Improvements through Interoperability and Exchange
Part of the premise behind big data, analytics and informatics, is the notion that they can be used to improve upon our current healthcare landscape. By identifying and reviewing relevant data, trends and deviations can be quickly recognized. This in turn helps businesses, physicians and patients efficiently enhance the domains in which they operate. I would like to use a study I read to illustrate what I mean by this. The topics of discussion will consist of a brief summary of the study, followed by contrasting that information against current industry standards, a quick look into whether or not these practices could apply to my organization and finally, what the implications are of adopting these new methods.
Summarization
The focus of the article I read centered around the difficulties encountered when dealing with the issue of interoperability. Specifically, this is in reference to how multiple vendors and networks address the problem of safely and securely transmitting a patient’s electronic health record (EHR). If you are wondering what informatics and big data consists of, consider it “the field that concerns itself with the cognitive, information processing, and communication tasks of medical practice, education, and research” (Reiner, 2011, p. 177).
In this study, according to The Office of the National Coordinator for Health Information Technology (n.d.), seven vendors; GE, Vitera, Cerner, SuccessEHS, NextGen, Allscripts and Greenway worked on the three main interoperability elements of record sharing by: defining the highest priority data used in the widest array of cases, conducting a technological assessment of EHR vendor production capabilities, and then developing a Continuity of Care Document (CCD) that was reached by consensus for 45% of the market in an effort to uphold the results of the findings.
By capturing and analyzing this data, these vendors were able to ensure EHR systems reduced information barriers to create a more standardized experience for data movement. Additionally, in an effort to minimize market inefficiency, more relationships have been brokered between providers and IT vendors to avoid incomplete and inconsistent data exchanges. Finally, by correcting the inability to reliably transmit clinical data, a reduction in unnecessary delivery costs has been realized, making it easier to pass those savings on to patients (The Office of the National Coordinator for Health Information Technology, n.d.).
Contrasting with Current Industry Standards
I do not want to imply that Big Data is an infallible science. The case study I used took place in 2012, which means we should see how that compares with current practices. We must understand that while it is certainly useful, “big data is prone to error and its application can result in misleading conclusions if the data set is filled with artifacts – deficiencies caused by flaws in equipment, technique, observation or data collection” (Otokiti, 2019, p. 426).
One of the major differences that has taken place is the shift on what is important for the concept of interoperability. “The healthcare sector is rapidly moving to the post-EHR era. The value of patient data is not in the data silos of EHRs but in the network that an HIE supports” (Chilmark Research, 2020, para. 5). Plainly put, the onus has moved from the matter of storage to a matter of connectivity.
Viability within the USAF
The question remains; is this practice something that could see use in my organization? Although my position is somewhat unique as a Magnetic Resonance Imaging technologist in the active duty component of the United States Air Force, the answer is a resounding yes. In fact, this has been standard practice for some time. To appropriately react and prepare for any contingency, we often utilize these networks to transfer imaging data offsite to avoid delays in diagnosis. This requires frequent and extensive use of exchange environments to be certain we are not creating a breach of data.
There has been a push as of late to begin the process of standardization across all facilities and DoD branches, with the goal of minimizing the interoperability issues brought forth in the earlier case study. “Information is critical to patient-centered care, and the field of health informatics has evolved in recent years to focus on how information is acquired, stored, and used in healthcare, with a particular emphasis on technology” (Snyder, Wu, Miller, Jensen, Bantug & Wolff, 2011, para. 5). This concept naturally aligns with Air Force tenets and as such integrates easily with our core mission constructs.
New Practice Implementation
However, one of the persisting roadblocks in overcoming these challenges lies in the plethora of vendors and equipment, as well as the money involved to consolidate those across entire networks and facilities. There will always be the added issue of employee pushback regarding the training required to learn how to use a new system, especially if they do not understand the reason behind the changes. While this is a transition that relies on careful navigation, putting these concepts into practice brings about significant benefits as well.
Again, using informatics as a frame of reference shows that the standardization of interoperability systems was met favorably by physicians who believed this was directly responsible for enhancing the quality of patient care (80%), bolstered the ability of care coordination (80%) and showed the flexibility needed to positively impact the growing field of medical home care (78%) (The Office of the National Coordinator for Health Information Technology, n.d.). Though these are astronomical numbers, please understand the context from which they were gathered so as to avoid falling into the trap of poor data collection I mentioned earlier.
Conclusion
All said, this should have helped clarify what big data is and how it is used. You can see how the paradigm has shifted over the years with the belief the interoperability is vital for improving both care and coordination. There is an on-going concentrated effort to diminish the effects of incompatible systems across vendor specific platforms, something I see daily used in my line of duty. Though implementation of these standards may initially be met with resistance, there is enough data on hand to suggest it is a venture worth pursuing.
References:
Otokiti, A. (2019). Using informatics to improve healthcare quality. International Journal of Health Care Quality Assurance, 32(2), 425–430. Using informatics to improve healthcare quality | Emerald Insight
Chilmark Research. (2020). 2012 HIE market report. Retrieved from At Last, It's Here: 2012 HIE Market Report | Chilmark Research
Dunham, D.T. (2020). Cafepharma. Retrieved from Henrietta Lacks and Medical Ethics
Reiner, B. I. (2011). Improving healthcare delivery through patient informatics and quality centric data. Journal of Digital Imaging, 24(2), 177–178. https://doi.org/10.1007/s10278-011-9363-4
Snyder, C. F., Wu, A. W., Miller, R. S., Jensen, R. E., Bantug, E. T., & Wolff, A. C. (2011). The role of informatics in promoting patient-centered care. Cancer journal (Sudbury, Mass.), 17(4), 211–218. The Role of Informatics in Promoting Patient-Centered Care
The Office of the National Coordinator for Health Information Technology. (n.d.). HealthIT.gov. Retrieved from Vendors and Communities Working Together: A Catalyst for Interoperability and Exchange | HealthIT.gov
Part of the premise behind big data, analytics and informatics, is the notion that they can be used to improve upon our current healthcare landscape. By identifying and reviewing relevant data, trends and deviations can be quickly recognized. This in turn helps businesses, physicians and patients efficiently enhance the domains in which they operate. I would like to use a study I read to illustrate what I mean by this. The topics of discussion will consist of a brief summary of the study, followed by contrasting that information against current industry standards, a quick look into whether or not these practices could apply to my organization and finally, what the implications are of adopting these new methods.
Summarization
The focus of the article I read centered around the difficulties encountered when dealing with the issue of interoperability. Specifically, this is in reference to how multiple vendors and networks address the problem of safely and securely transmitting a patient’s electronic health record (EHR). If you are wondering what informatics and big data consists of, consider it “the field that concerns itself with the cognitive, information processing, and communication tasks of medical practice, education, and research” (Reiner, 2011, p. 177).
In this study, according to The Office of the National Coordinator for Health Information Technology (n.d.), seven vendors; GE, Vitera, Cerner, SuccessEHS, NextGen, Allscripts and Greenway worked on the three main interoperability elements of record sharing by: defining the highest priority data used in the widest array of cases, conducting a technological assessment of EHR vendor production capabilities, and then developing a Continuity of Care Document (CCD) that was reached by consensus for 45% of the market in an effort to uphold the results of the findings.
By capturing and analyzing this data, these vendors were able to ensure EHR systems reduced information barriers to create a more standardized experience for data movement. Additionally, in an effort to minimize market inefficiency, more relationships have been brokered between providers and IT vendors to avoid incomplete and inconsistent data exchanges. Finally, by correcting the inability to reliably transmit clinical data, a reduction in unnecessary delivery costs has been realized, making it easier to pass those savings on to patients (The Office of the National Coordinator for Health Information Technology, n.d.).
Contrasting with Current Industry Standards
I do not want to imply that Big Data is an infallible science. The case study I used took place in 2012, which means we should see how that compares with current practices. We must understand that while it is certainly useful, “big data is prone to error and its application can result in misleading conclusions if the data set is filled with artifacts – deficiencies caused by flaws in equipment, technique, observation or data collection” (Otokiti, 2019, p. 426).
One of the major differences that has taken place is the shift on what is important for the concept of interoperability. “The healthcare sector is rapidly moving to the post-EHR era. The value of patient data is not in the data silos of EHRs but in the network that an HIE supports” (Chilmark Research, 2020, para. 5). Plainly put, the onus has moved from the matter of storage to a matter of connectivity.
Viability within the USAF
The question remains; is this practice something that could see use in my organization? Although my position is somewhat unique as a Magnetic Resonance Imaging technologist in the active duty component of the United States Air Force, the answer is a resounding yes. In fact, this has been standard practice for some time. To appropriately react and prepare for any contingency, we often utilize these networks to transfer imaging data offsite to avoid delays in diagnosis. This requires frequent and extensive use of exchange environments to be certain we are not creating a breach of data.
There has been a push as of late to begin the process of standardization across all facilities and DoD branches, with the goal of minimizing the interoperability issues brought forth in the earlier case study. “Information is critical to patient-centered care, and the field of health informatics has evolved in recent years to focus on how information is acquired, stored, and used in healthcare, with a particular emphasis on technology” (Snyder, Wu, Miller, Jensen, Bantug & Wolff, 2011, para. 5). This concept naturally aligns with Air Force tenets and as such integrates easily with our core mission constructs.
New Practice Implementation
However, one of the persisting roadblocks in overcoming these challenges lies in the plethora of vendors and equipment, as well as the money involved to consolidate those across entire networks and facilities. There will always be the added issue of employee pushback regarding the training required to learn how to use a new system, especially if they do not understand the reason behind the changes. While this is a transition that relies on careful navigation, putting these concepts into practice brings about significant benefits as well.
Again, using informatics as a frame of reference shows that the standardization of interoperability systems was met favorably by physicians who believed this was directly responsible for enhancing the quality of patient care (80%), bolstered the ability of care coordination (80%) and showed the flexibility needed to positively impact the growing field of medical home care (78%) (The Office of the National Coordinator for Health Information Technology, n.d.). Though these are astronomical numbers, please understand the context from which they were gathered so as to avoid falling into the trap of poor data collection I mentioned earlier.
Conclusion
All said, this should have helped clarify what big data is and how it is used. You can see how the paradigm has shifted over the years with the belief the interoperability is vital for improving both care and coordination. There is an on-going concentrated effort to diminish the effects of incompatible systems across vendor specific platforms, something I see daily used in my line of duty. Though implementation of these standards may initially be met with resistance, there is enough data on hand to suggest it is a venture worth pursuing.
References:
Otokiti, A. (2019). Using informatics to improve healthcare quality. International Journal of Health Care Quality Assurance, 32(2), 425–430. Using informatics to improve healthcare quality | Emerald Insight
Chilmark Research. (2020). 2012 HIE market report. Retrieved from At Last, It's Here: 2012 HIE Market Report | Chilmark Research
Dunham, D.T. (2020). Cafepharma. Retrieved from Henrietta Lacks and Medical Ethics
Reiner, B. I. (2011). Improving healthcare delivery through patient informatics and quality centric data. Journal of Digital Imaging, 24(2), 177–178. https://doi.org/10.1007/s10278-011-9363-4
Snyder, C. F., Wu, A. W., Miller, R. S., Jensen, R. E., Bantug, E. T., & Wolff, A. C. (2011). The role of informatics in promoting patient-centered care. Cancer journal (Sudbury, Mass.), 17(4), 211–218. The Role of Informatics in Promoting Patient-Centered Care
The Office of the National Coordinator for Health Information Technology. (n.d.). HealthIT.gov. Retrieved from Vendors and Communities Working Together: A Catalyst for Interoperability and Exchange | HealthIT.gov