Displaying 1-10 letters out of 57 published
Re:Any value of Early Warning Systems must rely on the prevalence of the conditions being sought
In reply to Bewley's response to our paper, we acknowledge that a number of studies have assessed the extent of major obstetric complications as higher than that cited in the RCOG publication [1-5]. Definitions as well as rate estimation of maternal morbidity vary widely across studies . However, the premise of our paper was not to minimise the scale and severity of the problem of maternal morbidity, but to explore the logic and perceived value of one particular safety solution, the MEOWS. In the light of our findings, we still conclude that the complexity of managing risk and safety within the maternity pathway, the associated opportunity costs of MEOWS and variation in implementation call into question its current role for routine use. We reiterate our belief that there is an urgent need for further research to validate the MEOWS for the maternity population.
References 1. Zhang WH, Alexander S, Bouvier-Colle MH, Macfarlane A; MOMS-B Group. Incidence of severe pre-eclampsia, postpartum haemorrhage and sepsis as a surrogate marker for severe maternal morbidity in a European population- based study: the MOMS-B survey. BJOG 2005;112:89-96. 2. Maternal Critical Care Working Group. Providing equity of critical and maternity care for the critically ill pregnant or recently pregnant woman. London: RCOG Press, 2011 3. Waterstone M, Bewley S, Wolfe C. Incidence and predictors of severe obstetric morbidity - a case control study. Br Med J 2001;322:1089-94 4. Brace, Victoria, Gillian Penney, and Marion Hall. Quantifying severe maternal morbidity: a Scottish population study. BJOG: An International Journal of Obstetrics & Gynaecology 2004;111:481-484 5. Zanconato, Giovanni, et al. Severe maternal morbidity in a tertiary care centre of northern Italy: a 5-year review. Journal of Maternal-Fetal and Neonatal Medicine 2012;25:1025-1028.
Conflict of Interest:
Any value of Early Warning Systems must rely on the prevalence of the conditions being sought
Mackintosh et al. have made a useful contribution to the literature about pregnant and parturient's safety (1). The purpose of an Early Warning System (EWS) is to take action before deterioration that may require multiorgan support in intensive care. The ethnographic technique revealed many perceived benefits of a simple, graphic monitoring tool that empowered escalation of concerns. The research team highlighted inconsistencies in implementation of EWS, multiple competing charts for antenatal, intrapartum, postnatal and high dependency care and also resistance to medicalising normal birth. However, if EWSs do 'work' (which may yet need proving), their value will also depend on the nature and extent of problems which should not be understated.
The authors state "for every [maternal] death, nine women develop major obstetric complications including haemorrhage, infection, hypertensive disorders and thromboembolism". The RCOG reference cited is itself in error as it reported the numbers of women in the UK utilising critical care settings, (260 vs 14/ 100 000 maternities, a ratio of 19 high dependency and intensive care admissions to each death) (2). The report explains how definitions of severe morbidity vary, but that the number of major obstetric complications may be as high as 86-fold the number of deaths (1 200/ 100 000 maternities) (2,3). EWSs may also have an impact upstream on moderate morbidity with its commoner human and financial costs.
1. Mackintosh N, Watson K, Rance S, Sandall J. Value of a modified early obstetric warning system (MEOWS) in managing maternal complications in the peripartum period: an ethnographic study. BMJ Qual Saf 2013;0:1-9. doi:10.1136/bmjqs-2012-001781
2. Maternal Critical Care Working Group. Providing equity of critical and maternity care for the critically ill pregnant or recently pregnant woman. London: RCOG Press, 2011:4
Conflict of Interest:
Separating fact from opinion - A response to 'The science of human factors: Separating fact from fiction'
In their paper 'The science of human factors: separating fact from fiction', Russ et al present a description of the human factors (HF) discipline, and discuss several cases where the science of HF has been misapplied in healthcare .
On examining some of the examples of misapplication they provide, it became apparent that in most cases the term 'human factors' was used to describe factors relating to human behavior (e.g. communication), rather than the scientific discipline [2, 3]. The research did not purport to adopt a HF methodology or stance. Are these really misconceptions about HF science?
Russ et al also provide examples of studies that refer to HF science but emphasize the failures of people. They describe this research as 'counterproductive' but the work they cite adopted HF methods and exposed some interesting aspects of human behaviour. For example, consultation with clinicians revealed that user acceptance of technology was critical for successful implementation of electronic medication management . In another study (of which I am an author), review of medication charts revealed that misuse of an electronic prescribing system was associated with the generation of unnecessary computerized safety alerts . We concluded that both system design and inadequate training may have contributed to system misuse.
In their viewpoint, Russ et al, discuss training at some length and provide an overview of where training is an appropriate versus inappropriate HF technique for improving patient safety . This discussion interested me as their table (Table 1) referred to few studies examining the effectiveness of training. They explain that training is not appropriate if it is designed to address a type of error committed by multiple users, as wide-spread error indicates a mismatch between system design and human characteristics. Identification of mismatch between design and human capabilities/limitations is at the crux of the HF discipline and is undoubtedly an important undertaking. But is it not also possible that all users received the same (ineffective) training, and so all made the same types of error? In the same way, Russ at al suggest that training is not appropriate when the goal is for individuals to stop using technologies in the wrong way. But can it not be that correct use of the system was not effectively demonstrated during training, and so users were not aware that more efficient use was possible?
I agree with Russ et al in that additional training should only be considered following an evaluation of system design, but what if design is intended to break free from previous iterations, with the aim of transforming or revolutionizing a task? There exists a tension between designing systems that replicate current processes and so integrate quickly into clinical practice versus designing systems that allow tasks to be completed in more efficient ways, but which require a change in work and cognitive processes and so necessitate a greater level of training. Russ et al were quick to criticize previous research but by taking a closer look there is value in all HF applications to healthcare.
1 Russ AL, Fairbanks RJ, Karsh B-T, Militello LG, Saleem JJ, Wears RL. The science of human factors: separating fact from fiction. BMJ Quality & Safety. 2013 April 16, 2013.
2 Cahan MA, Starr S, Larkin AC, Litwin DM, Sullivan KM, Quirk ME. Transforming the culture of surgical education: Promoting teacher identity through human factors training. Archives of Surgery. 2011;146(7):830-4.
3 Rosenstein AH, O'Daniel M. Impact and Implications of Disruptive Behavior in the Perioperative Arena. Journal of the American College of Surgeons. 2006;203(1):96-105.
4 Abrams H, Carr D. The Human Factor: Unexpected Benefits of a CPOE and Electronic Medication Management Implementation at the University Health Network. Healthcare Quarterly. 2005;8(Sp):94-8.
5 Baysari MT, Reckmann MH, Li L, Day RO, Westbrook JI. Failure to utilize functions of an electronic prescribing system and the subsequent generation of 'technically preventable' computerized alerts. Journal of the American Medical Informatics Association : JAMIA. 2012 Nov 1;19(6):1003-10.
Conflict of Interest:
We need to teach leadership and quality improvement to all doctors, not just a select few.
We read with interest and agreement the editorial by Claire Lemur and Fiona Moss(1). We very much concur with the point that we have to engage the next generation of clinicians in quality improvement to ensure the future of healthcare. In the article several leadership programmes are mentioned and in addition we would add the NHS Medical Directors Clinical Fellow Scheme(2). However all of these schemes involve a small number of junior doctors rather than the whole. They represent the icing but it is really the 'cake' that we must address.
In the Severn Deanery we have been running a structured, supported quality improvement programme for the Foundation Year One (FY1s) doctors. Starting four years ago in one hospital this now involves almost half of the 280 FY1s in the deanery, and we plan to include all by 2015. The FY1s chose the project that they feel is most relevant to them (i.e. weekend handover, discharge summaries etc) and then run the project using The Model for Improvement throughout their first year supported by mentors (often who are junior doctors themselves). It has been hugely successful. The only impediments to the further spread has been finding engaged permanent staff with sufficient quality improvement knowledge to mentor and support projects and a structure within the Hospital management to facilitate and recognise the innovations that result; there has been no problems with the enthusiasm and motivation from the juniors themselves. It will only be by up skilling and engaging the 'cake' that we will be able to prepare our future workforce for the task ahead.
1. Lemer C, Moss F. Patient safety and junior doctors: are we missing the obvious? BMJ Qual Saf 2013;22(1):8-10.
2. Coltart CE, Cheung R, Ardolino A, Bray B, Rocos B, Bailey A, et al. Leadership development for early career doctors. Lancet 2012;379(9828):1847-9.
Conflict of Interest:
Re: Harnessing the cloud of patient experience: using social media to detect poor quality healthcare
January 31, 2013
To the editors:
We were pleased to read the recent article by Greaves et al.1 outlining new methodological techniques to analyze patients' online ratings of care. We agree with the authors that social media websites represent a wealth of first-hand patient experiences with health and healthcare, but have largely remained untapped by biomedical researchers - especially to gain new insights into how to improve clinical care. We concur that "big data" techniques such as machine learning and natural language processing can be extremely powerful to synthesize the large amount of textual data on these sites.
However, our previous work has also suggested the importance of traditional research methods applied to social media content. In particular, qualitative analysis adds perspective to patients' online dialogue where big data mining techniques perhaps cannot. In a qualitative examination of primary care provider ratings on Yelp,2 we analyzed 712 reviews of 455 doctors in four large urban areas (Chicago, New York, Atlanta and San Francisco). We found that these provider ratings often reflected the entire visit experience (i.e., parking, wait times, front desk staff) rather than focusing solely on the clinical encounter with the provider. Similarly, we recently qualitatively coded over 450 Twitter messages about cancer screening,3 and found that miscellaneous tweets such as jokes or popular culture references could be distinguished from the rich information about personal patient experiences with pap smears or mammograms. In both instances, these nuances in the online content may have been missed by applying data mining or natural language processing alone.
Therefore, we advocate using mixed methods approaches to analyzing social media content about health and healthcare experiences, as these techniques are inherently complementary to one another. Big data approaches allow researchers to examine millions of messages to uncover trends and overall sentiment in the online content, as well as the potential to rank the prevalence of specific discussion topics on social media sites. However, in combination with qualitative analysis of a carefully selected subsample of online content, the textual data can be interpreted in light of additional context - allowing researchers both breadth and depth in their work.
Moreover, not only should we aim to understand patient values and preferences from the large amounts of publicly available dialogue on social media, but we should also look to online social media as a means to directly engage in this dialogue with patients. Because of the ease of use and the speed of information dissemination, online social media channels have become a cornerstone of everyday life, transforming the ways that society shares ideas and beliefs, news, and information about products and services among individuals and organizations. To be truly patient-centered, healthcare providers and systems should play an active role in communicating important health and healthcare messages through the channels in which growing numbers of patients are already engaged.
Courtney R. Lyles, PhD & Urmimala Sarkar, MD, MPH University of California San Francisco, Division of General Internal Medicine
References 1. Greaves F, Ramirez-Cano D, Millett C, Darzi A, Donaldson L. Harnessing the cloud of patient experience: using social media to detect poor quality healthcare. BMJ quality & safety 2013. 2. Lopez A, Detz A, Ratanawongsa N, Sarkar U. What patients say about their doctors online: a qualitative content analysis. Journal of general internal medicine 2012;27(6):685-92. 3. Lyles CR, Lopez A, Pasick R, Sarkar U. "5 Mins of Uncomfyness Is Better than Dealing with Cancer 4 a Lifetime": an Exploratory Qualitative Analysis of Cervical and Breast Cancer Screening Dialogue on Twitter. Journal of cancer education : the official journal of the American Association for Cancer Education 2012.
Conflict of Interest:
Engaging junior doctors in patient safety: Don't forget the basics
We read the study by Durani et al (1) and the accompanying editorial (2) with great interest. Aspiring to engage junior doctors in the safety and quality movement is a noble aim but in doing so it is essential to consider the influences of both the formal (explicit) curriculum and the informal ('hidden') curriculum on doctors in training. We feel that whilst Durani et al's questionnaire may be useful to chart temporal trends in junior doctors' knowledge and attitudes in patient safety, we would caution against using subtle differences uncovered in trainees' responses to inform the subsequent development of educational interventions. To do so risks 'over-engineering' approaches to patient safety education and neglecting the basics.
Our experience of implementing sustainable patient safety training across a Foundation School ('Lessons Learnt: Building a Safer Foundation')(3) has revealed two core ingredients for engaging junior doctors in safety and quality improvement - training providers as a minimum must ensure i) a safe environment for junior doctors to raise and act on safety concerns and ii) basic instruction and opportunities in patient safety and quality improvement for all junior doctors.
First and foremost, we argue that in order to engage junior doctors in safety improvement, above all, they need to feel safe in the environment within which they work. Whilst informal discussions of safety and quality issues by junior doctors are commonplace in the 'Doctors' Mess' and at other social gatherings, structured and protected opportunities to do so within teaching programmes are severely lacking.
Moreover, whilst leadership and quality improvement schemes described by Lemer et al(2) are laudable, they invariably appeal to a self-selected group and are not always accessible to all. In the UK, latest guidance by the General Medical Council emphasises the duty of doctors in raising and acting on concerns about patient safety(4) and that leadership and management is a core role of all doctors,(5) not reserved for the privileged few. To ensure equity of opportunity and to fulfil the regulator's standards we need to ensure the provision of basic training and opportunities for junior doctors across both the domains of patient safety and leadership.
Through providing basic instruction in patient safety and integrating facilitated case-based discussions of patient safety incidents (PSIs) within the teaching programme, we have successfully created a springboard for Foundation trainees' engagement in safety and quality improvement.(3) Importantly, trainees are not passive recipients of the intervention, rather active collaborators with trainee 'Leads' at each site leading local delivery of the programme and rising to the challenge of peer- leadership. Whilst we do not claim that our programme is a panacea for engaging junior doctors in quality and safety, we do feel it is an important first step in promoting wide-scale clinical engagement in the quality movement.
Conflict of Interest:
The authors are part of a team who developed, implemented and evaluated 'Lessons Learnt: Building a Safer Foundation' - a patient safety training programme for Foundation trainees in collaboration with the North Western Deanery and the Imperial Centre for Patient Safety and Service Quality. The programme won the BMJ Excellence in Healthcare Education Award 2012.
Extension of Emergency Care Summary availability in Secondary Care
The authors of the article 'Perceived Causes of Prescribing Errors by Junior Doctors in Hospitals' published in the BMJ Quality & Safety on 30 October 2012 report that "the main task factor identified was poor availability of drug information on admission (often out of hours)" and "Systems which should aid prescribers were not always available (e.g. the Emergency Care Summary was available, but the doctor did not have a password for it)". The article postulates that had the information contained in the Emergency Care Summary (ECS) been available, it would have led to a decrease in errors.
The ECS is a national system of shared electronic records in Scotland which enables up to date prescribing information from Primary Care systems to be available to clinicians working in unscheduled care i.e. Out of Hours, Ambulance, Emergency Rooms and Acute Receiving Units(1). It was designed to improve the information available when GP practices are closed. At the time of the study, in 2011, ECS was not available for junior doctors dealing with scheduled admissions in secondary care.
The lack of access to ECS in secondary care has been identified as a critical patient safety gap and plans have been made to address this. New developments to make the medication information in ECS available for all patients in hospitals and out patients are underway. In 2011, a pilot project in Lanarkshire reported(2) that the use of ECS for medicines reconciliation in Medicine for the Elderly, Orthopaedic admissions and Surgical day cases was found to be helpful by all users. A review of 31 cases found 119 discrepancies, between medicines information in ECS and the referral letter, an average of 5 per patient, as the average length of time between referral and pre-assessment was 110 days. The ECS records were accessed by nursing staff and pharmacists carrying out medicines reconciliation and was felt to be so beneficial that it was agreed to extend the use of ECS within secondary care using the Clinical Portals(3) to provide secure identity and event based governance(4).
The article states that "problems with inadequate quality medicines information at admission to hospital were highlighted. It is disappointing to see that measures such as the ECS which have been designed to tackle this very issue by providing an up to date list of patient's medicines are not working (many doctors said that they did not have access to the Emergency Care Summary)" and we would like to correct this statement as since it's inception the ECS was specifically designed to improve care Out of Hours and was not available to hospital doctors for planned admissions. Medicines reconciliation (a process by which the most recent and accurate sources of information are used to create a full list of medicines for a patient) has been a major priority for the Scottish Patient Safety Programme and they have helped to make the case for extending use of ECS for this purpose.
Significant developments are underway to extend access to ECS for all clinical users and eHealth developments such as the Clinical Portals will mean that ECS accounts and separate passwords will not be required in the longer term.
(1) http://www.nisg.scot.nhs.uk/currently-supporting/emergency-care- summary
(2) http://www.scimp.scot.nhs.uk/documents/ECS-Lanarkshire-Final- Report-v-6.0.pdf
Dr Libby Morris, eHealth Clinical Lead, Scottish Government Health and Social Care Directorate and GP, Hermitage Medical Practices, 5 Hermitage Terrace, Edinburgh, EH10 4RP
Dr Ian M Thompson, Chair, Emergency Care Summary Service Board and GP, East Linton Surgery, Station Road, East Linton, East Lothian, EH40 3DP
Jonathan Cameron, Programme Manager/ Interim Head of Project Management, National Information Systems Group, NHS National Services Scotland, Gyle Square, 1 South Gyle Crescent, Edinburgh EH12 9EB
Conflict of Interest:
LM and JC were responsible for managing the ECS as a development project. IMT is the clinical chair for ECS as a business as usual service.
Mandating of the RRS protocol to improve patient care, could this be the next step?
I appreciated Shearer et al's recent article in BMJQS, it brings to light the debilitating effects of ill-placed social and cultural influences, and the professional hierarchies evident in all hospitals. The issues identified from the research further validate the necessity for a systems approach when dealing with clinical risk management. That said, mandating rapid response systems (RRS) as part of hospital protocols should not be so quickly dismissed as an ineffective avenue to improving RRS effectiveness. It is not a new concept that workplace culture has much to do with clinical efficacy and patient safety; in fact, Leape and Berwick pinpoint culture as a significant barrier to progress in patient safety and highlight the necessity for dramatic changes to occur as the next step to achieving higher standards. Unequal relationships exist within the healthcare team, and inter-occupational hierarchies between doctors and nurses impede the flow of information, as does the seniority of doctors over their junior staff. This element of fear that is created by an institution's structure - fear of reprimand by senior staff, fear of failure to meet expectations, and fear of judgement from others, acts alongside a clinician's medical knowledge in determining whether or not to call for help in poorly defined clinical situations, or to activate the RRS protocol, even when the patient fulfils the defined criteria. Standardisation of processes is an acceptable and widely employed mechanism for the prevention of errors. Sliding scale insulin dosing and perioperative antibiotic protocols were adopted by institutions to produce significant improvements in patient safety, much of which younger clinicians, like myself, take for granted these days. Following the successful establishment of a rapid response team, it speaks for itself that an effective way to ensure that patients are receiving a high standard of care when their status is deteriorating is, not only to educate and train staff on the RRS, but also to make such a protocol compulsory.
At present, readily available and easily identifiable criteria exist to guide the management of specific diseases, and to minimise variations in clinical judgement within an institution. A mandated RRS protocol would provide a similar opportunity to remove the pressure of judging the risk involved in tricky clinical situations and the fear of repercussions associated with initiating the call. I imagine, like those sliding scales and antibiotic protocols, once implemented, a compulsory RRS protocol would seem like second nature. Explicit criteria for determining when one needs help and how to access that help, may serve as a means to effectively overcome the negative implications of workplace culture, as well as inter- and intra- professional hierarchies.
1. Shearer B, Marshall S, Buist MD, et al. What stops hospital clinical staff from following protocols? An analysis of the incidence and factors behind the failure of bedside clinical staff to activate the rapid response system in a multi-campus Australian metropolitan healthcare service. BMJ Qual. Saf.2012;21:569-75.
2. Kohn CT, Corrigan JM, Donaldson MS. Chapter 8: creating safety systems in health care organizations. To err is human: building a safer health system. Washington, DC: National Academy Press 1999:134-174.
3. Leape LL, Berwick DM. Five years after To Err Is Human, what have we learned? JAMA. 2005;293(19):2384-90
4. Mackintosh N, Sandall J. Overcoming gendered and professional hierarchies in order to facilitate escalation of care in emergency situations: the role of standardised communication protocols. Soc Sci Med. 2010;71(9):1683-6
5. Stewart J. To call or not to call: a judgement of risk by pre- registration house officers. Med Educ. 2008;42(9):938-44
6. Leape LL. Error in medicine. JAMA. 1994;272(23):1851-7
Conflict of Interest:
Innovative Ways to improve quality of discharge summaries
We read the article on discharge summaries by Mohta et al with interest. We passionately believe that we must keep trying innovative methods to improve the quality of this most important handover document of care. Earlier this month, our audit to evaluate the extent to which contents of all fields in the electronic discharge summary template are completed with relevant information, revealed that the trainees had failed to complete some of the most important fields in the template. We then interviewed doctors at different seniority in our hospital to find the reasons for such practice. We also interviewed GPs to confirm what they want in these summaries. Based on the results, we now intend to implement three interventions (1) Trainees will print random summaries completed by them to do CbD (Case-based discussion) with their supervisors for their e- portfolio. This will give them an opportunity for feedback from senior consultants (2) We intend to put a large sticker on the top of the case record for the clinicians to make note of any important clinical event as it happens which should become part of the discharge summary at the time of the patient discharge. Person completing the discharge summary will make sure that all events on the sticker form part of the summary (3) Formal training module on discharge summaries at the time of induction on the first day when the trainee joins the Department. It will be interesting to find the results of the closing loop results of this audit.
Conflict of Interest:
ANOM Chart: A Chart Worth Getting to Know
I appreciated seeing an introduction of analysis of means (ANOM) by Mohammed and Holder. As stated in their article, the technique is not well known, but nonetheless I would like to encourage people to learn this useful graphical display to compare groups. I have been using this method in healthcare improvement work (1,2) and would like to share a couple of lessons learned over the years. The proportion ANOM chart should meet most of your needs, since first continuous type data can be converted to a proportion. For example, length of stay (LOS) greater than 2 days can be used in the proportion ANOM chart to compare groups (such as hospitals or providers) versus using LOS in the continuous ANOM chart. Secondly, the proportion ANOM chart is easier to use since it is the p-chart (a statistical process control chart), which people may be familiar with. The only difference between the ANOM for proportions and the p-chart is the control limits on the ANOM are not set at 3 sigma - they are adjusted to account for number of groups being compared. The best reference I have seen on ANOM is in a book by Balestracci & Barlow.(3) Another issue with the ANOM chart is the denominator size - you need the right size for these charts to be most helpful. A good rule of thumb is 5. If you are comparing LOS greater than 2 days across hospitals and 25% is the overall rate then each hospital will need to have 21 or more patients (5/.25 = 20). If there were only 10 patients in each group, then the control limits will be too wide and may not yield useful information. Besides too few patients in the denominator, another issue is too many patients. If your subpopulation of patients is 1,000, then you have 50 times more patients than needed and you may have many groups crossing the limits, which most likely contains Type 1 errors and is also useless information. The primary purpose of the ANOM chart is to find the hospital (or whatever you are comparing) that is performing outside the system result because there will be opportunity to learn from the hospital that is performing beyond the others. One last lesson to keep in mind is the ANOM chart can be somewhat useless if you are analyzing rare events or a proportion that is less than 10%. For example, mortality rate (MR) for a specific procedure is 1.5% and you want to see if there is a difference across 15 hospitals; however, there are on average 100 patients per year that have the procedure. Using the 5 rule, you would need 334 or more patients in the denominator so you will need 3.3 years of data. You may have the data, but most likely you will only find a low performer, which can be motivating information for the low performing hospital but more useful information is finding a hospital that is doing this well. If a hospital had 0% MR, then the ANOM chart will not show the 0% crossing the lower limit with 334 patients in the denominator. The hospital would need to have 2.5 times more patients (835 with 0% MR) and then the result would be significantly different. If ANOM is not in your analytical tool box, I would highly suggest learning more about this method, since the graphical display does so effectively what statistical process charts are suppose to do - point out the difference between common and special cause variation.
1. Homa K. Analysis of means used to compare providers' referral patterns. Quality Management in Health Care 16(3): 256-264, July/September 2007. 2. Homa K, Kirkland KB. Determining next steps in a hand hygiene improvement initiative by examining variation in hand hygiene compliance rates. Quality Management in Health Care 20(2):116-121, April - June 2011 3. Balestracci D, Jr., Barlow JL. Quality Improvement. Practical Applications for Medical Group Practice. 2nd ed. Englewood, CO: Center for Research in Ambulatory Health Care Adminstration; 1998.
Conflict of Interest:
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