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The electronic health record (EHR) contains a massive amount of discrete patient data that are generated through the routine provision of patient care.
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EHR data can be so-called big data based on volume (total number of patients/data points), velocity (the rate at which it is generated), and/or variety.
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Data validation is imperative because many of the data were collected for clinical, rather than research, purposes.
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EHR data can be used to build large patient cohorts and/or identify patients with
Electronic Health Record–Enabled Research in Children Using the Electronic Health Record for Clinical Discovery
Section snippets
Key points
The electronic health record data set
The EHR data set is immense; the scale is on par with many of the big data disciplines such as genomics and proteomics. Across an entire children’s hospital, clinical care generates hundreds of thousands of data points per day and tens of millions of data points annually; data generated from ambulatory care and the narrative data contained within clinical notes add substantially more information. However, although the volume of data is alluring, some elements are easier to extract, some have
Electronic health record–enabled research methodologies and examples of analytical approaches
The types of studies that can be performed using EHR data typically conform to the fairly standard methodologies used with other types of data. A summary of these approaches and their advantages/disadvantages in clinical research informatics is shown in Table 2. Detailed in Table 3 is a comprehensive list, by study type, of EHR-enabled pediatric studies as of publication.
Limitations surrounding electronic health record–enabled research
EHR-enabled research and the data contained within the EHR offer several benefits. However, this methodology is subject to certain limitations. Most fundamentally, other than studies that use the EHR to facilitate prospective trials, using EHR data to enable clinical discovery is retrospective and observational in nature. Although many interesting associations can be identified, retrospective studies cannot prove causality. Some clinicians think of EHR-enabled inquiry as hypothesis generating
Summary
EHRs are becoming integrated into the fabric of children’s health and are critical to the future of clinical discovery. EHR-enabled research offers great potential; as EHR adoption expands, the possibilities of EHR-enabled clinical discovery will increase substantially. The capacity to generate vast retrospective cohorts and big data–sized data sets is one of the most practical applications of the technique. However, as clinicians come to better understand the intersection between the EHR, care
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Cited by (29)
Diverse and unselected adults with clinically relevant ACADS variants lack evidence of metabolic disease
2023, Molecular Genetics and MetabolismCitation Excerpt :Although EHR-linked biobanks offer tremendous opportunities for genetics and genomics research, the data in EHRs may be incomplete, inaccurate, and biased [22]. For example, ICD codes are not exhaustive and may be used inconsistently between providers [22–24]. This study was limited to sequence variants and did not identify copy number variants in the ACADS gene; however to date large copy number variants have not been described as disease-causing for SCADD [25].
Relative Incidence of Emergency Department Visits After Treatment for Prostate Cancer With Radiation Therapy or Radical Prostatectomy
2022, Practical Radiation OncologyCitation Excerpt :Therefore, a better understanding of the severity and likelihood of side effects associated with RP and RT will benefit patients in choosing a treatment for their prostate cancer. Structured electronic health record (EHR) data are becoming increasingly available in clinical data warehouses (CDWs) as hospitals and clinics have moved to EHRs, creating new opportunities to use real-world data to understand side effects.11-13 Although side effects are not directly captured in structured EHR data, emergency department (ED) visits can be measured in these data.
Inefficiencies of electronic medical record use by surgical healthcare providers
2022, Health Policy and TechnologyCitation Excerpt :Studies have indeed found that electronic health records facilitate multiple benefits to healthcare, including enabling improved attitude toward safety, reducing risk of error, and promoting shared decision-making between patients and providers.[5–8] Moreover, EMRs provide a platform amenable to research, trend analysis, and clinical discovery.[9–12] Nevertheless, several studies have noted usability issues common to EMRs.
Personalized Medicine and the Power of Electronic Health Records
2019, CellCitation Excerpt :In addition, large academic health systems or governments often make significant institutional investments, even when the direct downstream economic benefits are not always clear, recognizing the potential for personalized medicine to make real and lasting benefits for health and healthcare. The models in which health system data may be used to support personalized medicine research are varied, and there are special ethical and scientific (Hersh et al., 2013; Sutherland et al., 2016; Wolford et al., 2018) considerations to take into account when linking genomic data with EHRs. For example, participants in biobanks typically volunteer under broad informed consents, as EHRs are expected to add data types over time, and all possible uses of participants’ data are often unknown at the time of joining.
Improving the use of big data analytics within electronic health records: A case study baseD OpenEHR
2018, Procedia Computer Science
Disclosure: None of the authors have anything to disclose.