By Sarah Handzel, BSN, RN
Database management systems tie into almost every aspect of the clinical work environment today. According to the Office of the National Coordinator for Health Information Technology, 96% of non-federal acute care hospitals and 78% of outpatient physician offices use certified electronic health records (EHRs) to help manage patient care.1
As healthcare centers continue to adopt technology to create centralized database management system, some clinicians may wonder just how beneficial these systems are, especially now that new technologies, including ambulatory ECG devices, are increasingly being used by patients to provide continuous, real-time information about their heart health.
Benefits of a centralized database management system
As ECG technology continues to evolve, database management systems help clinicians continue to provide the highest quality care possible. While many of the benefits of such systems are obvious, clinicians and healthcare decision-makers might overlook certain advantages, such as:
- Connecting ECG technology: While the COVID-19 pandemic precipitated a in drop mergers and acquisitions within the healthcare industry, a recent report from Kaufman Hall suggests this trend is reversing. The report found 20 announced healthcare transactions in Q2 of 2023, up from 15 transactions in Q1 of the same year.2 These mergers often leave healthcare centers with various ECG technologies from several vendors. Centralized data systems help integrate all existing data into one shared platform, giving clinicians better access to historical patient information and the results of new diagnostic tests or therapeutic interventions.
- Identifying diagnostic trends: Evolving centralized data systems can store more patient information than ever before, creating a "data deluge." These huge data stores can be used to inform the decision-making process and provide better care. As the use of artificial intelligence (AI) expands in healthcare, these technologies may be used in conjunction with database management systems to analyze ECGs collected over time, enabling better detection of cardiovascular abnormalities. Using AI to evaluate large-scale ECG databases may save clinicians time and effort in diagnosing patients.
- Informing algorithms and deep learning opportunities for future AI: Procedures like transcatheter aortic valve replacement (TAVR) contribute significantly to survival rates for patients with conditions like aortic stenosis. However, physicians associate this procedure with conduction disturbances; unfortunately, problems like new-onset Afib occur with relative frequency, regardless of improvements in medical devices and surgical techniques.5 According to a review in the Journal of the American College of Cardiology, ambulatory ECG monitoring of patients undergoing TAVR could help identify patients with conduction issues both before and after surgery while also generating extremely large data sets.5 Future artificial intelligence (AI) platforms could use deep learning systems to review hi fidelity databases and create algorithms that allow clinicians to quickly and easily identify patients with various arrhythmias.
- Improving care coordination: Before digital database management systems, healthcare communications were often disjointed and inefficient. Well-designed, targeted care coordination delivered to the right individual helps improve outcomes across the healthcare spectrum, according to the Agency for Healthcare Research and Quality.3 A shared, centralized data system allows clinicians to view patient-specific information from virtually any location, enabling them to share ideas with other providers and manage a patient's care plan to provide the best outcome possible.
- Protecting private patient information: The U.S. Department of Health and Human Services Office for Civil Rights reports that, in the past 24 months, 700 hacking or other IT incidents resulted in protected health information breaches affecting millions of patients.4 Today, database management systems are more secure, offering better protection against denial of service (DDoS) attacks in particular. While centralized data systems store patient information in one convenient location, this information can usually also be stored externally, offering an alternative source of patient data if breaches occur.
Implications for ambulatory ECGs
Today, the availability of smartphones and other wearable devices makes it easier than ever for clinicians to monitor heart conditions and make definitive diagnoses via ambulatory ECG technology. Cardiology database management systems allow for fast data delivery and distribution, and can support ECG analysis on a variety of devices. Giving physicians this easy, fast access to ambulatory ECGs may be particularly important in evaluating patients who present with chest pain or other indicators of myocardial infarction in emergency department facilities.
This data access can enable clinicians to diagnose patients rapidly and activate life-saving interventions sooner. For example, the catheterization lab could be prepared earlier for a patient with suspected STEMI in order to provide potentially life-saving care more quickly. Coupling ambulatory ECG with database management systems can be especially useful for cardiologists who are away from ECG workstations when a patient arrives.
Making use of a database management system is becoming more crucial for providing the highest quality of care possible. If coupled with AI in the future, these systems may be used as an initial screening tool to better identify potential problems, even if standard ECGs are not indicative of any issues. For now, healthcare providers may find that such systems help them better analyze patient data, make diagnostic decisions, and determine which treatments are most likely to promote positive outcomes.
Resources:
1. National trends in hospital and physician adoption of electronic health records. The Office of the National Coordinator for Health Information Technology. https://www.healthit.gov/data/quickstats/national-trends-hospital-and-physician-adoption-electronic-health-records. Accessed November 2, 2023.
2. M&A quarterly activity report: Q2 2023. Kaufman Hall. Published July 13, 2023. https://www.kaufmanhall.com/insights/research-report/ma-quarterly-activity-report-q2-2023. Accessed November 2, 2023.
3. Care coordination. Agency for Healthcare Research and Quality. Last reviewed August 2018. https://www.ahrq.gov/ncepcr/care/coordination.html. Accessed November 2, 2023.
4. Cases currently under investigation. U.S. Department of Health and Human Services Office for Civil Rights. https://ocrportal.hhs.gov/ocr/breach/breach_report.jsf;jsessionid=263AE17073455B71C29108C464933295. Accessed November 2, 2023.
5. Muntané-Carol G, Philippon F, Nault I, et al. Ambulatory electrocardiogram monitoring in patients undergoing transcatheter aortic valve replacement. Journal of the American College of Cardiology. 2021;77(10):1344-1356. https://www.jacc.org/doi/10.1016/j.jacc.2020.12.062.
