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chatehr [2026/08/04 14:56]
nigam [Automations] |
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 | Streamline patient screening]], which turns a 5 to 20 minutes chart review into near-real-time eligibility insights. Each day the automation narrows 150 patient charts to roughly 30 highly probable cases reducing screening time and helping appropriately fill SN1’s 24 beds, relieve capacity pressure, and get patients to the right care setting faster. | {{ ::chatgpt_image_aug_4_2026_03_12_58_pm.png?nolink |}} |
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| * [[https://pulse.stanfordmedicine.org/articles/chatehr-automation-categorizes-surgical-patients-for-better-care-coordination | Identify patients for medical co-management during surgery]], which replaces a time-consuming, variable manual process with a scalable daily workflow that helps hospitalists focus on the surgical patients most likely to need support—improving efficiency and care coordination across neurosurgery, orthopedics, and ENT. | |
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| * [[https://pulse.stanfordmedicine.org/articles/chatehr-automation-supports-enhanced-surveillance-of-surgical-site-infections | Enhanced surveillance of surgical site infections]], which helps quality teams prioritize cases, reduce manual review burden, and improve the timeliness and accuracy of infection reporting—with a scalable path from colorectal surgery to 27 additional procedures. It reduces the number of patients charts needing a manual review by 40%. | * [[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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| * [[https://pulse.stanfordmedicine.org/articles/enterprise-contact-center-launches-chatehr-automation-referral-triage-indexing | Referral triage at the Enterprise Contact Center]], which classifies urgency and pre-fills key data for more than 1,000 daily referrals. The Enterprise Contact Center cut handling time by 17.7%, increased throughput by 17.8%, and reduced its backlog from about five to two business days—accelerating patient access while freeing staff to focus on exceptions. | \\ |
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| * [[https://pulse.stanfordmedicine.org/articles/how-ai-can-help-identify-eligibility-for-inpatient-hospice | Identify eligibility for Inpatient Hospice]], which narrows roughly 600 patient charts to 10–40 potentially eligible cases. The inpatient hospice automation makes possible a review that current staffing could not sustain—avoiding approximately 18–20 hours of work each day while enabling earlier clinician assessment and more timely, family-centered hospice conversations. | |
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| * [[https://pulse.stanfordmedicine.org/articles/orthopedics-launches-chatehr-automation-referral-summary-tool | Accelerate referral triage in Orthopedics]], which transforms complex orthopedic referral packets into standardized, Epic-integrated summaries. The automation has processed more than 4,700 documents and saves at least 1.7 staff hours each day—accelerating triage and scheduling while improving consistency and freeing staff to resolve missing information. | |
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| * [[https://pulse.stanfordmedicine.org/articles/patient-financial-services-launches-chatehr-automation-for-billing-review | Review of accounts with an LoA stop bill]], which automatically compares Letters of Agreement with billing data and writes match indicators and validation notes into Epic. This automation reduces a 10–15-minute-per-account manual review across hundreds of cases and millions in receivables, thus accelerating account resolution, reducing interpretation errors, and lowering downstream underpayment-recovery costs. | |
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| ===== User Interface ===== | ===== User Interface ===== |
| {{ :screenshot_2026-07-30_at_4.34.09 pm.png?nolink& }} | {{ :screenshot_2026-07-30_at_4.34.09 pm.png?nolink& }} |
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| ==== Testimonials ==== | ==== Testimonials ==== |
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| {{ :chatehr-testimonials.png?nolink& }} | {{ :chatehr-testimonials.png?nolink& }} |
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| ==== Current usage ==== | ==== Current usage ==== |
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| The panels below show current usage as of July 2026. The top left panel shows usage by role and to top right shows usage by service line. The bottom left panel shows usage by time and day of week, and the bottom right panel shows the top 20 tasks performed by the users. | The panels below show current usage as of July 2026, with 3400+ active users, 150,000+ sessions, and 140B tokens processed. The top left panel shows usage by role and to top right shows usage by service line. The bottom left panel shows usage by time and day of week, and the bottom right panel shows the top 20 tasks performed by the users. |
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| {{ ::screenshot_2026-08-03_at_1.42.18 pm.png?nolink |}} | {{ ::screenshot_2026-08-03_at_1.42.18 pm.png?nolink |}} |
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| ===== Our Journey ===== | ===== Our Journey ===== |
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| {{ ::chatgpt_image_aug_3_2026_06_24_36_pm.png?nolink |}} | {{ ::chatgpt_image_aug_3_2026_06_24_36_pm.png?nolink |}} |
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| ===== News coverage ===== | ===== News coverage ===== |
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