Devices useful to Patients
One of the devices that would be useful is a blood pressure measuring device. This device could be useful for patients who have either high or low blood pressure symptoms. The device helps the patients to monitor their blood pressure from home and hence they do not need o keep coming to the hospital for check ups. However, a hospital should also have enough of these devices such that the patients can always be monitored from there (Shimada, Kario, Kushiro, Teramukai, Zenimura, Ishikawa & Saito, 2016). It would be required and recommended that the patient, or the person taking care of them be trained on how to use these devices.
Another device that would be useful for patients required to monitor their condition at home is the Embletta device that can monitor apnoea/hypopnea syndrome. This device can help in the reduction of diagnosis costs, as he results that often come from it are usually accurate. In addition, the device can help reduce the waiting times for some of the patients who use it. After the monitoring, further medical advice and treatment should be the goal of the patients.
Other devices that are recommended and that should be used include tunnel central catheters. These are used mainly for monitoring the nutrition of the people who use them. The conditions that these people suffer from are mainly long term, hence the need for a device that a person can use and monitor from home. These devices have been in operation, especially in the European countries since the 1970s.
Another device that is recommended is the infusion pumps. These serve a similar purpose to the tunnel central catheters. Their use is highly recommended but is often not practiced. The reasons for the lack of practice include the availability of other devices. Another reason is that in most cases, the device is expensive and unavailable. However, the use of this device should be increased since it has a lot of benefits to the patients who may have conditions that require it.
Data analytics lead to improved outcomes
Data analytics often involve analyzing large cases of data from an area with a given population or from areas with different populations. The healthcare usually has a lot of data, due to the keeping of records at the various facilities. The need to analyze this data comes from mandatory requirements and also the realization that the analysis has the potential to improve healthcare in a number of ways. Due to advanced technology, most of this data is electronic in nature and can thus be analyzed electronically (Belle, Thiagarajan, Soroushmehr, Navidi, Beard & Najarian, 2015). This usually makes the analysis process easier. However, care has to be taken to avoid giving out patient specific information that could cause harm to the patients.
One of the ways in which the analysis of this kind of data proves to be helpful is in that it often shows the associations that exist between various types of diseases and illnesses. These are usually shown by the patterns in the patient’s location and their symptoms. Such discoveries often prove useful in giving prevention strategies and also in future identification of an illness or a disease (Belle, Thiagarajan, Soroushmehr, Navidi, Beard & Najarian, 2015). The data that is stored and analyzed in the United States has so far shown some of these results.
A good example of a case where data analytics have been helpful is in the case of public health. In my assessment, big data analysis has helped to detect diseases in their early stages. He symptoms of these diseases, especially when the disease is just about to show deeper symptoms or affect the person negatively are usually seen at this stage. Data analytics have been particularly useful in the case of tuberculosis, not just in the United States, but also in other parts of the world such as South Africa. With the electronic analysis, early signs, people at risk and prevention strategies have been seen and suggested.
Data fusion refers to the process by which multiple data is collected then represented using the same real-world object into a consistent and accurate representation. In the combat field, this technique is often used to determine some of the things that may affect the people in that field. From this technique, people working in that medical field are able to gauge and therefore come up with a good diagnosis for the people in this field (Goodman, Mahler & Nguyen, 2013). This diagnosis can then be used for the treatment of the individual or the different kinds of group.
In my opinion, this kind of data fusion and situational awareness is also needed in the medical field. The data can be collected from the mega electronic databases that are so widely spread nowadays. From this data, the people in the medical field can then use data fusion techniques to come up with accurate representations of the various ways in which various conditions present themselves in the bodies of different people. From this data, it can then be decided what kind of evidence based treatment is required for the individuals. He kind of analysis would also provide a good room for community health and community welfare when it comes to health
Another advantage is that this method allows for some relationships between illnesses in individuals to be observed. These relationships can then be used for development of further data and for the use of predicting illnesses early. From this, robust populations can be treated and taken care of without much struggle.
Six sigma analytics
One of the key concepts behind the six sigma analytics is in the kind of data that is used in it. The six sigma analytics often focuses on improving the kind of data and methods. It can be termed as a kind of predictive methodology rather than an analysis and research tool (Pyzdek & Keller, 2014). Usually, the predictions from this say what a person could possible do depending on the data and the situation and therefore give a guideline on what best to do in different situations.
Based on that nature of the six sigma analytics method, it is good to say that the method should not be used. Instead, companies, especially medical companies should strive for the use of bigger data in their company as it is often more helpful. The choice of objectives in the six sigma method also proves to be problematic. In the case of six sigma, the main objective often is to predict the kind of action to take. This should not always be the case. Better objectives could be improvement and better analysis. Six sigma does not give room for this kind of prediction
The six sigma method also seems to be only designed to give the data that one is looking for. It avoids deeper analysis and the use of more sophisticated methods. In addition to this, the process often leads to only the measurements of the systems and not their analysis. Working as a predictive method often proves problematic and this could lead to inaccurate data and inaccurate predictions. Finally, the design often shows the constraints of a design that are common with any design. The data may be accurate but the design does not allow much manipulation and thus the data is predictably obvious based on the design.
Belle, A., Thiagarajan, R., Soroushmehr, S.M., Navidi, F., Beard., D. A., & Najarian, K. (2015) Big Data Analytics in healthcare. Biomed. Research International, 2015
Goodman, I.R., Mahler, R.P., & Nguyen, H. T. (2013). Mathematics of data fusion (Vol. 37) Springer Science & Business Media
Pyzdek, T., & Keller, P. A. (2014) The six sigma handbook (p.25) McGraw-Hill education.
Shimada, K., Kario, T., Teramukai, S., Zenimura, N., Ishikawa, Y., &Saito, I. (2016). Prognostic significance of on-treatment home and clinic blood pressure for predicting cardiovascular events in hypertensive patients in the HONEST study. Journal of Hypertension, 34(8), 1520-1527
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