Sharing Patient Data in Diabetes - Essay Example

? Sharing patient data in diabetes. al affiliation: The global village is facing a pandemic of diabetes mellitus. Collaborative efforts are needed to combat against the pandemic. Data sharing and management of health care institutes have resolved the issue related lack of data. Interoperability has enhanced the patient care and efficient research against diabetes and other health related disorders. But, diabetes data sharing and interoperability is associated with some critical issues including privacy and security of data and data management system, interface problems and usage of legacy systems. Usage of legacy systems hinders the way of interoperability due to its diverse nature and incompatibility with the international standard system. The above-mentioned problems are significant to be resolved, to ensure an efficient data sharing in the health care field especially for the diabetes. This will help in the propagation of effective measures and data registries can be utilized worldwide. Sharing patient data in diabetes. Pandemic of diabetes has hit hard all the nations throughout the globe. According to National Diabetes Information Clearinghouse (2011), 8.3 percent of the United States’ population is suffering from the misery of diabetes, and is a seventh leading cause of death in the United States. This multi-factorial disease calls multi-sectorial management throughout the patients’ life. Need for the long-term judicious management of the disease, in favor of a quality of the patient’s life, brought the clinicians, of all nations, close together to find the way out of this problem. The data sharing strategy has done a lot to empower the research work in the field of Diabetology and is considered an efficient effort to find the solution of diabetes burden (Hurlbert, 2002). Data sharing among different institutions is quite a challenging approach because of different operational definitions, dissimilar legacy systems to store and manage data, disparate variables and linguistic issues (Jones et al., 1998). Data sharing among different settings require standardization, to remove the bias among the data provided by different health centers. Standardization has been efficiently provided by HL 7. Health level 7, a non-profitable organization, developed in 1987 and is now well-recognized by various nations, including America, Canada, Turkey, Australia, Germany, India, and Pakistan, as an efficient tool for health information system. Health level 7 aimed to ensure integrated, international health care data sharing and management by removing technology bias, linguistic barrier and other disparities in data storage and management (“Introduction to HL7 Standards,” n.d.) HL 7 works on the principal of standardization involving standardization of concept, document, application and messages. HL 7 standards include version 2x messaging standards, version 3 messaging standard, Arden syntax, claims attachment, etc. Through Health Level 7, data is transferred in the form of messages, and messages include patients’ records, progress reports, laboratory assays, clinical orders, etc. Transmission of diabetes data involves message development and shared information model that permits easy storage, transmission and retrieval of data. Messages are standardized, authorization is provided and security system is applied before data storage and sharing. Data can only be entered after authorization; once the relevant clinical data is entered into the electronic patient record system; MESSAGE CONSTRUCTOR transforms the message into XML version. XML version messages are user friendly and are technically supported by user software. VERSION MESSAGE SIGNER signs every message and transmits it to the receiver, in a serial order. Sequentially, validation of received XML message is done through SIGNATURE VALIDATOR, which ensures the compatibility of the data structure. Validated messages are interpreted by MESSAGE PARSER and, are stored into the data storage system. After storage, data can be shared with patients and other authorized recipients. Above mentioned technical procedure is involved to share relevant information among diabetologist, dietician, laboratory, pharmacy and diabetic patients. Standardization through an observation of a single system is required to be followed throughout the world to maintain interoperability, which simply means that data of one institution can be viewed and utilized unerringly and professionally on another location (Heubusch, 2006). Data sharing interoperability is economically sound to promote patient care especially in long-term diseases like diabetes. The major challenge for the provision of data sharing interoperability is the use of dissimilar technologies for data storage or using the software, not supporting the structure of another’s files. Interfacing issues lead to breaches in interoperability. This leads to problems in data transfer, retrieving and its interpretation. For an effective use of health care data, its accuracy is mandatory. During the diabetic data sharing, accuracy and updating of a data is also a major issue. No system is available to ensure that the data are up to date and are accurate. All the health care systems are not included in data sharing so; a useful data might be slipped off from the data storage system. Moreover, diabetes is a disease which remains silent for a long period, so cases are not detected and the incidence data, at the point, is usually not very accurate. The privacy of patients’ data is a big challenge of data sharing interoperability. This challenge of data storage costs a lot in terms of data accuracy. No doubt, data exchange and interoperability has bestowed a great deal of facility in the research work and patient care area, but interoperability has posed a major threat to the security of the data and many cases of sensitive data leakage have been reported. Not only the data are exposed to threats, but the e-data management system of an organization is also vulnerable to be hacked. Through defaults in the e-security system, the whole data in a system can be damaged or misused. Another challenge for interoperability is the use of legacy systems. Legacy systems are the old methods, in terms of hardware and software, to store and manage data. Usage of legacy systems for the health care data management interrupt in data sharing because they are mostly based on out-dated systems and their incorporation into the new software is complex and sometime, impossible. Legacy systems are not based on international standards, so data stored in them are not accurate and can only be used by local authorities. This generates gap in the availability of international health care data, so interoperability of the data is impossible. Wide variation exists between legacy systems of diabetes and other health care data storage and data transfer is difficult due to inappropriate data structure, disparities in file types, coding differences and interface problems. Adaptation of electronic data storage for diabetic patients has improved quality of patients care throughout the world (Richesson, 2011), and is a cost effective method of data collection for active research process in the field of diabetes and other health related troubles. But, more recent changes in the data management system are required to stop the evils associated with the data sharing. Authentication, Security enhancement and firewall mechanisms should be incorporated to guarantee the data security. Besides protecting the data, it will encourage more health care systems to deploy the data for international use. Reference: National diabetes statistics, 2011 - National diabetes information clearinghouse. (2011). National Diabetes Information Clearinghouse Home. Retrieved from http://diabetes.niddk.nih.gov/dm/pubs/statistics/#fast Hurlbert, M. (2002, May 31). Data sharing: Perspective of the juvenile diabetes research foundation international. Science Careers, from the journal Science. Retrieved from http://sciencecareers.sciencemag.org/career_magazine/previous_issues/articles/2002_05_31/noDOI.6320029328761163964 Jones, P. C., Silverman, B.C., Athanasoulis, M., Drucker. D., Goldberg, H., Marsh, J., Nguyen, C., Ravichandar, D., Reis, L., Rind, D., & Safran, C. (1998). Nationwide telecare for diabetics: a pilot implementation of the HOLON architecture. Proceedings of the AMIA Symposium, 346-350. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/9929239 Introduction to HL7 standards. (n.d.). Health Level Seven International - Homepage. Retrieved from http://www.hl7.org/implement/standards/index.cfm?ref=nav Heubusch, K. (2006). Interoperability: What it means, why it matters. Journal of AHIMA77, 1, 26-30. Richesson, R. L. (2011). Data standards in diabetes patient registries. Journal of Diabetes Science and Technology, 5(3), 476-485. Read More