Is payment by diagnosis for dementia a good strategy?

There is a considerable furore surrounding the new proposal to pay GPs £55 for each dementia diagnosis. The Patients Association called it “a step too far” that would mean a “bounty on the head” of some patients (link), while the Daily Mail quoted a GP as describing the programme as ‘an intellectual and ethical travesty.’ Vitriol aside, there are clearly some issues with incentivising clinicians on the basis of making diagnoses.

Payment by diagnosis could be compared to other schemes, such as the Pay for Performance (P4P) scheme, which Sutton et al (2012) demonstrated had a mortality reducing effect in hospitals in England. However, P4P created incentives by paying doctors on the basis of specific process variables, such as prescribing aspirin at discharge for patients with acute myocardial infarction. These incentives act by altering the opportunity cost of time. For clinicians qua clinicians they may prioritise their time differently in order to increase their revenue from medical practice so that they are more likely to engage in clinical tasks with higher earnings potential. For clinicians qua individuals they may allocate more time to labour, substituting from leisure or work at home, at the benefit of patients. The P4P interventions operate at a specific part of the healthcare causal chain, at the level of process or specific interventions, which may then generate an increase in detection rates or a reduction in adverse events, all leading to improved patient outcomes. Incentivising physicians by diagnosis, however, operates at a different part of the healthcare process. Certainly, the payment for diagnosis may ensure GPs spend more time diagnosing or working with potential dementia patients, in order to boost dementia detection rates; however, equally, a diagnosis per se does not require much time to make and doctors may be incentivised to make incorrect diagnoses. Furthermore, in distorting the opportunity costs of physician time, GPs will allocate more time to identifying dementia patients at the potential risk of neglecting other patients.

Dementia is a concern for an ageing population. Only around 50% of dementia cases are thought to have been diagnosed. The global burden of dementia and Alzheimer’s disease was estimated to be $422 billion in 2009, of which $124 billion was unpaid care (Wimo et al, 2010). One strategy for reducing the burden of dementia is earlier detection – before the development of frank dementia most patients have a period of cognitive decline and suffer from what is termed mild cognitive impairment (MCI) (Petersen et al, 1999). While the deterioration of cognitive function is inexorable in dementia patients, it may possibly be slowed with appropriate therapy, which would then potentially delay or prevent a patient requiring highly costly care for late stage dementia (Gestios et al, 2010, 2012, Petersen et al, 2005, Teixera et al, 2012). There would also be considerable benefit to people with MCI and their families where the devastating impact of dementia can be reduced. Whether or not an incentive for dementia diagnoses would lead to earlier detection remains to be seen. Nonetheless, it would seem that incentivising testing for MCI in order to improve early detection, would be a more appropriate strategy. Indeed, this is the aim with type 2 diabetes where the potential benefits of a screening programme have been discussed widely (Gillies et al, 2008, Kahn et al, 2010, Schaufler and Wolff, 2010, among many examples). Simply paying doctors every time they diagnose a case of diabetes would, at face value, be less effective, particularly since earlier cases may be harder to detect – the harder to detect cases would require more time on the part of the clinician, the marginal benefit of which may be smaller than the marginal cost to the clinician. Incentivising for conducting tests arguably does not discriminate on the same basis.

While this may be a step in the right direction to improve dementia detection rates, there may have been a more effective method of incentivising GPs than payment by diagnosis.

#HEJC for 03/06/2013

This month’s meeting will take place Monday 3rd June, at 5pm London time. That’ll be midday in Boston and 6pm in Geneva. Join the Facebook event here. We’ll also hold an antipodal meeting 12 hours later on Tuesday 4th June, at 5am London time. That’ll be midday in Beijing and 6pm on Monday in Honolulu. Join the Facebook event here. For more information about the Health Economics Twitter Journal Club and how to take part, click here.

The paper for discussion this month is a working paper published by the National Bureau of Economic Research. The authors are Janet Currie and W. Bentley MacLeodThe title of the paper is:

“Diagnosis and unnecessary procedure use: evidence from C-section”

Following the meeting, a transcript of the discussion can be downloaded here.

Links to the article

Direct: http://www.nber.org/papers/w18977

RePEc: http://ideas.repec.org/p/nbr/nberwo/18977.html

Other: tbc

Summary of the paper

In this paper the authors develop a model of diagnostic skill as an element of provider quality that is separate from a doctor’s skill in performing procedures. The model shows that higher surgical skill leads to higher use of surgical procedures across all patients, while better diagnostic skill results in fewer procedures for the low risk and more procedures for the high risk. When doctors face a dichotomous choice between an intensive and a non-intensive procedure they have a threshold level of patient condition; above which patients receive the intensive procedure and below which they receive the non-intensive procedure. The doctor’s threshold level is dependent on their surgical skill and the pecuniary benefit associated with carrying out the procedure. Greater diagnostic skill improves the precision of the doctor’s estimate of a patient’s condition and therefore improves the matching between patients and procedures; leading to better health outcomes. Taking the model to data on C-sections, the most common surgical procedure performed in the U.S., the authors show that improving diagnostic skills from the 25th to the 75th percentile of the observed distribution would reduce C-section rates by 11.7% among the low risk, and increase them by 4.6% among the high risk. Since there are many more low risk than high risk women, improving diagnosis would reduce overall C-section rates by about 5% of total births. Moreover, such an improvement in diagnostic skill would improve health outcomes for both high risk and low risk women, while improvements in surgical skill have the greatest impact on high risk women. The results are consistent with the hypothesis that efforts to improve diagnosis through methods such as checklists, computer assisted diagnosis, and collaborative decision making may improve patient outcomes.

Discussion points

  • Are there other aspects of physician skill that could be estimated in this way?
  • Is the characterisation of a doctor’s payoffs accurate?
  • To what other procedures could the model be applied?
  • To what extent could this model inform non-dichotomous physician decisions?
  • What are the key policy implications of these findings?

Missed the meeting? Add your thoughts on the paper in the comments below.