Introduction
Data compatibility helps electronic health records (EHR) sharing with other software systems in the medical field (Saleh et al., 2021). Ensuring data compatibility in various healthcare facilities can pose a problem that could affect important research like the one I am conducting. Data compatibility enables various staff members to access information in one EHR within a facility.
Data Compatibility
Having complete and continuous access to patient records using compatible EHR systems and various computer networks ensures data from multiple sources is compatible with our physician’s office data. Utilizing data standards that allow compatibility across the system is required. Data standardization ensures the comparison of similar data. An electronic HIE helps achieve appropriate data standardization. To understand that the data I am using for comparison is compatible with my office data, I will clearly define the criteria that determine compatibility, such as data structures, formats, and relevant standards. Doing so helps in establishing a baseline for comparison. Also, creating a mapping schema that outlines how data elements in the external data set correspond to those in my office data is another step. It helps in identifying and aligning similar data fields. We can create a list of patients who had their cancer stage documented or not if it was recorded at the time of admission or when the disease was discovered and entered into the EHR. This is one example that relates to our research. After that, we can identify the root cause of the issue and concentrate more of our efforts there to ensure that newly diagnosed patients’ cancer stages are recorded.
The main problem arising from data standardization is ensuring that multiple sources refer to the same disease (Aiello et al., 2020), in this case, cancer, and utilizing similar analysis for their data. Other challenges affecting data standardization include underlying formats, inconsistent terminology, and differences in the coding systems across sources.
Effects of Health Information Quality on the HIE
Health information exchange (HIE) plays a major role in facilitating data sharing of health information in local or regional areas among healthcare entities, while the National Database stores health data and is managed centrally. In other words, HIE focuses on regional collaboration, while the national database extends its scope to a national level. The problems that can develop if facilities submit incomplete or inaccurate information to an HIE can translate to compromised patient care, medical errors, and incorrect treatment decisions. Inaccurate data affects the comprehensive understanding of a patient’s health history, which results in inappropriate interventions. On the other hand, submitting incomplete or inaccurate information to a national database can translate to a compromised public health analysis, affect policy-making, and affect research accuracy. Notably, inaccurate data may distort the national health statistics, which affect resource allocation and healthcare planning. The complete and accurate data may affect my proposal by compromising the integrity of its research findings. It impacts the ability to draw concrete conclusions, translating to flawed insights.
Conclusion
Conducting documentation review depends on using multiple internal and external databases, including EHRs, to databases similar to AHRQ or CDC. It requires higher interoperability to collect and secure accurate and reliable data. The top priority of my office is to improve patient care and ease data retrieval and use within the facility. My proposal will follow the intended practices of reviewing and collecting data to benefit patients in the future.
References
Aiello, A. E., Renson, A., & Zivich, P. (2020). Social media and internet-based disease surveillance for public health. Annual review of public health, 41, 101. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959655/
Salleh, M. I. M., Abdullah, R., & Zakaria, N. (2021). Evaluating the effects of electronic health records system adoption on the performance of Malaysian health care providers. BMC medical informatics and decision making, 21(1), 1-13. https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-021-01447-4
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