Healthcare is under constant siege from ever-growing cyberattacks. Patient health data remains at high risk of breaches. One system glitch or stolen login credentials can expose millions of sensitive records. That’s why traditional security measures like passwords or phone verification are no longer sufficient. Healthcare biometric technology holds promise.
Adding biometric security measures, like fingerprints or facial scans, offers a much safer and effortless way to verify identity and improve electronic health record (EHR) matching across different health systems.
Key Takeaways
- Biometric solutions reduce medical record mix-ups and data leaks.
- Fingerprint, palm, iris, or face scans offer safer and faster patient identity verification.
- A balanced budget plan is key to adopting biometrics and training staff.
- Biometric data stored on patients’ personal devices require additional safeguards
The Need for Biometric Security in Healthcare
Understanding Data Breach Vulnerabilities
Healthcare facilities typically store a massive amount of sensitive health data on cloud servers so that both patients and providers can access it anytime, anywhere. But many users still use weak passwords or reuse the same passwords that they’ve used to open accounts on various platforms and websites, leaving loopholes for hackers to exploit and thereby gain access to health systems.
However, password attacks are just the tip of the iceberg. Hackers use phishing, spoofing, ransomware, malware, spyware, and many other tactics to lure users into sharing their login credentials or installing malicious software on their devices (1).
Over the years, the incidence of these cyberattacks has increased at a record speed. In 2023 alone, the HHS Office for Civil Rights (OCR) in the U.S. tracked 725 healthcare data breaches. The damage? Over 133 million highly sensitive health records were exposed, with each breach costing $10.93 million on average (2).
With biometric security, healthcare leaders can add an extra layer of safety to protect sensitive personal data from unauthorized access.
Importance of Patient Matching and Biometrics
Most Americans typically have multiple EHRs from different facilities. A majority of senior adults, for example, visit at least five doctors annually. As a result, providers often struggle to match those records, risking patient harm. Surveys reveal that nearly 50% of the time, these records get mismatched. These errors waste roughly $6 billion every year in the U.S. healthcare system (3),(4).
Incorporating biometrics in medical settings could help improve matching rates. These traits rarely change and are simple to use, as people already rely on them for phone logins. When paired with demographic details like birthdates, biometrics could make matching safer and error-free (4).
How Biometric Technology Works
Fingerprint, facial, iris, and palm scans are unique to each person. These features contain complex patterns that rarely change over time. Even when changes occur, they’re so small and subtle that they remain inseparable from the patient. As such, biometrics offers high precision in identity verification.
Fingerprint and palm scanning devices are relatively inexpensive. These small readers can be attached to computers or embedded in smartphones. However, older adults or those with skin issues may face difficulties.
Facial and iris recognition are contactless biometric options. Since most smartphones already use facial unlocks today, hospitals can readily adapt them for real-time patient matching, facilitating fast triage or urgent admissions. But one downside is that they require costly specialized cameras. Small hospitals may shy away due to budget constraints and training demands. Moreover, bias is possible if the system lacks diverse training data (4),(5),(6).
Advantages of Biometrics Over Traditional Security Measures
Reduced Data Breach Risks
Hackers can steal, reuse, or brute-force passwords. But they can’t do the same with facial or fingerprint scans, as patient identity is tied to their unique traits. That’s why providers implementing biometrics in medical settings have reported fewer data breaches (5).
Improved Patient Confidentiality
Secure logins mean little room for hackers to exploit. Locking each EHR with a patient’s biometrics ensures top-tier privacy. With fingerprint or facial recognition, staff can skip typing passwords, cutting the risk of credential leaks. This level of patient data biometric protection not only prevents accidental data breaches but also reassures patients that their information is safe (6),(7).
Streamlined Access to Medical Records
Every second matters during a medical emergency. Biometric logins give immediate EHR access to authorized personnel. With biometric security, healthcare staff can skip entering username-password combos. As a result, efficiency increases across the board, freeing resources for patient care (5),(7).
Implementation Challenges and Ethical Concerns
Cost and Technology Infrastructure
Adopting healthcare biometric technology requires a big upfront investment: new devices, system upgrades, and staff training. For smaller hospitals with limited IT resources, this can be very taxing. However, a carefully planned budget can balance the initial burden with long-term savings, as better security reduces data breach costs and operational disruptions (2),(5).
Privacy, Consent, and Data Storage
Because biometric data is permanent, any breach could compromise patient privacy indefinitely. HIPAA laws shield stored records in “covered entities,” but third-party apps may slip through regulatory loopholes. Healthcare leaders thus must ensure user consent and robust encryption.
Privacy by design can be a possible solution. For instance, some health IT systems store only encrypted templates instead of raw images. This approach respects patient autonomy while promoting patient data biometric protection (5),(7).
Regulatory and Standards Framework
No standard guidelines currently exist for using biometrics in healthcare. Vendors thus often differ in how they collect, store, and utilize biometric data, complicating system interoperability. The Office for the National Coordinator (ONC) and industry stakeholders are pushing for standardization, but progress is slow. In the meantime, hospitals must adopt best practices to ensure consistent results (5).
Strengthen Your Healthcare Data Security with IT Medical
EHR mismatches cost time and money. When patient health data is on the line, your system must prevent security threats and ensure seamless care.
At IT Medical, our experts understand the unique complexities of EHR security. We develop custom solutions that integrate biometric tools for secure, swift record matching.
Let’s take your cybersecurity to the next level. Partner with IT Medical to protect patient records, streamline operations, and build trust. Contact us today to learn more!
References
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Abdi, A., Bennouri, H., & Keane, A. (2024, June). . In 2024 13th Mediterranean Conference on Embedded Computing (MECO) (pp. 1-8). IEEE.
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Alder, S. (2024, July 31). Average cost of a data breach rises to $4.88M; falls to $9.77M in healthcare. The HIPAA Journal. Retrieved from: https://www.hipaajournal.com/cost-healthcare-data-breach-2024/.
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The Pew Charitable Trusts. (2020). Health care can learn from global use of biometrics: Examples from other industries could offer lessons for linking patient medical records. The Pew Charitable Trusts. Retrieved from: https://www.pewtrusts.org/-/media/assets/2020/11/healthcarebiometrics.pdf.
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Black Book Market Research. (2018). Improving Provider Interoperability Congruently Increasing Patient Record Error Rates, Black Book Survey. Retrieved from https://blackbookmarketresearch.newswire.com/news/improving-provider-interoperability-congruently-increasing-patient-20426295.
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The Pew Charitable Trusts. (2022, October). Biometrics can help match patients to their electronic health records. The Pew Charitable Trusts. Retrieved from: https://www.pewtrusts.org/en/research-and-analysis/reports/2022/10/biometrics-can-help-match-patients-to-their-electronic-health-records.
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Suleski, T., Ahmed, M., Yang, W., & Wang, E. (2023). A review of multi-factor authentication in the Internet of Healthcare Things. Digital health, 9, 20552076231177144.
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Weng, J. K., Virk, R., Kaiser, K., Hoffman, K. E., Goodman, C. R., Mitchell, M., … & Smith, B. D. (2024).
Automated, real-time integration of biometric data from wearable devices with electronic medical records: a feasibility study. JCO Clinical Cancer Informatics, 8, e2400040.