# Medical Equipment Preparers

> Prepare, sterilize, install, or clean laboratory or healthcare equipment. May perform routine laboratory tasks and operate or inspect equipment.

- **SOC code:** 31-9093.00
- **Canonical URL:** https://singulariki.com/roles/role-31-9093-00
- **Also known as:** Central Service Technician (CST), Central Sterile Supply Technician (CSS Technician), Certified Registered Central Service Technician (CRCST), Sterile Processing Technician (Sterile Processing Tech), Central Processing Technician (CPT), Instrument Technician, Sterile Preparation Technician, Sterile Processing and Distribution Technician (SPD Tech)
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Operate and maintain steam autoclaves, keeping records of loads completed, items in loads, and maintenance procedures performed.
- Clean instruments to prepare them for sterilization.
- Organize and assemble routine or specialty surgical instrument trays or other sterilized supplies, filling special requests as needed.
- Record sterilizer test results.
- Examine equipment to detect leaks, worn or loose parts, or other indications of disrepair.
- Report defective equipment to appropriate supervisors or staff.
- Disinfect and sterilize equipment, such as respirators, hospital beds, or oxygen or dialysis equipment, using sterilizers, aerators, or washers.
- Maintain records of inventory or equipment usage and order medical instruments or supplies when inventory is low.
- Stock crash carts or other medical supplies.
- Start equipment and observe gauges and equipment operation to detect malfunctions and to ensure equipment is operating to prescribed standards.
- Check sterile supplies to ensure that they are not outdated.
- Purge wastes from equipment by connecting equipment to water sources and flushing water through systems.

**Emerging tasks** (O*NET):
- Order medical supplies for healthcare facilities or laboratories.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Customer and Personal Service _(knowledge)_
- Near Vision _(ability)_
- English Language _(knowledge)_
- Problem Sensitivity _(ability)_
- Oral Comprehension _(ability)_
- Critical Thinking _(essential_skill)_
- Biology _(knowledge)_
- Monitoring _(essential_skill)_
- Quality Control Analysis _(transferable_skill)_
- Active Listening _(essential_skill)_
- Operations Monitoring _(transferable_skill)_
- Oral Expression _(ability)_

**Skills in demand:**
- English Language _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Biology _(Specialized Skill)_
- Speech Recognition _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Visualization _(Specialized Skill)_
- Time Management _(Common Skill)_
- Microsoft Word _(Common Skill)_

**Tools & technology:**
- eClinicalWorks EHR software _(hot technology)_
- Kronos Workforce Timekeeper _(hot technology)_
- MEDITECH software _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft SharePoint _(hot technology)_
- Microsoft Word _(hot technology)_
- Calendar software
- Database software
- Email software

## AI exposure & outlook

- **AI task-overlap index:** 14th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 28th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 19th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 3rd percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 63rd percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 10.0% growth (Growing fast); 10.9k annual openings; 76.5k → 84.2k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $46,490; 72,760 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

---
_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-31-9093-00_