The Life You Improve May Be Your Own: Honing Healthcare with Statistical Data Analysis
What does the eyesight of a homeless person have in common with complications from dental anesthesia? Or with reducing side-effects from cancer? Or monitoring artificial hip implants?
These are all subjects of recently published studies that use statistical analyses in Minitab to improve healthcare outcomes. And they're a good reminder that when we improve the quality of healthcare for others, we improve it for ourselves.
Vision care for the homeless
A recent retrospective review study was the first to investigate the visual healthcare needs of homeless people in the United Kingdom. Using clinical records of over 1,000 homeless individuals in East London who sought vision care, researchers summarized the demographics of this special-needs population and established baseline reference levels for future studies.
Using t-tests in Minitab, they determined that the homeless population tend to have more eye problems and greater need for visual care than the general population. Although vision problems might appear to be a secondary issue for those facing the constellation of severe, chronic problems often associated with homelessness, researchers point out that even something simple as a spectacle correction can substantially improve a person's quality of life. BMC Health Services Research 2016; 16:54.
Reducing complications from local anesthesia in oral surgery
Noting the proven ability of Six Sigma methodology to increase patient compliance and satisfaction, as well as hospital profitability, investigators applied quality improvement tools to identify and reduce the most common complications from local anesthesia in dental and oral surgery.
They used a Pareto chart to identify the most common complications, and a binomial capability analysis to evaluate the rate of complications before and after implementing remedial measures. The results showed a significant reduction in complications from local anesthesia (pre-improvement % defective 7.99 (95% CI 6.65, 9.51), vs post-improvement % defective 4.58 (95% CI 3.58, 5.77). Journal Clinical & Diagnostic Research. 2015;9(12) ZC34-ZC38.
Exercise, quality of life, and fatigue in breast cancer patients
Researchers explored associations between physical activity in women with breast cancer and their quality of life and levels of fatigue. Descriptive statistics were used to summarize characteristics of the study group. The nonparametric Kruskal-Wallis was used to evaluate differences in median scores, and Pearson's chi-square test was used to explore possible associations between categorical variables.
The authors found a significant positive correlation between increased physical activity level and a higher quality of life, as well as less fatigue. Although the study didn't prove a causal connection, their results support other studies that suggest that physical activity may help preserve quality of life and reduce side effects during cancer treatment. Rev Assoc Med Bras. 2016, 62(1).
Monitoring results of total hip replacement
In hip replacement surgery, an important technical factor is the inclination angle of the acetabular component. Variations from the target angle can lead to increased amount of wear and poorer outcomes after surgery. Therefore, researchers used time-weighted control charts in Minitab, such as CUSUM, EWMA, and MA charts, to monitor the acetabular inclination angle in the postoperative radiographs of patients who underwent hip replacement surgery. The control charts demonstrated that the surgical process, in relation to the angle achieved, was stable and in control. The researchers noted that the time-weighed control charts helped them make a "faster visual decision." Biomed Research International 2015; ID 199610.
What other types of quality improvement studies are being published in the fields of health and medicine? What are the overall trends for these studies? And how can the studies themselves be improved?
We'll look at that in my next post.