Data analysis technology has proved to be vital to the healthcare industry, patient care and medical research, despite its popularity in retail marketing, manufacturing, stock and financial transactions.
Big data is already used to find appropriate participants for clinical trials that meet the study criteria. Data is also used to predict how patients can respond to specific medicines for modelling purposes.
The most effective treatment pathway can be identified for patients based on the collective knowledge of what worked for similar people in the past by collecting information from millions and billions of patients of different unusual characteristics.
However, more intelligent monitoring devices communicating with other patient devices may greatly enhance this process, which may lower the need for direct doctor procedure and might be replaced by a phone call.
Big data analytics are intended only for the purpose of investigating a wide range of data and discovering hidden models, new correlations, market trends, preferences, and patient care. Some of the potential advantages of large data include cost savings and the inclusion of entire populations with robust samples eliminating possible sample distortions.
The large data reaches a speed not controlled by the investigator and has an inaccuracy level not found in the traditional investigation. Big data is typically collected for different purposes.
Big Data offers a variety of benefits in the Nursing Sector, some notable ones have been listed below.
Nurses are on the front lines when it comes to the recording and storage of information. Data capture starts when a patient registers in the health care group and continues through the history of oral medicine, blood drawings and each other step of the care episode.
The mass quantities of data generated by all organisations, and even throughout the country, are valuable for the improvement of care and best practice within a group, from test results to billing codes, and regularly record, verify, or leverage nursing information on all levels.
Another area of nursing practice affected by Big Data is to ensure adequate levels of personnel. Schedules change continually, and demand based on the number of patients and their needs fluctuates with personnel requirements.
When a team is short, employees in most industries will do their best to make it work and, possibly, deal with all the effects. If a nursing team is short on staff, life or death can be the case literally. Big data can enhance the efficiency of nursing leaders to determine how many personnel they need at any time.
Knowing future patient demand to ensure accurate planning and staffing by healthcare providers is an invaluable advantage for medical establishments. This information can, fortunately, be available and used to plan and manage the workforce.
(Related blog : What is Healthcare data analytics?)
Role of Big Data in nursing practice
When care is given to patients, the nurses want the best possible treatment strategy for their decisions. Big data facilitates the determination of the best practices and makes sure that they are used in the organisation. Research has shown there are several positive benefits to implementation of evidence-based best practices in clinical attention such as:
Improves patient outcomes
Reducing procedures that are unnecessary.
Improved safety for patients.
This principle has also an impact on nursing education and research to maximize time and other resources through best and most effective practices.
With big data, nurses can use data analysis to determine which way patients can be treated most efficiently, from documenting their visits to the most efficient means of working on a unit. Such analysis provides strong information for the development of guidance and legislation at the federal and national levels and for the determination of the operation of individual organizations.
Providers can streamline workflows, including clinical documentation, quality reporting, analysis, and monitoring, for primary and specific care. A healthcare organization can target overall effectiveness with EMR solutions, depending on its needs, or can target its most costly, high-risk fields such as acute care, cardiology or child care.
Big data can also be used to analyze workflows, which will enable nurses to have the confidence to decide how to best take care of patients.
Big data creates fresh opportunities for nurses, as well as improving existing practices. The focus on collecting and using data from systems such as EHRs can be seen in traditional positions. Let's see just a few new roles that create new nursing opportunities:
Nurse informaticists: The role of the nursing informaticist combines nursing practice with Information and communication technology to enhance care for patients. Caregivers also help shape health information technology practices and policies in health care organizations.
Chief nursing informatics officers: The Chief Information Technology Officer plays an emerging role in the health care executive suite for nurses. The CNIO acts as a connection between nurses and IT efforts, ensuring that regulatory changes are always met.
Clinical nurse leaders: Although the clinical nurse leader is not a new position, the introduction of big data led to developments. Patients wishing to advance to this role will benefit from their background in computer science and other fields of data use in the clinical field.
Recommended blog: 5 Applications of AI in clinical trials
Nursing documents are not always sharp and comparable to the rest of the care team in some care settings. Failure to standardize is challenging for comparing data. It is important that the data is standardized in order for sharp, comparable information to be possible.
Health data are generated at unbelievable rates and the data interpreting tools have not kept pace. There are still powerful tools to curate data and analyze data. The absence of common data definitions, shared documentation practices, and standard assessment tools hinder the use of big data at macro levels.
Since the aim is to achieve not only interoperable but also secure and standardized health data exchanges. Most EHR's are of a high dimensional nature and sparse population in several hospitals, which is a big problem when analyzing such data sets.
The quality of data and veracity of insights are other challenges. Visual representations that play an essential role in assisting nurses only prove a useful tool if the quality of the data is guaranteed.
Although the nursing community is not unique to some of these Big Data challenges, addressing them improves the community's collective knowledge and leads to activities that improve the quality of all areas of care.
(Also read: IoT in HealthCare)
Big data is the future—a future that requires critical thinking and the capability to evaluate data in order to ensure good decision making, "Simpson says. "In order to be able to focus on data through the specific lenses of nursing education, the nurses have to be part of this increasingly interdisciplinary process.
Health organizations expect big data and analytics to reduce the rising healthcare costs and improve the quality of care. There is now a real opportunity to take advantage of the huge amount of data on health and care that are captured and stored.
Health organizations take more risks with their patient populations, so they need more information on how well they perform, including their ability to identify patterns and decide which therapies are most effective for which patients.
Big data offers tremendous opportunities to accelerate the growth and synthesis of new knowledge to make a positive impact on nurses and the individuals and populations they serve.
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