Correspondence
graph, as there may be a strong laminar component to the resistive forces in Experiment 3, induced in the line. The further confounding factor in Experiment 3 is the ‘windkessel effect’ induced by the compliant pouch of the warmer circuit. This actually makes the system more efficient (functioning like the elastic human aorta), but means that emptying a 60-ml syringe into the system may take 10 s, but 60 ml volume may exit the system over 15 s. When these two factors are combined, one can see that the produced pressure/time graph may remain reciprocal at higher flows than would exceed the limit of turbulence of the cannula. However, in most non-linear, turbulent systems, this would not be observed. We would also debate McPherson’s observation that the rules pertaining to laminar flow are invalid outwith a perfect system. As long as all the values McPherson mentions remain constant, they can be condensed into a conversion factor. This is how we performed our analysis, and explains for example, why one can use a Fleisch screen, without having to measure the dimensions of each individual tube. McPherson’s interesting letter has caused us to revise our analysis of this system, and illustrates the strong contribution of the intravenous tubing to flow resistance. We enjoyed reading McPherson et al.’s article on the subject of laminar flow in cannulae, but noted that they had also overlooked this effect in their analysis [3]. It is not the static pressure that drives flow through the cannula, but rather the
Anaesthesia 2014, 69, 387–398
dynamic pressure (hydrostatic pressure – (flow x resistance of tubing)). As demonstrated above, that resistance can be very significant. Further work on this topic is perhaps required. We hope that our article helps to increase awareness of this technique, which we have found to be extremely useful, especially in the most unstable patients. It was rapidly adopted in several departments in which it was introduced, and we hope our publication and this correspondence will disseminate the technique to a wider audience. C. Smart St Helier Hospital Surrey, UK Email:
[email protected] No external funding and no conflicts of interest declared. Previously posted on the Anaesthesia correspondence website: www.anaesthesia correspondence.com.
References 1. O’Callaghan E, Singh S. Use of R-Lock one-way valve for rapid fluid administration using a three-way tap. Anaesthesia 2009; 64: 811–2. 2. Smart CM, Primrose CW, Peters AL, Speirits EJ. The properties of an improvised piston pump for the rapid delivery of intravenous fluids. Anaesthesia 2014; 69: 111–7. 3. McPherson D, Adekanye O, Wilkes AR, Hall JE. Fluid flow through intravenous cannulae in a clinical model. Anesthesia and Analgesia 2009; 108: 1198–202. doi:10.1111/anae.12647
Big Data and Big Numbers We recently encountered a difficulty when handling Big Data that is pertinent to the issues raised by
© 2014 The Association of Anaesthetists of Great Britain and Ireland
Dr Sessler in his recent editorial [1]. It has been brought to our attention that the number of patients (65 535) included in our recent observational audit of operative repair of hip fracture [2] is close to a very specific number, well known in computer circles as the largest 16-bit binary integer, or 216 (65 536). This is a frequently occurring limit found in data processing systems, colloquially referred to as the ‘64k’ limit, which restricts, for example, the row count of older versions of Microsoft Excel spreadsheets (before v.2007) [3], thereby affecting data storage and transfer involving older databases. Indeed, it became apparent that in our audit, which was to have run from 1 January 2012 to 31 December 2012, the data that were transferred from the Health and Social Care Information Centre (HSCIC) on behalf of the National Hip Fracture Database (NHFD) started from the point at which anaesthesia data were routinely collected (1 April 2011) and continued to the processing limit of the Excel row count, rather than to a defined time endpoint, 65 535 records (+ 1 title row = 65 536) having been collected by 13 April 2012. The error was compounded by the fact that previous figures from the NHFD for annual admissions for hip fracture in the UK suggested an expected number of ~65 000 patients in the dataset, so we were not alerted by any disparity between the number of patients observed and that expected. This issue of the Journal includes a Correction [4] that redefines the time period for the data included (thus leaving all the 389
Anaesthesia 2014, 69, 387–398
figures/calculations and conclusions still valid). Meanwhile, we would advise database researchers handling datasets in excess of 65 535 rows of patient records to use later versions of Microsoft Excel, and to confirm their denominator data through secondary, independent analysis. S. M. White Royal Sussex County Hospital Brighton, UK Email:
[email protected] I. K. Moppett University of Nottingham, Queen’s Medical Centre Campus Nottingham University Hospitals NHS Trust Nottingham, UK R. Griffiths Peterborough and Stamford Hospitals NHS Trust Peterborough, UK Competing interests as given in reference [2]. We are grateful to Mr Tim Bunning, Principal Consultant, Crown Informatics Limited, for alerting us to the possible error in the numbers. Previously posted on the Anaesthesia correspondence website: www.anaesthesiacorrespondence.com
References
1. Sessler DI. Big Data – and its contributions to peri-operative medicine. Anaesthesia 2014; 69: 100–5. 2. White SM, Moppett IK, Griffiths R. Outcome by mode of anaesthesia for hip fracture surgery. An observational audit of 65 535 patients in a national dataset. Anaesthesia 2014; 69: 224–30. 3. Microsoft Excel specifications and limits. http://office.microsoft.com/en-gb/exc el-help/excel-specifications-and-limitsHP005199291.aspx (accessed 06/02/ 2014). 4. Correction. Anaesthesia 2014; 69. doi:10.1111/anae.12652
390
Correspondence
Big Data – ethical perspectives Large, linked databases (‘Big Data’ [1]) use pseudonymised personal confidential data that have been anonymised but retain a residual risk of re-identification. Sessler outlines the potential benefits of these databases in his editorial [1], with regard to rapid improvements in the quality and affordability of healthcare. However, there are ethical aspects that must be considered when balancing potential benefits against potential harms. Non-maleficence describes ‘an obligation not to inflict harm on others’ [2]. The potential for harm in epidemiological database research is not as immediately apparent as for clinical trials, but individuals can still be wronged when they have not suffered direct harm per se. There are two main ethical areas of concern: firstly, that vulnerable groups may become stigmatised; and secondly that people are ‘treated’ as a means to an end, rather than as an end in themselves. Although the aim of collecting data about vulnerable groups is to improve care, information could be used to discriminate against them, or stigmatise them. Retained identifiers such as postcodes can provide information about disease burden linked to geographical socio-economic deprivation. In rare conditions, the possibility of re-identification becomes very real. Boyd [3] uses the example of an ethnic minority with an inheritable condition deemed potentially harmful to the majority population, who are coerced into
birth control. Public concerns often centre around inadvertent disclosure of information to third parties, including employers, insurance companies [4], drug companies or criminal organisations. Personal autonomy is recognised and protected through the process of providing consent, such that “patients must be fully informed of, and agree without coercion to, any participation in medical research” [5]. The Data Protection Act 1998 states that consent is not needed for anonymised data, and it has been argued that seeking formal consent for data inclusion within health databases could cause harm. The Academy of Medical Sciences has suggested that any insistence on formal consent could cause such significant selection, recruitment and participation bias that it would skew the data to such an extent as to make it not worth collecting [6]. It would also use precious resources such as time and money, and prohibit large studies. In addition to this, a traditional informed consent process, where a researcher asks for permission to do something to a participant at a single point in time, is likely to be unfit for purpose – the initial researcher is unlikely to know the nature of research to be carried out in the future, and future research would require re-consent, and therefore the necessity for patient contact identifiers to be held simultaneously on any database. Non-consensual use even of pseudonymised data risks damaging trust between patients, healthcare professionals and government bodies. NHS England has proposed
© 2014 The Association of Anaesthetists of Great Britain and Ireland
