Effective semantic interoperability enhances the exchange of properly interpreted information within a system. Restrictions on information exchange can be due to limited large data sharing, syntactic web synchronization error, and evolving semantic heterogeneity, affecting operational balance (Martínez-Costa et al., 2014). Healthcare systems experiencing interoperability challenges fail to secure timely access to information, electronic data integration, and poor health outcomes optimization, affecting the quality of care. For instance, delayed access to a patient’s current diagnosis results or medical history could lead to repetitive processes that derail health processes and cause issues such as misdiagnosis to occur (Martínez-Costa et al., 2014). All these flaws indicate that poor interoperability systems can affect the quality of care by delaying health processes.
The study purports that system interoperability is a game changer in enhancing efficiency in healthcare systems. Advantages of effective system interoperability include adaptability, data unity, information security, and few errors. Therefore, restrictions on achieving system interoperability indicate that these benefits will be restricted, resulting in delayed processes (Martínez-Costa et al., 2014). For instance, adaptability is whereby systems are automated to share information faster with relevant parties. Adaptability is hindered when the system is affected, affecting the overall functions.
Scope of the Research
While the immediate advantages of health interoperability are well documented, the challenges in the system and how it affects health quality are not explored adequately. Therefore, this study focuses on how interoperability challenges derail healthcare service quality in the US (Jaulent et al., 2018). The study is limited to recruiting 100 volunteer hospital experts using electronic health records to help elaborate on how interoperability challenges affect the meaningful use of information and the system’s issues. The setting of the study will be based within the capital city, considering that it is the busiest and have hospitals with the most advanced medical technology (Jaulent et al., 2018). The study will last for two months to ensure that the daily assessment of the hospital’s technology use is effectively monitored. The methodology will focus on observation and experimentation on how the EHR systems function.
The study will admit only general hospital volunteers considering they have a wider patient scope. This environment presents the pressure to constantly exchange data between experts to ensure efficiency and time management (Jaulent et al., 2018). Targeted volunteers will be required to review how the system works alongside test samples on the state of their system. For instance, volunteers will be required to retrieve data on a specific patient within a set timeline. Additionally, the volunteers will be required to explain problems encountered during data exchange to determine the specific problem in the system. The access speed will determine the system’s state, and the results will be recorded.
Significance of the Problem
The Health system interoperability challenge has resulted in poor quality healthcare service providers in the US. Interoperability systems enable practitioners to share data in real-time, strengthening service delivery by ensuring that data about the patient is readily available upon request. However, challenges in the system have become a significant setback in the operational efficiency of technology systems in the healthcare setting (Jaulent et al., 2018). Research highlighting these challenges is limited, considering that information about system interoperability issues is scarce (Jaulent et al., 2018). Furthermore, most of the literature exploring the limitations to system interoperability presents jargonized theories, including the aspect of policy restrictions that promotes confidentiality and autonomy. These findings indicate that not much has been explored concerning the fundamental issues affecting sustainable system interoperability, which is a gap to explore. Therefore, this study will benefit healthcare industry stakeholders and interested parties in healthcare delivery issues.
Guiding Research Questions
- What challenges affect the effective utilization of system interoperability in the healthcare sector?
- How does the challenge in system interoperability affect the quality of hospital services?
Variables and Definitions
The study utilizes dependent and independent variables to explain how each affects the other. In this case, the dependent variable is the system interoperability considering that manipulations of the independent variables can change it. Additionally, the state of system interoperability affects the outcome of this research, considering that the challenge is measured when dependent variables are altered (Andrade, 2021). The independent variables in this study include all the glitches that affect system interoperability, making it not function properly (Andrade, 2021). Such variables include restricted large data sharing, syntactic web synchronization, and evolving semantic heterogeneity. These challenges are the independent variables considering that they determine whether system interoperability is functional in the absence or non-functional in their presence.
Independent and dependent variables were selected for this study since the connection on the affective consequence of each variable is easily identified. This process enables the researcher to identify the outcome of their research by simply analyzing the cause-and-effect relationship between the present variable (Andrade, 2021). For instance, if there is a challenge in accessing information in an EHR system, the probability that system interoperability is affected by either syntactic web synchronization error or change in the system is guaranteed. This factor will enable the research to determine individual issues clogging the system.
Andrade, C. (2021). A student’s guide to the classification and operationalization of variables in the conceptualization and design of a clinical study: Part 1. Indian Journal of Psychological Medicine, 43(2), 177-179.
Jaulent, M. C., Leprovost, D., Charlet, J., & Choquet, R. (2018). Semantic interoperability challenges to process large amount of data perspectives in forensic and legal medicine. Journal of Forensic and Legal Medicine, 57, 19-23.
Martínez-Costa, C., Kalra, D., & Schulz, S. (2014). Improving EHR semantic interoperability: future vision and challenges. (eBook edition). IOS Press. Web.