NURS 6401 week 5 Discussion Essay
Informatics and Healthcare
The adoption of health informatics has revolutionized the healthcare industry by enhancing the quality of care and reducing cost of operation. There is no doubt that healthcare providers bear large costs when investing in health informatics. However, the costly investment in health informatics often pays through a number of benefits that providers realize after implementing health information systems such as electronic health records (Shekelle, & Goldzweig, 2009). There are many costs saving benefits that healthcare providers can achieve by implementing health informatics. A wealth of the literature indicates that health informatics cut on costs that health providers incur (Shekelle, & Goldzweig, 2009; Encinosa, & Bae, 2011). By using heath informatics, care providers can cut down their operating budget by reducing employees employed, limiting waste of drugs, reducing the amount of stationery used, and limiting medical errors. Health informatics is responsible for significant reduction in cost involved in the purchase of stationery, which lowers the operating budget.
Health informatics can reduce the cost of purchasing stationery in hospitals and other healthcare facilities. This is because health informatics offers care providers with a paperless environment, which reduces the amount of stationers necessary. While unknown to many people, many healthcare providers budget significant amount of money for the purchase of stationery (Jonietz, 2003). This is because care providers understand the many processes that require stationery for providers to meet the needs of healthcare consumers, but health informatics can reduce these costs tremendously.NURS 6401 week 5 Discussion Essay
First, health informatics can reduce the amount of money spent in purchasing stationery for writing appointments and scheduling. With the use of health informatics, care providers can use electronic appointment and scheduling system tools that will reduce unnecessary cost of purchasing this stationary. This cost saving can help reduce a significant amount of money from the operation budget of the hospital.
In addition, health informatics can also reduce the number of stationery that providers require to admit patients and store their information. A huge portion of funds enables care providers to purchase stationary for admitting patients and storing their information (Jonietz, 2003). Such purchases bloat the operating budget, but health informatics can reduce it considerably. For instance, patient admission and storage of information using personal health records can reduce the need of stationery. This will translate to enormous cost saving for providers with health information systems.
Stationery used in charting patient information is also another target for cost reduction in a paperless environment. In a tradition healthcare environment, clinicians require a lot of paper work to chart patients’ information (Jonietz, 2003). The more the paper needed, the more the cost that providers experience. Although this cost is high, health informatics, provide clinicians with electronic means to chart patients’ information and write comments, as well. This strategy has the potential of reducing cost of stationery that providers require.
Laboratory test and dispensing of drugs make use of many paper records, which cost a lot of money. However, the use of health information can reduce the number of paper records since physicians can use electronic means to store information and prescribe orders (Jonietz, 2003). This means that care providers can reduce costs they incur in purchasing stationery.
In conclusion, heath informatics lowers the costs for healthcare providers. Most importantly, it cuts down on the amount of stationery that healthcare providers use in providing care and achieving other administrative function. Through a paperless environment, health informatics allows care providers lower to considerably their operating budget.
In the field of medicine and nursing, there are plenty of situations when doctors or nurses have to make decisions, prescribe medicines or define diagnosis when there is no sufficient information for selecting a certain variant, or where some factors are unknown. In such situations medial professionals rely on their experience and intuition. However, such decision-making process is quite risky, because human beings might make mistakes, forget something, may not operate large amounts of data quickly etc. Such human factors may influence health and life of the patients.NURS 6401 week 5 Discussion Essay
In order to help doctors, nurses and other medical professionals, computer based systems for making such decisions and analyzing information have been designed. The two main types of automated systems are decision making systems and expert systems. The aim of this essay is to discuss these two kinds of systems, analyze their applications in medicine or nursing, set examples of such systems and consider the dilemma of decision making in medical field.
Expert systems
An expert system is software that attempts to reproduce the performance of one or more human experts, most commonly in a specific problem domain, and is a traditional application and/or subfield of artificial intelligence (Chytil & Engelbrecht 1997). In traditional computer programs, data is analyzed and after computations result is show to the user. In expert systems, the process of decision-making is based on the data given to the system (which usually represents the predetermined base of human expert knowledge in the chosen area). Generally, the expert system consists of the knowledge base, also known as heuristics, and the inference engine. The inference engine makes associations between the facts using hierarchical relationships assigned to data elements. Expert systems might be used as separate decision-making systems, but more often they are aimed to assist the doctor in analysis of a problem where uncertain factors are included.
The most frequently mentioned expert system – Mycin – was developed in the early 70s at Stanford University. The system chooses the best way of treating the patient who probably has an infectious disease; the system identifies the virus and suggests treatment. In 1980s another expert system has been introduced – Internist 1. This system is designed to aid the physician to implement a differentiated diagnostics process (Chytil & Engelbrecht 1997).
Decision support systems
Decision support systems (DSS) are a specific class of computerized information systems that supports business and organizational decision-making activities. A properly-designed DSS is an interactive software-based system intended to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions (Jones & Patronis 1996).The key to decision support systems is to collect data, analyze and shape the data that is collected and then try to make sound decisions or construct strategies from analysis.NURS 6401 week 5 Discussion Essay
Basically, a decision support system includes a dynamic knowledge base and inferencing mechanism; medial-logic modules are used for choosing the best solution. The DSS may be based on expert systems, on artificial neural networks, or include elements of both systems, which is called connectionist expert systems (Ifeachor 1998). Artificial neural networks have proven to be quite efficient for non-linear data modeling and decision-making. Neural networks imitate the actions of a human brain in the process of selecting a solution. The decision support systems represent wider class of applications because they may be used for making dynamic solutions and applying them in situations with changing environment (though proper training should be done to the system previously). Classical examples of decision support systems are clinical decision support systems such as AAPHelp, designed to support the diagnosis of acute abdominal pain and, based on analysis, the need for surgery; PIP (Present Illness Program) that gathered data and generated hypotheses about disease processes in patients with renal disease, ONCOCIN – a rule-based medical expert system for oncology protocol management designed to assist physicians with the treatment of cancer patients receiving chemotherapy (Armoni 2000). The latter system used a special language for modeling decisions and sequencing actions over time.
Decision making dilemma
At first glance, expert and decision making systems are ideal solution for medicine and should be used for diagnosing, prescribing treatment and solving problematic situations. However, there are several ethical and logical dilemmas concerning artificial intelligence in medical sphere.
First of all, there is a significant group of patients who would not trust computer systems and prefer to contact with a human being during the treatment. Secondly, the knowledge base and inferencing systems are programmed and taught by people, which means there might be ambiguous or mistaken patterns in the system. Thirdly, the changing environment and its estimation is in many cases still better done by people than by AI systems.Taking into account all the above-mentioned facts, it is possible to conclude that the most efficient application of expert and decisions making systems is when close interaction between the system and the doctor is maintained. In case of collaboration experience and vision of the medical professional is supplemented by the ability of the AI system to analyze large amounts of data, speed and associative links.
Conclusion
Expert and decision support systems play an important role in the development of modern medicine; they help to eliminate human mistakes and significantly broaden the scope of analysis for doctors, nurses etc. However, human decisions cannot be totally replaced by automated systems and the best application of artificial intelligence in the medical sphere is when close collaboration between medical professional and expert or decision support system exists.NURS 6401 week 5 Discussion Essay
The fields of informatics and clinical informatics fields use information technology to enhance effectiveness in the industries applying this knowledge. Clinical informatics refers to the use of information applied in health care services. It refers to combination of advanced quality, effectiveness and creation of new opportunities in the health care. Health informatics contributes to the understanding, desegregation and usage of information technology in health care environments. This assists in ascertainment of enough and qualified support of clinician attainable goals and industry’s splendid performance. This field deals with funds, tools and procedures necessitated in maximizing acquiring, storing, recovering and use of information in health and medication. The use of clinical informatics has facilitated improved health outcomes of individuals and general public at large and also has made the relationship between patients and clinician to improve at great extents (Kaplan, 2001).
On the other hand, informatics refers to the discipline of computer information systems. It entails use of data processing and practical application of information systems in the industries. It involves the study of structure, precise rules specifying how to solve problems, interaction taking place between natural and artificial systems, which are involved in storage, processing, accessing and transmission of information. This branch of knowledge considers the construction of computer interfaces that works together with the intervention and interaction between humans and information systems (Kaplan, 2001). The two examples of clinical informative that have facilitated in improving patient care are use of POE system and decision support system. At the Brigham and Women’s in Boston, Massachusetts, use of physicians order entry(POE) with decision support system has facilitated to enhanced application of suitable medications for risky clinical situations, for example, using subcutaneous heparin to avoid venous thromboembolism. POE has caused reduced errors in medication, enhanced prescription and guide when making treatment decisions Kaplan, B. (2001).
Data Management by Nurse Manager to Improve Patient Care on Their Unit
Nurse Managers are mandated with the duties of managing finances, staffing, ensuring satisfaction of patients and staffs. They also have responsibilities to maintain safety environment for employees, patients and guests and quality of care maintained while matching goals of their units to those of hospital strategic goals. Nurse managers can use data management to help them in staffing matters of their units. This is because there is a direct relationship between nurse staffing and the quality of outcomes in healthcare units (Kaplan, 2001).NURS 6401 week 5 Discussion Essay
Availability of data that shows the effectiveness of a nurse toward the execution of assessments and interventions intended to maximize outcomes helping in discontinue adverse events, can help in staffing needs of the unit. For example, accuracy of a nurse in administering medications and proper prescription to the patients improving safety of the patients while minimizing rates of errors in care units can be accessed using management data during staffing. Another example of management data that can be used is in managing resources. Nurse managers can use data management to evaluate the units’ costs and incomes and allocate funds to the most effective use that would help in cutting down unnecessary expenses. For instance while ordering for medicines they should evaluate most probable health issues in their units avoiding unnecessary stocks, additionally, timely re-ordering to prevent incurring stock out costs (Kaplan, 2001).
The reasons for a push was meant for implementation of Electronic health records (E.HR) by President Bush by year 2014 were to enhance healthcare safety of the patients hence improving quality and cutting costs. Electronic health records (EHR) are meant to maintain patient’s clinical information to physicians when required irrespective of locality and time. This was meant to reduce the rates of errors during medication process as a resulting from lack of patient’s records from the prevailed paper based records in America. The rationale in the implementation of the EHR is that, they have high chances of alerting the physicians about the probable errors hence influencing their behavior towards evidence-based decisions (Bates, 2005).NURS 6401 week 5 Discussion Essay