Comparing Alternate Procurement Operations The Case of Hospital Soft FM Service in England

Transcription

1 Comparing Alternate Procurement Operations The Case of Hospital Soft FM Service in England Alex Murray Teaching Fellow, School of Construction & Project Management, The Bartlett, University College London Amir Mohammadi MSc graduate, School of Construction and Project Management, The Bartlett, University College London Graham Ive Senior Lecturer, School of Construction and Project Management, The Bartlett, University College London Abstract The following paper presents a study of the operational cost and performance of core soft FM services in English hospitals, grouped by procurement method applied. A more precise method for discerning the procurement used for cleaning and catering services was developed, allowing 2 important improvements on previous studies. Firstly, controlling for the approximately one third of PFI contracts which do not include core soft FM services within the scope of the contract. Secondly, this allows the inclusion of services that have been procured via separate outsourced contracts. Data for 2008 is analysed and findings suggest that private provision does improve value for money in some services, notably catering. Samples include facilities of varying age, as exploratory data analysis suggested age of facility was not a valid predictor variable, an issue discussed in within the paper. Theory is considered in terms of incentives and opportunities to invest in operations, specifically the idea that integrated procurement, such as PFI, can deliver lower overall whole life cost from returns in improved operations. Further, the paper provides insight on the variance in levels of cost incurred and performance achieved for large samples of operational facilities, providing an opportunity for further research into other non-procurement determinants of FM performance. Contextual statistics on the prevalence of healthcare facility procurement via PFI are presented, along with suggestions for improvements regarding how public clients might monitor and assess future performance of services. Keywords: Hospital FM, value for money, PFI, outsourced, procurement.

2 1. Introduction There are now over 700 signed UK PFI contracts with great diversity in duration, size and scope. According to the latest Treasury PFI signed projects list, financial close has been met on projects which have already, or are soon to deliver in the next few years over 50bn in contract capital values (not indexed, HM Treasury, 2013). While this sum seems vast, we should maintain context that this is actually a relatively small proportion of total Government funded investment in gross fixed capital formation (ONS, 2006). The UK Coalition Government recently re-launched PFI following a lengthy review of the role of private financed in publicly funded capital investment (HM Treasury, 2012), yet the role of private finance remains a relatively new experiment in public procurement. Considering the significant sums of tax receipts required to fund these projects, assessments of their operations are imperative to assess PFI s effectiveness in achieving value for money (VfM). The National Audit Office shares this ambition: there is a pressing need for better quality evaluation of private finance and other forms of procurement Government need particularly to ensure that they can compare the benefits and costs of different procurement routes. (NAO, 2009a, pg 4) In light of this, the following paper seeks to provide an insight on cost and quality of core soft FM services within operational healthcare facilities. Specifically, the focus is on cleaning and catering. In addition to observing services provided within PFI facilities, data was sourced to allow comparisons of services provided in house by the public sector, as well as via outsourced contracts with the private sector. Analysis of soft FM services is imperative to those PFI contracts that include accommodation elements, such as schools and hospitals, as such services will require relatively larger proportions of committed resources over the life of the asset to maintain contracted levels of service. 1.1 Contract scope PFI is characterised as being a form of integrated contracting, meaning it combines the responsibility for both construction and operations of a facility under one contract (Hart, 2003; Hart et al., 1997). The scope of these operations vary greatly between contracts (as do the capital assets commissioned), and as such it is not surprising to point out that approximately one third of the hospital contracts operational in 2009/10 were found not to include cleaning and catering within their scope (NAO, 2010). Previous analysis of these services were unable to control for this issue of inconsistent scope between contracts (Ive et al., 2010; KPMG, 2010). Since these analyses, the required data has been accessed to control for this issue, as well as sufficient data developed to include assessment of separately outsourced services. The following analyses seek to provide insight on the issue of whether procurement method has an impact on operational service cost and quality, and hence indicate the VfM achieved.

3 2. Theoretical context of PFI soft FM services The following discussion focuses on the particularities of soft FM services within PFI contracts. An important distinction includes the difference between some forms of integrated contracts, which include only the Hard FM aspects of operations (M&E maintenance, hence DBFM), and those including a range of soft FM services, such as cleaning and catering (DBFO). There is also range in the scope of soft service provision, some contracts not including IT support or laundry within a hospital for example. This is important, as the potential for savings to be made from investment in operations will depend on contract scope. Improvements in operational services (lower cost or improved quality) may result, for example, from opportunities to locate some services off site (e.g. catering), or potential improvements of facility logistics for movement of resources around the facility. Based on the example below, it is reasonable to expect soft FM services typically ranging between 20-30% of the UCP, so significant sums of public money are at stake (NAO, 2007a, pg. 5). Figure 1: Breakdown of Darent Valley hospital Budgeted Unitary Charge Annual PFI Cost ( 19 million p.a.) (NAO, 2007a) With integrated contracts, the SPV takes the risk for cost of construction and operation of the asset, as well as associated financing costs. Operational costs are downwardly constrained by the quality of service they have agreed to provide in the output specification of the contract (Murray et al., 2012). Non-adherence to these levels of provision incurs prohibitive financial penalties. In this sense, there is an exception for Soft FM services whose price (what SPVs charge, rather than what it costs to provide) is open to a form of negotiation usually every 5 7 years. This periodic reassessment of the price of soft services is referred to as the benchmarking and market-testing procedures (BM&MT), which attempt to maintain VfM (NAO, 2007b). Ironically, this pursuit of VfM may limit the extent to which whole life cost risk is actually transferred, undermining the core business case for applying PFI. The relative benefits of alternative procurement methods is fundamental for public clients to consider, as explored in some insightful studies (Bajari and Tadelis, 2001; Ive and Chang, 2007). Further, the extent to which there is incentive to invest in operations will also depend on the ownership structure within the SPV. Whoever owns the sub-contractor providing the operational

4 service, and has an equity stake within the SPV (typically 10% in total with other shareholders), will have two sources of financial return. These include the profits from their present provision of operational services and future shareholder returns from investments in the longer-term project. The hard FM subcontractors are typically owned by a company that is an equity owner in the SPV, the externalities between design / construction improvements and building operations being arguably greater for hard FM services than for soft FM. Problems arise when opportunities to reduce WLC for soft FM services become apparent expost. If capital sums are required to achieve this (e.g. re-configuration of internal layouts or procurement of additional long-term fixed capital), there is reduced incentive to incur sunk costs given the potential future competition introduced via BM&MT. This is pertinent given the likelihood that WLC reducing innovations may result from accumulated knowledge about operations of often unique facilities (Grant & Ries, 2013). Such innovations can only be assessed during operations, and so are difficult to specify ex-ante contractually. One might imagine an outsourced contractor who is not a shareholder having little incentive within their short-term contract of typically 2-5 years to undertake WLC reducing investments in fixed capital, which might reasonably depreciate over a 10 year period. A further point concerns the limits to which well anticipated ex-ante whole life cost innovations are achieved in the context of extensive sub-contracting in non integrated forms of contracting (Rintala, 2004, pg. 45). The financial consequences for the SPV if underperforming in operations are less than if during construction, as without commissioning UCPs will not begin to flow. Conversely, with sub-par operational services you are likely only to incur part deductions. For that reason, you might expect to see a smaller differential between contracted operational service prices in PFI and those in the open market for outsourced soft FM services, especially when compared to the construction elements of contracts where there is greater risk transfer. This credible risk transfer in PFI construction is well evidenced (NAO, 2009b, 2003), as yet to be so objectively analysed in operational services. Price differentials for operational service contract may be down to superior performance of some PFI services (Mohammadi et al., 2013; KPMG, 2010). 3. Method 3.1 Data sources The principal source for data in analyses is the NHS maintained Hospital Estate and Facilities Statistics (HEFS) site level report for This provides cleaning and catering cost data, cleaning performance indicators (NHS National Specification of Cleanliness (NSC) scores), as well as crucial data on site level facility characteristics including size and age asset profiles. Additional data on quality of service indicators, in the form of patient environment ratings (in part resulting from cleaning services as well as physical maintenance of surroundings) and catering service ratings, was sourced from Patient Environment and Action Team (PEAT) reports from 2008 for service indicators, and 2010 for data to help allocate procurement method (as this is only available from 2010 onwards).

5 3.2 Variables 1 Cleaning cost: produced by dividing headline HEFS site level Cleaning services cost by Occupied floor area giving an annual m 2 cost of cleaning variable. The latest year available is 2008 as a result of surprising reductions in the publication of data on hospitals facilities. Cleanliness: a percentage score assessment against the NSC. This is produced via selfassessment by NHS Trusts, entailing a pass or fail audit of 49 elements, such as cleanliness of fixtures and fittings and equipment available in the hospital. Cost per patient meal day: a direct read off of the HEFS site level report cost of feeding one patient per day (patient meal day) ( ). No normalisation was required for this variable as it is already in per patient per day format. Patient environment and food ratings: patient environment ratings, published by what was the National Patient Safety Agency (NPSA), are results of assessments against non-clinical service aspects of patient surroundings taking into account organisational policies, cleanliness, infection control, environmental aspects and conditions in access/external areas. Food ratings are similarly assessments of aspects of the quality of catering provision. 3.3 Sampling process The site level HEFS reports formed the basis of the 2008 sample of sites. The process involves removing all sites where patients are not treated and accommodated, as well as those that are unclassified, reducing 1,965 sites down to 1,052. This leaves those hospitals classified as Community, General acute, Long stay, Multi-service, Short term non-acute and Specialist. Exploratory data analysis revealed that using facility age (as measured by detailed age asset profile data within HEFS reports) as a predictor variable for both cleaning services cost and quality (NSC) did not produce a significant result (see analysis below). As a result of this finding, analyses proceeded to include older facilities within the analysis to increase sample sizes and the likelihood of findings effects resulting from procurement associated differences. These older facilities are notably present in the large samples of facilities where services are provided in-house. 3.4 Procurement route Procurement route applied in each facility was determined by reference to multiple sources, including: a list of PFI healthcare facilities made available by the NHS information centre; site level returns to the PEAT report in 2010; as well as a dataset derived from responses to the 2010 NAO survey of operational hospitals PFI contracts. Access to the final source was kindly 1 For brevity, readers are encouraged to read (Ive et al., 2010) for further discussion of variables analysed and detailed sampling process applied.

6 granted by the NAO under a freedom of information request. The years of these reports are different due to data availability. There is a key assumption that allows this empirical analysis, this being that the reported procurement method in 2010 from the NAO survey and PEAT reports is the same as the procurement method applied two years previous in 2008, when the service cost and quality indicators are available. This is a reasonable assumption given the relative infrequency in changes of procurement for operational services once in operations. 4. Analysis and results For brevity of this paper, analyses are presented graphically and then discussed briefly with reference to observed inferential statistics (ANOVA analysis). 4.1 Age of facility against cost and performance Figure 2 & 3: Normalised cleaning cost to facility age by procurement (2008) Figure 4 & 5: NSC audit score to facility age by procurement (2008) As can be seen from the above analysis, the impact of facility age, as measured by what proportion of the facility was built post 1995, on cost of cleaning and resulting NHS NSC score (%) is seemingly negligible. There is no evidence to accept that older facilities, by these measures of resource allocation and service performance, perform any worse. This finding goes against conventional thought, as one of the primary reasons to renew a building is to improve its performance. While surprising, this finding supports the author s decision to continue to include older facilities within proceeding analyses.

7 Propor on of sample (%) 4.2 Cleaning services Figures 6 & 7: Cleaning costs distribution and NSC by procurement (2008) 2 The analysis of the distribution in cleaning costs between the three procurement types indicates no obvious difference. In interpreting these results it must be remembered that the in-house sample is much larger (at approximately 335 facilities depending on outlier policy applied) than the outsourced (about half at approximately 160 facilities) and the contracted PFI sample (about one tenth at approximately 35). Hence, it is not surprising we observe more outliers in the inhouse sample, many of which may be more easily explained with reference to the particular context of that facility. For example, many mental health facilities are more likely to have services provided in-house, and such are expected to incur higher costs given the stricter requirements of their operations. This visual finding for cleaning cost is supported by ANOVA results that fail to reject the null hypothesis (smallest observed p-value is 0.39 with the strictest outlier policy applied). However, the ANOVA on NSC scores reveals that differences are significant, and that outsourced and PFI contracted cleaning services are associated with better average NSC audit scores than where cleaning services are provided in-house (p-value < depending on outlier policy applied) Patient environments inhouse n = 329 outsourced n = 155 contracted = Acceptable or worse Good Excellent Figure 8: Patient Environment ratings distribution by procurement (2008) 2 Contracted refers to PFI procured facilities

8 Propor on of samples (%) The figure above suggests that similar proportions of the three samples are within each of the three performance categories, though in-house performs a little worse with higher proportion of its sample in the Acceptable or worse rating. Performing a simple chi squared analysis to provide a statistical finding reveals a p-value of 0.22, so again we failed to reject the null hypothesis of no difference in performance between procurement method applied, in terms of which promotes more favourable patient environments. 4.4 Catering services cost and performance inhouse n = 315 outsourced n = 159 contracted n = Acceptable or worse Good Excellent Figures 9 & 10: Catering cost & performance dist. by procurement (2008) A visual inspection of the above cost analysis suggests in-house provision of catering services varies greatly in cost per patient meal day. As mentioned, this will in part be down to the greater sample size, but that issue aside the lack of outliers in the contracted PFI sample is notable, especially on the upper bounds of the distribution. The statistics support that private provision of catering services is cheaper than in-house (p-value < 0.05). A chi squared analysis of the food ratings above delivers a p-value of 0.845, suggesting that we can not reject the hypothesis that the above distributions of the three procurement methods over the range of performance levels are sampled from the same population distribution, that is, there is seemingly no difference in service performance. With the strong result for lower cost of catering services when they are provided privately as part of an outsourced contract or integrated into a PFI contract, these findings suggest private catering services provide better VfM than publicly provided catering services. 5. Discussion The lower level of outliers (higher and lower values) in cost measures for the PFI samples could be interpreted as providing greater cost certainty for services. This is characteristic of PFI in that it passes cost risk for delivery of specified levels of service. This might not necessarily be the case with an outsourced arrangement where the contract is more input based (PFI being focussed around an output specification), where the client may often ask for ad hoc additional resources to be allocated to ensure quality of service. It should also be noted that many of the newer PFI hospitals include the larger General acute facilities, which may reasonably provide

9 significant scope for economies of scale for services such as cleaning and catering. Hence, it may not be the procurement type driving lower catering cost but rather facility type. Another potential source of the observed lower catering costs might be the presence of returns from investment in operations, which one would expect to continue to be realised in the PFI contracted facilities. Whilst we do see significantly lower cost for PFI catering services compared to in-house provision, the similarity seen between both types of private provision suggest a minimal presence of these returns, given that outsourced contracts are shorter term yet still achieved similarly low service costs. As for why we have not observed differences in cleaning services but have in catering, one explanation may be greater potential for capital-intensive processes in catering when compared to more labour intensive cleaning provision. Private providers are more likely to seek and consider more capital-intensive methods given their greater freedom and incentive to appropriate returns from investments in operations. This aspect will be limited by the term of the contract and so the opportunity to recoup investment in capital. Conversely, a counterfactual to this restriction includes the factor mobility of machinery and equipment that can reduce cost, given that many large service contractors will have multiple contracts within close proximity to one another. The data presented is for a particular year (2008) due to limitations in the availability of time series data. In light of the data transparency policy of the recent UK Coalition Government, it is noted that this is one sector where data availability has declined, rather than improved. Given the need for local public clients to monitor service performance and central authorities to maintain a portfolio perspective, it is hoped non-public datasets are of much better quality for appropriate assessment of on-going VfM. This likely varies greatly by Trust and facility. Finally, given this research observes that PFI soft FM services are of equal or better quality and incur no greater cost generally, thus supporting better VfM, it is questionable why new PF2 contracts will not be allowed to include soft FM services within their scope (HM Treasury, 2012). Given these findings, this suggests a potential lack of evidence-based policy in this area. 6. Conclusions and further research The first surprising result of these analyses is that facility age seemingly has little impact on as measured cost or performance. The measure of NSC performance is not completely objective and so could be open to potential measurement biases that may partly explain this result. However, cost data should bear out the benefits of newer facilities. That said, recent PFI facilities aside, new facilities are not necessarily designed to benefit the cost (inputs) and performance (outputs) of FM services, but rather the outcomes of users (practitioners and patients), an aspect beyond this papers scope. The main finding is that procurement does seem to have an impact on service cost and performance. Private provision is associated with higher NSC audit scores in cleaning services,

10 despite similar levels of cost. In catering, benefits of private provision are not in better quality services, but lower cost, indicating overall improved VfM. The differences between outsourced and PFI contracted services are marginal, suggesting that there is little or no evidence to support the notion of returns from investment in operations. However, we are at present limited in our ability to observe these returns due to the poor availability of data on when new facilities are commissioned, preventing superior comparative lifecycle assessment. It is hoped soon to be published data on FM outputs in schools 3 will allow a study providing a more sophisticated analysis on returns from investment. Further research which could provide significant insight involves breaking down these samples between different hospital types to ascertain which facilities are associated with higher services costs and performance indicators. These could serve as potentially useful benchmarks for public sector clients to compare the performance of their services to for means of more contextually sensitive contract re-negotiations. References Amir Mohammadi, Alex Murray, Andrew Edkins, Value for Money in Hospital Facilities Management: The Evidence. The Infrastructure Forum. Grant, A., Ries, R., Impact of building service life models on life cycle assessment. Building Research & Information Vol. 41, pgs Bajari, P., Tadelis, S., Incentives versus Transaction Costs: A Theory of Procurement Contracts. RAND Journal of Economics. Vol. 32, No. 3, pgs Hart, O., Incomplete Contracts and Public Ownership: Remarks, and an Application to Public Private Partnerships. The Economic Journal, Vol. 113, pgs Hart, O., Shleifer, A., Vishny, R.W., The Proper Scope of Government: Theory and an Application to Prisons. Quarterly Journal of Economics. Vol. 112, pgs HM Treasury, A new approach to public private partnerships. HM Treasury, PFI signed projects list March Available at: [Accessed: September 15th, 2013] Ive, G., Chang, C.-Y., The principle of inconsistent trinity in the selection of procurement systems. Construction Management and Economics, Vol. 25, No. 7, pgs Department for Education Property Data Survey Programme data, due for already postponed release in 2015.

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