Analytics and Lean Health Care to Address Nurse Care Management Challenges for Inpatients in Emerging Economies.

Autor: Moreno-Fergusson ME; Doctor in Nursing Science, Faculty of Nursing and Rehabilitation, Universidad de La Sabana, Chía, Cundinamarca, Colombia., Guerrero Rueda WJ; Doctor in Engineering, Faculty of Engineering, University of La Sabana, Chía, Cundinamarca, Colombia., Ortiz Basto GA; Professor, Faculty of Engineering, Universidad de La Sabana, Chía, Cundinamarca, Colombia., Arevalo Sandoval IAL; Master in Bioethics, Nursing Deputy Director, Clinica Universidad de La Sabana, Chía, Cundinamarca, Colombia., Sanchez-Herrera B; Master in Science of Nursing, Gerontological Nurse Practitioner, High Prestige Professor, Universidad de La Sabana, Chía, Cundinamarca, Colombia.
Jazyk: angličtina
Zdroj: Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing [J Nurs Scholarsh] 2021 Nov; Vol. 53 (6), pp. 803-814. Date of Electronic Publication: 2021 Oct 19.
DOI: 10.1111/jnu.12711
Abstrakt: Purpose: Prescriptive and predictive analytics and artificial intelligence (AI) provide tools to analyze data with objectivity. In this paper, we provide an overview of how these techniques can improve nursing care, and we detail a quantitative model to afford managerial insights about care management in a Hospital in Colombia. Our main purpose is to provide tools to improve key performance indicators for the care management of inpatients which includes the nurse workload.
Methods: The optimal nurse-to-patient assignment problem is addressed using analytics, lean health care, and AI. Also, we propose a new mathematical model to optimize the nurse-to-patient assignment decisions considering several variables about the patient state such as the Barthel index, their risks, the complexity of the care, and the mental state.
Findings: Our results show that there are several processes inherent to compassionate nursing care that can be improved using technology. By using data analytics, we can also provide insights about the high variability of the care requirements and, by using models, find nurse-to-patient assignments that are nearly perfectly balanced.
Conclusions: We illustrated this improvement with a pilot test that makes the equitable distribution of nursing workload the functionality of this strategy. The findings can be useful in highly complex hospitals in Latin America.
Clinical Relevance: The proposed model presents an opportunity to make near perfectly balanced nurse-to-patient assignments according to the number of patients and their health conditions using technology.
(© 2021 The Authors. Journal of Nursing Scholarship published by Wiley Periodicals LLC on behalf of Sigma Theta Tau International.)
Databáze: MEDLINE
Externí odkaz: