HIMT 204 Lecture 5: Electronic Health Information & Record System Core Clinical Applications (Part II) PDF

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PamperedNewOrleans

Uploaded by PamperedNewOrleans

Imam Abdulrahman Bin Faisal University

2024

Nouf Alassaf

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clinical decision support systems EHR healthcare medical informatics

Summary

This document presents a lecture on Electronic Health Information & Record System Core Clinical Applications (Part II) for the academic year 2024-2025. The lecture covers different types of clinical decision support systems (CDSS), their benefits and challenges, including leadership commitment, medico-legal concerns, over-alerting. It also discusses the key capabilities of Electronic Health Records (EHRs), such as health information, result management, order management, and decision support, with examples and practical applications.

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College of Applied Medical Sciences in Dammam Academic Year 2024-2025 Health Information (HIMT 204) Electronic Health Information & Record System Core Clinical Applications (Part II) Lec tu re 5...

College of Applied Medical Sciences in Dammam Academic Year 2024-2025 Health Information (HIMT 204) Electronic Health Information & Record System Core Clinical Applications (Part II) Lec tu re 5 Nouf Alassaf Clinical Decision Support System (CDSS) CDSS: Definition CDSS: Definition (Cont.) - CDSS helps organization to achieve their care delivery objectives - Similar to GPS, CDSS: o provides information tailored to the current situation o reduces the cognitive burden of users o uses programmed logic, typically in the form of "if-then" rules CDSS: Definition (Cont.) - “Clinical decision support system (CDSS) is a system that provides clinicians, staff, patients or other individuals with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and healthcare” CDSS: Pre-implementation - Before CDSS: Clinical Decision Support (CDS) referred to any resource aiding decision-making - Ex: o Using notes as a reminder for flu shots o Clinical pocket guides: handy references for practical, must-know information to deliver safe and effective healthcare CDSS: Types CDSS comes in many different forms, the main types are: 1. Calculator o Now embedded into most EHRs o Ex: Appropriate antibiotic dosing calculations based on kidney function (creatinine clearance) Example of calculator CDSS CDSS: Types (Cont.) 2. Infobutton o Point of care reference information o Enable users to connect to a variety of embedded internal and external educational resources Example of infobutton used for lab test status CDSS: Types (Cont.) 3. Dashboard o Include any type of patient summary, flow chart of lab results or vital signs or a disease registry Example of dashboard for urgent care CDSS: Types (Cont.) 4. Hyperlink o Web-based reference information o Ex: o links to knowledge references o links to local policies Example of hyperlink in nursing care plan CDSS: Types (Cont.) 5. Alert o Serve to provide timely feedback to the clinician about potential problems, during or after the patient visit o Appear as: o pop-up boxes (event-driven) which require action, or o sidebar notification which gives informative or give advice CDSS: Types (Cont.) 5. Alert Example of interruptive pop-up alert Example of non-interruptive sidebar alert CDSS: Types (Cont.) 6. Reminder o Called best practice advisory o Helps deliver quality preventive care and management of chronic diseases o Appear as pop-up box (time triggered) o Is not always heeded by busy clinicians who may choose to ignore them Example of lung cancer screening reminder CDSS: Types (Cont.) 7. Order checking o Rules based o Provides recommendations that clinician usually has the option of overruling – i.e., does not replace clinician expertise CDSS: Types 8. Order set o Special orders that reflect clinical practice guidelines, thus offering optimal patient care o It is researched, adopted and modified o Ex: community acquired pneumonia (CAP) order set is: Certain antibiotic, chest X-ray, and oxygen use CDSS: Benefits 1. Reducing variation in care o CDSS supports provider adherence to evidence-based practice (particularly when integrated with CPOE) o Ex: Diagnoses may come with a set of associated orders Pre-programmed, reviewed, and approved orders guide providers in following protocols CDSS: Benefits (Cont.) 2. Improvement in patient safety and reduction of medical errors o Order checking: verifying that an action was the intended one o Alert: drug-drug interaction o Infobutton: providing medication advice o Reminder: annual mammogram CDSS: Benefits (Cont.) 3. Reducing costs o Studies shows using CDSS and CPOE can reduce length of stay and decrease medications costs A Tierney study (1993) found a savings of $887 per admission when orders were written using CPOE and CDSS o This is achieved through: Reducing drug expenses by showing cheaper alternatives and using generic drugs Catching duplicate or unnecessary orders Fewer unnecessary tests being ordered Reduced malpractice risks Better utilization of blood products CDSS: Benefits (Cont.) 4. Support clinical research o Ability to identify research subjects 5. Improvement of population health o Identification of high-cost/needs patients o Mass customized messaging EHR Challenges & Key Capabilities EHR: Challenges EHR like any technology, may face any of the following barriers such as 1. Leadership commitment o EHR impacts workflow throughout the organization 2. Medico-legal concerns (especially with CDSS) o Potential for altered patient outcomes o Failing to adhere to evidence-based guidelines o Ignoring alerts or recommendations EHR: Challenges (Cont.) 3. Avoiding over-alerting (Van der Sijs, 2006) o Alert fatigue is a significant issue in CDSS o Physicians override alerts 49-96% of the time, usually for good reasons: Only 2-3% of overrides lead to an adverse drug event Reviewers agree with overrides 95.6% of the time Recommendations include reviewing and reducing unnecessary alerts EHR: Challenges (Cont.) 4. Challenges with CPOE: o Slower than traditional scribbling o More complicated process o Can burden physicians 5. Cost: implementation and maintenance can be expensive 6. Lack of confidence in the system: resistance from staff due to unfamiliarity 7. Reliability: concerns about system downtimes or errors 8. Insufficient training: lack of proper education on how to use the system effectively EHR: Key Capabilities - Institute of Medicine (IOM) identified set of eight core care delivery functions that EHR systems should be capable of performing in order to promote greater safety, quality and efficiency in health care delivery 1. Health information and data 2. Result management 3. Order management 4. Decision support 5. Electronic communication and connectivity 6. Patient support 7. Administrative processes and reporting 8. Reporting and population health EHR: Key Capabilities (Cont.) 1. Health information and data POC (problem summary list) POC (problem report) EHR: Key Capabilities (Cont.) 2. Result management - The ability for all providers in different settings to quickly access new and past test results Source system (laboratory information system) EHR: Key Capabilities (Cont.) 3. Order management - The ability to enter and store orders for prescriptions, tests, and other services Core clinical application (electronic prescription) EHR: Key Capabilities (Cont.) 4. Decision support - Reminders, prompts, and alerts to improve compliance with best clinical practices, ensure preventive practices CDSS (reminder) EHR: Key Capabilities (Cont.) 5. Electronic communication and connectivity - Efficient, secure, and readily accessible communication among providers and patients within and between organizations Connectivity (Patient portal) EHR: Key Capabilities (Cont.) 6. Patient support - Tools that give patients access to their health records, provide interactive patient education, and help them carry out home- monitoring and self-testing Hyperlink (patient education) EHR: Key Capabilities (Cont.) 7. Administrative processes and reporting - Administrative tools, including billing and scheduling systems Foundation System (calendar) EHR: Key Capabilities (Cont.) 8. Reporting and population health - Electronic data storage that uses standardized data formats to quickly meet reporting requirements Infrastructure (Continuity of Care Document) EHR: Key Capabilities (Cont.) Class Activity By implementing the following applications, what key capabilities will be achieved? Patient CPOE Portal Email 1. Health information and data 5. Electronic communication & connectivity 2. Result management 6. Patient support 3. Order management 7. Administrative processes and reporting 4. Decision support 8. Reporting and population health Summary - Core clinical application is an essential component of EHR - POC charting is different based on the clinical role and type of data - EMAR uses barcode or RFID to automate the medication administration processes and making sure of the 5 rights - Ordering stage has the highest medication errors followed by administration phase - CPOE enables providers to enter all types of orders into EHR - CDSS is any tool that reduces the cognitive burden of providers to provide care - Three indications for the need to CDSS either organizational need, evidence-based, or accreditation - There are many benefits of EHR provide, but organization must consider the challenges and design to overcome them - IOM identified 8 core functions that EHR should be capable of References Al-Harbi, R. (2017). Stages of the medication use process and medication errors.. https://www.slideshare.net/cetdmgh/stages-of-the-medication-use-process-and- medication-errors [Presentation]. Alyssa. (2017). Clinical decision support systems [Video]. YouTube. https://www.youtube.com/watch?v=nB05_QbPS0A&ab_channel=Alyssa Autry Learn Now. (2018). Practical nursing - medication administration records and prepping medications [Video]. YouTube. https://www.youtube.com/watch?v=XYKbcTsu0MQ&ab_channel=AutryLearnNow Basicmedical Key. (2017). Understanding and interpreting medication orders. https://basicmedicalkey.com/understanding-and-interpreting-medication-orders/# Elden, N. M. K., & Ismail, A. (2016). The importance of medication errors reporting in improving the quality of clinical care services. Global Journal of Health Science, 8(8), 243. https://doi.10.5539/gjhs.v8n8p243 Emily, R. & Coutts, T. (2017). How consistency in EHR design can contribute to patient safety. https://ehrablog.org/2017/11/10/how-consistency-in-ehr-design-can-contribute- to-patient-safety/ References (Cont.) Holdsworth, M. Fichtl, R., Raisch, D., Hewryk, A., Behta, M., Mendez-Rico, E., Wong, C., Cohen, J., Bostwick, S. & Greenwald, B. (2007). Impact of computerized prescriber order entry on the incidence of adverse drug events in pediatric inpatients. Pediatrics, 120(5). 1058-1066. https;// doi.10.1542/peds.2006-3160 Hebda, T., Hunter, K. & Czar, P. (2024). Handbook of informatics for nurses and healthcare professionals. (7th ed.). Pearson. Chapter 7. Hoyt, R. E. &Yoshihashi, A. K. (2018). Health informatics: Practical guide for healthcare and information technology professionals. (7th ed.). Lulu.com. Chapter 4 & 8 Kuo, G., Phillips, R., Graham, D., Hickner, J. (2008). Medication errors reported by US family physicians and their office staff. Quality and Safety in Health Care.17(4):286- 290. https://doi.10.1136/qshc.2007.024869 Nuckols, T. K., Asch, S. M., Patel, V., Keeler, E., Anderson, L., Buntin, M. B., & Escarce, J. J. (2015). Implementing Computerized Provider Order Entry in Acute Care Hospitals in the United States Could Generate Substantial Savings to Society. Joint Commission journal on quality and patient safety, 41(8), 341–350. https://doi.org/10.1016/s1553-7250(15)41045-1 References (Cont.) Osheroff, J., Teich, J., Levick, D., Saldana, L., Velasco, F., Sittig, D., Rogers, K., Jenders, R. (2012). Improving outcomes with clinical decision support: an implementer’s guide. (2nd ed.) Healthcare Information and Management Systems. Van der Sijs, H., Aarts, J., Vulto, A. & Berg, M. (2006). Overriding of drug safety alerts in computerized physician order entry. Journal of the American Medical Informatics Association.13(2):138-47. Https://doi: 10.1197/jamia.M1809. Yoshida, E. Fei, S., Bavuso, K., Lagor, C. & Maviglia, S. (2018). The Value of monitoring clinical decision support interventions. Applied Clinical Informatics.9(1):163-173. https://doi: 10.1055/s-0038-1632397 THANK YOU

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