EHR and Electronic Prescribing Errors: Alert Fatigue and Physician Liability

Table of Contents

1. The Promise and Peril of EHR Systems
2. Types of EHR and e-Prescribing Errors
3. Alert Fatigue: When Safety Systems Become Liability
4. EHR Usability and Patient Safety
5. Clinical Decision Support Systems (CDSS)
6. Legal Liability for EHR Errors
7. Proving Negligence in EHR Cases
8. The Future: AI in Prescribing and Liability
9. Frequently Asked Questions

The Promise and Peril of EHR Systems

Electronic Health Records (EHRs) were introduced with the promise of reducing medication errors through:

• Legible orders (eliminating handwriting errors)
• Clinical decision support (drug interaction alerts, allergy alerts, dose checking)
• Barcode medication administration integration
• Real-time access to patient data

The federal HITECH Act of 2009 incentivized EHR adoption, and by 2025, virtually all hospitals and most physician practices in New York use EHR systems. The major EHR vendors include Epic, Cerner (Oracle Health), Meditech, and Allscripts.

While EHRs have reduced certain types of errors (particularly those related to illegible handwriting), they have introduced new categories of errors — and new forms of malpractice liability.

[Link to: /medical-malpractice/medication-errors]

Types of EHR and e-Prescribing Errors

Wrong Patient Selection

EHR systems display patient lists, and a momentary click on the wrong name can send an order to the wrong patient. This is particularly dangerous in systems with similar patient names or when multiple patient charts are open simultaneously. The standard of care requires verifying the patient's identity at every order entry.

Order Set Errors

EHRs use order sets — pre-built collections of orders for specific conditions (e.g., "sepsis bundle," "CHF admission"). While order sets improve efficiency, they can cause errors when:

• The wrong order set is selected
• Orders within the set are not customized for the individual patient
• The order set contains outdated or incorrect orders
• The physician clicks "accept all" without reviewing each order

Dropdown and Auto-complete Errors

When typing a medication name, the EHR may auto-complete to a different medication. Similarly, dropdown menus for dose, route, or frequency can lead to selecting the wrong value. These errors are particularly common when:

• The EHR interface is poorly designed
• The dropdown list is long or poorly organized
• The physician is rushing or distracted
• The auto-complete algorithm suggests the wrong entry

Copy-Forward Errors

EHRs allow physicians to copy forward notes and orders from previous encounters. While efficient, this practice can perpetuate errors:

• Continuing medications that should have been discontinued
• Copying notes that reference the wrong patient or encounter
• Perpetuating outdated clinical information

Alert Override Errors

Clinical decision support systems generate alerts for drug interactions, allergies, duplicate therapy, and dose checking. When physicians override these alerts without clinical justification, the safety system is defeated. Studies show override rates of 49% to 96% for all alerts.

E-prescribing Transmission Errors

E-prescribing involves transmitting prescriptions electronically from the EHR to the pharmacy. Errors can occur when:

• The prescription is transmitted to the wrong pharmacy
• The transmission is garbled or truncated
• The pharmacy's system interprets the data differently than the EHR
• Free-text fields are misinterpreted

Interface and Interoperability Errors

When EHRs interface with other systems (pharmacy, laboratory, smart pumps), data can be lost, duplicated, or corrupted. Interface errors can cause:

• Medication orders not reaching the pharmacy
• Wrong patient data being transmitted
• Duplicate orders being created

Alert Fatigue: When Safety Systems Become Liability

What Is Alert Fatigue?

Alert fatigue is the desensitization that occurs when healthcare providers are exposed to too many clinical alerts. When the EHR generates alerts for every potential drug interaction, allergy, dose range, and duplicate therapy — many of which are clinically irrelevant — providers learn to override alerts automatically without reading them.

The Scope of the Problem

Research consistently shows:

• Physicians receive an average of 63 alerts per day in some EHR systems
• Override rates range from 49% to 96% for all alerts
• For drug interaction alerts specifically, override rates exceed 90%
• Most overridden alerts are indeed clinically irrelevant, but a small percentage are critical

Why Alert Fatigue Creates Legal Liability

When a physician overrides a clinically significant alert — such as a severe drug interaction or a documented allergy — and the patient is harmed, the override becomes evidence of negligence. The EHR audit trail will show:

• The alert was generated
• The physician overrode it
• Whether the physician documented a reason for the override

The Institutional Responsibility

Hospitals have a responsibility to tune their clinical decision support systems to reduce alert fatigue:

• Alert specificity — Alerts should be clinically relevant and actionable
• Tiered alerts — Critical alerts should be interruptive; less critical alerts should be informational
• Alert monitoring — Hospitals should monitor override rates and investigate high rates
• Alert refinement — Alert rules should be regularly reviewed and refined

Failure to tune CDS systems can create institutional liability — a hospital that configures its EHR to generate hundreds of irrelevant alerts is contributing to the culture of alert fatigue.

[Link to: /medical-malpractice/medication-errors/5-rights-of-administration]

EHR Usability and Patient Safety

Poor Usability as a Safety Hazard

The FDA, ONC (Office of the National Coordinator for Health IT), and The Joint Commission have all recognized that poor EHR usability contributes to medication errors. Common usability issues include:

• Cluttered screens — Too much information displayed at once, making it easy to miss critical data
• Inconsistent navigation — Different workflows for similar tasks, causing confusion
• Default values — EHR defaults that are not appropriate for all patients (e.g., defaulting to oral route when IV is needed)
• Small click targets — Buttons that are too small, leading to wrong selections
• Color coding — Inconsistent or absent color coding for high-alert medications

The SAFER Guides

The ONC developed the SAFER (Safety Assurance Factors for EHR Resilience) Guides to help healthcare organizations assess EHR safety. The guides address:

• High-priority practices for safe EHR use
• Organizational responsibility for EHR safety
• Contingency planning for EHR downtime
• System interfaces and interoperability

EHR Vendor Liability

In some cases, the EHR vendor may share liability for medication errors caused by software defects, poor usability, or failure to meet safety standards. Under New York products liability law, claims against EHR vendors may be based on:

• Design defect — The EHR is inherently unsafe due to its design
• Failure to warn — The vendor failed to adequately warn of known safety risks
• Breach of warranty — The EHR did not perform as warranted

However, EHR vendor liability is complex because of federal preemption issues under the 21st Century Cures Act and the ONC Health IT Certification Program.

Clinical Decision Support Systems (CDSS)

How CDSS Works

Clinical decision support systems provide physicians with:

• Drug-drug interaction alerts — Warning when two medications may interact
• Drug-allergy alerts — Warning when a medication conflicts with a documented allergy
• Dose checking — Warning when a dose is outside the recommended range
• Duplicate therapy alerts — Warning when a medication duplicates an existing order
• Drug-condition alerts — Warning when a medication is contraindicated for a patient's condition
• Drug-pregnancy alerts — Warning when a medication is contraindicated in pregnancy

Legal Significance of CDSS

When a CDSS alert is generated and overridden, the EHR audit trail preserves:

• The type of alert
• The specific clinical content (which drug, which interaction)
• The user who received the alert
• Whether the alert was overridden
• The documented reason for override (if any)

This audit trail is powerful evidence in malpractice cases. It can prove that the physician was warned of a risk and chose to proceed anyway.

Legal Liability for EHR Errors

Physician Liability

Physicians remain responsible for the orders they enter, regardless of the EHR system's design. If a physician:

• Selects the wrong patient
• Chooses the wrong medication from an auto-complete list
• Overrides a clinically significant alert without justification
• Uses "copy forward" without reviewing each order

...the physician can be held liable for the resulting harm.

Hospital Liability

Hospitals are responsible for:

• Selecting and implementing safe EHR systems
• Configuring CDS alerts appropriately
• Training staff on EHR use
• Monitoring alert override rates
• Maintaining EHR system security and integrity

EHR Vendor Liability

EHR vendors may be liable for:

• Software defects that cause incorrect data display
• Poor usability that contributes to errors
• Failure to meet ONC safety certification requirements
• Failure to warn of known safety risks

The 21st Century Cures Act

The 21st Century Cures Act (2016) includes provisions on EHR safety, including "information blocking" prohibitions and EHR certification requirements. While the Act does not create a private right of action, it establishes safety standards that can be referenced in malpractice cases.

Proving Negligence in EHR Cases

EHR Audit Trail

The EHR audit trail is the most important evidence in EHR error cases. It shows:

• Who accessed the patient's record and when
• What orders were entered and by whom
• What alerts were generated and whether they were overridden
• What modifications were made to orders
• When the patient was identified for each order

In New York, under PHL § 18 and CPLR § 3121, plaintiffs are entitled to obtain EHR audit trails during discovery.

Litigation Hold

A litigation hold letter should be sent immediately to preserve:

• EHR audit trails
• CDS configuration data
• Alert logs
• System access logs
• Order set configurations
• Interface logs

Expert Testimony

EHR cases may require specialized experts:

• A physician expert in the relevant specialty
• A nursing expert for administration-related errors
• A pharmacy expert for pharmacy-related errors
• A health informatics expert or EHR usability expert to testify about EHR design and safety standards

[Link to: /medical-malpractice/medication-errors/known-allergens]

The Future: AI in Prescribing and Liability

AI-Assisted Prescribing

Artificial intelligence is increasingly being used in medication management:

• AI dosing tools — Algorithms that calculate optimal doses based on patient data
• Predictive analytics — Identifying patients at risk for adverse drug events
• AI scribes — Transcribing physician notes and orders using natural language processing
• Drug interaction AI — More sophisticated interaction checking than rule-based CDSS

Legal Implications of AI in Prescribing

When AI contributes to a medication error, liability questions include:

• Is the physician liable for relying on AI recommendations?
• Is the hospital liable for implementing an AI system?
• Is the AI developer liable for algorithm defects?
• What is the standard of care when AI and human judgment conflict?

New York has not yet developed specific case law on AI liability in medical malpractice, but the existing framework — professional standard of care, products liability, informed consent — will likely apply. The key question will be whether the physician's reliance on AI was reasonable under the circumstances.

The AMA's Guidance

The American Medical Association recommends that AI be used as a decision support tool, not a decision replacement. Physicians must:

• Understand the AI's capabilities and limitations
• Verify AI recommendations against clinical judgment
• Document the reasoning behind accepting or rejecting AI recommendations
• Maintain ultimate responsibility for clinical decisions

Frequently Asked Questions

What is alert fatigue in EHR systems?

Alert fatigue is the desensitization that occurs when healthcare providers receive too many clinical alerts and begin overriding them without reading them. Override rates range from 49% to 96% for all alerts. Alert fatigue defeats the purpose of clinical decision support systems and creates legal liability when significant alerts are overridden.

Can I sue the hospital for an EHR medication error?

Yes. Hospitals are responsible for selecting and implementing safe EHR systems, configuring clinical decision support appropriately, training staff, and monitoring alert override rates. If the hospital's EHR configuration contributed to a medication error, the hospital can be held liable.

Can I sue the EHR vendor?

EHR vendor liability is possible but complex. Claims may be based on design defect, failure to warn, or breach of warranty. However, federal preemption issues under the 21st Century Cures Act and ONC certification requirements complicate vendor liability claims.

What is an EHR audit trail?

An EHR audit trail is a log of all actions taken within the EHR system — who accessed the record, what orders were entered, what alerts were generated and overridden, and when each action occurred. The audit trail is critical evidence in malpractice cases involving EHR errors.

What is a clinical decision support system (CDSS)?

A CDSS is software within the EHR that provides physicians with alerts for drug interactions, allergies, dose checking, duplicate therapy, and other safety checks. CDSS is designed to prevent medication errors but is only effective when alerts are clinically relevant and acted upon.

Can AI in prescribing create malpractice liability?

Yes. When AI contributes to a medication error, liability questions include whether the physician's reliance on AI was reasonable, whether the hospital properly implemented the AI system, and whether the AI developer is liable for algorithm defects. The AMA recommends AI be used as decision support, not decision replacement.

How do I get the EHR audit trail for my case?

Under New York PHL § 18 and CPLR § 3121, plaintiffs are entitled to obtain EHR audit trails during discovery. Your attorney should also send a litigation hold letter immediately to preserve audit trails, alert logs, system configurations, and other electronic evidence.

This article is for informational purposes only and does not constitute legal advice. Prior results do not guarantee a similar outcome. No attorney-client relationship is created by reading this article or contacting MDLaw Firm.