CARIN BB) We build the Patient Access API to the CARIN Blue Button implementation guide, so members can access their claims and clinical data through third-party apps. Provider Directory API (Da Vinci PDex) We build the Provider Directory API to the relevant Da Vinci guides. Payer-to-Payer Data Exchange We build payer-to-payer data exchange so member data follows them between plans, as the rules intend. Prior Authorization API (phasing in by 2027) We build toward the CMS Interoperability and Prior Authorization Final Rule, including the Prior Authorization API, whose requirements phase in by 2027 — see our overview of 21st Century Cures Act compliance. Payer Market Segments We Serve We build for commercial health plans, Medicare Advantage, Medicaid managed care, third-party administrators (TPAs), and pharmacy benefit managers (PBMs) — each with its own regulatory and operational profile. Integration Standards We work across the payer integration stack: X12 EDI (837, 835, 270/271, 276/277, 278), HL7 FHIR for the Cures Act APIs (built on our FHIR API development), the Da Vinci implementation guides, and the CARIN Alliance implementation guides. Modernization for Legacy Payer Systems Legacy Mainframe Migration We modernize legacy mainframe payer systems incrementally, preserving the business logic that runs the plan — see our software modernization practice. Claims Adjudication Modernization We modernize claims adjudication so it is faster, more transparent, and easier to maintain. Data Warehouse Modernization We modernize payer data warehouses to support analytics, reporting, and the interoperability APIs. Engagement Models We work in four common shapes: a custom payer platform build, Cures Act compliance engineering, legacy payer system modernization, and payer-tech SaaS product development — all on our custom healthcare software foundation. Schedule a Payer Software Discovery Call → Frequently Asked Questions Are you Cures Act compliance ready? Yes. We build the CMS interoperability APIs — Patient Access (CARIN Blue Button), Provider Directory (Da Vinci PDex), payer-to-payer exchange, and the Prior Authorization API phasing in by 2027 — to the relevant implementation guides, and help you sequence the work against the compliance dates. Can you work with our existing core admin system? Yes. We integrate with your existing core administrative / claims system rather than assuming a rip-and-replace, building member and provider platforms, APIs, and automation around the core you already run. Do you handle X12 EDI? Yes. X12 EDI is core to payer integration — 837, 835, 270/271, 276/277, and 278 — and we build and integrate these transactions alongside the FHIR-based Cures Act APIs. Have you worked with TPAs and PBMs? Yes. We build for TPAs and PBMs as well as health plans, accommodating the distinct workflows — administrative services, pharmacy benefits, and the integrations each requires. Schedule a Payer Software Discovery Call → Reviewed by Taction Software’s payer technology and healthcare integration engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA — see our HIPAA-compliant development and data security practices.

AI medical coding has crossed from hype into production, and the economics are hard to ignore: coding is high-volume, labor-intensive, and increasingly hard to staff. Taction Software builds custom AI medical coding — autonomous and computer-assisted coding across ICD-10, CPT, HCC, and DRG — for health systems, revenue cycle companies, and payers that want to cut coding cost and turnaround without sacrificing accuracy or compliance. We build with confidence-based routing and human-in-the-loop review, so automation earns trust instead of creating audit risk. For the deeper analysis behind this, see our article on AI medical coding and CDI with LLMs. This page is about building the software. Schedule an AI Coding ROI Workshop → (NDA-protected) AI coding specialist team · medical coding domain expertise · EHR & RCM integration experience · HIPAA + BAA Why AI Medical Coding Is Now Production-Ready LLM Advances Enable Production Accuracy Modern LLMs, combined with retrieval and validation, reach accuracy levels on many coding tasks that earlier rule-based and statistical systems could not — moving AI coding from assistive novelty to production tool. This builds on our clinical NLP and healthcare RAG work. Labor Cost Pressures Driving Demand Coder shortages and rising labor cost make manual-only coding harder to sustain, pushing organizations toward automation that augments their teams. Documentation Quality Improvements AI coding tightens the loop between documentation and codes, surfacing documentation gaps that affect both compliance and reimbursement. Speed-to-Bill Acceleration Faster, more consistent coding shortens the time from encounter to bill, improving cash flow. AI Coding Solutions We Build Autonomous Coding High-confidence auto-coding, confidence-based routing, and human-in-the-loop for low confidence — so the system codes what it can defend automatically and routes the rest to coders, rather than forcing risky end-to-end automation. Computer-Assisted Coding (CAC) Code suggestions in the coder workflow, documentation-improvement hints, and compliance review that make existing coders faster and more accurate. HCC Risk Adjustment Coding Risk Adjustment Factor (RAF) optimization, suspect condition identification, and retrospective and prospective workflows, complementing our payer AI work — done compliantly, capturing conditions that are genuinely supported by documentation. Clinical Documentation Improvement (CDI) Specificity querying and compliance and severity capture so documentation supports correct codes and severity. Code Sets We Cover We cover the full coding surface: ICD-10-CM (diagnosis), ICD-10-PCS (inpatient procedure), CPT-4 (outpatient procedure), HCPCS Level II, HCC (risk adjustment), and MS-DRG and APR-DRG. Coding Specialties Supported We support inpatient coding, outpatient and profee coding, emergency department coding, radiology coding, anesthesia coding, and risk adjustment coding — each with its own rules and documentation patterns. Accuracy, Validation, & ROI Accuracy Benchmarking Methodology We benchmark accuracy on your own data against expert-coded references, by specialty and code set, so you know real performance before you rely on it — not a vendor’s headline number. Audit & QA Workflows We build audit and QA workflows so coded output is continuously sampled and reviewed, keeping accuracy and compliance visible over time. ROI Calculation Framework We model ROI with you based on your volume, current coding model, and case mix. AI coding can substantially reduce cost-per-chart and turnaround, but the real number depends on your specifics — so we estimate it honestly rather than promising a fixed percentage. Integration We integrate with EHRs (Epic, Cerner, athenahealth) via our Epic integration and HL7 work, with RCM systems, and with HIM workflows, so AI coding fits into your revenue cycle rather than bolting on beside it. All built on our custom healthcare software foundation. Schedule an AI Coding ROI Workshop → Frequently Asked Questions How accurate is AI coding? Accuracy varies by specialty, code set, and documentation quality, so a single headline number is misleading. We benchmark on your data against expert-coded references and design confidence-based routing so only high-confidence codes are applied automatically, with the rest going to your coders. Will it replace our coders or augment them? For most organizations, augment. The reliable model today is autonomous coding for high-confidence cases plus human-in-the-loop for the rest, which raises throughput and consistency while keeping coders on the judgment-heavy work. We design to your risk tolerance. How is it different from existing CAC tools? Traditional CAC suggests codes from rules and templates. Modern AI coding uses LLMs with retrieval and validation for stronger suggestions and, where confidence supports it, autonomous coding with audit trails — not just hints in the coder’s screen. What’s the ROI? ROI is driven by your coding volume, current model (internal, outsourced, or hybrid), and case mix. We build an ROI estimate with you in the workshop rather than quoting a generic figure, because the savings that matter are yours, not an average. Can we deploy on-premises? Yes. Where data cannot leave your environment, we deploy on-premises or in your private cloud, drawing on our on-prem LLM work. Schedule an AI Coding ROI Workshop →Reviewed by Taction Software’s healthcare AI and revenue-cycle engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA — see our HIPAA-compliant development and data security practices.

Clinical decision support is in the middle of an AI-driven renaissance — and a hard-won lesson. The first generation of CDSS drowned clinicians in alerts and trained them to ignore it. Modern CDS is different: context-aware via CDS Hooks, AI-augmented, and designed to fit the workflow rather than interrupt it. Taction Software builds clinical decision support — rule-based and AI-powered, embedded via CDS Hooks and SMART on FHIR — for health-tech companies building CDS products and health systems building internal CDSS, with clinical informatics input and FDA-aware engineering. Schedule a CDS Strategy Workshop → (NDA-protected) Clinical informatics input · FDA-aware engineering · healthcare AI credentials · EHR integration experience Modern CDS: Beyond Alert Fatigue Why Traditional CDSS Failed (Alert Fatigue) First-generation CDSS fired too many low-value alerts, so clinicians learned to dismiss them. Any modern CDS effort has to start by taking alert fatigue seriously — see our perspective on AI-powered clinical decision support. Context-Aware CDS via CDS Hooks CDS Hooks lets decision support fire at the right moment in the workflow — patient view, order select, order sign — with relevant, contextual guidance instead of blanket alerts. AI-Augmented Decision Support AI extends CDS from static rules to risk prediction and pattern recognition, drawing on our healthcare RAG and clinical NLP capabilities — always with the clinician in the loop. Embedded vs. Standalone CDSS We build CDS embedded directly in the EHR workflow and standalone CDSS accessed alongside it, depending on your use case and integration constraints. CDS Solutions We Build Rule-Based CDSS Clinical logic authoring, knowledge base management, and versioning and change control — the backbone of transparent, auditable decision support. AI-Powered Clinical Decision Support Risk prediction models, diagnostic support models, and treatment recommendation models, built with validation and clinician oversight rather than black-box automation. CDS Hooks Integration EHR integration via CDS Hooks, custom card UI design, and workflow integration (order sign, patient view) so guidance appears at the right decision point. Clinical Quality Measure Computation eCQM implementation and real-time quality reporting so quality measurement is built into the same system. FDA Considerations for AI CDSS FDA SaMD Framework For CDS that is regulated as software as a medical device, we engineer within the FDA SaMD framework — risk classification, design controls, and validation. 21st Century Cures Act CDS Carve-Out Some clinical decision support qualifies for the Cures Act CDS exemption from device regulation when it meets the statutory criteria, including that the clinician can independently review the basis. We design with that distinction in mind so it is clear which side of the line your product sits on. PCCP (Predetermined Change Control Plan) For AI/ML-based CDS, we account for the FDA’s Predetermined Change Control Plan approach so models can be updated within an agreed, pre-cleared envelope. Validation & Verification Requirements We build the validation and verification, and the documentation, that regulated CDS requires and that reviewers expect. EHR Integration for CDSS We integrate CDS through CDS Hooks, SMART on FHIR apps, native EHR integration (Epic, Cerner) via our Epic integration and HL7 work, and API-based integration — all built on our FHIR API development and custom EHR foundations. Clinical Domains We’ve Built CDS For We have built decision support across domains including sepsis prediction and alerting, risk stratification (readmission, mortality), medication safety, imaging triage and prioritization, antibiotic stewardship, and behavioral health risk (see our behavioral health software work) — each with appropriate validation and clinician oversight. CDS Development Process Clinical Discovery & Domain Expert Engagement We start with clinical discovery and domain-expert engagement, because CDS that ignores clinical reality fails no matter how good the engineering is. Model Development & Validation We develop and validate the logic or models against clinically reviewed data. Workflow Integration Design We design how the guidance fits the workflow, so it informs decisions without adding noise. EHR Integration Engineering We engineer the EHR integration via CDS Hooks, SMART on FHIR, or native paths. Clinical Pilot & Validation We pilot in a real clinical setting and validate performance and workflow fit before scaling. Production Deployment We deploy to production with monitoring, under our HIPAA-compliant development and data security practices. Schedule a CDS Strategy Workshop → Frequently Asked Questions Do you handle FDA submission? We build SaMD-aware software and the validation and documentation that support an FDA submission, and we help you understand whether your CDS is regulated or qualifies for the Cures Act CDS carve-out. The submission itself is led by you and your regulatory advisors; we are not a regulatory consultancy. How do we avoid alert fatigue? By treating it as a design constraint from the start: firing guidance only at the right workflow moment via CDS Hooks, tuning thresholds to clinically meaningful events, suppressing low-value and duplicate alerts, and validating with clinicians that the signal is worth the interruption. Can you integrate with Epic and Cerner? Yes. We integrate via CDS Hooks, SMART on FHIR, and native EHR paths with Epic and Cerner, with the specifics depending on your access agreements with the EHR vendors. What about validation studies? We build the validation into the development process — validating logic and models against clinically reviewed data and piloting in a real setting before scaling. For regulated CDS, we structure validation and verification to support your regulatory pathway. Schedule a CDS Strategy Workshop → Reviewed by Taction Software’s healthcare AI and clinical informatics engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA. For broader AI work, see our healthcare AI solutions.

Retrieval-augmented generation has become the dominant pattern for production healthcare AI — because it grounds the model in real sources, keeps knowledge current, and makes outputs auditable and citable. But healthcare RAG is unforgiving: chunk clinical documents wrong, retrieve poorly, or skip evaluation, and you ship something that sounds confident and is sometimes wrong. Taction Software builds production-grade healthcare RAG — clinical document ingestion, retrieval, grounded generation, and citation — for health-tech companies and provider organizations that need AI they can actually trust and defend. Schedule a Healthcare RAG Architecture Workshop → (NDA-protected) LLM & RAG engineering credentials · healthcare AI specialist team · HIPAA + BAA Why RAG Dominates Production Healthcare AI Hallucination Reduction with Source Grounding RAG grounds the model’s answers in retrieved source content, which substantially reduces hallucination compared to asking a model to answer from memory. Up-to-Date Clinical Knowledge RAG lets the system draw on current guidelines and documents without retraining the model every time knowledge changes. Auditability & Citation Because answers trace back to retrieved sources, RAG supports citation and audit — essential in healthcare, where you must be able to show where an answer came from. Customization Without Fine-Tuning RAG adapts the system to your knowledge base and content without the cost and complexity of fine-tuning a model. Our Healthcare RAG Architecture Document Ingestion & Processing Clinical document parsing, PHI redaction where needed, chunking strategies tuned for clinical content, and metadata enrichment — the foundation that determines retrieval quality. Vector Store & Retrieval Vector DB selection (Pinecone, Weaviate, pgvector, Qdrant), hybrid retrieval (vector + keyword), re-ranking models, and retrieval evaluation so the right content surfaces for every query. LLM Integration Prompt engineering for clinical context, context-window management, and multi-turn conversation handling to turn retrieved content into accurate, useful answers. Citation & Source Attribution Clinical source citation, confidence scoring, and an audit trail for AI outputs so every answer is traceable and defensible. Healthcare RAG Use Cases We Build We build clinical decision support chatbots (with clinician oversight — see our perspective on clinical decision support), patient-facing health Q&A (via our patient portal work), clinical knowledge base search, care-guideline compliance tools, and clinical trial eligibility matching — often combined with our clinical NLP capabilities. HIPAA Compliance for RAG Systems BAA-Covered LLM Providers We use LLM providers that will sign a BAA when PHI is processed in the cloud, and architect so PHI is handled correctly throughout. On-Premises RAG Deployment Where data cannot leave your environment, we deploy RAG fully on-premises or in your private cloud — drawing on our on-prem LLM work. PHI Handling in Retrieval We design how PHI is handled in ingestion and retrieval — including redaction where appropriate — so the retrieval layer does not become a compliance gap. Audit Logging Requirements We build the audit logging HIPAA expects around PHI access and AI outputs, consistent with our HIPAA-compliant development and data security practices. RAG Evaluation Framework Retrieval Quality Metrics (NDCG, MRR) We measure retrieval with metrics like NDCG and MRR, because if retrieval is weak, no amount of prompting fixes the answer. Generation Quality (Groundedness, Relevance) We evaluate generation for groundedness and relevance, so answers are supported by the retrieved sources and actually address the question. Production Monitoring We build production monitoring so quality is tracked over time and regressions are caught, not discovered by users. Engagement Models We work in three common shapes: a greenfield RAG system build, RAG integration into existing healthcare applications, and a RAG architecture review of a system you have already started — all within our broader healthcare AI and custom healthcare software work. Schedule a Healthcare RAG Architecture Workshop → Frequently Asked Questions RAG vs. fine-tuning for healthcare? For most healthcare applications, RAG is the better default: it grounds answers in sources, keeps knowledge current, and supports citation and audit. Fine-tuning helps with style, format, or narrow specialized behavior. They are complementary — we frequently use RAG as the backbone and fine-tuning selectively where it earns its cost. Which vector DB do you recommend? It depends on your scale, infrastructure, and compliance needs. We work with Pinecone, Weaviate, pgvector, and Qdrant, and recommend based on deployment model (especially on-premises requirements), scale, and how the vector store fits the rest of your stack — not a one-size answer. How do you prevent hallucinations? RAG itself reduces hallucination by grounding answers in retrieved sources. We strengthen that with strong retrieval and re-ranking, prompts that constrain the model to the retrieved context, citation and confidence scoring, and evaluation for groundedness, so unsupported answers are caught. On-prem or cloud RAG? Both are viable. Cloud is faster to build and scale; on-premises or private-cloud RAG is the answer when data cannot leave your environment. We architect for your compliance and data-sovereignty requirements either way. Schedule a Healthcare RAG Architecture Workshop → Reviewed by Taction Software’s healthcare AI engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA.

Most of the value in healthcare data is locked in unstructured text — clinical notes, discharge summaries, pathology reports, correspondence. Clinical NLP is how you unlock it: extracting structured, coded, analyzable information from narrative that was never designed for a machine to read. Taction Software builds custom clinical NLP — document summarization, auto-coding, social-determinants extraction, risk stratification, and more — for healthcare analytics teams, payer informatics groups, and research organizations that need production-grade medical text understanding. Schedule a Clinical NLP Use Case Workshop → (NDA-protected) ML & NLP engineering credentials · clinical validation input · HIPAA + BAA Use Cases for Clinical NLP Clinical Document Summarization Condensing long records and note histories into usable summaries for clinicians and downstream systems. ICD-10 / CPT / SNOMED Auto-Coding Extracting and suggesting codes from narrative documentation — see our perspective on AI medical coding. Social Determinants of Health (SDoH) Extraction Surfacing social-determinant signals buried in notes that structured fields rarely capture. Clinical Trial Eligibility Matching Matching patients to trial criteria by reading the unstructured record, not just the coded fields. Risk Stratification from Unstructured Notes Pulling risk signals out of narrative text to feed risk models and care management. Quality Measure Computation Computing quality measures that depend on information found only in free text, supporting your healthcare analytics. Our Clinical NLP Capabilities Foundation Model Approaches LLM-based NLP (GPT-4, Claude, Gemini), domain-adapted open source (Med-PaLM, ClinicalBERT, BioGPT), and hybrid approaches that combine the strengths of each for accuracy and cost control. Information Extraction Named entity recognition, relation extraction, temporal reasoning, and negation and uncertainty detection — the core extraction tasks clinical text demands. Terminology Mapping SNOMED CT, ICD-10, RxNorm, and LOINC mapping, plus custom ontology mapping, so extracted concepts are standardized and interoperable. Document Understanding Section-header detection, clinical document classification, and multi-document synthesis so the system understands structure, not just words. NLP for Specific Healthcare Workloads Payer Risk Adjustment NLP Extracting conditions from notes to support accurate, compliant risk adjustment — complementing our payer AI work. Clinical Quality Reporting NLP Reading narrative to compute and support quality reporting that coded data alone cannot. Pharmacovigilance & Adverse Event Detection Detecting adverse events and safety signals in clinical and post-market text. Real-World Evidence Generation Turning unstructured clinical data into structured inputs for real-world evidence studies. Productionizing Clinical NLP Performance & Accuracy Validation We validate NLP against held-out, clinically reviewed data, because a model that looks good in a demo is not the same as one that holds up in production. Bias & Fairness Testing We test for bias and fairness across populations, so the system does not encode or amplify disparities. Production Monitoring & Drift Detection We build monitoring and drift detection so accuracy is tracked over time and degradation is caught early. HIPAA-Compliant Deployment We deploy NLP under HIPAA safeguards, including on-premises where data cannot leave your environment — drawing on our on-prem LLM, HIPAA-compliant development, and data security practices. Engagement Models We work in three common shapes: custom NLP product development, NLP integration into existing platforms, and NLP research-to-production engineering — taking a promising research model and making it robust, validated, and deployable. This builds on our broader healthcare AI and custom healthcare software work. Schedule a Clinical NLP Use Case Workshop → Frequently Asked Questions LLM vs. traditional NLP for clinical text? Both have a place. LLMs are powerful for summarization, flexible extraction, and document understanding; traditional and domain-specific models can be more efficient, controllable, and auditable for high-volume, well-defined extraction. We frequently use a hybrid approach, choosing per task based on accuracy, cost, latency, and explainability needs. How do you handle medical jargon & abbreviations? We use clinically adapted models and terminology resources, and tune to your specialty and document types, so the system correctly interprets medical jargon, abbreviations, and context rather than guessing. What about negation and uncertainty? Negation and uncertainty are first-class concerns in clinical NLP — “no evidence of,” “rule out,” “possible.” We build explicit negation and uncertainty detection so extracted findings reflect what the note actually asserts. Can you train on our specific data? Yes. We adapt and, where appropriate, fine-tune models on your data under a signed BAA, with controls ensuring your data is not used to train third-party models and stays within your compliance boundary. Schedule a Clinical NLP Use Case Workshop → Reviewed by Taction Software’s healthcare AI and NLP engineering team. ISO 27001-certified information security management. PHI is handled under a signed BAA.