Electronic health records have transformed how medical information is stored and shared, but they come with a significant set of concerns that affect doctors, patients, and healthcare organizations alike. The issues range from physician burnout and medication errors to massive data breaches and records cluttered with duplicate information. Here’s what you should know about the real-world problems EHRs create.
Physician Burnout and After-Hours Charting
One of the most widespread complaints about EHRs is how much time clinicians spend on documentation instead of patient care. In a 2017 national survey, 43.9% of U.S. physicians reported symptoms of burnout, and 30% pointed to the increasing computerization of medical practice as a top contributor. Another 55% cited bureaucratic tasks, many of which are tied directly to EHR requirements.
The documentation burden doesn’t end when the workday does. In a large survey of over 36,000 physicians, 35% reported spending 6 to 15 hours per week charting outside normal business hours, including evenings and weekends. Another 9% spent 16 hours or more per week on after-hours documentation. That’s essentially a second part-time job spent typing into a computer rather than resting or seeing patients.
Patient Safety Risks From Poor Design
EHRs were supposed to reduce medical errors, and in many ways they have. But they’ve also introduced new categories of mistakes that didn’t exist with paper records. Research in intensive care units found that EHR-related medication errors included duplicate orders, overdoses caused by confusing interface designs, and orders with missing information. In one study, 56% of duplicate medication orders were classified as EHR-related, meaning the system’s design played a direct role.
Interface problems are a recurring theme. When screen layouts make it hard to enter a one-time dose alongside an existing daily order, overdoses can result. When the system guides clinicians through data entry but doesn’t force them to complete critical fields, essential information gets left out. And when alerts for duplicate orders are poorly designed, clinicians either ignore them or override them without reading them carefully.
Alert Fatigue Is Dangerously Real
EHR systems generate safety alerts to warn clinicians about drug interactions, allergies, and dosing problems. In theory, this is protective. In practice, the sheer volume of alerts has created a phenomenon called alert fatigue, where clinicians stop paying attention. Override rates for EHR alerts run as high as 96%. One health system tracked 675,613 alerts per month, and clinicians overrode 94.6% of them.
The problem is circular. When most alerts are irrelevant or low-value, clinicians learn to click past them reflexively. But buried among those hundreds of thousands of ignorable warnings are genuinely dangerous situations. High alert volume increases mental workload, encourages workarounds, and leads to ordering mistakes. Even worse, a clinician may occasionally follow a false-positive alert and take the wrong action for a patient, causing the very harm the system was designed to prevent.
Half of Clinical Notes Are Duplicated Text
Copy-and-paste functionality in EHRs has created a documentation crisis. A large-scale analysis found that 50.1% of all clinical text in electronic records was duplicated from previous notes about the same patient. That fraction grew steadily over time, rising from 33% of notes written in 2015 to 54.2% in 2020. Physician notes specifically contained between 30% and 70% duplicate content.
This isn’t just an annoyance. When text is copied forward note after note, outdated information persists as though it’s current. Errors in one note spread virally through the record until they exist in so many copies that correcting them becomes nearly impossible. Clinicians reading through a chart can’t easily tell which information is fresh and which was pasted from a note written months or years earlier. The result is wasted time, inaccurate records, and a growing risk of medical errors built on stale data.
Malpractice Claims Tied to EHR Problems
EHR-related issues now show up regularly in medical malpractice cases. An analysis of claims identified two broad categories of problems: system issues (data routing failures, software glitches, autopopulation errors) and user issues (copy-paste mistakes, overridden alerts, workarounds). Among user-related malpractice cases, the most common triggers were difficulties during EHR system conversions (16 cases), failures to notice a worsening condition because notes were pre-populated or copy-pasted (10 cases), and misrouted information (7 cases).
The real-world consequences are stark. In one case, a patient developed drug toxicity because a copied note failed to document that the patient was already taking the medication. In another, an ultrasound result was never scanned into the EHR, delaying a cancer diagnosis. A pediatric patient received a drug they were allergic to because the allergy had been documented in a paper record but never uploaded into the electronic system. A discharge order that was electronically signed omitted a critical blood-thinning medication, and the patient was later admitted with a stroke.
Systems That Don’t Talk to Each Other
Interoperability, the ability of different EHR systems to share patient data seamlessly, remains one of the field’s biggest unsolved problems. When a patient moves between hospitals, specialists, or clinics that use different systems, their records often don’t follow them. Poor connectivity between organizations forces staff into double documentation, entering the same information into multiple systems and then cross-checking to make sure it matches.
This fragmentation increases workload for providers and creates gaps in care. If a specialist can’t see what your primary care doctor ordered, tests get repeated, medications get duplicated, and critical context gets lost. Standards for data exchange have improved over the years, but system compatibility issues, slow response times, server crashes, and software failures continue to plague many healthcare organizations.
Cybersecurity and Data Breaches
Healthcare data is extraordinarily valuable to hackers, and the digitization of medical records has made it a massive target. In 2024 alone, protected health information for nearly 277 million individuals was exposed or stolen. That followed 168 million records exposed in 2023. Healthcare consistently ranks as the most expensive industry for data breaches, with costs averaging $7.42 million per incident in the U.S. as of 2025.
For patients, the concern isn’t abstract. Cross-sectional survey data shows that roughly 89% of people consider it “very serious” if hackers gain access to medical record systems. About 77% feel the same way about employers, insurance companies, or banks accessing their health data. Even among people who generally trust healthcare institutions to protect their information, nearly 27% believe the risk of unauthorized access is high. People with lower trust in the system are far more concerned: 59% of them rate the risk of unauthorized record access as high, and 54% believe the consequences would be serious.
The Financial Burden on Practices
Implementing an EHR system is expensive, particularly for smaller practices. Research from the Agency for Healthcare Research and Quality found that a five-physician practice can expect to spend roughly $233,000 over the planning period and first year of EHR use, which works out to about $46,659 per physician. That includes capital expenditures around $61,300, operating costs near $85,500, and hundreds of hours of staff time for planning and training.
Costs do decline after the initial rollout. After the first year, monthly maintenance drops to about $1,650 per physician. But the upfront investment is a serious barrier for small and independent practices, and it doesn’t account for the productivity losses that occur while staff learn a new system. For large hospital networks, the figures scale dramatically higher, and system conversions or upgrades can trigger years of disruption.
Built-In Bias That Affects Care
As artificial intelligence tools are increasingly layered on top of EHR data to assist with diagnoses and treatment decisions, a less visible concern has emerged: the data itself carries bias. EHR records reflect decades of healthcare disparities, including unequal access to insurance, inconsistent screening practices across racial and ethnic groups, and diagnostic patterns shaped by socioeconomic factors. When AI models are trained on this data, they can reproduce and amplify those disparities.
For example, racial and ethnic minority children and adolescents are more likely to receive an advanced cancer diagnosis compared to non-Hispanic white patients, a gap partly explained by differences in insurance coverage and healthcare access. If an algorithm learns from that pattern without correcting for it, it may systematically underestimate risk in certain populations. Disease misclassification, biased risk scores, and unequal treatment recommendations are all documented consequences of building AI tools on biased EHR data.