Introduction
In the healthcare setting, initiatives to enhance safety improvements and quality are paramount to counter all the related healthcare problems. In the contemporary world, technological advancements, specifically in the medical field, have led to a radical improvement in the delivery of services (Scales & Schuman, 2014). Despite these advancements, society is in the initial stages of progress, where some growth aspects are registered on a daily basis. With all these advancements, it is argued that we are in a time of growing pains where the medical field due to challenges associated with the integration of services, quality of services, and sustainable pricing, specifically in all pharmaceutical products. Although innovations have taken a massive role in changing how services are delivered in healthcare, it will require some time before all the advancements fully address the problems (Scales & Schuman, 2014). This paper will highlight some of the approaches that can be embraced to address a problem mainly within the healthcare setting, the risk mitigation approaches, and the implementation of the new compliance requirements.
Currently, the policy community has put a lot of concern on the impacts of interoperability, commonly referred to as consumer data access, which is a significant issue in the healthcare sector. The medical industry has been prone to medical errors due to adequate consumer data access for a long time. Such errors have become a widespread concern within the healthcare system, subjecting individuals to life-threatening advances (Kouroubali & Katehakis, 2019). This has been a problem that has enhanced efforts initiated by the consumers to ensure improvement in how most of the medical information is usually shared mainly by doctors and other clinicians. The growing presence of errors in the medical field, subjecting people to risks, is a significant concern, proving that interoperability is a significant problem in healthcare. Observation on how the medical errors are increasing is a clear indication of inadequate data, mainly between the doctors and other medical practitioners.
Events such as healthcare crises usually necessitate or trigger the initiation of a continuous improvement process, especially in healthcare. This is mainly because poor healthcare in a nation usually has health-related and economic impacts specifically to patients and the more extensive healthcare system (Scales & Schuman, 2014). The quality improvement process is mainly the systematic improvement in how care is primarily given to patients. The process especially seeks to ensure standardization of the process and the structure to ensure reduction in the variation and acquire the necessary results that lead to improved outcomes mainly to patients. Events that amount to healthcare crises include poor healthcare, which negatively impacts the delivery of healthcare to patients. The aspect of enhancement in the research has a positive impact that usually leads to an adequate comprehension of how all the improvements in patient care can be attained and sustained.
The tools utilized to identify interoperability in the healthcare sector include electronic health records (EHRs) and patient registries. These tools use the information related to patients’ clinical information (Gliklich et al., 2019). The EHR is an electronic device that is usually utilized by the healthcare system to collect and store patient data. It is mainly used in clinical care and other healthcare administrators in order to trace some of the individual information. On the other hand, a patient registry primarily refers to the established system that utilizes observation as a study method to collect clinical data in order to evaluate the prevalence of particular diseases (Scales & Schuman, 2014). All these tools offer a solution to interoperability by mainly providing a unique opportunity that the healthcare systems can embrace to develop some internal strategies. The registries help capture all the EHR data mainly from different healthcare systems that usually receive data on an interval basis (Gliklich et al., 2019). The EHRs offer various forms of data that can be integrated into the registry, which significantly impacts the accessibility of previous patient data. The implementation of the registry and EHRs has been a major boost in the advancement of patient care, causing a significant shift in the consumer accessibility of data.
How to Go About the Interpolability of the Health System
The interoperability of healthcare records must be a top priority for the management of healthcare systems. There must be a universal approach to healthcare systems, terms and data management and must touch specifically on all aspects of the healthcare system. Data remains a priority resource for organizations, and the processes of handing data and the storage thereof of health records can be leveraged to make it accessible. Available at every time the stakeholders need it. It narrows down to the commitment by the organizational stakeholders to have the data exchange integrated and streamlined. Member exchanges, patients sharing of information, and information flow can be handled from this perspective. There are various ways in which healthcare data can be streamlined by improving the health information exchange and embracing the digital space to promote the electronic transfer and sharing of healthcare information securely and confidentially (Bacci & Berenbrok, 2018). With such a transformation, the retrieval and sharing of this information can be safer, efficient, and convenient.
Compliance with Interpolability calls for an incentivized approach to motivate the stakeholders to migrate into the digital space. There are serialized steps to the Interpolability if digital records can best be understood by first analyzing the adoption and optimization mechanisms, then establishing the standards of Interpolability. Once done, those standards and processes can be measured against the costs, the budgetary allocation, the resource availability and how to mobilize enough, and the needed capital investments. Electronic health records management is the bottom line of the integration of the health systems. Once the system has been adopted in one department, it can be duplicated in all the departments and digitized every data available in the system (Bacci & Berenbrok, 2018). The system can be accelerated and improved to enhance interparty communications and exchanges in the best interest of service improvements. The aim is to provide strategic, structured, and holistic customer-driven services. With the adoption and standardization of the electronic health records management system, the reach is likely broader, and diversity is appreciated.
This can be done at the admissions, consultations, referrals, and discharges of patients and during the examination and give the patients and network of trusted experts to consult from. It is also sufficient to record, automate and share patients’ data seamlessly and conveniently. As a result of this sensitivity, however, there are costs and risks associated with Interpolability that cannot be ignored. Some costs covered by the system involve upgrading the security and privacy mechanism for the system—the best approach to researching the best practice for the system and the rules of engagement. There is an Interpolability framework on policy and standards established to govern the solution and can act as a standard measure for the systems. It also offers a comprehensive environment for testing and monitoring the system. The systems coordination mechanism and capabilities are tested against the laid frameworks and established standards. Machine learning technologies and blockchain can also be integrated into the information Interpolability, especially at the payment and exit steps of the healthcare system (Gordon & Catalini, 2018). Interoperability aims to bring into perspective a serene way of data quality management and standardization in healthcare. It is a threat to the existing world when data is collected and handled haphazardly while the necessary framework exists to streamline data management.
Healthcare professionals, members of the management panel, patients, and service providers are the primary stakeholders for the system. They are critical for information sharing and testing the proposed solutions and information exchange, financial performance, and cost analysis interrogators and crucial for clinical data collection and sharing. Risks associated with the approach will be mitigated and a structured hierarchical and timely approach with clarity of communication and a centralized effort to address the risks as they approach (Holmgren et al., 2017). Data needs to be reality available and accessible. Thus, barriers to this goal must be broken decisively and holistically by investing considerate capital and mobilizing the necessary resources to achieve this milestone. Quality and the regulatory framework must, however, remain a priority.
References
Bacci, J. L., & Berenbrok, L. A. (2018). Innovative advances in connectivity and community pharmacist patient care services: Implications for patient safety. Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy, 38(8), 867-874. https://doi.org/10.1002/phar.2148
Gliklich, R. E., Leavy, M. B., & Dreyer, N. A. (2019). Tools and Technologies for Registry Interoperability, Registries for Evaluating Patient Outcomes: A User’s Guide, Addendum 2 [Internet].
Gordon, W. J., & Catalini, C. (2018). Blockchain technology for healthcare: facilitating the transition to patient-driven interoperability. Computational and structural biotechnology journal, 16, 224-230. https://doi.org/10.1016/j.csbj.2018.06.003
Holmgren, A. J., Patel, V., & Adler-Milstein, J. (2017). Progress in interoperability: measuring US hospitals’ engagement in sharing patient data. Health Affairs, 36(10), 1820-1827. https://www.healthaffairs.org/doi/full/10.1377/hlthaff.2017.0546
Kouroubali, A., & Katehakis, D. G. (2019). The new European interoperability framework as a facilitator of digital transformation for citizen empowerment. Journal of biomedical informatics, 94, 103166.
Scales, C. D., & Schulman, K. A. (2014). Triggering management for quality improvement. Health services research, 49(5), 1401.
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