Nursing personnel workload and staffing need for rural hospitals of Darjeeling District, India: Assessment by application of workload indicators of staffing need tool (World Health Organization)

• 主要な著者: Sk Golam Mortuja (著者), Samir Dasgupta (著者), Sharmistha Bhattacherjee (著者), Abhijit Mukherjee (著者)
• フォーマット: 図書
• 出版事項: Wolters Kluwer Medknow Publications, 2023-01-01T00:00:00Z.
• 主題: article
• オンライン･アクセス: Connect to this object online.
• Notes: 0019-557X; 10.4103/ijph.ijph_1678_22
• Keywords: health workforce; human resources for health; workload indicators of staffing need; Public aspects of medicine; RA1-1270
• Source: Indian Journal of Public Health, Vol 67, Iss 4, Pp 654-659 (2023)

Background: The Workload Indicators of Staffing Need (WISN) human resource planning and management tool developed by Shipp (1998) and popularized by the World Health Organization gives health managers a way to analyze and calculate correct staffing levels in health facilities. Objectives: This study aimed to assess the current workload and staffing need of staff nurses for rural hospitals in Darjeeling district, West Bengal. Materials and Methods: Primary data were collected by interviews with nursing personnel using a semi-structured interview schedule. Secondary data were obtained from available records at the rural hospitals. Workload components were established for health service activities, support activities, and additional activities. Staffing needs based on workload was calculated after adjusting allowance multiplier. Results: WISN findings highlighted varying degrees of health worker shortages and inequities in their distribution at different health facilities. WISN ratio indicated that the work pressure of health staff was highest at Kharibari RH (0.45), followed by Naxalbari RH (0.54). About 43% of nurses' time was occupied with support activities, instead of nursing care. Conclusions: WISN method can help policy-makers in optimizing utilization of existing human resources. There is a need to adopt flexible health workforce planning and recruitment policy to manage the patient load and disease burden.