Which AI agents work with Endo Inpatient Ehr Glycemic Surveillance Vs Standard Care?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Who published Endo Inpatient Ehr Glycemic Surveillance Vs Standard Care?

dromlakhani (@dromlakhani) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Endo Inpatient Ehr Glycemic Surveillance Vs Standard Care by dromlakhani

Name: Endo Inpatient Ehr Glycemic Surveillance Vs Standard Care
Rating: 4.2 (5 reviews)
Author: dromlakhani

Endo Inpatient Ehr Glycemic Surveillance Vs Standard Care

Recommends implementing inpatient glycemic surveillance and management programs that leverage EHR data to identify and mitigate hypoglycemia risk versus standard care. Triggered by establishing hypoglycemia reduction programs, using EHR alerts for glucose trends, or responding to CMS hypoglycemia quality measures.

dromlakhani Updated Sep 8, 2026 10 repo stars

File contents

Inpatient Glycemic Surveillance and Management Programs Leveraging EHR Data vs Standard Care for Hypoglycemia Risk

STEP 1 — Gather Information

Collect inpatient glucose data from the EHR, including point-of-care blood glucose (POC-BG), laboratory-drawn values, and continuous glucose monitoring (CGM) if available; analyze trends for high and low glucose patterns to generate proactive alerts.

STEP 2 — Rule In / Rule Out

Determine if the patient has a history of severe hypoglycemia (requiring assistance), impaired awareness of hypoglycemia (IAH), or medical conditions predisposing to severe hypoglycemia (renal or hepatic dysfunction); if any are present, rule in as high risk; otherwise, rule out as standard care.

STEP 3 — Classify or Stratify

Stratify ruled-in high-risk patients by the number of risk factors present (e.g., single factor vs multiple factors) to prioritize intensity of surveillance and intervention.

STEP 4 — Decide

For patients stratified as high risk, activate the EHR-based glycemic surveillance program with real-time alerts and staff-driven insulin adjustments; for low-risk or ruled-out patients, continue standard glucose monitoring without enhanced EHR surveillance.

Clinical Guardrails / Mimics / Pitfalls

Do not rely solely on CGM values without POC-BG confirmation; avoid using the program in patients with conditions that impair CGM accuracy (e.g., hypotension, vasoconstriction, edema, DKA); ensure staff are trained to interpret and act on alerts to prevent alarm fatigue; verify EHR integration includes all glucose sources before launching surveillance.

Concrete Clinical Example

A 68‑year‑old woman with type 2 diabetes and CKD stage 3 is admitted for pneumonia; her EHR shows a prior episode of severe hypoglycemia requiring assistance. The surveillance system detects a declining glucose trend and triggers an alert; the nurse reduces her basal insulin infusion, preventing a hypoglycemic event during hospitalization.

Source: Management of Individuals With Diabetes at High Risk for Hypoglycemia: An Endocrine Society Clinical Practice Guideline, Endocrine Society, 2023, https://doi.org/10.1210/clinem/dgac596

---name: endo-inpatient-ehr-glycemic-surveillance-vs-standard-caredescription: Recommends implementing inpatient glycemic surveillance and management programs that leverage EHR data to identify and mitigate hypoglycemia risk versus standard care. Triggered by establishing hypoglycemia reduction programs, using EHR alerts for glucose trends, or responding to CMS hypoglycemia quality measures.---# Inpatient Glycemic Surveillance and Management Programs Leveraging EHR Data vs Standard Care for Hypoglycemia Risk## STEP 1 — Gather InformationCollect inpatient glucose data from the EHR, including point-of-care blood glucose (POC-BG), laboratory-drawn values, and continuous glucose monitoring (CGM) if available; analyze trends for high and low glucose patterns to generate proactive alerts.## STEP 2 — Rule In / Rule OutDetermine if the patient has a history of severe hypoglycemia (requiring assistance), impaired awareness of hypoglycemia (IAH), or medical conditions predisposing to severe hypoglycemia (renal or hepatic dysfunction); if any are present, rule in as high risk; otherwise, rule out as standard care.## STEP 3 — Classify or StratifyStratify ruled-in high-risk patients by the number of risk factors present (e.g., single factor vs multiple factors) to prioritize intensity of surveillance and intervention.## STEP 4 — DecideFor patients stratified as high risk, activate the EHR-based glycemic surveillance program with real-time alerts and staff-driven insulin adjustments; for low-risk or ruled-out patients, continue standard glucose monitoring without enhanced EHR surveillance.## Clinical Guardrails / Mimics / PitfallsDo not rely solely on CGM values without POC-BG confirmation; avoid using the program in patients with conditions that impair CGM accuracy (e.g., hypotension, vasoconstriction, edema, DKA); ensure staff are trained to interpret and act on alerts to prevent alarm fatigue; verify EHR integration includes all glucose sources before launching surveillance.## Concrete Clinical ExampleA 68‑year‑old woman with type 2 diabetes and CKD stage 3 is admitted for pneumonia; her EHR shows a prior episode of severe hypoglycemia requiring assistance. The surveillance system detects a declining glucose trend and triggers an alert; the nurse reduces her basal insulin infusion, preventing a hypoglycemic event during hospitalization.**Source:** Management of Individuals With Diabetes at High Risk for Hypoglycemia: An Endocrine Society Clinical Practice Guideline, Endocrine Society, 2023, https://doi.org/10.1210/clinem/dgac596

Frequently asked questions