Policymakers use performance targets to evaluate the quality of output due to the nature of the hospital activity that depends on various sets of objectives and multiple output. In the public sector, officials and bureaucrats are paid regardless of their performance and their failures. The structural reforms of the public service provision aim at creating incentives by introducing set of rewards and penalties for performance. The lack of measurable outcome measurements and reliable output standards make it quite difficult for public sector officials to base their pay on their performance (Prendergast
2003; Di Mascio and Natalini
2013).
Classical organisational theory articulated by Max Weber and Frederick Taylor believes that public organisations are described by rationality whenever goals are specific and well-formalised. Organisation theory argues that public organisation is characterised by multiplicity of purposes, functions and objectives which create a complex system that struggle to optimise the social value added. Yet, the theory recognises the relevance of performance management strategy as a goal setting framework where public managers have clear objectives with less ambiguity in policy targets. This system of organisational behaviour creates a clear framework for reward, sense of accomplishment and a clear picture of identification of problems and designing solutions through management by objectives approach (Osborne
2006). However this approach of management by objectives emphasises on the relevance of the identification of measures of performance that reflect the real outcome of public organisation (Lemieux-Charles et al.
2003).
Plethora of public management studies –for example Heinrich (
2002) and Latham et al. (
2008) - discuss the problems of performance management design and argue their little effectiveness as policy instruments for increased public sector accountability. Osborne (
2007) discusses three main methods for creating incentives in the public sectors. First is the
entrepreneurial management where policy makers introduce profit-maximisation motives for the public sector while second methods is introducing competition between public (in-house teams) and private service provider which is known as
managed competition. Finally is
performance management strategy which sets clear performance measurements and certain policy objectives with quantifiable targets.
The first two alternatives of creating incentives in the public sector might not be in congruency with the nature of some public services or might be politically contentious. Performance management is a method of creating a system of incentives based on which a reward/penalty scheme is applied to bring accountability and measurability to the public services. This strategy requires the pre-designation of policy target(s) in a measurable form, monitoring of performance standards and applying some methods of feedback (Bevan and Hood
2006a). Linking performance to set of incentives might take the form of financial rewards like pay rise, bonus or sharing certain percent of the budget savings or psychological motives for example acknowledgements, reputational gains, awards or autonomy in management. One form of psychological rewards for the successful commitment to the targets is less relaxed monitoring and more empowerment for the bureaucrats. These performance standards and governance by targets might be remarkably beneficial whenever there is a pressing need to improve quality in any complex system as the public services (Beer
1985; Propper et al.
2010).
How effective is performance standard management in providing incentives for improving quality in the public services? Carter et al. (
1995) posit that performance indicators are not solutions by themselves rather they open a room for investigation and understanding of social benefits/costs of the public provision of services, some of which are good performance standards that could reflect some aspects of the policy outcomes and others are short and limited. Holmstrom and Milgrom (
1991) argue that setting measures of performance based on which incentives are linked is a difficult task. In the health care sector, one measurable policy objective is difficult to reflect diversified output, many aspects of quality and contribute to the achievement of the policy outcome and attains the highest social gains. The principal-agent problem acknowledges the degree to which the performance standard could be incomplete and the intricacy of the responses of managers in the public sector (Goddard et al.
2000). However, the inefficiencies of the public organisation, the separation between the ownership and the management, the immeasurability of some public service outcomes, poor definition of goals and sometimes clashing and inconsistent objectives necessitates the presence of the performance standard schemes (Burgess and Ratto
2003). Heckman et al. (
1997) argue that any performance target should systematically reflect the real value added from the public services. To do otherwise may result in less value and higher social cost, as was the case of a job training scheme policy where the use of employability and earning levels as a standard for measuring the performance of the programme led to “cream skimming”, significant gaming costs and deteriorated efficiency (Courty and Marschke
1997). Propper et al. (
2010) suggest that these performance standards and governance by targets might be beneficial whenever there is a pressing need to improve quality in any complex system such as healthcare sector.
Bevan and Hood (
2006a) discuss ratchet effect, threshold effect and output distortion as three types of target gaming. Ratchet effects refer to the incentive of public managers to report low performance levels to avoid penalties of not attaining high policy expectations (Bird et al.
2005; Goddard et al.
2000). The threshold effects indicate setting a threshold for performance based on which a public unit is not motivated to exceed even if it can do better. Output distortions is a type of gaming where managers seek to achieve policy targets at the expense of many aspects of outcome and quality characteristics that are not easily measured which was remarkably obvious in the Soviet Union regime.
Therefore, the outcome of performance management strategy could be framed as one of the following alternatives as discussed by Bevan and Hood (
2006a). First is the success of the policy indicators in reflecting all aspects of public service quality. Second is where performance management strategy succeeds in hitting policy targets but at the cost of deteriorated quality in other relevant but unmeasured aspects of policy outcome (output distortion effect). Third is the case where the performance indicators are absolutely imperfect measures of the policy outcome which is the case of “hitting the target and missing the point”. Fourth is where public managers fail to meet the performance standards. Therefore, the performance standards should just serve as monitoring tools considering their tentative nature rather than an output as such (Bird et al.
2005).
Bevan and Hood (
2006a) claim that the NHS in the UK have done little effort to reveal gaming by hospitals in reporting waiting times and incidences of gaming appear on inquiry basis rather than systematic monitoring. National Audit office (
2001) investigated the incidence of gaming for appointments of outpatients and inpatient admissions and revealed the manipulation of nine NHS trusts for their patient waiting lists impacting the records of 6000 patients. This gaming inquiry was ensued by a study of 41 trusts by the Audit Commission (
2003) that showed evidence of deliberate manipulation and fabrication for waiting time lists by three trusts. The previous incidences show that public organisations under the pressure of meeting the performance indicators might have higher incentive for gaming.
On the other hand, policy targets in the NHS is deemed to have significantly improved one dimension of the quality of health care with no patient waiting more than four hours in the A&E department and more than 18 months for admission. Before the adoption of the policy targets the percentage of patients exceeding the latter figures was above 20% (Bevan and Hood,
2006b). It is generally believed that the star rating system has significantly contributed to the performance of the quality aspects targeted by the policy. In the same line Wilson (
1989) and Dewatripont et al. (
1999) highlight the significant effect of designating high profile targets on increasing the productivity of the public organisations due to developing sense of the ‘mission’ to achieve a set of critical tasks and focus on policy priorities even on the expense of sacrificing other objectives.
High powered incentive system hospitals who focus on reducing waiting time, which is the rewarded and well monitored policy objective, might compromise some degree of quality that is less monitored. This study evaluates whether this was the case. This paper tests the output distortion theory of performance managements strategies adopted in high powered incentive regime. The analysis empirically testes whether lower waiting time, hospitals with higher share of waiting admission and better scored of waiting time as assessed by patients would have compromised other aspects of quality that are less monitored or not subject to targets.
Literature Review
Waiting admission is a rationing mechanism to bring equilibrium between supply of health care services and the demand in the NHS as public service where patients face zero price at the point of demand (Januleviciute et al.
2013). From the supply side the government in the last decade has been busy with dealing with supply bottlenecks to expand treatment capacity by providing extra finance for elective surgery, involving the private sector to increase the capacity and introduce contestability and better management of theatres and diagnostic equipment (Harrison and Appleby
2009). Policies that aimed at management of the demand side aimed at introducing guidelines for patient referral system and methods of prioritisation (Dimakou et al.
2009).
Rowan et al. (
2004) could not find empirical evidence that performance standards of the star rating scheme affected the quality of clinical output of the adult critical care in the NHS hospital. Propper et al. (
2008) show that the English health care system that adopted waiting-time target has shown significant reduction in the waiting admission compared to Scotland that has not adopted similar policies. Siciliani et al. (
2009) find that the relationship between waiting time and cost is non-linear and that the optimal waiting time that would minimise hospital cost would be ten days in a sample of 137 hospitals in the English NHS. However, in many specifications waiting time appear to be insignificant to the cost of hospital. Cooper et al. (
2009) show that NHS reforms since 2001 including waiting time targets and increased competition and patient’s choice, has improved equality and by 2007 the association between waiting time and levels of deprivation has been less obvious. Propper et al. (
2010) find that waiting time targets in the English health care has led to significant reduction in the length of waiting time and this has not decreased the quality of care and also has not resulted in any gaming or reduction of effort on less monitored activities. Propper (
1995), using valuations obtained from trade-offs from experimental setup, estimates the money value of 30 days reduction in the waiting time for elective surgeries to be £35 on average for high income groups. With a total number of waiting admission from 1990 to 1991 of 13 million patient, the study estimated the costs of 30 days waiting time to be £650 million.
Siciliani and Hurst (
2005) investigate means of reducing waiting times in the OECD countries from the supply and demand sides. On the supply side, they see the public health system is operating close or near full employment/capacity, then cooperating with local or international private provider could be a short run solution for excessive waiting time. On the demand side, management of waiting admission could be an effective policy for reducing waiting time. This would include clinical prioritisation system and financial incentives for provider to reduce waiting time. Gravelle and Siciliani (
2008) discuss the waiting time as a rationing mechanism for the supply of health care. The study finds that the optimal waiting time is higher for patients with a smaller marginal disutility from waiting which implies that longer waiting would not significantly deteriorate their health condition. Nikolova et al. (
2016) using conditional density estimation show that waiting time policies resulted in prioritization of patients who waited for longer time on the expense of patients who waited less. This shows that setting priorities in admitting patients to elective treatment has been affected by waiting time targets rather than clinical prioritisation. This is supported by Januleviciute et al. (
2013) who find that the adoption of waiting time policy targets in both cases of Norway and Scotland resulted in shorter waiting times for patients who waited for long period and this came at the expense of not considering clinical priorities. In Norway, meeting the maximum waiting time limit implied that clinically high priority patients have to wait for longer period, yet in Scotland urgent patient group was not statistically affected.
Policy targets are acknowledged for its success in enhancing the performance of the public sector whenever there are areas of significant room for improvement. However, Appleby et al. (
2003) argue that policy initiatives that aimed at reducing waiting time has been effective in shortening extreme long waiting times but has not successfully affected the average waiting time. The findings show that trusts which effectively succeeded in reducing waiting time had a good understanding of the whole health care system and adopted other measures to keep this reduction in waiting time sustainable. In this small sample set, a survey for the consultants working in three departments showed that 40% of the consultants observed positive health outcome gains of patients waiting for shorter periods because of waiting times targets. Oliver (
2005) discusses the development of the waiting time policies in the English NHS and argue that further pressure on the reduction of waiting time like this proposed by Wanless Review for 2022/23 must be balanced with the outcome objectives of the healthcare system.
This study examines the extent to which the adopted schemes of measuring performance in the health care have a positive effect on policy outcomes and quality of services in the health care sector. Is it possible attribute the improvement (or deterioration) in the health outcome to the performance management strategy and policy incentives? This paper attempts to empirically examine the impact of focusing on waiting time targets on other aspects of quality and performance which are not measured by the target as proposed by Bevan and Hood (
2006a) and Propper et al. (
2010). The paper is structured as follows. Section two is methods which discusses the econometric model, estimation techniques and data while Sections four and five are the results and discussion and policy implications respectively.