| Literature DB >> 28012431 |
Veronica Toffolutti1, Aaron Reeves2, Martin McKee3, David Stuckler4.
Abstract
There has been extensive outsourcing of hospital cleaning services in the NHS in England, in part because of the potential to reduce costs. Yet some argue that this leads to lower hygiene standards and more infections, such as MRSA and, perhaps because of this, the Scottish, Welsh, and Northern Irish health services have rejected outsourcing. This study evaluates whether contracting out cleaning services in English acute hospital Trusts (legal authorities that run one or more hospitals) is associated with risks of hospital-borne MRSA infection and lower economic costs. By linking data on MRSA incidence per 100,000 hospital bed-days with surveys of cleanliness among patient and staff in 126 English acute hospital Trusts during 2010-2014, we find that outsourcing cleaning services was associated with greater incidence of MRSA, fewer cleaning staff per hospital bed, worse patient perceptions of cleanliness and staff perceptions of availability of handwashing facilities. However, outsourcing was also associated with lower economic costs (without accounting for additional costs associated with treatment of hospital acquired infections).Entities:
Keywords: Contracting-out; Hospital acquired infections; Hospital cleaning; Outsourcing
Mesh:
Year: 2016 PMID: 28012431 PMCID: PMC5267843 DOI: 10.1016/j.socscimed.2016.12.015
Source DB: PubMed Journal: Soc Sci Med ISSN: 0277-9536 Impact factor: 4.634
Fig. 1MRSA Incidence Rate by type of cleaning service in 2010.
Mean variation due to contracting-out cleaning services vis-a-vis retaining them in house on MRSA incidence rate.
| Incidence rate of MRSA infection | ||||
|---|---|---|---|---|
| Bivariate association | Adjusted models | Propensity score matching | Heckman selection model | |
| Mean variation due to contracting-out cleaning services vis-a-vis retaining them in house | 0.42*** | 0.22** | 0.29*** | 0.26 |
| – | – | – | 0.71 | |
| Number of Trust-years | 582 | 582 | 446 | 582 |
Notes: Source: Data from Hospital data from Patient Environment Action Teams (PEAT) dataset (from 2010 till 2012), Patient-Led Assessments of the Care Environment (PLACE) (2013–2015), ERIC (Estates Return Information Collection) (2010–2015), NHS Inpatient Survey (2010–2014), NHS Staff Survey (2010–2014), and Public Health for England (2010–2014). Robust SE clustered at Trust level for models 1 and 2 and bootstrapped SE-values in parentheses (250 replications), stratifying by type of cleaning service, for models 3, 4 and 5. Coefficients represent average variation in MRSA incidence rate between Trust which outsource their cleaning services and those which retain their cleaning services in house.The dependent variable represents the incidence of MRSA infection at Trust level. Trust are matched through Matching (model 3) and their distribution are aligned by region, number of beds, number of specialist sites, number of multi sites. After having aligned the distribution we regress, through a linear model, the dependent variable on the number of beds, average length of stay, regional and year dummies.
*p < 0.05 **p < 0.01 ***p < 0.001.
Association of contracting out cleaning services on economic cost outcomes.
| Cost per bed | Staff per bed | |
|---|---|---|
| Mean variation due to contracting-out cleaning services vis-a-vis retaining them in house | -£236*** | −0.01 p.*** |
| Number of Trust-years | 446 | 442 |
Notes: Source: Data from Hospital data from Patient Environment Action Teams (PEAT) dataset (from 2010 till 2012), Patient-Led Assessments of the Care Environment (PLACE) (2013–2015), ERIC (Estates Return Information Collection) (2010–2015), NHS Inpatient Survey (2010–2014), NHS Staff Survey (2010–2014), and Public Health for England (2010–2014). Bootstrapped SE-values in parentheses (250 replications), stratifying by type of cleaning service. Coefficients represent average variation in MRSA incidence rate between Trust which outsource their cleaning services and those which retain their cleaning services in house. The dependent variable represents: cost for cleaning (per-bed column 1, measured in £), staff employed for cleaning per-bed (column 2, measured in people per bed [p]).Trust are matched through Propensity Score Matching and their distribution are aligned by region, number of beds, number of specialist sites, number of multi sites. After having aligned the distribution we regress, through a linear model, the dependent variable on the number of beds, average length of stay, regional and year dummies.
*p < 0.05 **p < 0.01 ***p < 0.001.
Association of contracting out cleaning services with other outcomes.
| Hand-washing availability | Excellent cleanliness bathroom | Excellent cleanliness room | |
|---|---|---|---|
| Mean variation due to contracting-out cleaning services vis-a’-vis retaining them in house | −1.22%*** | −0.45%*** | −0.76%*** |
| Number of Trust-years | 362 | 446 | 446 |
Notes: Source: Data from Hospital data from Patient Environment Action Teams (PEAT) dataset (from 2010 till 2012), Patient-Led Assessments of the Care Environment (PLACE) (2013–2015), ERIC (Estates Return Information Collection) (2010–2015), NHS Inpatient Survey (2010–2014), NHS Staff Survey (2010–2014), and Public Health for England (2010–2014). Bootstrapped SE-values in parentheses (250 replications), stratifying by type of cleaning service. Coefficients represent average variation in MRSA incidence rate between Trust which outsource their cleaning services and those which retain their cleaning services in house. The dependent variable represents: the percentage of staff reporting that hand-washing material is always available (column 1), percentage patients reporting excellent cleanliness of the bathroom they use (column 2) and percentage patients reporting excellent cleanliness of the room or ward they stayed (column 3). Trust are matched through Propensity Score Matching and their distribution are aligned by region, number of beds, number of specialist sites, number of multi sites. After having aligned the distribution we regress, through a linear model, the dependent variable on the number of beds, average length of stay, regional and year dummies.
*p < 0.05 **p < 0.01 ***p < 0.001.