Category Archives: Director’s Choice – From the Journals

Does Having an Empathetic Doctor Improve Clinical Outcomes?

Expressions of empathy by a doctor can improve patient satisfaction.[1] And there is evidence that expression of empathy can be taught.[2] But does consultation with an empathetic doctor result in better symptom control than consultation with a doctor who is not as empathetic? A recent review of the topic found seven RCTs addressing this point.[3] The outcomes were measured on a continuous scale so they could be combined through their standardised mean difference in a meta-analysis. All point estimates were favourable and there was a statistically significant effect across all seven included studies. The difference of 0.42 of a standard deviate for pain was described as ‘moderate’, but sounds impressive to me. The study also included trials of ‘positive communication’ designed to engender good expectations of treatment effect. Again, modest effects were noted, but I am cautious about such an approach as it may topple over into dishonesty. Empathy is a different matter and this paper provides yet more evidence on how important it is. Doctors need to display warmth, consideration and appropriate affect – they have to make an effort and do ‘emotional work’. Building a relationship with patients is the essence of practice. Making the diagnosis and performing procedures is the easy bit for experienced doctors. But there is no ceiling to excellence in patient communication.

— Richard Lilford, CLAHRC WM Director

References:

  1. Kim SS, Kaplowitz S, Johnston MV. The Effects of Physician Empathy on Patient Satisfaction and Compliance. Eval Health Prof. 2004; 27(3): 237-51.
  2. Lilford RJ. Is it Possible to Teach Empathy? NIHR CLAHRC West Midlands News Blog. 10 November 2017.
  3. Howick J, Moscrop A, Mebius A, et al. Effects of empathic and positive communication in healthcare consultations: a systematic review and meta-analysis. J Roy Soc Med. 2018.
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Which Combinations of Chronic Conditions have the Greatest Burden of Disease?

CLAHRC WM investigators are carrying out work on multi-morbidity. Which combinations of diseases are most debilitating for patients? According to Jia, et al. conditions individually with the greatest burden of disease are heart failure and depression.[1] The worst combination among 13 conditions was any combination including heart failure and depression.  High blood pressure and arthritis have much lower burdens of disease as measured by QALYs, either singly or in combination.

— Richard Lilford, CLAHRC WM Director

Reference:

  1. Jia H, Lubetkin EI, Barile JP, Horner-Johnson W, DeMichele K, Stark DS, Zack MM, Thompson WW. Quality-adjusted Life Years (QALY) for 15 Chronic Conditions and Combinations of Conditions Among US Adults Aged 65 and Older. Med Care. 2018; 56(8): 740-6.

‘A-PINCH’ medicines – Those Largely Responsible for Medication-Related Harm

Last year the WHO announced their third global safety challenge.[1] [2] Three main challenges are included:

  1. High-risk situations.
  2. Polypharmacy.
  3. Transitions of care – an increasing priority for CLAHRC WM.

And the medicines to be wary about are the small proportion that are responsible for a large proportion of medication-related harm, covered by the ‘A-PINCH’ acronym: Antibiotics, Potassium and other electrolytes, Insulin, Narcotics (and other sedatives), Chemotherapeutic agents, and Heparin (and other anti-coagulants). Medicines review is important when patients transition across care providers.

— Richard Lilford, CLAHRC WM Director

References:

  1. Shiekh A, Dhingra-Kumar N, Kelley E, Kieny MP, Donaldson LJ. The Third Global Patient Safety Challenge: Tackling Medication-Related Harm. Bull World Health Organ. 2017; 95: 546.
  2. Donaldson LJ, Kelley ET, Dhingra-Kumar N, Kiney M-P, Shiekh A. Medication Without Harm: WHO’s Third Global Patient Safety Challenge. Lancet. 2017; 389: 1680-1.

Retrospective Study of the Quality of Care Given to Patients Who Have Died – A Design That Should Be Laid to Rest According to Bach, et al.

Prof Tim Hofer (University of Michigan) drew this important article to my attention.[1] Bach and colleagues consider studies of the quality of care given to people who have recently died. Such studies sound laudable, but they are a poor reflection of the care given to dying patients.  Why is it that these apparently well-meaning studies provide biased results? There are two main problems. First, when patients are still alive it is not known who will die – many who die are not identified as dying, while many identified as dying do not do so. Thus, dead patients are a poor reflection of dying patients; they are a highly skewed group. Second, when the care given to dead people is examined, a time interval prior to death must be specified and the results obtained are highly sensitive to this arbitrary threshold. This study used real, population-based cohorts to show how differences in subject selection and time lead to massive bias. Retrospective case series, based on events that precede eligibility for inclusion in the cohort, simply should not be used to quantify the quality of care.

— Richard Lilford, CLAHRC WM Director

Reference:

  1. Bach PB, Schrag D, Begg CB. Resurrecting Treatment Histories of Dead Patients. JAMA. 2004; 292: 2765-70.

Before and After Study Shows Large Reductions in Surgical Site Infections Across Four African Countries

This important study from the WHO Infection Prevention and Control global unit was based on a multi-component intervention.[1] The intervention consisted of a number of specific measures, including not shaving the skin prior to surgery, antibiotic prophylaxis and proper skin preparation. It also included some generic cultural components, including the promotion of operating theatre discipline.

The incidence of post-operative infections of the surgical site was halved from 8% to about 4% following implementation of the intervention. No contemporaneous national initiative took place in any of the countries concerned, so I think that a general temporal effect, or rising tide,[2] is unlikely. Moreover, process measures improved in line with the clinical outcomes. A cause-effect explanation is thus plausible.

Yet, people will be properly sceptical of this result. Determining a surgical site infection (SSI) is subjective, as has been shown in many empirical studies.[3] Such measurements are likely to be reactive, meaning that there is an interaction between the intervention and the outcomes observed. The way to get around this is to objectify the observations in some way, such as by blinding the observers. Reactivity is a limitation on most studies of SSIs, whether randomised or observational. In my opinion, it is worth spending additional money to avoid this problem, which cannot simply be wished away. Possible methods to get around the problem include: use of observers who move from institution to institution and who do not know where or when interventions were implemented; or use of images scored blindly by independent observers. If this is too expensive, then independent sampling of wards taken at random by a truly blinded observer should be used. In the meantime, given the likely reactivity of the measurement, it is prudent to interpret RCTs of methods to reduce SSIs with caution.

— Richard Lilford, CLAHRC WM Director

References:

  1. Allegranzi B, Aiken AM, Kubilay NZ, et al. A multimodal infection control and patient safety intervention to reduce surgical site infections in Africa: a multicentre, before-after, cohort study. Lancet Infect Dis. 2018; 18: 507-15.
  2. Chen YF, Hemming K, Stevens AJ, Lilford RJ. Secular trends and evaluation of complex interventions: the rising tide phenomenon. BMJ Qual Saf. 2016; 25: 303-10.
  3. Taylor JS, Marten CA, Potts KA, et al. What is the Real Rate of Surgical Site Infection? J Oncol Pract. 2016; 12(10): e878-83.

Public versus Private Providers: Simple Solutions are Simplistic!

The CLAHRC WM Director has always been interested in public versus private provision of services. Very few people wish to privatise the judiciary or the army, and very few want to bring supermarkets or car factories into public ownership. However, there is plenty of dispute about many other services, such the rail tracks or care homes.

Previous news blogs summarised the result of studies of private versus government schools in Pakistan [1] and in the USA.[2] Tony Culyer compared private with public care homes and found no difference; they were equally bad.

So, the CLAHRC WM Director was fascinated by a recent article on government outsourcing in The Economist (30 June).[3] The conclusion here is nuanced. It turns out that over many industries public provision can be just as good as private provision, but usually, when the public provision involves competition. Thus, we should expect a very different outcomes when a public provider competes with a private provider, versus public providers in a system with no private providers. So, it seems to come down to monopoly versus multiple providers and having some element of competition.

In healthcare there is a further factor at play, the need to integrate over many service providers. Introducing competition in such a system is more difficult than simple competition between providers. Of course, healthcare also suffers from endemic market failure due to information asymmetries.

Many areas and economics remain unresolved. It is often much easier to identify what not to do, than to identify precisely what to do.

— Richard Lilford, CLAHRC WM Director

References:

  1. Lilford RJ. League Tables – Not Always Bad. NIHR CLAHRC West Midlands News Blog. 28 August 2015.
  2. Lilford RJ. Government vs. Private Schools. NIHR CLAHRC West Midlands News Blog. 23 June 2017.
  3. The Economist. Britain’s outsourcing model, copied around the world, is in trouble. The Economist. 28 June 2018.

Adrenaline vs. no Adrenaline for Out of Hospital Cardiac Arrest

An iconic trial of over 8,000 participants was published last week by CLAHRC WM affiliate Gavin Perkins and colleagues comparing administration versus non-administration of epinephrine (adrenaline) for out of hospital cardiac arrest.[1] Overall only about one person in fifty survived such an event. The trial showed a higher survival rate among patients in the adrenaline group, but a lower rate of neurologically intact survivals. This can be accounted for by a higher rate of severe neurological damage in the adrenaline group. This result is broadly consistent with trials of high versus low dose adrenaline, where the higher dose is associated with more survival, but a higher proportion of survivors with neurological damage.

Congratulations to the trial team who brought many patients and the public on side before conducting the trial. This ensured that the trial would be completed under a fair amount of press scrutiny and even criticism.

The trial shows a trade-off between survival and intact survival. Public consultation carried out by the investigators suggested that people are more concerned with long-term than short term outcome. It would be extremely interesting to elicit trade-off functions from representative members of the public, say by means of discrete choice experiments. Here is a situation where consent cannot be acquired at the point of treatment and so, absent a close relative at the scene, choice of option has to be guided by public norms.

— Richard Lilford, CLAHRC WM Director

Reference:

  1. Perkins GD, Ji C, Deakin CD, et al. A Randomized Trial of Epinephrine in Out-of-Hospital Cardiac Arrest. New Engl J Med. 2018;.

Calling All Service Delivery Researchers

Daw and Hatfield draw attention to an important source of bias in non-experimental matched before and after studies.[1] Matching can introduce a bias under these circumstances. The bias results when regression to the mean is a possibility. Consider an intervention targeted at institutions with a high mortality rate. Matching will introduce bias because the intervention cluster has a low mortality relative to its group and the control cluster has a high mortality relative to its group. If this were not so, then they would not have matched. So a difference between the two groups may emerge over time, and be ascribed to any intervention, even when there was no intervention effect.  Traditionally, we say that as confounder is associated with the intervention (treatment assignment) and the outcome. However, a confounder can be associated with the intervention and the propensity of the outcome to change over time. This applies in before and after studies (difference-in-difference studies; studies with control for baseline conditions). The article confirms this theoretical problem by means of Monte Carlo simulations. This seems a very important point for all health service researchers to be aware of.

— Richard Lilford, CLAHRC WM Director

Reference:

  1. Daw JR & Hatfield LA. Matching and Regression to the Mean in Difference-in-Differences Analysis. Health Res Educ Trust. 2018.

More Evidence that it Really is Possible to Reduce Readmission Rates in Hospitals

In the early days of our CLAHRC we were asked by Toby Lewis and colleagues at Sandwell and West Birmingham hospitals, to advise on reducing readmissions. We examined scores for the risk of a readmission and the headroom for further improvement, given that most readmissions result from intercurrent disease.[1]

Further evidence that reduced rates can be achieved comes from the Medicare shared savings programme, which involves financial incentives.[2] A difference-in-differences estimation was carried out among participating and non-participating hospitals. The study involved over 1,500 hospitals. Hospitals participating in the programme showed greater reduction in readmission rates. This difference was only half a percentage point for heart failure, but this was still significant given the very large sample size. Participating hospitals also had a greater reduction in readmissions from all causes, but here the difference was only a tenth of a percentage point and was not significant.

What are the take home messages? First, working hard at your readmissions will have an effect. Second, don’t expect to see the results in your board papers; this is one of many examples where any effects from generic (system level) health services interventions are unlikely to show up in anything but the most massive studies, as we have argued before.[3]

— Richard Lilford, CLAHRC WM Director

Reference:

  1. Lilford RJ. Predicting Readmissions on the Basis of a Well-Known Risk of Readmission Score. NIHR CLAHRC West Midlands News Blog. 4 August 2017.
  2. Kim Y, Thirulumaran CP, Li Y. Greater Reductions in Readmission Rates Achieved by Urban Hospitals Participating in the Medicare Shared Savings Program. Med Care. 2018; 56(8): 686-92.
  3. Lilford RJ, Chilton PJ, Hemming K, Girling AJ, Taylor CA, Barach P. Evaluating policy and service interventions: framework to guide selection and interpretation of study end points. BMJ 2010; 341: c4413.

An Incredibly Important Study on Neurology and Psychiatry Published in Science

In previous blogs we have reported on genome wide association studies in psychiatric conditions. For example such studies have played a pivotal role in working out the molecular biology of schizophrenia.[1]

Now, genome wide association studies have been used to see how psychiatric and neurological diseases cluster by genetic polymorphism.[2] An organisation called the BrainSTORM Consortium cross-correlated the genetic variations of 25 psychiatric and neurological diagnoses.

It turns out that genetic correlations between psychiatric disorders are common, but there are no such associations between the major neurological diseases examined, or between neurological and psychiatric conditions. There was considerable overlap between major depression, schizophrenia and attention deficit hyperactivity disorder. Anorexia nervosa clusters with schizophrenia and obsessive compulsive disorder. However post-traumatic stress disorder showed no significant correlation with other psychiatric conditions.

No wonder that it has proven difficult to slot psychiatric illness into neat and discrete clinical entities. On the other hand, this seems little different to autoimmune diseases where there is also a considerable overlap between disease types.

— Richard Lilford, CLAHRC WM Director

References:

  1. Lilford RJ. Psychiatry Comes of Age. NIHR CLAHRC West Midlands News Blog. 11 March 2016.
  2. The Brainstorm Consortium, Anttila V, Bulik-Sullivan B, et al. Analysis of shared heritability in common disorders of the brain. Science. 2018; 360: eaap8757.