Time Machine

Medical and Health Services Managers

Scrub through 137 years of this role's history — from when it first emerged, through every wave of technology that reshaped it, to the cited projections for where it's heading next.

Ledger accounting + paper records + physical plant inspection

Hill-Burton federal construction programs + systematic plant management

Medicare + Medicaid compliance and cost-reporting infrastructure

Medicare DRGs + prospective payment — the financial management era

HIPAA compliance systems + early EHR governance

AI operations platforms — Epic Cosmos AI, Oracle Health Clinical AI Agent, AKASA, Innovaccer

19001925195019752000now

Drag the dot, click anywhere on the track, or use ← → arrow keys (Shift for 10-year jumps, PgUp/PgDn for 25).

2026

Known today as Medical and Health Services Manager (BLS SOC 11-9111)

US Employment

616K

BLS OEWS May 2024 establishment-survey data per O*NET. The dramatic jump from 509,500 (2023) to 616,200 (2024) — a 21% single-year increase — likely reflects a methodology or scope expansion in the 2024 OEWS survey cycle, as single-year growth of this magnitude is atypical. The Data USA ACS household survey for this code reports 789,849 in 2024, a higher figure that incorporates the full non-establishment-survey universe. Both numbers converge on the same directional story: this occupation has grown from approximately 406,000 in 2018 to somewhere in the 500,000–790,000 range in 2024, depending on survey methodology. The BLS OEWS figure is used for consistency with BLS projections.

Median Annual Wage

$117,960

Source: BLS-OEWS

Tool of the era · AI operations platforms — Epic Cosmos AI, Oracle Health Clinical AI Agent, AKASA, Innovaccer

By 2023-2025, AI had arrived at scale in the administrative layer of US healthcare, and medical and health services managers became the humans responsible for governing it. Epic Cosmos AI Insights (GA October 2025), drawing on 305 million patient records across the Epic Health Research Network, lets a single department head benchmark their outcomes in real time against the national peer group — a capability that previously required a full analytics team. AKASA Authorization automates prior-authorization workflows, claiming 60% faster turnaround; Oracle Health's Clinical AI Agent claims 93% reduction in PA processing time. HFMA's 2026 Revenue Cycle AI Adoption Report found 71% of CFOs report AI in revenue cycle, with adopting health systems improving net collection rates 3-5 percentage points. The AHA 2025 AI Landscape Report found 83% of hospital leaders say AI influences operational decisions; 47% say AI governance is a board agenda item. HIMSS 2026 found 62% of CMOs and COOs now personally co-own AI deployment decisions. AI is not replacing the health services manager — it is expanding the scale at which one manager can operate, and simultaneously adding AI governance accountability as a new permanent duty.

BLS projects +29% employment growth 2023-2033 for this occupation — the fastest among major management occupations — consistent with the thesis that AI is expanding the role's scope rather than contracting it. The governance accountability for AI tool deployment is accruing to health services managers, not away from them.

Beat · 2025

AHA's 2025 Health Care AI Landscape Report finds that 83% of hospital leaders report AI now influences operational decisions and 47% say AI governance is a board agenda item. HIMSS 2026 finds that 62% of CMOs and COOs personally co-own AI deployment decisions. Health services managers have become the de facto AI governance executives in their organizations — responsible for vendor selection, model validation, regulatory compliance for AI-generated outputs, and change management across clinical and administrative workforces. This is a new, permanent duty that did not exist in the role five years earlier.

Projection cone · present → 2034

What credible sources project

Scrub the slider past now to anchor each scenario on the scrubber. The spread you see below is the range of futures credible sources project for this role.

BLS Occupational Outlook Handbook 2023-33

→ 2033

+29%

BLS Employment Projections — industry-occupation matrix + replacement-need modeling. 2023-33 cycle: +29% growth ("Much faster than average"), 61,400 projected annual openings. This is the fastest projected growth rate of any major management occupation in the 2023-33 BLS projection cycle. The BLS attributes growth to an aging population, expansion of group medical practices and outpatient care settings, a growing volume of healthcare transactions requiring administrative oversight, and continued regulatory complexity from value-based care, HIPAA, and quality reporting mandates.

BLS Occupational Outlook Handbook 2024-34

→ 2034

+23%

BLS Employment Projections — 2024-34 cycle: +23% growth ("Much faster than average"), 62,100 projected annual openings. The somewhat lower percentage growth in the 2024-34 cycle vs. the 2023-33 cycle reflects a higher 2024 baseline count (616,200 vs. 509,500) and a longer base from which percentage growth naturally moderates. In absolute terms, both projections expect roughly 130,000-140,000 net new positions over the decade. The occupation is projected to produce more new and replacement openings annually than most comparable management occupations.

McKinsey Global Institute (2023)

→ 2030

+22%

McKinsey's July 2023 'Generative AI and the Future of Work in America' projects the largest absolute job gains in healthcare — demand for 3.5 million more health aides and technicians plus additional healthcare professionals. The employment mix through 2030 is expected to shift toward more healthcare and managerial positions. McKinsey explicitly models healthcare management as a growth category because the aging-population demand driver exceeds any productivity gain from administrative AI. The +22% figure approximates the McKinsey healthcare managerial growth signal for the 2023-2030 period, consistent with the BLS OOH growth trajectory.

Eloundou et al. — "GPTs are GPTs" (2023)

→ 2030

+15%

GPT-4 task-by-task labeling against O*NET task statements. Medical and health services managers score in the medium-high LLM-exposure range — many of the coordination, documentation, reporting, and analytical tasks are classified as E1 or E2 (LLM-exposed, with or without tools). The +15% projection approximates the New Bearings augmentation-upside interpretation: LLM exposure for this occupation category is primarily task automation within an expanding role, not role substitution. The information-intensive coordination tasks (prior auth oversight, quality metric reporting, policy drafting) that carry LLM exposure are being automated at the margins while regulatory accountability, governance, and stakeholder management — low-exposure tasks — remain the core of the role. Consistent with BLS +29% growth: Eloundou exposure for management roles is augmentative, not substitutive.

Frey & Osborne (2013)

→ 2030

-3%

Gaussian-process classifier on O*NET task features. Health services and hospital administrators were classified as LOW computerization risk in the F&O framework — the social intelligence, judgment under moral pressure, and regulatory accountability dimensions of the role placed it well below the 50% automation-risk threshold. The -3% figure represents a conservative lower-cone bound, reflecting F&O's implicit prediction of effectively stable employment (low but non-zero displacement at the margins for the most routine administrative tasks). The social intelligence bottleneck — managing a medical staff, credentialing physicians, representing the organization in regulatory surveys — is structural and survives the 2013 technology landscape.

Today, in this role

What's shifting in the work right now

The historical view above shows how this role has moved. This is the present-day detail: which AI tools are picking up which tasks, where the edge still is, and the natural directions this work can grow.

What's changing in your day

Three parts of your work where AI is already doing real lifting — and what stays yours.

AI is sitting alongside you here

Manage patient-flow and operational throughput — reviewing AI-generated bed-management, OR scheduling, and ED throughput dashboards from Epic or Oracle Health, authorizing AI-recommended capacity adjustments (elective procedure rescheduling during surge, diversion protocols, escalation of admit orders), and making the clinical-operations trade-off calls when AI models surface conflicting optimization signals that require contextual judgment about care priorities.^[9],[7],[1]

Tools picking this up

Epic Cosmos AI Insights ↗Oracle Health Clinical AI Agent ↗

Where your edge is

AI throughput tools have measurably compressed ED boarding times and improved OR utilization at early-adopter health systems — the manager who deploys and champions these tools is demonstrating direct ROI to the CFO. Your human edge is in the escalation decisions: when AI recommends diversion and the ER director disagrees, the final call is yours. Build your situational-awareness skills (reading patient acuity and staff strain signals simultaneously) so that your escalation decisions are faster and better-calibrated than the default.

AI is sitting alongside you here

Oversee population health and care-gap closure programs — using Innovaccer or Epic population health tools to identify high-risk patient panels, commissioning Hippocratic AI outreach calls for chronic disease management and preventive care gaps, reviewing AI-generated outreach response rates and clinical outcomes, and presenting population health performance to value-based care contract stakeholders (payers, ACOs) with attribution and intervention narratives.^{[10],[11],[6]}

Tools picking this up

Innovaccer Health AI Platform ↗Hippocratic AI Nurse Co-Pilot ↗

Where your edge is

Population health at scale is now an AI-native function — Innovaccer and Epic can identify care gaps for hundreds of thousands of patients simultaneously. Your value is in the payer-relations and contract accountability layer: interpreting performance data relative to value-based contract targets, negotiating quality bonus thresholds with payers, and making the resource investment decisions (hiring care coordinators, expanding telehealth) that move population health metrics. Master your ACO or MA contract's quality measure specifications — that is the language your payer cares about.

AI is sitting alongside you here

Direct the revenue cycle function — reviewing AI-generated prior-authorization workflow outcomes from AKASA Authorization and Epic claim-scrubbing alerts, setting the escalation threshold for human review, monitoring net collection rate and denial rate trends on Innovaccer or Health Catalyst dashboards, and presenting revenue cycle performance to the CFO and board with variance explanations that require operational context the AI cannot hold.^[5],[12],[9]

Tools picking this up

AKASA Authorization Management ↗Innovaccer Health AI Platform ↗Health Catalyst AI Analytics ↗

Where your edge is

HFMA 2026 finds health systems deploying AI in revenue cycle improve net collection rates by 3-5 percentage points — adopt early and frame it as a direct contribution to the organization's financial margin. Your durable value is in interpreting the AI's performance data (why denial rates spiked for a specific payer in a specific DRG category) and negotiating the payer-contract terms and escalation decisions that no automation touches.

Where this role is heading

Natural next steps for someone with your foundation — not exits, evolutions.

A direction you could grow

Chief Executives

Medical and Health Services Managers who build a track record of AI governance leadership, revenue cycle performance improvement, and clinical quality outcomes naturally become candidates for CNO, CMO, or hospital CEO roles. The BLS projects +29% growth for this occupation through 2034, driven in part by the expansion of the C-suite into AI-governance roles that did not exist five years ago. The CHRO-to-CEO pathway in healthcare follows clinical operations expertise into executive accountability: the manager who demonstrated measurable ROI from AI tool deployments, improved accreditation standing, and led a clinical workforce retention program has the portfolio for a C-suite candidacy. High transition difficulty because the gap from department-level to enterprise accountability requires demonstrated financial performance, board-governance experience, and political capital across medical staff, nursing, and administrative domains simultaneously.

What you'd add

· Executive leadership credentials: MHA (Master of Health Administration) or MBA Healthcare Management — DHA (Doctor of Healthcare Administration) for academic medical center tracks
· Board governance: presenting to a board of directors, governance committee management, strategic planning facilitation at enterprise scale
· Financial stewardship: enterprise operating and capital budget ownership, value-based contract strategy, system-level margin management
· AI governance for health systems: enterprise AI policy design, vendor oversight at scale, regulatory-submission accountability for AI-informed decisions
· Medical staff leadership: Medical Executive Committee relations, credentialing governance at health system level, physician compact development

What it takesA real upskill — but a natural one

Present-day sources

Sources

Every claim on this page traces back to one of the following. Updated 2026-05-23.

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