We feel that this article and accompanying press release have failed to fully acknowledge some significant limitations of the study. We feel these limitations are important when making the conclusion that following guidelines by earlier referral would be associated with earlier cancer diagnosis.
1. There is no recognition that the cancer diagnosed in the year following index consultation may not have any association with the index consultation. For example a non-urgent referral for breast lump who developed bladder carcinoma in the following year would be included as someone who could have benefitted from earlier referral.
2. There is no attempt to acknowledge screening cancer diagnoses. Again these would be included despite them being unrelated to any previous “red flag” symptoms.
3. Most significantly, there is no acknowledgement that not “following guidelines” is often an important part of shared decision-making that prevents morbidity related to diagnostic processes and treatment. Although the article explains that co-morbidities and age greater than 85 are associated with lower referral rates; it fails to recognise that any delay in cancer diagnosis in this group would often not be considered a “missed opportunity”,. There is sometimes no clinical benefit to the patient of earlier diagnosis. In relation to this It also fails to recognise that many local 2ww guidelines include severe frailty as an exclusion criteria for an urgent or 2w...
We feel that this article and accompanying press release have failed to fully acknowledge some significant limitations of the study. We feel these limitations are important when making the conclusion that following guidelines by earlier referral would be associated with earlier cancer diagnosis.
1. There is no recognition that the cancer diagnosed in the year following index consultation may not have any association with the index consultation. For example a non-urgent referral for breast lump who developed bladder carcinoma in the following year would be included as someone who could have benefitted from earlier referral.
2. There is no attempt to acknowledge screening cancer diagnoses. Again these would be included despite them being unrelated to any previous “red flag” symptoms.
3. Most significantly, there is no acknowledgement that not “following guidelines” is often an important part of shared decision-making that prevents morbidity related to diagnostic processes and treatment. Although the article explains that co-morbidities and age greater than 85 are associated with lower referral rates; it fails to recognise that any delay in cancer diagnosis in this group would often not be considered a “missed opportunity”,. There is sometimes no clinical benefit to the patient of earlier diagnosis. In relation to this It also fails to recognise that many local 2ww guidelines include severe frailty as an exclusion criteria for an urgent or 2ww referral.
The authors of this paper describe GP decision-making as ‘good but not good enough’. Their paper also highlights considerable variation among clinicians with the highest referrers being more than two times more likely to refer patients with red flag symptoms for cancer investigation than the lowest referrers. When we consider this wide disparity among individual doctors, we must look at how we can objectively and consistently reduce this. How can we make the diagnostic process in primary care ‘reliable, not heroic’ [1]?
Previous papers have considered interventions that can reduce the global burden of diagnostic errors in primary care [2], including the use of information technology tools. Perhaps we can consider that better use of technology such as Clinical Decision Support Systems (CDSS) could improve clinical diagnostics especially in those areas with clear guideline-based practice such as in the decision to refer urgently for suspected cancer [3]. These tools can be used to provide appropriate suggestions for differentials at any point in the clinical consultation or offer ‘alerts’ at the end of the consultation if there are important diagnoses that haven’t been considered [4].
Uptake of CDSS has been poor [5] and clinician response to these tools when they have been implemented are mixed [6] despite them showing that they increase physician’s diagnostic accuracy [7, 8]. At present, clinical work mostly only uses inconsistently implemented ‘alerts’. Some...
The authors of this paper describe GP decision-making as ‘good but not good enough’. Their paper also highlights considerable variation among clinicians with the highest referrers being more than two times more likely to refer patients with red flag symptoms for cancer investigation than the lowest referrers. When we consider this wide disparity among individual doctors, we must look at how we can objectively and consistently reduce this. How can we make the diagnostic process in primary care ‘reliable, not heroic’ [1]?
Previous papers have considered interventions that can reduce the global burden of diagnostic errors in primary care [2], including the use of information technology tools. Perhaps we can consider that better use of technology such as Clinical Decision Support Systems (CDSS) could improve clinical diagnostics especially in those areas with clear guideline-based practice such as in the decision to refer urgently for suspected cancer [3]. These tools can be used to provide appropriate suggestions for differentials at any point in the clinical consultation or offer ‘alerts’ at the end of the consultation if there are important diagnoses that haven’t been considered [4].
Uptake of CDSS has been poor [5] and clinician response to these tools when they have been implemented are mixed [6] despite them showing that they increase physician’s diagnostic accuracy [7, 8]. At present, clinical work mostly only uses inconsistently implemented ‘alerts’. Sometimes, these alerts can reduce inappropriate prescribing and improve patient health [9] although poorly implemented alerts can add to the doctor’s burden [10]. Only small studies have previously looked at the acceptability of these alerts [11] which highlights an area rich for further action and research to improve patient outcomes.
Investment in better and more effective technologies in the primary care consulting room has the potential to reduce the disparity between different doctors’ referral rates and provide a more consistent adherence to the cancer referral guidelines potentially increasing our detection rate.
References
1 Schiff GD, Bates DW. Can Electronic Clinical Documentation Help Prevent Diagnostic Errors? New England Journal of Medicine 2010;362:1066–9. doi:10.1056/NEJMp0911734
2 Singh H, Schiff GD, Graber ML, et al. The global burden of diagnostic errors in primary care. BMJ Quality & Safety 2017;26:484–94. doi:10.1136/bmjqs-2016-005401
3 Graber ML. Reaching 95%: Decision support tools are the surest way to improve diagnosis now. BMJ Quality & Safety Published Online First: October 2021. doi:10.1136/bmjqs-2021-014033
4 Nurek M, Kostopoulou O, Delaney BC, et al. Reducing diagnostic errors in primary care. A systematic meta-review of computerized diagnostic decision support systems by the LINNEAUS collaboration on patient safety in primary care. European Journal of General Practice 2015;21:8–13. doi:10.3109/13814788.2015.1043123
5 Cheraghi-Sohi S, Alam R, Hann M, et al. Assessing the utility of a differential diagnostic generator in UK general practice: A feasibility study. Diagnosis 2021;8:91–9. doi:10.1515/dx-2019-0033
6 Ford E, Edelman N, Somers L, et al. Barriers and facilitators to the adoption of electronic clinical decision support systems: A qualitative interview study with UK general practitioners. BMC Medical Informatics and Decision Making 2021;21. doi:10.1186/s12911-021-01557-z
7 Kostopoulou O, Rosen A, Round T, et al. Early diagnostic suggestions improve accuracy of GPs: A randomised controlled trial using computer-simulated patients. British Journal of General Practice 2015;65:e49–54. doi:10.3399/bjgp15X683161
8 Riches N, Panagioti M, Alam R, et al. The Effectiveness of Electronic Differential Diagnoses (DDX) Generators: A Systematic Review and Meta-Analysis. PLOS ONE 2016;11:e0148991. doi:10.1371/journal.pone.0148991
9 McKibben S, Bush A, Thomas M, et al. An electronic alert to reduce excessive prescribing of short-acting Beta2-agonists for people with asthma in East London: A retrospective case-control study using routine primary care data. In: M-Health/e-health. European Respiratory Society 2020. 1364. doi:10.1183/13993003.congress-2020.1364
10 Cecil E, Dewa LH, Ma R, et al. General practitioner and nurse practitioner attitudes towards electronic reminders in primary care: A qualitative analysis. BMJ Open 2021;11:e045050. doi:10.1136/bmjopen-2020-045050
11 Kelsey EA, Njeru JW, Chaudhry R, et al. Understanding User Acceptance of Clinical Decision Support Systems to Promote Increased Cancer Screening Rates in a Primary Care Practice. Journal of Primary Care & Community Health 2020;11:215013272095883. doi:10.1177/2150132720958832
Conflict of Interest
None declared
2.
Title: “Inadequate limitations”
Author: William P, Hart, Katarzyna, Grellier
In response to the published article Concordance with urgent referral guidelines in patients presenting with any of six ‘alarm’ features of possible cancer: a retrospective cohort study using linked primary care records"
Rapid response:
Other Contributors:
October 13, 2021
We feel that this article and accompanying press release have failed to fully acknowledge some significant limitations of the study. We feel these limitations are important when making the conclusion that by following guidelines, earlier referral would be associated with earlier cancer diagnosis.
1. There is no recognition that the cancer diagnosed in the year following index consultation may not have any association with the index consultation. For example a non-urgent referral for breast lump who developed bladder carcinoma in the following year would be included as someone who could have benefitted from earlier referral.
2. There is no attempt to acknowledge screening cancer diagnoses. Again these would be included despite them being unrelated to any previous “red flag” symptoms.
3. Most significantly, there is no acknowledgement that not “following guidelines” is often an important part of shared decision-making that prevents morbidity related to diagnostic processes and treatment. Although the article explains that co-morbidities and age greater than 85 are associated with lower referral rates; it fails to recognise that any delay in cancer diagnosis in this group would often not be considered a “missed opportunity”,. There is sometimes no clinical benefit to the patient of earlier diagnosis. In relation to this It also fails to recognise that many local two-week wait guidelines include severe frailty as an exclusion criteria for an urgent or two-week wait referral.
Conflict of Interest
None declared
The recent article by Muskens et al "Overuse of diagnostic testing in healthcare: a systematic review" published online on May 10, 2021, admirably describes the prevalence and overuse of low-value diagnostic tests in multiple healthcare settings, but does not offer possible explanations or solutions. Some salient reasons are (1): 1. Physicians do not consider healthcare costs during a diagnostic workup; 2. Malpractice concerns; 3. An excessive fee-for-service mentality--more tests and consultations generate more income; 4. Lack of trust in clinical skills versus high technology testing; 5. Believing that diagnostic workups should eliminate all conceivable etiologies; and 6. Patients may experience greater satisfaction with more testing.
Underlying these last three possibilities is the failure to appreciate that in science, especially after Darwin, Einstein and Heisenberg, absolute certainty is considered unachievable. Facts and theories, and clinical diagnoses, are now rated on the probability that they are true. A diagnosis is more probable than not, or more probable than another, based on degrees of evidence. Hence recent interest in Bayesianism, which analyses evidence in terms of probability. When determining the efficacy of additional tests, Bayesianism requires a pre-test (a priori) probability estimate of the diagnosis. The more probable a diagnosis is clinically (a priori) and the greater the diagnostician's clinical confidence, the less nec...
The recent article by Muskens et al "Overuse of diagnostic testing in healthcare: a systematic review" published online on May 10, 2021, admirably describes the prevalence and overuse of low-value diagnostic tests in multiple healthcare settings, but does not offer possible explanations or solutions. Some salient reasons are (1): 1. Physicians do not consider healthcare costs during a diagnostic workup; 2. Malpractice concerns; 3. An excessive fee-for-service mentality--more tests and consultations generate more income; 4. Lack of trust in clinical skills versus high technology testing; 5. Believing that diagnostic workups should eliminate all conceivable etiologies; and 6. Patients may experience greater satisfaction with more testing.
Underlying these last three possibilities is the failure to appreciate that in science, especially after Darwin, Einstein and Heisenberg, absolute certainty is considered unachievable. Facts and theories, and clinical diagnoses, are now rated on the probability that they are true. A diagnosis is more probable than not, or more probable than another, based on degrees of evidence. Hence recent interest in Bayesianism, which analyses evidence in terms of probability. When determining the efficacy of additional tests, Bayesianism requires a pre-test (a priori) probability estimate of the diagnosis. The more probable a diagnosis is clinically (a priori) and the greater the diagnostician's clinical confidence, the less necessary is additional testing. Since it is impossible to prove absence of disease, testing can only support or not support a specific clinical diagnosis.
But there is a quid pro quo: Tests can be harmful and costs uncontrolled. Given the subjective nature of characterizing truth and justifying beliefs, the medical profession might consider differentiating levels of evidence or burdens of proof regarding diagnostic accuracy much as the legal profession does: in less stringent civil cases the burden of proof is preponderant, more likely than not, >50%. In more severe criminal cases the burden of proof is beyond reasonable doubt, indubitable. While this legal dichotomization is probably too simplistic for all clinical issues, it can serve as a guide. Graded burdens of proof for differing clinical presentations could alter physician behavior, enhance patient satisfaction, reduce malpractice concerns, and contribute to lower health care costs without compromising individual patient care.
Parenthetically, after decades of teaching medical students and house staff officers of the importance of clinical skills to minimize excessive testing, I joined a multispecialty healthcare group from which I was eventually dismissed for not ordering enough tests and generating sufficient testing income. My philosophy, which I strongly believe in, came back to bite me.
1. Horowitz SH. Diagnostic decision-making, burdens of proof, and a $6000 per hour memory lapse. JAMA Int Med; 2013;176:1493-1494.
We thank Professors Marang-van de Mheen and Vincent for their comments [1] on our examination of variations in weekend and weekday admission care quality during the introduction of seven day services in England [2]. Their analysis and logic models demonstrate with admirable simplicity the complexity of these causal pathways.
One of the pathways which is not highlighted in the literature is how quality of pre-hospital care may impact on the post-admission phase in hospital. Using exploratory data from the 20 hospitals in our data set, we have shown that while in-hospital care quality did not vary between weekend and weekday admissions, and had improved over time, there was a concurrent deterioration in performance indicators related to care in the community preceding hospital admission. Weekend admissions were much less likely to have been referred by family doctors, and more likely to attend hospital by emergency ambulance, to be dependent on others for activities of daily living, and to be candidates for palliative care. These differences became more marked with the passage of time. In a separate single-centre study we have shown that patients admitted at weekends are sicker than those admitted on weekdays [3]. We therefore contend that while there may be opportunities to improve hospital care across all days of the week, the cause for the weekend effect may reside in community healthcare services. As the weekend effect is a global phenomenon [4], policy makers a...
We thank Professors Marang-van de Mheen and Vincent for their comments [1] on our examination of variations in weekend and weekday admission care quality during the introduction of seven day services in England [2]. Their analysis and logic models demonstrate with admirable simplicity the complexity of these causal pathways.
One of the pathways which is not highlighted in the literature is how quality of pre-hospital care may impact on the post-admission phase in hospital. Using exploratory data from the 20 hospitals in our data set, we have shown that while in-hospital care quality did not vary between weekend and weekday admissions, and had improved over time, there was a concurrent deterioration in performance indicators related to care in the community preceding hospital admission. Weekend admissions were much less likely to have been referred by family doctors, and more likely to attend hospital by emergency ambulance, to be dependent on others for activities of daily living, and to be candidates for palliative care. These differences became more marked with the passage of time. In a separate single-centre study we have shown that patients admitted at weekends are sicker than those admitted on weekdays [3]. We therefore contend that while there may be opportunities to improve hospital care across all days of the week, the cause for the weekend effect may reside in community healthcare services. As the weekend effect is a global phenomenon [4], policy makers and researchers should turn their attention to examining the quality of pre-hospital care at weekends.
1. Marang-van de Mheen PJ, Vincent C. Moving beyond the weekend effect: how can we best target interventions to improve patient care? BMJ Quality & Safety Published Online First: 11 February 2021. doi: 10.1136/bmjqs-2020-012620
2. Bion J, Aldridge C, Girling AJ, et al. Changes in weekend and weekday care quality of emergency medical admissions to 20 hospitals in England during implementation of the 7-day services National health policy. BMJ Qual Saf 2020. doi:doi:10.1136/bmjqs-2020-011165.
3. Sun J, Girling AJ, Aldridge C, Evison F, Beet C, Boyal A, Rudge G, Lilford RJ, Bion J. Sicker patients account for the weekend mortality effect among adult emergency admissions to a large hospital trust. BMJ Qual Saf. 2019 Mar;28(3):223-230. doi: 10.1136/bmjqs-2018-008219.
4. Chen Y-F, Armoiry X, Higenbottam C, et al. Magnitude and modifiers of the weekend effect in hospital admissions: a systematic review and meta-analysis. BMJ Open 2019;9:e025764. doi:10.1136/bmjopen-2018-025764
Adherence Issues in Population with Intellectual Disabilities
Bernadette Flood PhD MPSI, Pharmacist, Daughters of Charity Disability Support Services
Link to Original article: Medication non-adherence: an overlooked target for quality improvement interventions
Commentary on: Medication non-adherence: an overlooked target for quality improvement interventions, Bryony Dean Franklin, Gary Abel, Kaveh G Shojania (2019-12-20). 10.1136/bmjqs-2019-009984
Non adherence to prescribed medication is a complex problem. The complexity is increased in vulnerable population groups such as the population with intellectual disabilities. A person with an intellectual disability may often be dependent on ‘healthcare by proxy’ where another person makes healthcare decisions on their behalf. People with intellectual disabilities may also be ‘invisible’ to pharmacists dispensing prescribed medicines. Many pharmacists may have little experience of the challenges faced by this high risk group of patients [1] who may be prescribed high risk medications such as diabetic medicines including insulin and anti-epileptic medications. People with intellectual disabilities and their family carers, support workers etc. may be unaware of the consequences of poor adherence to prescribed medicines. The difficulties of involving a parent proxy in a three-way relationship involving an adult at risk of lacking decision-making capacity, their proxy, and a treating clinician have been ra...
Adherence Issues in Population with Intellectual Disabilities
Bernadette Flood PhD MPSI, Pharmacist, Daughters of Charity Disability Support Services
Link to Original article: Medication non-adherence: an overlooked target for quality improvement interventions
Commentary on: Medication non-adherence: an overlooked target for quality improvement interventions, Bryony Dean Franklin, Gary Abel, Kaveh G Shojania (2019-12-20). 10.1136/bmjqs-2019-009984
Non adherence to prescribed medication is a complex problem. The complexity is increased in vulnerable population groups such as the population with intellectual disabilities. A person with an intellectual disability may often be dependent on ‘healthcare by proxy’ where another person makes healthcare decisions on their behalf. People with intellectual disabilities may also be ‘invisible’ to pharmacists dispensing prescribed medicines. Many pharmacists may have little experience of the challenges faced by this high risk group of patients [1] who may be prescribed high risk medications such as diabetic medicines including insulin and anti-epileptic medications. People with intellectual disabilities and their family carers, support workers etc. may be unaware of the consequences of poor adherence to prescribed medicines. The difficulties of involving a parent proxy in a three-way relationship involving an adult at risk of lacking decision-making capacity, their proxy, and a treating clinician have been rarely considered[2] .
The international trend to deinstitutionalise the care of people with intellectual disabilities will require that this complex group of patients receive support from care givers and health and social care professionals in the community setting to ensure quality medication use. Pharmacists have a role to play.
Pharmacists and Adherence in Population with Intellectual Disabilities
It is thought that only around half of medicines for long-term conditions are taken as prescribed in developed countries, and there is little evidence of any improvement in adherence rates over the past 50 years[4] . Some factors that can impact adherence in the population with intellectual disabilities have been identified in USA [5] :
1. Patients with intellectual disabilities may not have the ability to fully understand the importance or impact of the medications they’re given. This altered perception or ability may have profound effects on treatment, particularly for chronic conditions.
2. Patients with intellectual disabilities can also have various living situations, which can impart more challenges to medication therapy and adherence. These living arrangements can range from total independence to residing in group homes. It was found that patients with intellectual disabilities living in group homes had higher adherence rates compared with those who lived independently or in a family home.
3. Socioeconomic factors may impact these individuals’ ability to adhere to a medication regimen. Medicaid enrolment and minority race/ethnicity have been associated with reduced medication adherence in individuals with intellectual disabilities.
Almost all of the interventions found to be effective for long-term care are complex, including combinations of more convenient care, information, reminders, self-monitoring, reinforcement, counselling, family therapy, psychological therapy, crisis intervention, manual telephone follow-up, and supportive care. Even the most effective interventions have not led to large improvements in adherence and treatment outcomes [6]. More frequent interaction with patients with attention to adherence in every healthcare encounter appears to be a common thread in all interventions.
Pharmacists and others involved must work out how to match patients to the interventions already available. Individual interventions may only be effective when directed at the subset of the population whose reason for non-adherence is targeted by the particular intervention. This is an area in which pharmacists with specialist knowledge of adherence and other medicine related issues in the population with intellectual disabilities can play a role.
References:
[1].Flood, B. and Henman, M.C. (2015), Case study: hidden complexity of medicines use: information provided by a person with intellectual disability and diabetes to a pharmacist. Br J Learn Disabil, 43: 234-242. doi:10.1111/bld.12121 https://onlinelibrary.wiley.com/action/showCitFormats?doi=10.1111%2Fbld....
[2].Redley, M., Prince, E., Bateman, N., et al. (2013), The involvement of parents in healthcare decisions where adult children are at risk of lacking decision‐making capacity: a qualitative study of treatment decisions in epilepsy. Journal of Intellectual Disability Research, 57: 531-538. doi:10.1111/j.1365-2788.2012.01556.x
[3].Hom, C.L., Touchette, P., Nguyen, V., et al. (2015), Living arrangement and medication non‐adherence. J Intellect Disabil Res, 59: 48-54. doi:10.1111/jir.12123
[4].Nieuwlaat R, Wilczynski N, Navarro T et al. Interventions for enhancing medication adherence. Cochrane Database Syst Rev 2014; issue 11. Art. No: CD000011.doi:10.1002/14651858.CD000011.pub4
[5].Factors Affecting Adherence in Patients with Intellectual Disabilities. 2016-11-07 09:54:07 Erik Hefti, Pharm D, MS https://www.pharmacytimes.com/contributor/erik-hefti-pharmd-ms/2016/11/f...
[6]. Haynes RB, Ackloo E, Sahota N, McDonald HP, Yao X. Interventions for enhancing medication adherence. Cochrane Database of Systematic Reviews 2008, Issue 2. Art. No.: CD000011. DOI: 10.1002/14651858.CD000011.pub3
Conflict of Interest
None declared
We thank the French Society of Emergency Medicine for such a large study. However it is difficult to conclude regarding a number of limitations due to the observational cross-sectional study scheme.
The main critics concern the 3 measurements tools allowing to decide appropriateness of ED visits or not. Appropriate Use Score Method: the authors decide a cut-off based on Italian litterature data which is not French sounded; Possible GP Use Method : it would be more accurate to have an external evaluation instead of a judge and part one ; Resource Utilisation Method : the elephant in the room is the result of consultation and the final diagnostic as well.
I don’t discuss here the relevance of a number of items as distance between home and ED Departments, medical density and so far.
Specifically I doubt it is possible to interpret socioeconomic and territorial factors results without diagnostics and diagnostic frequency on June, 11, 2013
We are looking forward for more studies informing use of ED departments.
In their editorial commenting on our paper “Association of registered nurse and nursing support staffing with inpatient hospital mortality,” [1] Aiken and Sloane misrepresent our study results, conclusions and implications. They characterize our study as examining the impact of substitution of nursing support staff for professional nurses or registered nurses (RNs) (commonly described as skill mix). This is done despite acknowledging that we stated our findings should not be interpreted to mean that nursing aides can safely substitute for RNs. Furthermore, as Aiken and Sloane acknowledge each of us have published multiple studies [2 3] showing efforts to deskill the nursing work force will increase deaths, adverse events and costs. This conclusion was also restated in a recent editorial in this journal by one of us. [4]
Aiken and Sloane discuss the paper as though it is about skill mix, characterizing our findings as “counter” to our earlier published papers that did analyze skill mix. However, the current paper and the recent Griffith’s paper Aiken and Sloane also reference[5], “examine nursing support staffing not as a substitute for RNs, as studies of skill mix do, but …rather examine the impact of shortfalls in support staffing given established RN- nursing support staffing models.” What our paper and Griffiths paper do is examine shortfalls from established levels of nurse support staffing as a complement of typical RN staffing withi...
In their editorial commenting on our paper “Association of registered nurse and nursing support staffing with inpatient hospital mortality,” [1] Aiken and Sloane misrepresent our study results, conclusions and implications. They characterize our study as examining the impact of substitution of nursing support staff for professional nurses or registered nurses (RNs) (commonly described as skill mix). This is done despite acknowledging that we stated our findings should not be interpreted to mean that nursing aides can safely substitute for RNs. Furthermore, as Aiken and Sloane acknowledge each of us have published multiple studies [2 3] showing efforts to deskill the nursing work force will increase deaths, adverse events and costs. This conclusion was also restated in a recent editorial in this journal by one of us. [4]
Aiken and Sloane discuss the paper as though it is about skill mix, characterizing our findings as “counter” to our earlier published papers that did analyze skill mix. However, the current paper and the recent Griffith’s paper Aiken and Sloane also reference[5], “examine nursing support staffing not as a substitute for RNs, as studies of skill mix do, but …rather examine the impact of shortfalls in support staffing given established RN- nursing support staffing models.” What our paper and Griffiths paper do is examine shortfalls from established levels of nurse support staffing as a complement of typical RN staffing within established unit-level nurse staffing models. Both papers find these shortfalls also increase patient risk of death. In our article, we posit two complementary mechanisms through which low nurse support staffing might increase patient risk – by adding to the workload of RNs who have to take on the support staff work, and decreasing the direct observation of patients. Regardless of mechanism, we and Griffiths conclude that providing adequate nursing support staff as well as adequate RN staffing may be necessary to assure safe and reliable care. This is not a skill mix-staffing model issue, but an issue of having adequate staffing.
There is no question that patients are kept safe and care delivered reliably only when there are adequate numbers of RNs. Our paper’s finding on the impact on mortality of shortfalls in RN staffing from established, typical levels reinforce this conclusion. Assuring these levels needs to be a priority of health system administrators, regulators and payers. But this paper also indicates that assuring adequate support for RNs is also important for patient safety. It is disappointing that Aiken and Sloane did not understand the distinction between supporting RNs and substituting for them with lower skilled staff. It is an important distinction that the readers of BMJQS should understand and the editorial should have made clear.
References
1. Needleman J, Liu J, Shang J, Larson EL, Stone PW. Association of registered nurse and nursing support staffing with inpatient hospital mortality. BMJ Qual Saf 2020;29(1):10-18 doi: 10.1136/bmjqs-2018-009219[published Online First: Epub Date]|.
2. Needleman J, Buerhaus PI, Stewart M, Zelevinsky K, Mattke S. Nurse staffing in hospitals: is there a business case for quality? Health affairs (Project Hope) 2006;25(1):204-11 doi: 10.1377/hlthaff.25.1.204[published Online First: Epub Date]|.
3. Glance LG, Dick AW, Osler TM, Mukamel DB, Li Y, Stone PW. The association between nurse staffing and hospital outcomes in injured patients. BMC Health Serv Res 2012;12:247 doi: 10.1186/1472-6963-12-247[published Online First: Epub Date]|.
4. Needleman J. Nursing skill mix and patient outcomes. BMJ Qual Saf 2017;26(7):525-28 doi: 10.1136/bmjqs-2016-006197[published Online First: Epub Date]|.
5. Griffiths P, Maruotti A, Recio Saucedo A, et al. Nurse staffing, nursing assistants and hospital mortality: retrospective longitudinal cohort study. BMJ Qual Saf 2018 doi: 10.1136/bmjqs-2018-008043[published Online First: Epub Date]|.
I write in response to the article published in your journal “Passing the acid test? Evaluating the impact of national education initiatives to reduce proton pump inhibitor use in Australia” (Bruno C et al., BMJ Qual Saf 2019). I am writing as NPS MedicineWise evaluation found a significant impact on general practitioner prescribing of proton pump inhibitors (PPIs) following their educational programs in 2009 and 2015. I acknowledge that the article is well written, the methods are well described, and the approach includes a number of sensitivity analyses. However, I would like to highlight some key points on the analysis methods used that differ from the approach taken by NPS MedicineWise and about which I have some concerns.
The 2015 NPS MedicineWise educational program on PPIs was part of a larger educational strategy over a decade to support best-practice prescribing of PPIs by general practitioners (GPs) and included Pharmaceutical Benefits Scheme (PBS) feedback to GPs in Australia. This consists of a letter that includes information of the individual GP’s prescribing of PPIs compared to their peers. Programs launched in 2009 and 2018 on PPI prescribing for GPs also included face-to-face educational visits to GP practices. The 2015 campaign, which did not include these face-to-face visits, aimed to reinforce the impact of the earlier 2009 campaign.
NPS MedicineWise has conducted an evaluation of the 2009 and 2015 education programs on GP prescribing o...
I write in response to the article published in your journal “Passing the acid test? Evaluating the impact of national education initiatives to reduce proton pump inhibitor use in Australia” (Bruno C et al., BMJ Qual Saf 2019). I am writing as NPS MedicineWise evaluation found a significant impact on general practitioner prescribing of proton pump inhibitors (PPIs) following their educational programs in 2009 and 2015. I acknowledge that the article is well written, the methods are well described, and the approach includes a number of sensitivity analyses. However, I would like to highlight some key points on the analysis methods used that differ from the approach taken by NPS MedicineWise and about which I have some concerns.
The 2015 NPS MedicineWise educational program on PPIs was part of a larger educational strategy over a decade to support best-practice prescribing of PPIs by general practitioners (GPs) and included Pharmaceutical Benefits Scheme (PBS) feedback to GPs in Australia. This consists of a letter that includes information of the individual GP’s prescribing of PPIs compared to their peers. Programs launched in 2009 and 2018 on PPI prescribing for GPs also included face-to-face educational visits to GP practices. The 2015 campaign, which did not include these face-to-face visits, aimed to reinforce the impact of the earlier 2009 campaign.
NPS MedicineWise has conducted an evaluation of the 2009 and 2015 education programs on GP prescribing of PPIs and found a significant decrease in the volume of high and standard PPIs prescribed to concessional patients.
There are a number of ways in which our analysis differs to that described in the Bruno et al. article:
• Our analysis found a reduction in high/standard PPI dispensed volumes from GP prescriptions for concessional patients over four times that found in the Bruno et al. article. Our analysis was focussed on GP prescribing, as they were the target prescribers for our education programs. In contrast, the Bruno et al. article includes all dispensed prescriptions including those by specialists. Specialists may be prescribing PPIs more frequently for people with more complicated conditions for which long-term PPI use is appropriate.
• The authors of the Bruno et al. article have used a novel approach by looking at a sample of 10% of individual longitudinal PBS patient data and used novel data analysis methods. In contrast, we use the complete PBS data for concessional patients and analyse dispensing volumes using best practice time series analysis.
• We analyse trends over multiple years, whereas the Bruno et al. analysis used data from one year before and after the 2015 NPS MedicineWise program, although they did adjust for seasonality. Benefits of a multiple year analysis include taking into account additional factors such as the impacts of previous programs, consumers stockpiling medicines once they reach the PBS safety net and other environmental factors.
• In the Bruno et al. article they only assessed a change in the dispensing levels after the interventions although there is a clear upward trend in PPI prescriptions over the years prior to the intervention. They did not assess a change in slope (i.e. change in trend) which NPS MedicineWise considers in evaluation work using time series analysis. One possible reason for an upward trend is a continual increase in the size of the population with gastro-oesophageal reflux disease (GORD) due to population growth, and this is particularly strong in older populations. I would recommend assessing total dispensing over time as an age-standardised or age-specific population rate to control for change in the size of the population at risk of being prescribed PPIs.
Since NPS MedicineWise launched the Choosing Wisely Australia initiative in April 2015, three recommendations from medical colleges and societies about the use of PPIs have been published – from the Royal Australian College of General Practitioners (RACGP) in April 2015, the Gastroenterological Society of Australia (GESA) in October 2016 and the Royal Australasian College of Physicians’ Paediatrics & Child Health Division in September 2017. The 2018 NPS MedicineWise educational program included recommendations on PPIs from RACGP and GESA. One of the program’s aims was to grow GP awareness of the RACGP recommendation and GPs were encouraged to regularly review patients with GORD on PPIs, with the aim of reducing or ceasing PPIs altogether.
A GP survey conducted in February 2019 asked GPs to rate their agreement with the RACGP statement before and after participating in the NPS MedicineWise program. The result was a significant 13% increase in GP awareness of the RACGP recommendation after participating, demonstrating that educational activities do have an important role in behaviour change.
There is a need for further research into the impact of reducing PPI use on GORD symptom control. Further evaluation is planned and the MedicineInsight dataset provides a unique opportunity to explore the reasons general practitioners prescribe PPIs to patients. MedicineInsight, managed by NPS MedicineWise with support funding from the Australian Government Department of Health, is a large-scale national general practice dataset that extracts and collates longitudinal, de-identified patient health records from general practice clinical information systems.
As a non-physician often working as a researcher with physicians, I didn't know whether to laugh or cry at the explanation in this article as to why certain specialties might get lower patient satisfaction scores than internists. Yes, it may well be that the episodic nature of the encounter with a non-chosen physician leads to lower satisfaction. But given the long history of jokes within medicine based on the personality type differences among specialties, and, one would think, given the authors' personal experiences in say, their last dermatology appointment, might not differences among doctors rather than patient issues be at least be presented as a hypothesis? The briefest of Googling finds a post in the KevinMD blog, directed towards physicians, on "remarkably distinct" cultures. (The blog is here: https://www.kevinmd.com/blog/2018/07/what-personality-type-fits-your-med.... One of the literature links is here: https://onlinelibrary.wiley.com/doi/full/10.1111/j.1365-2923.2011.04099.x)
I admire the question and rigor the researchers used in answering it. But, in the Discussion, simply assuming "differences in perception must be due to the patient" fails to meet the test of common sense.
We can only reiterate the points brought forward by Carl Macrae in “The problem with incident reporting”. In our own work with incident reporting systems in the UK and Austria we observe that an estimated 50% of incident reports are eliminated without further consideration due to their non-clinical nature, even if they may affect patient safety. The remaining clinical reports are then pigeonholed to fit existing medical categories of expertise for further investigation. Hence, current incident reporting practices do not truly reflect the systemic complexities of medical errors, which are composed of both clinical and non-clinical elements. Incident reporting systems in healthcare need to either use more stringent reporting criteria to exclude non-clinical incidents upfront (even if they affect patient safety), but this would mean cutting themselves short of opportunities for whole system improvement. Alternatively, non-clinical reports should be further investigated to determine their potential contribution to (un)safe practice. This is likely to require the inclusion of non-clinical, organisational experts in the analysis of incident reports.
We feel that this article and accompanying press release have failed to fully acknowledge some significant limitations of the study. We feel these limitations are important when making the conclusion that following guidelines by earlier referral would be associated with earlier cancer diagnosis.
Show More1. There is no recognition that the cancer diagnosed in the year following index consultation may not have any association with the index consultation. For example a non-urgent referral for breast lump who developed bladder carcinoma in the following year would be included as someone who could have benefitted from earlier referral.
2. There is no attempt to acknowledge screening cancer diagnoses. Again these would be included despite them being unrelated to any previous “red flag” symptoms.
3. Most significantly, there is no acknowledgement that not “following guidelines” is often an important part of shared decision-making that prevents morbidity related to diagnostic processes and treatment. Although the article explains that co-morbidities and age greater than 85 are associated with lower referral rates; it fails to recognise that any delay in cancer diagnosis in this group would often not be considered a “missed opportunity”,. There is sometimes no clinical benefit to the patient of earlier diagnosis. In relation to this It also fails to recognise that many local 2ww guidelines include severe frailty as an exclusion criteria for an urgent or 2w...
The authors of this paper describe GP decision-making as ‘good but not good enough’. Their paper also highlights considerable variation among clinicians with the highest referrers being more than two times more likely to refer patients with red flag symptoms for cancer investigation than the lowest referrers. When we consider this wide disparity among individual doctors, we must look at how we can objectively and consistently reduce this. How can we make the diagnostic process in primary care ‘reliable, not heroic’ [1]?
Previous papers have considered interventions that can reduce the global burden of diagnostic errors in primary care [2], including the use of information technology tools. Perhaps we can consider that better use of technology such as Clinical Decision Support Systems (CDSS) could improve clinical diagnostics especially in those areas with clear guideline-based practice such as in the decision to refer urgently for suspected cancer [3]. These tools can be used to provide appropriate suggestions for differentials at any point in the clinical consultation or offer ‘alerts’ at the end of the consultation if there are important diagnoses that haven’t been considered [4].
Uptake of CDSS has been poor [5] and clinician response to these tools when they have been implemented are mixed [6] despite them showing that they increase physician’s diagnostic accuracy [7, 8]. At present, clinical work mostly only uses inconsistently implemented ‘alerts’. Some...
Show MoreThe recent article by Muskens et al "Overuse of diagnostic testing in healthcare: a systematic review" published online on May 10, 2021, admirably describes the prevalence and overuse of low-value diagnostic tests in multiple healthcare settings, but does not offer possible explanations or solutions. Some salient reasons are (1): 1. Physicians do not consider healthcare costs during a diagnostic workup; 2. Malpractice concerns; 3. An excessive fee-for-service mentality--more tests and consultations generate more income; 4. Lack of trust in clinical skills versus high technology testing; 5. Believing that diagnostic workups should eliminate all conceivable etiologies; and 6. Patients may experience greater satisfaction with more testing.
Underlying these last three possibilities is the failure to appreciate that in science, especially after Darwin, Einstein and Heisenberg, absolute certainty is considered unachievable. Facts and theories, and clinical diagnoses, are now rated on the probability that they are true. A diagnosis is more probable than not, or more probable than another, based on degrees of evidence. Hence recent interest in Bayesianism, which analyses evidence in terms of probability. When determining the efficacy of additional tests, Bayesianism requires a pre-test (a priori) probability estimate of the diagnosis. The more probable a diagnosis is clinically (a priori) and the greater the diagnostician's clinical confidence, the less nec...
Show MoreWe thank Professors Marang-van de Mheen and Vincent for their comments [1] on our examination of variations in weekend and weekday admission care quality during the introduction of seven day services in England [2]. Their analysis and logic models demonstrate with admirable simplicity the complexity of these causal pathways.
Show MoreOne of the pathways which is not highlighted in the literature is how quality of pre-hospital care may impact on the post-admission phase in hospital. Using exploratory data from the 20 hospitals in our data set, we have shown that while in-hospital care quality did not vary between weekend and weekday admissions, and had improved over time, there was a concurrent deterioration in performance indicators related to care in the community preceding hospital admission. Weekend admissions were much less likely to have been referred by family doctors, and more likely to attend hospital by emergency ambulance, to be dependent on others for activities of daily living, and to be candidates for palliative care. These differences became more marked with the passage of time. In a separate single-centre study we have shown that patients admitted at weekends are sicker than those admitted on weekdays [3]. We therefore contend that while there may be opportunities to improve hospital care across all days of the week, the cause for the weekend effect may reside in community healthcare services. As the weekend effect is a global phenomenon [4], policy makers a...
Adherence Issues in Population with Intellectual Disabilities
Bernadette Flood PhD MPSI, Pharmacist, Daughters of Charity Disability Support Services
Link to Original article: Medication non-adherence: an overlooked target for quality improvement interventions
Commentary on: Medication non-adherence: an overlooked target for quality improvement interventions, Bryony Dean Franklin, Gary Abel, Kaveh G Shojania (2019-12-20). 10.1136/bmjqs-2019-009984
Non adherence to prescribed medication is a complex problem. The complexity is increased in vulnerable population groups such as the population with intellectual disabilities. A person with an intellectual disability may often be dependent on ‘healthcare by proxy’ where another person makes healthcare decisions on their behalf. People with intellectual disabilities may also be ‘invisible’ to pharmacists dispensing prescribed medicines. Many pharmacists may have little experience of the challenges faced by this high risk group of patients [1] who may be prescribed high risk medications such as diabetic medicines including insulin and anti-epileptic medications. People with intellectual disabilities and their family carers, support workers etc. may be unaware of the consequences of poor adherence to prescribed medicines. The difficulties of involving a parent proxy in a three-way relationship involving an adult at risk of lacking decision-making capacity, their proxy, and a treating clinician have been ra...
Show MoreWe thank the French Society of Emergency Medicine for such a large study. However it is difficult to conclude regarding a number of limitations due to the observational cross-sectional study scheme.
The main critics concern the 3 measurements tools allowing to decide appropriateness of ED visits or not. Appropriate Use Score Method: the authors decide a cut-off based on Italian litterature data which is not French sounded; Possible GP Use Method : it would be more accurate to have an external evaluation instead of a judge and part one ; Resource Utilisation Method : the elephant in the room is the result of consultation and the final diagnostic as well.
I don’t discuss here the relevance of a number of items as distance between home and ED Departments, medical density and so far.
Specifically I doubt it is possible to interpret socioeconomic and territorial factors results without diagnostics and diagnostic frequency on June, 11, 2013
We are looking forward for more studies informing use of ED departments.
To the editor,
In their editorial commenting on our paper “Association of registered nurse and nursing support staffing with inpatient hospital mortality,” [1] Aiken and Sloane misrepresent our study results, conclusions and implications. They characterize our study as examining the impact of substitution of nursing support staff for professional nurses or registered nurses (RNs) (commonly described as skill mix). This is done despite acknowledging that we stated our findings should not be interpreted to mean that nursing aides can safely substitute for RNs. Furthermore, as Aiken and Sloane acknowledge each of us have published multiple studies [2 3] showing efforts to deskill the nursing work force will increase deaths, adverse events and costs. This conclusion was also restated in a recent editorial in this journal by one of us. [4]
Aiken and Sloane discuss the paper as though it is about skill mix, characterizing our findings as “counter” to our earlier published papers that did analyze skill mix. However, the current paper and the recent Griffith’s paper Aiken and Sloane also reference[5], “examine nursing support staffing not as a substitute for RNs, as studies of skill mix do, but …rather examine the impact of shortfalls in support staffing given established RN- nursing support staffing models.” What our paper and Griffiths paper do is examine shortfalls from established levels of nurse support staffing as a complement of typical RN staffing withi...
Show MoreI write in response to the article published in your journal “Passing the acid test? Evaluating the impact of national education initiatives to reduce proton pump inhibitor use in Australia” (Bruno C et al., BMJ Qual Saf 2019). I am writing as NPS MedicineWise evaluation found a significant impact on general practitioner prescribing of proton pump inhibitors (PPIs) following their educational programs in 2009 and 2015. I acknowledge that the article is well written, the methods are well described, and the approach includes a number of sensitivity analyses. However, I would like to highlight some key points on the analysis methods used that differ from the approach taken by NPS MedicineWise and about which I have some concerns.
The 2015 NPS MedicineWise educational program on PPIs was part of a larger educational strategy over a decade to support best-practice prescribing of PPIs by general practitioners (GPs) and included Pharmaceutical Benefits Scheme (PBS) feedback to GPs in Australia. This consists of a letter that includes information of the individual GP’s prescribing of PPIs compared to their peers. Programs launched in 2009 and 2018 on PPI prescribing for GPs also included face-to-face educational visits to GP practices. The 2015 campaign, which did not include these face-to-face visits, aimed to reinforce the impact of the earlier 2009 campaign.
NPS MedicineWise has conducted an evaluation of the 2009 and 2015 education programs on GP prescribing o...
Show MoreAs a non-physician often working as a researcher with physicians, I didn't know whether to laugh or cry at the explanation in this article as to why certain specialties might get lower patient satisfaction scores than internists. Yes, it may well be that the episodic nature of the encounter with a non-chosen physician leads to lower satisfaction. But given the long history of jokes within medicine based on the personality type differences among specialties, and, one would think, given the authors' personal experiences in say, their last dermatology appointment, might not differences among doctors rather than patient issues be at least be presented as a hypothesis? The briefest of Googling finds a post in the KevinMD blog, directed towards physicians, on "remarkably distinct" cultures. (The blog is here: https://www.kevinmd.com/blog/2018/07/what-personality-type-fits-your-med.... One of the literature links is here: https://onlinelibrary.wiley.com/doi/full/10.1111/j.1365-2923.2011.04099.x)
I admire the question and rigor the researchers used in answering it. But, in the Discussion, simply assuming "differences in perception must be due to the patient" fails to meet the test of common sense.
We can only reiterate the points brought forward by Carl Macrae in “The problem with incident reporting”. In our own work with incident reporting systems in the UK and Austria we observe that an estimated 50% of incident reports are eliminated without further consideration due to their non-clinical nature, even if they may affect patient safety. The remaining clinical reports are then pigeonholed to fit existing medical categories of expertise for further investigation. Hence, current incident reporting practices do not truly reflect the systemic complexities of medical errors, which are composed of both clinical and non-clinical elements. Incident reporting systems in healthcare need to either use more stringent reporting criteria to exclude non-clinical incidents upfront (even if they affect patient safety), but this would mean cutting themselves short of opportunities for whole system improvement. Alternatively, non-clinical reports should be further investigated to determine their potential contribution to (un)safe practice. This is likely to require the inclusion of non-clinical, organisational experts in the analysis of incident reports.
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