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The Use of Statistics within Mercy Hospital, Coconut Grove, Miami, Florida

The use of statistical information has increased tremendously given the need to understand the current trends in service provision, goods purchase and even environmental change. It is thus important to understand the methods through which data is collected and analyzed and various uses of the data. In Mercy Hospital, Coconut Grove, Miami, Florida, statistics has become the main means of ensuring delivery of quality services and also disease prevention and survey. Some of the uses of statistics in this hospital include measuring patient mortality from a specific cause, e.g. breast cancer. Such measures are used by the hospital to alert the local authorities to the need to increase the funding of healthcare facilities and research for cure of that condition. Statistical data can also be used to measure the infection rates in a specific region in order to know the prevalence of a given disease in that population and prepare adequately in terms of medication and personnel. Statistics is also used in analyzing the admission trend to find out when the hospital receives the highest load of patients since this is important in planning for bed capacity and personnel allocation to different departments. Statistics is also employed for research purposes to gauge the spread of specific vices in society such as gender based violence. This is important for administration; it prompts them to support relevant legislation to deal with the issue and also to provide adequate care for the victims after discharge.

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An example of descriptive statistics used in Mercy Hospital is the mode. It is used to analyze the susceptibility of population to a specific infection based on age groups. Forinstance, the mode is used to determine the age group most commonly affected by venereal diseases, which then helps public health workers in organizing counseling sessions and sensitization forums.

An example of inferential statistics used in Mercy Hospital is the average. It is important when there is a need to establish the number of patients expected in a month in the hospital. This number is calculated based on the admission in the same month for the past five years. This is essential for preparation in terms of accommodation, medication and also personnel. It also helps the hospital management make a decision as to whether the hospital should expand. This data is also employed when the management wants to lobby for more funding from the government (Gibson et al., 2008).

Nominal data is used to find out the difference in admissions between males and females. Thus, it is normal for such information to be included in the admission sheet. It is also useful when allocating wards to ensure a female patient is not taken to a males’ ward. Ordinal data is also employed in numbering of beds. It helps the hospital personnel to find patients easily by following the details in the admission sheet which normally indicate the bed allocated. However, it does not mean that a patient in bed number 1 is in a more critical condition than the one in bed number 31. Perhaps the most widely used level of measurement is the interval. Every morning, the nurses have to take the vitals of patients which include the temperature, indicated in degrees Fahrenheit. For instance, it can be recorded as 94 degree Fahrenheit. The fourth level of measurement, the ratio data, is also widely used in this hospital setting. Measuring the weight of patients at admission is a common procedure; this data is used when prescribing drugs such as cardiac glycosides. Sometimes, both the weight and height are measured when there is a need to compute the basal metabolic rate of an individual considered to be obese. The weight data can be used in epidemiology to gauge the prevalence of a condition such as heart disease among the overweight compared to those whose weight is normal for their age (Rafferty et al., 2007).

Accurate interpretation of statistical information is critical for this hospital to ensure that the admission of patients does not exceed the hospital capacity. This is avoided by proper detailing of the available beds at any given moment. Secondly, decisions on funding depend on accurate data since the amount of funds is limited while too many activities needing funding; an example is purchase of drugs versus purchase of patient recreational facilities. When giving prescriptions, it is important to consider gender, age, body weight of the patient and also diseases that the patient suffers from. Failure to do this may result in adverse reactions from the patient and even death, which has both professional and legal consequences.

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Conclusion

It is evident that Mercy Hospital makes use of data from all the four levels of measurement to make decisions aimed at ensuring proper service delivery and safety of the patients. It is also important to emphasize the need for proper and accurate interpretation of the data to avoid making errors that can lead to loss of funds and even patients’ lives.

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