Research at the Point of Care: Using Electronic Medical Record Systems to Generate Clinically Meaningful Evidence
Health care leaders have recommended the use of health information technology to improve the quality of patient care. In athletic training, using informatics, such as electronic medical records (EMRs), would support practice-based decisions about patient care. However, athletic trainers (ATs) may lack the knowledge to effectively participate in point-of-care clinical research using EMRs. To discuss the role of EMRs in athletic training and identify methodologic approaches to conducting clinical research at the point of care. The 2020 Commission on Accreditation of Athletic Training Education curricular content standards included the use of an electronic patient record to document care, mitigate error, and support decision making through the collection and use of patient data (Standard 64). Patient data are collected by ATs at the point of care via routine documentation, and these data can be used to answer clinical questions about their practice. Observational or descriptive study designs are ideal for this type of data. Observational research (ie, case-control, cross-sectional, cohort studies) evaluates factors that influence patients' lives in the “real world,” whereas descriptive research (ie, case study or series, descriptive epidemiology studies) identifies characteristics of individuals and groups. If ATs are comprehensively documenting patient care using an EMR, they have the means to participate in observational and descriptive research. Using an EMR to its full capacity allows ATs to collect meaningful data at the point of care, conduct practice-based research, and improve health care for the patient and clinician. However, to ensure data quality, these approaches must include routine and comprehensive documentation habits.Context
Objectives
Description
Clinical and Research Advantages
The widespread call to leverage health information technology (HIT) for patient care can be traced back 2 decades to the Institute of Medicine's landmark publication, Crossing the Quality Chasm.1 Since then, the National Academy of Medicine has consistently advocated for the implementation of HIT to meet the complex needs of the 21st-century patient,2 facilitate the exchange of health information,2,3 deliver high-quality patient-centered care,2,4,5 and advance research in health care.2,6,7 Additionally, the US health care system has become increasingly digitized as a result of federal initiatives such as the Health Information Technology for Economic and Clinical Health Act.8 This act incentivized and supported the implementation of electronic records with the aims of (1) improving quality, safety, and efficiency and reducing health disparities, (2) increasing patient engagement, (3) improving care coordination, (4) expanding population and public health, and (5) ensuring adequate privacy and security protection for personal health.9
As the most commonly recognized form of HIT, electronic records are crucial to the patient-clinician relationship and allow information to be “interactive, real time, and prospective.”1 In general, electronic records offer a method for collecting meaningful patient data that support and improve patient care. On a global health care level, electronic records have been used to better understand disease diagnoses and prognoses,10,11 improve disease treatment and management strategies,12,13 reduce health care costs,14,15 and improve patient outcomes.16 Because of these benefits, members of the Athletic Training Strategic Alliance17 have encouraged the use of HIT in athletic training, including electronic records. Although the terms electronic medical record (EMR) and electronic health record (EHR) are often used interchangeably, they are different. Electronic medical records are standalone systems that reside in a single location and do not interact with other electronic patient records, whereas EHRs have various levels of connectivity between providers or entities so that information can be shared more efficiently and data can be aggregated.18 Some athletic trainers (ATs) employed by hospitals or health services systems may use an EHR for patient documentation, but most ATs likely use EMRs as part of their clinical practice.
THE ROLE OF EMRs IN ATHLETIC TRAINING
The Commission on Accreditation of Athletic Training Education19 recently published the “2020 Standards for Accreditation of Professional Athletic Training Programs.” The new curricular content standards include the use of an EMR to document care, mitigate error, and support decision making through the collection and use of patient data under the health care informatics core competency (Standard 64).19 This core competency corresponds well20 with EMR-related recommendations described in the Board of Certification Practice Analysis21 and the National Athletic Trainers' Association Educational Competencies,22 which support the usefulness of HIT and EMRs in athletic training. Most recently, the Athletic Training Strategic Alliance's document, “The Prioritized Research Agenda for the Athletic Training Profession,”17 highlighted the importance of HIT and patient documentation data in advancing athletic training practice and improving the quality of patient care. Taken together, these efforts emphasize the vital role HIT, EMRs, and patient care data will play in the future of our profession.
Although most EMR-related initiatives are aimed at improving “immediate” patient care (ie, patient care documentation, communication, access to patient records), EMRs can be useful for conducting point-of-care clinical research on a short-term or long-term basis if leveraged properly. Collecting patient data at the point of care through routine patient care documentation allows clinicians to deliver effective, evidence-based services and reduce research-specific clinic visits and overall health care costs for the patient.23 Despite these potential benefits, it is evident that ATs do not comprehensively document care and use EMRs to their full capacity.24–26 Several groups have analyzed patient care documentation in athletic training, particularly for injury surveillance. For example, researchers have used the National Collegiate Athletic Association Injury Surveillance Program and High School Reporting Information Online system for a decade to describe the injury and exposure data of athletes participating in 13 collegiate and high school sports.27 Although these data-collection systems yield reliable and valid findings about injury incidence in various sport participation settings, additional opportunities exist to improve care beyond tracking injuries and capturing descriptive data.
A CALL TO ACTION: USING EMRs TO CONDUCT RESEARCH AT THE POINT OF CARE IN ATHLETIC TRAINING
Observational Studies
If ATs are comprehensively documenting patient care using commonly recorded variables (Table 1), they should be able to support observational research efforts and use EMR data in a clinically meaningful way. Observational research is performed in a “real-world” clinical setting and evaluates factors that influence patients' lives as they naturally exist.28 Associations between the recorded variables and outcomes of interest are then analyzed. Although observational studies lack the internal validity of randomized controlled trials, their strong external validity can provide more clinically meaningful findings for athletic health care.29,30

Several approaches can be used when conducting observational research using data derived from an EMR (Tables 2 and 3). Because clinicians using an EMR have existing data, retrospective studies are recommended as a first step. One retrospective approach is a case-control study31 (Figure 1 and Table 2), in which the goal is to establish a relationship between exposures (ie, intervention, characteristic, or experience32) and an outcome. Another approach is the cross-sectional study design33 (Figure 2 and Table 2), which compares multiple groups at 1 point in time. The prospective cohort study design34 (Figure 3 and Table 2) should also be considered; its goal is to determine whether a particular recorded variable is associated with an outcome. However, it is important to note that due to its prospective nature, this design requires an additional level of planning.





Citation: Journal of Athletic Training 55, 2; 10.4085/1062-6050-113-19



Citation: Journal of Athletic Training 55, 2; 10.4085/1062-6050-113-19



Citation: Journal of Athletic Training 55, 2; 10.4085/1062-6050-113-19
Example of an Observational Study
Teel et al31 recently investigated the effect of several acute variables on concussion-recovery patterns in collegiate and high school athletes. Variables were collected at baseline (eg, concussion history) or at initial injury evaluation (eg, amnesia, loss of consciousness) by an AT participating in the Concussion Prevention Initiative.31 Patients were tracked for 90 days postinjury and their data were extracted from the Concussion Prevention Initiative database by the investigators.31 This is an example of a study that could have been conducted with an EMR. To comply with current recommendations for best practice,35 ATs should already be documenting such variables in their EMRs. Thus, a case-control study could be conducted that retrospectively relates concussion-evaluation variables to the classification of patients as having experienced prolonged recovery (cases) versus normal (controls) recovery.
Descriptive Studies
Descriptive studies are another type of clinical research that can be supported by an EMR. The aim of descriptive studies is to examine the behaviors, conditions, and characteristics of individuals and groups.36 Common approaches to descriptive studies are the case study and series,37 in which the goal is to depict the characteristics of a patient or group of patients with a rare condition, and descriptive epidemiology designs,38 in which the goal is to describe injuries, illnesses, or conditions in relation to time, place, and patient (Tables 1 and 2). Studies based on data from the Athletic Training Practice-Based Research Network26,39–41 and National Athletic Treatment, Injury and Outcomes Network42,43 have demonstrated the meaningfulness of descriptive designs. Using data derived from these networks, researchers have offered insights into athletic training clinical practice, including common injuries managed,26,39 evaluation techniques employed,44 treatments and services provided,26,39–43 and estimated direct costs recorded by ATs.41
Descriptive studies are also valuable for quality improvement initiatives, which have been a recent focus in athletic training education19 and practice.45,46 The first step of any quality improvement effort is to describe a problem that is based on data collected during patient care. Using the STEEP (safe, timely, effective, efficient, equitable, patient-centered) framework for improvement,1 ATs can identify potential practice gaps by analyzing patient data. If a problem is identified, a quality improvement initiative can be developed to address the gap, and the EMR can be used to measure whether any improvements occur.45
Example of a Descriptive Study and Quality Improvement
A simple but meaningful example of how a descriptive study drives quality improvement involves looking at the evaluation patterns of ATs to determine whether best practices are being followed. The Ottawa Ankle Rules47 are well-known and accepted practice guidelines for referring patients for radiographs after a foot or ankle injury. Thus, ATs could retrospectively analyze all patients with foot or ankle injuries who were referred for radiographs to determine whether they actually met the Ottawa Ankle Rules criteria. If the percentage of patients meeting the radiograph and Ottawa Ankle Rules requirements was relatively low (eg, 70% or less), then a continuous quality improvement initiative could be instituted to improve that percentage over time. Potential improvements could include implementing educational strategies for ATs, providing clinical decision support system features within the EMR, and establishing a departmental policy for a successive plan-do-study-act cycle.48
CONSIDERATIONS
An advantage of using an EMR is its ability to facilitate access to meaningful, accurate, reliable, and complete data.49 However, a limitation of conducting research this way is that the quality of the data depends on the quality of the patient care documentation. Inaccurate, incomplete, or missing health information may adversely affect patient care.49 As a result, to support EMR-based research efforts, comprehensive and consistent patient care documentation is crucial.
The use of an EMR has been shown to improve patient care documentation practices50 and communication among providers51 without increasing the time that clinicians spend documenting.52 Yet, numerous health care providers (eg, physicians,53 nurses,54 pharmacists55) often cite barriers to high-quality documentation. Although ATs recognize the importance of patient care documentation, they identified time, uncertainty regarding what to document, and facility and personnel resources as obstacles to documentation.25 Standard operating procedures and standardized reporting methods may provide strategies for improving documentation habits.17,56 In addition, comprehensive and continuous EMR training preserves data quality,56,57 and documentation peer reviews can hold clinicians accountable for their documentation practices.57 Thus, these strategies should be used before and during EMR-based research efforts to optimize data quality.
The mechanics of patient care documentation also affect the ability to conduct quality research using an EMR. For example, baseline testing58 or injury registration59 is often separate from injury documentation, requiring clinicians to document in multiple systems and researchers to compile data from multiple sources to analyze the data prospectively. Because a perceived lack of time is a reported barrier to quality medical record keeping,25 reducing or eliminating the documentation of information in multiple systems is recommended to improve data quality, reduce data redundancy, and increase the feasibility of EMR-based research.
A potential challenge to EMR-based research efforts in athletic training is the lack of continuity between medical records maintained by ATs and those maintained by the patient's external physician or health care system. Athletic trainers are often outside the formal health care system,60 so extracting comprehensive data from the electronic patient records of multiple health care providers can be difficult. This may hinder an AT's ability to answer certain research questions. For instance, unless the care provided by external providers during rehabilitation is considered, studies investigating recovery trajectories may not accurately reflect the effectiveness of certain treatments because data points from external providers will be missing.
CONCLUSIONS
Over the last 2 decades, the use of HIT has been emphasized in the US health care system. In athletic training, recent efforts have highlighted the vital role EMRs may play in improving the quality of patient care and advancing the profession. Although the use of EMRs has primarily focused on injury surveillance, ATs have a valuable opportunity to collect patient care data in a manner that could drive clinically meaningful research, including observational studies, descriptive studies, and quality improvement projects. These types of studies can ultimately benefit ATs and their patients, but proactive planning is required to ensure that the data collected are of high quality. Implementing strategies such as standard operating procedures, continuous EMR training, peer-to-peer documentation audits, and limiting entry of information into multiple systems can enhance and preserve data quality and increase the feasibility of EMR-based research efforts. Although the athletic training profession has made progress in the use of point-of-care data to support injury-surveillance and practice characterization studies, future investigators should conduct prospective, cost-analysis, and comparative effectiveness research using electronic records.

Case-control study design.

Cross-sectional study design.

Prospective cohort study design.
Contributor Notes