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* Corresponding author. Abstract This article provides fi ndings from a survey of fraud and error loss measurement exercises in the health-care sector in six countries, which show the rates and frequency of fraud losses. The article argues that in a period of fi nancial retrenchment cost savings are seen as important and necessary, but the issue of fraud is often downplayed or ignored as a means to meet some of these reductions. The authors show how signifi cant fraud losses can be in health-care systems, but also how they can be reduced by the appropriate counter fraud strategy, offering a less painful means to cut budgets.

Security Journal (2012) 25, 76 – 87. doi: 10.1057/sj.2011.7 ; published online 25 April 2011 Keywords: fraud ; health care ; NHS ; business cost and measurement Introduction Industrialised countries spend signifi cant amounts of money on health care. In the United States, it is more than 2.3 trillion dollars ( National Health Care Anti-Fraud Association, 2010 ); in the United Kingdom £ 109 billion, with £ 94.5 billion spent on the National Health Service (NHS); in the European Union, (EU) it is 1 trillion euros ( Gee et al , 2009 ). Many factors such as new expensive drugs, state-of-the-art technological services, an ageing popu- lation, increased public expectations and demands for a service, rise in obesity and fraudu- lent acts by patients, professionals and health-care providers among others all put increasing pressure on health-care expenditure. A host of initiatives have been pursued to contain these increasing costs and reduce fraud, such as: investment in ‘ better ’ technology; improving the quality and effi ciency of health care by restructuring ( Rose and Coates, 2010 ) to tackle social issues, for example obesity; decreasing unwarranted variation in medical practice across geographical regions to increase patient satisfaction; stopping ‘ unnecessary ’ care; adjusting provider(s) compensation for a service(s), for example payments to dentists; ‘ effi cient ’ management and regulation of health care; preventing diseases such as, diabetes and cardiovascular disease, which are very expensive to treat over long periods of time and encouraging people to pay for private health care. • • • • • • 77 © 2012 Macmillan Publishers Ltd. 0955–1662 Security Journal Vol. 25, 1, 76–87 The scale of health-care fraud Fraud, however, is often downplayed as a potential cost saving by many organisations across a variety of public and private sectors (Brooks et al , 2009; Button et al , 2009; Smith et al , 2011) and is seen as relatively easy to commit (Gill, 2005). The NHS has attempted to reduce the incidence of fraud since 1998 through its counter fraud service. The European Healthcare Fraud and Corruption Network (EHFCN) has also assisted in counter- ing this problem through the sharing of best practice and the facilitation of cooperation across member states since it was formed in 2004. In the USA the National Health Care Anti Fraud Association, which is a combination of private and public health representatives, has openly stated it is an organisation focused exclusively on the fi ght against health-care fraud since 1985.

These organisations are a platform on which to build . Every pound, euro or dollar lost to fraud undermines health-care services around the world to provide essential treatment and care. Although funds lost to fraud are damaging at all times, now in a period of fi nancial retrenchment stopping fraud is even more important so that essential services can be provided . The focus of this article is primarily on the English-speaking world, but where relevant, and useful, we have drawn on examples from the EU and elsewhere and make sug- gestions on how to reduce fraud as an unnecessary business cost to providing health care.

This article will therefore illustrate the variety of frauds committed by people working in and contracted to providing health-care services, drawing on NHS and international case studies of private and public sector health-care fraud. Subsequently, we examine the differ- ent types of existing fraud measurements and highlight the advantages and limitations of these approaches. Then, we explain how the measurement of health-care fraud is open to improvement by drawing on 69 international exercises that measure both a percentage loss rate (PLR) and frequency fraud rate (FFR) of health-care fraud. In the conclusion, we sug- gest that losses to fraud can be measured, and that at a time of fi nancial retrenchment this approach is one that should be an integral part of any international health-care service rather than being downplayed or ignored . Fraud in Health care In England and Wales, there is a comprehensive legal defi nition of fraud; it is defi ned as a false representation, abuse of position or failing to disclose information ( Fraud Act, 2006, Chapter 35, p. 2 ). New offences also include possession of articles intended for use in fraud and making or supplying articles for fraud. There are many different types of fraud, but our concern is with those committed in the fi eld of health care, which are numerous. The follow- ing list identifi es some common types of fraud that occur in health-care systems, some of which are common to many areas of commerce, others peculiar to health care. Claiming payment exemptions for medical services that one is not entitled to.

Billing for services not provided.

‘ Padding out ’ claims for services provided.

Exaggerating patient lists to claim greater revenues.

Performing unnecessary medical treatments to increase revenues.

Accepting bribes to favour and / or endorse certain drugs.

Under-declaring private work. • • • • • • • 78 © 2012 Macmillan Publishers Ltd. 0955–1662 Security Journal Vol. 25, 1, 76–87 Brooks et al Providing false data for applications for employment / promotion.

False over-time claims.

Submitting false invoices for payment.

Adding ghost employees on the payroll.

False expense claims. These above-mentioned examples are just a sample of the frauds committed rather than an exhaustive list. Fraud can be committed by dentists, pharmacists, hospital managers, individuals or people working in collusion, patients, doctors. It is therefore easy to see that health care is open to abuse. This, however, does not mean that it cannot be reduced. In the cases mentioned below, there are examples of practitioners, administrators and nurses committing fraud in both the public and private sector, which indicate a variety of weaknesses in the system of health-care provision. Case 1 John Hudson was working as a dentist in a private prison for which he was paid. He negoti- ated an NHS contract to deliver the same services. However, he failed to declare payment for this work. This fraud lasted from May 2007 to July 2008. He defrauded the NHS of £ 307 000 and pleaded guilty to 27 counts of retaining wrongful credits. He was sentenced to 30 months in prison ( Counter Fraud NHS Business Service Authority, 2010a ). Civil recov- ery has started to secure repayment of the stolen funds. Case 2 The US Department of Justice has arrested and charged 28 people for operating a 25-state scheme to defraud Medicare. The fraudsters set up phony clinics across the United States and were paid more than US $ 35 million ( £ 22 million) in false medical bills. Offi cials at Medicare became suspicious when they noticed bills from ophthalmologists for bladder tests; from ear, nose and throat specialists for ultrasound scans; and from a forensic pathol- ogist for offi ce visits. The crimes were carried out by a crime syndicate that stole the identi- ties of doctors and patients and used them to fi le reimbursement requests to Medicare for procedures supposedly performed at 118 clinics in 25 states ( Charatan, 2010 ). Case 3 A general practitioner (GP) in France invoiced prescription forms for consultations and visits to patients, whom he did not visit. The GP falsifi ed invoices for a 15-month period and • • • • • • • • • • • 79 © 2012 Macmillan Publishers Ltd. 0955–1662 Security Journal Vol. 25, 1, 76–87 The scale of health-care fraud claimed more than S 60 000 illegally. The investigation found that 2503 false acts had been committed during this period ( EHFCN, 2011b ). Case 4 Lorraine Nkuni Tshuma gained admission to a 3-year nursing diploma course, sponsored by the East of England Strategic Health Authority and an NHS student bursary of £ 30 972 and dependants ’ allowance for her three children using a fake Home Offi ce letter that granted her ‘ indefi nite leave to remain in the United Kingdom ’ . Lorraine Nkuni Tshuma had also made false claims about her education and went on to work in the private health-care sector.

Her deceptions were worth £ 60 000 in total, including a loss to the NHS of £ 49 210. She was sentenced to 12 months imprisonment, suspended for 18 months and 220 h of unpaid com- munity work and served with a deportation order ( Counter Fraud NHS Business Service Authority, 2010b ). Case 5 Four doctors, four pharmacists and one pharmaceutical representative were involved in a case of fraudulent prescriptions that amounted to more than S 40 000 in Spain. The primary health-care doctors wrote prescriptions in the name of elderly patients they had visited in the same primary health-care centre. However, no medicines were prescribed to the patients.

Instead, the doctors gave the prescriptions to the pharmaceutical representative who would in turn fi ll in the prescriptions with high-cost medicines produced by the laboratory he represented. The representative would then give the prescriptions to the pharmacists, who would then invoice the medicines to CatSalut, the Catalan Health Service. A total of 557 fraudulent prescriptions were found, representing an amount of S 42.910 ( EHFCN, 2011a ).

The above-mentioned cases provide a snapshot of some of the diverse methods that fraudsters use to defraud health-care systems . The nature of the scale of the problem of health-care fraud has led some countries to create specialist structures to deal with this prob- lem. In 1998, in England and Wales, the National Counter Fraud Directorate was created.

This was subsequently expanded and has been through several name changes to become an organisation employing over 50 staff, but more importantly infl uencing and directing the work of over 300 counter-fraud specialists employed by NHS Trusts. In effect, what has been created could be described as the ‘ NHS Fraud Police ’ .

Fraud can be dealt with as a criminal, civil, regulatory and / or internal disciplinary matter.

It is perhaps seen as negative to claim that it is impossible to stop all fraud. The past 10 years have shown that fraud losses are rarely reduced by operational work to detect and investi- gate fraudsters ( Gee et al , 2010 ). The extent to which fraud losses are detected is usually low, even in organisations that have spent time and resources in trying to deal with these crimes, and the ease with which so many of them are committed (see NHS Counter Fraud Strategy, 1998 ), because of its low visibility ( Fraud Review Team, 2006 ) .

As fraud is based on deception, disguise and hiding or presenting false ‘ facts ’ that appear real, the detection of fraud and fraudsters is extremely diffi cult, and even when caught 80 © 2012 Macmillan Publishers Ltd. 0955–1662 Security Journal Vol. 25, 1, 76–87 Brooks et al diffi cult to sentence. However, what is not always inevitable is that there is a weakness in processes and systems, which allows fraud to exist. Making the environment diffi cult for fraudsters is not as problematic as it appears . Professional investigation, uncovering infor- mation and gathering evidence are useful in reducing fraud. However, we suggest that what is needed is a systematic approach that focuses on high-volume, low-level frauds, as well as on rare high-profi le frauds. This can be achieved by using fraud risk measurement exercises that focus on minimising and reducing fraud rather than reacting to it. However, before we tackle health-care fraud, we need to measure the problem as much as we can. It is to this problem that we now turn. The measurement of fraud Until 2006 and the passage of the Fraud Act, there was no codifi ed set of offences in England and Wales ( Farrell et al , 2007 ), as is still the case in many countries. There has been (and still is) much debate over what should be considered fraud ( Gill, 2005 ; Doig, 2006 ; Levi and Burrows, 2008 ). Many organisations and individuals are reluctant – even when they know it has happened – to report frauds and, instead deal with it in-house or pursue it through the civil courts ( Higson, 1999 ; Button et al , 2009 ). Perhaps, most importantly, many frauds are undiscovered and therefore hidden from offi cial returns. This means recorded statistics of fraud presented by the police and relevant bodies only capture a limited amount of fraud ( Doig and Levi, 2009 ; Doig and Macaulay, 2010 ; Gannon and Doig, 2010 ).

Even with visible street crime, measuring and recording can be diffi cult. Recorded crime statistics are often criticised as being inaccurate (see Maguire, 2007 ) and of providing a limited picture of the real extent of crime. The British Crime Survey, though, is seen as more accurate because it is based on a large statistically valid sample of the British popula- tion and records their experience of crime victimisation ( Maguire, 2007 ) rather than just offi cially record crime. This problem of recording and measuring is compounded when dealing with hidden, complex fraud ( Hoare, 2007 ; Levi et al , 2007 ; Levi and Burrows, 2008 ), as many people are unaware they are a victim.

However, in the past 10 years the approaches to measuring fraud have progressed, par- ticularly in the Department of Work and Pensions ( DWP, 2007 ) and the NHS, which have used statistically valid risk measurement exercises to combat fraud. Both have been suc- cessful; for example, the NHS Counter Fraud and Security Management Service reduced the incident of fraud by £ 811 million from 1996 to 2006 ( NHS, 1998 ) alone. The DWP and the NHS are, however, the exception rather than the rule. Most still rely on detected fraud, and ‘ guesstimates ’ rather than sound methodological approaches.

In some cases, organisations simply added up the value of losses found in cases of detected fraud and assumed that this fi gure represents the total losses incurred. However, this ignores the reality that for the fi gure to be accurate there would need to be a 100 per cent successful detection rate, which is impossible. For this reason, this approach will always signifi cantly underestimate the cost and prevalence of fraud.

A different approach is a ‘ guesstimate ’ , which is really nothing more than a survey of opinion(s). For example, the Association of Certifi ed Fraud Examiners (ACFE) regularly surveys key counter fraud professionals and asks them to estimate the percentage and actual 81 © 2012 Macmillan Publishers Ltd. 0955–1662 Security Journal Vol. 25, 1, 76–87 The scale of health-care fraud losses from occupational fraud ( ACFE, 2007 ) in the organisation that they represent. These tend to vary signifi cantly according to the perceived seriousness of the problem at the time and / or the extent to which their organisation has an appetite to tackle the problem, if in fact it recognises there is one. Although this approach might represent a valid survey of opinion, it does not represent a valid survey of losses ( Gee et al , 2010 ). For some then, this is a ‘ guesstimate ’ because it is not rooted in sound methodological principles.

The HM Treasury produces an annual report on the reported losses to fraud across the public sector. Government Departments are therefore surveyed and provide information on known fraud. This approach is also limited and substantially underestimates the cost of fraud. It is a survey of known internal fraud rather than of other types of fraud, for example external private contracted work, and is therefore a measurement of detected fraud only.

The HM Treasury, however, generates information on counter-fraud strategies such as ‘ Managing the Risk of Fraud: A Guide for Managers ’ (2003) and ‘ Good Practice in Tack- ling External Fraud ’ , in association with the National Audit Offi ce (2004) , which is inform- ative and useful . The Audit Commission, similar to the HM Treasury surveys detected fraud losses. It has, and is expected, as part of its remit to undertake surveys on public sector fi nances. However, it is not part of its role to assess the level and incident of fraud. It has undertaken such functions, for example assessing housing tenancy fraud. Again, its survey is not based on a statistically valid loss measurement exercise. However, a note of caution needs to be raised here, as fraud, regardless of the sector, is always hard to measure because of the deceptive nature of the crime .

Furthermore, sometimes the organisations concerned have decided not to publish the results. Transparency about the scale of health-care fraud is a part of the problem. This is a key factor in tackling fraud, because attention can be focused and a proportionate invest- ment made to deal with the type of health-care fraud. In some cases, those directly involved in countering fraud have also decided, confi dentially, to provide information about unpub- lished exercises for wider consideration ( Gee et al , 2010 ). Although these have been included in the results section, no specifi c reference has been made to the organisations concerned. We do, however, emphasise that publishing the work and results of risk assess- ment exercises and fraud is useful in two ways; it raises the public profi le of health-care fraud, which might raise public awareness of these types of fraud, which in turn might lead to ownership of the problem from the point of view of ‘ citizens ’ and see fraud as a direct cost that results in a service being either withdrawn or reduced because of lack of funds .

However, these risk assessments and measurement of losses are cost effective only if some- thing is done to remedy them. Measuring Health-care Fraud The most accurate measures of fraud are presently fraud loss risk measurement exercises.

The central premise of this approach is that within a total number of transactions there will be a number of fraudulent and mistaken cases (contractors paid twice, wrong salary paid and so on as a result of error rather than fraud), which have not been discovered. A fraud risk measurement exercise focuses on a specifi c area of activity, such as procurement, payrolls, expense claims and so on. A statistically valid sample is then reviewed and from this they are usually classifi ed as fraudulent, error or acceptable. The important difference in this type 82 © 2012 Macmillan Publishers Ltd. 0955–1662 Security Journal Vol. 25, 1, 76–87 Brooks et al of measurement compared with others is that by assessing a range of transactions in detail those undertaking the review are able to discover a sample of cases of fraud and error, which otherwise would not have been discovered. From this, it is then possible to extrapolate on the actual levels of fraud (to a specifi c statistical confi dence level). The aim of this exercise then is to uncover the fraud and also errors committed.

This article reviewed 69 exercises from 33 organisations from the United Kingdom, United States, France, Belgium, the Netherlands and New Zealand. None were found in Asia or Africa. We only used statistically valid exercises, which have considered a statistically valid sample of income or expenditure; have sought and examined information indicating the presence of fraud, error or correct- ness in each case within that sample; have been externally validated; have a measurable level of statistical confi dence; and have a measurable level of accuracy. However, there are a number of caveats. None of these cases cover the costs associated with investigating fraud and developing anti-fraud cultures in the workplace, which would increase the total costs of fraud further. Some of these exercises have resulted in estimates of the health-care FFR, some of the percentage of expenditure lost to health-care fraud and some have measured both. It is also the case that some exercises have separately identifi ed measured health-care fraud and error and some have not. In some cases, there have been repeated exercises to measure fraud and error losses in a single area of expenditure.

To avoid skewing the overall results by including a disproportionate quantity of data from one source, only the results from the fi rst and most recent exercises have been included.

In most of these instances, fraud and error losses have been signifi cantly reduced since the initial measurement exercises.

Although it is necessary to make these caveats clear, the importance of the evidence collated here should not be underestimated. The evidence shows health-care fraud and error losses can be measured – they have been successfully measured many times, in many different organisations and across the world. However, even more important is the fact that the evidence shows that losses to health-care fraud and error are signifi cant and seriously undermine the quality and extent of patient care, which can be provided ( Gee et al , 2010 ).

The range of types of income and expenditure where losses have been measured include fraud and error. The specifi c areas where losses have been measured include the fraudulent provision of sickness certifi cates; prescription fraud by pharmacists; prescription fraud by patients; fraud and error concerning capitation payments to GPs; fraud and error concerning payments made to doctors to manage a patient ’ s medical care; the evasion of dental charges by patients; fraud and error by opticians concerning the provision of sight tests; fraud and error concerning employees of health-care organisations; fraud and error concerning payments for in-patient hospital services. • • • • • • • • • • • • • • 83 © 2012 Macmillan Publishers Ltd. 0955–1662 Security Journal Vol. 25, 1, 76–87 The scale of health-care fraud All of these exercises include fraud by patients, health-care professionals, doctors, dentists, pharmacists, hospital managers and contractors. We are not suggesting that these exercises are comprehensive, but they are without doubt a substantial contribution to detect- ing, measuring and reducing the incident of health-care fraud. The Extent of Health-care Fraud From the research, two types of fi gures have been produced; these are a PLR (the proportion of expenditure lost to fraud and error) a fraud error and frequency rate (FEFR – the frequency of fraud and error. However, before we progress, a note of caution is required.

The same exercise can produce different PLR and FFR fi gures. For example, 100 items of expenditure out of a thousand transactions might be found to be fraudulent. This would produce an FFR of 10 per cent. However, the particular 100 items might have a value of £ 12 000 and if the total expenditure from those 1000 was £ 100 000 that would produce a PLR of 12 per cent. The items of expenditure where fraud is found to be present may either be greater or less than the average value of all of the items of expenditure. For example, it may be that fraud tends to affect items of expenditure that are of a higher value – this will result in the PLR being higher than the FFR.

From the 69 exercises the range of percentage losses (PLR) for health care was found to be between 3.29 per cent and 10.00 per cent, with an average PLR of 5.59 per cent (see Figure 1 ).

Such a percentage, although small, is still a signifi cant loss when we consider the amount of funds spent to provide health care, with more than 2.3 trillion dollars lost in the United States ( National Health Care Anti-Fraud Association, 2010 ) alone. Even a loss of 3.29 per cent of this sum of money is substantial. Error in processing and paying for health care can be reduced by administration, diligence, effi cient and up-to-date technology; it is fraud that is most damaging, particularly if we make no attempt to measure and use counter-fraud measures. Previous research on the public sector has already highlighted limited anti-fraud culture, fraud awareness sessions and screening of both internal and externally contracted employees ( Button and Brooks, 2009 ).

Figure 1 : Proportion of health-care funds lost to fraud and error. 84 © 2012 Macmillan Publishers Ltd. 0955–1662 Security Journal Vol. 25, 1, 76–87 Brooks et al All of the PLR fi gures were more than 3 per cent, with more than one-fi fth showing losses of more than 8 per cent (see Figure 2 ). Again, although these percentages might seem small, they are a small percentage of substantial health-care budgets. Furthermore, these are the best measurements of health-care fraud we have at present and they will not capture all fraud.

The range of FFRs was found to be between 0.47 and 7.1 per cent, with an average FFR of 4.23 (see Figure 3 ). This appears to confi rm that with health-care fraud the PLR is higher – at both the lowest and highest FFR – suggesting that even though the frequency (FFR) has been measured at 0.47 the PLR is 3.29, with the highest at 7.1. (FFR) and the PLR at 10 per cent.

In Figure 4 , less than 92 per cent of the exercises showed FFR fi gures of between 3 per cent and 8 per cent.

The majority of these losses, 92.59 per cent, are in the 3 – 8 per cent category. This is a high frequency of fraud. On the basis of this evidence, it is clear that health-care fraud and error losses in any organisation should currently be expected to be at least 3 per cent, probably more than 5 per cent and possibly as much as 10 per cent. Figure 2 : Percentage loss by amount. 8.00% 7.00% 6.00% 5.00% 4.00% 3.00% 2.00% 1.00% 0.00%0.47% LOWEST FRAUD RATE AVERAGE FRAUD RATE HIGHEST FRAUD RATE 4.23%7.10% Figure 3 : Frequency of health-care funds lost to fraud and error. 85 © 2012 Macmillan Publishers Ltd. 0955–1662 Security Journal Vol. 25, 1, 76–87 The scale of health-care fraud By value of income or expenditure measured, the United States has undertaken the greatest amount of work in this area. This is a direct refl ection of the Improper Payments Information Act of 2002, which requires designated major US public authorities to estimate the annual amount of payments made where fraud and error are present, and to report the estimates to the President and Congress with a progress report on actions to reduce them. In the EU, although there has not previously been any legal requirement, there is a growing understanding that the key to successful loss reduction is to understand the nature and scale of the problem. For example, in Europe, the European Healthcare Fraud and Corruption Declaration of 2004 called for the development of a European common standard of risk measurement, with annual statistically valid follow-up exercises to measure progress in reducing losses to fraud and corruption throughout the EU. Conclusion This article has illustrated that it is possible to measure the nature and extent of health-care fraud. This is the fi rst step to reducing the incidence of fraud. If an organisation is not aware of the extent or nature of its losses, how can it apply the right solution and reduce them?

Where losses have been measured, and the organisations concerned have accurate informa- tion about the nature and extent of fraud, there are examples that losses have been substan- tially reduced, for example, NHS. From this research, we can confi dently claim that losses to health-care fraud and error can be measured – and cost effectively; on the basis of the evidence, it is likely that losses in any health-care organisation and in any area of expenditure will be at least 3 per cent, probably more than 5 per cent and possibly as much as 10 per cent; and • • Figure 4 : Percentage loss by amount. 86 © 2012 Macmillan Publishers Ltd. 0955–1662 Security Journal Vol. 25, 1, 76–87 Brooks et al with the benefi t of accurate information about their nature and extent, they can be reduced signifi cantly in relation to errors on payments for in-patient hospital services. With so much lost to fraud and error, and in a time of fi nancial retrenchment, fraud is a business cost we can ill afford. The use of risk measurement exercises is both worthwhile and necessary if the fraud is to be reduced. In a climate of cost reduction in many countries and the substantial costs of health-care, governments would be well advised to extend fraud loss risk measurement exercises and build appropriate strategies upon these. References ACFE . ( 2007 ) ACFE Report to the Nation . London: ACFE . Brooks , G . , Button , M . and Frimpong , K . ( 2009 ) Policing fraud in the private sector: A survey of the FTSE 100 companies in the UK . International Journal of Police Science and Management 11 (4) : 493 – 504 . Button , M . and Brooks , G . ( 2009 ) ‘ Mind the Gap ’ , Progress towards developing anti-fraud culture strategies in UK central government bodies . Journal of Financial Crime 16 : 229 – 244 . Button , M . , Lewis , C . and Tapley , J . ( 2009 ) Fraud Typologies and the Victims of Fraud Literature Review . London: National Fraud Authority . Charatan , F . ( 2010 ) US Justice Department brings charges in massive Medicare fraud scheme . British Medical Journal , http://www.bmj.com/content/341/bmj.c5865.full?sid=53197eb8-d0ac-49df-a2a6-8c46a3987754 , accessed 28 November 2010 . Counter Fraud NHS Business Service Authority . ( 2010a ) Prison dentist behind bars for £ 307,000 NHS fraud . British Medical Journal , http://www.nhsbsa.nhs.uk/3244.aspx , accessed 28 November 2010 . Counter Fraud NHS Business Service Authority . ( 2010b ) Anglia Ruskin University student sentenced for NHS fraud . British Medical Journal , http://www.nhsbsa.nhs.uk/3189.aspx , accessed 28 November 2010 . Department for Work and Pensions . ( 2007 ) Fraud and Error in the Benefi ts System April 2005 to March 2006 . London: Department for Work and Pensions . Doig , A . ( 2006 ) Fraud . Cullompton, UK: Willan . Doig , A . and Levi , M . ( 2009 ) Inter-agency work and the UK public sector investigation of fraud 1996 – 2006:

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