Introduction
Consistent implementation of the health policy has allowed to achieve certain results in preserving the health of patients at Downtown Hospital in Chicago, Illinois. This paper is an assessment of statistical data on the improvement of the health care system in this medical institution. Medical and social diagnostics and analysis of the achieved results make it possible to conclude about the results of the implemented changes. The study of social feedback on the degree of satisfaction of society in the field of healthcare will allow to justify a set of measures to improve healthcare.
Nurse Staffing
There is a close relationship between nurse staffing, patient wait times, and satisfaction. Patient satisfaction is the inner feelings of patients from the experience of interacting with a medical center. They are often related to the speed of medical care; the more nursing staff, the shorter the waiting time. With a heavy workload of medical specialists, they cannot receive patients quickly, and queues form (Ransom et al. 2008). Therefore, patient satisfaction is proportional to nurse staffing and directly proportional to waiting time. Waiting time indicators depend on nurse staffing and with a decrease in this indicator also become lower.
Confirmation of the existence of these dependencies can be found if closely regarding the indicators of Downtown Hospital. During the year, the number of nursing staff increased by 15 employees: from 117 to 132. It can be noted that hiring new employees allowed them to receive patients faster. According to the data, over the year, the waiting time of patients decreased from 61 minutes to 26, which is more than twice. However, the degree of patient satisfaction increased slightly; this may be due to the peculiarities of the attitude of the staff.
Average Patient Wait Times
Standard waiting times for patients depend on the type of medical care and range from 20 minutes to several hours. Waiting time is the most significant loss in the clinic; such a key step as increasing the number of nurses will lead to a reduction in the waiting time for admission to treatment rooms (Ransom et al. 2008). Consequently, it will entail the exclusion of other losses in the flow of expectation of value. The expansion of the nursing staff contributes to the division of patient flows in the temporal, spatial and structural fields. This action allows to eliminate uneven loading at certain stages of medical care.
At the time of the data collection, 117 nurses were working at Downtown Hospital, and the wait time was 61 minutes. Even with a slight increase in the nursing staff by 2 employees, the wait time has significantly decreased and has become 49 minutes. In the following months, the nursing staff continued to increase, and began to amount to 132 people. Along with the expansion of the number of nurses, the waiting time also decreased. When 130 nurses started working at Downtown Hospital, it dropped to 32, and then to 30 minutes. This indicates that there is a strong relationship between the indicators of patient wait time and the number of nurses.
Medication Administration Errors
Infections associated with the provision of medical care represent a serious public health problem due to their frequent occurrence. They lead to morbidity and mortality and are a significant burden for health workers. Medical errors are also often the cause of outbreaks of infectious diseases. According to official statistics, the average number of medication errors and HAIs for the national average is 8-25% (Ransom et al. 2008). According to Downtown Hospital statistics, the number of medication administration errors and healthcare-associated infections (HAIs) does not correspond to the national average data, exceeding it.
The growth of medicine administration errors can be noted, most likely associated with an increase in the number of nursing staff. Since the beginning of the year, they have increased from 31% to 39%. The indicator during the entire time of the data gathering was higher than normal. As for healthcare-associated infections, on the contrary, their number has significantly decreased. At the beginning of the year, it was 5.1%, and at the end of the observations, the indicator decreased to 3.8%. This may be due to the fact that nurses have the opportunity to devote more time to each of the patients due to the increase in nursing staff.
Healthcare-Associated Infections
The number medication administration errors at Downtown Hospital for the year varied from 24% to 39%. At the beginning of the data collection, this indicator was average compared to the general annual. At the end of the observations, the highest index of errors in taking medications was recorded. Given the various measures of data, it does not appear that the hospital has not significantly improved its quality, safety, and patient satisfaction over the last two years (Feldman et al. 2018). In the previous months before the last data collection, the number of medication administration errors had the lowest rate of all time. However, the latest data collection recorded a catastrophically high figure exceeding the state norm. At the same time, the patient satisfaction index has not changed much, remaining at the level of 70-71%. At the same time, the previous measurement even showed a significant decrease in the patient satisfaction compared to the initial level.
Patient Satisfaction
As it was established above, the level of patient satisfaction directly depends on wait times and HAIs. The wait times for Downtown Hospital index has improved markedly over the past two years. At the start of data collection, it was 61 minutes. At the end of the observations, the average waiting time has been reduced by more than two times and is 26 minutes. The HAIs indicator also decreased; it initially corresponded to the national norm, but at the end of the observations it even dropped below the norm.
Almost half of the outliers reviewed worsened their indicators, while the indicators of the other half improved. Quality indicators, such as waiting time and the number of nurses, have changed for the better. However, the number of medication errors significantly exceeded the state norm (Tully & Cantrill 2000). Perhaps this is what influenced the fact that the patient satisfaction index has not changed in two years, despite all the improvements. At the beginning of data collection, it was 70%, and two years later – 71%, that is, the indicator remained unchanged.
Conclusion
Taking into account the experience of Downtown Hospital in Chicago, it can be concluded that in order to improve the quality management system of a medical and preventive institution, it is necessary to take into account a wide range of indicators. All of them are closely interrelated and are important for patient satisfaction. By improving a part of the indicators of the quality of medical care, it is impossible to achieve a complete result. It is necessary to make changes more gradually, otherwise the hospital administration may not be able to cope with their regulation, which will lead to a large number of errors.
Reference List
Feldman, S, Buchalter, S & Hayes, L 2018, ‘Health information technology in healthcare quality and patient safety: Literature review’, JMIR Med Inform, vol. 6, no. 2, pp. 10-26.
Ransom, E, Joshi, M, Nash, D & Ransom, S 2008, The healthcare quality book: Vision, strategy, and tools, Health Administration Press, Chicago, ILL.
Tully, M & Cantrill, J 2000, ‘The validity of the modified patient generated index: A quantitative and qualitative approach’, Quality of Life Research, vol. 9, no. 2, pp. 509-520.