In a hospital settings statistics are used to measure a wide variety of data, from patient satisfaction to measurement of standards. Each department within a hospital uses statistical information to help improve the department’s function, compliance, and hand-off. In surgery department, two of the most important statistical information we gather and use are patient satisfaction scores and Surgical Care Improvement Project (SCIP) information. Patient satisfaction scores help us learn what is working as a department and where we may need some fine tuning.
SCIP is used to measure our adherence to Joint Commission (JC) and Centers for Medicare and Medicaid Services (CMS) standards (“Cms. gov”, 2013). SCIP is very imperative not only for patient safety but also for compliance with JC and CMS standards (“The Joint Commission”, 2014). The information collected for SCIP compliance is; last dose of beta blockers (if used), the use of the appropriate antibiotic for the surgery performed, the use of antibiotics before and after surgery, the use of sequential compression device to prevent thrombosis, and the discontinuation of a Foley catheter within 48 hours post-surgery.
SCIP is initiated in the preoperative area and discontinued 48 hours after surgery. We collect SCIP information after each patient is transferred to the floor from surgery; we can gather our data and determine if SCIP standards were followed or was there a fallout. If there was a fallout, where did this occur? Once we can determine where the fallout occurred we are able to educate those involved. Our SCIP scores are an example of descriptive statistical data; they show a wide spread of information. Figure 1 shows SCIP data that was collected from June 2012 to May 2015 (Luis Diego Concepcion, personal communication, July 30, 2014).
Figure 1 Patient satisfaction scores are important for growth, improvement and accountability. The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) is a national survey used to gather patients’ point of view that can be used for developing new ways to improve the quality of healthcare and make healthcare establishments accountable for their actions (“Cms. gov”, 2013). Our patient satisfaction surveys are done by a third party and asks questions about the patient’s most recent visit to the hospital.
These surveys are done randomly and given to any patient whether their visit was for a blood draw or heart transplant. There are a number of questions ask such as the ease of the admissions process, the treatment of staff, pain control, cleanliness of hospital, food quality, treatment of physicians, if information given was clear and concise, how likely are you visit this hospital again, and would you like to recognize anyone? Our patient satisfaction score are an example of inferential statistics because we can take these random surveys and determine a generalized sample of our patient’s population satisfaction scores.
With these scores, we can generally determine how the majority of our patient were treated and if they were satisfied. Figure 2 shows patient satisfactions scores for surgical patients from August 2013 to July 2014 (Luis Diego Concepcion, personal communication, July 30, 2014). Figure 2 In order to use statistical data collected, we must make sure it is gathered and studied correctly. Using the four levels of measurement allows us to take all data that is collected and learn, adjust practice, educate and inform our patients, staff and doctors.
In surgery, we use all four levels of measurement. Nominal level of measurement is used for classifying the degree of sickness of patients going under anesthesia. We use ASA level developed by the American Society of Anesthesiologist Physician Status (“Cleveland Clinic”, 2014). The classification starts at an ASA 1, which is a healthy normal patient expected to do well intraoperative and postoperative to an ASA 6, which is a patient who is declared brain dead and is an organ donor (“Cleveland Clinic”, 2014).
We use this information for communication purposes and help the surgical team plan treatment and adjust accordingly. In the surgery department, we use the ordinal level of measurement to track on time surgery starts and room time turnovers. This data that is gathered allows us to track staff readiness, surgeon punctuality, anesthesia availability, equipment availability, and preoperative effectiveness. We use this data to inform us on how we are doing as a department and where we may need to adjust our practice.
This is also a good tool to use for surgeon recruiting purposes; surgeons like to get in, get going, and get out efficiently. This data allows them to see how we work as a department and if they would like to bring their cases to our operating room. In order to maintain safe operating conditions, we keep track of temperature and humidity of operating rooms daily. Operating room temperature are maintained between 68° & 73°, and humidity is to be maintained between 20% and 60% (“AORN”, 2014). The maintaince temperature and humidity range can inhibit bacterial growth and prevent postoperative infection.
The temperature and humidity are recorded daily in each operating room and rectified immediately if there is an out of range reading. Ratio level of measurement is used when we gather data to determine the amount of time a particular surgeon will takes to do a particular surgery. This data is used to make our surgery schedule. We know if a surgeon typically take two hours to complete a total knee replacement but is always 30 minutes late, we will not place a surgeon who is typically 30 minutes early in the room following that late surgeon.
It is a fine balance, figuring out how to make the puzzle fit together. The data collected is length of surgical procedure then we add 15 minutes for room turnover time. Over time we will have an average for each surgeon and each of their surgeries, this data allows us to develop our schedule once the procedure has been posted. When accurate information is gathered and evaluated, the leadership team is able to develop appropriate interventions and initiate new standards or improve old standards.
In the hospital setting, we are always striving to better ourselves, meet higher standards and be the best. It takes time and money to gather statistical data, interpret it, and make a difference with it. Heath care standards are set because they are best practice or evidence based, which were developed base on statistical studies. Without this statistical data, we would not have these measures to meet, maintain, or exceed. With healthcare changing and advancing so will our studies and statistical data. References AORN. (2014). Retrieved from http://www. aorn.
org/Clinical_Practice/Clinical_FAQs/Environment_of_Care. aspx Cleveland Clinic. (2014). Retrieved from http://my. clevelandclinic. org/services/anesthesia/hic_asa_physical_classification_ system. aspx CMS. gov. (2013). Retrieved from http://www. cms. gov/Medicare/Quality-Initiatives- Patient-Assessment-Instruments/HospitalQualityInits/HospitalHCAHPS. html The Joint Commission. (2014). Retrieved from http://www. jointcommission. org/core_measure_sets. aspx http://www. cms. gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/HospitalHCAHPS.
html http://www. jointcommission. org/core_measure_sets. aspx http://my. clevelandclinic. org/services/anesthesia/hic_asa_physical_classification_system. aspx http://www. aorn. org/Clinical_Practice/Clinical_FAQs/Environment_of_Care. aspx References Larsson, S. , Lawyer, P. , Garellick, G. , Lindahl, B. , & Lundstrom, M. (2012). Use of 13 disease registries in 5 countries demonstrates the potential to use outcome data to improve health care’s value. Health Affairs, 31(1), 220-7. Retrieved from http://search. proquest. com/docview/916577711? accountid=458.