DefinePK hosts the largest index of Pakistani journals, research articles, news headlines, and videos. It also offers chapter-level book search.
Title: The Workload Pressures Experienced by Nurses at Public Sector Hospitals, Peshawar
Authors: Hassan Mehmood Khan, Wajiha Qamar, Mehran Qayum, Naveed Sadiq, Nadia Pervaiz, Shifa Haider Sawal
Journal: Journal of Gandhara Medical and Dental Sciences (JGMDS)
Publisher: Gandhara University, Peshawar
Country: Pakistan
Year: 2022
Volume: 9
Issue: 3
Language: English
Keywords: HealthplanningManagementworkloadworkforce Staffing Resources
OBJECTIVE
The study's objective was to assess that nurses working in in-patient wards were under workload stress.
METHODOLOGY
Descriptive observational research on nurses working in the in-patient ward of a public sector hospital in Peshawar was undertaken in November 2020. Workload Indicators of Staffing Need (WISN), a tool established by the World Health Organization (WHO) to anticipate the number of health staff needed to cope with workload pressure, was used to determine nurses' workload. To ensure the successful implementation of the WISN methodology, three tiers of committees were developed, including steering, technical, and expert committees. Data were also analyzed using the tool.
RESULTS
Nurses in the hospital's in-patient unit work 1966 hours per year. Health service activities, support, and other activities account for 47.92%, 33.33%, and 18.75% of all nurses' time, respectively, during this time. Four nurses were working in the hospital during the research study; however, WISN estimated that three nurses were needed to cope with the ward's workload pressure, and one nurse was overstaffed at the time. The WISN ratio calculated was 1.33.
CONCLUSIONS
The study concluded that there was no workload pressure on nurses (negative), and the ward had an extra nurse who could be accommodated in any other department with greater demand.
To assess if nurses working in in-patient wards at a public sector hospital in Peshawar were under workload stress.
Descriptive observational research conducted in November 2020 at a public sector hospital in Peshawar. The Workload Indicators of Staffing Need (WISN) tool, developed by the WHO, was used to determine nurse workload. Three tiers of committees (steering, technical, and expert) were established to ensure the successful implementation of the WISN methodology. Data were analyzed using the WISN software.
graph TD
A["Conduct Descriptive Observational Research"] --> B["Apply WISN Tool"];
B --> C["Establish Committees"];
C --> D["Collect Service Statistics"];
D --> E["Analyze Data using WISN Software"];
E --> F["Determine Nurse Workload and Staffing Needs"];
F --> G["Conclude on Workload Pressure"];
The WISN approach is a valuable tool for assessing staffing needs based on workload. The study found a surplus of one nurse in the in-patient ward, suggesting that this nurse could be reassigned to an area with greater demand. The hospital management should assess workload pressures in other units and adjust staffing accordingly to optimize service delivery. While WISN is widely used, its findings cannot be generalized without considering factors like topography and demography.
Nurses in the in-patient unit worked an average of 1966 hours per year. Health service activities, support, and other activities accounted for 47.92%, 33.33%, and 18.75% of nurses' time, respectively. The WISN estimation indicated that 3 nurses were needed to manage the ward's workload, while 4 nurses were employed, resulting in one surplus nurse. The WISN ratio calculated was 1.33.
The study concluded that there was no workload pressure on nurses in the in-patient ward, and there was a surplus of one nurse. Appropriate health workforce management and planning, utilizing tools like WISN, can significantly impact the productivity and efficiency of the healthcare industry.
1. The study was conducted in November 2020. (Confirmed by text)
2. The WISN estimated that 3 nurses were needed for the ward's workload. (Confirmed by text)
3. The WISN ratio calculated was 1.33. (Confirmed by text)
Loading PDF...
Loading Statistics...