Analysis of a Pertinent Healthcare Issue
The selected pertinent health issue is quality of care. Quality of care is determined by various factors including accurate diagnosis. Statistics indicate that the quality of care deteriorates upon misdiagnosis. In the United States 12 million patients are misdiagnosed, a condition which increases the cost of treatment and in some cases leads to death (Khullar & Jena, 2016). Late diagnosis of cancer has been associated with misdiagnosis when patients first felt unwell. Poor quality of care is a major issue in our healthcare facility. The reason is that patients are provided with the wrong medical treatment thus leading to poor patient outcome (Desai & Dave, 2017). It has affected the organization since the cost of treatment has increased by 25 percent as a result of poor quality of care.
The hospital has recorded over 270 cases of misdiagnosis annually. The highest percent of misdiagnosis is among female patients compared to male patients. Female patients who are over 40 years take 40 percent of all cases of misdiagnosis (Khullar & Jena, 2016). The statistics have prompted the organization to discuss ways that can be used to reduce the severity of the condition. Healthcare providers who are found guilty of any misdiagnosis are fired and those who are left end up less motivated. Annually over 15 healthcare professionals are fired due to cases of gross misconduct that results in provision of poor quality care (Desai & Dave, 2017). Additionally, the impact has increased the labor cost by 15 percent since new professionals have to be hired when the old ones are fired. It is also hard to maintain continuity of care since patients are served by different nurses due to the high employee turnover.
Desai and Dave (2017) carried out a study on a comparison between artificial intelligence systems and manual methods of in diagnosis of electrocardiogram. The study argues that a combination of human brain and artificial intelligence can enhance the quality of diagnosis. The scholars insist that artificial intelligence cannot operate on their own and thus they need human intervention. The approach of blending artificial intelligence and human brains is aimed at enhancing the quality of care. The results of the study indicated that 33 percent of cases of an electrocardiogram are absolutely misdiagnosed while 44 percent are relatively misdiagnosed and only 23 percent are accurately diagnosed (Desai & Dave, 2017). The study that was carried out in the Pacific Institute of Medical Sciences using 30 electrocardiogram cases indicated that adoption of artificial intelligence is necessary. The technology provides in-depth analysis and accurate detection of a condition compared to the manual methods that are not intensive.
Newman-Toker et al. (2019) carried out a study on serious misdiagnosis-related harms in malpractice claims. The study utilized data from a database on misdiagnosis to estimate the severity of the condition. It focused on 53,377 cases of misdiagnosis over a specified period of time. The study revealed that 21 percent of the cases were due to missed or delayed diagnosis. Most of the cases led to death or permanent disability. Additionally, the results of the study corroborate with previous research that misdiagnosis mostly occurs in primary care and emergency department. The recommendation of the study is that healthcare practitioners should be trained to understand the severity of their actions. It should help them shift focus to eliminate cases of misdiagnosis which undermine the quality of care (Newman-Toker et al., 2019). It also compromises the treatment of the actual illness such as cancer. For example, delayed or missed diagnosis of cancer provides the cancerous cells an opportunity to spread past a full-blown stage that is hard to treat.
The strategies presented in the articles are relevant to the pertinent health issue. Quality of care can be enhanced by integrating the human brain with artificial intelligence systems. Artificial intelligence is one of the strategies that enhance precision during surgery or other medical procedures. Intensive care is also enhanced using technology (Khullar & Jena, 2016). Another strategy is that practitioners should be trained to understand how to avoid missed diagnosis. They also understand the severity of their actions, which can lead to death, and thereby be keen in their work.
The proposed strategies will affect the healthcare organization positively since it will provide a hint on how to improve the quality of care. It will also suggest to the management on the need to integrate artificial intelligence systems in primary and acute healthcare (Khullar & Jena, 2016). The adoption of the strategies will eliminate cases of missed diagnosis or misdiagnosis. It is also important that the strategies will impact the policies of the organization. It will prompt the management to retrain the nurses and other healthcare practitioners on the expected quality of care (Newman-Toker et al., 2019). The technology will also enhance the number of patients attended to per day. Therefore, patients will be happy when they know they will be treated in the right way using advanced technologies and systems. The cost of treatment is also likely to reduce since cases of misdiagnosis will reduce significantly.
Desai, V., & Dave, D. (2017). Is artificial intelligence better than manual methods in diagnosis of electrocardiograms (ECGs) or not? International Journal of Advances in Medicine, 4(5), 1463.
Khullar, D., & Jena, A. B. (2016). Reducing prognostic errors: a new imperative in quality healthcare. BMJ, 352, i1417.
Newman-Toker, D. E., Schaffer, A. C., Yu-Moe, C. W., Nassery, N., Tehrani, A. S. S., Clemens, G. D., … & Siegal, D. (2019). Serious misdiagnosis-related harms in malpractice claims: The “Big Three”–vascular events, infections, and cancers. Diagnosis, 6(3), 227-240.