Demand for long-term care services is projected to increase in most developed countries due primarily to improved life expectancy, which will place increased pressure on public expenditure (European Commission, 2018). Expectations about the quality of care are also continuing to grow. Both these factors, combined with austerity in spending programmes, are generating pressing questions about the most cost-effective use of resources (Knapp, 2013). Prevention is increasingly considered an essential dimension of social care. The underlying assumption is that preventive services will promote individuals’ well-being, quality of life, health and independence which, in the long term, will reduce demand and lower overall costs (Kumpers et al., 2010).
The development of prevention in adult social care (ASC) in England has been a prominent policy emphasis over the last decade (HM Government, 2006; HM Government, 2007; Think Local Act Personal, 2011; Department of Health, 2010). The Care Act 2014 identifies ‘promoting individual well-being’ and ‘preventing needs for care and support’ as the first two of seven general local authority responsibilities. The statute imposes a duty on councils to identify existing services, facilities and resources with which to fulfil this new duty (HM Government, 2014). Furthermore, the Care and Support Statutory Guidance noted that ‘at every interaction with a person, a local authority should consider whether or how the person’s needs could be reduced or other needs could be delayed from arising’ (Department of Health, 2014, p.3). The advocacy of prevention in ASC is not new (Wistow and Lewis, 1997; Godfrey, 2001; Department of Health, 1998) but the 2014 Act is the first to make prevention a statutory responsibility in ASC.
The Care Act implementation guidance recognised that preventative goals required the involvement of many services including public health, the NHS, transport, leisure, housing and the voluntary and community sectors (Department of Health, 2014). This emphasis on inter-agency partnerships to promote preventative approaches reflects the need to draw on a wider range of potentially lower cost resources and, further, is an expression of the need to mitigate the combined impact of fiscal austerity and population ageing (Miller, 2014). In practice, evidence supporting the (cost) effectiveness of joint services is limited and often shows mixed results (Mason et al., 2015; Damery et al., 2016). Evidence about how Councils implement prevention with health partners is a particularly serious gap (Miller, 2014).
Despite successive governments’ advocating prevention in ASC since the late 1990s, its meaning remains elusive and, in practice, the term has described a wide range of objectives and interventions. The concept of prevention has a longer history in public health — and subsequently the NHS — than in ASC. In the health field, its definition and scope have expanded over the years from one of focussing on risk factors associated with specific diseases and limiting the progression of such diseases to include a focus on reducing the consequences of disease and disability and on addressing health inequalities (Starfield et al., 2008). It is also argued that prevention is a social good, in itself, and should be applied generally and not only in health and social care settings (Ataguba and Mooney, 2011). One early approach in social care was to adapt the public health framework of primary, secondary and tertiary prevention1 (Lombard, 2013; Gordon, 1983; ADSS, 1999). However, Godfrey (2001) warned against transferring health concepts of prevention to social care without a theoretical framework capable of understanding risk within a wider psycho-social context. Wistow and Lewis (1997) proposed a two-fold definition of prevention specific to social care, which included the following:
The first part of this definition could be seen as person-centred and resource-focused, since it combines evidence suggesting that people preferred to live in their homes rather than institutions (Ryan et al., 2009; Allen et al., 1992; EHRC, 2011) with aspirations to reduce institutional care spending. This apparently fortunate coincidence of personal and organisational objectives has continued to underpin much of the subsequent policy interest in prevention (Knapp, 2013; Miller and Allen, 2013; Allen and Glasby, 2013). The Care Act 2014 embraces the second, broader definition of prevention, which encompasses social inclusion, empowerment, health, social and economic wellbeing. The Care Act Statutory Guidance (Department of Health, 2014) also notes that there is no single definition of prevention and that different local approaches may be developed to fulfil councils’ legal duties around prevention. Nonetheless, to the extent that clarity about what constitutes prevention remains lacking at either the national or local level, what is to be evaluated will remain unclear and the development of local evidence about its effects will be hindered.
The adequacy of ASC funding has been of concern, particularly because of rising demands due to ageing populations combined with sustained financial austerity (Fernandez et al., 2013; Charlesworth and Thorlby, 2012; LGA, 2017). Data show that net current spending on ASC fell by 8.4% in real terms between 2010/11 and 2016/17 (Cromarty, 2017). Although the Association of Directors of Adult Social Services emphasise the importance of prevention in reducing demand, its 2016 Budget Survey reported that councils were reducing funding for prevention to meet the costs of core statutory duties (ADASS, 2016). Observers have noted that the Care Act failed to recognise the limited budgets that authorities are working within, and the consequential constraints on the implementation of new statutory duties, including prevention (Slasberg and Beresford, 2014, Richards and Williamson, 2015). As financial resources have been more constrained, local governments have responded in different ways, ranging from cutbacks and retrenchment to finding innovative ways to improve organisational performance (Overmans and Noordegraaf, 2014; Lowndes and McCaughie, 2013; Hastings et al., 2015). For example, collaboration between services and sectors have been advocated as an important tool for improving resource utilisation and generating new capacities (Lowndes and Squires, 2012). Moreover, local governments’ responses to austerity tend to be influenced by a range of external factors, including local population structures and demands, relationships with local communities and the history of joint working between agencies, as well as internal factors like leadership skills and spending flexibility (Cepiku et al., 2016).
On paper, however, councils reported increasing levels of implementation readiness. The Care and Support Act Implementation Stocktake reported that, by June 2014, 44% of councils were either prepared or had made progress to implement the prevention vision of the Care Act2, while 39% were at an early point of progress in preparations (LGA, 2014). A year later, 64% of authorities reported having a cross-organisation prevention strategy and 81% had arrangements to identify people who would benefit from prevention (LGA, 2015).
Despite continuing policy expectations that preventative care will deliver cost-savings to ASC and wider systems, formal evidence is neither extensive nor robust. Literature reviews emphasised that evidence about what works in prevention remained under-developed with the result that local policy makers lacked information about how to invest their resources optimally (Allen and Glasby, 2013; Miller and Allen, 2013; Curry, 2006). The need ‘to improve the way evidence is accessed and used’ led the Department of Health to support the establishment of a Prevention Library as a single, accessible source of evidence for prevention (HM Government, 2012, p.26). The Library has concentrated, so far, on largely descriptive accounts of emerging prevention-related interventions. The Library currently contains little evidence of the impact of preventative interventions on costs and outcomes, or their optimal targeting on individuals with particular combinations of needs (https://www.scie.org.uk/prevention/, last accessed 24th September 2019). The limited existing evidence is concentrated on the areas of: reablement (see, for example, Glendinning et al., 2010; Francis et al., 2011) telecare (Steventon and Bardsley, 2012; Henderson et al., 2014; Hirani et al., 2014; van den Berg et al., 2012; Barlow et al., 2007), falls prevention (Keall et al., 2015; Farag et al., 2015; Gillespie et al., 2012) and various forms of community interventions (Cook et al., 2013; Windle et al., 2011; Haslam et al., 2014; Skingley et al., 2015; Lawlor, 2014; Jopling, 2015; Kinsella, 2015; Cattan et al., 2008). Evidence of cost-effectiveness is, however, scarce (for exceptions see, for example, Knapp et al., 2010; Henderson et al., 2014; Windle et al., 2009). Moreover, the available evidence may not be transferable to unique local contexts and more local evaluations are needed to support judgements about the most cost-effective targeting of limited resources. In summary, the implication of the above literature is that local authorities have relatively few evidence sources to assist them to make informed investment decisions in support of their new statutory duty towards prevention.
Reporting on the experiences of six councils implementing preventative schemes, Miller et al. (2015) noted the challenge of developing prevention evaluation frameworks due to data and resource limitations, even though councils recognised the importance of understanding prevention effects. The study reported on the development of community-based approaches to prevention based on mobilising local assets. Such approaches are illustrative of the range of prevention initiatives across England and reflect the Care Act’s recognition that preventative models should differ according to local needs, partnerships and community resources. In these circumstances, they argue, an essential step in developing local evaluation frameworks involves better understandings of: how different authorities translate prevention strategies into operational practices; and how far they have access to data to assess interventions’ effectiveness in their particular context.
Against this background, an exploratory study was conducted in six authorities to investigate how existing local approaches to prevention across ASC, including policy objectives, expected outcomes and associated information capabilities, support prevention duties. The study was intended as a first step in developing locally appropriate evaluation frameworks to support evidence-based commissioning and the targeting of local prevention initiatives.
This paper aims to answer the following questions:
This paper draws on findings from a broader study focussed on securing a better understanding of factors important for developing a local prevention evaluation framework. The detailed description of the study and its findings can be found in Marczak, Wistow and Fernandez (2019). Here we use data collected in that study through the following instruments: a rapid literature review of the evidence on prevention and cost-effectiveness; a documentary review of local policies related to prevention within the case study local authorities and a review of their relevant data collection; and in-depth interviews in sampled local areas. We discuss each of these instruments next.
We conducted a rapid review of evidence relating to the implementation of prevention in social care and its effectiveness. Academic and grey literature were included in the review if it discussed evidence on outcomes, costs and/or cost effectiveness of specified preventative services. Twenty-three papers published between 2000 and 2014 were initially included; an additional six papers published in 2015 were subsequently identified and added in 2016. The searches were conducted using the following online databases: Kings Fund, ScienceDirect, NICE, RiPfA, Google Scholar, PubMed and Cochrane. Searches were carried out on the title and abstract of papers. The key words were used flexibly in different combinations. Overall, three sets of keywords were combined relating to: 1) nature of the interventions, e.g.: prevention, reablement, falls, befriending, community navigators, isolation, etc. 2) policy area, e.g.: social care, long-term care, dependency, disability, aged care, etc. 3) costs and outcomes, e.g.: costs, cost-effectiveness, efficiency, savings, effectiveness, outcomes, wellbeing, satisfaction, quality of life, independence, Activities of Daily Living (ADLs), etc. The results informed the background section above and assisted in the design of topic guides and the analysis of documents describing prevention objectives and priorities in the six authorities included in the study.
For the six authorities, we reviewed Joint Health and Wellbeing Strategies (JHWS), local prevention strategies where available, ASC strategies and any other local policies which shed light on councils’ approaches to prevention (see Table 1 for local documents reviewed). Documentary analyses also provided interview questions and prompts for the interviews, which helped us to secure richer understandings of the characteristics and impact of local policy contexts.
|No||Type of local authority||Informants’ roles||Policy Documents reviewed in each of the authorities|
|LA 1||Metropolitan Borough||R1: Head of Service, Access and Prevention, Adult Social Services
R2: Information Analyst
|LA 2||London Borough (outer)||R1: OT Professional Lead, Commissioning||
|LA 3||London Borough (outer)||R1: Promoting Independence Programme Manager
R2: Promoting Independence Officer
Adult Social Services, Health and Housing
|LA 4||Metropolitan Borough||R1: Assistant Director, Older People and Personalisation
R2: Head of Service, Housing Support
R3: Business Intelligence Manager
|LA 5||A Non-Metropolitan County||R1 and R2: Strategic Development Managers in Adult Social Services||
|LA 6||Metropolitan Borough||R1 and R2: Market Manager and Strategic Commissioner responsible for prevention
Joint Commissioning Team, Health and Social Care
Assessing cost-effectiveness in prevention can be particularly challenging due to the multidimensionality of outcomes involved, long time periods required to assess outcomes and savings from preventative interventions, and because the data required to measure what would have happened in the absence of preventative services are difficult to obtain (Miller and Allen, 2013; Knapp, 2013). To explore the potential for local data collections to inform the continued evaluation of the cost-effectiveness of prevention, we examined local data collection processes and analytical strategies. We reviewed blank assessment forms used by councils to record assessments of user needs and eligibility for services. In addition, we examined the kinds of data councils gathered about service receipt and client outcomes.
In-depth, semi-structured interviews were used to explore how prevention was understood in each area from different professional perspectives and to investigate whether, how and why evaluation processes were conducted at local levels. The interviews enabled us to ask broad questions based on the research objectives highlighted above and also to probe and clarify informants’ responses (Lincoln and Denzin, 2000; Ritchie and Lewis, 2003; Patton, 2002). Respondents were asked to elaborate on the local understanding of, and the goals associated with, prevention, local prevention policies, commissioning of preventative interventions and collaboration with other agencies. For example, although initially a broad question in relation to understanding prevention was asked, prompts were then used to elaborate on the responses. We also asked about key activities related to on-going evaluations of prevention, including services covered, outcomes prioritised, indicators adopted, cross-agency analyses, degree of computerisation, frequency of data collection and existence of additional evaluations of their prevention initiatives.
An end-of-project workshop was held with participating authorities to discuss the overall findings of the project.
The sample of Local Authorities for the case studies was a convenience one. Email invitations with information about the project were sent to managers and commissioners in the authorities identified through the research team’s knowledge of individual authorities’ work on prevention in ASC, together with other colleagues’ experience of collaborating with them in the past. Key considerations included the ability and willingness of authorities to participate in the study at a time of substantial demands on their workforces. In addition, we aimed to cover a range of local authority types and geographical locations. The final sample includes examples of the main categories of local authorities in England, such as metropolitan, London boroughs and a non-metropolitan county. Constrained by the limited availability of respondents within the narrow timeframe for data collection, we sought to capture a range of perspectives on prevention across all six councils, including senior and middle managers, commissioners and analysts. One council declined to provide in-depth information about evaluation methods and analytical capabilities so we were restricted to collecting information on local policies and practice. In total, we interviewed twelve key informants in six authorities (see Table 1). Interviews were conducted by the authors between March and May 2014; four were by telephone and the remainder in person.
We obtained ethical approval from the Health Research Authority’s Social Care Research Ethics Committee, reference 14/IEC08/0008 and informed consent to participate and to record the interviews was obtained from all respondents prior to interviews. Respondents were provided information verbally and in writing about their rights and the obligations of the researcher, as well as given an opportunity to ask questions before consenting. The names of authorities and interviewees were replaced by a code to protect their confidentiality.
Interviews were recorded, transcribed verbatim and material was entered into qualitative data management software: NVivo 10 (QSR International Pty Ltd., 2014). Thematic analysis was used to organise data systematically by focusing on identification and reporting of patterns and themes across the whole dataset to interpret the material (Boyatzis, 1998; Braun and Clarke, 2006). Initial codes were generated by breaking the transcripts’ down into smaller components, coding them in a systematic manner across the whole dataset and collating passages relevant to each code. Coded data were used to develop themes. Preliminary themes were identified against our core research objectives and question guide topics. Preliminary themes were then checked by reviewing each coded passage under each theme to ensure that the coded passages gathered under the themes formed a coherent pattern. Codes that did not fit preliminary themes were reviewed and either assigned to different themes or new themes were generated. More systematic thematic analysis required coding each document systematically and was not a practical or efficient option for analyzing so wide a range of documents in this small scoping study. Some texts included substantial amounts of data not directly relevant to prevention. Consequently, the authors focused selectively on extracting and analyzing only those parts of the documents that they collectively judged relevant to the study. The authors thus reviewed local policy documents and assessment forms manually.
Care has been taken to draw on quotations and evidence from the interviews and documentary analysis from a wide range of Councils and informants to avoid overemphasis on individual case sites. Nevertheless, the exploratory nature of the study and the small sample size limits the generalisability of its findings.
This section begins by reporting local understandings of the concept of prevention and the content of associated policies. Next, we consider the role of integration in prevention as part of a wider discussion of commissioning prevention. We subsequently review the evaluation processes and methods employed by different local authorities. Finally, we report on how local council utilise existing evidence on prevention to inform their investment strategies.
Three of the six ASC departments reported that they had prepared formal prevention strategies. Where authorities did not have freestanding prevention policy or strategy documents, prevention objectives were included in plans for specific services or user groups. In such cases, however, respondents suggested that the lack of an explicit policy framework was a barrier to a clear conceptualisation of prevention and thus to the effective implementation of preventative objectives and interventions. Indeed, some respondents attributed the lack of explicit conceptualisation of prevention to the fact that the national and local commitment to prevention was more rhetorical than tangible. Furthermore, such respondents believed that the lack of clarity about the meaning of prevention further hindered efforts to translate preventative policies into everyday practices:
People talk about prevention and say we are doing it but unless it is really clear what that means…you cannot change your practice… If you just say things are preventative, my understanding of preventative, your understanding, somebody else’s understanding is open to interpretation. (R1, LA2)
Goals such as promoting social and economic wellbeing, improving health, independent living, community resilience and social inclusion were all highlighted in prevention policies. Although it was not always clear how respondents derived their definitions of prevention, increasing demand for services and decreasing financial resources appeared to play important roles since the major conceptualisation of prevention was related to its potential to reduce demand for social care:
It [prevention] is all about cost…It is about saving money… (R2, LA6)
…in terms of reduced costs, reducing demand for statutory services…those two [goals] are very much at the very top. (R1, LA3)
Respondents did recognise that prevention strategies should also aim to improve the quality of life and wellbeing, but they frequently reported that financial austerity was shifting the focus of senior management priorities away from a twin track approach towards one with an overriding emphasis on cost reduction and demand management.
Different understandings of prevention translated into divergent opinions about the types of services considered to have preventative effects. Existing evidence about prevention effectiveness appeared to play some role in respondents’ responses as some advanced a relatively narrow definition that depended on the existence of evidence that particular interventions (e.g. reablement) could prevent or delay the development of (higher levels of) needs. Others defined prevention as a broad umbrella term to describe a wide range of interventions that could be demonstrated to promote independence and wellbeing:
Apart from reablement and telecare we do equipment…it is not clear whether equipment is preventative… there is no evidence to suggest that equipment in itself prevents further services being required. (R1, LA1)
All of our services are preventative…particularly if you are looking at that kind of high definition [of prevention] around wellbeing and independence etc. (R1, LA3)
Different conceptualisations of prevention and perceptions of which services were preventative and which were not, influenced understandings of the key evaluation questions to be addressed, the outcomes to be measured and the relevant tools for data collection.
Two out of three prevention strategies which had been developed within the six authorities were prepared jointly with partners such as Clinical Commissioning Groups (CCGs) (NHS organisations who purchase local health care), public health departments (also located within local authorities) and voluntary organisations. A number of relevant interventions were commissioned and/or provided jointly with other agencies in the voluntary, private and public sectors including: health care, public health, housing and transport services. The degree of partnership varied and collaborative working was said to be most frequent in services for people with mental health needs and learning disabilities. One authority invested in and monitored telecare, telehealth, falls prevention and reablement jointly with the NHS. In some authorities, the transfer of responsibility for public health from the NHS to local government appeared to have begun to facilitate opportunities for developing more integrated approaches to prevention.
However, in one locality a prevention strategy led by public health through a Health and Wellbeing Board provided an example of how public health and ASC could collaborate to align prevention objectives and implementation frameworks. The strategy’s goals focused on ensuring that older people were safe and independent by seeking to reduce social isolation and loneliness, and by providing care and support in the community, including adequate housing. It indicates a possibility of a system-wide perspective on prevention and demonstrates that local authorities can successfully bring together their public health responsibilities and capabilities with an ASC approach to prevention. However, partnerships with other NHS agencies were reported to have been less successful in this locality:
R2: public health, they are getting it because they are part of council…certainly they support prevention… I am not sure whether the rest of health is on the same page…
R1: We tried with our assistive technology, but it has been difficult to engage our health colleagues…most of the engagement with health tends not to maximise that preventative side. (LA4)
Such shortfalls in collaboration with health partners could seriously undermine the potential of partnerships to help councils make better use of limited resources and generate innovative interventions and capacities (Lowndes and Squires, 2012).
Three local authorities shared aggregate data with the NHS linked to specific services, i.e. hospital discharge or reablement and one council was focusing on linking its case management data with primary care records. Individual-level data was not generally shared between the councils and the NHS, due to information governance issues and the continuing absence of data sharing protocols. Incompatible IT systems hindered integrated working. Different priorities, organisational processes, planning cycles and weak communication between social and health care professionals were also described as potentially creating conflict rather than collaboration. Lack of managerial commitment and cultural obstacles were reported to hinder data sharing:
It [data] tends to be used internally, as a rule it does not tend to get shared across agencies, not for any reason apart from they are not particularly interested in the data from us. (R2, LA1)
Notwithstanding these challenges, informants recognised the importance of inter-agency collaboration in sharing individual-level data to secure better understandings of potential returns across care systems from investing in prevention. Informants often suggested that the Better Care Fund3 provided a promising platform for data sharing and establishing how far whole systems benefits flowed from investments in prevention by ASC approaches. Partnerships have thus the scope to be a vital element in delivering an effective prevention agenda.
All councils collected quantitative administrative data relevant to assessing the effects of prevention either on an ad hoc basis or as a part of on-going performance reviews. Some also gathered qualitative data, mostly related to interventions involving the community and voluntary sectors (e.g. time banks, befriending). It was suggested that assessing the impact of such community-level interventions was particularly challenging because of the multiplicity of variables seen to be influencing the relationship between interventions and outcomes in those settings.
If you put in reablement…,the evidence is better because you can see when you start and when you decrease [the needs] … with information and advice, we have struggled with that…how we are gonna measure it… we get communities to work with individuals, we have a problem about how we measure the impact …if we do not have evidence that it is delivering against reducing and delaying [needs]…that will be one of the areas where the budget cuts will come from. (LA 3)
Local authorities formally piloted some services, most frequently reablement, typically with the objective of assessing their effectiveness and cost-effectiveness. Telecare, community navigators, adaptations and falls prevention were also commonly piloted. Often, however, only basic descriptive data were collected. Most of the information captured for adaptations, telecare, telehealth and falls prevention covered the amount of equipment provided, the number of individuals served and costs per client or item of equipment. These data did not allow for robust cost-effectiveness evaluations of prevention initiatives.
Performance and outcomes were monitored using local administrative measures, users’ views and, in some areas, the Adult Social Care Outcomes Framework (ASCOF). However, not all authorities thought ASCOF was relevant for measuring preventive services, as some respondents were not aware that ASCOF contained items that could measure prevention effects.4
Longitudinal data collections are vital for the assessment of prevention-related effects, since the full effects of preventative interventions may take time to materialise. Only one local authority had good longitudinal data related to support plans; another had some longitudinal data linked to a number of services. Three authorities were not collecting such data, though two of those said they had the ability to do so if required. Moreover, local in-house studies to evaluate prevention effects tended to be short term, covering a maximum of 24 months, and often much shorter periods (of between 6 and 12 months). Consequently, local evaluations were often restricted to the immediate consequences of prevention investment decisions, despite the longer-term nature of changes to cultures and working practices they implied. Similarly, the time periods involved in evaluations are likely to have been too short to pick up the emergence of unintended consequences of investment in prevention and we found few references to this aspect of implementation in our literature review.
Descriptive methods were mainly used to produce local evaluations and authorities generally generated descriptive reports of area patterns of interventions’ uptake and/or expenditure; team-level or district-level analyses were sometimes produced on an ad hoc basis. Such a focus on collecting process indicators can however conflict with national commissioning goals to improve individuals’ outcomes and the associated requirement for data about the impact of services on the lives of service users (Willis and Bovaird, 2012; Bovaird and Davies, 2011).
Informants in three authorities reported having the capacity and capabilities to collect data and to produce robust analyses in-house. Two others said that even when data were collected, a shortage of analysts, particularly with advanced statistical skills, limited their abilities to use it. Some informants reported that budgetary pressures led senior management to perceive the costs of data collection and analysis as excessive in a context where the retrenchment of local analytical capabilities appeared to be a common response to financial pressures. In such circumstances, some respondents identified the need for external support to adopt more sophisticated but time-consuming evaluation tools such as simple regression methods.
The research highlighted important differences within and across authorities in respondents’ understanding of types of data gathered locally and available nationally in relation to prevention. The interpretation of which services and outcomes were relevant for inclusion in the evaluation of prevention effects also differed. Moreover, interviews and the end-of-project workshop indicated that the link between local policy decision-making and the utilisation of existing routine data was weak in some local authorities, not least because some decision makers were not fully aware of the level and content of data collected locally. It was generally recognised that better integration of evidence into local decision-making could potentially lead to improved resource targeting but existing capacities and capabilities were not always sufficiently fit for purpose in this respect.
Our findings, however, suggested that evidence was often sought by commissioners and utilised by them when available. Although the authors did not prompt respondents about the role of evidence in commissioning, it emerged from the data that the willingness to commission preventative services was strongly related to the availability of evidence about the cost-effectiveness of particular interventions. Adaptations, telecare, falls preventions and reablement appeared to be more commonly commissioned because local or external research was interpreted as providing evidence of their cost-saving potential. Conversely, justifying the commissioning of primary prevention and/or some other community-based services was more challenging due to perceptions that evidence about their effects was more limited. Overall, the lack of credible data on cost-effectiveness was reported to make it difficult to convince senior management to invest in prevention in a fiscal environment whose impact was depicted in the following terms: “policies are not driving our strategy; it is budget saving which is driving our strategy…” (R1, LA6). The same respondent described how the management emphasis was on immediate ASC savings rather than long term benefits for the wider care system:
The problem with selling prevention… to say, ‘look if you invest here now this is how it will impact on the budget in 3, 4 years’ time’. But obviously they are under pressure now…they need to make savings that will have an immediate impact… what we cannot do is to look at the impact [of prevention] on the whole system over a period of time, we do not have that empirical evidence to sell prevention.
Externally conducted research was used to support business cases but reliance on such evidence was considered a ‘leap of faith’ (R2, LA6) due to uncertainty about its transferability to local contexts. The lack of local evidence on prevention and the growing imperative for authorities to deliver short-term cost-savings may thus pose a severe barrier to investment in prevention, particularly low-level interventions about which evidence was seen to be particularly scarce.
The Care Act 2014 imposed an obligation on local authorities to provide services that contribute towards preventing or delaying the development of needs for care and support for identified groups of adults through developing local approaches to prevention (HM Government, 2014). A significant challenge for local policy makers when attempting to meet this new obligation is the limited amount of high quality evidence about which preventative interventions work, why and for whom (Miller and Allen, 2013; Miller et al., 2015; Curry, 2006). By providing insights into processes by which prevention is conceptualised and preventive services are designed, implemented and evaluated, our study has added to the limited literature on the subject and sheds light on the challenges involved in developing preventative strategies and evaluation methods.
While local authorities differed widely in the volume and variety of data collected, they predominantly conducted descriptive analyses, which provided limited insight into the effectiveness and cost-effectiveness of interventions. Key informants emphasized difficulties in gathering relevant data to evaluate prevention and, most importantly, the lack of research expertise locally to develop evaluation methods that would best exploit data routinely collected through current administrative systems. The relative absence of longitudinal evaluations as well as the concentration of evaluations on a limited range of interventions may tend to restrict local investments to the narrow range of prevention schemes where evidence is most developed. Although our data suggest that the potential for robust cost-effectiveness evaluations remains underexploited, more systematic reflections on realistic options for data collection and analysis prior to the introduction or piloting of schemes would enable local evaluations to surface and challenge the assumptions on which resource allocations were based and amend service models before wider implementation (Miller and Whitehead, 2015).
Our findings confirm that despite the increasing policy focus on prevention, the concept remains unclear (Starfield et al., 2008; Curry, 2006; Lombard, 2013). Prevention meant different things to different people in our study and the significant interest among our respondents in developing and utilising the potential of preventative services more fully was restricted by conceptual ambiguities. Such features of local approaches inevitably spill over into evaluation design with the lack of clarity or consensus over policy and practice objectives impacting on local considerations of the key issues for, and methods of, data collection. The under conceptualisation of prevention and its contested nature posits serious challenges to the development of necessary evaluations and requires further study.
Our findings add to the existing literature by helping us to better understand reasons behind the paucity of local evidence on prevention, along with local challenges of investing in preventative interventions and evaluations in a time of austerity. Although much has been written about the impact of austerity on local service provision (NAO, 2014; Hastings et al., 2012; Fernandez et al., 2013) less attention has been paid to how austerity is affecting commissioning practices. Our evidence indicates that the shift towards outcomes-based commissioning in the public sector, with its focus on achieving the greatest and often longer term benefits for users (Bovaird and Davies, 2011; Willis and Bovaird, 2012) could be hampered by the current financial climate, through the impact of austerity on local data collection, including limited focus on outcome indicators. Austerity makes it increasingly urgent for local authorities to exploit cost-effective opportunities for preventative investment, and thus to develop local evaluation frameworks that generate the evidence to justify commissioning of prevention and changes in the targeting of local resources. Unfortunately, this research found evidence that the same pressures on local resources have reduced local appetites for investing in the data gathering and analytical capabilities necessary for evaluating the success of local preventative efforts. This paradox was seen to be posing severe challenges to the commissioning of preventive interventions in the sites where we conducted our study.
ASC has been facing tightening of local budgets for a number of years and this research found evidence to support earlier concerns that implementing councils’ new prevention duty could be seriously compromised (Slasberg and Beresford, 2014; Richards and Williamson, 2015). Although austerity can be managed by various means such as finding innovative ways to improve performance and collaboration across different agencies (Cepiku et al., 2016; Overmans and Noordegraaf, 2014; Lowndes and Squires, 2012), the findings of this study indicate that the focus on budget savings may translate into prioritising investment in a limited set of preventative interventions where existing evidence illustrate most cost-saving potential in the short term. This local focus on cost-savings appears therefore to be poorly aligned with stated national policy goals of improving clients’ outcomes and the emphasis on wellbeing and maintaining independence over the longer term. In addition to immediate pressures to reduce local budgets, a likely explanation for the emphasis on short-term cost savings in local interpretations of prevention is its link with the integration agenda.
Indeed, social care prevention objectives are often expressed in terms of the potential contribution of social care to improving the performance of the health care system, for instance by reducing hospital delayed transfers of care and readmission rates. Our study contributes to the limited evidence on local integration practices in the prevention field. The findings indicate that whereas collaboration between ASC and public health was, in some localities, seen to be improving since the latter transferred to local government, joint work in this field and with the health service was hampered by cultural differences and technical problems. Lack of a shared vision for prevention, including shared understandings of its purpose and roles, different internal processes for decision making, as well as incompatible IT systems appear to constitute significant barriers to the success of such joint working and its evaluation. Current efforts to improve integrated working between social care and other agencies should spur efforts to improve the extent of data sharing, particularly at the level of individuals, in order to support the evaluation of prevention efforts, and their impact on costs and outcomes across agencies (Erens et al., 2016).
Although based on a small sample of six local authorities, the study has helped to identify and assess local concepts of prevention and their operationalization in different contexts, together with the methods used to evaluate prevention-related services. At present, the evidence examined suggests that important differences exist in the conceptualization of prevention within, as well as across, local authorities, and that these differences are undermining the development of coherent, integrated prevention strategies, linked practice guidelines and local evaluations. Improvements in the administrative data held by local authorities and the emerging possibilities of utilising linked individual health and social care records present a largely unexploited opportunity to implement local evaluation systems, which would enable policy makers to take fuller advantage of opportunities for cost-effective prevention. Thinking more systematically about ways in which existing data could be utilised would be more cost-effective than bespoke evaluations and would help councils to make better informed, locally grounded investment decisions. Future studies could develop and test methods for evaluating prevention effects based on administrative data and identify routes through which councils might implement their methods. Assessing cost-effectiveness in prevention is challenging not only due to the lack of a shared understanding of what prevention is, but also because of the difficulties in demonstrating causality between the preventative interventions and outcomes over time. Amongst others, key evaluative challenges include the long timeframes required for observing the full consequences of preventative investments, the lack of experimental evidence and the challenges involved in disentangling the effects of services and needs (Knapp, 2013; Miller and Allen, 2013). Existing analytical frameworks such as The Production of Welfare5 (PoW) could underpin the estimation of cost-effectiveness of prevention using councils’ data as PoW provides clarity in the specification of factors relevant to the production of welfare in social care. It maps out the relationships between services, needs, other factors and outcomes and provides a framework with which to isolate service contribution to individuals’ outcomes (Knapp, 1984). Evaluations could apply, for example, cost functions or production functions to estimate how the intermediate and final outputs vary with service use, and service users and carers needs-related characteristics and to estimate the impact of different services on costs and outcomes (for examples of methods see Davies et al., 2000; Forder et al., 2014). However, more research and development are necessary to provide robust and locally useable frameworks.
1Referring respectively to interventions aiming to: a) Protect against the risk of developing a disease or disability; b) Stop or slow the progress of disease, and c) Help individuals cope with the consequences of a disease and/or disability and as a result to maximise their quality of life and reduce the need for more intensive care.
2‘Completed’, made ‘advanced’ or ‘moderate’ progress in identifying people who may have care and support needs that are not currently being met to ensure they receive preventative services in line with the new statutory requirement.
3The Better Care Fund (BCF) created pooled budgets between health and social care services (from April 2015) to support transformation towards integrated care and to improve outcomes for people with care and support needs. Local plans for the use of the pooled budgets were agreed between local authorities and Clinical Commissioning Groups.
4For example, the item measuring proportion of older people (65 and over) who were still at home 91 days after discharge from hospital into reablement/rehabilitation services (based on www.content.digital.nhs.uk, accessed 10/10/2016).
5The Production of Welfare (POW) model could help to structure the understanding of factors to be considered in examining the contribution of prevention services to users’ and carers’ outcomes. POW stresses the individuality of the needs and preferences of social care users’ and carers, and the personal nature of support. POW establishes clear theoretical expectations about the relationship between needs, services and outcomes at the individual level, and emphasises the need, to inform policy making effectively, to understanding local processes and structures explaining why and how changes take place (Davies and Knapp 1981).
This paper presents independent research funded by the NIHR School for Social Care Research (NIHR SSCR). The views expressed in this paper are those of the authors and not necessarily those of the NIHR SSCR. The authors gratefully acknowledge the time and expertise provided by the respondents in this study.
This article is independent research by the National Institute for Health Research School for Social Care Research. The views expressed are those of the author(s) and not necessarily those of the NIHR SSCR, the National Institute for Health Research or the Department of Health and Social Care. The authors declare that they have no competing interests.
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