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Predicting The Future Of Medical Health Records Essay

Predicting the Future of Medical Health Records Predict the form and function of medical health records in 2030 (provide specific example to support your response).

With the advent of digital databases used to store vast amounts of medical information, health histories, and vital statistics for millions of patients across America, a concept known on the local level as electronic medical recordkeeping (EMR), and collectively forming the electronic health record (EHR), the delivery of healthcare services has undergone a rapid transformation during the last two decades. The traditional clipboard and paper chart carried by physicians and nurses, which held an often indecipherable maze of pencil-etched recordings made throughout a patient's stay, has since been replaced in many modern healthcare facilities by the iPad and other handheld computer tablet devices. Banks of unwieldy filing cabinets, each storing hundreds of individual patient files, have vanished in the private practices and doctor's offices of America's healthcare providers, with a simple server system allowing for the storage of millions of files on a single hard drive. Through the implementation of advanced software systems, diagnostic tools have now become intuitive, scanning through a patient's entire archived medical record and searching for connections that may ordinarily escape the consideration of a single doctor handling dozens of cases concurrently.

Even with the array of tangible improvements made during the last decade by the adoption of EMR and EHR methodologies, many information technology experts believe the most influential advancements have yet to come, citing the almost exponential rate of diffusion to conclude that "under current conditions, EHR adoption will reach its maximum market share in 2024 in the small practice setting" (Ford, Menachemi & Phillips, 2006). One need only look to the telecommunications market to observe the rapid rate of change that technological advancement can exert on a previously...

The advantages afforded by wireless internet access, and the concept of server-less "cloud" computing which has evolved in its wake, appear to be the most likely innovation to effect EMR and EHR practices in the next two decades. Indeed, the use of cloud computing within the study of human genomics has demonstrated the clear advantages of this method of data storage and retrieval, with many experts stating that "alternative computing architectures, in particular cloud computing environments, may help alleviate this increasing pressure and enable fast, large-scale, and cost-effective comparative strategies going forward" (Wall et al., 2010). It stands to reason that, if the current rate of technological advancement and implementation holds steady through 2030, a modern hospital at that time would be completely interconnected with surrounding healthcare providers, allowing nurses and physicians to aggregate and interpret data from pharmaceutical prescriptions, medical check-ups, and other diagnostic data. At this time, cloud computing technology will have likely replaced traditional serve farms as the preferred mode of data storage, making the process of assessing a patient's health nearly instantaneous upon their entrance to the facility. For regular patients suffering from chronic conditions, the use of electronic bracelets or similar devices may allow the check-in process to be eliminated entirely, with patients walking through a scanner and having their pertinent data instantly transmitted to a waiting staff of nurses and physicians who are already familiarized with his or her symptoms.
2.) Describe the most likely impediments to health care information access in 2030 and make at least two (2) recommendations to avert those impediments that can be implemented now.

With any rapid technological advancement there will always…

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References

Ford, E.W., Menachemi, N., & Phillips, M.T. (2006). Predicting the adoption of electronic health records by physicians: When will health care be paperless?. Journal of the American Medical Informatics Association, 13(1), 106-112. Retrieved from http://jamia.bmj.com/content/13/1/106.abstract

Wall, P.T., Kudtarkar, P., Fusaro, V.A., & Pivoravov, R. (2010). Cloud computing for comparative genomics. BMC Bioinformatics, 11(259), Retrieved from http://www.biomedcentral.com/1471-2105/11/259
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