Statistics in the Workplace
Statistics are used in my workplace for many reasons. My primary function is to maximize the capabilities of the military treatment facility at the same time ensuring patients receive quality health care in a timely fashion whether it is direct or purchased care. All requests for purchased care are first reviewed for medical necessity and are then re-directed within the military treatment facility for right of first refusal. If the military treatment facility does not have the capability, the requests are forwarded to the managed care service contractor. We also monitor referral patterns, and identify trends relating to network leakage, network care ...view middle of the document...
We look at all specialty care networked out of our organization. The data is generally organized and entered into a table for viewing ease and clarity. We usually always have a handful of specialties that we simply cannot avoid purchasing care for so we look to identify trends to see why data increased in some months or declined in others. We usually determine that in those periods of influx that we have either lost a provider to deployment, provider shortages due to staffing issues in general, personal time off for providers during certain times of the year. These trends also help us to identify periods of time when fewer patients are seen not necessarily due to provider shortage but because the patients are not presenting for care. We have noticed that fewer patients come in for care during holiday seasons and that we may have an increase in orthopedic care due to increased injuries in the summer months. Of course most of this varies from year to year.
According to “Basic Statistical Concepts for Nurses” (2011), “Inferential statistics are mathematical procedures which help the investigator to predict or infer population parameters from sample measures. This is done by a process of inductive reasoning based on the mathematical theory of probability (Fowler, J., Jarvis, P. & Chevannes M. 2002)” (Inferential Statistics).
An example of inferential statistics at my workplace recently was a climate survey completed by employees. The survey allows employees to voice their concerns anonymously. After the survey period is complete, the data is collected, reported, and the commanding officer holds a town hall meeting to discuss the findings and address concerns mentioned in the survey. I say this survey is inferential because we never get 100% participation from the employees. So the concerns of a few must represent the whole and the commanding officer must draw his own conclusions about the workplace climate based on the survey opinions of a few employees. I believe this last survey had only about 15% percent of our employees participate despite the many reminders sent out via e-mail. I am convinced that the CO can only generalize the workplace climate based on a 15% participation rate.
Levels of Measurement
The levels of measurement are nominal level of measurement, ordinal level of measurement, interval level of measurement, and ratio level of measurement.
A nominal level of measurement is, “A level of measurement for qualitative data that consist of names, labels, or categories only and cannot be ranked or ordered” (Bennett, Briggs, & Triola,...