Healthcare and Life Sciences Capability Model: AI-Ready Edition

This healthcare business capability model gives CIOs, architects and transformation leads at hospitals and health systems, pharmaceutical and biotechnology companies and medical device companies one model for deciding where AI goes. It covers development programs, clinical research, regulatory affairs, product quality, regulated production, product safety and medical affairs, and the hospital areas of patient access and revenue cycle, care delivery and clinical support, as 61 L2 capabilities. For each L2 capability it records the target AI mode, the oversight it needs and its risk tier, and a 40-question readiness assessment tests whether the organization can act on the ranking.

About the Healthcare and Life Sciences Capability Model

The model describes a health system or a life sciences company by the work it does, not by the systems it runs or the departments on its organization chart. Its 10 L1 capabilities are product development portfolio and programs; clinical research and evidence generation; regulatory affairs and product registration; regulated product quality management; regulated production and product supply; product safety and vigilance; medical affairs, market access and healthcare engagement; and three that belong to hospitals and health systems: patient access and revenue cycle management, care delivery management, and clinical support, patient safety and health records. They break down into 61 L2 and 255 L3 capabilities, each defined to L3, with 249 KPIs at L2 and stable IDs you can cite in a program plan, a business case or a vendor scorecard.

Hospitals and Health Systems, Pharmaceuticals and Biotechnology, and Medical Devices sit inside that structure rather than beside it. Hospitals and Health Systems adds clinical research site operations, then referral and scheduling, registration and coverage verification, charge capture and clinical coding, claims and denials, patient financial services and health plan contracting; emergency, inpatient, perioperative and outpatient services, care coordination and discharge, and clinical orders and documentation; and pharmacy, laboratory and imaging services, clinical engineering, medical staff and nurse staffing, patient safety and infection prevention, and health information management. The care capabilities describe how a hospital organizes and runs its services, from triage and admission to procedures and discharge, and hold no diagnoses, treatments or clinical guidelines. Pharmaceuticals and Biotechnology adds discovery research, early clinical development, process and formulation development, and expanded access. Medical Devices adds design controls and device risk management, device software lifecycle management, and device installation, service and clinical training. Each segment capability carries its segment in the workbook, so a device company filters to the shared work plus its own. Finance, people, procurement, technology and the other work every large enterprise does stay in the enterprise capability model and are not repeated here.

The AI layer sits on top of the names and definitions. This edition adds an AI profile for every L2 capability: the opportunities, the work that stays human, KPIs and AI measures, prerequisites, risks and workforce impact. Every L3 is rated for work pattern, target AI mode, AI fit and risk tier, with a note on what AI may do and who decides, so the whole model can be drawn as one heatmap and ranked by a risk-adjusted score. The case assessment and safety reporting profile in the public sample shows the split this produces: AI may summarize each safety case, check the event against the current labeling and propose where and by when it must be reported, while the Product Safety Physician assesses seriousness and causality and the Head of Product Safety and Vigilance decides whether the case is reportable and approves its report.

Why It Matters

Health systems and life sciences companies tend to be described in the vocabulary of their systems: the electronic health record, the billing system, the clinical trial management system, the safety database, the quality management software. Each department maps its own corner, so a hospital's revenue cycle, its pharmacy and its research office rarely share one structure, and a company that develops, makes and sells regulated products keeps separate maps for research, quality, safety and commercial work. AI proposals then arrive department by department and tool by tool, judged one at a time, with no shared way to compare them or to see which decisions they touch.

With one model for the organization, those parts are described in the same terms. The shared capabilities hold the regulated work at least two segments do, the segment capabilities hold what only one does, and each capability already states the AI mode it suits, the oversight it needs and the risk it carries. Decisions about AI in admissions, orders, coding, product release, safety reporting and recalls, where a wrong output can delay care, release a batch that should have been held or miss a reportable event, are then made against criteria set in advance instead of case by case.

What's Inside

The Capability Model edition holds the model, its AI layer and the files to work with them:

The Capability Model edition holds the model, its AI layer and the files to work with them:

• 10 L1, 61 L2 and 255 L3 healthcare and life sciences capabilities, with definitions to L3 and 249 KPIs at L2
• A full AI profile for every L2 capability: opportunities, what stays human, KPIs, AI measures, prerequisites, risks and workforce impact
• AI ratings for every L3: work pattern, target AI mode, AI fit and risk tier
• A prioritization model with a risk-adjusted score and rank for every L2 capability, using your own ratings and weights
• An AI heatmap of the whole model
• A 40-question weighted AI readiness assessment
• A Welcome document, the capability map deck, standalone capability definitions and KPIs documents, the Excel workbook, the user guide
• Bonus files: a healthcare and life sciences glossary, A Practical Guide to Business Architecture, a capability modeling overview, an AI-ready capability profile template and capability relationship mapping templates
• Free corrections, and new versions free for 180 days

Every file names your organization and carries your license ID. Ratings describe a typical large enterprise and are a starting point for your own.

Where It Is Used

AI opportunity assessment across segments. Rate the 61 L2 capabilities with your own scores and weights, for the shared work and for the segment you run. The ranked results show where AI serves a hospital's access, billing and care operations, a medicine maker's discovery and process development, or a device maker's design and service work, and where the shared regulated work comes first.

Setting oversight for clinical, quality and safety decisions. Use the oversight level and risk tier in each profile as the starting point for deciding where AI may act and where a person decides. The capabilities that place patients, verify medication orders, release products, assess safety cases and decide recalls carry the ratings that tell a governance group where to look first.

Rationalizing clinical and quality applications. Map the electronic health record modules, pharmacy, laboratory and billing systems, or the clinical trial, safety, quality and production record systems, to the L3 capabilities they support. The map shows duplicate systems, gaps and work carried by spreadsheets nobody owns, with one set of capability IDs across sites and businesses.

Integrating an acquired hospital or product line. Map the acquired organization's operations to the shared capabilities and to its segment before the integration plan is written. The overlap shows what can be combined, and the segment capabilities show what has to be kept because the acquired business runs different services or makes different products.

Scoping a system or service partner evaluation. Before evaluating an electronic health record, a revenue cycle service, a clinical trial platform or a quality system, mark the capabilities the purchase must support, including segment ones such as prior authorization requests, early clinical development or device software release. Answers are then scored against named capabilities and their KPIs instead of feature lists.

A capability-based transformation plan. Sequence an operations or AI program by capability instead of by department or system, using the prioritization model and the readiness assessment. Each step names the capabilities it changes, so progress is reported in terms that clinical, quality, research and finance leaders all recognize.

Who Works With It

Business and enterprise architects. Use the model as the reference structure for health and life sciences work, tailor it to the organization's segment, and link applications, processes and initiatives to its capabilities.

Chief operating officers, chief medical officers and chief nursing officers. Use the AI profiles and the heatmap to see which hospital operations are ready for AI support, and confirm that every decision about a patient's care stays with the clinician named for it.

Heads of patient access, revenue cycle, pharmacy, laboratory and imaging. Check the profiles for scheduling, registration, coding, claims, patient balances and clinical support services, and adjust the ratings to how their departments work.

Research, regulatory, quality and product safety leaders. Review the risk tiers and the work that stays human in clinical studies, submissions, deviations, product release, safety cases and recalls, and confirm who decides each before any AI work starts.

Medical affairs, market access and device service leaders. Review the profiles for medical information, promotional material review, access contracts, patient support programs and device service, and set the oversight each needs.

Transformation leaders. Use the ranked capabilities to choose where a program starts and to explain that choice to clinical, scientific and business leadership.

A Blank Slate, Consultants, or a Reference Model

There are three ways for a health system or a life sciences company to get a capability model, and the difference that matters most is the time to a first draft that clinical, quality, research and business leaders all accept.

• Building it from a blank slate. Architects run workshops with each department, gather what people do, reconcile the vocabularies of clinical, administrative, research and quality teams, and draft definitions and KPIs. The result fits the organization, but the structure takes several review cycles to settle, and the AI layer is still to design.
• Hiring consultants to build it. Consultants bring a method and often a starting structure of their own, and run the elicitation for you. Much of the effort goes into drafting structure that is much the same at every hospital or product company, and the result is a document your team did not build and has to learn.
• Starting from this model. Your team starts with a defined, rated model of the shared work and the three segments, sets aside the segments it does not run, and spends its workshops on what is different about its own organization. The first review is about your organization, not about what a capability model is.

Advisers who know health care or life sciences are still useful once the model is in hand: tailoring it to your services or products, running the prioritization with your leadership and planning the change. That work needs knowledge of your organization; drafting the generic list of what a hospital or a medicine maker does does not.

First Steps

These steps take a team from the download to a ranked list of where AI work starts:

1. Read the Welcome document and the user guide to see how the model, the AI profiles and the workbook fit together.
2. Filter the workbook's Segment column to the shared capabilities plus the segment your organization runs.
3. Review the definitions and KPIs with the clinical, research, quality and business leaders who own them and record where your organization differs.
4. Adjust the AI ratings and the weights in the prioritization model to reflect your own services, products and priorities.
5. Run the readiness assessment, then use the ranked results and the heatmap to choose where AI work starts.

Read the Public Sample

The sample follows one thread through the package, case assessment and regulatory safety reporting, and is 0.46% of the content. From the Case Assessment and Regulatory Safety Reporting (HL-6.2) AI profile:

• Work patterns: Judgment-based decision, Rules-based decision, Transactional processing
• Target AI mode: Augment
• Human oversight: Human-in-the-loop
• AI fit / Value / Feasibility / Data readiness: 3 / 5 / 3 / 3 (1–5)
• Risk tier: High
• Roadmap wave: Wave 2
• AI opportunity: Summarize each safety case's narrative, history and concomitant medicines for the Product Safety Physician, with the facts that bear on seriousness and causality
• What stays human: The Product Safety Physician assesses seriousness and causality for each safety case; AI summaries and proposals go forward only through that assessment

Upgrade Credit

Start here and move up later: the full price of this edition counts toward the Business Architecture for Healthcare and Life Sciences: AI Transformation Blueprint if you upgrade within 90 days. Email support@ciopages.com with your order number for a one-time checkout code.

Frequently Asked Questions

What is the difference between the two editions?

The AI-Ready Capability Model covers the capability map, an AI profile for every L2 capability, prioritization, the heatmap and the readiness assessment. The AI Transformation Blueprint adds value streams redesigned for AI, the business data model, agent specifications, use cases, responsible AI principles and controls, the operating model and the roadmap, a leadership presentation template, and bonus files on roles, operating model archetypes and transformation.

Can I upgrade from the Capability Model to the Blueprint later?

Yes. The full price you paid for the Capability Model counts toward the Blueprint if you upgrade within 90 days. Email support@ciopages.com with your order number for a one-time checkout code.

What happens after 180 days?

Your license to use the files does not end. Corrections are free for as long as you use the files. New versions released within 180 days of purchase are free: we email you a new download link when one is released. There is no renewal after that: you can buy a new version at 25% off its price.

Can I load the content into our own AI tools?

Yes, within the license. The Enterprise license allows internal tools, including your own assistants and agents. Neither license allows training, fine-tuning or prompting AI systems for third parties.

Does the package cover AI laws and regulations?

No, by design. It is business architecture: capabilities, value streams, data and the AI layer describe what a health system or a life sciences company does and how AI fits, and they hold whichever laws apply where you operate. The risk tiers, principles and controls are durable practices your compliance team maps to your own jurisdictions.

Why not just ask ChatGPT or another AI assistant?

An AI assistant can draft a list of what a hospital or a medicine maker does in a minute, and for getting oriented in an unfamiliar part of the industry that is often enough. This model is for decisions that have to stand up to review by clinical, quality, product safety and compliance leadership. Its capabilities keep stable IDs, the links between capabilities, ratings and the readiness assessment are checked before release, every L2 capability carries a rated AI profile with a risk tier, the segments are tagged instead of mixed in, and the scoring model uses weights you set. A generated list changes each time you ask and checks none of that.