Topic: Case Study Analysis
Review the case study below. Write a 1,750- to 2,100-word paper that addresses the following regarding the case study:
• What measures are used to monitor and revise quality program implementation? Are the measures appropriate considering the circumstances? Why do you think this?
• What regulatory and accreditation standards exist? What strategies are used for meeting these standards? Are the strategies appropriate considering the circumstances? Why do you think this?
• What barriers may interfere with implementing or revising the quality measures described in the study? How could the organizations overcome those barriers?
Format your paper consistent with APA guidelines. No plagiarism on the paper. Keep it confidential.
Please Read the Case Study below and write a paper based on the requirements posted above. Use at least four peer review references.
CASE Study: FALLS
Using data to improve patient safety is not only required by governmental agencies but has become a recent focus of media attention. The reason regulatory agencies require data about falls, for example, is that falls are prioritized as a high-risk problem that can result in fractures,
surgery, or worse. Because falls are a patient safety concern, if safety is a high priority for the organization, part of its stated mission, then preventing falls is important.
Nursing staff collect information about falls: incident reports record
the time, place, date, frequency, and reason for the fall. Patient assessment
and H&P (history and physical) target certain patients as highly susceptible to falling. Falls have an impact on LOS, especially when the resulting injuries require tests and treatment. Patients who fall, and their families, complain about their care in a formal way, such as through satisfaction surveys or complaints to the organization, suggesting that better
care would have prevented the fall from occurring. Patients and their
families have instituted lawsuits as a result of falls.
Malpractice suits are increasingly being brought after falls, because they are thought to be preventable and can result in serious injury. Jury awards for these perceived “unnecessary” complications have been high.
Why is it that hospitals cannot prevent patient falls? The methodological explanation is that the “fall prevention” ranking (that is, a given patient’s likelihood of falling) is perceived to be a nursing assessment issue. This perception is itself a problem, due to the conflicting desires to show not only that the rates are low but also to illustrate to regulatory agencies that the measure, which they require, is being used. In fact, the report of low rates is based on poorly defined measures.
A valid measure defines a set of events that occurs in a circumstance where there were opportunities for that type of event to occur. Figure 2.2 graphically illustrates how to define a quality measure. The number of events is thenumerator of the measure, and the number of
opportunities for that event to occur is thedenominator.
For example, if you are interested in examining how many falls resulted
in fractures, the numerator of the measure would be exactly that—the number of patient falls that resulted in fractures. The denominator would encompass the totality of all falls. If 20 falls resulted in fractures, and there were 100 falls in total, the numerator (20) is a subset of the denominator (100). The measure of the falls is calculated as a rate, in this case, 20/100, or 20 percent. The numerator, orNof a measure, defines what you want to study or what question you want to investigate or which hypothesis you want to test. Therefore theNcan be as specific or as general as appropriate. If you were interested in determining the influence of medication on falls, you might want to know the rate of medicated patients who fell. The measure would be
events/opportunities, orN/D—in this case the number of patients on sedatives who fell/the total number of patients who fell (see Figure 2.3).
Quality Measure =Event = Numerator
Event = Number of Sedated patients who Fell
Opportunity Total Number of patient Falls
Because major falls that cause injury and even death still occur, the focus is shifting from reacting to an event toward developing prevention programs. Another reason to adopt such a focus is that the majority of today’s hospital patient population is at high risk for falls because they are increasingly elderly, living longer, experiencing multiple diseases, and taking many medications. Even those organizations that have developed a falls prevention program have a high rate of falls because the assessment and program can be so routinized that it becomes
a paper exercise to illustrate to the accreditation agencies that the organization is in compliance with assessing patients.
There are organizations that believe if there are no falls being reported, there are no falls occurring. Patent nonsense. The New York State Commissioner of Health has taken an hard-line approach to the reporting of errors and is critical of hospitals that underreport. She is quite right to take this position, because without information, improvements cannot be intelligently implemented.
In our health care system it took almost eight months to develop a definition of “fall” that was acceptable to all caregivers. What might seem to a layperson a straightforward concept can be quite complicated?
For example, does a “fall” have to result in the patient being on the floor? Can a patient “fall” if that patient is being assisted onto a chair by a caregiver? Does a “fall” have to be observed by another to distinguish it from a collapse or a faint? Measurements cannot be standardized unless everyone involved in data collection understands what data they are collecting.
It’s obvious that if the reasons for the falls are understood and if appropriate improvements can be developed and implemented, that would decrease the incidence of falls. This decrease would produce many advantages: the organization’s safety objectives would be met, the potential for malpractice claims against the hospital would be reduced, patient satisfaction would be increased, the budget would no longer be adversely affected by costs of falls, LOS would be reduced, and most important, patient safety would be preserved.
With data, professionals can understand the scope of the problem they have and determine whether resources should be used for improvements. If you have 10 falls per 1,000 patients (1 percent), over the course of six months, perhaps you would determine that your improvement efforts should be focused elsewhere. But if you discover that your unit or hospital has 10 falls per 50 patients, or 20 percent every week, you know you have a far more serious problem to address.
You need a sense of the dimensions of the problem, that is, data that reveal how many incidents (the numerator of the measure) were related to how many possibilities (the denominator), and also a time frame to delimit that data, to help you measure, or quantify, the incidence of falls, or any other variable. The numerator of a measure is defined by the question being considered, such as do elderly patients with diabetes have an increased likelihood of a fall? With data, such questions can be answered accurately.
Data can be gathered on patient age, patient diagnosis, and the time when (on what shift) the patient falls. In addition, information is readily available on the patient-staff ratio at the time of the fall, on the unit of the patient who falls, and on the cause of the fall. There can be many
variables to assess. Was the call bell not answered in a timely way? Was there an obstruction on the floor? Were the lights not working properly? Did medication play a part? What happened to the patient is also documented: was there an injury, what kind of injury was it, what was
the cost in terms of LOS, and what were the unanticipated services (return to the OR) or clinical outcomes, such as infection or malpractice suits? All these pieces of data are associated with measures. Taken together the information enables an administrator to grasp the situation
in a complex way (rather than to assume the nurse was not doing her or his job) and implement improvements. Good administrators have valid data underlying their decisions. Data collection and analyses should also be the responsibility of clinical supervisors, such as the head nurses and the chairs of clinical departments.
Regulatory agencies require hospitals and health care organizations to correlate human resource indicators, such as staffing ratios, with quality indicators, such as falls. A common suggestion that makes a kind of intuitive sense is that patient falls are related to the number of
nurses and other health care staff available for bedside care on the unit, if deployed appropriately. However, in our system, when we collected information that tracked staffing turnover with the rate of falls (see Figure 2.4), it appeared there was no correlation between them.
Our conclusion was that a single indicator (that is, staffing) was insufficient
to explain as complex a phenomenon as falls. For example, case mix index, that is the degree of illness associated with specific diagnoses, in combination with staffing ratios, may be more informative about patients at risk for falls. Without these data, leadership might have been tempted to increase staff, with the associated expense, to reduce falls—without success.
Case Study Analysis
This assignment is due Week Five.
|Content60 Percent||Points Available12||Points EarnedX/12||Additional Comments:|
|· Evaluated measures used to monitor and revise quality program implementation· Evaluated strategies for meeting regulatory and accreditation standards· Analyzed barriers that may interfere with implementing or revising quality measures|
|Organization / Development20 Percent||Points Available4||Points EarnedX/4||Additional Comments:|
|· Paper is1,700 to 2,100 wordsin length· The introduction provides sufficient background on the topic and previews major points· The conclusion is logical, flows, and reviews the major points· At least four sources are cited that support the information|
|Mechanics20 Percent||Points Available4||Points EarnedX/4||Additional Comments:|
|· The paper, including the title page, reference page, tables, or appendixes, is consistent with APA guidelines for format as directed by the instructor.· The paper is laid out with effective use of headings, font styles, and white space.· Rules of grammar, usage, and punctuation are followed; spelling is correct.|
|Total Available||Total Earned|