Electronic Medical Records: Friend or Foe?

Educational Objectives

The goal of this program is to improve integration of electronic medical records (EMRs) into clinical practice. After hearing and assimilating this program, the clinician will be better able to:

1. Use data mapping tools to extract information from EMRs.
2. Anticipate effects of implementation of EMRs on clinical practice.

Summary

Electronic medical records (EMR): clinicians formerly had to visit a patient’s room to check vital signs; medication orders were written on the patient’s chart and laboratory results were printed; EMRs increase efficiency, improve access to information at individual and population levels, facilitate evaluation of patient history and previous treatment, improve legibility of documentation, and enhance communication with consultants, family members, and trainees; the EMR is the longitudinal collection of electronic health information for and about a patient; immediate electronic access to person and population level information by authorized personnel is available; EMRs should support decision-making that enhances the quality, safety, and efficiency of patient care; specific rules guide processing of EMRs; EMRs are a medium for communication and a legal document; EMRs are a source of clinical outcomes and health services research, and may serve as a resource for practitioner education; EMRs provide alerts and reminders to clinicians and may be used for quality improvement

EMRs in sedation services: improves documentation of complications; clinicians may have different ways of describing complications; minor and major complications should have standard definitions; use of the EMR results in consistent use within a group; EMRs improve revenue cycle and billing accuracy; data from the sedation team and volume is tracked which allows for revenue generation and increasing of capabilities; EMRs aid in patient scheduling and in accuracy of medication orders; EMRs may be billing-focused or care delivery-focused; becoming involved with designing an EMR provides an opportunity to make it more useful for clinicians; the type of output data required should be considered when designing an EMR system

EMR for quality improvement: EMR systems are able to automatically collect data that is a by-product of regular care and quickly provide feedback; immediate feedback is the best feedback

Barriers to quality improvement: cost — EMR systems are expensive; different modalities may benefit quality improvement but are expensive; time and technical support is required to build add-on services; learning curve — the learning curve to use the EMR as a quality improvement tool is steep; return on investment (ROI) — management is concerned about ROI; EMRs do not provide direct ROI from sedation services or from quality improvement; health care providers that aim to reduce hospital stay duration may lose revenue; however, clinicians focus on patient care and do not compromise care for ROI; technical support — technical support professionals may be hard to find and are expensive; technical support to assist the health care provider for quality improvement through EMR may be difficult to arrange; communication standards — an institution may not receive the EMR of a patient from another institution; EMR which are designed incorrectly may impede clinician workflow; complexity of aggregate data — definition of terms, eg, length of stay, visit, encounter, may not be standardized

Research: EMRs assist in research by providing access to data from a large quantity of patients; automatic extraction of information from medical records is possible; however, extracting information from multiple domains is complex and requires extensive data mapping; data mapping requires time and additional costs; coding is inconsistent; data mapping tools (Epic Cosmos) may provide access to the records of 217 million patients in the United States and 9.1 billion encounters; the data is diverse and representative; data from inpatient and outpatient settings is integrated; artificial intelligence data mapping software based on large language models (LLMs) (ChatGPT) may soon be available; LLMs are capable of natural recognition of language queries and can extract information from text documents to improve interactive data analysis; automated messages may be created to be kept as notes or used as messages for patients about their procedure and potential complications

Education: EMRs may be used to outline treatment workflows; immediate feedback on medications is possible; EMRs may be used to communicate with families about, eg, preparing for the procedure, scheduling of the procedure; images and laboratory data are provided to physicians; however, providers may neglect to include a differential diagnosis in their notes; EMRs reduce direct communication among physicians on patient rounds; clinicians may not remember doses of general medications because of reliance on EMRs

Readings

Hodgson T, Burton-Jones A, Donovan R, et al. The role of electronic medical records in reducing unwarranted clinical variation in acute health care: Systematic review. JMIR Med Inform. 2021;9(11):e30432. Published 2021 Nov 17. doi:10.2196/30432; Sauer CM, Chen LC, Hyland SL, Girbes A, Elbers P, Celi LA. Leveraging electronic health records for data science: common pitfalls and how to avoid them. Lancet Digit Health. 2022;4(12):e893-e898. doi:10.1016/S2589-7500(22)00154-6; Singh A, Jadhav S, Roopashree MR. Factors to overcoming barriers affecting electronic medical record usage by physicians. Indian J Community Med. 2020;45(2):168-171. doi:10.4103/ijcm.IJCM_478_19.

Disclosures

For this program, members of the faculty and planning committee reported nothing relevant to disclose.

Acknowledgements

Dr. Dalabih was recorded at the Society for Pediatric Sedation 2023 Annual Conference, held September 21-23, 2023, in Chicago, IL, and presented by the Society for Pediatric Sedation. For information on future CME activities from this presenter, please visit https://pedsedation.org/. Audio Digest thanks the speakers and presenters for their cooperation in the production of this program.

CME/CE INFO

Accreditation:

The Audio- Digest Foundation is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

The Audio- Digest Foundation designates this enduring material for a maximum of 0.75 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Audio Digest Foundation is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center's (ANCC's) Commission on Accreditation. Audio Digest Foundation designates this activity for 0.75 CE contact hours.

Lecture ID:

AN663501

Expiration:

This CME course qualifies for AMA PRA Category 1 Credits™ for 3 years from the date of publication.

Instructions:

To earn CME/CE credit for this course, you must complete all the following components in the order recommended: (1) Review introductory course content, including Educational Objectives and Faculty/Planner Disclosures; (2) Listen to the audio program and review accompanying learning materials; (3) Complete posttest (only after completing Step 2) and earn a passing score of at least 80%. Taking the course Pretest and completing the Evaluation Survey are strongly recommended (but not mandatory) components of completing this CME/CE course.

Estimated time to complete this CME/CE course:

Approximately 2x the length of the recorded lecture to account for time spent studying accompanying learning materials and completing tests.

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