Respond to at least two of your colleagues* on two different days, by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks.
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Respond to at least two of your colleagues* on two different days, by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks.
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Big Data Risk and Rewards
In understanding the concept of Big Data it is necessary to understand the foundation of informatics, which involves the use of Raw data from which information can be acquired and knowledge derived (Laureate Education, 2018). As nurse leaders big data is the collection of data sets from this data information is derived then organized in a manner in which it is meaningful and from this information nurse leaders are able to derive analytical data which is useful for decision making, by the relevant users of the information or the organization to help in accomplishing its goals (Thew, 2016).
The benefits to be derived from Big data are numerous. Data that is processed in a Big data technological use initially are either in the form of semi-structured or structured forms which are converted into data which will support decisions that are made within the organization.
Patients admits and discharges over a time interval can be used in deciding staffing needs in the long run for the organization. Sound decision made can lead to cost reduction for the organization (Wang, et al., 2018). Another benefit of Big data is the optimization of operation, this is accomplished by synthesizing all the information, where it is meaningful to users of the information. Data that is processed from Big data system which was originally in a semi-structured form after organization will enable users to have a consistent flow of information and traceability (Wang, et al., 2018). The goal of Big data within the healthcare system is an easier technological communication between networks, organization or facilities that support evidence-based decision making and actions. The benefits from the use of Information technological system is the improvement of quality, accurate clinical information which will help health care providers and other users to give an efficient patient centered care (Wang, et al., 2018). Data will also be transferable quickly across health care systems that will aid treatment processes.
Initially, the use of Big Data can be cumbersome and time consuming and a system must be implemented to aid in organization and decision- making process. The initial process involves analyzing data which can be very time consuming as most of the data may have to be gathered from paper sources. It requires the use of more than one person to organize and gather the necessary information. With Big data, data is obtained from all departments and can be frustrating, particularly when different terms and jargons may be used by the various departments for example human resource, social workers, and clinical staff may have to meet to discuss differences in communication to understand the system and to make it feasible for all who will utilize the relevant information (Wang, et al., ).This can be mitigated by meetings, discussions, e-mails and a dynamic communication routine by department heads and staff members. IT expertise, have to be a major part of the process of Big data in terms of education of staff members.
Reference
Laureate Education (Producer). (2018). Data-Information- Knowledge-Wisdom (Video File).
Baltimore, MD: Author.
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse executive.
Retrieved form https://www.healthleadersmedia.com/nursing/big-data-means-big-
Potential-challenges-nurse-execs
Wang, Y. Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities
and potential benefits for health care organizations. Technological Forecasting and
Social Change, 126(1). 3-13. Doi:1016/jtechfore.2015.12.019.
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The utilization of big data creates the possibility to reduce expenses in a clinical system’s services. For example, readmission of patients increases costs to the health system and decreases hospitals’ reimbursement if readmission occurs within 30 days from discharge. Medicare is the primary source of payment for hospitals. Medicare has the Hospital Readmission Reduction Program (HRRP) that encourage hospitals to reduce readmissions. The program was initiated through the Affordable Act Care in 2013 (Center for Medicare & Medicaid Services). Patients who are readmitted to the same hospital or another applicable acute care hospital for any reason. Hospitals or clinical settings reducing readmission will optimize their costs with the patient. The payment adjustment factor is a weighted average of a hospital’s performance across the six HRRP measures during the three-year HRRP performance period.
Data collection has generated enormous opportunities for clinical applications. For example, routine care and insurance claims. Data interpretation using analytical skills improves efficiency and quality, resulting in better healthcare practices and improved patient outcomes (McGonigle, and Mastrian, 2018).
Systems are developed to increase the number of resources for interpreting outcomes from the treatment of medication. The availability of the data does not translate into or clinical practice. At least, in a short period. Many times causal relationships of medication and treatment with the expected outcome are not conclusive as knowledge. To become a standard of caring requires validation by regulators, which take an extended period. For a medication to be available to patients takes typically five years, independently to big data as a source of information.
Thew (2016) declared, “to ensure big data is used to influence outcomes that are meaningful to the nursing profession; nurses executives need to act as data visionaries and architects.” However, care delivery can be optimized by improving communication with the patient in the discharge plan to reduce readmission. A follow up system by telehealth has brought improvement for medication compliance. For example, at the hospital that I work, the data related to readmission of patients demonstrated that a significant number of patients stop taking their medication or failure to be in compliance after one week of being discharged. A follow-up by telehealth one week after discharge to reinforce medication compliance reduced a patient’s readmission within 30 days from the date of release. A nurse informaticist interpreting data could make more inferences and extend the time for patients to be readmitted. For example, telehealth helps with medication compliance and helps with reinforcing coping skills through mechanisms learned at the hospital.
References
Center for Medicare & Medicaid Services (n.d.). Hospital Readmission Reduction Program. Retrieved from https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/HRRP/Hospital-Readmission-Reduction-Program
McGonigle, D., and Mastrian, K. G. (2018). Nursing Informatics (4th ed.). Jones & Bartlett.
Thew, J. (2016). Big data means big potential, challenges for nurses execs. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse- execs
