A Systematic Literature Review of Efficiency Measurement in Nursing Homes

Abstract

Background: As our population ages at an increasing rate, the demand for nursing homes is rising. The challenge will be for nursing homes to maintain efficiency with limited resources while not compromising quality. This study aimed to review the nursing home efficiency literature to survey the application of efficiency methods and the measurements of inputs, outputs, facility characteristics and operational environment, with a special focus on quality measurement. Methods: We systematically searched three databases for eligible studies published in English between January 1995 and December 2018, supplemented by an exhaustive search of reference lists of included studies. The studies included were available in full text, their units of analysis were nursing homes, and the analytical methods and efficiency scores were clearly reported. Results: We identified 39 studies meeting the inclusion criteria, of which 31 accounted for quality measures. Standard efficiency measurement techniques, data envelopment analysis and stochastic frontier method, and their specifications (orientation, returns to scale, functional forms and error term assumptions) were adequately applied. Measurements of inputs, outputs and control variables were relatively homogenous while quality measures varied. Notably, most studies did not include all three quality dimensions (structure, process and outcome). One study claimed to include quality of life; however, it was not a well-validated and widely used measure. The impacts of quality on efficiency estimates were mixed. The effect of quality on the ranking of nursing home efficiency was rarely reported. Conclusions: When measuring nursing home efficiency, it is crucial to adjust for quality of care and resident’s quality of life because the ultimate output of nursing homes is quality-adjusted days living in the facility. Quality measures should reflect their multidimensionality and not be limited to quality of throughput (health-related events). More reliable estimation of nursing home efficiencies will require better routine data collection within the facility, where well-validated quality measures become an essential part of the minimum data requirement. It is also recommended that different efficiency methods and assumptions, and alternative measures of inputs, outputs and quality, are used for sensitivity analyses to ensure the robustness and validity of findings.

Assessing the Distribution of Elderly Requiring Care: A Case Study on the Residents in Barcelona and the Impact of COVID-19

“…These facilities would cost a significant amount of money to set up and have significant maintenance costs associated with cleaning and rent. Additionally, as the number of patients admitted to the facilities increases, the quality of service each client receives decreases as the relative space per user drops [ 13 , 14 ]. Each facility has a maximum capacity, and once that capacity is met, they cannot accept any more people.…”

What Counts in Nursing Homes’ Quality and Efficiency? Results From Data Envelopment Analysis in Italy

“… 1 Measuring efficiency and understanding the sources of inefficiencies can help facilities identify how well they are operating in relation to similar organizations and determine where to focus to improve their productivity. 8 For example, an organization was considered technically efficient if it produced the maximum desired outputs from the minimum inputs such as labour, capital, equipment and technology. Typical inputs for a NH are the number of beds, full-time-equivalent staff hours, administration and supplies/consumables.…”

“…The efficiency of a NH is affected by many factors, including resident dependency level, staffing mix, facility location, management and ownership structure, and operational objectives. 1 , 8 …”

“…As integrated approaches, the Tobit regression is among the most used in the literature and as explanatory variables for efficiency score studies usually consider descriptive measures such as ownership, occupancy rate and clinical situation of residents. 8 , 14 , 16 …”

Degrees of Shortage and Uncovered Ratios for Long-Term Care in Taiwan’s Regions: Evidence from Dynamic DEA

“…For variable selection, 16 articles utilized full-time equivalent staff (including nursing and non-nursing) as the input variable, while a few papers took population aged over 84 as the output variable. In the DEA field of research, most articles used several beds, full-time nurses, and labor wage as inputs and the number of resident days, number of residents, or case-mix index as outputs [ 27 ].…”