Electronic health record


An electronic health record is the systematized collection of electronically stored patient and population health information in a digital format. These records can be shared across different health care settings. Records are shared through network-connected, enterprise-wide information systems or other information networks and exchanges. EHRs may include a range of data, including demographics, medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, personal statistics like age and weight, and billing information.
For several decades, EHRs have been touted as key to increasing quality of care. EHR combines all patients' demographics into a large pool, which assists providers in the creation of "new treatments or innovation in healthcare delivery" to improve quality outcomes in healthcare. Combining multiple types of clinical data within electronic health records has enabled clinicians to identify and stratify patients with chronic conditions. EHR systems may also support improvements in quality of care through the use of data and analytics to help prevent hospitalizations among high-risk patients.
EHR systems are designed to store data accurately and to capture a patient's state across time. It eliminates the need to track down a patient's previous paper medical records and assists in ensuring data is up-to-date, accurate, and legible. It also allows open communication between the patient and the provider while providing "privacy and security." EHR is cost-efficient, decreases the risk of lost paperwork, and can reduce risk of data replication as there is only one modifiable file, which means the file is more likely up to date. Due to the digital information being searchable and in a single file, EMRs are more effective when extracting medical data to examine possible trends and long-term changes in a patient. The widespread adoption of EHRs and EMRs may also facilitate population-based studies of medical records.

Terminology

The terms electronic health record, electronic patient record, and electronic medical record have often been used interchangeably, but "subtle" differences exist. The EHR is a more longitudinal collection of the electronic health information of individual patients or populations. The EMR, in contrast, is the patient record created by providers for specific encounters in hospitals and ambulatory environments and can serve as a data source for an EHR.
EMRs are essentially digital versions of the paper documents used in a clinician's office, typically functioning as an internal system within a practice. An EMR includes the medical and treatment history of patients treated by that specific practice.
In contrast, a personal health record is an electronic application for recording individual medical data that the individual patient controls and may make available to health providers.

Comparison with paper-based records

While there is ongoing debate regarding the advantages of electronic health records compared with paper records, the research literature presents a more nuanced view of their benefits and limitations.
Increasing discontent and burnout among healthcare professionals is well documented as of 2023, with several studies finding that a leading cause of job frustration and increasing stress for most doctors and nurses is the increasing burden of increasingly complex record-keeping, paperwork, and administrative workloads.. Proponents of EHR note that these systems can substantially reduce such burdens, for example cutting spent on insurance eligibility tasks by more than 80%.
But along with increased convenience, transparency, portability, and accessibility, there is also an increased risk that sensitive information may be accessed by unauthorized persons or unscrupulous users. This is acknowledged by the increased security requirements for electronic medical records included in the Health Insurance Portability and Accountability Act and by large-scale breaches in confidential records reported by EMR users.
Meanwhile, handwritten paper medical records may be poorly legible, which can contribute to medical errors. Pre-printed forms, standardization of abbreviations, and standards for penmanship were encouraged to improve the reliability of paper medical records. An example of possible medical errors is the administration of medication. Medication is an intervention that can turn a person's status from stable to unstable very quickly. With paper documentation it is very easy to not properly document the administration of medication, the time given, or errors such as giving the "wrong drug, dose, form, or not checking for allergies," and could affect the patient negatively. It has been reported that these errors have been reduced by "55-83%" because records are now online and require specific steps to avoid these errors.
Electronic records may help with the standardization of forms, terminology, and data input. Digitization of forms facilitates the collection of data for epidemiology and clinical studies. However, standardization may create challenges for local practice. Overall, those with EMRs that have automated notes and records, order entry, and clinical decision support had fewer complications, lower mortality rates, and lower costs.
EMRs can be continuously updated. If the ability to exchange records between different EMR systems were perfected, it would facilitate the coordination of health care delivery in non-affiliated health care facilities. In addition, data from an electronic system can be used anonymously for statistical reporting in matters such as quality improvement, resource management, and public health communicable disease surveillance. However, it is difficult to remove data from its context.

Patient access to electronic health records

Providing patients with information is central to patient-centered health care and has been shown to positively affect health outcomes. Providing patients access to their health records, including medical histories and test results via an EHR, is a legal right in some parts of the world.
There is evidence that patient access may help patients understand their conditions and actively involve them in their management. For example, granting people who have type 2 diabetes access to their electronic health records may help these people to reduce their blood sugar levels.
Challenges with sharing the electronic health record with patients include a risk of increased confusion or anxiety if a person does not understand or cannot contextualize the testing results. In addition, many EHRs are not designed for people of all educational levels and do not consider the needs of those with a lower level of education or those who are not fluent in the language. Accessing the EHR requires a level of proficiency with electronic devices, which adds to a disparity for those without access or for those who have a mental or physical illness that restricts their access to the electronic system.

Use in research and development

Electronic medical records could also be studied to quantify disease burdens – such as the number of deaths from antimicrobial resistance – or help identify causes of, factors of, links between, and contributors to diseases, especially when combined with genome-wide association studies.
This may enable increased flexibility, improved disease surveillance, better medical product safety surveillance, better public health monitoring, increased quality of care, and novel life-saving treatments.

Issues

Privacy: For such purposes, electronic medical records could potentially be made available in securely anonymized or pseudonymized forms to ensure patients' privacy is maintained, even if data breaches occur. There are concerns about the efficacy of some currently applied pseudonymization and data protection techniques, including the applied encryption.
Documentation burden: While such records could enable avoiding duplication of work via records-sharing, documentation burdens for medical facility personnel can be a further issue with EHRs. This burden could be reduced via voice recognition, optical character recognition, other technologies, physician involvement in software changes, and other means which could possibly reduce the documentation burden to below paper-based records documentation and low-level documentation.

Applications using software

Theoretically, free software such as GNU Health and other open-source health software could be used or modified for various purposes that use electronic medical records, i.e., via securely sharing anonymized patient treatments, medical history, and individual outcomes.
  • Decision support: Electronic health records could support clinical decision-support systems.
  • Personalized medicine: They could be used among other biodata for digital twins for personalized medicine.
  • mHealth integration: They could be coupled with mHealth mobile applications and wearable technology.
  • Screening: Artificial intelligence systems could use this data, as well as other integrated data, to screen for potential diseases via multimodal learning.
  • Syndromic surveillance: Real-time analysis and data mining of the records could be used, along with other data, in syndromic surveillance to rapidly identify common exposures among patients suspected of being part of an outbreak, for epidemic forecasting and for early outbreak detection, especially in identified potential pandemic pathogen hotspot regions and potentially as a means for pandemic prevention.
  • Vaccination deployment: Interoperable, collaboratively developed, standardization-based health records systems could increase the speed of vaccination campaigns and reduce their costs or workloads. According to Dr. Bob Kocher, as of 2021, there are "1,000 different electronic health record systems in the U.S., and almost every hospital and clinic has a slightly different system tailored to its own needs" which caused difficulties and delays during COVID-19 vaccinations, with similar problems being reported in other countries.
  • Medical outcomes data: Such records could also be used to match patients to clinical trials with software, reducing the burden on users to partake in research and making previously siloed primary care data more valuable to society at larger or other patients.