A Novel Drug for Tuberculosis

Once rampant across the globe Tuberculosis has been brought under control, first by improved hygiene standards, and then antibiotic drugs, such as isoniazid and rifampicin, developed in the 1950s and 1960s. However, it remains one of the top 10 causes of death across the world, infecting 10.4 million people and killing 1.8 million in 2015, the vast majority (95%) in low- and middle-income countries.[1] Further, there has been a rise of TB strains that are resistant to antibiotics – around 480,000 people developed multi-drug resistant TB (MDR-TB) in 2015.[1] Of these, only 52% were successfully treated by second-line treatment options, such as extensive chemotherapy. More worryingly, there has been a rise in cases developing extensive drug resistance (XDR-TB), which has very limited treatment options. One of the United Nation’s Sustainable Development Goals is to end the TB epidemic by 2030, but to do this new antibiotics are needed to which no resistance has developed.

University of Warwick researcher Gregory Challis, together with Eshwar Mahenthiralingam and colleagues, recently discovered a promising candidate – gladiolin. [2] Bacteria belonging to the genus Burkholderia are able to thrive in a diverse range of environments thanks to their ability to produce potent antibiotics to remove any competition. Researchers were able to isolate gladiolin by screening one such strain, B. gladioli, that was taken from a child with cystic fibrosis. Gladiolin works by inhibiting RNA polymerase (a validated drug target in TB), has significantly improved chemical stability compared to structurally similar antibiotics, and has low cytotoxicity in mammals. Further research found that while gladiolin was less effective (compared to isoniazid and rifampicin) against strains of TB with no resistance, it had good activity against several strains of TB that were resistant to isoniazid and rifampicin. It is hoped that gladiolin will be the starting point for developing new drugs that can tackle MDR-TB and XDR-TB.

— Peter Chilton, Research Fellow

References:

1. World Health Organization. Tuberculosis Fact Sheet. 2017.
2. Song L, Jenner M, Masschelein J, et al. Discovery and Biosynthesis of Gladiolin: A Burkholderia gladioli Antibiotic with Promising Activity against Mycobacterium tuberculosis. J Am Chem Soc. 2017; 139(23): 7974-81.

Declining Readmission Rates – Are They Associated with Increased Mortality?

I have always been a bit nihilistic about reducing readmission rates to hospitals.[1][2] However, I may have been overly pessimistic. A new study confirms that it is possible to reduce readmission rates by imposing financial incentives.[3] Importantly, this does not seem to have caused an increase in mortality – as might occur if hospitals were biased against re-admitting sick patients in order to avoid a financial penalty. “False null result” (type two error), do I hear you ask? Probably not, since the data are based on nearly seven million admissions. In fact, 30 day mortality rates were slightly lower among hospitals that reduced readmission rates.

— Richard Lilford, CLAHRC WM Director

References:

1. Lilford RJ. If Not Preventable Deaths, Then What About Preventable Admissions? NIHR CLAHRC West Midlands News Blog. 6 May 2016.
2. Lilford RJ. Unintended Consequences of Pay-For-Performance Based on Readmissions. NIHR CLAHRC West Midlands News Blog. 13 January 2017.
3. Joynt KE, & Maddox TM. Readmissions Have Declined, and Mortality Has Not Increased. The Importance of Evaluating Unintended Consequences. JAMA. 2017; 318(3): 243-4.

Predicting Readmissions on the Basis of a Well-Known Risk of Readmission Score

A recent NIHR CLAHRC West Midlands study examined a score based on co-morbidities, hospital use before the index admission, length of stay, and rate of admission – the LACE score.[1] The findings broadly corroborate the score and previous evidence – high scores are statistically associated with risk of readmission, but predictive accuracy is low and hardly likely to improve on clinical assessment; no doctor would use such a test to identify patients. This is an inpatient study based on over 90,000 admissions. We do not want every clinical action to be codified in a score – it is a waste of time. Moreover, most readmissions are caused by a new problem.[2] So a more sensible way forward, from my point of view, would be a general index of risk of deterioration to cover patients at all points in their journey. Would the ‘frailty index’ [3] [4] serve this purpose perfectly well?

— Richard Lilford, CLAHRC WM Director

References:

1. Damery S, Combes G. Evaluating the predictive strength of the LACE index in identifying patients at high risk of hospital readmission following an inpatient episode: a retrospective cohort study. BMJ Open. 2017; 7: e016921.
2. Lilford RJ. Unintended Consequences of Pay-for-Performance Based on Readmissions. NIHR CLAHRC West Midlands News Blog. 13 January 2017.
3. Lilford RJ. Future Trends in NHS. NIHR CLAHRC West Midlands News Blog.
4. Clegg A, Bates C, Young J, et al. Development and validation of an electronic frailty index using routine primary care electronic health record data. Age Ageing. 2016.

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

Reference:

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.

An Issue of BMJ with Multiple Studies on Diet

This News Blog often contains information about diet and health. For example, we have cited evidence that salt is enemy number one [1]; trans-fats are unremittingly bad news [2]; and large amounts of sugar are harmful.[3] After that the risks become really rather small – relative risks of about 20%. Fruit, and more especially vegetables, are good news. Milk is an unhealthy drink in adults (never intended for that purpose and galactose is harmful, unless removed during a fermentation process).[4] Three further studies of diet were included in a single recent issue of the BMJ.[5-7]

The first study by Etemadi, et al. looked at meat consumption in a large cohort of people (n= 536,969) who gave detailed dietary histories.[5] The evidence corroborates other studies in showing that red meat is harmful, increasing relative risk of death by about 20% in high meat eaters compared to moderate meat eaters. The difference is greater if the comparison is made with people who obtain almost all of their meat in the form of fish and chicken. The causes of death that showed greatest increases in risk with high red meat consumption were cancer, respiratory disease and liver disease. Surprisingly, perhaps, increased risk from stroke was nugatory. The increased risk in unprocessed meat is probably related to haem iron, and in processed meat to nitrates/nitrites – there are all pro-oxidant chemicals. Of course this is an association study, so some uncertainty remains. The main problem with meat, as the BMJ Editor points out,[8] is the harmful environmental effects; apparently animal husbandry contributes more to global warming than burning fossil fuels. I take the environmental effects seriously – perhaps we will one day vilify meat farmers more vociferously than we currently vilify tobacco farmers. After all, individuals don’t have to smoke, but cannot protect themselves from the harmful effects of pollution.

Meanwhile, for those who are interested, the other two relevant articles in this issue of the BMJ looked at avoiding gluten in people who do not have celiac disease (no benefit and evidence points towards harm),[6] and the beneficial effect of a low salt and fat diet on gout.[7]

— Richard Lilford, CLAHRC WM Director

References:

1. Lilford RJ. Effects of Salt in Diet. NIHR CLAHRC West Midlands News Blog. 17 October 2014.
2. Lilford RJ. On Diet Again. NIHR CLAHRC West Midlands News Blog. 23 October 2015.
3. Lilford RJ. How Much Sugar is Too Much? NIHR CLAHRC West Midlands News Blog. 25 September 2015.
4. Lilford RJ. Two Provocative Papers on Diet and Health. NIHR CLAHRC West Midlands News Blog. 12 December 2014.
5. Etemadi A, Sinha R, Ward MH, Graubard BI, Inoue-Choi M, Dawsey SM, Abnet CC. Mortality from different causes associated with meat, heme iron, nitrates, and nitrites in the NIH-AARP Diet and Health Study: population based cohort study. BMJ. 2017; 357: j1957.
6. Lebwohl B, Cao Y, Zong G, Hu FB, Green PHR, Neugut AI, Rimm EB, Sampson L, Dougherty LW, Giovannucci E, Willett WC, Sun Q, Chan AT. Long term gluten consumption in adults without celiac disease and risk of coronary heart disease: prospective cohort study. BMJ. 2017; 357: j1892.
7. Rai SK, Fung TT. Lu N, Keller SF, Curhan GC, Choi HK. The Dietary Approaches to Stop Hypertension (DASH) diet, Western diet and risk of gout in men: prospective cohort study. BMJ. 2017; 357: j1794.
8. Godlee F. Red meat: another inconvenient truth. BMJ. 2017; 357: j2278.

Introducing Hospital IT systems – Two Cautionary Tales

The beneficial effects of mature IT systems, such as at the Brigham and Women’s Hospital,[1] Intermountain Health Care,[2] and University Hospitals Birmingham NHS Foundation Trust,[3] have been well documented. But what happens when a commercial system is popped into a busy NHS general hospital? Lots of problems according to two detailed qualitative studies from Edinburgh.[4] [5] Cresswell and colleagues document problems with both stand-alone ePrescribing systems and with multi-modular systems.[4] The former drive staff crazy with multiple log-ins and duplicate data entry. Nor does their frustration lessen with time. Neither system types (stand-alone or multi-modular) presented a comprehensive overview of the patient record. This has obvious implications for patient safety. How is a doctor expected to detect a pattern in the data if they are not presented in a coherent format? In their second paper the authors examine how staff cope with the above problems.[5] To enable them to complete their tasks ‘workarounds’ were deployed. These workarounds frequently involved recourse to paper intermediaries. Staff often became overloaded with work and often did not have the necessary clinical information at their fingertips. Some workarounds were sanctioned by the organisation, others not. What do I make of these disturbing, but thorough, pieces of research? I would say four things:

1. Move slowly and carefully when introducing IT and never, never go for heroic ‘big bang’ solutions.
2. Employ lots of IT specialists who can adapt systems to people – do not try to go the other way round and eschew ‘business process engineering’, the risks of which are too high – be incremental.
3. If you do not put the doctors in charge, make sure that they feel as if they are. More seriously – take your people with you.
4. Forget integrating primary and secondary care, and social care and community nurses, and meals on wheels and whatever else. Leave that hubristic task to your hapless successor and introduce a patient held booklet made of paper – that’s WISDAM.[6]

— Richard Lilford, CLAHRC WM Director

References:

1. Weissman JS, Vogeli C, Fischer M, Ferris T, Kaushal R, Blumenthal B. E-prescribing Impact on Patient Safety, Use and Cost. Rockville, MD: Agency for Healthcare Research and Quality. 2007.
2. Bohmer RMJ, Edmondson AC, Feldman L. Intermountain Health Care. Harvard Business School Case 603-066. 2002
3. Coleman JJ, Hodson J, Brooks HL, Rosser D. Missed medication doses in hospitalised patients: a descriptive account of quality improvement measures and time series analysis. Int J Qual Health Care. 2013; 25(5): 564-72.
4. Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. Safety risks associated with the lack of integration and interfacing of hospital health information technologies: a qualitative study of hospital electronic prescribing systems in England. BMJ Qual Saf. 2017; 26: 530-41.
5. Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. W. Workarounds to hospital electronic prescribing systems: a qualitative study in English hospitals. BMJ Qual Saf. 2017; 26: 542-51.
6. Lilford RJ. The WISDAM* of Rupert Fawdry. NIHR CLAHRC West Midlands News Blog. 5 September 2014.

Effectiveness of Debunking Online

In a recent News Blog we looked at how users of Social Media Sites, such as Facebook, tend not to view information that disagrees with their own ideas.[1] This has been backed up by another recent study by Zollo et al. in PLoS One.[2] Here the authors examined the Facebook activity of 54 million users over five years, and compared how users who usually look at proven, scientific information, and those who look at unsubstantiated, conspiracy-like posts (i.e. not reported in the mainstream media) interacted with specific debunking posts. They found that such users generally existed in ‘echo chambers’, interacting primarily with either scientific or conspiracy-like posts and pages. The authors then focussed on a set of 50,220 debunking posts, and found that around 67% of ‘likes’ and 50% of comments for these pages came from the users who consumed proven information, while only 7% of ‘likes’ and 4% of comments came from those users who viewed unsubstantiated information. Interestingly, the comments made by both groups were mainly negative. Further analysis showed another interesting finding – users of the conspiracy echo chamber who did not interact with debunking posts were 1.76 times more likely to stop interacting with unsubstantiated news in the future – i.e. interacting with debunking posts was associated with an increased interest in unsubstantiated, conspiracy-like content.

The authors suggest that these results support the ‘inoculation theory’ – exposure to repeated, mild challenges to their beliefs leads people to become more resistant to change, even if latter arguments are stronger and more persuasive. Maybe a different approach is needed.

— Peter Chilton, Research Fellow

References:

1. Lilford RJ. It is Really True: Detailed Analysis Shows That Social Media Really Do Lead to Silo Thinking. NIHR CLAHRC West Midlands News Blog. June 23, 2017.
2. Zollo F, Bessi A, Del Vicario M, et al. Debunking in a world of tribes. PLoS One. 2017; 12(7): e0181821.

Another Interesting Trial of an Educational Intervention – This Time Concerning Access

Young people from disadvantaged backgrounds are less likely to apply to elite universities, both in the UK and the US, than those from economically better-off backgrounds. This finding applies even after controlling for exam results prior to application – i.e. the GCSE results in England. So Sanders and co-authors from the Behavioural Insights Team and the English Department for Education did an inexpensive trial of an inexpensive intervention.[1] The outcomes were application to, and acceptance into, an elite university (defined as belonging to the Russell Group). The intervention consisted of a letter sent to students from disadvantaged backgrounds who were on track to attend an elite university given their GCSE grades. Eligible schools were randomised to control conditions or one of three interventions: to receive a letter written by a pseudonymous male student (Ben) at Bristol University on Department for Education note paper; to receive a similar letter from a female student (Rachel) at the same university; or to receive letters from both Ben and Rachel. Three hundred schools (clusters) and 11,104 students participated. It was then a simple matter to collect the outcomes from the agency that supervises the admission process (the Universities and Colleges Admissions Service, UCAS). Receipt of a letter was associated with a non-significant increase in applications, and eventual admission to, an elite university. The increase was greatest and statistically significant for students who received both letters – from 8.5% acceptance among controls, to 11.4% in the ‘double dose’ intervention group – an increase of 2.9 percentage points (or 34 percent relative risk). Certainly, these results add to growing evidence concerning aspirations in education – see recent News Blogs on keeping children back a year [2], streaming [3], and the Michelle Obama effect.[4]

— Richard Lilford, CLAHRC WM Director

References:

1. Sanders M, Chande R, Selley E. Encouraging People into University. London: Department for Education; 2017.
2. Lilford RJ. Keeping a Child Back at School. NIHR CLAHRC West Midlands News Blog. 10 March 2017.
3. Lilford RJ. Evidence-Based Education (or How Wrong the CLAHRC WM Director was). NIHR CLAHRC West Midlands News Blog. 15 July 2016.
4. Lilford RJ. More on Education. NIHR CLAHRC West Midlands News Blog. 16 September 2016.

Length of Hospital Stay

The average length of hospital stay for patients has ‘plummeted’ over the last thirty years, from 10 days in 1983 to 5 days in 2013.[1] However, the proportion of patients discharged to a nursing facility has quadrupled over this same period.[2] So, from the point of view of the patient, the stay away from home has not changed as much as it might be inferred from an uncritical analysis of inpatient stays. So, how have home-to-home times changed? This was assessed by Barnett et al.[3] on the basis of Medicare administration claims for 82 million hospitalisations over the years 2004 to 2011 inclusive.

Yes, the mean length of hospital stay declined (from 6.3 to 5.7 days), but the mean length of stay in post-acute care facilities increased from 4.8 to 6 days. Total home-to-home time increased from 11.1 to 11.7 days. This is not necessarily a bad thing, but it must be taken into account in assessing costs and benefits of care. The risk of iatrogenic harm and costs are lower in nursing facilities than hospitals. However, the article cited here does not consider the possibility that these risks and costs are not lower for the group of people in nursing facilities who would otherwise be cared for in hospital.

— Richard Lilford, CLAHRC WM Director

References:

1. Centers for Medicare and Medicaid Services. CMS program statistics: 2013 Medicare Utilization Section. 2017.
2. Tian W (AHRQ). An All-Payer View of Hospital Discharge to Postacute Care, 2013. Rockville, MD: Agency for Healthcare Research and Quality; 2016.
3. Barnett ML, Grabowski DC, Mehrotra A. Home-to-Home Time – Measuring What Matters to Patients and Payers. N Engl J Med. 2017; 377: 4-6.

Update on Scientists Being Held Accountable for Impact of Research

I recently wrote a news blog on the dangers of researchers being advocates for their own work. Readers may be interested in an article from an authoritative source that I chanced upon recently, published in BMC Medicine (Whitty JM. What Makes an Academic Paper Useful for Health Policy? BMC Med. 2015; 10: 301).

— Richard Lilford, CLAHRC WM Director