Electronic Health records

Keywords

1. Electronic Health Records
2. Medication Data Quality
3. EHR Completeness
4. Saudi Pharmaceutical Journal
5. Pharmacoepidemiological Research

In the era of digital health information, Electronic Health Records (EHRs) stand as a pivotal component in enhancing patient care, conducting clinical research, and improving public health surveillance. A study published in the Saudi Pharmaceutical Journal has shed light on the quality and completeness of medication-related data drawn from EHRs, which bears consequential implications for pharmacoepidemiological research and healthcare practice.

The study, featured in the May 2019 issue of the Saudi Pharmaceutical Journal, was conducted by a team of researchers from prominent institutions such as the College of Pharmacy at King Saud University and the Saudi Patient Safety Centre. The analysis, supported by the Medication Safety Research Chair of King Saud University, focused on a retrospective cross-sectional study leveraging data from a tertiary hospital’s EHR database in Saudi Arabia. A DOI associated with this study is 10.1016/j.jsps.2019.01.013, highlighting its digital accessibility for scholarly reference.

The research aimed to quantify the completeness of the medication-related information in the patients’ records, which is critical for ensuring the reliability of healthcare delivery and research endeavors. The presence of complete data including patient demographics, clinical diagnosis, and medication-related information represents the backbone of informative and actionable EHRs.

A total of 23,411 unique patient records were extracted and analyzed, of which 89.9% possessed complete data in terms of demographics and clinical diagnosis. Furthermore, 83.1% of the records were found to have comprehensive medication-related information. The study also found nuanced differences in data completeness when considering encounter types — outpatient data was 91.0% complete, while inpatient data was marginally higher at 93.2%.

These findings are indicative of the potential value EHRs hold as a resource for research, especially in the realm of medication usage assessment. Nonetheless, the research also underscored the need for further studies to delve into the content-related specifics and the different dimensions of data quality within EHRs systems.

To place this research in a broader context, it stands on the shoulders of preceding scholarly works. Ambinder (2005) has discussed the advent of EHRs as a transformative element in the oncology practice, demonstrating early recognition of EHR importance. Blumenthal and Tavenner (2010) elaborated on the ‘meaningful use’ of EHRs, which has provided a framework for utilizing electronic records to improve patient care. Buck et al. (2009) showed the potential for EHRs to highlight inappropriate medication prescribing in outpatient practices, signaling the importance of accurate data for medication safety.

Studies by Castro et al. (2013) and Cebul et al. (2011) further substantiate the multipurpose nature of EHR data, from cardiac risks to diabetes care. Coorevits et al. (2013) and DeVoe et al. (2011) expanded the discourse to the new opportunities EHRs present for clinical research and the verification of preventive care data, respectively.

Hasanain et al. (2015) focused on the knowledge and preferences of healthcare professionals regarding EMR systems in Saudi Arabia, which provides a regional perspective relevant to the current study. Häyrinen et al. (2008) provided foundational knowledge through their comprehensive review of EHR definitions and impacts, which acts as a touchstone in EHR-related discourse.

The study’s publication is a critical addition to the growing body of literature about EHRs and specifically medication data quality. It contributes important findings that can shape future policies and initiatives aimed at enhancing EHR capabilities for research and clinical use.

The work by Alwhaibi Monira M. and her colleagues sets a precedent for healthcare providers, policymakers, and researchers in Saudi Arabia and beyond to prioritize the maintenance of complete and precise EHR data. Achieving such a standard would be instrumental in elevating patient care and the validity of pharmacoepidemiological studies, leading to improved outcomes on a systemic level.

Progress in this field requires an interdisciplinary approach, involving clinicians, IT specialists, researchers, and regulators, all working collaboratively to harness the full potential of EHR data. With the rise of big data and advanced analytics, the importance of maintaining high-quality digital health records cannot be understated, as they are the fodder for predictive models, retrospective analyses, and ultimately, the catalyst for informed clinical decisions and public health strategies.

In conclusion, EHRs have already transformed healthcare delivery and research, allowing for streamlined processes and richer, more robust datasets. The study published in the Saudi Pharmaceutical Journal offers valuable insights into the necessity for continuous monitoring and improvement of the quality and completeness of medication-related EHR information, emphasizing its critical role in the healthcare ecosystem. It lays the groundwork for ongoing improvement efforts and validates the shared goal of more thoughtful, data-driven healthcare environments in Saudi Arabia and the world over.

References

1. Ambinder E.P. (2005). Electronic health records. Journal of Oncology Practice, 1(2), 57–63. doi:10.1200/JOP.2005.1.2.57
2. Alwhaibi Monira M., et al. (2019). Measuring the quality and completeness of medication-related information derived from hospital electronic health records database. Saudi Pharmaceutical Journal, 27(4), 502-506. doi:10.1016/j.jsps.2019.01.013
3. Blumenthal D., Tavenner M. (2010). The “meaningful use” regulation for electronic health records. The New England Journal of Medicine, 2010(363), 501–504. doi:10.1056/NEJMp1006114
4. Buck M.D., et al. (2009). Potentially inappropriate medication prescribing in outpatient practices: prevalence and patient characteristics based on electronic health records. American Journal of Geriatric Pharmacotherapy, 7(2), 84–92. doi:10.1016/j.amjopharm.2009.04.003
5. Castro V.M., et al. (2013). QT interval and antidepressant use: a cross-sectional study of electronic health records. BMJ, 346. doi:10.1136/bmj.f288
6. Cebul R.D., et al. (2011). Electronic health records and quality of diabetes care. The New England Journal of Medicine, 365(9), 825–833. doi:10.1056/NEJMsa1102519
7. Coorevits P., et al. (2013). Electronic health records: new opportunities for clinical research. Journal of Internal Medicine, 274(6), 547–560. doi:10.1111/joim.12119
8. DeVoe J.E., et al. (2011). Electronic health records vs Medicaid claims: completeness of diabetes preventive care data in community health centers. Annals of Family Medicine, 9(4), 351–358. doi:10.1370/afm.1267
9. Hasanain R.A., et al. (2015). Electronic medical record systems in Saudi Arabia: Knowledge and preferences of healthcare professionals. Journal of Health Informatics in Developing Countries, 9(1).
10. Häyrinen K., et al. (2008). Definition, structure, content, use and impacts of electronic health records: A review of the research literature. International Journal of Medical Informatics, 77(5), 291–304. doi:10.1016/j.ijmedinf.2007.09.001