Integration between various systems
Discuss about the Enterprise Information Architecture for EHR System.
Enterprise information architecture can be considered as the subset of the enterprise architecture process. Enterprise architecture with careful analysis of requirements and the principles helps to predict the appropriate model that can effectively manage information and distribute it throughout the organization so that the data can be used effectively. The architecture also helps in performing data integration so that the data that is collected from various resources can be effectively realized and maintained properly. With the advancement of technology there has been a complete makeover in the way organizations used to manage their data and put that into practice (Malyzhenkov and Ivanova 2017).
A digital revolution seems to be going on across various sectors, thanks to the technological advancement. The revolution is also prevalent in the healthcare sector as well. Healthcare organization are considering to implement electronic health record system for collecting and storing information related to the patient , doctor and various department of the healthcare organization so that those data can be used whenever necessary to p-perform the desired function. However with the benefits, there are some challenges of integrating electronic health record system (EHR).
The main challenge that the system brings for the organization is the management of the data which is not only high in volume and frequency, but also includes unstructured data which is difficult to be interpreted and analyzed. However, with careful choice of technology this problem can be effectively solved so that the full benefits of the system can be realized to obtain the desired productivity for the organization.
The task of providing quality medical services irrespective of the locations is a major challenge. Sometimes there is lack of quality doctors and in many cases the level of expertise of the doctors is also questionable which often leads to errors in medical services. The electronic record of medical information is intended to provide reliable services by sharing medical related information across different location within and outside the premises of the medical organizations (Da Xu 2014). However, in order to achieve the feat, it is not only important to record the information about the medical conditions of the patients, but various systems that stores other related information like the history of the patient treatment, the doctors assigned for the patent and even the information about the organization is particularly important in this context. However integration between these systems is not only challenging, but needs efficient solution to deal with the issues. Without the integration of the interrelated systems, it is not possible to realize the full potential of the electronic health record system. Enterprise Information Architecture provides the reference to design the appropriate architecture to perform the integration across the system.
Choice of proper information technology
Electronic heath record system helps in collecting various information about the health related data. However it is important to provide this information in quick time and accurately at the doctors often need to access data on demand to make strategic decision for improving health related services. Enterprise information architecture helps to maintain the quality of the information provided and also ensures that data are provided whenever it is needed without any issues. EIA helps to design an integrated healthcare system which is capable in providing timely and accurate health related information which the healthcare providers may refer to get more comprehensive view about the patient to provide quality health care service. Integrated health care system provides the basis for designing a strong electronic health recording architecture that is efficient in addressing the entire health system (Chorafas 2016). Integrated health information system helps the professional to mitigate with the issues like choice of proper instruments and methodology to record information, assessing the originality of the data recorded and keeping the data secured as well as maintaining the integrity and confidentiality of the data. Proper enterprise information architecture helps to address all these issues which are difficult to maintain with manual approach.
There are various information technologies to design electronic health recording system, however it is always difficult to identify the correct one by evaluating the needs and purpose of integrating the system. Enterprise information architecture with a thorough assessment of the nature of the data being recorded and the scope of uses, provides the correct choice of information technology that has the ability to address the requirement effectively and efficiently. The architecture is also capable to evaluate the overall information architecture and finds the issues with the existing infrastructure and suggest the necessary changes that needs to be considered before applying new technology and integrating it with the existing information system to make it more relevant for the organization where the system is being is implemented so that the full benefits of the system can be retrieved (Reiss-Brennan et al. 2016).
The data that is recorded in the electronic health record system varies in nature. Although most of the time the data is structured in nature, however it is not mandatory that the data will be always of that nature(Stonova 2014). Now it is relatively easy to work with structured data and get useful information from those data as the patterns are already defined in the data structure. In case of the unstructured data, the pattern in the data is hard to identify and that is why it is even more difficult to analyse them with traditional data analysis technique.
Data security
Big data analytics helps to work with various data format. It does not matter whether the data is structured or unstructured in nature. The technique is equally efficient in analysing both types of data. Big data analytics with the combination of artificial intelligence and machine learning algorithm helps to find the pattern in the data which is quite difficult or impossible to achieve with the standard data analytics technique (Raghupati and Raghupati 2014). Without finding the pattern in the data, it is not possible to retrieve the required information which is essential to serve the patient in efficient way.
The data that is stored in the electronic health record system, it highly sensitive in nature and it is often more valuable compared to the data related to credit and debit card information. It is the main reason that the hackers are more interested in obtaining these data. Hence the medical record system is one of the most preferred targets of the hackers (Feldman, Martin and Skotnes 2015). In the span of last three years 42.5% of the all the data breaches are related to the health care sector and a whopping 91% of the health care organizations have reported for at least one data breaches in the previous two years (Meeks et al. 2014).
One of the major reasons that the organization have not yet opted for the cyber security measures is the amount of complexity and the cost associated with it (Xhafa et al. 2015).. It is quite possible that during the venerability check by the IT experts, one of the important issues has been missed and due to this the system may be exposed to the external hackers for venerability in the database security (Wager, Lee and Glaser 2017). In order to maintain the data base security and keep the availability and integrity of the data intact it is not sufficient to have the HIPAA compliance. . It is important to adopt cyber security best practises. HIPAA refers to the health insurance portability and accountability act. The act provides the standards to protect the patient data that is highly sensitive in nature. However, the standard does not include the encryption technique as mandatory feature (Dinev et al. 2016). In order to truly make the data secure, data level encryption is must along with the institutional level encryption to perfectly secure the data from illegal access and hacking (Ben-Assuli 2015).
Organization are implementing the digital health recording system to bring more automation and transparency in the process of recording and retrieving data regarding the patient, doctors as well as information about the treatment provided so that all the information can be effectively managed for providing quality services to the patient. In order to store and access so many data the storage not only has to be flexible but scalable as well . The problem with the traditional data storage systems are that it is not only limited in storage capabilities, but also does not offer features like flexibility and scalability (Chu et al. 2014).
In order to obtain those features along with literarily unlimited amount storage, cloud storage is an excellent choice. Cloud storage offers storage on demand and whenever it is necessary. The storage is provided remotely without the requirement of establishing the infrastructure and complex computing systems. However the features varies along with the chosen model of cloud computing, but the overall principle is same and has the capability of addressing the storage requirement effectively and efficiently (Li et al. 2016).
Conclusion:
The report after analysing various facts and reviewing scholarly articles concludes that applying digital approach to record various information related to the patient and the associated entities, has proven to be an effective means for the organizations. It not only helps the organizations to collect data efficiently, but also felicitates to offer better medical services to the patient based on the information. Not only the organization, even the patient has the flexibility to access their medical data without requiring to organize the data as the data is already stored in an organized way in the electronic health record. However, there are some issues with electronic data recording system that need to be addressed carefully and efficiently to realize the full benefits of the system. Facts like data security and data integrity are some of the serious issues that need careful attention. In order to bring more transparency and efficiency in the design process there should be proper reference architecture to provide complete guide like choice of technology, addressing the organizational requirement and preparing a through assessment of the existing architecture and modification to the architecture if needed. Enterprise reference architecture has the ability to act as reference architecture to provide full support in this context.
Big data analytics are excellent choice for advanced data analytics. Hadoop is low cost, offers distributed file systems that supports rapid data share across various data nodes or data servers (Seay et al. 2015). The platform offers excellent features like scalability, flexibility and robustness along with advanced data analytics techniques. Hence the framework is highly recommended for big data management.
Cloud storage is an efficient choice to store ample amount data. However it needs careful analysis of the service providers in order to choose the right ones based on the requirements.. Amazon is the market leader in cloud services and provides assurance for data security and service quality (Varia and Mathew 2014). Amazon web service or AWS platform is the recommended cloud service provider.
The importance of enterprise information architecture as the reference architecture (EIA RA) has already been discussed in the previous section in details. However it is important to choose the correct framework for the enterprise information architecture. Two of the most commonly used frameworks are The Open Group Architecture Framework (TOGAF) and the Zachman Enterprise Architecture Framework (ZEAF). The framework which is recommended here is the TOGAF. The framework is fully efficient in managing organizational information. It helps to analyze the organizational architecture in three layers, business architecture to realize the business objectives, data architecture for collecting and retrieving infrastructure and technical architecture for describing the hardware and software infrastructure and suggest modification based on the analysis and requirements which is important to design effective information architecture in the organization (Malyzhenkov and Ivanova 2017).
References:
Adler-Milstein, J., DesRoches, C.M., Kralovec, P., Foster, G., Worzala, C., Charles, D., Searcy, T. and Jha, A.K., 2015. Electronic health record adoption in US hospitals: progress continues, but challenges persist. Health Affairs, 34(12), pp.2174-2180.
Ben-Assuli, O., 2015. Electronic health records, adoption, quality of care, legal and privacy issues and their implementation in emergency departments. Health Policy, 119(3), pp.287-297.
Chorafas, D.N., 2016. Enterprise architecture and new generation information systems. CRC Press.
Chu, C.K., Chow, S.S., Tzeng, W.G., Zhou, J. and Deng, R.H., 2014. Key-aggregate cryptosystem for scalable data sharing in cloud storage. IEEE transactions on parallel and distributed systems, 25(2), pp.468-477.
Da Xu, L., 2014. Enterprise integration and information architecture: a systems perspective on industrial information integration. Auerbach Publications.
Dinev, T., Albano, V., Xu, H., D’Atri, A. and Hart, P., 2016. Individuals’ attitudes towards electronic health records: A privacy calculus perspective. In Advances in healthcare informatics and analytics (pp. 19-50). Springer, Cham.
Feldman, B., Martin, E.M. and Skotnes, T., 2015. Big data in healthcare hype and hope. October 2012. Dr. Bonnie, 360.
Li, Z., Dai, Y., Chen, G. and Liu, Y., 2016. Toward network-level efficiency for cloud storage services. In Content Distribution for Mobile Internet: A Cloud-based Approach (pp. 167-196). Springer, Singapore.
Madden, J.M., Lakoma, M.D., Rusinak, D., Lu, C.Y. and Soumerai, S.B., 2016. Missing clinical and behavioral health data in a large electronic health record (EHR) system. Journal of the American Medical Informatics Association, 23(6), pp.1143-1149.
Malyzhenkov, P. and Ivanova, M., 2017, June. An Enterprise Architecture-Based Approach to the IT-Business Alignment: An Integration of SAM and TOGAF Framework. In Workshop on Enterprise and Organizational Modeling and Simulation(pp. 159-173). Springer, Cham.
Malyzhenkov, P.V. and Ivanova, M.I., 2017. An architectural approach to IT-business alignment. BIZNES INFORMATIKA-BUSINESS INFORMATICS, 41(3), pp.56-64.
Meeks, D.W., Smith, M.W., Taylor, L., Sittig, D.F., Scott, J.M. and Singh, H., 2014. An analysis of electronic health record-related patient safety concerns. Journal of the American Medical Informatics Association, 21(6), pp.1053-1059.
Raghupathi, W. and Raghupathi, V., 2014. Big data analytics in healthcare: promise and potential. Health information science and systems, 2(1), p.3.
Reiss-Brennan, B., Brunisholz, K.D., Dredge, C., Briot, P., Grazier, K., Wilcox, A., Savitz, L. and James, B., 2016. Association of integrated team-based care with health care quality, utilization, and cost. Jama, 316(8), pp.826-834.
Seay, C., Agrawal, R., Kadadi, A. and Barel, Y., 2015, April. Using hadoop on the mainframe: A big solution for the challenges of big data. In Information Technology-New Generations (ITNG), 2015 12th International Conference on(pp. 765-769). IEEE.
Stonová, M., 2014. Unstructured Data in Healthcare. International Journal on Biomedicine and Healthcare, 2(1), pp.34-36.
Varia, J. and Mathew, S., 2014. Overview of amazon web services. Amazon Web Services.
Wager, K.A., Lee, F.W. and Glaser, J.P., 2017. Health care information systems: a practical approach for health care management. John Wiley & Sons.
Wittig, M. and Wittig, A., 2016. Amazon web services in action(p. 424). Manning.
Xhafa, F., Li, J., Zhao, G., Li, J., Chen, X. and Wong, D.S., 2015. Designing cloud-based electronic health record system with attribute-based encryption. Multimedia Tools and Applications, 74(10), pp.3441-3458.
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