Tag Archives: Director & Co-Directors’ Blog

Towards a Unifying Theory for the Development of Health and Social Services as the Economy Develops in Countries

In a previous news blog I proposed grassroots solutions to the transportation of critically ill patients to hospital.[1] Other work has demonstrated the effectiveness of community action groups in many contexts, such as maternity care.[2] More recently I have read that the Kenyan government is proposing a combination of local authority and community action (Water Sector Trust Fund) to improve water and sewage in urban settlements.[3] The idea is for the local authority to provide the basic pipe infrastructure and then for local communities to establish linkages to bring water and sewage into homes. The government does not merely lay pipes, but also stimulates local involvement, including local subsidies and micro-enterprises. This epitomises collaboration between authorities and community groups.

In an extremely poor, post-conflict country, such as South Sudan, it is hard to find activities where the authorities and local people work together to improve health and wellbeing. On the other hand, in extremely rich countries like Norway and Switzerland, the government provides almost all that is required; all the citizen has to do is walk into the bathroom and turn on the tap.

The idea that is provoked by these many observations is that different solutions suit different countries at different points in their development. So much so obvious. Elaboration of the idea would go something like this. When a country is at the bottom end of the distribution for wealth, there is very little to be done other than put the basics of governance and law and order into place and try to reduce corruption. Once the country becomes more organised and slightly better off, a mixture of bottom-up and top-down solutions should be implemented. At this point, the tax base is simply too small for totally top-down, Norwegian style, solutions. In effect the bottom-up contribution makes good the tax deficit – it is a type of local and voluntary taxation. As the economy grows and as the middle class expands, the tax base increases and the government can take a larger role in funding and procuring (or providing) comprehensive services for its citizens.

This might seem anodyne written down as above. However, it is important to bear in mind that harm can be done by making the excellent the enemy of the good. Even before a substantial middle-class evolves in society, wealth is being generated. I recently visited a number of urban settlements (slums) in Nigeria, Pakistan and Kenya. All of these places were a hive of economic activity. This activity was mostly in the informal sector, generating small surpluses. Such wealth is invisible to the tax person, but it is there, and can be used. Using it requires organisation: “grit in the oyster”. The science base on how best to provide this ‘grit’ is gradually maturing. In order for it to do so, studies must be carried out across various types of community engagement and support. I expect this to be a maturing field of inquiry to which the global expansion of the CLAHRC message can contribute. Members of our CLAHRC WM team are engaging in such work through NIHR-funded programmes on health services and global surgery, and we hope to do so with regard to water and sanitation in the future.

— Richard Lilford, CLAHRC WM Director


  1. Lilford RJ. Transport to Place of Care. NIHR CLAHRC West Midlands News Blog. 29 September 2017.
  2. Lilford RJ. Lay Community Health Workers. NIHR CLAHRC West Midlands News Blog. 10 April 2015.
  3. Water Sector Trust Fund, GIZ. Up-scaling Basic Sanitation for the Urban Poor (UBSUP) in Kenya. 2017.

Transport to Place of Care

Availability of emergency transport is taken for granted in high-income countries. The debate in such countries relates to such matters as the marginal advantages of helicopters over vehicle ambulances, and what to do when the emergency team arrives at the scene of an accident. But in low- or low-middle-income countries, the situation is very different – in Malawi, for example, there is no pretence that a comprehensive ambulance system exists. The subject of transport does not seem to get attention commensurate with its importance. Researchers love to study the easy stuff – role of particulates in lung disease; prevalence of diabetes in urban vs. rural areas; effectiveness of vaccines. But study selection should not depend solely on tractability – the scientific spotlight should also encompass topics that are more difficult to pin down, but which are critically important. Transport of critically ill patients falls into this category.[1]

Time is of the essence for many conditions. Maternity care is an archetypal example,[2] where delayed treatment in conditions such as placental abruption, eclampsia, ruptured uterus, and obstructed labour can be fatal for mother and child. The same applies to acute infections (most notably meningococcal meningitis) and trauma where time is critical (even if there is no abrupt cut-off following the so called ‘golden hour’).[3] The outcome for many surgical conditions is affected by delay during which, by way of example, an infected viscus may rupture, an incarcerated hernia may become gangrenous, or a patient with a ruptured tubal pregnancy might exsanguinate. However, in many low-income countries less than one patient in fifty has access to an ambulance service.[4] What is to be done?

The subject has been reviewed by Wilson and colleagues in a maternity care context.[5] Their review revealed a number of papers based on qualitative research. They find the theory that one might have anticipated – long delays, lack of infrastructure, and so on. They also make some less intuitive findings. People think that having an emergency vehicle at the ready could bring bad luck, and that it is shameful to expose oneself when experiencing vaginal bleeding.

Quite a lot of work has been done on the use of satellites to develop isochrones based on distances,[6] gradients, and road provision. But working out how long it should take to reach a hospital does not say much about how long it takes in the absence of a service for the transport of acutely sick patients.

We start from the premise that, for the time being at least, a fully-fledged ambulance service is beyond the affordability threshold for many low-income countries. However, we note that many people make it to hospital in an emergency even when no ambulance is available. This finding makes one think of ‘grass-roots’ solutions; finding ways to release the capacity inherent in communities in order to provide more rapid transfers. An interesting finding in Wilson’s paper is that few people, even very poor people, could not find the money for transfer to a place of care in a dire emergency. However, this does not square with work on acutely ill children in Malawi (Nicola Desmond, personal communication), nor work done by CLAHRC WM researchers showing the large effects that user fees have in supressing demand, especially for children, in the Neno province of Malawi.[7] In any event, a grass roots solution should be sought, pending the day when all injured or acutely ill people have access to an ambulance. Possible solutions include community risk-sharing schemes, incentives to promote local enterprises to transport sick people, and automatic credit transfer arrangements to reimburse those who provide emergency transport.

I am leading a work package for the NIHR Global Surgery Unit, based at the University of Birmingham, concerned with access to care. We will describe current practice across purposively sampled countries, work with local people to design a ‘solution’, conduct geographical and cost-benefit analyses, and then work with decision-makers to implement affordable and acceptable improvement programmes. These are likely to involve a system of local risk-sharing (community insurance), IT facilitated transfer of funds, promotion of local transport enterprises, community engagement, and awareness raising. We are very keen to collaborate with others who may be planning work on this important topic.

— Richard Lilford, CLAHRC WM Director


  1. United Nations. The Millennium Development Goals Report 2007. New York: United Nations; 2007.
  2. Forster G, Simfukew V, Barber C. Use of intermediate mode of transport for patient transport: a literature review contrasted with the findings of Transaid Bicycle Ambulance project in Eastern Zambia. London: Transaid; 2009.
  3. Lord JM, Midwinter MJ, Chen Y-F, Belli A, Brohi K, Kovacs EJ, Koenderman L, Kubes P, Lilford RJ. The systemic immune response to trauma: an overview of pathophysiology and treatment. Lancet. 2014; 384(9952): 1455-65.
  4. Nyamandi V, Zibengwa E. Mobility and Health. 2007. In: Wilson A, Hillman S, Rosato M, Costello A, Hussein J, MacArthur C, Coomarasamy A. A systematic review and thematic synthesis of qualitative studies on maternal emergency transport in low- and middle-income countries. Int J Gynaecol Obstet. 2013; 122(3): 192-201.
  5. Wilson A, Hillman S, Rosato M, Skelton J, Costello A, Hussein J, MacArthur C, Coomarasamy A. A systematic review and thematic synthesis of qualitative studies on maternal emergency transport in low- and middle-income countries. Int J Gynaecol Obstet. 2013; 122(3): 192-201.
  6. Frew R, Higgs G, Harding J, Langford M. Investigating geospatial data usability from a health geography perspective using sensitivity analysis: The example of potential accessibility to primary healthcare. J Transp Health 2017 (In Press).
  7. Watson SI, Wroe EB, Dunbar EL, Mukherjee J, Squire SB, Nazimera L, Dullie L, Lilford RJ. The impact of user fees on health services utilization and infectious disease diagnoses in Neno District, Malawi: a longitudinal, quasi-experimental study. BMC Health Serv Res. 2016; 16(1): 595.

Stop Being Beastly to Malthus!

I never understand why people think that Malthus got it so badly wrong. His argument (the Malthusian trap) was that resources are finite and that, therefore, there must be some limit to the number of people that the world can feed.[1] While it certainly turned out that the world can feed many more people than he thought, this does not disprove the underlying theorem. At some point there must come a threshold, where food supply really fails to meet the demand. If we generalise from food to include water, then that point might not be as far away as complacent people think. Of course, we also have to take into account the environmental damage associated with feeding, transporting, and keeping a large number of people warm.

Malthus has become almost a figure of derision. While he may have been wrong about when, the jury is still out about whether. He was right about the generic point, that there is a limit to the carrying capacity of our planet. Food is central to this, because even if we do not run out of food, much environmental damage is caused in its production.

The world’s population will stabilise in about 50 years, although African populations will continue to expand for a while longer.[2] So we should mitigate the environmental effects of food production. I like to eat beef from time to time. However the production of beef is very energy intensive and the methane released by cattle contributes about 20% of the total global warming.[3] So I favour a tax on all beef, similar to that on fuel. Such a tax is more justifiable even, then a tax on sugar and tobacco. This is because consumption of sugar and tobacco does not have the strong externalities associated with fossil fuels and production of beef. There is no proper libertarian argument against taxation in circumstances where strong externalities apply.[4] Pigovian taxes are taxes designed to compensate for externalities and to reduce behaviour that harms others; they would seem entirely justified in this case. I am less of a fan of Pigovian taxes to deal with internalities – that is to stop people from harming themselves. But as it turns out, red meat is bad for our health, as discussed in a recent news blog.[5]

So let us give Malthus his due. He might have got the detail wrong, but his principle still stands. I vote for the rehabilitation of Malthus.

— Richard Lilford, CLAHRC WM Director


  1. Malthus TR. An Essay on the Principle of Population. London, UK: J. Johnson, 1798.
  2. Lilford RJ. The Population of the World – Will Depend on What Happens in Africa. NIHR CLAHRC West Midlands News Blog. 9 January 2015.
  3. Steinfeld H, Gerber P, Wassenaar T, Castel V, Rosales M, de Hann C. Livestock’s Long Shadow: Environmental Issues and Options. Rome, Italy: Food and Agriculture Organization, 2006.
  4. Lilford RJ. An Issue of BMJ with Multiple Studies on Diet. NIHR CLAHRC West Midlands News Blog. 4 August 2017.
  5. Capewell S, Lilford R. Are nanny states healthier states? BMJ. 2016; 355: i6341.

A Secondary Sanitary Revolution? What About the First One?

Water and sanitation is being taken increasingly seriously in Low- and Middle-Income Countries (LMICs). This is a good thing because, despite improved treatment of diarrhoea and vaccination against rotavirus,[1] gastrointestinal diseases are one of the two biggest causes of death in children under the age of five.[2] Yet recent evaluations of water and sanitation interventions show patchy results [3] and are overall disappointing.[4] [5] Very few studies have been done in urban areas, but infant death rates in slums are unconscionably high.[6]

Why are water and sanitation interventions so disappointing in the LMICs of today when the Sanitary Revolution around the turn of the 19th century was so successful? Well it turns out that the Sanitary Revolution was a bit of a myth – Thomas McKeown, Professor of Social Medicine at the University of Birmingham, caused quite a stir by pointing this out in the 1970s.[7] The ‘historical epidemiology’ of this time period is intensely interesting. While sequential chlorination of water in North American cities in the early years of the 1900s was associated with corresponding dramatic drops in the incidence of typhoid fever,[8] establishment of water and sanitation in the Netherlands [9] and Estonia [10] produced no benefit whatsoever on gastrointestinal deaths. Only one-third of the reduction in gastrointestinal-related deaths observed in around the turn of the 18th century Germany could be attributed to water and sanitation improvements.[9]
So why do water and sanitation interventions produce such variable, and often disappointing, benefits? In rural India this can often be attributed to low use of facilities, but little or no health benefit has been observed, even when uptake has been high. A number of (non-exclusive) theories can be adduced:

1) The inadequate dose theory. This holds that the type of intervention deployed in LMICs has generally been inadequate. For example, pit latrines (classed as ‘improved sewerage’ by the UN) do not clean up the environment adequately.[11] Similarly, water pipes may be installed, but the water may be contaminated en route.[12] St Petersburg is a notorious example.

2) The tipping point theory. This theory is an elaboration of the above inadequate dose theory and postulates a non-linear relationship between the intensity, type of water and sanitation (facility), and coverage of interventions and health, with increasing and then decreasing returns to scale as shown in Figure 1. By this theory, many interventions (such as pit latrines) simply fail to reach the ‘tipping point’, especially in densely inhabited city areas.

085 DCB A Secondary Sanitary Revolution Fig 1

3) The deep contamination theory (Figure 2). By this theory contamination follows many routes and becomes embedded in local communities, with transmission routes that are frequently replenished, so that garbage dumps, flies, nappies, soil and the human gut all act as repositories of infection. Food may be contaminated along its supply chain, as well as in preparation. Floods sweep sewage out of drains and back into communities. Cleaning up such an environment moves the tipping point (shown in Figure 1) to the right (meaning it is harder to reach) and may also take time to effect – a point to which we return.


4) The multiple agent hypothesis. By this theory some germs are more easily eradicated than others. Typhoid is waterborne, but, unlike cholera, it cannot replicate in water. Ensuring uncontaminated water may be enough to eradicate this particular problem. However, hookworms are at the other end of the spectrum, since they can be carried asymptomatically and linger in soil. There is even some evidence that organisms gain virulence as they are passed rapidly from host to host.[13] So this theory predicts that some types of infection might decrease more rapidly than others in response to an intervention. Moreover, some real gains, with respect to some type of serious infection, might be obscured by little or no change in more common, but less serious infections.

5) The multiple causes theory. This theory relies on evidence that malnutrition and gastrointestinal infections are self-reinforcing. Certainly malnutrition is associated with an altered microbiome, which, in turn, reduces absorption of food, creating a vicious cycle.[14] The microbiome affects the immune system, which, in turn, affects resistance to infection.

6) The ‘double-handed’ hygiene hypothesis. Hygiene can compensate for dirty water and a contaminated environment, and some of the most consistently effective interventions in LMICs have been based on improved hygiene and near use decontamination.[4] [15] On the other hand, hygiene does not seem important in places where exposure to harmful pathogens is low and, in such circumstances, hygiene may be too fastidious, leading to allergic illnesses.

7) The insensitive outcome hypothesis. Measuring the health benefit of sanitation is not unproblematic – the standard question on diarrhoea enquires about loose stools over a three-day period, and the measurement error appears to be large.[16] An account of blood in stools, signifying dysentery (Shigella and amoeba) is more specific, but is much rarer, leading to imprecision (lack of statistical power). Anthropological measurements reflect long-term conditions, and many factors, including gastrointestinal infections and malnutrition (see above), and also age of weaning, birth weight, and mother’s weight (inter-generational effects). We are working on designing a better (equally sensitive, but more specific and less reactive) method to measure gastrointestinal health.[17]

There may well be an element of truth in all these hypotheses. If a fully functioning water and sewerage system was installed, lanes paved and drained, and garbage eliminated, then there would probably be an impressive and rapid improvement in gastrointestinal health, especially if malnutrition was also tackled. But the same water and sewerage system would probably have moderate and delayed benefits if not accompanied by the other measures mentioned. What nutrition and vaccination would achieve without water and sanitation is unknown, but as they are less expensive, the experiment should be tried in places where water and sanitation improvements are some time away. In-depth study of transmission routes will help explicate some of the other theories postulated and careful comparative studies will help identify the tipping point for the most cost-effective solutions. What is for sure is that science has a role to play in unravelling the process by which we may achieve a Second Sanitary Revolution.

— Richard Lilford, CLAHRC WM Director


  1. GBD Diarrhoeal Diseases Collaborators. Estimates of global, regional, and national morbidity, mortality, and aetiologies of diarrhoeal diseases: a systematic analysis for the Global Burden of Disease Study 2015. Lancet Infect Dis. 2017; 17: 909-48.
  2. Global Burden of Disease Pediatrics Collaboration. Global and National Burden of Diseases and Injuries Among Children and Adolescents Between 1990 and 2013. JAMA Pediatr. 2016; 170(3): 267-87.
  3. Lilford RJ, Oyebode O, Satterthwaite D, et al. Improving the health and welfare of people who live in slums. Lancet. 2017; 389: 559-70.
  4. Wolf J, Prüss-Ustün A, Cumming O, et al. Assessing the impact of drinking water and sanitation on diarrhoeal disease in low- and middle-income settings: systematic review and meta-regression. Trop Med Int Health. 2014; 19(8): 928-42.
  5. Fuller JA, Westphal JA, Kenney B, Eisenberg JNS. The joint effects of water and sanitation on diarrhoeal disease: a multicountry analysis of the Demographic and Health Surveys. Trop Med Int Health. 2015; 20(3): 284-92.
  6. Feikin DR, Olack B, Bigogo GM, et al. The burden of common infectious disease syndromes at the clinic and household level from population-based surveillance in rural and urban Kenya. PLoS One. 2011; 6: e16085.
  7. McKeown T, Record RG, Turner RD. An interpretation of the decline of mortality in England and Wales during the twentieth century. Popul Stud. 1975. 29(3): 391-422.
  8. Cutler D & Miller G. The Role of Public Health Improvements in Health Advances: The 20th Century United States. NBER Working Paper 10511. Cambridge, MA: National Bureau of Economic Research; 2004.
  9. Van Poppel F & van der Heijden C. The effects of water supply on infant and childhood mortality: a review of historical evidence. Health Trans Rev. 1997; 7(2): 113-48.
  10. Jaadla H & Puur A. The impact of water supply and sanitation on infant mortality: Individual-level evidence from Tartu, Estonia, 1897-1900. Popul Stud. 2016; 70(2): 163-79.
  11. Nakagiri A, Niwagaba CB, Nyenje PM, Kulabako RN, Tumuhairwe JB, Kansiime F. Are pit latrines in urban areas of sub-Saharan Africa performing? A review of usage, filling, insects and odour nuisances. BMC Public Health. 2016; 16: 120.
  12. Eschol J, Mahapatra P, Keshapagu S. Is fecal contamination of drinking water after collection associated with household water handling and hygiene practices? A study of urban slum households in Hyderabad, India. J Water Health. 2009; 7(1): 145-54.
  13. Ewald PW. Waterborne transmission and the evolution of virulence among gastrointestinal bacteria. Epidemiol Infect. 1991; 106: 83-119.
  14. Rook G, Bäckhed F, Levin BR, McFall-Ngai MJ, McLean AR. Evolution, human-microbe interactions, and life history plasticity. Lancet. 2017; 390: 521-30.
  15. Freeman MC, Garn JV, Sclar GD, Boisson S. The impact of sanitation on infectious disease and nutritional status: A systematic review and meta-analysis. Int J Hyg Environ Health. 2017; 220(6): 928-49.
  16. Schmidt WP, Arnold BF, Boisson S, et al. Epidemiological methods in diarrhoea studies – an update. Int J Epidemiol. 2011; 40(6): 1678-92.
  17. Lilford RJ. Protocol to Test Hypothesis That Streptococcal Infections and Their Sequelae Have Risen in Incidence Over the Last 14 Years in England. NIHR CLAHRC West Midlands News Blog. 13 January 2017.

Measuring the Quality of Health Care in Low-Income Settings

Measuring the quality of health care in High-Income Countries (HIC) is deceptively difficult, as shown by work carried out by many research groups, including CLAHRC WM.[1-5] However, a large amount of information is collected routinely by health care facilities in HICs. This data includes outcome data, such as Standardised Mortality Rates (SMRs), death rates from ’causes amenable to health care’, readmission rates, morbidity rates (such as pressure damage), and patient satisfaction, along with process data, such as waiting times, prescribing errors, and antibiotic use. There is controversy over many of these endpoints, and some are much better barometers of safety than others. While incident reporting systems provide a very poor basis for epidemiological studies (that is not their purpose), case-note review provides arguably the best and most widely used method for formal study of care quality – at least in hospitals.[3] [6] [7] Measuring safety in primary care is inhibited by the less comprehensive case-notes found in primary care settings as compared to hospital case-notes. Nevertheless, increasing amounts of process information is now available from general practices, particularly in countries (such as the UK) that collect this information routinely in electronic systems. It is possible, for example, to measure rates of statin prescriptions for people with high cardiovascular risk, and anticoagulants for people with ventricular fibrillation, as our CLAHRC has shown.[8] [9] HICs also conduct frequent audits of specific aspects of care – essentially by asking clinicians to fill in detailed pro formas for patients in various categories. For instance, National Audits in the UK have been carried out into all patients experiencing a myocardial infarction.[10] Direct observation of care has been used most often to understand barriers and facilitators to good practice, rather than to measure quality / safety in a quantitative way. However, routine data collection systems provide a measure of patient satisfaction with care – in the UK people who were admitted to hospital are surveyed on a regular basis [11] and general practices are required to arrange for anonymous patient feedback every year.[12] Mystery shoppers (simulated patients) have also been used from time to time, albeit not as a comparative epidemiological tool.[13]

This picture is very different in Low- and Middle-Income Countries (LMIC) and, again, it is yet more difficult to assess quality of out of hospital care than of hospital care.[14] Even in hospitals routine mortality data may not be available, let alone process data. An exception is the network of paediatric centres established in Kenya by Prof Michael English.[15] Occasionally large scale bespoke studies are carried out in LMICs – for example, a recent study in which CLAHRC WM participated, measured 30 day post-operative mortality rates in over 60 hospitals across low-, middle- and high-income countries.[16]

The quality and outcomes of care in community settings in LMICs is a woefully understudied area. We are attempting to correct this ‘dearth’ of information in a study in nine slums spread across four African and Asian countries. One of the largest obstacles to such a study is the very fragmented nature of health care provision in community settings in LMICs – a finding confirmed by a recent Lancet commission.[17] There are no routine data collection systems, and even deaths are not registered routinely. Where to start?

In this blog post I lay out a framework for measurement of quality from largely isolated providers, many of whom are unregulated, in a system where there is no routine system of data and no archive of case-notes. In such a constrained situation I can think of three (non-exclusive) types of study:

  1. Direct observation of the facilities where care is provided without actually observing care or its effects. Such observation is limited to some of the basic building blocks of a health care system – what services are present (e.g. number of pharmacies per 1,000 population) and availability (how often the pharmacy is open; how often a doctor / nurse / medical officer is available for consultation in a clinic). Such a ‘mapping’ exercise does not capture all care provided – e.g. it will miss hospital care and municipal / hospital-based outreach care, such as vaccination provided by Community Health Workers. It will also miss any IT based care using apps or online consultations.
  2. Direct observation of the care process by external observers. Researchers can observe care from close up, for example during consultations. Such observations can cover the humanity of care (which could be scored) and/or technical quality (which again could be scored against explicit standards and/or in a holistic (implicit) basis).[6] [7] An explicit standard would have to be based mainly on ‘if-then’ rules – e.g. if a patient complained of weight loss, excessive thirst, or recurrent boils, did the clinicians test their urine for sugar; if the patient complained of persistent productive cough and night sweats was a test for TB arranged? Implicit standards suffer from low reliability (high inter-observer variation).[18] Moreover, community providers in LMICs are arguably likely to be resistant to what they might perceive as an intrusive or even threatening form of observation. Those who permitted such scrutiny are unlikely to constitute a random sample. More vicarious observations – say of the length of consultations – would have some value, but might still be seen as intrusive. Provided some providers would permit direct observation, their results may represent an ‘upper bound’ on performance.
  3. Quality as assessed through the eyes of the patient / members of the public. Given the limitations of independent observation, the lack of anamnestic records of clinical encounters in the form of case-notes, absence of routine data, and likely limitations on access by independent direct observers, most information may need to be collected from patients themselves, or as we discuss, people masquerading as patients (simulated patients / mystery shoppers). The following types of data collection methods can be considered:
    1. Questions directed at members of the public regarding preventive services. So, households could be asked about vaccinations, surveillance (say for malnutrition), and their knowledge of screening services offered on a routine basis. This is likely to provide a fairly accurate measure of the quality of preventive services (provided the sampling strategy was carefully designed to yield a representative sample). This method could also provide information on advice and care provided through IT resources. This is a situation where some anamnestic data collection would be possible (with the permission of the respondent) since it would be possible to scroll back through the electronic ‘record’.
    2. Opinion surveys / debriefing following consultations. This method offers a viable alternative to observation of consultations and would be less expensive (though still not inexpensive). Information on the kindness / humanity of services could be easily obtained and quantified, along with ease of access to ambulatory and emergency care.[19] Measuring clinical quality would again rely on observations against a gold standard,[20] but given the large number of possible clinical scenarios standardising quality assessment would be tricky. However, a coarse-grained assessment would be possible and, given the low quality levels reported anecdotally, failure to achieve a high degree of standardisation might not vitiate collection of important information. Such a method might provide insights into the relative merits and demerits of traditional vs. modern health care, private vs. public, etc., provided that these differences were large.
    3. Simulated patients offering standardised clinical scenarios. This is arguably the optimal method of technical quality assessment in settings where case-notes are perfunctory or not available. Again, consultations could be scored for humanity of care and clinical/ technical competence, and again explicit and/or implicit standards could be used. However, we do not believe it would be ethical to use this method without obtaining assent from providers. There are some examples of successful use of the methods in LMICs.[21] [22] However, if my premise is accepted that providers must assent to use of simulated patients, then it is necessary to first establish trust between providers and academic teams, and this takes time. Again, there is a high probability that only the better providers will provide assent, in which case observations would likely represent ‘upper bounds’ on quality.

In conclusion, I think that the basic tools of quality assessment, in the current situation where direct observation and/or simulated patients are not acceptable, is a combination of:

  1. Direct observation of facilities that exist, along with ease of access to them, and
  2. Debriefing of people who have recently used the health facilities, or who might have received preventive services that are not based in these facilities.

We do not think that the above mentioned shortcomings of these methods is a reason to eschew assessment of service quality in community settings (such as slums) in LMICs – after all, one of the most powerful levers to improvement is quantitative evidence of current care quality.[23] [24] The perfect should not be the enemy of the good. Moreover, if the anecdotes I have heard regarding care quality (providers who hand out only three types of pill – red, yellow and blue; doctors and nurses who do not turn up for work; prescription of antibiotics for clearly non-infectious conditions) are even partly true, then these methods would be more than sufficient to document standards and compare them across types of provider and different settings.

— Richard Lilford, CLAHRC WM Director


  1. Brown C, Hofer T, Johal A, Thomson R, Nicholl J, Franklin BD, Lilford RJ. An epistemology of patient safety research: a framework for study design and interpretation. Part 1. Conceptualising and developing interventions. Qual Saf Health Care. 2008; 17(3): 158-62.
  2. Brown C, Hofer T, Johal A, Thomson R, Nicholl J, Franklin BD, Lilford RJ. An epistemology of patient safety research: a framework for study design and interpretation. Part 2. Study design. Qual Saf Health Care. 2008; 17(3): 163-9.
  3. Brown C, Hofer T, Johal A, Thomson R, Nicholl J, Franklin BD, Lilford RJ. An epistemology of patient safety research: a framework for study design and interpretation. Part 3. End points and measurement. Qual Saf Health Care. 2008; 17(3): 170-7.
  4. Brown C, Hofer T, Johal A, Thomson R, Nicholl J, Franklin BD, Lilford RJ. An epistemology of patient safety research: a framework for study design and interpretation. Part 4. One size does not fit all. Qual Saf Health Care. 2008; 17(3): 178-81.
  5. Brown C, Lilford R. Evaluating service delivery interventions to enhance patient safety. BMJ. 2008; 337: a2764.
  6. Benning A, Ghaleb M, Suokas A, Dixon-Woods M, Dawson J, Barber N, et al. Large scale organisational intervention to improve patient safety in four UK hospitals: mixed method evaluation. BMJ. 2011; 342: d195.
  7. Benning A, Dixon-Woods M, Nwulu U, Ghaleb M, Dawson J, Barber N, et al. Multiple component patient safety intervention in English hospitals: controlled evaluation of second phase. BMJ. 2011; 342: d199.
  8. Finnikin S, Ryan R, Marshall T. Cohort study investigating the relationship between cholesterol, cardiovascular risk score and the prescribing of statins in UK primary care: study protocol. BMJ Open. 2016; 6(11): e013120.
  9. Adderley N, Ryan R, Marshall T. The role of contraindications in prescribing anticoagulants to patients with atrial fibrillation: a cross-sectional analysis of primary care data in the UK. Br J Gen Pract. 2017. [ePub].
  10. Herrett E, Smeeth L, Walker L, Weston C, on behalf of the MINAP Academic Group. The Myocardial Ischaemia National Audit Project (MINAP). Heart. 2010; 96: 1264-7.
  11. Care Quality Commission. Adult inpatient survey 2016. Newcastle-upon-Tyne, UK: Care Quality Commission, 2017.
  12. Ipsos MORI. GP Patient Survey. National Report. July 2017 Publication. London: NHS England, 2017.
  13. Grant C, Nicholas R, Moore L, Sailsbury C. An observational study comparing quality of care in walk-in centres with general practice and NHS Direct using standardised patients. BMJ. 2002; 324: 1556.
  14. Nolte E & McKee M. Measuring and evaluating performance. In: Smith RD & Hanson K (eds). Health Systems in Low- and Middle-Income Countries: An economic and policy perspective. Oxford: Oxford University Press; 2011.
  15. Tuti T, Bitok M, Malla L, Paton C, Muinga N, Gathara D, et al. Improving documentation of clinical care within a clinical information network: an essential initial step in efforts to understand and improve care in Kenyan hospitals. BMJ Global Health. 2016; 1(1): e000028.
  16. Global Surg Collaborative. Mortality of emergency abdominal surgery in high-, middle- and low-income countries. Br J Surg. 2016; 103(8): 971-88.
  17. McPake B, Hanson K. Managing the public-private mix to achieve universal health coverage. Lancet. 2016; 388: 622-30.
  18. Lilford R, Edwards A, Girling A, Hofer T, Di Tanna GL, Petty J, Nicholl J. Inter-rater reliability of case-note audit: a systematic review. J Health Serv Res Policy. 2007; 12(3): 173-80.
  19. Schoen C, Osborn R, Huynh PT, Doty M, Davis K, Zapert K, Peugh J. Primary Care and Health System Performance: Adults’ Experiences in Five Countries. Health Aff. 2004.
  20. Kruk ME & Freedman LP. Assessing health system performance in developing countries: A review of the literature. Health Policy. 2008; 85: 263-76.
  21. Smith F. Private local pharmacies in low- and middle-income countries: a review of interventions to enhance their role in public health. Trop Med Int Health. 2009; 14(3): 362-72.
  22. Satyanarayana S, Kwan A, Daniels B, Subbaramn R, McDowell A, Bergkvist S, et al. Use of standardised patients to assess antibiotic dispensing for tuberculosis by pharmacies in urban India: a cross-sectional study. Lancet Infect Dis. 2016; 16(11): 1261-8.
  23. Kudzma E C. Florence Nightingale and healthcare reform. Nurs Sci Q. 2006; 19(1): 61-4.
  24. Donabedian A. The end results of health care: Ernest Codman’s contribution to quality assessment and beyond. Milbank Q. 1989; 67(2): 233-56.

Patient and Public Involvement: Direct Involvement of Patient Representatives in Data Collection

It is widely accepted that the public and patient voice should be heard loud and clear in the selection of studies, in the design of those studies, and in the interpretation and dissemination of the findings. But what about involvement of patient and the public in the collection of data? Before science became professionalised, all scientists could have been considered members of the public. Robert Hooke, for example, could have called himself architect, philosopher, physicist, chemist, or just Hooke. Today, the public are involved in data collection in many scientific enterprises. For example, householders frequently contribute data on bird populations, and Prof Brian Cox involved the public in the detection of new planets in his highly acclaimed television series. In medicine, patients have been involved in collecting data; for example patients with primary biliary cirrhosis were the data collectors in a randomised trial.[1] However, the topic of public and patient involvement in data collection is deceptively complex. This is because there are numerous procedural safeguards governing access to users of the health service and that restrict disbursement of the funds that are used to pay for research.

Let us consider first the issue of access to patients. It is not permissible to collect research data without undergoing certain procedural checks; in the UK it is necessary to be ratified by the Disclosure and Barring Service (DBS) and to have necessary permissions from the institutional authorities. You simply cannot walk onto a hospital ward and start handing out questionnaires or collecting blood samples.

Then there is the question of training. Before collecting data from patients it is necessary to be trained in how to do so, covering both salient ethical and scientific principles. Such training is not without its costs, which takes us to the next issue.

Researchers are paid for their work and, irrespective of whether the funds are publically or privately provided, access to payment is governed by fiduciary and equality/diversity legislation and guidelines. Access to scarce resources is usually governed by some sort of competitive selection process.

None of the above should be taken as an argument against patients and the public taking part in data collection. It does, however, mean that this needs to be a carefully managed process. Of course things are very much simpler if access to patients is not required. For example, conducting a literature survey would require only that the person doing it was technically competent and in many cases members of the public would already have all, or some, of the necessary skills. I would be very happy to collaborate with a retired professor of physics (if anyone wants to volunteer!). But that is not the point. The point is that procedural safeguards must be applied, and this entails management structures that can manage the process.

Research may be carried out by accessing members of the public who are not patients, or at least who are not accessed through the health services. As far as I know there are no particular restrictions on doing so, and I guess that such contact is governed by the common law covering issues such as privacy, battery, assault, and so on. The situation becomes different, however, if access is achieved through a health service organisation, or conducted on behalf of an institution, such as a university. Then presumably any member of the public wishing to collect data from other members of the public would fall under the governance arrangements of the relevant institution. The institution would have to ensure not only that the study was ethical, but that the data-collectors had the necessary skills and that funds were disbursed in accordance with the law. Institutions already deploy ‘freelance’ researchers, so I presume that the necessary procedural arrangements are already in place.

This analysis was stimulated by a discussion in the PPI committee of CLAHRC West Midlands, and represents merely my personal reflections based on first principles. It does not represent my final, settled position, let alone that of the CLAHRC WM, or any other institution. Rather it is an invitation for further comment and analysis.

— Richard Lilford, CLAHRC WM Director


  1. Browning J, Combes B, Mayo MJ. Long-term efficacy of sertraline as a treatment for cholestatic pruritus in patients with primary biliary cirrhosis. Am J Gastroenterol. 2003; 98: 2736-41.

Cognitive Behavioural Therapy vs. Mindfulness Therapy

It is known that mindfulness therapy is effective in improving depression and, in many circumstances, in improving chronic pain (see later in News Blog). What is not so clear is whether it is better than the more standard therapy of cognitive behavioural therapy (CBT).

Cognitive behavioural therapy aims to abolish or reduce painful and harmful thoughts. Mindfulness therapy on the other hand does not seek to extirpate the depressing thoughts, but rather to help the person disassociate themselves from the harmful consequences of these thoughts. It often involves an element of meditation.

We have found three recent studies which compare CBT and mindfulness therapy head-to-head for depression.[1-3] In all three RCTs the two therapies were a dead heat. In short, both methods seem equally effective and certainly they are both better than nothing. But does this mean that they are equal; that the choice does not matter one way or the other?

In this article I argue that the fact that the two therapies all equally effective in improving mood, does not mean that they are equivalent. This is because they are designed to have different effects – abolition of harmful thoughts in one case, learning to live with them in the other. So it is reasonable to ask which one would prefer, abolishing the painful thoughts or simply learning not to be affected by them.

Philosophically, the argument behind CBT is that thoughts, at least at a certain level, are a kind of behaviour. They are a behaviour in the sense that they can be changed under conscious control. Mindfulness therapy does not attempt to ‘over-write’ thoughts. This means that the two therapies, in so far as they achieve their objectives, are not philosophically equivalent. Moreover, there are arguments in favour of removing the harmful thoughts, even if this does not result in any greater improvement in mood than the counter-factural. Consider a man whose wife is annoyed by certain movements that he is unable to control. It is surely much better, both from her point of view and from the point of view of the husband, that these painful thoughts should be removed altogether, rather than just tolerated. Alternatively, consider a person who is chronically distressed by a recurring memory of the painful death of a parent. Again, it is surely better that this person trains himself to think of another aspect of the parent’s life whenever the troubling thoughts recur, than to simply continue to remember the death, but not get upset by it.

So, I think that CBT is philosophically preferable to mindfulness therapy, even if it is no more effective in improving mood. From a philosophical point of view, it is important to develop a high rectitude way of thinking. When negative or morally questionable thoughts pop into the brain, as they do from time to time, these should be suppressed. A racist thought, for example, should be replaced with thoughts of higher rectitude. It is the purpose of the examined life to be able to control negative or bigoted thoughts and supplant them with more positive thoughts under conscious control. From this philosophical perspective CBT can be seen as an extension of the human ability to supplant negative or reprehensible thoughts with ones that are more positive or of higher rectitude. I choose CBT over mindfulness; for all that they might be equally effective in elevating mood, psychiatric treatments have implications that go beyond purely clinical outcomes – since they affect the mind there is always a philosophical dimension.

— Richard Lilford, CLAHRC WM Director


  1. Manicavasagar V, Perich T, Parker G. Cognitive Predicators of Change in Cognitive Behaviour Therapy and Mindfulness-Based Cognitive Therapy for Depression. Behav Cogn Psychother. 2012; 40: 227-32.
  2. Omidi A, Mohammadkhani P, Mohammadi A, Zargar F. Comparing Mindfulness Based Cognitive Therapy and Traditional Cognitive Behavior Therapy With Treatments as Usual on Reduction of Major Depressive Symptoms. Iran Red Crescent Med J. 2013; 15(2): 142-6.
  3. Sundquist J, Lilja A, Palmér K, et al. Mindfulness group therapy in primary care patients with depression, anxiety and stress and adjustment disorders: randomised controlled trial. Br J Psychiatry. 2015; 206(2): 128-35.

The Beneficial Effects of Taking Part in International Research: an Old Chestnut Revisited

Two recent and well-written articles grapple with this question of whether or not clinical trials are beneficial, net of any benefit conferred by the therapeutic modalities evaluated in those trials.[1] [2]

The first study from the Netherlands concerns the effect of taking part in clinical trials where controls are made up of people not participating in trials (presumably because they were not offered entry in the trial).[1] This is the topic of a rather extensive literature, including a study to which I contributed.[3] The latter study found that the putative ‘trial effect’ applied only in circumstances where care given to control patients was not protocol-directed. In other words, our results suggested that the ‘trial effect’ was really a ‘protocol effect’. In that case the effect should be ephemeral and disappear as greater proportions of care become protocolised. And that is what appears to have happened – Lin, et al.[1] report no benefit to trial participants versus non-trial patients for the highly protocolised disease Hodgkin lymphoma. They speculate that while participation in trials does not affect individual patient care in the short-term, hosting trials does sensitise clinicians at an institutional level, so that they are more likely than clinicians from non-participating hospitals to practice evidence-based care. However, they offer no direct evidence for this assertion. Such evidence is, however, provided by the next study.

The effects of high participation rates in clinical trials at the hospital level is evaluated in an elegant study recently published in the prestigious journal ‘Gut’.[2] The team of authors (that includes prominent civil servants and many distinguished cancer specialists and statisticians) compared outcomes from colon cancer according to the extent to which the hospital providing treatment participated in trials. This ingenious study was accomplished by linking the NIHR’s data on clinical trials participation to cancer registry data and Hospital Episode Statistics. It turned out that risk-adjusted survival was significantly better in the high participation hospitals than in lower participation hospitals, even after substantial risk-adjustment. “Residual confounding” do I hear you say? Perhaps, but the authors have two further lines of evidence for the causal explanation. First, they documented a dose-response; the greater the level of participation, the greater the improvement in survival. Of course, an unknown confounder that was correlated with participation rates would produce just such a finding. The second line of evidence is more impressive – the longer the duration over which a hospital had sustained high participation rates, the greater the effect. Again, of course, this argument is not impregnable – duration might not serve as a good Instrumental Variable. How might the case be further strengthened (or refuted)? By unravelling the theoretical pathway between explanatory and outcome variables.[4] Since this is a database study, the process variables that might mediate the putative effect were not available to the authors. However, separate studies have indeed found an association between improved processes of care and trial participation.[5] Taken in the round, I think that a cause/effect explanation holds (>90% of my probability density favours the causal explanation).

— Richard Lilford, CLAHRC WM Director


  1. Liu L, Giusti F, Schaapveld M, et al. Survival differences between patients with Hodgkin lymphoma treated inside and outside clinical trials. A study based on the EORTC-Netherlands Cancer Registry linked data with 20 years of follow-up. Br J Haematol. 2017; 176: 65-75.
  2. Downing A, Morris EJA, Corrigan N, et al. High hospital research participation and improved colorectal cancer survival outcomes: a population-based study. Gut. 2017; 66: 89-96.
  3. Braunholtz DA, Edwards SJ, Lilford RJ. Are randomized clinical trials good for us (in the short term)? Evidence for a “trial effect”. J Clin Epidemiol. 2001; 54(3): 217-24.
  4. 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 pointsBMJ. 2010; 341: c4413.
  5. Selby P. The impact of the process of clinical research on health service outcomes. Ann Oncol. 2011; 22(s7): vii2-4.

Private Consultations More Effective than Public Provision in Rural India

Doing work across high-income countries (CLAHRC WM) and lower income countries (CLAHRC model for Africa) provides interesting opportunities to compare and contrast. For example, our work on user fees in Malawi [1] mirrors that in high-income countries [2] – in both settings, relatively small increments in out-of-pocket expenses results in a large decrease in demand and does so indiscriminately (the severity of disease among those who access services is not shifted towards more serious cases). However, the effect of private versus public provision of health care is rather more nuanced.

News Blog readers are likely aware of the famous RAND study in the US.[3] People were randomised to receive their health care on a fee-for-service basis (‘privately’) vs. on a block contract basis (as in a public service). The results showed that fee-for-service provision resulted in more services being provided (interpreted as over-servicing), but that patients were more satisfied clients, compared to those experiencing public provision. Clinical quality was no different. In contrast, a study from rural India [4] found that private provision results in markedly improved quality compared to public provision, albeit with a degree of over-servicing.

The Indian study used ‘standardised patients’ (SPs) to measure the quality of care during consultations covering three clinical scenarios – angina, asthma and the parent of a child with dysentery. The care SPs received was scored against an ideal standard. Private providers spent more time/effort collecting the data essential for making a correct diagnosis, and were more likely to give treatment appropriate to the condition. First, they compared private providers with public providers and found that the former spent 30% more time gathering information from the SPs than the public providers. Moreover, the private providers were more likely to be present when the patient turned up for a consultation. There was a positive correlation between the magnitude of fees charged by private providers and time spent eliciting symptoms and signs, and the probability that the correct treatment would be provided. However, the private providers are often not doctors, so this result could reflect different professional mix, at least in part. To address this point, a second study was done whereby the same set of doctors were presented with the same clinical cases – a ‘dual sample’. The results were even starker, with doctors spending twice as long with each patient when seen privately.

Why were these results from rural India so different from the RAND study? The authors suggest that taking a careful history and examination is part of the culture for US doctors, and that they had reach a kind of asymptote, such that context made little difference to this aspect of their behaviour. Put another way, there was little headroom for an incentive system to drive up quality of care. However, in low-income settings where public provision is poorly motivated and regulated, fee-for-service provision drives up quality. The same seems to apply to education, where private provision was found to be of higher quality than public provision in low-income settings – see previous News Blog.[5]

However, it should be acknowledged that none of the available alternatives in rural India were good ones. For example, the probability of receiving the correct diagnosis varied across the private and public provider, but never exceeded 15%, while the rate of correct treatment varied from 21% to about 50%. Doctors were more likely than other providers to provide the correct diagnosis. A great deal of treatment was inappropriate. CLAHRC West Midlands’ partner organisation in global health is conducting a study of service provision in slums with a view to devising affordable models of improving health care.[6]

— Richard Lilford, CLAHRC WM Director


  1. Watson SI, Wroe EB, Dunbar EL, et al. The impact of user fees on health services utilization and infectious disease diagnoses in Neno District, Malawi: a longitudinal, quasi-experimental study. BMC Health Serv Res. 2016; 16: 595.
  2. Carrin G & Hanvoravongchai P. Provider payments and patient charges as policy tools for cost-containment: How successful are they in high-income countries? Hum Resour Health. 2003; 1: 6.
  3. Brook RH, Ware JE, Rogers WH, et al. The effect of coinsurance on the health of adults. Results from the RAND Health Insurance Experiment. Santa Monica, CA: RAND Corporation, 1984.
  4. Das J, Holla A, Mohpal A, Muralidharan K. Quality and Accountability in Healthcare Delivery: Audit-Study Evidence from Primary Care in India . Am Econ Rev. 2016; 106(12): 3765-99.
  5. Lilford RJ. League Tables – Not Always Bad. NIHR CLAHRC West Midlands News Blog. 28 August 2015.
  6. Lilford RJ. Between Policy and Practice – the Importance of Health Service Research in Low- and Middle-Income Countries. NIHR CLAHRC West Midlands News Blog. 27 January 2017.

And Today We Have the Naming of Parts*

Management research, health services research, operations research, quality and safety research, implementation research – a crowded landscape of words describing concepts that are, at best, not entirely distinct, and at worst synonyms. Some definitions are given in Table 1. Perhaps the easiest one to deal with is ‘operations research’, which has a rather narrow meaning and is used to describe mathematical modelling techniques to derive optimal solutions to complex problems typically dealing with the flow of objects (people) over time. So it is a subset of the broader genre covered by this collection of terms. Quality and safety research puts the cart before the horse by defining the intended objective of an intervention, rather than where in the system the intervention impacts. Since interventions at a system level may have many downstream effects, it seems illogical and indeed potentially harmful, to define research by its objective, an argument made in greater detail elsewhere.[1]

Health Services Research (HSR) can be defined as management research applied to health, and is an acceptable portmanteau term for the construct we seek to define. For those who think the term HSR leaves out the development and evaluation of interventions at service level, the term Health Services and Delivery Research (HS&DR) has been devised. We think this is a fine term to describe management research as applied to the health services, and are pleased that the NIHR has embraced the term, and now has two major funding schemes ­– the HTA programme dealing with clinical research, and the HS&DR dealing with management research. In general, interventions and their related research programmes can be neatly represented as shown in the framework below, represented in a modified Donabedian chain:

078 DCB - Figure 1

So what about implementation research then? Wikipedia defines implementation research as “the scientific study of barriers to and methods of promoting the systematic application of research findings in practice, including in public policy.” However, a recent paper in BMJ states that “considerable confusion persists about its terminology and scope.”[2] Surprised? In what respect does implementation research differ from HS&DR?

Let’s start with the basics:

  1. HS&DR studies interventions at the service level. So does implementation research.
  2. HS&DR aims to improve outcome of care (effectiveness / safety / access / efficiency / satisfaction / acceptability / equity). So does implementation research.
  3. HS&DR seeks to improve outcomes / efficiency by making sure that optimum care is implemented. So does implementation research.
  4. HS&DR is concerned with implementation of knowledge; first knowledge about what clinical care should be delivered in a given situation, and second about how to intervene at the service level. So does implementation research.

This latter concept, concerning the two types of knowledge (clinical and service delivery) that are implemented in HS&DR is a critical one. It seems poorly understood and causes many researchers in the field to ‘fall over their own feet’. The concept is represented here:

078 DCB - Figure 2HS&DR / implementation research resides in the South East quadrant.

Despite all of this, some people insist on keeping the distinction between HS&DR and Implementation Research alive – as in the recent Standards for Reporting Implementation studies (StaRI) Statement.[3] The thing being implemented here may be a clinical intervention, in which case the above figure applies. Or it may be a service delivery intervention. Then they say that once it is proven, it must be implemented, and this implementation can be studied – in effect they are arguing here for a third ring:

078 DCB - Figure 3

This last, extreme South East, loop is redundant because:

  1. Research methods do not turn on whether the research is HS&DR or so-called Implementation Research (as the authors acknowledge). So we could end up in the odd situation of the HS&DR being a before and after study, and the Implementation Research being a cluster RCT! The so-called Implementation Research is better thought of as more HS&DR – seldom is one study sufficient.
  2. The HS&DR itself requires the tenets of Implementation Science to be in place – following the MRC framework, for example – and identifying barriers and facilitators. There is always implementation in any trial of evaluative research, so all HS&DR is Implementation Research – some is early and some is late.
  3. Replication is a central tenet of science and enables context to be explored. For example, “mother and child groups” is an intervention that was shown to be effective in Nepal. It has now been ‘implemented’ in six further sites under cluster RCT evaluation. Four of the seven studies yielded positive results, and three null results. Comparing and contrasting has yielded a plausible theory, so we have a good idea for whom the intervention works and why.[4] All seven studies are implementations, not just the latter six!

So, logical analysis does not yield any clear distinction between Implementation Research on the one hand and HS&DR on the other. The terms might denote some subtle shift of emphasis, but as a communication tool in a crowded lexicon, we think that Implementation Research is a term liable to sow confusion, rather than generate clarity.

Table 1

Term Definitions Sources
Management research “…concentrates on the nature and consequences of managerial actions, often taking a critical edge, and covers any kind of organization, both public and private.” Easterby-Smith M, Thorpe R, Jackson P. Management Research. London: Sage, 2012.
Health Services Research (HSR) “…examines how people get access to health care, how much care costs, and what happens to patients as a result of this care.” Agency for Healthcare Research and Quality. What is AHRQ? [Online]. 2002.
HS&DR “…aims to produce rigorous and relevant evidence on the quality, access and organisation of health services, including costs and outcomes.” INVOLVE. National Institute for Health Research Health Services and Delivery Research (HS&DR) programme. [Online]. 2017.
Operations research “…applying advanced analytical methods to help make better decisions.” Warwick Business School. What is Operational Research? [Online]. 2017.
Patient safety research “…coordinated efforts to prevent harm, caused by the process of health care itself, from occurring to patients.” World Health Organization. Patient Safety. [Online]. 2017.
Comparative Effectiveness research “…designed to inform health-care decisions by providing evidence on the effectiveness, benefits, and harms of different treatment options.” Agency for Healthcare Research and Quality. What is Comparative Effectiveness Research. [Online]. 2017.
Implementation research “…the scientific inquiry into questions concerning implementation—the act of carrying an intention into effect, which in health research can be policies, programmes, or individual practices (collectively called interventions).” Peters DH, Adam T, Alonge O, Agyepong IA, Tran N. Implementation research: what it is and how to do it. BMJ. 2013; 347: f6753.

We have ‘audited’ David Peters’ and colleagues BMJ article and found that every attribute they claim for Implementation Research applies equally well to HS&DR, as you can see in Table 2. However, this does not mean that we should abandon ‘Implementation Science’ – a set of ideas useful in designing an intervention. For example, stakeholders of all sorts should be involved in the design; barriers and facilitators should be identified; and so on. By analogy, I think Safety Research is a back-to-front term, but I applaud the tools and insights that ‘safety science’ provides.

Table 2

“…attempts to solve a wide range of implementation problems”
“…is the scientific inquiry into questions concerning implementation – the act of carrying an intention into effect, which in health research can be policies, programmes, or individual practices (…interventions).”
“…can consider any aspect of implementation, including the factors affecting implementation, the processes of implementation, and the results of implementation.”
“The intent is to understand what, why, and how interventions work in ‘real world’ settings and to test approaches to improve them.”
“…seeks to understand and work within real world conditions, rather than trying to control for these conditions or to remove their influence as causal effects.”
“…is especially concerned with the users of the research and not purely the production of knowledge.”
“…uses [implementation outcome variables] to assess how well implementation has occurred or to provide insights about how this contributes to one’s health status or other important health outcomes.
…needs to consider “factors that influence policy implementation (clarity of objectives, causal theory, implementing personnel, support of interest groups, and managerial authority and resources).”
“…takes a pragmatic approach, placing the research question (or implementation problem) as the starting point to inquiry; this then dictates the research methods and assumptions to be used.”
“…questions can cover a wide variety of topics and are frequently organised around theories of change or the type of research objective.”
“A wide range of qualitative and quantitative research methods can be used…”
“…is usefully defined as scientific inquiry into questions concerning implementation—the act of fulfilling or carrying out an intention.”

 — Richard Lilford, CLAHRC WM Director and Peter Chilton, Research Fellow


  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. Peters DH, Adam T, Alonge O, Agyepong IA, Tran N. Implementation research: what it is and how to do it. BMJ. 2013; 347: f6753.
  3. Pinnock H, Barwick M, Carpenter CR, et al. Standards for Reporting Implementation Studies (StaRI) Statement. BMJ. 2017; 356: i6795.
  4. Prost A, Colbourn T, Seward N, et al. Women’s groups practising participatory learning and action to improve maternal and newborn health in low-resource settings: a systematic review and meta-analysis. Lancet. 2013; 381: 1736-46.

*Naming of Parts by Henry Reed, which Ray Watson alerted us to:

Today we have naming of parts. Yesterday,

We had daily cleaning. And tomorrow morning,

We shall have what to do after firing. But to-day,

Today we have naming of parts. Japonica

Glistens like coral in all of the neighbouring gardens,

And today we have naming of parts.