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Run npx skillmds@latest add dromlakhani/es-ehr-glycemic-surveillance-vs-standard-care-inpatient in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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

Es Ehr Glycemic Surveillance Vs Standard Care Inpatient by dromlakhani

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

Es Ehr Glycemic Surveillance Vs Standard Care Inpatient

Recommends implementing EHR-leveraged glycemic surveillance and management programs for hospitalized patients at risk for hypoglycemia to reduce hypoglycemic episodes. Triggered when clinicians ask, "Should I implement EHR-based glycemic surveillance for this inpatient at risk for hypoglycemia?" or "Is system-based glycemic management preferred over standard care?"

dromlakhani Updated Sep 8, 2026 10 repo stars

File contents

EHR-Based Glycemic Surveillance vs Standard Care for Inpatients

STEP 1 — Gather Information

Collect patient risk factors for hypoglycemia (history of severe hypoglycemia requiring assistance, impaired awareness of hypoglycemia, renal or hepatic dysfunction, age ≥65 years) and compile EHR-derived glycemic data (point-of-care glucose, laboratory glucose, CGM if available) to identify patterns of hypo- and hyperglycemia.

STEP 2 — Rule In / Rule Out

Determine if the patient meets criteria for high risk for hypoglycemia (yes/no). If yes, proceed to EHR-based surveillance; if no, continue standard care.

STEP 3 — Classify or Stratify

Stratify risk by severity (e.g., prior severe hypoglycemia requiring assistance vs impaired awareness alone) and glycemic variability (frequency of glucose <70 mg/dL or >180 mg/dL) to prioritize intensity of surveillance and intervention.

STEP 4 — Decide

For high-risk patients, activate an EHR-leveraged glycemic surveillance program that provides real-time alerts for low/high glucose trends and enables protocol-driven insulin adjustments; for low-risk patients, maintain routine point-of-care glucose monitoring without automated surveillance.

Clinical Guardrails / Mimics / Pitfalls

Do not rely solely on CGM or EHR glucose values for insulin dosing without confirmatory point-of-care testing; avoid using the system in patients with conditions that impair CGM accuracy (severe hypotension, vasoconstriction, edema, DKA, high-dose vitamin C, hydroxyurea); ensure staff are trained to interpret alerts and act promptly; do not replace clinical judgment with automated alerts.

Concrete Clinical Example

A 70-year-old woman with type 2 diabetes on basal-bolus insulin, admitted for cellulitis, with a prior episode of severe hypoglycemia requiring glucagon. EHR surveillance detects a trend of morning glucose <70 mg/dL over two days; the glycemic team reduces her basal insulin dose, preventing further lows.

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

---name: es-ehr-glycemic-surveillance-vs-standard-care-inpatientdescription: Recommends implementing EHR-leveraged glycemic surveillance and management programs for hospitalized patients at risk for hypoglycemia to reduce hypoglycemic episodes. Triggered when clinicians ask, "Should I implement EHR-based glycemic surveillance for this inpatient at risk for hypoglycemia?" or "Is system-based glycemic management preferred over standard care?"---# EHR-Based Glycemic Surveillance vs Standard Care for Inpatients## STEP 1 — Gather InformationCollect patient risk factors for hypoglycemia (history of severe hypoglycemia requiring assistance, impaired awareness of hypoglycemia, renal or hepatic dysfunction, age ≥65 years) and compile EHR-derived glycemic data (point-of-care glucose, laboratory glucose, CGM if available) to identify patterns of hypo- and hyperglycemia.## STEP 2 — Rule In / Rule OutDetermine if the patient meets criteria for high risk for hypoglycemia (yes/no). If yes, proceed to EHR-based surveillance; if no, continue standard care.## STEP 3 — Classify or StratifyStratify risk by severity (e.g., prior severe hypoglycemia requiring assistance vs impaired awareness alone) and glycemic variability (frequency of glucose <70 mg/dL or >180 mg/dL) to prioritize intensity of surveillance and intervention.## STEP 4 — DecideFor high-risk patients, activate an EHR-leveraged glycemic surveillance program that provides real-time alerts for low/high glucose trends and enables protocol-driven insulin adjustments; for low-risk patients, maintain routine point-of-care glucose monitoring without automated surveillance.## Clinical Guardrails / Mimics / PitfallsDo not rely solely on CGM or EHR glucose values for insulin dosing without confirmatory point-of-care testing; avoid using the system in patients with conditions that impair CGM accuracy (severe hypotension, vasoconstriction, edema, DKA, high-dose vitamin C, hydroxyurea); ensure staff are trained to interpret alerts and act promptly; do not replace clinical judgment with automated alerts.## Concrete Clinical ExampleA 70-year-old woman with type 2 diabetes on basal-bolus insulin, admitted for cellulitis, with a prior episode of severe hypoglycemia requiring glucagon. EHR surveillance detects a trend of morning glucose <70 mg/dL over two days; the glycemic team reduces her basal insulin dose, preventing further lows.**Source:** Management of Individuals With Diabetes at High Risk for Hypoglycemia: An Endocrine Society Clinical Practice Guideline, Endocrine Society, 2023, DOI: 10.1210/clinem/dgac596

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