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JAMA Sep 2023There is increased interest in and potential benefits from using large language models (LLMs) in medicine. However, by simply wondering how the LLMs and the applications...
IMPORTANCE
There is increased interest in and potential benefits from using large language models (LLMs) in medicine. However, by simply wondering how the LLMs and the applications powered by them will reshape medicine instead of getting actively involved, the agency in shaping how these tools can be used in medicine is lost.
OBSERVATIONS
Applications powered by LLMs are increasingly used to perform medical tasks without the underlying language model being trained on medical records and without verifying their purported benefit in performing those tasks.
CONCLUSIONS AND RELEVANCE
The creation and use of LLMs in medicine need to be actively shaped by provisioning relevant training data, specifying the desired benefits, and evaluating the benefits via testing in real-world deployments.
Topics: Language; Medical Records; Medicine; Computer Simulation; Machine Learning
PubMed: 37548965
DOI: 10.1001/jama.2023.14217 -
Journal of Medical Internet Research Dec 2023Electronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the... (Review)
Review
BACKGROUND
Electronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the most adopted EHR system across the globe. Despite its global reach, there is a gap in the literature detailing how EHR systems such as Epic have been used for health care research.
OBJECTIVE
The objective of this scoping review is to synthesize the available literature on use cases of the Epic EHR for research in various areas of clinical and health sciences.
METHODS
We used established scoping review methods and searched 9 major information repositories, including databases and gray literature sources. To categorize the research data, we developed detailed criteria for 5 major research domains to present the results.
RESULTS
We present a comprehensive picture of the method types in 5 research domains. A total of 4669 articles were screened by 2 independent reviewers at each stage, while 206 articles were abstracted. Most studies were from the United States, with a sharp increase in volume from the year 2015 onwards. Most articles focused on clinical care, health services research and clinical decision support. Among research designs, most studies used longitudinal designs, followed by interventional studies implemented at single sites in adult populations. Important facilitators and barriers to the use of Epic and EHRs in general were identified. Important lessons to the use of Epic and other EHRs for research purposes were also synthesized.
CONCLUSIONS
The Epic EHR provides a wide variety of functions that are helpful toward research in several domains, including clinical and population health, quality improvement, and the development of clinical decision support tools. As Epic is reported to be the most globally adopted EHR, researchers can take advantage of its various system features, including pooled data, integration of modules and developing decision support tools. Such research opportunities afforded by the system can contribute to improving quality of care, building health system efficiencies, and conducting population-level studies. Although this review is limited to the Epic EHR system, the larger lessons are generalizable to other EHRs.
Topics: Adult; Humans; Electronic Health Records; Software; Databases, Factual; Electronics; Health Services Research
PubMed: 38100185
DOI: 10.2196/51003 -
The American Journal of Nursing Aug 2023The benefits and consequences of patient access to health records.
The benefits and consequences of patient access to health records.
Topics: Humans; Medical Records Systems, Computerized; Patient Access to Records
PubMed: 37498015
DOI: 10.1097/01.NAJ.0000947376.76540.20 -
JAMA Network Open Aug 2023Despite the large health burden, reliable data on sepsis epidemiology are lacking; studies using International Statistical Classification of Diseases and Related Health... (Observational Study)
Observational Study
IMPORTANCE
Despite the large health burden, reliable data on sepsis epidemiology are lacking; studies using International Statistical Classification of Diseases and Related Health Problems (ICD)-coded hospital discharge diagnosis for sepsis identification suffer from limited sensitivity. Also, ICD data do not allow investigation of underlying pathogens and antimicrobial resistance.
OBJECTIVES
To generate reliable epidemiological estimates by linking data from a population-based database to a reference standard of clinical medical record review.
DESIGN, SETTING, AND PARTICIPANTS
This was a retrospective, observational cohort study using a population-based administrative database including all acute care hospitals of the Scania region in Sweden in 2019 and 2020 to identify hospital-treated sepsis cases by ICD codes. From this database, clinical medical records were also selected for review within 6 strata defined by ICD discharge diagnosis (both with and without sepsis diagnosis). Data were analyzed from April to October 2022.
MAIN OUTCOMES AND MEASURES
Hospital and population incidences of sepsis, case fatality, antimicrobial resistance, and temporal dynamics due to COVID-19 were assessed, as well as validity of ICD-10 case identification methods compared with the reference standard of clinical medical record review.
RESULTS
Out of 295 531 hospitalizations in 2019 in the Scania region of Sweden, 997 patient medical records were reviewed, among which 457 had sepsis according to clinical criteria. Of the patients with clinical sepsis, 232 (51%) were female, and 357 (78%) had at least 1 comorbidity. The median (IQR) age of the cohort was 76 (67-85) years. The incidence of sepsis in hospitalized patients according to the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) criteria in 2019 was 4.1% (95% CI, 3.6-4.5) by medical record review. This corresponds to an annual incidence rate of 747 (95% CI, 663-832) patients with sepsis per 100 000 population. No significant increase in sepsis during the COVID-19 pandemic nor a decrease in sepsis incidence when excluding COVID-19 sepsis was observed. Few sepsis cases caused by pathogens with antimicrobial resistance were found. The validity of ICD-10-based case identification in administrative data was low.
CONCLUSIONS AND RELEVANCE
In this cohort study of sepsis epidemiology, sepsis was a considerable burden to public health in Sweden. Supplying administrative data with information from clinical medical records can help to generate reliable data on sepsis epidemiology.
Topics: Humans; Female; Aged; Aged, 80 and over; Male; Incidence; Cohort Studies; Pandemics; COVID-19; Sepsis; Medical Records; Anti-Infective Agents
PubMed: 37642964
DOI: 10.1001/jamanetworkopen.2023.31168 -
Computers in Biology and Medicine Oct 2023Medical record images in EHR system are users' privacy and an asset, and there is an urgent need to protect this data. Image steganography can offer a potential...
Medical record images in EHR system are users' privacy and an asset, and there is an urgent need to protect this data. Image steganography can offer a potential solution. A steganographic model for medical record images is therefore developed based on StegaStamp. In contrast to natural images, medical record images are document images, which can be very vulnerable to image cropping attacks. Therefore, we use text region segmentation and watermark region localization to combat the image cropping attack. The distortion network has been designed to take into account the distortion that can occur during the transmission of medical record images, making the model robust against communication induced distortions. In addition, based on StegaStamp, we innovatively introduced FISM as part of the loss function to reduce the ripple texture in the steganographic image. The experimental results show that the designed distortion network and the FISM loss function term can be well suited for the steganographic task of medical record images from the perspective of decoding accuracy and image quality.
Topics: Medical Records; Confidentiality; Medical Informatics
PubMed: 37603961
DOI: 10.1016/j.compbiomed.2023.107344 -
Critical Care Clinics Oct 2023Electronic medical records (EMRs) constitute the electronic version of all medical information included in a patient's paper chart. The electronic health record (EHR)... (Review)
Review
Electronic medical records (EMRs) constitute the electronic version of all medical information included in a patient's paper chart. The electronic health record (EHR) technology has witnessed massive expansion in developed countries and to a lesser extent in underresourced countries during the last 2 decades. We will review factors leading to this expansion, how the emergence of EHRs is affecting several health-care stakeholders; some of the growing pains associated with EHRs with a particular emphasis on the delivery of care to the critically ill; and ongoing developments on the path to improve the quality of research, health-care delivery, and stakeholder satisfaction.
Topics: Humans; Electronic Health Records
PubMed: 37704334
DOI: 10.1016/j.ccc.2023.03.004 -
American Journal of Surgery Dec 2023
Topics: Humans; Writing; Medical Records
PubMed: 37468386
DOI: 10.1016/j.amjsurg.2023.07.005 -
Journal of Biomedical Informatics Jul 2023With the growth of data and intelligent technologies, the healthcare sector opened numerous technology that enabled services for patients, clinicians, and researchers.... (Review)
Review
With the growth of data and intelligent technologies, the healthcare sector opened numerous technology that enabled services for patients, clinicians, and researchers. One major hurdle in achieving state-of-the-art results in health informatics is domain-specific terminologies and their semantic complexities. A knowledge graph crafted from medical concepts, events, and relationships acts as a medical semantic network to extract new links and hidden patterns from health data sources. Current medical knowledge graph construction studies are limited to generic techniques and opportunities and focus less on exploiting real-world data sources in knowledge graph construction. A knowledge graph constructed from Electronic Health Records (EHR) data obtains real-world data from healthcare records. It ensures better results in subsequent tasks like knowledge extraction and inference, knowledge graph completion, and medical knowledge graph applications such as diagnosis predictions, clinical recommendations, and clinical decision support. This review critically analyses existing works on medical knowledge graphs that used EHR data as the data source at (i) representation level, (ii) extraction level (iii) completion level. In this investigation, we found that EHR-based knowledge graph construction involves challenges such as high complexity and dimensionality of data, lack of knowledge fusion, and dynamic update of the knowledge graph. In addition, the study presents possible ways to tackle the challenges identified. Our findings conclude that future research should focus on knowledge graph integration and knowledge graph completion challenges.
Topics: Humans; Electronic Health Records; Pattern Recognition, Automated; Knowledge Bases; Delivery of Health Care; Decision Support Systems, Clinical
PubMed: 37230406
DOI: 10.1016/j.jbi.2023.104403 -
Orphanet Journal of Rare Diseases Sep 2023To obtain updated estimates of the incidence and prevalence of neurofibromatosis type 1 (NF1) and type 2 (NF2). (Meta-Analysis)
Meta-Analysis
OBJECTIVE
To obtain updated estimates of the incidence and prevalence of neurofibromatosis type 1 (NF1) and type 2 (NF2).
STUDY DESIGN
We conducted a systematic search of NF1 and NF2 incidence or prevalence studies, in OVID Medline, OVID Embase, Web of Science, and Cinahl. Studies were appraised with the Joanna Briggs Institute Prevalence Critical Appraisal tool. Pooled incidence and prevalence rates were estimated through random-effects meta-analysis.
RESULTS
From 1,939 abstracts, 20 studies were fully appraised and 12 were included in the final review. Pooled NF1 prevalence was 1 in 3,164 (95%CI: 1 in 2,132-1 in 4,712). This was higher in studies that screened for NF1, compared to identification of NF1 through medical records (1 in 2,020 and 1 in 4,329, respectively). NF1 pooled birth incidence was 1 in 2,662 (95%CI: 1 in 1,968-1 in 3,601). There were only 2 studies on NF2 prevalence, so data were not pooled. Pooled NF2 birth incidence was 1.08 per 50,000 births (95%CI: 1 in 32,829-1 in 65,019).
CONCLUSION
We present updated estimates of the incidence and prevalence of NF1 and NF2, to help plan for healthcare access and allocation. The prevalence of NF1 from screening studies is higher than from medical record studies, suggesting that the disease may be under recognized. More studies are needed regarding the prevalence of NF2.
Topics: Humans; Incidence; Neurofibromatosis 1; Prevalence; Health Services Accessibility; Medical Records
PubMed: 37710322
DOI: 10.1186/s13023-023-02911-2 -
Annual International Conference of the... Jul 2023To solve the difficulty of medical data sharing in traditional medical information systems, we proposed an electronic medical record secure-sharing scheme based on the...
To solve the difficulty of medical data sharing in traditional medical information systems, we proposed an electronic medical record secure-sharing scheme based on the Blockchain technique. The encrypted text of the patient's electronic medical record is stored in the cloud server while the metadata of the medical record and access strategy is stored in the blockchain system. We employed smart contracts in the blockchain system to achieve user rights management. We used the decentralized, tamper-proof, and traceable features of the blockchain to realize the safe sharing of electronic medical records. The experimental results of security analysis show that the method can defend against potential network attacks while satisfying patient privacy protection and confidentiality. This study verifies the feasibility and great operating efficiency of the blockchain-based electronic medical record security sharing scheme.Clinical relevance- Our proposed blockchain-based electronic medical record-sharing scheme has great potential for the safe access of third-party users to patient data.
Topics: Humans; Electronic Health Records; Blockchain; Computer Security; Confidentiality; Text Messaging
PubMed: 38083057
DOI: 10.1109/EMBC40787.2023.10340218