posted on 2020-12-14, 14:43authored byShiovan Ni Luasa
The evaluation of technical efficiency (TE) and its determinants in the Irish nursing home (INH)
care provision is an important research area for a number of reasons. First, Ireland’s population is ageing
quickly, and it is the increase in the ‘oldest’ old that is going to be the most dramatic. Second, all of the nursing
homes (NHs) examined in this research – both public and private – are in receipt of a quasi-subvention by the
state; and third, Irish policy-makers have moved away from the traditional public provision of nursing home
(NH) care in favour of incentivising private delivery. As the costs of long-term care (LTC) are expected to
increase considerably as the population ages, the estimation of technical efficiencies is essential in assessing
whether NHs can utilize their resources more efficiently in order to reduce their costs of care. This research is
the first attempt to investigate the efficiency of nursing home services using Irish data.
This thesis measures and appraises TE in 38 public and 72 private (including voluntary) LTC units in Ireland
using detailed primary data which were collected via face-to-face interviews for the years 2008-2009. The
analysis is input-oriented and hence looks at the amount by which inputs can be proportionally reduced, while
holding output constant. Here output is given by the number of total patient days, while inputs are measured as
medical staff, non-medical staff and the number of beds in a NH unit. This research also considers a case-mix
adjusted efficiency model. The outcomes of this model are compared with the standard approach which does
not adjust for the severity cases of patients. A comprehensive set of environmental variables are employed to
investigate their effect as potential determining factors of efficiency in Irish long-stay facilities. Investigating
the factors driving productive efficiency can assist policy-makers in explaining the possible managerial slack in
the INH sector. Conventional determinants are included such as ownership, size and age along with other firm
characteristic variables, together with output characteristics of NHs such as the HMD rate, chain status, and
numerous quality related factors.
Using a primary dataset for INHs, this study applies a conventional DEA model to identify technical and scale
inefficiencies. Then, both the homogenous bootstrap (HB) and the two-stage double bootstrap (DB) DEA
methods are employed to obtain confidence intervals for the bias-corrected DEA scores. This research compares
the obtained mean technical and scale efficiency scores, and the distribution of these scores for both public and
private (and voluntary) NHs, and also for other subsamples of NHs, such as chain and non-chain private homes,
and urban and rural units. To examine the impact of potential TE determinants, this thesis applies alternative
semi-parametric two-stage methods, such as Tobit regressions and the DB DEA model. Crucially, the DB DEA
integrates the effects of TE determinants as explanatory variables in estimating the true efficiencies. Hence, the
DB DEA method affords bias-corrected DEA scores after controlling for the effects of the efficiency factors.
However, none of the two-stage approaches account for data noise. Hence, a fully parametric SFA input-distance
function is estimated, which controls for data noise and allows us to obtain unbiased TE estimates and
parameters of the determining variables.
The findings of this thesis suggest that the conventional DEA model overestimates both the technical and scale
efficiency of NHs in comparison to the semi-parametric (HB and DB) DEA methods. The SFA method fails to
deliver valid results when output is measured as total patient days, because of convergence issues, which might
be due to the small data sample and the cross-sectional nature of the data. INHs are only 52% to 58% technically
efficient on average, and these estimates are based on our preferred estimation method, the DB DEA. Hence,
NHs in Ireland are considerably inefficient as they could reduce the usage of resources by 42 to 48 % in order
to be technically efficient. INHs are also only 89% scale efficient. The scale efficiency (SE) is higher than the
TE, inferring that the productivity of INHs will result to a greater extent from pure TE improvement rather than
SE. This result coincides with another finding that smaller NHs are more technically efficient than larger homes.
Importantly, the private NHs are more technically efficient than public units. However, case-mix as measured
by the high-max dependency rate of residents has a negative effect on TE and it is higher in public NHs. While
the ratio of medical to non-medical staff, and the labour to capital ratio have positive effects on the TE of INHs,
there is a trade-off between TE and other quality factors, such as staffing levels and staff flexibility. Overall,
the analysis of factors which explain the TE of long-stay facilities in Ireland is important given that these units
are considerably inefficient.