# Digital Scientists — Detailed Reference

> Digital Scientists is an innovation partner for firms executing on their innovation strategy. We take software and AI from prototype to production so it delivers measurable ROI, and clients own what we build. In business since 2007, based in Atlanta, Georgia, with US-based senior architecture and development. $20M+ verified client ROI, deep healthcare proof.

## About

Digital Scientists is an innovation partner for firms executing on their innovation strategy. We take software and AI from prototype to production so it delivers measurable ROI, and clients own what we build outright, including the code, IP, and roadmap. In business since 2007, based in Atlanta, Georgia. Our senior architecture and development team is US-based, most with 10 to 15 years of experience, and we bring in partners to scale as needed. For two decades we have helped clients from the Fortune 10 to startups deliver software that improves the human experience, with our deepest proof in healthcare: clinical documentation, revenue cycle management, virtual care and patient engagement, and clinical workflows.

We are not a staffing firm or a generalist consultancy. We are an innovation partner that takes software and AI from prototype to production and hands clients systems they own. We are accountable for outcomes from discovery through production.

## Problems We Solve

**Page:** https://digitalscientists.com/problems/

Six business problems clients hire Digital Scientists to solve. They are business problems, not
industries; the same six show up in healthcare, energy, logistics, defense and consumer.

- **New Product** (https://digitalscientists.com/problems/build-a-new-product/): "We have a product opportunity, but not the team to build it." An idea and no product team. A product team, ready now.
- **Roadmap Capacity** (https://digitalscientists.com/problems/increase-engineering-capacity/): "Our roadmap is committed. Our team is full." Approved work, no engineers. A second team that ships it.
- **Platform Modernization** (https://digitalscientists.com/problems/modernize-your-platform/): "Our business has outgrown our platform." A platform you've outgrown. Modernize while you operate.
- **Cost of Operations** (https://digitalscientists.com/problems/reduce-cost-of-operations/): "We need to do more work at a lower cost." Headcount grows with volume. AI does the routine work.
- **Product Competitiveness** (https://digitalscientists.com/problems/product-competitiveness/): "We're losing customers and deals we should be winning." Losing demos and clients. Fix what's losing the deal.
- **Innovation / R&D** (https://digitalscientists.com/problems/innovation-and-rd/): "How do we build what's next while delivering what matters now?" Ideas keep getting shelved. An R&D team beside yours.

### Questions buyers ask
Real questions from buyer calls, with the answers on each problem page.

**New Product** (https://digitalscientists.com/problems/build-a-new-product/)
- Q: Should we hire a CTO first or use a product development partner?
  A: Not before you know what the product is. One hire is not a product team, and your first technical hire is easier to get right once the product is defined. We stand in as the product team (research, design, architecture and engineering) while you prove the opportunity. You own the code and IP, and when you take it in-house, we help you hire and hand over.
- Q: Why do quotes to build our software product vary so much?
  A: Because each firm priced a different product. A spec, especially one drafted with an AI tool, reads complete before it is. It doesn’t settle what goes in version one, what to buy versus build, or what compliance will demand, and a fixed bid on those gaps comes back as change orders. A Blueprint settles them first and gives you a budget range you can defend.
- Q: What should the first version (MVP) of a new product include?
  A: An MVP is a market test, not a smaller product. Build only what tests the assumption that sinks the business if it’s wrong, and put it in front of buyers who would pay. Compliance your market requires goes in version one. It’s not a later feature. Most MVPs take 4 to 16 weeks.
- Q: Can we build the real product on top of our prototype?
  A: Use it as the brief, not the foundation. A prototype shows what you want the product to do. It doesn’t carry the workflows, data model and constraints the real product runs on. Bring it, with your specs or deck, to a Blueprint, and we turn it into the version a production team can build from.

**Roadmap Capacity** (https://digitalscientists.com/problems/increase-engineering-capacity/)
- Q: How do we bring in an outside development team without creating rework for our engineers?
  A: Rework happens when two teams end up building two versions of the product. We work inside your stack, your Jira and your review process, and we agree the integration points and release date with your engineers before we build. Your engineers review our code, so any mismatch shows up in week one, not at handoff.
- Q: Who owns the code when an outside firm builds part of our roadmap?
  A: You own all of it: the code, the documentation and the IP, in your own repositories. What matters is whether your team can run it after we leave. A Full Build ends with architecture diagrams, API docs, runbooks and structured handoff sessions with your engineers. After that you decide whether it comes back to your team or we keep going with you.
- Q: How much of my team’s time will an outside engineering team need?
  A: It takes less engineering time than most buyers expect and more subject-matter time. Our senior lead runs the discovery and organizes the work, so your engineers mostly review code. The one thing we can’t replace is the person who knows your business rules. That person has to stay involved and make the calls.
- Q: How fast can an outside team start shipping an approved roadmap item?
  A: Sprint 0 sets the architecture, infrastructure and delivery plan, and every two-week sprint after that ends with working software you can test. The ship date usually depends on when your team can integrate and release the work, so we plan backward from that date. If the item still needs defining, a Blueprint makes it build-ready in one to four weeks.

**Platform Modernization** (https://digitalscientists.com/problems/modernize-your-platform/)
- Q: Should we rewrite our legacy platform from scratch or modernize it in pieces?
  A: Not all at once. Full rewrites take several quarters, hinge on the two or three people who know the old system, and rebuild yesterday’s workflows on a new stack. Decide piece by piece what to keep, connect, replace, or retire, and prove the riskiest change first, usually the data or a key integration.
- Q: How do we move customers off an old platform without losing them?
  A: Plan the sunset as carefully as the rollout. Customers tolerate a new look. They leave over a lost workflow, or over one module updated while two stay old. Move one product line or customer group first, run old and new side by side, and verify the outputs match before anyone switches.
- Q: Should we replace our platform with off-the-shelf software or build our own?
  A: Decide by workflow, not by product. Where the workflow is standard, buy the service and keep renting it. Where the workflow is how you compete, prescriptive software starts driving your process, and the license bill never stops. Get the recommendation from engineers with no vendor partnerships to protect.
- Q: How do we get the board to fund modernizing a platform that still works?
  A: Don’t pitch it as refactoring. Nobody funds that. Tie it to what the current system costs today: the spreadsheets and re-keying it forces, the licenses you’d retire, the growth it blocks. Then test whether the pain justifies the cost, and ask for the first phase, not the whole program.

**Cost of Operations** (https://digitalscientists.com/problems/reduce-cost-of-operations/)
- Q: How do I prove the ROI of AI automation to my CFO?
  A: Stop counting hours saved. A CFO hears freed-up time as soft savings, because people fill it with other work. Before you start, name a number the business already tracks: cost per case, revenue you fail to capture, fines and audit exposure, or growth absorbed without a hire. Write down the baseline, then measure the pilot against it.
- Q: Which business process should we automate with AI first?
  A: Not the biggest one. Pick work your people spend real hours on today, where doing it faster moves money or risk, where a wrong answer is only a recommendation a person overrides, and that starts from one or two inputs. Skip anything that needs five systems on day one. Then prove it on your own records before you fund the build.
- Q: Should we buy software or build a custom AI workflow to cut operating costs?
  A: Run any product against your exact workflow, not its demo; that is where most fall apart. Licenses are the line item that only grows, and you pay for features you never use. Building means owning code and models that need updating. Build where the workflow is specific to how you run and the return covers ownership. Buy the rest.
- Q: Does automating operations with AI mean cutting staff?
  A: Only if you choose that. Most growing operators have more work than people, so the better measure is how much volume the current team absorbs before the next hire. AI takes the reading, re-keying and rule checks. A person stays on every decision and handles the exceptions. What you do with the freed capacity is a leadership call.

**Product Competitiveness** (https://digitalscientists.com/problems/product-competitiveness/)
- Q: Does a better user experience actually help win more deals?
  A: Only when the product is what’s losing the deal. “Every product in our space has a bad UI” doesn’t tell you whether it is. Ask the buyers who saw both demos and chose someone else. If they name price or a missing capability, a redesign won’t move win rate. If they couldn’t see what your product does better, it will.
- Q: We’re funding a rebuild of our product. How do we avoid ending up with the same experience?
  A: The team that built the current product will rebuild it the way they already see it. The workflows come out right and the experience comes out the same. Start from the job your buyers are trying to finish. Test the riskiest part with real users, before the build starts and while changes are still cheap.
- Q: How do I build the business case for redesigning our product?
  A: Tie it to numbers the board already tracks: win rate, churn, support cost and time to onboard a customer. Then back it with evidence from the people who decide, not internal opinion: what lost buyers said, and how real users did on a prototype. If the board needs the case before any design work, start with an Assessment.
- Q: What should a product design engagement deliver besides slides?
  A: Something your engineers can build from. A Blueprint ends with research from the people who decide, then an architecture and a development plan with milestones and a budget. The four-week version adds working software tested with real users. The research, designs and IP are yours, whether we build it or your own team does.

**Innovation / R&D** (https://digitalscientists.com/problems/innovation-and-rd/)
- Q: How should a company decide which innovation bets to keep funding?
  A: Fund each bet the way a venture investor would: a set amount from a ring-fenced fund, a milestone, and a go or no-go before the next check. Start with the core of the value, not the full feature list. If the core doesn’t hold, shut the bet down and move the money to the next one.
- Q: Should we build an internal innovation team or use an outside R&D partner?
  A: Most companies have no R&D group, and the teams they do have are committed to this year’s numbers. A partner gives you a working team beside yours now, and the code, research, and data models stay yours. When you want to bring the work in-house, we help you hire and build your own team as part of the transfer.
- Q: What does an innovation partner deliver: a strategy deck or working software?
  A: Working software. An early-stage bet is scoped to the one thing that has to be true, not a finished product, and you agree up front where that line sits. Every stage leaves you something you keep and use: code, designs, research, and data models, with no licensing fees.
- Q: How much of our own team’s time does an outside innovation team need?
  A: Your core team stays on this year’s plan. The time we ask for comes from your subject-matter experts, who join a bet when it needs what they know, with a C-suite sponsor signing off. Budget for that time: the experts drive the key calls, and nobody outside your company can replace what they know.

## What We Do

Digital Scientists takes software and AI from prototype to production. Clients own what
we build outright, including the code, IP and roadmap.

### The engagement ladder

- **Blueprint** (https://digitalscientists.com/services/blueprint/): Define what to build in 1-4 weeks. Three tiers starting at $10K; we recommend the two-week Medium tier. Bring your specs, prototypes, and research, we pressure-test it and produce the shared spec both sides build from.
- **Working Session** (https://digitalscientists.com/services/working-session/): A one-day strategy workshop to align stakeholders, map opportunities, and identify the highest-ROI starting point for your product investment.
- **Assessment** (https://digitalscientists.com/services/assessment/): A 4-week paid Assessment for AI, custom software, modernization, or strategic diagnostic initiatives. Quantified ROI, technical feasibility, board-ready business case. Fixed fee, $15K to $25K.
- **Rapid Experiment** (https://digitalscientists.com/services/rapid-experiment/): A one-day proof of concept to quickly test whether an idea is worth prototyping, before investing in a full sprint.
- **The Experiment** (https://digitalscientists.com/services/the-experiment/): A functional prototype in 5 days. We build the riskiest part of your product with real users, real data, and real code, so you know before you invest.
- **Full Build** (https://digitalscientists.com/services/full-build/): Production engineering for validated products. Sprint-based delivery with senior engineers, from architecture through launch.
- **Technical Advisory** (https://digitalscientists.com/services/technical-advisory/): Architecture review, technology selection, and engineering leadership from senior practitioners. The technical north star your team needs to build it right.
- **Production Support** (https://digitalscientists.com/services/production-support/): Managed services for production software. Bug fixes, feature enhancements, performance tuning, and on-call support so your team can focus on the business.
- **Monitoring & Ops** (https://digitalscientists.com/services/monitoring-ops/): DevOps and site reliability engineering to catch problems before your users do. Monitoring, alerting, and infrastructure management.
- **The Lab** (https://digitalscientists.com/services/the-lab/): An embedded innovation partnership for enterprises. Ongoing R&D, product strategy, and engineering, a dedicated team that operates like your internal...

### Disciplines

- **Product strategy** (https://digitalscientists.com/product-strategy-consulting/): Product strategy consulting that ends in a plan your engineers can build, not a deck. Decide what to build first, prove the riskiest part, and budget it in 1–4 weeks.
- **Product management** (https://digitalscientists.com/product-management/): Product management embedded in every engagement. Market awareness, business modeling, validated learning, and data-driven prioritization, not just timelines and budgets.
- **UX research and design** (https://digitalscientists.com/ux-design/): Complex workflows, simple UI. Healthcare, SaaS, enterprise. User research, JTBD, service design, design systems, AI experience. Senior team since 2007.
- **Engineering** (https://digitalscientists.com/development/): Senior architects orchestrate AI-accelerated delivery. 15-20 years avg experience, 200+ products shipped. Senior US team, AI-accelerated delivery.
- **Minimum viable product** (https://digitalscientists.com/minimum-viable-product/): U.S.-based senior team. 200+ products shipped since 2007, including successful exits. AI-accelerated MVP development, and all the IP is yours.
- **New product development** (https://digitalscientists.com/new-product-development/): We help clients move through the Pragmatic Framework to build digital products that solve real market problems. Research, architecture, and AI-accelerated build, from concept to commercialization.
- **Platform modernization** (https://digitalscientists.com/platform-modernization/): Modernize your legacy platform without shutting down. Architecture review, phased delivery, AI-accelerated development, and build-operate-transfer. Since 2007.
- **API and integration** (https://digitalscientists.com/api-integration-development/): Digital Scientists builds custom APIs, system integrations, and data pipelines that connect your platforms, partners, and products into a unified ecosystem.
- **Mobile** (https://digitalscientists.com/mobile-app-development/): Custom iOS and Android app development from a senior US team. 200+ products shipped since 2007. Native and cross-platform. You own the code and the IP.
- **IoT** (https://digitalscientists.com/iot-application-development/): Connected products in production: fleet, RPM, smart locks, wearables. Firmware, mobile, and cloud, BLE, OBD-II, cellular. Since 2007. You own the IP.

## Forward Deployed Engineering

**Page:** https://digitalscientists.com/services/forward-deployed-ai-engineering/

Forward Deployed Engineering (FDE): a senior US team embedded in your operation to make AI drive productivity and returns. On your stack, and you own what we build.

It is the embedded model Palantir pioneered, right-sized for the mid-market. There is no
platform to rent and no licence, and the client owns what gets built.

**How it differs from staff augmentation.** Pods are small. The client's operations people
work directly with a senior US-based engineer to define and improve the workflows being
built, with no account layer and no handoff between the person who owns the process and
the person building it.

### System of intelligence

**Page:** https://digitalscientists.com/healthcare/forward-deployed-engineering/system-of-intelligence/

Healthcare’s next strategic advantage gets built in the layer above the EHR, the system of intelligence. The argument behind every Digital Scientists engagement.

A system of intelligence is the decision layer above the systems of record, turning data
into action. FDE is how it gets built: on the client's stack, inside their operation.

### Further reading

- How Forward Deployed AI Engineering works: https://digitalscientists.com/blog/how-forward-deployed-ai-engineering-works/
- Partner or in-house for an AI build: https://digitalscientists.com/blog/partner-or-in-house-ai-build/

## AI Solutions in Production

**Page:** https://digitalscientists.com/ai-machine-learning/

Digital Scientists builds custom AI solutions that run in production, not pilots. $20M+ in
verified client ROI across engagements. The work spans generative AI, machine learning,
computer vision, NLP and AI agents, and it is built on the client's stack and owned by the
client.

### Where it has paid

- **RAF/HCC code optimization**: $2.4M+ compliant revenue recovered, +34% missed code detection.
- **MDS/PDPM optimization**: $10M+ PDPM revenue recovered and $2M+ in quality incentives.
- **Ambient clinical documentation**: 45 minutes to 5 minutes per visit, via HealthContext.AI.
- **Predictive risk stratification**: identifying high-risk patients before adverse events.
- **Revenue cycle automation**: prior authorization, denial management, claims processing.

### Why most AI does not ship

The gap is not the algorithm. It is the last mile: integration with the system of record,
workflow fit, data quality, change management and regulatory constraint. Most AI projects
stall partway through that journey.

### Further reading

- Where to start with AI: https://digitalscientists.com/blog/where-to-start-with-ai/
- How to pick the AI workflow that pays back: https://digitalscientists.com/blog/how-to-pick-the-ai-workflow-that-pays-back/
- The ROI of AI: https://digitalscientists.com/blog/the-roi-of-ai/
- Getting healthcare AI into production: https://digitalscientists.com/blog/healthcare-ai-into-production/

## Cortex: On-Premise Document Intelligence

**Page:** https://digitalscientists.com/ventures/cortex/

Cortex is an on-premise document intelligence platform, also called intelligent document
processing (IDP), that reads any document and answers questions about it with a
page-level citation. It handles PDFs, scans, faxes and handwritten notes, and the data
never leaves the client's network.

- Query response in under 1 second
- 315 documents per hour on a single GPU
- $0.02 of compute per page
- Zero documents sent off-site

Built for environments where cloud AI is off the table: HIPAA, SOC 2, 21 CFR Part 11,
FedRAMP and fully air-gapped networks. Cortex is an accelerator, not a SaaS subscription;
it deploys on the client's hardware and the client owns the deployment.

## Virtual Care and Telemedicine

**Page:** https://digitalscientists.com/healthcare/domains/virtual-care-platforms/

Digital Scientists builds virtual care platforms and operates one. NeverAlone is a 24/7
clinical safety net that Digital Scientists designed, built and runs in production. It
connects seniors, IDD individuals and post-acute residents with care partners over
real-time video, integrating with pharmacy systems, EHRs and third-party provider networks.

### NeverAlone, running in production today

- 26,000+ patients across 130+ facilities in 7 states
- 96% treat-in-place rate
- Provider reached in under 3 minutes
- 100,000+ calls in 2024
- 3x nurse capacity

### What a virtual care platform is

Telehealth is one component. A virtual care platform is the connected system, joining four
moving parts: synchronous telehealth (video and messaging visits), remote patient
monitoring (continuous device data from blood pressure cuffs, glucometers, pulse oximeters
and continuous monitors), AI-powered virtual care assistants (routine monitoring,
medication management, escalation triage), and bidirectional EHR and payer integration so
data flows where care decisions get made.

Video is the easy part. The hard parts are workflow integration, multi-state licensing
logic, payer billing alignment, RPM data routing, and the operations behind them.

Settings: acute and ambulatory, post-acute and skilled nursing, home health and hospice,
behavioral health, and rural populations who cannot reach specialty care without a
90-minute drive.

## Patient Engagement

**Page:** https://digitalscientists.com/healthcare/domains/patient-engagement-platforms/

The portal that came with the EHR was not built for engagement. Standard portals satisfy
Meaningful Use; they do not drive activation, retention or care plan adherence. Digital
Scientists builds patient engagement platforms families actually use, with the same
operational discipline applied at NeverAlone, where 26,000+ patients and their families
log in across 7 states.

A portal is one component. A patient engagement platform connects patients and families to
the care team across the full care journey: the portal itself (records, messaging,
scheduling), family proxy access, asynchronous symptom reporting, RPM data fed back to the
patient, education and care plan adherence prompts, video visits, and the secure
communication that ties them together. Mobile-first, EHR-native and bidirectional.

## Healthcare AI Development

**Page:** https://digitalscientists.com/healthcare/ai-development/

Digital Scientists provides custom healthcare AI development services. We build AI, machine learning, and NLP solutions trained on client data, integrated with EHRs, and designed for specific clinical workflows.

### The Healthcare AI Problem

The $420 billion digital health market is flooded with AI demos that work in a conference room but fail at the bedside. The gap isn't the algorithm — it's the last mile: EHR integration, clinical workflow fit, data quality, change management, and regulatory constraints. Most healthcare AI projects stall at step 4 of a 10-step journey. Digital Scientists delivers all 10.

### What We Build

- **Artificial Intelligence**: Algorithms that analyze medical data, identify patterns, and support clinical decisions. Custom models trained on client data, integrated with existing systems.
- **Machine Learning**: Explainable, audit-defensible models for risk stratification, outcome prediction, RAF scoring, readmission prevention. Every recommendation traces to source data.
- **Natural Language Processing**: Extract meaning from clinical notes, transcribe encounters, automate documentation. Powers ambient AI scribes and code extraction from unstructured text.

### Where Healthcare AI Delivers ROI

- **RAF/HCC Code Optimization** (HIGHEST ROI): AI analyzing EHR and claims data to identify missed diagnosis codes. $2.4M+ recovered for one client, +34% missed code detection.
- **Clinical Documentation AI** (FASTEST PAYBACK): Ambient AI scribes reducing documentation from 45 minutes to 5 minutes per visit via HealthContext.AI.
- **MDS/PDPM Optimization**: AI-powered MDS coding. $10M+ PDPM revenue recovered, $2M+ quality incentives for CommuniCare.
- **Predictive Risk Stratification**: ML models identifying high-risk patients before adverse events for proactive population health intervention.
- **Revenue Cycle Automation**: AI agents for prior authorization, denial management, claims processing, and payer-specific intelligence.
- **Readmission Prevention**: ML models flagging at-risk patients for targeted follow-up and care coordination.

### Non-Negotiable Requirements

Every healthcare AI solution includes: EHR interoperability (HL7 FHIR, CCDA, X12 EDI), HIPAA compliance with PHI de-identification for model training, clinical workflow integration (no separate login), real-time processing, audit-defensible AI, and scalable cloud-native architecture.

### Technology Stack

- LLMs & NLP: OpenAI GPT-4, Azure OpenAI, LangChain, custom fine-tuned models, clinical NER
- Machine Learning: PyTorch, TensorFlow, scikit-learn, XGBoost, SageMaker
- Cloud: AWS, Azure, HIPAA-compliant hosting, VPC isolation
- Data: HL7 FHIR, CCDA, X12 EDI, Apache Airflow, Spark, custom ETL
- EHR: PointClickCare and Gehrimed in production, Epic in R&D, Cerner and MatrixCare via FHIR/HL7/ADT, custom API connectors
- Languages: Python, Node.js, React, React Native, Ruby on Rails

### Frequently Asked Questions

**What is healthcare AI development?**
Building custom AI, ML, and NLP solutions for healthcare organizations. Unlike off-the-shelf tools, custom healthcare AI is trained on your data, integrated with your EHR, and designed for your clinical workflows.

**Why do 95% of healthcare AI pilots fail?**
They solve a technical problem without solving the workflow problem. The AI works in a demo but doesn't integrate with the EHR or fit how clinicians work. DS delivers all 10 steps from data foundation through production deployment.

**How long does it take?**
Concept to production in approximately 8 weeks using a 4-phase methodology: Discover, Experiment, Engineer, Optimize.

**What is the ROI?**
$20M+ verified client ROI. $2.4M+ RAF revenue recovery, $10M+ PDPM optimization, 45→5 min documentation time.

**How do you ensure HIPAA compliance?**
Built in from day one: encryption, role-based access, audit trails, PHI de-identification for model training, BAA compliance, audit-defensible AI.

**Can healthcare AI integrate with our EHR?**
Yes. PointClickCare and Gehrimed are in production on platforms we operate. Epic is integrated in an R&D environment. For Cerner, MatrixCare, and other systems we integrate via HL7 FHIR APIs, ADT feeds, and custom data exchange. AI embedded directly in the clinician's workflow — no separate login.

## RCM AI ROI Deployment Assessment

**Page:** https://digitalscientists.com/healthcare/revenue-cycle-ai-assessment/

**Related:** Companion to the Revenue Cycle AI domain page (https://digitalscientists.com/healthcare/domains/revenue-cycle-ai/) which covers the broader domain expertise and the deeper Revenue Integrity Audit (2 to 4 weeks, $15K to $25K). The RCM AI ROI Deployment Assessment is the lighter 1 to 2 week decision sprint tier.

**Promise:** Find the first revenue-cycle workflow where AI can prove ROI.

**Audience:** Hospital CFOs, CEOs, COOs, Revenue Cycle Directors, PFS Directors, and CIOs, plus revenue-cycle partner firms (billing, denials, coding, CDI consultancies, healthcare IT).

**The problem:** Hospitals are being asked to evaluate AI, but the investment case is rarely clear. Budgets are constrained, revenue-cycle teams are overloaded, vendors are pitching products and dashboards, and CFOs need a credible investment case before funding a speculative AI engagement. The question is not "Should we buy AI?" but "Where can we prove a practical outcome?"

**Four value levers (the ROI model):**
- Recover more: capture dollars that would otherwise be delayed, denied, underpaid, or written off.
- Recover faster: accelerate cash by helping teams act earlier or prioritize better.
- Use staff capacity better: focus limited revenue-cycle staff on the work most likely to create value.
- Prevent avoidable loss: reduce preventable denials, underpayments, write-offs, and rework.

RCM AI ROI formula: incremental cash recovered + avoidable loss reduced + staff capacity redirected, minus deployment and operating cost.

**Common starter workflows:**
- A/R collection prioritization (ranking open claims by expected recovery value)
- Claim follow-up triage (routing by status, payer, and dollar value, not aging alone)
- Denial and write-off reduction (identifying denial reason codes and payer patterns driving preventable loss)
- Payer contract and underpayment review (surfacing accounts paid below contracted rate)
- Coding and CDI review (cross-referencing the clinical record against the coded claim)
- Work queue intelligence (prioritized queues that learn from outcomes)

**Workflow scoring criteria:** financial value, data availability, workflow readiness, human review path, implementation complexity, governance and risk, and ability to measure lift against a baseline.

**The engagement (two stages):**

Stage I — RCM AI ROI Deployment Assessment, 1 to 2 weeks, $10K fixed fee. Digital Scientists works with the team to determine whether one revenue-cycle workflow has enough value and readiness to justify a deployment. Inputs: A/R aging, claims history, denial reason codes, payer mix, remittance and write-off patterns, underpayment indicators, staff workflows and work queues, available exports and reports. Outputs: first workflow recommendation, ROI hypothesis with a conservative range, data and workflow readiness snapshots, success metric and measurement approach, governance and risk considerations, and a proceed / wait / fix-readiness recommendation.

Stage II — If the case is strong, build one workflow. 8 to 14 weeks fixed-window. Pilot phases: confirm baseline and success metric, design the workflow with operators, build the workflow intelligence layer, run with human review, measure lift against the baseline, then decide to scale, stop, or adjust.

**Client-owned intelligence:** The payer patterns, workflow rules, prioritization logic, and operating knowledge uncovered through the engagement belong to the client. Digital Scientists captures it in a system the client owns and can improve over time. No platform license. No tool resale. You are not outsourcing your expertise, you are capturing it, using it, and owning it.

**Anchor demo:** Model Hospital simulation. A 5 to 7 minute walkthrough of a simulated community hospital with roughly 3,800 open claims, 320 daily collector touches, and a 120 day horizon. Compares an aging-only baseline to a Digital Scientists prioritization workflow, with a built-in holdout for measurement. Synthetic data only.

**Revenue-cycle proof point:** CommuniCare MDS Optimization, $24M+ in documented revenue impact. Post-acute proof of the same operating model: workflow intelligence layered on existing systems, measured revenue lift, client-owned IP. Translates to acute hospital revenue cycle.

**Six buyer concerns and answers:**
- Cost: fixed-fee assessment, fixed-window pilot, no platform license.
- Risk: human-in-the-loop, holdout-based measurement, narrow scope.
- Experience: CommuniCare MDS Optimization, $24M+ revenue impact.
- Ownership: client owns the data, the workflow logic, and the measurement framework.
- Speed: decision in 1 to 2 weeks, pilot result in 8 to 14 weeks.
- Compliance: PHI handled under BAA, security and governance reviewed with the CIO from day one.

**Delivery model:** Forward Deployed Engineering (FDE). A small, embedded senior US product, workflow, AI, and engineering team that works inside your operation. The embedded model Palantir pioneered, right-sized for the mid-market; you own what we build. Not staff augmentation.

**FAQ:**
- Is this an AI product or a service? Neither. An engagement to find the first revenue-cycle workflow worth building, then to build that workflow. The resulting workflow intelligence layer belongs to the client.
- Do you need EHR access for the assessment? Not for the assessment. Digital Scientists works from existing exports for the first 1 to 2 weeks. Deeper integration is part of the build phase only if the case is strong.
- What if the assessment says do not proceed? That is a successful assessment. The client leaves with a workflow opportunity map and a clear view of readiness gaps.
- How is PHI handled? Under BAA, with documented chain of custody. CIO is the governance counterpart from day one.

## Healthcare Data Analytics & Engineering

**Page:** https://digitalscientists.com/healthcare/data-engineering/

Digital Scientists provides end-to-end healthcare data analytics consulting and engineering services. We build the data infrastructure that turns fragmented healthcare data into actionable insights and measurable ROI.

### What We Build

- **Data Aggregation**: Unify data from EHRs, claims systems, medical devices, labs, and operational databases into a single source of truth. We normalize disparate formats — HL7, FHIR, CCDA, X12 EDI, and proprietary feeds — into clean, queryable datasets.
- **ETL Pipelines**: Extract, transform, and load data reliably and at scale with automated pipelines built on Apache Airflow, Spark, and dbt. Both batch and real-time streaming for clinical and operational data flows.
- **Data Lakes & Warehouses**: Scalable storage architecture using medallion patterns (bronze/silver/gold) on AWS S3, Redshift, Snowflake, and Delta Lake — ready for analytics and AI workloads.
- **Analytics & BI**: Custom dashboards and reports in Tableau, Power BI, or bespoke React interfaces connected to live data.
- **Real-Time Analytics**: Stream processing for time-sensitive clinical and operational data including census tracking, bed management, staffing optimization, and clinical alerting.
- **Data Quality & Governance**: Automated validation, cleansing, and standardization pipelines with HIPAA-compliant access controls, audit trails, data lineage tracking, and PHI de-identification.

### Applications

- **RAF/HCC Code Mining**: AI-assisted analysis of EHR and claims data to identify missed diagnosis codes and optimize risk adjustment scores. Recovered $2.4M+ in compliant revenue for one client with +34% missed code detection improvement.
- **MDS/PDPM Optimization**: AI-powered MDS coding optimization. $10M+ in PDPM revenue recovered and $2M+ in quality incentives for CommuniCare, one of the nation's largest post-acute care providers.
- **SDOH Visualization**: Interactive population health maps and dashboards transforming social determinants data into actionable insights. Built for Duke Health's SDOH research program.
- **Compliance Reporting**: Automated cross-platform reporting for CMS, HEDIS, MIPS, and state regulatory requirements.
- **Population Risk Stratification**: Predictive analytics to segment patient populations by risk level and prioritize interventions.
- **Claims Analysis & Denial Prevention**: Pattern identification for denial prevention, revenue leakage detection, and revenue cycle optimization.

### Technology Stack

- **Data Processing**: Apache Airflow, Apache Spark, dbt, AWS Glue, Python, SQL
- **Storage**: AWS S3, Amazon Redshift, Snowflake, Delta Lake, PostgreSQL
- **BI & Visualization**: Tableau, Power BI, custom React dashboards, Metabase
- **Healthcare Standards**: HL7 FHIR, CCDA, X12 EDI, ICD-10, CPT, SNOMED CT, LOINC
- **Cloud**: AWS (primary), Azure, HIPAA-compliant hosting with VPC isolation
- **EHR Integrations**: PointClickCare and Gehrimed in production, Epic in R&D, Cerner and MatrixCare via FHIR/HL7/ADT, custom API connectors

### Process

Our healthcare data engineering process moves from discovery to production insights in approximately 8 weeks:

1. **Discovery** (Weeks 1-2): Audit existing data sources, identify gaps, define business questions and success metrics.
2. **Blueprint** (Week 2-3): Design data architecture, ETL processes, analytics framework, and governance model.
3. **Develop & Launch** (Weeks 3-7): Build pipelines, load data, create dashboards, validate insights against ground truth.
4. **Grow** (Week 8+): Add data sources, expand analytics, train your team. Build-Operate-Transfer model for long-term ownership.

### Frequently Asked Questions

**What is healthcare data analytics?**
Healthcare data analytics is the practice of collecting, integrating, and analyzing data from clinical, financial, and operational systems to improve patient outcomes, reduce costs, and optimize operations. The foundation is data engineering — building the pipelines and infrastructure that make analytics possible at scale.

**How long does it take to build a healthcare data pipeline?**
Digital Scientists moves from discovery to production insights in approximately 8 weeks. Complexity varies based on the number of source systems, data volume, and compliance requirements.

**What's the ROI of healthcare data engineering?**
Our clients have achieved $20M+ in verified ROI. Specific examples: $2.4M+ in compliant RAF revenue recovery, $10M+ in PDPM optimization, 45-minute clinical documentation reduced to 5 minutes.

**What healthcare data standards do you support?**
HL7 FHIR, CCDA, X12 EDI, ICD-10, CPT, SNOMED CT, and LOINC.

**How do you ensure HIPAA compliance in data pipelines?**
Encryption at rest and in transit, role-based access controls, audit trails, data lineage tracking, PHI de-identification, VPC isolation — built in from day one.

**What's the difference between a data lake and a data warehouse?**
A data lake stores raw data in its original format at low cost and massive scale. A data warehouse stores cleaned, structured data optimized for fast queries. In healthcare, you typically need both. We design medallion architectures that combine the best of both approaches.

**Can you integrate with our existing EHR system?**
Yes. PointClickCare and Gehrimed are in production on platforms we operate. Epic is integrated in an R&D environment. For Cerner, MatrixCare, and other systems we integrate via HL7 FHIR APIs, ADT feeds, and custom data exchange. We build custom connectors for any EHR with an API or data export capability, focusing on bidirectional data flow.

## Healthcare UX Design & Research

**Page:** https://digitalscientists.com/healthcare/ux-research/

Digital Scientists provides healthcare UX design consulting and research services. We design clinical software that providers, patients, and care teams actually use — grounded in field research, not assumptions.

### The Healthcare UX Problem

Healthcare software fails when it's designed by engineers who've never watched a nurse document care at 2 AM. Physicians spend 9 minutes in their EHR for every 15 minutes with a patient (AMA/Tebra 2025). Every 1-point improvement in EHR usability correlates with 3% lower odds of physician burnout (JAMA Network Open). Only 54% of patients who activated a portal logged even one session (ONC). 75% of physicians believe their EHR contributes to burnout.

### Our Approach

- **User Research**: Ethnographic interviews, co-creation workshops (30+ participants, 7 workshops in one week with older adults), 4-month diary studies, workflow shadowing, contextual inquiry, persona development. We conduct research in real clinical settings with real stakeholders.
- **UX Design**: Information architecture, interaction design, design systems, WCAG/Section 508 accessibility. Interfaces for EHR systems, telehealth platforms, patient portals, medical devices, clinical decision support, and MDS documentation.
- **Human Factors**: IEC 62366 medical device usability engineering, cognitive load analysis, error prevention design, clinical decision support optimization for FDA-regulated software.

### Co-Creation With Real Users

Over four months, we conducted ethnographic interviews, diary studies, and seven co-creation workshops with 30+ seniors designing an in-home care service. We learned that printed slides need high-contrast paper because projectors don't work, that activities need mobility accommodations, and that showing genuine interest matters more than any design framework. Our research uncovered an entirely new service option that reshaped the product roadmap.

### What Healthcare UX Delivers

- Documentation time reduced from 45 minutes to 5 minutes
- 96% treat-in-place rate on NeverAlone virtual care platform
- 100K+ virtual care calls completed across 130+ facilities
- Up to 60% increase in patient engagement from UX-driven design
- Up to 40% improvement in medication adherence from user-friendly app design
- Hospitals with "excellent" satisfaction scores: 4.7% net margins vs 1.8% at lower-rated

### Healthcare UX Use Cases

- EHR systems (PointClickCare, Epic, custom platforms)
- Telehealth platforms (NeverAlone — 130+ facilities, 7 states)
- Patient portals and digital front doors
- Medical devices and RPM (IEC 62366 compliance)
- Clinical decision support systems
- Clinical documentation (MDS assessments, care plans)
- Mental health applications (Fathers' UpLift custom EHR)

### UX Tools & Standards

- Design: Figma, Sketch, Adobe XD, InVision
- Research: Dovetail, UserTesting, Maze, Hotjar
- Accessibility: axe, WAVE, VoiceOver, JAWS
- Standards: WCAG 2.1, Section 508, ADA, IEC 62366, HIPAA

### Frequently Asked Questions

**What is healthcare UX design?**
Healthcare UX design is designing digital products — EHR systems, patient portals, telehealth platforms, clinical decision support tools, and medical devices — so that they actually get used by providers, patients, and care teams. Unlike consumer UX, healthcare UX must account for regulated environments, clinical workflow constraints, life-safety requirements, and multiple user types.

**How does UX research improve clinical workflows?**
Through workflow shadowing, contextual interviews, and usability testing with real providers, we identify friction points that drain time and increase errors. Every 1-point improvement in EHR usability correlates with 3% lower odds of physician burnout (JAMA Network Open).

**What's the difference between healthcare UX and consumer UX?**
Consumer UX optimizes for engagement and conversion. Healthcare UX optimizes for accuracy, speed, and safety in high-stakes environments with HIPAA compliance, clinical terminology, multi-stakeholder workflows, and regulatory standards like IEC 62366.

**How long does a healthcare UX audit take?**
2-4 weeks depending on complexity. Includes heuristic evaluation, stakeholder interviews, workflow analysis, and a prioritized findings report.

**What is IEC 62366?**
The international standard for usability engineering applied to medical devices, including software as a medical device (SaMD). Required for FDA-regulated healthcare software.

**How does UX design improve EHR usability?**
Reducing clicks per task, surfacing the right information at point of care, simplifying documentation workflows. We reduced documentation time from 45 minutes to 5 minutes in one engagement.

## Rural Health Transformation Program (RHTP)

**Page:** https://digitalscientists.com/rural-health-transformation/

Digital Scientists is a technology implementation partner and solution architect for organizations delivering Rural Health Transformation Program initiatives. RHTP is a $50 billion CMS program authorized by Section 71401 of Public Law 119-21, distributing $10 billion per year from FY2026 through FY2030. All 50 states were approved in December 2025. Assistance Listing 93.798; NOFO number CMS-RHT-26-001.

### How the Money Is Split

Funding splits into $25B baseline, divided equally among approved states, and $25B workload, which is scored. The workload score is 50% rural score factors (rural population, rural facility share, uncompensated care, land area, Medicaid DSH hospitals) and 50% technical score factors, recalculated annually. Each factor is scored out of 100 across all 50 states and a state's award equals its share of all approved states' total points, so it is a relative competition.

### The Sixteen Technical Score Factors

- Population Health, 13.00% total: clinical infrastructure 3.75, health and lifestyle 3.75, SNAP waivers 3.75, nutrition CME 1.75
- Provider Networks, 9.25% total: rural partnerships 3.75, EMS 3.75, certificate of need 1.75
- Workforce, 7.25% total: talent recruitment 3.75, licensure compacts 1.75, scope of practice 1.75
- Payment and Integration, 9.25% total: Medicaid value-based incentives 3.75, dual eligibles 3.75, STLDI 1.75
- Technology and Access, 11.25% total: remote care services 3.75, data infrastructure 3.75, consumer-facing technology 3.75

CMS classifies every factor as data-driven, initiative-based, or a state policy action. 37.5 of the 50 technical points are initiative-based, meaning earned by proposing initiatives and following through. States begin at 50% on initiative-based factors and earn the remainder by implementing initiatives and meeting milestones.

### FY2026 Obligation by State

All 50 states hold an award. $10.0 billion was obligated for federal fiscal year 2026, ranging from $147.3M in New Jersey to $281.3M in Texas. Source: USAspending.gov, Assistance Listing 93.798, pulled 16 August 2026.

- Alabama: $203.4M
- Alaska: $272.2M
- Arizona: $167.0M
- Arkansas: $208.8M
- California: $233.6M
- Colorado: $200.1M
- Connecticut: $154.2M
- Delaware: $157.4M
- Florida: $209.9M
- Georgia: $218.9M
- Hawaii: $188.9M
- Idaho: $186.0M
- Illinois: $193.4M
- Indiana: $206.9M
- Iowa: $209.0M
- Kansas: $221.9M
- Kentucky: $212.9M
- Louisiana: $208.4M
- Maine: $190.0M
- Maryland: $168.2M
- Massachusetts: $162.0M
- Michigan: $173.1M
- Minnesota: $193.1M
- Mississippi: $205.9M
- Missouri: $216.3M
- Montana: $233.5M
- Nebraska: $218.5M
- Nevada: $179.9M
- New Hampshire: $204.0M
- New Jersey: $147.3M
- New Mexico: $211.5M
- New York: $212.1M
- North Carolina: $213.0M
- North Dakota: $198.9M
- Ohio: $202.0M
- Oklahoma: $223.5M
- Oregon: $197.3M
- Pennsylvania: $193.3M
- Rhode Island: $156.2M
- South Carolina: $200.0M
- South Dakota: $189.5M
- Tennessee: $206.9M
- Texas: $281.3M
- Utah: $195.7M
- Vermont: $195.1M
- Virginia: $189.5M
- Washington: $181.3M
- West Virginia: $199.5M
- Wisconsin: $203.7M
- Wyoming: $205.0M

### The Eleven Approved Uses of Funds

Categories A through K: A prevention and chronic disease, B provider payments (capped at 15% of annual award, may not supplant insurance-reimbursable services), C consumer technology solutions, D training and technical assistance, E workforce, F IT advances, G appropriate care availability, H behavioral health, I innovative care, J capital expenditures and infrastructure, K fostering collaboration. States must carry out at least three.

### Deadlines and Recovery of Funds

Year 1 funds must be obligated by 30 October 2026, and FY2027 allocations are announced by 31 October 2026. Funds a state has not spent by the end of the following fiscal year are redistributed to other states, and money earmarked but not paid out does not count as spent. Anything unexpended as of 1 October 2032 returns to the Treasury. RHTP is a cooperative agreement, not a grant: CMS stays substantially involved after award and may reduce, withhold or recover funds used inconsistently with the application.

### How a Technology Partner Reaches the Work

Only states could apply and that window closed 5 November 2025, so every dollar reaching a build reaches it through someone else's award, by one of four routes: named in a subrecipient application, subcontract to an awardee, subcontract under a prime, or direct state procurement. Federal subaward data shows the money pooling in aggregators: 23 hospital and health associations account for $205.5M while 93 individual hospitals and health systems account for $61.2M.

### What Digital Scientists Builds Against These Objectives

Treatment in place, virtual care command centers, patient engagement, revenue cycle management, value-based care platforms, interoperability and health information exchange integration, clinical workforce capacity, and multi-tenant platforms that let one solution serve many health systems.

### Proof: NeverAlone

NeverAlone is a 24/7 virtual care platform Digital Scientists designed, built and operates. It runs across 130+ facilities in 7 states supporting 26,000+ patients, at a 96% treat-in-place rate with providers reached in under 3 minutes.

### Frequently Asked Questions

**What is the Rural Health Transformation Program?**
A $50 billion CMS program authorized by Section 71401 of Public Law 119-21, distributing $10 billion per year from FY2026 through FY2030 to all 50 states. Assistance Listing 93.798, NOFO CMS-RHT-26-001.

**How much did my state get?**
See the FY2026 obligation by state list above. Awards range from $147.3M in New Jersey to $281.3M in Texas, totalling $10.0 billion for FY2026.

**Can a vendor apply for RHTP funding directly?**
No. Only states could apply, and that window closed 5 November 2025. A technology partner reaches the work by being named in a subrecipient application, subcontracting to an awardee, subcontracting under a prime, or through direct state procurement.

**Is the award fixed for five years?**
No. The technical score is recalculated annually, and a state's award is its share of all approved states' total points, so allocations move each year.

**What is the deadline for Year 1 funds?**
Year 1 funds must be obligated by 30 October 2026. FY2027 allocations are announced by 31 October 2026.

**What happens when RHTP funding ends?**
The program funds five fiscal years and ends 30 October 2030. The non-supplanting rule points at an operating model: billing through CCM, PCM, RPM and BHI where care is reimbursable, and shared service fees, operating budget lines, payer arrangements, licensing revenue or documented savings for everything else.

## Security, Privacy and Compliance

**Page:** https://digitalscientists.com/healthcare/security-phi/

Digital Scientists builds HIPAA-compliant platforms with executed BAAs, ePHI safeguards
mapped to the HIPAA Security Rule, and a secure SDLC.

- **HIPAA.** Administrative, physical and technical safeguards, workforce training and data
  handling practices meet the HIPAA Security Rule, Privacy Rule and Breach Notification Rule.
- **BAAs.** Executed with every covered entity and subcontractor, before any data is
  exchanged or system access is granted. Also maintained with cloud providers.
- **Breach history.** Zero breaches in Digital Scientists history.
- **SOC 2 Type II.** Working toward it. Not yet certified. Controls and evidence collection
  run on ERAMBA, a GRC platform providing continuous monitoring and audit-readiness tracking.
- **HITRUST CSF.** On the roadmap. Not held today.
- **Regulated software.** FDA cybersecurity guidance, ISO 13485, IEC 62304 and IEC 62366
  apply where the work is regulated medical software.
- **In the build.** Encryption at rest and in transit, role-based access control, audit
  trails, data lineage tracking, PHI de-identification for model training, and VPC isolation.

## Industries Served

Digital Scientists works across regulated and operationally complex industries. Healthcare
is the deepest proof; it is not the boundary.

### Healthcare
Digital Scientists' deepest proof. Clinical documentation, revenue cycle management,
virtual care and patient engagement, and clinical workflows, delivered for providers,
payers and healthcare software companies.

**Post-acute care** (https://digitalscientists.com/healthcare/post-acute-care/) is a
continuum spanning 14+ care settings: skilled nursing facilities, home health agencies,
hospice, assisted living, memory care, CCRCs, IRFs, LTACHs, IDD services, PACE and
transitional care. Each carries a different regulatory framework, payment model and IT
requirement. Delivered work for multi-site post-acute operators includes 24/7 virtual care
(NeverAlone: 100,000+ calls, 130+ facilities, 7 states, 96% treat-in-place, 95% nurse
approval, SBAR-based triage and EHR-integrated encounters), MDS/PDPM optimization
($10M+ PDPM revenue recovered, $2M+ quality incentives, PointClickCare in production and
MatrixCare via FHIR/HL7), ambient documentation AI (45 minutes to 5 minutes per visit via
HealthContext.AI), and RAF/HCC coding AI ($2.4M+ compliant revenue recovery).

**Healthcare SaaS** (https://digitalscientists.com/healthcare/saas-development/):
HIPAA-compliant multi-tenant platform development, healthcare workflow applications,
patient portals, provider tools and practice management systems.

Other markets served: health systems, senior living, home health and hospice, IDD
services, and rural health (see the Rural Health Transformation Program section above).


### Energy and Utilities
**Page:** https://digitalscientists.com/energy/
Custom software for energy and utilities: grid operations, field workforce tools, and regulatory compliance. Representative work includes replacing a 20-year-old evaluation and
collaboration platform for nuclear power operations that carried mounting technical debt
and security risk, beginning as an 8-week Blueprint and becoming a multi-engagement
partnership through production and ongoing support; and cross-functional operations
performance dashboards aligned to Power BI and Tableau, taking leadership from executive
strategy down to field-level operations, from stakeholder research through validated
prototypes.

### Logistics and Supply Chain
**Page:** https://digitalscientists.com/logistics/
AI-native software for supply chain, fleet, and warehouse operations. Senior US team, we've shipped for ToolsGroup, Fortna, NAPA, HD Supply, Hubbell, and Star Leasing. Start with a Blueprint.

### Defense and Government
**Page:** https://digitalscientists.com/defense/
Mission-critical software for defense and government. Secure cloud, data analytics, and field-ready mobile apps. In the 13-month GSA Multiple Award Schedule application process. Delivering since 2007.

### Retail, Consumer and Marketing Technology
Delivered work for Mailchimp (innovation programme, Creative Assistant, Tempo CRM),
Office Depot, NAPA and Genuine Parts, AmericasMart, Wahoo Fitness and MyUS.com.

### Financial Services and Insurance
Delivered work for Atlanticus/Fortiva, OneShield Software and Apex HCM.

## Case Studies with Verified Results

- **RAF/HCC Coding Automation**: $2.4M+ compliant revenue recovery, +34% missed code detection. Built data pipelines analyzing EHR and claims data to identify missed HCC codes. https://digitalscientists.com/case-studies/raf-hcc-coding/
- **CommuniCare MDS/PDPM Optimization**: $10M+ PDPM revenue recovered, $2M+ quality incentives. AI-powered MDS coding for one of the nation's largest post-acute care providers (350+ facilities). https://digitalscientists.com/case-studies/communicare-mds/
- **Congruity Health Analytics Platform**: AI-driven chronic disease analytics platform enabling predictive interventions for population health management. https://digitalscientists.com/case-studies/congruity-health/
- **Duke Health SDOH Research Platform**: Interactive SDOH data visualization and CRM platform helping Duke strengthen community partnerships. https://digitalscientists.com/case-studies/sdoh-research-platform/
- **NeverAlone Virtual Care Platform**: Comprehensive virtual care and clinical documentation platform. https://digitalscientists.com/case-studies/never-alone/
- **HealthContext AI Clinical Documentation**: AI-powered clinical documentation system reducing documentation time from 45 minutes to 5 minutes. https://digitalscientists.com/case-studies/healthcontext-ai/

## Insights

**Blog:** https://digitalscientists.com/blog/

### AI, from decision to production

- Where to start with AI: https://digitalscientists.com/blog/where-to-start-with-ai/
- How to pick the AI workflow that pays back: https://digitalscientists.com/blog/how-to-pick-the-ai-workflow-that-pays-back/
- The ROI of AI: https://digitalscientists.com/blog/the-roi-of-ai/
- Partner or in-house for an AI build: https://digitalscientists.com/blog/partner-or-in-house-ai-build/
- How Forward Deployed AI Engineering works: https://digitalscientists.com/blog/how-forward-deployed-ai-engineering-works/
- Getting healthcare AI into production: https://digitalscientists.com/blog/healthcare-ai-into-production/

### Guides

- AI partner evaluation checklist: https://digitalscientists.com/blog/assets/guides/ai-partner-evaluation-checklist.html
- AI workflow opportunity scorecard: https://digitalscientists.com/blog/assets/guides/ai-workflow-opportunity-scorecard.html
- In-house AI readiness checklist: https://digitalscientists.com/blog/assets/guides/in-house-ai-readiness-checklist.html

### Healthcare data and analytics

- How healthcare data analytics is improving outcomes: https://digitalscientists.com/blog/data-analytics-improve-healthcare-outcomes/
- Big data analytics in healthcare: https://digitalscientists.com/blog/big-data-in-healthcare/
- Predictive analytics in healthcare: https://digitalscientists.com/blog/predictive-analytics-in-healthcare/
- Leveraging AI for ROI in healthcare: https://digitalscientists.com/blog/leveraging-ai-for-roi-in-healthcare-10-custom-solutions-for-2026/
- 7 technologies fueling healthcare revenue cycle management: https://digitalscientists.com/blog/healthcare-revenue-cycle-management-key-technologies/

## Company Facts

- Founded: 2007
- Headquarters: Atlanta, Georgia (serving all of metro Atlanta)
- CEO: Bob Klein
- COO: Nick Alexander
- Team: Senior US-based architecture and engineering. Digital Scientists leads every engagement; we bring in a nearshore partner team only where a specific client or stack needs added scale or a lower-cost engineer.
- Delivery model: Forward Deployed Engineering. Small pods, with the client's operations people working directly with a senior US-based engineer to define and improve the workflows being built.
- Focus: Prototype to production, systems of intelligence, Forward Deployed Engineering (FDE), custom software and product; deep healthcare proof (revenue cycle management, virtual care and patient engagement, clinical workflows)
- Compliance: HIPAA, HL7/FHIR
- Verified ROI: $20M+ across healthcare clients
- Key results: $2.4M+ compliant RAF revenue recovery, $10M+ PDPM optimization, $2M+ quality incentives
- EHR integrations: PointClickCare and Gehrimed in production, Epic in R&D, Cerner and MatrixCare via FHIR/HL7/ADT
- Engagement model: Build-Operate-Transfer (BOT)

## Contact

- Website: https://digitalscientists.com
- Phone: 404.654.3855
- Schedule a call: https://digitalscientists3.pipedrive.com/scheduler/kOOeAEu2/meeting-with-bob-klein
- Location: Atlanta, GA
- Get started: https://digitalscientists.com/start/