Category Archives: Director & Co-Directors’ Blog

Electronic Patient Notes and Patient Safety

In a previous news blog we drew attention to the psychological consequences of insinuating a computer into the clinician-patient consultation. The deleterious effect of computers on the clinician-patient interaction was published by the CLAHRC WM Director over three decades ago.[1] This concern has been corroborated in Robert Wachter’s recent book.[2]

In this news blog we will focus on another disadvantage of the current generation of electronic clinical notes. This is the threat to patient safety that results from the inchoate nature of electronic clinical record systems. In short, they do not reflect the heuristic patterns that determine appropriate clinical care. This failure to follow medical logic is most dangerous in the context of diagnosis.

While clinical diagnosis may sometimes be clear from a single episode of care, the correct diagnosis frequently depends on the pattern of data as it emerges over time. Just as an understanding of politics requires an understanding of history, so a clinical diagnosis frequently requires an understanding, not just of the current symptoms and signs, but also of their provenance.

Building on this safe premise, one has to conclude that the way clinical record systems are organised can either facilitate or hinder accurate diagnosis. Diagnostic errors are the single largest threat to patient safety [3]; it is all very well to promote evidence-based care and safe prescribing, but if the patient is on the wrong pathway, then they are heading for a big disaster. Diagnosis lies at the heart of clinical medicine and a system that impedes accurate diagnosis is likely to do more harm than good. A recent study of electronic notes carried out by Aziz Sheikh, in collaboration with CLAHRC WM, showed that big reductions in medication error could be achieved by means of electronic prescribing and decision support [in press]. However, careful qualitative research showed that the electronic prescribing systems disrupted the normal flow of knowledge, and that doctors had to implement numerous ‘work-arounds’. This way be dragons!

The problems of disorganised clinical information have been the subject of investigation for over half a century; Professor Laurence Weed’s system of problem-orientated notes inspired the CLAHRC WM Director when he was a young doctor (a long time ago)! The most urgent requirement in modern computing is not to saturate the health service with electronic records, but to develop them in a way that preserves the logic of medical practice. In the meantime we should rely on structured paper-based notes, such as those recommended by Rupert Fawdry,[5] and confine the use of computers to things that they really are good at, such as electronic prescribing and disseminating medical images.

— Richard Lilford, CLAHRC WM Director


  1. Brownbridge G, Lilford RJ, Tindale-Biscoe S. Use of a computer to take booking histories in a hospital antenatal clinic. Acceptability to midwives and patients and effects on the midwife-patient interaction. Med Care. 1988;26(5):474-87.
  2. Wachter R. The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Computer Age. New York, NY: McGraw-Hill Education. 2015.
  3. Singh H, Schiff GD, Graber ML, Onakpoya I, Thompson MJ. The global burden of diagnostic errors in primary care. BMJ Qual Saf. 2017; 26: 484-94.
  4. Lilford RJ. The WISDAM of Rupert Fawdry. NIHR CLAHRC West Midlands News Blog. 5 September 2014.

The Health Economics of Infertility Treatment

Recently I found myself holding forth on the above topic in a plenary talk at the International Federation of Fertility Societies combined meeting with the African Fertility Society in Kampala. I made the point that the health economics of infertility raises a number of issues that are not generally considered in the standard canon for health economic assessment of health technology assessments (HTA).[1] Four issues stand out:

  1. The benefits of infertility treatment are more difficult to capture on a single quality of life (QoL) scale than in the case for standard HTA.
  2. The standard practice of discounting benefits can be questioned.
  3. The beneficiaries are more diverse, potentially extending to many family members.
  4. The issue of whether the lifelong utility of the potential child should be include is controversial.

I shall briefly consider these in turn.

  1. Benefit – generic quality of life (QoL) scales do not seem up to the job. First, it is very difficult to capture the benefits over a lifetime. The ‘area under the curve’ is the important relevant quantity and this is not well captured in cross-sectional studies. Second, QoL deteriorates when a sub-fertile couple have a baby, as it does for fertile people. I discovered this many years ago in a collaborative study with the Health Economics department at the University of York (unpublished). This finding reinforces the importance of a lifetime perspective. Third, it is doubtful that maximisation of the dimensions captured in a generic QoL scale are the things that people wish to maximise when they decide to have children – there is a deeper purpose in play. So, a utility function based on a direct trade-off would be preferable to a standard generic QoL scale, such as the SF-12 or EQ-5D. This way, the respondent can take a lifetime perspective and factor in all the valued benefits and disbenefits of treatment. Torrance used a standard gamble on a large study of US citizens and measured a disutility of 0.07 (utility 0.93).[2] That is to say, the average respondent would run up to a 7% risk of death to enable them to have a first child. Such a standard gamble method would likely underestimate the utility loss for those who actually experience infertility for reasons David Arnold and I explicated elsewhere.[3] A perhaps better method to capture the benefit over a lifetime would be willingness-to-pay studies and here, in addition to studies at the population level (say using discrete choice methods), studies of revealed preferences are possible. This is because much IVF takes place in an entirely private market. This enables the ‘market clearing’ price for infertility services to be observed (ideally in relation to disposable income). The high proportions of disposable incomes infertile people allocate to infertility treatment, sometimes amounting to catastrophic losses,[4] provides some evidence that Torrance’s study underestimates the trade-offs people will make in order to have children.
  2. Choice of discount rate – The fact that benefits continue to accrue, and may increase, over time, suggests that discounting may not be normative. Given that disbenefits generally precede benefits, it makes little sense to discount from the point of intervention. That said, it is important to factor disbenefits of treatment and downstream costs into the analysis. Disbenefits include the cost and discomfort of treatment and knock-on costs, for example, resulting from an increased risk of prematurity. Conversely, there may be hidden benefits beyond the joys of parenthood – for example, in reduced Intimate Partner Violence.[5]
  3. Diverse beneficiaries – In ‘normal’ health economics, benefits are hypotheticated on the affected person, even though loved ones also stand to benefit. Loved ones benefit through the improved health of the affected person. Ignoring third party benefits can be condoned on the ‘level playing field’ principle – in a comparison across diseases of middle-age, beneficiaries of various alternative treatments are in a roughly similar position – they have similar numbers of loved ones on average. On this basis, the decision tree can be ‘pruned’. It could be argued that this argument breaks down when comparisons are made across generational lines. In the particular case of infertility, mothers and fathers get direct benefits, as do grandparents and others, not only through the ‘affected’ person, but directly from the child that results from the treatment. For instance, the father is just as much a beneficiary as the mother. Grandparents are not far behind – I can attest to that. On the other hand, factoring these beneficiaries into the equation seems to tilt the playing field too far the other way, i.e. towards infertility services. Factoring the benefits that accrue to all these people would weight services for children in general, and infertility services in particular, very strongly. This is a topic requiring more philosophical analysis and, perhaps, empirical investigation.
  4. What about the child who would otherwise not have existed – the question of the utility of the hypothetical lives is vexed. Certainty, no-one counts the utility loss from contraception, even when no later ‘replacement child’ is envisaged. On the other hand, the utility of neonatal survival is included in standard economic practice. My preference is not to include this utility, but I am hard-pressed to defend this on a bottom-up, philosophical basis. Richard Hare, the famous Oxford philosopher, did attempt such an analysis and his conclusions support my instinct. Certainly, including the lifetime utility of the child massively improves the cost-benefit ratio of infertility services,[6-8] and if the tax return from the child is included, then a treatment such as IVF becomes a ‘no-brainer’ since it ‘dominates’ – it saves money and yields benefit down to a very low success rate (<6% of so).[9]

What would happen if we:

  1. Accepted a utility function of 0.9 (close to that of Torrance).
  2. Ignored other beneficiaries, including the child?

We present such an analysis below. Even under these relatively conservative constraints, IVF is cost-effective in most countries, and could be cost-effective in LMICs if some new idea, such as incubation within the vagina, were used.

Say we gave infertility a disutility of 0.1 over 50 years, undiscounted.
Then, the utility in an infertile couple successfully treated = 5 QALYs undiscounted and 1.1 discounted at 3%.
Let’s say society will pay $100 per QALY.
Then a treatment with a 25% success rate can have a net cost of up to $125 undiscounted, but less than $28 discounted.

— Richard Lilford, CLAHRC WM Director

I thank Sheryl van der Poel for sending some of the references quoted in this article.


  1. Drummond MF. Methods for the economic evaluation of health care programmes. Oxford: Oxford University Press. 2005.
  2. Torrance GW. Measurement of Health State Utilities for Economic Appraisal. J Health Econ. 1986; 5: 1-30.
  3. Arnold D, Girling A, Stevens A, Lilford R. Comparison of direct and indirect methods of estimating health state utilities for resource allocation: review and empirical analysis. BMJ; 2009; 339: b2688.
  4. Wu AK, Odisho AY, Washington III SL, Katz PP, Smith JF. Out-of-Pocket Fertility Patient Expense: Data from a Multicenter Prospective Infertility Cohort. J Urology. 2014; 191(2): 427-32.
  5. Stellar C, Garcia-Moreno C, Temmerman M, van der Poel S. A systematic review and narrative report of the relationship between infertility, subfertility, and intimate partner violence. Int J Gynecol Obstet, 2016; 133: 3-8.
  6. Connolly MP, Pollard MS, Hoorens S, Kaplan BR, Oskowitz SP, Silber SJ. Long-term Economic Benefits Attributed to IVF-conceived Children: A Lifetime Tax Calculation. Am J Manag Care. 2008; 14(9): 598-604.
  7. Svensson A, Connolly M, Gallo F, Hägglund L. Long-term fiscal implications of subsidizing in-vitro fertilization in Sweden: A lifetime tax perspective. Scand J Pub Health. 2008; 36: 841-9.
  8. Fragoulakis V & Maniadakis N. Estimating the long-term effects of in vitro fertilization in Greece: an analysis based on a lifetime-investment model. Clinicoecon Outcomes Res. 2013; 5: 247-55.
  9. Baird DT, Collins J, Egozcue J, et al. Fertility and Ageing. Hum Reprod Update. 2005; 11(3): 261-76.

The Underestimated Issue of Contingency in Study Design and Interpretation

The central dogma of evidence-based care is that parameter estimates from clinical studies should inform clinical decisions. In its archetypal form the parameter estimates are obtained from head-to-head comparisons in randomised controlled trials (RCTs). Consider first clinical treatments, such as drugs, devices and talking therapies. Here, a target clinical population is defined in whom the treatment is hypothesised to have a beneficial effect – for instance the hypothesis that a left ventricular device for patients in Grade III heart failure may reduce the death rate within two years from 50% to 40% – a ten percentage point improvement. Such a treatment effect can be achieved with a sample of only 1,036 patients (false positive [alpha error] 5%; false negative [beta error] 10%). The same type of simple calculation can be performed across treatment types and outcomes – improve depression scores in people already depressed; pedagogic methods and examination scores in children sitting a particular examination.

Contingent effects
Consider now a diagnostic/screening test (hereafter called a ‘test’). Here again a population of interest would be described, pregnant women, say, or febrile patients. However, in this case the purpose of the population eligible for the test is to identify a further (sub) population – those eligible for treatment for the condition for which the person has tested positive. Here we wish to compare outcomes among a population given a test, but where the benefit is contingent on the treatment effect among those who test positive. This means that the intervention effect is greatly ‘diluted’ by all the people screening negative. Moreover, the dilution effect is not linear; for every halving of absolute effect size, the sample size needs to quadruple – other factors being equal. To put all this another way, the proportion of true positives among all tested, sets an upper limit for the benefit of a test. Take, for example, a test for postnatal depression, which occurs with sufficient severity to warrant treatment in, say, 10% of women. Consider a population of 10,000 pregnant women – 1,000 can expect to get postnatal depression. Standard screening methods can identify 60% of these women – 600 in our ‘population’. A new genetic test comes along that might identify a further 20%. In that case 80% of affected patients will be identified vs. 60% without the test. This amounts to 200 additional women in the original 10,000. Treatment can ‘cure’ depression in half of depressed women, so the incidence of depression in the screened population would drop by one percentage-point. These crude, indicative, figures are laid out below.

096 DCB - Underestimated cost Table 1

Indicative (not real) figures to calculate realistic outcomes for a population screening test.
A trial to detect a one percentage point difference in outcome would require 14,200 participants; whereas a trial to determine the effect of a potential new treatment for use in screen positive women that could ‘cure’ 70% vs. a 50% control rate would require a total of only about 248 participants, other things being equal (α = 0.05; β = 0.9 and no loss to follow-up).

The same general principle applies to generic service delivery interventions that operate through a causal chain with contingent effects, such as this:

096 DCB - Underestimated cost Fig 1

The mathematics of these cases have been worked out by our group elsewhere.[1-3]

In conclusion, it is important to model plausible effect sizes in advance to verify the plausibility of sample size calculations when the observed effect is contingent on upstream events in the causal chain. Causal thinking in clinical and service delivery research can help us identify realistic sample sizes for hypothesis tests.

— Richard Lilford, CLAHRC WM Director


  1. 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.
  2. Yao GL, Novielli N, Manaseki-Holland S, Chen YF, van der Klink M, Barach P, Chilton PJ, Lilford RJ, European HANDOVER Research Collaborative. Evaluation of a predevelopment service delivery intervention: an application to improve clinical handovers. BMJ Qual Saf. 2012; 21(s1):i29-i38.
  3. Watson SI & Lilford RJ. Essay 1: Integrating multiple sources of evidence: a Bayesian perspective. In: Challenges, solutions and future directions in the evaluation of service innovations in health care and public health. Southampton (UK): NIHR Journals Library, 2016.

A Heretical Suggestion!

The locus of health care is moving increasingly towards the community. In high-income countries (HIC) the greatest burden of health falls to frail elderly people with multiple chronic diseases. Hospital is often bad news for such people, both from a psychological and physical point of view.[1] There are good arguments for avoidance of admissions, and for increasing care provision in the community in HICs. In low- and middle-income countries (LMICs) there are also good arguments for community care. The WHO estimates that over three-quarters of all care could be most appropriately delivered in the community. The Declaration of Alma Ata and the Bamako Initiative from the United Nations both support the development of community care for LMICs. In this News Blog I wish to probe this subject more deeply. I will argue that community care is entirely appropriate for preventive outreach care. However, I will argue that we should re-examine the case for promoting community over hospital settings for demand-led care, especially in deprived urban environment.

My re-examination of this subject came about as a result of recent tours of eight slums within Nigeria, Kenya, Pakistan and Bangladesh. While all of these areas have a strong need for supply-side preventive care in the community, I have come to question the wisdom of trying to develop demand-led care within slum localities. My misgivings are based on a number of personal observations and from a reading of the relevant literature.

On site observations suggest that local residents prefer to use hospital facilities, even when this is less convenient than a more accessible community clinic. Some, but not all, slums are reasonably well supplied by local clinics. These clinics are usually staffed by medical officers or nurses rather than doctors. In many cases they have been provided by NGOs. I have observed that these clinics do not have many clients. When I draw attention to this, I am often told that this is because I have come at a quiet period. However, when I probe more deeply, I learn that the outpatients departments of nearby hospitals receive the bulk of the patients. Certainly that is my impression on visits to hospitals in LMICs where outpatient departments ‘heave’ with patients. This finding triangulates with work that colleagues and I have carried out in India under MRC sponsorship.

Not only do local residents seem to prefer hospital-based outpatient’s care, but my reading of the literature suggests that they are right to do so. Working with colleagues, I am carrying out a review of the quality of care provided in local settings in LMICs. The literature shows that such care is almost universally of a low standard, irrespective of whether the provider is private or public. Care given by doctors is generally better than that given by non-medical personnel, but even so is of a poor standard when delivered in the community. The quality of care across both settings is a topic of enquiry in the NIHR Unit on Health Service Provision in Slums that I direct. However, I suspect that the hospital will come out on top.

The corollary of the above, rather preliminary findings, is that we should be cautious about wholesale, and perhaps ideologically-driven, policies to deliver demand-based healthcare coverage in community settings  in low-income urban environments. Pending further research I hypothesise that it may be better to improve access and quality in hospital settings, at least in the first instance. Before taking fixed positions on these important issues we need to understand more about access to healthcare at the demand-side, the quality of such healthcare, and the most-cost effective approaches to driving up the quality of health care.

Please note that all of the above remarks apply to healthcare at the demand-side. That is to say, where a person has sought care for a perceived health problem. We fully support outreach primary preventive services to ensure vaccination, detect malnutrition, and ensure that people stick to their HIV and other treatment regimes.

Box A. Section VI of the Declaration of Alma-Ata

Primary health care is essential health care based on practical, scientifically sound and socially acceptable methods and technology made universally accessible to individuals and families in the community [emphasis added] through their full participation and at a cost that the community and country can afford to maintain at every stage of their development in the spirit of selfreliance and self-determination. It forms an integral part both of the country’s health system, of which it is the central function and main focus, and of the overall social and economic development of the community. It is the first level of contact of individuals, the family and community with the national health system bringing health care as close as possible to where people live and work, and constitutes the first element of a continuing health care process.”

— Richard Lilford, CLAHRC WM Director


  1. Lilford RJ. Intensive Care Harmful in Elderly Patients. NIHR CLAHRC West Midlands News Blog. 7 December 2017.

Factors Associated with De-Adoption

CLAHRC WM News Blog readers know about factors associated with adoption of new technology. Where the treatment is within the gift of a single clinician, then the following barriers / facilitators determine the probability of adoption:

  1. The strength of the evidence.
  2. Prior beliefs – when a person has no strong opinion, then evidence of given strength will be more influential than when it must compete with strong prior beliefs.[1] For example, I would take some convincing that homeopathy is effective.
  3. Psychological approach – when the new evidence requires practitioners to give up something they are accustomed to doing, then change is harder to achieve. (X-rays came into routine use within four years of Röentgen’s discovery, while antisepsis took over a generation.)
  4. Psychological predisposition – according to Rogers, some people are psychologically predisposed to be early adopters or laggards (but this can be specific to the technology concerned).
  5. Role models and other forms of influence from the social environment.
  6. The presence of subconscious ‘clues’ in the environment – nudge theory.[2]
  7. Financial incentives at the personal level – but watch out for perverse effects.

When adoption is not in the gift of individual clinicians, the organisation as a whole has to respond. Many barriers / facilitators can be encountered.

  1. Changing supply chains so that the appropriate technology is available and can be maintained. This is a large barrier in low-income countries.
  2. Arranging for training / education when a new technology supplants an existing technology.
  3. Support across the organisational hierarchy to send out the right social ‘signals’ (see also above).
  4. Co-ordination across barriers – different professions and across organisational boundaries. We have discussed barriers and facilitators to cross-border facilitation in previous blogs.[3]
  5. Financial incentives at the organisational level,[4] although again these can have negative side-effects.[5] [6]
  6. Fit with established workflows and the immediate demands of a situation – a particular problem with IT, as described in previous blogs.[7] [8] Put simply, the more disruptive the technology, the harder change is to achieve and the greater the risk that any adoption will introduce new risks.

All of the above problems require an organisation to have time and people to help solve problems – the concept of absorptive capacity, which has been explored in our CLAHRC.[9]

But what about de-adoption; does that have different features? This topic was studied in a recent issue of the BMJ.[10] They looked at different individual features associated with de-adoption of carotid revascularisation procedures that are falling from vogue, but which are still indicated in some cases. Here clinicians should ‘exnovate’ by scaling back rather than eschewing the procedure completely. More experienced physicians and smaller practices were associated with faster exnovation, but patient factors, strangely, were not. The authors suggest that early adopters tend to be early de-adopters. Far from convincing me that there is something special about de-adoption / exnovation, the evidence actually presented did not suggest that the factors are qualitatively different to those associated with adoption in the first place.

— Richard Lilford, CLAHRC WM Director


  1. Johnson SR, Tomlinson GA, Hawker GA, Granton JT, Feldman BM. Methods to elicit beliefs for Bayesian priors: a systematic review. J Clin Epidemiol. 2010; 63(4): 355-69.
  2. Lilford RJ. Demystifying Theory. NIHR CLAHRC West Midlands News Blog. 10 April 2015.
  3. Lilford RJ. Evaluating Interventions to Improve the Integration of Care (Among Multiple Providers and Across Multiple Sites). NIHR CLAHRC West Midlands News Blog. 10 February 2017.
  4. Combes G, Allen K, Sein K, Girling A, Lilford R. Taking hospital treatments home: a mixed methods case study looking at the barriers and success factors for home dialysis treatment and the influence of a target on uptake rates. Implement Sci. 2015; 10: 148.
  5. Lilford RJ. Financial Incentives for Providers of Health Care: The Baggage Handler and the Intensive Care Physician. NIHR CLAHRC West Midlands News Blog. 25 July 2014.
  6. Lilford RJ. Two Things to Remember About Human Nature When Designing Incentives. NIHR CLAHRC West Midlands News Blog. 27 January 2017.
  7. Lilford RJ. Introducing Hospitals IT Systems – Two Cautionary Tales. NIHR CLAHRC West Midlands News Blog. 4 August 2017.
  8. Lilford RJ. New Framework to Guide the Evaluation of Technology-Supported Services. NIHR CLAHRC West Midlands News Blog. 12 January 2018.
  9. Currie G, Croft C. Enhancing absorptive capacity of healthcare organizations: The case of commissioning service interventions to avoid undesirable older people’s admissions to hospitals. In: Swan J, Newell S, Nicolini D. Mobilizing Knowledge in Healthcare. Oxford: Oxford University Press; 2016. p.65-81.
  10. Bekelis K, Skinner J, Gottlieb D, Goodney P. De-adoption and exnovation in the use of carotid revascularization: retrospective cohort study. BMJ. 2017; 359: j4695.

New Framework to Guide the Evaluation of Technology-Supported Services

Heath and care providers are looking to digital technologies to enhance care provision and fill gaps where resource is limited. There is a very large body of research on their use, brought together in reviews, which among many others, include, establishing effectiveness in behaviour change for smoking cessation and encouraging adherence to ART,[1] demonstrating improved utilisation of maternal and child health services in low- and middle-income countries,[2] and delineating the potential for improvement in access to health care for marginalised groups.[3] Frameworks to guide health and care providers when considering the use of digital technologies are also numerous. Mehl and Labrique’s framework aims to help a low- or middle-income country consider how they can use digital mobile health innovation to help succeed in the ambition to achieving universal health coverage.[4] The framework tells us what is somewhat obvious, but by bringing it together it provides a powerful tool for thinking, planning, and countering pressure from interest groups with other ambitions. The ARCHIE framework developed by Greenhalgh, et al.[5] is a similar tool but for people with the ambition of using telehealth and telecare to improve the daily lives of individuals living with health problems. It sets out principles for people developing, implementing, and supporting telehealth and telecare systems so they are more likely to work. It is a framework that, again, can be used to counter pressure from interest groups more interested in the product than the impact of the product on people and the health and care service. Greenhalgh and team have now produced a further framework that is very timely as it provides us with a tool for thinking through the potential for scale-up and sustainability of health and care technologies.[6]

Greenhalgh, et al. reviewed 28 previously published technology implementation frameworks in order to develop their framework, and use their own studies of digital assistive technologies to test the framework. Like the other frameworks this provides health and care providers with a powerful tool for thinking, planning and resisting. The Domains in the Framework include, among others, the health condition, the technology, the adopter system (staff, patients, carers), the organisation, and the Domain of time – how the technology embeds and is adapted over time. For each Domain in the Framework the question is asked whether it is simple, complicated or complex in relation to scale-up and sustainability of the technology. For example, the nature of the condition: is it well understood and predictable (simple), or poorly understood and unpredictable (complex)? Asking this question for each Domain allows us to avoid the pitfall of thinking something is simple when it is in reality complex. For example, there may be a lot of variability in the health condition between patients, but the technology may have been designed with a simplified textbook notion of the condition in mind. I suggest that even where clinicians are involved in the design of interventions, it is easy for them to forget how often they see patients that are not like the textbook, as they, almost without thinking, deploy their skills to adapt treatment and management to the particular patient. Greenhalgh, et al. cautiously conclude that “it is complexity in multiple domains that poses the greatest challenge to scale-up, spread and sustainability”. They provide examples where unrecognised complexity stops in its tracks the use of a technology.

— Frances Griffiths, Professor of Medicine in Society


  1. Free C, Phillips G, Galli L. The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review. PLoS Med. 2013;10:e1001362.
  2. Sondaal SFV, Browne JL, Amoakoh-Coleman M, Borgstein A, Miltenburg AS, Verwijs M, et al. Assessing the Effect of mHealth Interventions in Improving Maternal and Neonatal Care in Low- and Middle-Income Countries: A Systematic Review. PLoS One. 2016;11(5):e0154664.
  3. Huxley CJ, Atherton H, Watkins JA, Griffiths F. Digital communication between clinician and patient and the impact on marginalised groups: a realist review in general practice. Br J Gen Pract. 2015;65(641):e813-21.
  4. Mehl G, Labrique A. Prioritising integrated mHealth strategies for universal health coverage. Science. 2014;345:1284.
  5. Greenhalgh T, Procter R, Wherton J, Sugarhood P, Hinder S, Rouncefield M. What is quality in assisted living technology? The ARCHIE framework for effective telehealth and telecare services. BMC Medicine. 2015;13(1):91.
  6. Greenhalgh T, Wherton J, Papoutsi C, Lynch J, Hughes G, A’Court C, et al. Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies. J Med Internet Res. 2017;19(11):e367.

Patient’s experience of hospital care at weekends

The “weekend effect”, whereby patients admitted to hospitals during weekends appear to be associated with higher mortality compared with patients who are admitted during weekdays, has received substantial attention from the health service community and the general public alike.[1] Evidence of the weekend effect was used to support the introduction of ‘7-day Service’ policy and associated changes to junior doctor’s contracting arrangement by the NHS,[2-4] which have further propelled debates surrounding the nature and causes of the weekend effect.

Members of the CLAHRC West Midlands are closely involved in the HiSLAC project,[5] which is an NIHR HS&DR Programme funded project led by Professor Julian Bion (University of Birmingham) to evaluate the impact of introducing 7-day consultant-led acute medical services. We are undertaking a systematic review of the weekend effect as part of the project,[6] and one of our challenges is to catch up with the rapidly growing literature fuelled by the public and political attention. Despite that hundreds of papers on this topic have been published, there has been a distinct gap in the academic literature – most of the published papers focus on comparing hospital mortality rates between weekends and weekdays, but virtually no study have compared quantitatively the experience and satisfaction of patients between weekends and weekdays. This was the case until we found a study recently published by Chris Graham of the Picker Institute, who has unique access to data not in the public domain, i.e. the dates of admission to hospital given by the respondents.[7]

This interesting study examined data from two nationwide surveys of acute hospitals in 2014 in England: the A&E department patient survey (with 39,320 respondents representing a 34% response rate) and the adult inpatient survey (with 59,083 respondents representing a 47% response rate). Patients admitted at weekends were less likely to respond compared to those admitted during weekdays, but this was accounted for by patient and admission characteristics (e.g. age groups). Contrary to the inference that would be made on care quality based on hospital mortality rates, respondents attending hospital A&E department during weekends actually reported better experiences with regard to ‘doctors and nurses’ and ‘care and treatment’ compared with those attending during weekdays. Patients who were admitted to hospital through A&E during weekends also rated information given to them in the A&E more favourably. No other significant differences in the reported patient experiences were observed between weekend and weekday A&E visits and hospital admissions. [7]

As always, some cautions are needed when interpreting these intriguing findings. First, as the author acknowledged, patients who died following the A&E visits/admissions were excluded from the surveys, and therefore their experiences were not captured. Second, although potential differences in case mix including age, sex, urgency of admission (elective or not), requirement of a proxy for completing the surveys and presence of long-term conditions were taken into account in the aforementioned findings, the statistical adjustment did not include important factors such as main diagnosis and disease severity which could confound patient experience. Readers may doubt whether these factors could overturn the finding. In that case the mechanisms by which weekend admission may lead to improved satisfaction Is unclear. It is possible that patients have different expectations in terms of hospital care that they receive by day of the week and consequently may rate the same level of care differently. The findings from this study are certainly a very valuable addition to the growing literature that starts to unfold the complexity behind the weekend effect, and are a further testament that measuring care quality based on mortality rates alone is unreliable and certainly insufficient, a point that has long been highlighted by the Director of the CLAHRC West Midlands and other colleagues.[8] [9] Our HiSLAC project continues to collect and examine qualitative,[10] quantitative,[5] [6] and economic [11] evidence related to this topic, so watch the space!

— Yen-Fu Chen, Principal Research Fellow


  1. Lilford RJ, Chen YF. The ubiquitous weekend effect: moving past proving it exists to clarifying what causes it. BMJ Qual Saf 2015;24(8):480-2.
  2. House of Commons. Oral answers to questions: Health. 2015. House of Commons, London.
  3. McKee M. The weekend effect: now you see it, now you don’t. BMJ 2016;353:i2750.
  4. NHS England. Seven day hospital services: the clinical case. 2017.
  5. Bion J, Aldridge CP, Girling A, et al. Two-epoch cross-sectional case record review protocol comparing quality of care of hospital emergency admissions at weekends versus weekdays. BMJ Open 2017;7:e018747.
  6. Chen YF, Boyal A, Sutton E, et al. The magnitude and mechanisms of the weekend effect in hospital admissions: A protocol for a mixed methods review incorporating a systematic review and framework synthesis. Systems Review 2016;5:84.
  7. Graham C. People’s experiences of hospital care on the weekend: secondary analysis of data from two national patient surveys. BMJ Qual Saf 2017;29:29.
  8. Girling AJ, Hofer TP, Wu J, et al. Case-mix adjusted hospital mortality is a poor proxy for preventable mortality: a modelling study. BMJ Qual Saf 2012;21(12):1052-56.
  9. Lilford R, Pronovost P. Using hospital mortality rates to judge hospital performance: a bad idea that just won’t go away. BMJ 2010;340:c2016.
  10. Tarrant C, Sutton E, Angell E, Aldridge CP, Boyal A, Bion J. The ‘weekend effect’ in acute medicine: a protocol for a team-based ethnography of weekend care for medical patients in acute hospital settings. BMJ Open 2017;7: e016755.
  11. Watson SI, Chen YF, Bion JF, Aldridge CP, Girling A, Lilford RJ. Protocol for the health economic evaluation of increasing the weekend specialist to patient ratio in hospitals in England. BMJ Open 2018:In press.

Traditional Healers and Mental Health

The case for traditional healers in mental health

There are two arguments for traditional healer involvement in mental health provision; one pragmatic and one theoretical. The pragmatic argument turns on the huge shortfall in human resources to deal with mental health problems in low- and middle-income countries (LMICs).[1] Traditional healers could make up for this shortage in human resources in the formal sector. A theoretical argument for the role of traditional healers turns on cultural factors. The argument here is that traditional healers are ideally placed to intervene in conditions with social origins, or when symptoms are coloured by cultural assumptions. Traditional healers, one might suppose, can tap into the beliefs and expectation of local people to reach parts of the mind that are simply inaccessible under a ‘medical model’. According to this argument modern medicine is the appropriate vehicle for the diagnosis and management for the conditions that are mainly of the body. It would be unwise, for example, to rely on traditional healers for the treatment of an acutely febrile child, or for provision of contraceptive advice. However, the traditional healer might be the appropriate first port of call for people with conditions of the mind.

The case against traditional healers in mental health

An argument against the above position is that the most serious types of mental health condition, psychotic illnesses, require modern pharmacotherapy, at least to stabilise patients. While all psychiatric conditions are of both brain and mind, psychotic conditions can be closer in form to those of standard medical diseases and the effects of properly targeted chemotherapy can be dramatic. There are many well documented cases where access to appropriate pharmacological therapy was denied or cruelly delayed while patients were treated unsuccessfully by traditional healers. From this perspective one should no more consult a traditional healer for a mental illness than for suspected malaria.

Reconciling the case for and against: a topic for investigation and research

On the one hand, traditional healers can offer culturally sensitive treatment for non-psychotic conditions, while on the other hand, severe mental illness requires medical services. It could be argued that traditional and modern medical services should be integrated so that traditional healers could treat the majority of patients, i.e. those with non-psychotic diseases, while allopathic clinicians treat the more severe cases. Moreover, different people have different preferences, and individuals may wish to receive care from both types of providers, even for the same illness. These would seem to be further arguments to integrate traditional and allopathic services within the same system and, indeed, in an integrated reimbursement system. Before implementing such a system it would surely be sensible to evaluate the effectiveness of traditional healers in the treatment of various psychiatric conditions and to ensure that, with the appropriate education, they would be able to refer cases that need medical treatment.

Philosophical problems in collaboration between traditional healing and modern medicine

The CLAHRC WM Director is keen to explore the relative effectiveness of traditional and allopathic treatments for non-psychotic mental illness but he is concerned that there may be irreconcilable philosophical differences in the traditional versus allopathic approach. This concern arises from different ontologies that underpin the different kinds of service. That is to say these traditions have different views on what counts as truth. Modern medical practice is very much a product of what might be called ‘enlightenment thinking’; practice built on an understanding of biological mechanisms / scientific explanations.[2] Such a world view is a far cry from the assumptions that underpin traditional healing, and which are guided by a set of traditional beliefs, often of a religious nature. So the question is whether it is possible to truly integrate systems with such different sets of underpinning assumptions? This is partly an empirical question – different systems could be examined to understand how well they can work together. The CLAHRC WM Director understands that moves are afoot to integrate allopathic medicine with traditional Chinese medicine in China, and in Ayurvedic medicine in India. It would be interesting to make independent studies of these systems. But in the meantime I would suggest a thought experiment. Let us imagine a proposed trial of rose-hip water vs. anti-depressant medication taking place in an integrated hospital. The allopathic practitioners present this as a placebo-controlled trial, while the traditional healers present this as a trail of two effective alternatives – the underlying belief systems determine how the treatments are presented. The CLAHRC WM Director suspects that it is very difficult to really integrate two systems based on very different philosophical premises. It is one thing to make irenic statements about mutual respect and so on, but another to supress tensions that seem likely to arise from fundamentally irreconcilable philosophical assumptions.

Living with contradictions

The question of integrating these different systems of thought is, perhaps, unresolvable. The systems have existed side by side for a hundred years or more. In high-income countries there is a thriving industry in complementary therapies and the list of alternative methods is almost too long to recite. Likewise traditional medicine and modern medicine have existed side by side quite happily in Africa, South Asia and China for many years. The populations in all these countries seem, on the whole, pretty savvy at working out which method is more appropriate for them in which condition. I have never heard of anyone going to a homeopath for their family planning needs. But systems co-existing in society is one thing, integrating them in common administrative and reimbursement systems is another. Every now and then there is an attempt to unite religion and science around a common purpose – the Lancet commission is currently involved in such a process.[3] [4] However, it may be the case that like religion and science; traditional and allopathic medicine can live happily side by side within the same community and within the same individual. Whether and how they can really be brought together in a structural / organisational sense, for example in the same institution or within the same reimbursement system, is a matter for analysis and exploration. One thing I am sure of is that policy should not be made as though this were a technical issue and without considering the very different world views that lie behind each type of provision. Maybe the best that can be accomplished is for the systems to become more aware of each other and cross-refer when necessary, but to continue to make their own independent contributions?

— Richard Lilford, CLAHRC WM Director


  1. Rathod S, Pinninti N, Irfan M, Gorczynski P, Rathod P, Gega L, Naeem F. Mental Health Service Provision in Low- and Middle-Income Countries. Health Serv Insights. 2017; 10:
  2. Spray EC. Health and Medicine in the Enlightenment. Jackon M (ed). The Oxford Handbook of the History of Medicine. 2011.
  3. Horton R. When The Lancet went to the Vatican. Lancet. 2017; 389: 1500.
  4. Lee N, Remuzzi G, Horton R. The Vatican-Mario Negri-Lancet Commission on the value of life. Lancet. 2017; 390: 1573.

50 Year Anniversary of the First Human Heart Transplant: Lessons for Today

On 3 December we commemorated the 50 year anniversary of the world’s first heart transplant. The operation took place in the early hours of a Saturday morning at the Groote Schuur hospital in Cape Town, South Africa. Christiaan Barnard sutured Denise Darvall’s donated heart into the chest of the recipient, Louis Washkansky. Barnard restarted the new heart with an electric shock and then tried to wean the recipient off the heart and lung machine. But the new heart could not take the strain and Washkansky had to go back on the machine. The second attempt also failed, but when the heart and lung machine was turned off for the third time the recipient’s blood pressure started to climb. It kept on climbing, and soon Denise Darvall’s small heart had taken over the perfusion of Louis Washkansky’s large frame. Later that morning the world woke to the news of the world’s first heart transplant. Looking back over fifty years what should we make of Barnard’s achievement?

The transplant in an historical perspective

The two decades preceding the heart transplant have sometimes been referred to as the golden age of medical discovery.[1] The transplant can be ‘fitted’ retrospectively as the culmination of this golden age just as Neil Armstrong’s moon walk, two years later, can be seen as the crowning achievement of the space race. They belong to a number of technical achievements, including the first “test tube” baby and the first man in space, which are emblematic of human progress. They generate great public interest and media attention, but differ from more fundamental intellectual discoveries, such as the double helix in DNA or Higgs boson, that are rewarded with Nobel prizes.

The heart transplant in the ‘heroic’ medical age

In his book ‘One Life’ Barnard provides an interesting cameo of the power and autonomy of the medical profession in his time.[2] He recalls writing up the routine operation note that must follow any surgical procedure. The anaesthetist, ‘Oz’, suggested that Dr Jacobus Burger, the hospital superintendent, should be informed. Barnard asked whether he should wake him so early in the morning, but Oz replied that the night’s events warranted such an intrusion. At first the befuddled Dr Burger, aware if work in the animal lab, thought that he was being informed about another heart transplant in dogs. However, even when he learned that the transplant involved a human heart, he cryptically thanked the surgeon and replaced the receiver. Nowadays, the idea of carrying out a procedure of such novelty, cost and risk without formal sanction would be unfathomable. The vignette from the doctor’s tearoom vividly illustrates how the relationship between the medical profession and the broader society has changed over one generation. Rene Amalberti argues [3] that many professions progressed through a heroic age in the twentieth century before gradually becoming more formalised and regulated – aviation followed a similar trajectory following Charles Lindbergh’s dramatic flight across the Atlantic in 1927.

Gradually changing ethical norms

The ethics of heart transplants relate mainly to organ donation. In ‘One Life’ Barnard describes the tense atmosphere in the operating room as the team waited for the donor heart to stop after turning off Darvall’s ventilator. In fact, they did not wait, and Barnard’s brother Marius has stated he persuaded Christiaan to stop the donor heart by injecting a concentrated dose of potassium in order to give Washkansky the best chance of survival. Today two different doctors need to independently carry out tests to confirm the donor is brain stem dead before the heart can be removed, as opposed to waiting for death by the whole-body standard, i.e. when there is brain death and the heart has stopped beating.

Public views of heart transplants, then and now

Following the operation the exhausted Barnard went home for a sleep. In the afternoon he returned to the hospital where he was surprised to find his route obstructed by a large crowd of reporters. He had unleashed a tide of publicity and acclaim that resonated for many decades, but dissenting voices were also heard. Some, notably Malcolm Muggeridge, the editor of Punch magazine, attacked the operation on the basis of a near mystical reverence for the human heart and to this Barnard had a succinct response: “it’s merely a pump.” Others worried about the allocation of scarce resources to such a high-tech solution when people were dying from malnutrition and malaria. Defence of the procedure came, albeit years later, from the economics profession when it was shown that the operation has a highly favourable cost-to-benefit ratio (at least in a high-income country).[4] The procedure not only extends life by many years on average, but greatly improves the quality of that life. In fact, patients feel much better from the moment they regain consciousness after the operation despite pain from the sternotomy. The operation is now uncontroversial and is performed routinely in high-income countries. It was long predicted that a mechanical pump would supplant the need for transplantation. Mechanical hearts have improved,[5] but they are largely seen as a bridge to transplantation, rather than a better alternative.

If Christiaan Barnard had not performed his operation, heart transplants would have developed anyway (the second transplant was carried out independently by Adrian Kantrowitz in the USA on 6 December). I was a school boy with hopes of getting into medical school when Washkansky received his new heart. I was among the many millions who were swept up in the wonder of the event and it still stirs my imagination half a century later. And my family knows that I wish to donate my own heart if the circumstances arise.

— Richard Lilford, CLAHRC WM Director


  1. Lilford RJ. Future Trends in NHS. NIHR CLAHRC West Midlands. 25 November 2016.
  2. Barnard C & Pepper CB. One Life. Toronto, Canada: Macmillan; 1969.
  3. Amalberti R. The paradoxes of almost totally safe transportation systems. Saf Sci. 2001; 37(2-3): 109-26.
  4. O’Brien BJ, Buxton MJ, Ferguson BA. Measuring the effectiveness of heart transplant programmes: Quality of life data and their relationship to survival analysis. J Chron Dis. 1987; 40(s1): s137-53.
  5. Girling AJ, Freeman G, Gordon JP, Poole-Wilson P, Scott DA, Lilford RJ. Modeling payback from research into the efficacy of left-ventricular assist devices as destination therapyInt J Technol Assess Health Care. 2007; 23(2): 269-77.

Is Research Productivity on the Decline Internationally?

I have written previously on the so-called ‘golden age of medical research,’ [1] which coincides roughly with the first two decades of my life – 1950-1970. The premise of a golden age entails the conclusion that it is followed by a less spectacular age where marginal returns are lower per unit of input – say per researcher. So, where does the truth lie – is research becoming ever more efficient, or is the productivity of research declining? This subject has been carefully examined by a number of scholars, most recently by Bloom and others.[2] First they looked at aggregate supply of researchers and economic output across the US economy, and they found a relationship that looks like this:

091 DCB Figure 1

So, productivity per researcher appears to decline with time and does so quite rapidly – the graph uses log scales. The drop in unit productivity has been fully compensated by growth in the number of researchers.

Given the obvious problems of studying this phenomenon at the aggregate level, the researchers turn to individual topics, such as number of transistors packed onto a single chip. It turns out that keeping Moore’s law going takes a rapidly increasing number of researchers. However, diminishing returns are not just observed in electronics, the authors found the same phenomenon in agriculture and medicine. Research productivity in the pharmaceutical industry is one-tenth of what it was in 1970, and mortality gains have peaked in cancer and in heart disease. To some extent one can see this effect in the number of authors of medical papers, such as those in genetic epidemiology – they often run literally into hundreds. It would appear that ideas really are getting harder to find and/or when found they portend smaller gains.

I have previously made the obvious point that improved care reduces the headroom for future improvements.[3] Of course, economic growth and further improvement in health still turn on new knowledge and technology without which the supply-side of the economy must stagnate. The phenomenal growth of some emerging economies has been possible because of the non-rivalrous nature of previous discoveries made elsewhere. But we need to continue to advance for all that advances are hard to make. One of these advances concerns making optimal use of existing knowledge, and that is where CLAHRCs come into their own – we trade in knowledge about knowledge.

— Richard Lilford, CLAHRC WM Director


  1. Lilford RJ. Future Trends in NHS. NIHR CLAHRC West Midlands. 25 November 2016.
  2. Bloom N, Jones CI, Van Reenen J, Webb M. Are Ideas Getting Harder to Find? Centre for Economic Performance Discussion Paper No. 1496. 2017.
  3. Lilford RJ. Patient Involvement in Patient Safety: Null Result from a High Quality Study. NIHR CLAHRC West Midlands. 18 August 2017.