Antenatal Corticosteroids

The CLAHRC WM Director was awarded a grant to study uptake of effective practice in the UK over 20 years ago. The study showed that the majority of eligible patients were receiving antenatal corticosteroids in the UK.[1] However, it would appear that this treatment, which is effective in protecting the newborn from respiratory disease and brain damage, is given to only half of eligible people across 29 low- and middle-income countries.[2] The next step should be to identify barriers and facilitators to guide development of an intervention.

— Richard Lilford, CLAHRC WM Director


  1. Wilson B, Thornton JG, Hewison J, Lilford RJ, Watt I, Braunholtz D, Robinson M. The Leeds University Maternity Audit Project. Int J Qual Health Care. 2002; 14(3): 175-81.
  2. Vogel JP, Souza JP, Gülmezoglu AM, et al. Use of antenatal corticosteroids and tocolytic drugs in preterm births in 29 countries: an analysis of the WHO Multicountry Survey on Maternal and Newborn Health. 2014; 384(9957): 1869-77.

A Low-Value Paper on the Assessment of High-Value Care

The provision of ‘high-value’ care (HVC) – balancing health outcomes from treatment against financial costs, potential adverse events and the disutility of undergoing treatment – has become increasingly important in a time of austerity and patient-centred care. A recent paper in the Annals of Internal Medicine therefore set out to establish whether a subset of single-best answer questions used as part of a wider knowledge-based examination could be an effective tool for assessing trainees’ knowledge of HVC.[1] Thirty-eight existing questions were identified as assessing domains of HVC and the scores of around 18,000 residents were analysed for evidence of validity. We are not informed of the extent to which any of the measures of HVC used in the study were reliable, although an examination including just 38 questions is unlikely to have sufficient reliability to be used to classify trainees.

The analysis proceeds at the level of the training programme (N=362) and no data on the variability of trainees’ scores within a programme, compared to that between programmes, are provided. We are informed that the HVC subscore correlates positively at programme level with total examination scores, although no quantitative measure of the correlation is provided and any such measure would inevitably be biased upwards by the inclusion of the HVC subscore in the total score. Despite the authors’ statement that their findings “support the importance of the training environment in fostering HVC” (p. 737), there was poor agreement between programme quartiles based on HVC subscores and a measure of hospital care intensity (a quadratic weighted kappa of 0.17 was calculated from data provided). Evidence of validity at trainee level could have been provided, as survey data on self-reported HVC behaviours was also collected, but again analysed at programme level (with no consistent relationship identified across the eight HCV behaviours included in the survey).

Research in medical education – of which assessment is a key domain – is often seen as the poor bedfellow of clinical research. Guidance on reporting and interpreting validity evidence is available [2] and needs to be followed if medical education research is to raise its profile.

— Celia Taylor, Senior Lecturer


  1. Ryskina KL, Korenstein D, Weissman A, Masters P, Alguire P, Smith CD. Development of a High-Value Care Subscore on the Internal Medicine In-Training Examination Assessing Residents’ Knowledge of HVC. Ann Intern Med. 2014; 161(10): 733-9.
  2. Downing SM. Validity: on the meaningful interpretation of assessment data. Med Educ. 2003; 37(9): 830-7


Challenging the Idea of Hospital Culture

Welcome to this first News Blog of 2015, and happy birthday to sibling CLAHRCs. We are exactly one year old!

One of the things our CLAHRC likes to do is challenge the perceived wisdom. Today we challenge the idea that hospitals have a pervading culture that has a profound influence on the performance of front-line staff across the board – in particular, we question the idea that safe care turns on this latent variable of culture. Of course, we do not doubt the concept of culture itself. National cultures certainly exist, as eloquently demonstrated in a study of propensity among UN headquarters staff of different nationalities to misuse diplomatic immunity in violation of New York’s parking restrictions.[1] Similarly, there may be micro-cultures among certain specialities or in particular locations (such as wards/units) within a hospital.[2] But we think that culture is a weak force at the hospital level. Our argument is part theoretical, part empirical.

Theoretically, staff have cultural ties outside their hospital, particularly to their trade organisations, which operate over longer time frames than employment contracts. Within hospitals, interaction across departments is limited and episodic. There are thus reasons, a priori, to be sceptical about the hospital as the cultural locus for clinical staff.

A number of studies have looked for correlations between culture and various measures of hospital ‘performance’.[3] [4] [5] [6] [7] The results are mixed at best and the authors tend to seek reasons for unimpressive results, rather than question the importance of ‘culture’ itself. Correlations, albeit weak ones, have been found between mortality and staff satisfaction,[8] and between patient and staff satisfaction,[9] but many other potential explanations, such as better staff/patient ratios in higher performing institutions, could explain these findings. When looking for a direct correlation between culture and clinical performance none is found.[10] If culture were important then there should be a correlation between adherence to the tenets of good clinical practice between hospital departments/specialities within hospitals, but none is found.[11] Even within departments/specialities, correlations between individual tenets are either weak [12] [13] or non-existent.[14]

Why has the notion of hospital culture received such widespread support in the face of such paltry evidence? We speculate that the notion has been imported, along the supply line for management ideas, from the private sector. We suspect that commercial organisations have cultures that are stronger than those in hospitals. It is easy to be persuaded that ENRON, for example, had such a corporate culture – malign in that case. Whatever the explanation, it is clear to us that this notion of hospital culture feeds into a ‘meta-narrative’ – a story that is amplified through social networks to become an accepted part of folklore. Such stories become self-referential and hard to oppose – for example, we have anecdotal evidence of strong publication bias in studies on culture and plan to investigate this formally. We seek views and potential collaborators in future study of this topic from our readership. Happy New Year!

— Richard Lilford, CLAHRC WM Director
— Yen-Fu Chen, Senior Research Fellow


  1. Fisman R, Miguel E. Cultures of Corruption: Evidence from Diplomatic Parking Tickets. NBER Working Paper No. 12312. 2006.
  2. Brewer BB. Relationships among teams, culture, safety, and cost outcomes. West J Nurs Res. 2006; 28(6): 641-53.
  3. Wagner C, Mannion R, Hammer A, Groene O, Arah OA, Dersarkissian M, Sunol R. The associations between organizational culture, organizational structure and quality management in European hospitals. Int J Qual Health Care. 2014. 26(s1): 74-80.
  4. Willis C, Saul J, Bevan H, et al. Sustaining organizational culture change in health systems? J Health Organ Manag. [In Press].
  5. Mannion R, Davies TW, Freeman T, Millar R, Jacobs R, Kasteridis P. Overseeing oversight: governance of quality and safety by hospital boards in the English NHS. J Health Serv Res Policy. 2015; 20(s1): 9-16.
  6. Davies HT, Mannion R, Jacobs R, Powell AE, Marshall MN. Exploring the relationship between senior management team culture and hospital performance. Med Care Res Rev. 2007 64(1): 46-65.
  7. Millar R, Mannion R, Freeman T, Davies HT. Hospital Board Oversight of Quality and Patient Safety: A Narrative Review and Synthesis of Recent Empirical Research. Milbank Q. 2013; 91 (4): 738–70.
  8. Pinder RJ, Greaves FE, Aylin PP, Jarman B, Bottle A. Staff perceptions of quality of care: an observational study of the NHS Staff Survey in hospitals in England. BMJ Qual Saf. 2013; 22(7): 563-70.
  9. Dawson J. Staff experience and patient outcomes: what do we know? A report commissioned by NHS Employers on behalf of NHS England. London: NHS Confederation. 2014. [Online].
  10. Scott T, Mannion R, Marshall M, Davies H. Does organisational culture influence health care performance- a review of the evidence. J Health Serv Res. 2003; 8: 105-17.
  11. Jha AK, Li Z, Orav EJ, Epstein AM. Care in U.S. hospitals – the Hospital Quality Alliance Program. New Engl J Med. 2005; 353: 265-74.
  12. Peterson ED, Roe MT, Mulgund J , et al. Association between hospital process performance and outcomes among patients with acute coronary syndromes. 2006; 295: 1912-20.
  13. Bradley EH, Herrin J, Elbel B, et al. Hospital quality for acute myocardial infarction: correlation among process measures and relationship with short-term mortality. JAMA. 2006; 296: 72-8.
  14. Wilson B, Thornton JG, Hewison J, Lilford RJ, Watt I, Braunholtz D, Robinson M. The Leeds University Maternity Audit Project. Int J Qual Health Care. 2002; 14: 175-81.

The Population of the World – Will Depend on What Happens in Africa

In a recent post, we drew attention to the importance of the support ratio (defined as the ratio of people aged 20-64 to those over 64, or under 20) in determining living standards (per capita natural wealth).

Gerland and colleagues have recently reported on the latest UN report “World Population Projections”.[1] Projected population growth rates and support ratios have been modelled for the remainder of the century by continent. Their model represents an advance on previous deterministic models, since it used Bayesian methodology to sample from distributions for model parameters, such as fertility rates. The resulting probabilistic sensitivity analysis yielded narrower credible limits than previous crude models. The model also admits external evidence by eliciting prior distributions for unobserved events, such as future life expectancy.

According to the model projections, Africa’s population will be similar to that of Asia by the end of the century, and there is a probability of about 70% that it will exceed it. However, the support ratio for Africa will be much higher (over 5) than for Asia (under 3) or current high-income countries (under 2). Africa will be the new ‘superpower’.

Of course, demography is an inherently uncertain business. Current evidence suggests that fertility rates in Africa are declining at a considerably slower rate than they did in Asia and South America at a corresponding stage of development (see our previous blog). If, however, the rate of decline accelerates soon, then the world’s population will be considerably smaller than projected above.

Our CLAHRC is collaborating with the African Population and Health Research Center (APHRC) in Nairobi to test the hypothesis that early signs of an increase in the rate of decrease are imminent. One thing is reasonably clear, major catastrophe (such as nuclear war) aside, uncertainty about the world’s future population turns mainly on uncertainties about Africa’s population.

— Richard Lilford, CLAHRC WM Director


  1. Gerland P, Raftery AE, Ševčíková H, Li N, Gu D, Spoorenberg T, Alkema L, Fosdick BK, Chunn J, Lalic N, Bay G, Buettner T, Heilig GK, Wilmoth J. World population stabilization unlikely this century. Science. 2014; 346(6206): 234-7.

Paying for Health

The CLAHRC WM director has long been fascinated by the link between how health is paid for and access, quality, and satisfaction. The famous RAND RCT showed that fee-for-service systems resulted in more satisfied patients, but at the cost of over-servicing, compared with capitation payment.[1] This is consistant with economic theory. No changes in quality were detected. Subsequent sharp improvements in care quality in the public Veterans Affairs system vs. other American institutions has led many to speculate that the profit motive is inimical to quality.

So what happens when hospitals convert from not-for-profit to for-profit status? Joynt, Orav and Jha, conducted a controlled before and after study among no less than 237 converting hospitals and 631 matched control hospitals.[2] While the converting hospitals improved their financial margins, no significant changes were observed for adherence to quality standards, nurse to patient ratios, access for poor or minority patients, or mortality. The primary outcomes of interest were expressed as differences in differences, meaning that each hospital acted as its own control, thereby mitigating bias. The authors did not find any effect of time since conversion.

While on the subject of behavioural economics, a paper by Whaley and colleagues will also provoke readers.[3] This study concerns the effect of price transparency on utilisation rates for various services in an insurance-based system involving an element of cost-sharing with patients. The intervention was simple – making prices available online to prospective service users. Most people did not use the service, but given an insured population of half a million individuals, there were still plenty who did. These people were less likely to use a service (lab testing, imaging or clinician visit) than those who did not avail themselves of the pricing service.

Was this because they were already predisposed to parsimony? On the contrary: researchers looked at the behaviour of both groups before introduction of the online pricing service, showing that people who used the service had higher than average utilisation prior to the information service, and lower utilisation after it had been introduced. Making the service available seems to have made them more discriminating consumers.

— Richard Lilford, CLAHRC WM Director


  1. Davies AR, Ware Jr JE, Brook RH, Peterson JR, Newhouse JP. Consumer acceptance of prepaid and fee-for-service medical care: results from a randomized controlled trial. Health Services Research. 1986;21(3):429.
  2. Joynt KE, Orav E, Jha AK. Asociation between hospital conversions to for-profit status and clinical and economic outcomes. 2014; 312(16): 1644-52.
  3. Whaley C, Schneider Chafen J, Pinkard S, Kellerman G, Bravat D, Kocher R, Sood N. Association between availability of health service prices and payments for these services. 2014; 312(16): 1670-6.

Preventing Re-admissions

CLAHRC WM is working with Sandwell and Birmingham Hospitals group to improve care of patients on discharge from hospital. This is a worthwhile exercise since handover from hospital to community is a ‘fault-line’ for safe care. Some think that improving care over this transition may reduce re-admission rates, and indeed differences in re-admission rates across hospital sites within the group prompted the above initiative in the first place.

However, the CLAHRC WM Director is circumspect regarding the prospects for reduced re-admissions. His argument is simple: most re-admissions result from inter-current or progressive disease, while the proportion of re-admissions that are preventable is small, especially beyond the first four weeks after discharge. It follows that re-admissions are a small signal easily buried in noise.[1] This does not, of course, mean that improving care at discharge is not a worthwhile objective.

A recent RCT of an expensive intervention based on one-to-one self-management education from a discharge nurse, backed up by telephone calls after discharge, did not lead to reduced re-admissions and may have actually increased hospital contact overall.[2] Is this yet a further example of an intervention motivated by the need to reduce healthcare utilisation that results instead in improved care but no reduction, or even an increase, in healthcare costs?

— Richard Lilford, CLAHRC WM Director


  1. Girling AJ, Hofer TP, Wu J, Chilton PJ, Nicholl JP, Mohammed MA, Lilford RJ. Case-mix adjusted hospital mortality is a poor proxy for preventable mortality: a modelling study. BMJ Quality & Safety. 2012; 21: 1052-6.
  2. Goldman LE, Sarkar U, Kessell E, et al. Support From Hospital to Home for Elders: A Randomized Trial. Ann Intern Med. 2014; 161(7): 472-81.

Failure to replicate earlier findings

A recent paper by Horton [1] attracted 1,576 views and 123 tweets within ten days of its publication.[2] A major scientific breakthrough? Hardly, the paper reported failure to replicate an earlier finding. Whose earlier finding? Horton’s! Horton suggests two reasons for his failure to replicate earlier results: lack of generalisability or type 1 error (false positive result arising through the play of chance). Both papers dealt with memory clues through associations – the idea that a clue, such as a place or a person that was present when the memory was stored in the brain, could prompt its recall.

The CLAHRC WM director thinks Type 1 error is the likely explanation. A positive value is much less impressive evidence against the null hypothesis than many suppose.[3] A Bayesian approach [4] would have forestalled such a volte-face.

— Richard Lilford, CLAHRC WM Director


  1. Brown-Schmidt S, Horton WS. The Influence of Partner-Specific Memory Associations on Picture Naming: A Failure to Replicate Horton (2007). PLoS ONE. 2014; 9(10): e109035.
  2. Reas E. This Week’s Most Discussed PLOS Neuroscience Article: The Influence of Partner-Specific Memory Associations on Picture Naming: A Failure to Replicate. [Online]. 2014.
  3. Goodman S. A Dirty Dozen: Twelve P-Value Misconceptions. Semin Hematol. 2008; 45(3): 135-40.
  4. Goodman SN. Toward Evidence-Based Medical Statistics. 2: The Bayes Factor. Ann Intern Med. 1999; 130: 1005-13.

Behaviour Change – Special Issue of Psychology and Health

Readers of this News Blog know that CLAHRCs are interested in behaviour change – CLAHRCs not interested in this subject should send the money back! So a recent special issue of Psychology and Health on the risk of bias in RCTs of behaviour change interventions should pique our interest. Unsurprisingly, much of the material is old hat to clinical and service delivery researchers, and the issues discussed are not specific for behaviour change interventions. Drug trials are the exception in not having to cope with difficulties such as in blinding therapists (leading to co-intervention or contamination), blinding patients and observers (leading to detection bias for subjective outcomes), and isolating or standardising the active ingredient of the intervention. The above problems are shared with trials of most types of intervention; surgery, physiotherapy, targeted service change, generic service change, and so on. One author conflates randomisation (a procedure to guard against selection bias) with other procedures, such as double blinding (which guards against performance and detection bias).[1] In fact, they are separate causes of bias and it is possible to have one without the other.

If you have time for only one article, I recommend the paper by Jim McCambridge [2] on the social psychology of research participation. This includes question-behaviour effects where consent procedures or outcome questionnaires (applied to control and intervention groups) interact with the intervention to attenuate or amplify its effects. To deal with this, they recommend the Solomon-4 design where randomisation is to both intervention and (enhanced) questionnaires in a 2×2 factorial design. A real example where filling in a lengthy questionnaire interacted synergistically with an intervention is given. McCambridge makes the excellent point that the problems don’t go away just because a study is not randomised. The article, however, also deals with randomisation itself. Being assigned to a control group might be associated with ‘resentful demoralisation’. Here Zelen randomisation (no consent from control group) is one possibility. Another, oft recommended by the CLAHRC WM Director, is ensuring that only patients in equipoise [3] enter a trial, as originally recommended by Brewin and Bradley.[4]

— Richard Lilford, CLAHRC WM Director


  1. Tarquinio C, Kivits J, Minary L, Coste J, Alla F. Evaluating complex interventions: Perspectives and issues for health behaviour change interventions. Psychol Health. 2015; 30(1): 35-51.
  2. McCambridge J. From question-behaviour effects in trials to the social psychology of research participation. Psychol Health. 2015; 30(1): 72-84.
  3. Lilford RJ, Jackson J. Equipoise and the ethics of randomization. J R Soc Med. 1995; 88(10): 552-9.
  4. Brewin CR, Bradley C. Patient preferences and randomised clinical trials. BMJ. 1989; 299(6694): 313-5.

Measuring Quality of Care

McGlynn and Adams [1] repeat a point frequently made by the CLAHRC WM Director – before using outcomes to judge the quality of care, first model plausible effects.[2] [3] Only a small fraction of an outcome may be amenable to improved care.

The rate of hospital deaths in the UK is about 3%. Allowing a generous 20% of those to be preventable sets an upper headroom for improvement of 0.6%. So don’t expect quality of care to show up in mortality statistics. Or, to take another example, about 1% of hospital patients suffer a preventable medication related adverse event.[4] So don’t expect improved medicine management to show up in quality of life scores among the hospital population.

— Richard Lilford, CLAHRC WM Director


  1. McGlynn EA, Adams JL. What makes a good quality measure? JAMA. 2014; 312(15): 1517-8.
  2. Yao GL, Novielli N, Manaseki-Holland S,Chen YF, van der Klink M, Barach P, Chilton PJ, Lilford RJ. Evaluation of a predevelopment service delivery intervention: an application to improve clinical handovers. BMJ Qual Saf. 2012; 21(s1): i29-38.
  3. Girling AJ, Hofer TP, Wu J, Chilton PJ, Nicholl JP, Mohammed MA, Lilford RJ. Case-mix adjusted hospital mortality is a poor proxy for preventable mortality: a modelling study. BMJ Quality & Safety. 2012; 21: 1052-6.
  4. de Vries EN, Ramrattan MA, Smorenburg SM, Gouma DJ, Boermeester MA. The incidence and nature of in-hospital adverse events: a systematic review. Qual Saf Health Care. 2008; 17(3): 216-23.

Two Provocative Papers on Diet and Health

People are always extremely interested in research on diet and health. Who would have thought that milk was so bad for you? Not only does milk increase risk of heart disease, but it aggravates the one condition that one might have supposed it would protect against, namely osteoporosis. Why doesn’t this high calcium drink prevent calcium loss from bone? The sugar in milk is lactose, a disaccharide derived from glucose and galactose. Galactose may be great for babies, but it is a powerful oxidant, and oxidants are harmful for adults. So it turns out milk aggravates osteoporosis leading to more fractures.[1] However, if you ferment the sugar to lactic acid, for example in producing yoghurt or soured milk, then these negative associations disappear. So the loss of bone in elderly people is not a calcium deficiency disease in most cases, and milk is positively harmful for bone maintenance. Most animals become lactase deficient, losing the ability to digest lactose after weaning.[2] This is not just an accident; it protects them from the harmful effect of galactose. For some reason humans are not so lucky and retain the enzyme. We therefore need to pre-ferment our lactose before consumption. Not surprisingly, a lively correspondence ensured after publication of this provocative paper, but the authors mount a convincing defence.

The question of what sort of diet to take to lose weight is a long-standing controversy – low carbohydrate or low fat? Well a recent randomised trial shows that a low carbohydrate option is much superior in terms of both weight loss and lipid profile.[3] I don’t think we should be surprised: very high carbohydrate diets are an anomaly that would not have occurred in human evolution before the relatively recent discovery of agriculture. It is a pity that the good Dr Atkins didn’t live to see his theory vindicated.

— Richard Lilford, CLAHRC WM Director


  1. Michaëlsson K, Wolk A, Langenskiöld S, Basu S, Warensjö Lemming E, Melhus H, Byberg L. Milk intake and risk of mortality and fractures in women and men: cohort studies. BMJ. 2014; 349: g6015.
  2. Desai BB. Handbook of Nutrition and Diet. New York, NY: Marcel Dekker, Inc. 2000.
  3. Bazzano LA, Hu T, Reynolds K, Yao L, Bunol C, Liu Y, Chen C-S, Klag MJ, Whelton PK, He J. Effects of Low-Carbohydrate and Low-Fat Diets: A Randomized Trial. Ann Intern Med. 2014; 161(5): 309-18.