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chatehr [2026/08/04 16:30]
nigam [Testimonials] |
chatehr [2026/08/05 09:26] (current)
nigam [Automations] |
| ===== Automations ===== | ===== Automations ===== |
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| Automations are fixed prompts applied to defined sets of patients. Across seven operational workflows, these automations convert high-volume, repetitive review into focused, actionable work embedded in the EHR. They help place patients in the right care setting, identify surgical patients who may need medical co-management, strengthen infection surveillance, accelerate referral triage, surface patients who may benefit from inpatient hospice, standardize complex orthopedic referrals, and validate billing accounts. Collectively, they narrow 150 daily charts to about 30 likely Sequoia candidates and roughly 600 charts to 10–40 potential hospice candidates; reduce surgical-site-infection manual review by 40%; process more than 1,000 referrals per day with 17.8% higher throughput; cut referral backlog from five to two business days; and save substantial staff time in orthopedic triage and billing review—demonstrating how validated, workflow-integrated LLM automation can expand capacity, improve consistency, and accelerate patient care while retaining human oversight. | Automations are fixed prompts applied to defined sets of patients. Across seven operational workflows, these automations convert high-volume, repetitive review into focused, actionable work embedded in the EHR. They help place patients in the right care setting, identify surgery cases who may need medical co-management, strengthen infection surveillance, accelerate referral triage, surface patients who may benefit from inpatient hospice, standardize complex orthopedic referrals, and validate billing accounts. |
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| | * [[https://pulse.stanfordmedicine.org/articles/ai-tool-will-streamline-patient-screening-at-sequoia | Streamlined patient screening]] turns a 5 to 20 minutes chart review for 150 patient charts to roughly 30 highly probable cases. |
| | * [[https://pulse.stanfordmedicine.org/articles/chatehr-automation-categorizes-surgical-patients-for-better-care-coordination | Identifying patients for surgical co-management]] lets hospitalists focus on the right neurosurgery, orthopedics, and ENT patients. |
| | * [[https://pulse.stanfordmedicine.org/articles/chatehr-automation-supports-enhanced-surveillance-of-surgical-site-infections | Surveillance of surgical site infections]] reduces chart review by 40%, and improves the timeliness of infection reporting. |
| | * [[https://pulse.stanfordmedicine.org/articles/enterprise-contact-center-launches-chatehr-automation-referral-triage-indexing | Referral triage at the Contact Center]], cuts time by 17.7%, raises throughput by 17.8%, and reduced backlog from five to two days. |
| | * [[https://pulse.stanfordmedicine.org/articles/how-ai-can-help-identify-eligibility-for-inpatient-hospice | Identifying eligibility for Inpatient Hospice]], screens 600 patient charts to find 10–40 eligible cases to avoid 18–20 hours each day. |
| | * [[https://pulse.stanfordmedicine.org/articles/orthopedics-launches-chatehr-automation-referral-summary-tool | Accelerated referral triage in Orthopedics]], processes over 4,700 documents and saves at least 1.7 staff hours each day. |
| | * [[https://pulse.stanfordmedicine.org/articles/patient-financial-services-launches-chatehr-automation-for-billing-review | Review of accounts with an LoA stop bill]], saves 10–15 min/account per resolution and lowers underpayment recovery cost. |
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| ===== Our Journey ===== | ===== Our Journey ===== |
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| ===== News coverage ===== | ===== News coverage ===== |
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