Statistical Methods in Hospitals

There are various types of statistical methods that can be used for data gathering and analyses. Apparently, the use of these formulas is very much dependent on the type of data as well as the goal of the researcher in manipulating them. In the field of health care and medical instrumentations, the appropriate use of statistical methods will provide a more dramatic support in decision making processes.

The field of hospital and medical care involves the collection of data pertaining to different medical procedures. If a person is interested in extracting information form these data, it is very important that he knows how to collect and derive them from raw information.

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If a hospital in on the process of gathering information form its patients, it would be appropriate to use the tabular method of data acquisition. A tabular method may be the simplest form of numerical gathering because it only involves the outright count process of direct responses. This method is suitable in collecting data in count form. For example, an individual may collect various responses corresponding to the specified answers in a certain questionnaire survey. One example would be whether the patient is satisfied with the performance of the nurses. The responses may be recorded using tabular methods.

Another approach that can be employed in collecting data can be in the form of surveys. Since the tabular method is restricted to binary responses (e.g. Yes or No), it is somehow limited if additional information is to be collected. With surveys, additional information may be derived from the subjects such as, range of service satisfaction, age of the patient, nature of illnesses and other pertinent information.

When data sets were already collected, the next step would be interpretation and presentation. There are various statistical ways to present data. For a hospital setting, graphical illustration may be employed. The collected data may be transformed and converted into a graph display where the summary of the scope is presented. Some of the most common methods are pie chart, line graph and tables. All of these methods can be used to present the numerical data to other individuals concerned in the study. In contrast with tabular numerical values, graphical displays provide a bigger picture of distribution for analyzing data.

The methods in statistics are very diverse and target specific interpretation depending on the study. For hospital data, the most common formulations involve the averaging process or the mean, the distribution errors for standard deviation and even the ordinary count frequency or the mode. However, simple as they seem, these are just the primary basic steps in extracting deeper information from a collected set of data.

For hospital or health care based studies, the use of Univariate and multivariate analysis may be employed. For example, if the researcher wishes to provide a picture of interrelationships of different hospital service factors, he can use multivariate analysis to derive the answer. One example can be, whether the recovery of the patients is dependent of the type of room or, is the gender of nurse affects the behavior of the patients. Such study cases may be done using statistical analysis methods. These types of analyses may be derived using regression. Regression provides information about the nature of the relationship between the variables (StatsDirect, 1990).

Basically, using statistical processes employs a generalized specific goal, to aid in the decision making process of the individual. Because of exemplified importance of statistics in predicting or giving summary data outputs, it has become a very important tool in the field of medical and health care domains.

There are relatively advantages and disadvantages in the interpretation of statistical data in accordance to decision making. If a method is accurate, it can denote a higher order of confidence among the researchers that a certain degree of event will actually happen. The statistical method will support the intention of the organization to pursue an activity based on the results of statistical studies. Because it has a higher form of accuracy, the main goal of implementing the decision will already provide a picture of what is going to happen after the results are obtained. However not because the study is accurate, implies that is it all but advantageous. In statistics, the main course of analysis lies on the data itself. The results will greatly depend on what qualities of data were collected. Given this assumption, there are times that even the formulation was accurate; it may not be useful for decision making processes. The results may be contrasting to the ones expected by the researcher. In this case, he may not be able to implement his goal as it may compromise various resources such as time, money and manpower. This is the main reason why statistical methods are not always in favor of the goal of the researcher.

Understanding the use of statistical methods to various fields can be a good approach in strengthening decision making procedures. Because of these mathematical and formula based analyses, a hospital care unit may be able to derive information from collected samples of data.

References:

StatsDirect. 1990-2007. Advice: Linear regression & correlation. Relationship between two variables measured on the same group. Retrieved May 22, 2007 from http://www.statsdirect.com/help/methods__interval_normal_vs_interval_normal.htm.

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