Paubox reported the controversy between hospitals, federal regulators and third party tracking technologies in January 2024. In that discussion it was noted how tracking code on healthcare websites can transmit data to third party companies. The simple fact is that a normal digital workflow has the potential to become a privacy issue when an organization fails to verify what information passes through it or where that information goes.

Patient data moves through many workflows between care providers, electronic health records (EHRs), labs, billing platforms, vendors, and communication systems. A digital process can run exactly how it is configured to and still generate an incorrect result if the data, recipient, permissions, or output have not been validated.

Validation confirms that information or an action adheres to a predefined set of rules. Health care organizations should have these checks in place anytime protected health information (PHI) enters a workflow, switches systems, reaches an intended recipient, or triggers a follow-up task.

 

What workflow validation means

Healthcare workflow validation revolves around three core concepts. What goes into a system, what occurs during info transfer between systems, and what exits the organization.

An evaluation published in the Journal of Medical Internet Research indicates that “incomplete EMR data were found to impact clinical outcomes”. Other noted effects include damage to communication, research, and organizational outcomes. A single missing field can therefore compromise all subsequent processes that reference it.

Providers can use validation rules to flag an error where it can first be found. Then, providers can use HIPAA compliant email to send a secure correction request. The Office for Civil Rights under the Department of Health and Human Services (HHS OCR) also recommends that regulated entities discover how electronic PHI enters, is used, and exits their internal systems.

 

Patient intake and registration

HIPAA providers can validate required registration fields, proper format, and potential duplicate patient record submissions.

When testing methodologies for preventing duplicate patient registrations, researchers reviewed 398,939 confirmed duplicate patient records. They discovered that the middle-name field was different in 58.30% of duplicate pairs where a nondefault value was entered. Social Security numbers were different in 53.54% of pairs.

These findings highlight why duplicate matching should not rely on a single field. Rather, an automated system can assess multiple identifiers then forward uncertain matches to staff for review.

HIPAA secure email gives providers a way to request patients confirm or update demographic data through a secure medium. HHS email usage guidelines also lists verifying an email address or sending an initial confirmation message as methods to prevent accidental disclosure.

Even if an address is formatted correctly, it can still belong to the wrong patient. Format validation is only one part of the solution. Patient matching rules, confirmation steps, and human verification are also necessary when records appear to conflict.

 

Forms, referrals, and uploaded information

Healthcare forms can confirm patients answered all required questions, selected an approved response, signed the document, and attached a requested file. Likewise, a referral form might not allow submission until the referring provider, clinical reason for referral, and supporting records have been entered.

Another review examined electronic referral systems and their impact on clinical quality. Results showed electronic referrals “reduce missing or incomplete information in the referral process.” When an error rates review analyzed the error rate when clinical and research data were processed manually versus electronically, reported error rates ranged from 2 to 2784 errors per 10,000 data fields. Although the study focused on clinical research data, the disparity points out the value of structured collection and automated validation when processing healthcare information. File uploads require additional checks such as permitted file types, file size limits, required attachments, and virus scanning. Files that fail to pass policy rules should be quarantined or rejected.

 

Data moving between healthcare systems

Data can appear complete in one system and incomplete once it’s been mapped to another system. APIs can automate this process by allowing different systems to communicate with each other, but their requests and responses should still be validated.

Fast Healthcare Interoperability Resources (FHIR) is a standard that dictates how to structure and transmit electronic healthcare information. Researchers in a JMIR paper studied several FHIR tests and found a statistically significant positive relationship between repeated testing and specification compliance.

Healthcare organizations can validate if required fields are present, if data types match specifications, patients are correctly identified, API keys are valid, response codes make sense, and software versions will work together. Invalid requests should go to an exception queue instead of being marked as completed tasks.

 

Test results and outbound messages

Clinical communications must include validation. There is no assurance a message was generated that the intended provider saw, acknowledged, and acted upon it. A laboratory system can send a notification without validating that the correct provider received and responded to it.

According to an Author Manuscript study on abnormal-result alerting practices, clinicians failed to document follow-up within 30 days of automated abnormal outpatient laboratory results 7% of the time and automated abnormal imaging results 8% of the time. For both scenarios, providers also failed to acknowledge alerts 18% of the time for imaging and 10% of the time for laboratory results. Automating notifications was not enough to close the loop.

Instead, healthcare organizations can validate that a test or procedure was completed, the correct individual was notified, the message was successfully sent, responsibility was assigned, and follow-up was documented. Another study suggested that emailing test results may help increase awareness of pending and finalized results but emphasized the importance of defined responsibilities and efficient processes.

In their data brief report, Paubox’s 2026 Healthcare Data Breach Trends found that 60% of polled healthcare organizations shared PHI via email unintentionally. HIPAA compliant email platforms can utilize data loss prevention (DLP) rules that scan messages and attachments and then quarantine those that require user intervention.

 

Audit logs and manual review

Without a record of failed validations, successful validation is pointless. An audit log keeps a time-stamped record of system events. Clinical researchers wrote that EHR audit logs create a “time-sequenced record of actions performed by clinicians.”

Healthcare organizations have the option to record which rule was triggered, what result occurred, when it happened, which workflow was affected, and what exception was raised. If an alert repeatedly fails, someone can investigate if a form needs updating, a service isn’t integrated, a routing rule is inaccurate, or staff need additional training. HIPPA regulation also requires audit logs and periodic review. Although many parts of the validation process can be automated, humans must always review ambiguous patient matches, clinical significance, authorization exceptions, false positives, and other scenarios that need explanation.

 

FAQs

Can healthcare providers enter PHI into an AI tool?

Providers should only enter PHI into an AI tool that their organization has approved.

 

Is a business associate agreement (BAA) enough to make an AI workflow HIPAA compliant?

A BAA establishes permitted uses of PHI and requires the vendor to apply appropriate safeguards. However, HHS explains that covered entities and business associates must also conduct risk analyses and comply with the applicable HIPAA requirements.

 

Can AI-generated messages be sent through HIPAA compliant email?

Yes, provided the AI use has been approved and the message is validated before it is sent. Secure email protects PHI during transmission, but encryption does not confirm that an AI-generated message is medically accurate or addressed to the correct patient.

 

What should providers check before sending AI-generated content to a patient?

Providers should confirm that the content matches the patient’s medical record and does not contain invented facts, missing warnings, or instructions intended for another patient. They should also review the language for clarity, reading level, and appropriate urgency.