Optimizing staffing, quality, and cost in home healthcare nursing: theory synthesis

Abstract

Aims: To propose a new theory pinpointing the optimal nurse staffing threshold delivering the maximum quality of care relative to attendant costs in home health care.

Background: Little knowledge exists on the theoretical foundation addressing the inter-relationship among quality of care, nurse staffing, and cost.

Design: Theory synthesis.

Data sources: Cochrane Library, PubMed, CINAHL, EBSCOhost Web and Web of Science (25 February - 26 April 2013; 20 January - 22 March 2015).

Implications for nursing: Most of the existing theories/models lacked the detail necessary to explain the relationship among quality of care, nurse staffing and cost. Two notable exceptions are: 'Production Function for Staffing and Quality in Nursing Homes,' which describes an S-shaped trajectory between quality of care and nurse staffing and 'Thirty-day Survival Isoquant and Estimated Costs According to the Nurse Staff Mix,' which depicts a positive quadric relationship between nurse staffing and cost according to quality of care. A synthesis of these theories led to an innovative multi-dimensional econometric theory helping to determine the maximum quality of care for patients while simultaneously delivering nurse staffing in the most cost-effective way. The theory-driven threshold, navigated by Mathematical Programming based on the Duality Theorem in Mathematical Economics, will help nurse executives defend sufficient nurse staffing with scientific justification to ensure optimal patient care; help stakeholders set an evidence-based reasonable economical goal; and facilitate patient-centred decision-making in choosing the institution which delivers the best quality of care.

Conclusions: A new theory to determine the optimum nurse staffing maximizing quality of care relative to cost was proposed.

Keywords: cost; home health care; nurse staffing; nursing; nursing theory; nursing workforce policy; optimization; quality of care; theory synthesis.