Correct prediction of risk and risk stratification is an important goal to guide clinical in the decision making and patient outcomes. (Moonesinghe, Ramani et al.2013) Living in the Big data era, created vast opportunities to build various prediction models. Analyzing the raw data and extracted information from various source of data could enable us in better clinical decisions and outcomes. In this project we analyzed the raw data from the Multi-Parameter Intelligent Monitoring in Intensive Care (MIMIC III) database. In exploring an approach to decision support based on information extracted from a clinical database, we developed attributable risk and risk stratification models of intensive care unit (ICU) patients.
The risk of ICU patients
...n Article Nielsen et al (2013) Diagnostic Accuracy hierarchy methods is applied which is review on second level (II) i.e. Randomised Controlled Trial and Meta-Analysis in the Pyramid level. These are also considered as gold standard in hierarchy of research design for evaluating the safety of a treatment. Also therapeutic study method is applied where different patients of age groups are used to treat with two different temperatures. There are two different trial methods used in this study. Here the level of hierarchy is high so that we can trust the result based on the data provided. We can also provide and opportunities to collect useful information about adverse affect such as temperature control over cardiac arrest. In the Meta-Analysis method multiple treatment groups are been treated with each other. There is also observational study performed in the article.
Jahi McMath is a 13-year-old girl living in Oakland, CA who was declared brain dead by multiple neurologists more than three months ago. Jahi was declared brain-dead December 12th after barriers during surgery a few days earlier to remove her tonsils, adenoids, and uvula at Children's Hospital & Research Center Oakland. At least three neurologists confirmed that Jahi was unable to breathe on her own, had no blood flow to her brain, and had no sign of electrical activity in her brain. Moreover, a court order kept Jahi's body on a ventilator while independent experts could be brought in to confirm the results (Wells, 2014). Even so, the McMath family was able to secure the release of Jahi's body through the county coroner, who issued a death certificate, and have been keeping her on a ventilator at an undisclosed facility ever since. This all occurred after Children’s Hospital released Jahi due to her severe brain damage along with the probability of the hospital receiving profit from discharging Jahi before her or her family were ready for her to be released (Johnson and Rhodes, 2010, p. 61).
The Kaplan–Meier estimator is a product limit estimator that is used for estimating the survival function from lifetime data [24]. The aim of this estimator is to estimate a population of patients’ survival curve from a sample. This estimator is used in addition to the Receiver-operator characteristic ROC curve to evaluate the performance of the prediction model [25-27]. Of course, if every patient is followed until death, the curve may be estimated simply by computing the fraction surviving at each time. However, in most medical studies patients tend to drop out, become lost to follow up, move away, etc. The Kaplan-Meier analysis allows estimation of survival over time, even when patients drop out or are studied for different lengths of time.
...the tools meet both CPA and Health of the Nation outcome scales requirement (DOH 2007). The Risk is assessed using the Face Risk Profile. This tool is really easy to use as it has Five sets of Risks indicators, these are then coded as present or absent and a risk status (0-4) is judged (DOH 2007). The problem with this assessment is that the patient would sometimes need to be involved and at present because of Julie’s presenting problems this would not be able to happen but parts of the Risk Profile can be filled in by the Nurse who is in charge of Julie care and wellbeing. The problem with the actuarial approach is that sometimes these tools may not give a conclusive answer to the problem. However many researchers would suggest that the use of both actuarial and clinical risk assessment would be better for a nurse to use to come up with an accurate risk assessment.
Healthcare providers must make their treatment decisions based on many determining factors, one of which is insurance reimbursement. Providers always consider whether or not the organization will be paid by the patients and/or insurance companies when providing care. Another important factor which affects the healthcare provider’s ability to provide the appropriate care is whether or not the patient has been truthful, if they have had access to health, and are willing to take the necessary steps to maintain their health.
Wiles, L.L. Simko, L.C. & Schoessler, M. (2013). What do I do now? Clinical Decision making
Many people are afraid to make decisions concerning their wishes when they die. This includes fear of making wills and making critical decisions that affect lives of others when they are not there. When the patients are terminally ill, they become incapable of making these decisions and they are often assisted or directed by some external forces to make these decisions. This paper exploits options and conditions of different terminally ill patients with a keen look at their mental and health status. It is also going to explore on those patients with DNR (Do not Resuscitate) orders and advance directives.
...2011). Risk assessment has evolved and research has shown that Structured Professional Judgement emerges as the most promising way forward in risk assessment, as it includes both static and dynamic risk factors, and combines statistical accuracy with clinical experience.
I use different strategies when I do clinical decision making especially working with birth to18-years-old, our physical therapy program alone will not provide a good clinical decision making skills. Besides our physical therapy program I take every year continuing education in my field (Pediatric) through online or onsite seminars. I learned a lot now, when compare to the beginning of my physical therapy carrier. Our learning is never going to stop especially in our heath care field and every day we learn something new in our field. When I was in college my principal used to tell us that after we finish our physical therapy program we should work under senior physical therapist for at least two years to gain more experience before working independently. In the beginning, I was not really comfortable working with babies. But now I want to work only with children not adults because I am very comfortable with children after learning them well. I am still learning and getting more experience with children every day. ever before.
Saluja, U., & Idris, N. B. (2012). Information Risk Management: Qualitative or Quantitative? Cross Industry Lessons from Medical and Financial Fields. Systemics, Cybernetics and Informatics, 10(3), 54-59.
Researchers work hard to eliminate bias from outcomes through approaches that diminish subjectivity and modification from unknown sources. Randomization, use of well-matched controls, and blinding of analysts and researchers are some ways to try to a...
[Cover: discussion about how risks are balanced during risk assessment, why this is a difficult task -> proposing a set of principles and practical measures that might assist both researchers and patients, to enable more informed decisions about risk]
An employee does an unsatisfactory job on an assigned project. Explain the attribution process that this person's manager will use to form judgments about this employee's job performance.
Decision making is the selection of a process to evaluate options and find a solution to a problem. The decisions making process can be one of the most difficult roles of working within a team. Although, certain situations will necessitate different approaches of decision making in order to be effective. Every decision-making process produces a final choice that best benefits the team. The solution to making better decisions is through recognizing and developing employee’s strengths (Sorenson, 2014). By applying the strengths based approach a manager can successfully develop an engaged and results driven employee.
Machine learning is a branch of artificial intelligence that aims at solving real life engineering problems. It provides the opportunity to learn without being explicitly programmed and it is based on the concept of learning from data. It is so much ubiquitously used dozen a times a day that we may not even know it. The advantage of machine learning (ML) methods is that it uses mathematical models, heuristic learning, knowledge acquisitions and decision trees for decision making. Thus, it provides controllability, observability and stability. It updates easily by adding a new patient‘s record.