The third project is only one project listed which could fund this RCT because it is to be implemented from 2016 to 2018. But content of project 81603659 is prevention and treatment of cognitive impairment in epileptic rats, not a human RCT. Although the content of project 81603659 is still not revealed, this fact can be confirmed on web site of National Natural Science Foundation of China,...
The third project is only one project listed which could fund this RCT because it is to be implemented from 2016 to 2018. But content of project 81603659 is prevention and treatment of cognitive impairment in epileptic rats, not a human RCT. Although the content of project 81603659 is still not revealed, this fact can be confirmed on web site of National Natural Science Foundation of China, http://npd.nsfc.gov.cn/fundingProjectSearchAction!search.action, with search results of number 81603659. If this project is funding ChiCTR-IOR-1701039, both of them will face serious ethical issues.
First of all, adequate and legitimate financial support is one of the most important conditions to guarantee basic ethical requirements of a clinical trial for human-being such as completeness of the RCT and safety of research subjects involved. Second, fake fund declaration in research article is an academic misconduct because it results in serious ethical issues described before. Finally, reading and references for protocol of an RCT with ethical issues, i.e. article e015983, will mislead readers of this journal and result in inappropriate financial support for further research projects.
In view of the above reasons, I would like to request editorial board of BMJ Open to confirm the authenticity of financial support of RCT ChiCTR-IOR-1701039 and article e015983 and reconsider whether publication of article e015983 meets fundamental medical ethical standards or not.
Best wishes
Yuzhen Li
Hangzhou Street Community Health Service Center, Binhai New Area, Tianjin, PRC
Aside form many of the concerns about the imputed causality of the conclusions in this paper, there are some simple issues with the data. It would be helpful to clarify them.
The biggest issue is the disparity between the age standardised death rates (ASDR) used in the paper (calculated by the authors) and the ASDR as published by the ONS. The paper claims to use the ONS template to perform their own calculations, but the numbers are very different from the actual numbers published by the ONS. The ASDR for England and Wales in the ONS stats is a little over 1,000 per 100,000 in 2016 but the figures used in the paper seem to be around 500.
At first glance this looks like the paper has used the 1976 standard European population instead of the more recent and more reliable 2013 population (see a comparison of the two here https://www.nrscotland.gov.uk/files/statistics/age-standardised-death-ra... ). It is unclear whether this makes a huge difference to the results, but the reason for the disparity should have been noticed and mentioned or it casts a serious shadow over the results. And, why do your own calculations when the results of that calculation are actually available from a reliable source like the ONS? This is a strange choice.
Also, in assuming that the key relevant causes are primarily related to health and soci...
Aside form many of the concerns about the imputed causality of the conclusions in this paper, there are some simple issues with the data. It would be helpful to clarify them.
The biggest issue is the disparity between the age standardised death rates (ASDR) used in the paper (calculated by the authors) and the ASDR as published by the ONS. The paper claims to use the ONS template to perform their own calculations, but the numbers are very different from the actual numbers published by the ONS. The ASDR for England and Wales in the ONS stats is a little over 1,000 per 100,000 in 2016 but the figures used in the paper seem to be around 500.
At first glance this looks like the paper has used the 1976 standard European population instead of the more recent and more reliable 2013 population (see a comparison of the two here https://www.nrscotland.gov.uk/files/statistics/age-standardised-death-ra... ). It is unclear whether this makes a huge difference to the results, but the reason for the disparity should have been noticed and mentioned or it casts a serious shadow over the results. And, why do your own calculations when the results of that calculation are actually available from a reliable source like the ONS? This is a strange choice.
Also, in assuming that the key relevant causes are primarily related to health and social care resources without some simple comparisons to other data that is also available seems a little premature. Mortality trends are also available for many other European countries in this format. PHE's analysis pointed out this in commenting on some recent changes in mortality: "The increase in mortality rates in 2015 was not limited to England alone. It was seen across Europe on a comparable scale. The six biggest countries in the European Union (France, Germany, Italy, Poland, Spain, UK), all saw a fall in their life expectancies for both sexes." Whether this is also explains the earlier increases from 2011 to 2014 is unclear, but the comparisons with other datasets in other countries should surely have been done. If some external cause (a severe flu strain for example), common across many countries, were impacting the data, surely this should be a relevant confounding factor?
I can't be sure these factors are relevant to the paper's conclusions, but the fact they have not been considered or discussed is a cause for some due skepticism.
We thank Prof. Helio S. A. Camargo Jr, a respected author of a handbook on breast image exams, for his letter, which presents an opportunity to make our points clearer. We agree that “having a mammogram is not the same thing as being screened with mammography”. According to Tomazelli et al (2017), based on the National Breast Cancer Control Information System (Sismama), 96.2% of the mammograms in Brazil were for screening (performed in asymptomatic women) and 3.8% were diagnostic (in patients with suspicious breast cancer signs and/or symptoms), in the period they analyzed (2010-2011) (1).
That means that less than 1 in 25 mammograms in Brazil were diagnostic, which must be one of the lowest rates in the world. The proportion of screening over diagnostic mammography must have further increased, with the expansion in coverage of breast screening in the last five years (2). The distribution of the mammographies for reasons other than screening are, therefore, diluted in the municipalities, without forming specific clusters.
We also agree that “death certificates in Brazil do not always reflect the actual cause of death” and we recognized this limitation in our study. But is noteworthy the Brazilian health information system has improved dramatically in last decades since the creation of SUS (Public Health System) in 1988, in terms of quality and completeness. The analysis of data quality collected by the Mortality Information System indicates t...
We thank Prof. Helio S. A. Camargo Jr, a respected author of a handbook on breast image exams, for his letter, which presents an opportunity to make our points clearer. We agree that “having a mammogram is not the same thing as being screened with mammography”. According to Tomazelli et al (2017), based on the National Breast Cancer Control Information System (Sismama), 96.2% of the mammograms in Brazil were for screening (performed in asymptomatic women) and 3.8% were diagnostic (in patients with suspicious breast cancer signs and/or symptoms), in the period they analyzed (2010-2011) (1).
That means that less than 1 in 25 mammograms in Brazil were diagnostic, which must be one of the lowest rates in the world. The proportion of screening over diagnostic mammography must have further increased, with the expansion in coverage of breast screening in the last five years (2). The distribution of the mammographies for reasons other than screening are, therefore, diluted in the municipalities, without forming specific clusters.
We also agree that “death certificates in Brazil do not always reflect the actual cause of death” and we recognized this limitation in our study. But is noteworthy the Brazilian health information system has improved dramatically in last decades since the creation of SUS (Public Health System) in 1988, in terms of quality and completeness. The analysis of data quality collected by the Mortality Information System indicates that, between 2000 and 2009, there was an improvement in coverage and the completeness of variables collected by this system. The causes of death presented a significant improvement in their definition throughout the decade (3). In 2010, the proportion of deaths due to ill-defined causes in the Southeast region of Brazil was 8.1%, decreasing to 7.1% after the investigation and reclassification proposed by the Ministry of Health (4). Additionally, the availability of large computerized databases on health turned the record linkage technique into an alternative for different study designs, particularly spatial analysis (5).
We agree that lack of access to data of the private sector is a serious problem, in terms of transparency and accountability of processes and outcomes in Brazil. Beyond diseases with mandatory notification and vital statistics (births and deaths), information about morbidity and hospitalization in the private sector is not publicly available on a regular basis, and usually accessed only from population-based household surveys, such as Demographic and Health Surveys (6). While SUS data is publicly available in open databases (except for issues related to patient confidentiality), information of private sector is treated as a black box, which limits comparison with public sector.
We would be glad to collaborate on joint analysis of the private sector regarding breast cancer, and other relevant public health problems.
Warmest regards,
Carmen Simone Grilo Diniz
Alessandra Cristina Guedes Pellini
Adeylston Guimarães Ribeiro
Marcello Vannucci Tedardi
Marina Jorge de Miranda
Michelle Mosna Touso
Oswaldo Santos Baquero
Patrícia Carla dos Santos
Francisco Chiaravalloti-Neto
References
1 - Tomazelli JG, Migowski A, Ribeiro CM, Assis M, Abreu DMF. Avaliação das ações de detecção precoce do câncer de mama no Brasil por meio de indicadores de processo: estudo descritivo com dados do Sismama, 2010-2011. Epidemiol Serv Saúde 2017;26(1):61-70.
2 - Vigitel Brasil 2016: Vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico. Ministério da Saúde, Secretaria de Vigilância em Saúde, Departamento de Vigilância de Doenças e Agravos não Transmissíveis e Promoção da Saúde. Brasília: Ministério da Saúde, 2017. [cited 2017 Nov 6] Available from: http://portalarquivos.saude.gov.br/images/pdf/2017/junho/07/vigitel_2016...
3 - Maranhão AGK, Vasconcelos AMN, Aly CMC, Rabello Neto DL, Porto DL, Oliveira H, et al. Como morrem os brasileiros: caracterização e distribuição geográfica dos óbitos no Brasil, 2000, 2005 e 2009. Ministério da Saúde, organizador. Saúde Brasil 2010: uma análise da situação de saúde e evidências selecionadas de impacto de ações de vigilância em saúde. Brasília: Ministério da Saúde; 2011. v. 1. p. 51-78. [cited 2017 Nov 21] Available from: http://www.repositorio.unb.br/bitstream/10482/12475/1/CAPITULO_ComoMorre...
4 - França E, Teixeira R, Ishitani L, Duncan BB, Cortez-Escalante JJ, Morais Neto OL, Szwarcwald CL. Ill-defined causes of death in Brazil: a redistribution method based on the investigation of such causes. Rev Saúde Pública 2014;48(4):671-681. [cited 2017 Nov 21] Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102014000....
5 - Peres SV, Latorre MRDO, Tanaka LF, Michels FAZ, Teixeira MLP, Coeli CM, Almeida MF.. Melhora na qualidade e completitude da base de dados do Registro de Câncer de Base Populacional do município de São Paulo: uso das técnicas de linkage. Rev bras Epidemiol 2016;19(4):753-765.
6 - Diniz CSG, d'Oliveira AFPL, Lansky S. Equity and women's health services for contraception, abortion and childbirth in Brazil. Reprod Health Matters 2012;20(40): 94-101.
Further to my earlier response to this article, it is probably appropriate to add some further clarifying detail. The principal problem lies in the fact that the detailed trends in deaths do not conform to the assumed calendar year breaks assumed in this study. The international evidence indicates that deaths (and medical admissions) have for many years shown on/off switching along with single-year-of-age specific changes.
Indeed deaths and medical admissions are not the only health factors to be affected and the gender ratio at birth along with admissions for certain conditions during pregnancy and childbirth also simultaneously change. The ratio of female to male admissions also show unexplained and simultaneous changes (and have done so for many years). It is difficult to pin these changes on a simple spending explanation.
Hospital bed occupancy likewise undergoes unexplained changes. It has also been my experience from a 25-year career in healthcare analysis that delayed discharges of care always increase during these unexplained periods of higher deaths and medical admissions.
Rather than citing all the individual studies can I refer the reader to over 200 studies on this topic published over the past 9 years. These can be found at http://www.hcaf.biz/2010/Publications_Full.pdf
I hope this will lead to the further fruitful investigation of this enigmatic and recurring phenomena....
Further to my earlier response to this article, it is probably appropriate to add some further clarifying detail. The principal problem lies in the fact that the detailed trends in deaths do not conform to the assumed calendar year breaks assumed in this study. The international evidence indicates that deaths (and medical admissions) have for many years shown on/off switching along with single-year-of-age specific changes.
Indeed deaths and medical admissions are not the only health factors to be affected and the gender ratio at birth along with admissions for certain conditions during pregnancy and childbirth also simultaneously change. The ratio of female to male admissions also show unexplained and simultaneous changes (and have done so for many years). It is difficult to pin these changes on a simple spending explanation.
Hospital bed occupancy likewise undergoes unexplained changes. It has also been my experience from a 25-year career in healthcare analysis that delayed discharges of care always increase during these unexplained periods of higher deaths and medical admissions.
Rather than citing all the individual studies can I refer the reader to over 200 studies on this topic published over the past 9 years. These can be found at http://www.hcaf.biz/2010/Publications_Full.pdf
I hope this will lead to the further fruitful investigation of this enigmatic and recurring phenomena.
I do not refute the hypothesis that spending constraints had adverse health impacts. However, the authors do not provide convincing evidence to support their hypothesis. For example, it does not seems sensible to investigate separately the association between spending and number of deaths by place of deaths. Surely, what we care about is the total number of deaths? If we find more deaths at home and in care homes and fewer deaths in hospital, this could be a good thing, since hospital is not most people's preferred place of death. Since the authors do not present results for all deaths, we do not know if the main effect is shifting deaths from hospitals to other places.
Table 1 reports the number of observations as 28. So there are 14 data points for male mortality and 14 data points for female mortality. But the explanatory variables, expenditure on health and social care, are not reported separately for males and females. So the same values of these variables are used twice!
The associations between spending and mortality reported in the paper are clearly not causal relationships. Nevertheless, the authors claim that around £25 to £30 billion additional spending are required to close the gap.
The description of the methods are misleading. The authors describe their models as fixed effects regression models but what they actually do is a long way from a fixed effects model traditionally used by economists to control for area-specific unobserved e...
I do not refute the hypothesis that spending constraints had adverse health impacts. However, the authors do not provide convincing evidence to support their hypothesis. For example, it does not seems sensible to investigate separately the association between spending and number of deaths by place of deaths. Surely, what we care about is the total number of deaths? If we find more deaths at home and in care homes and fewer deaths in hospital, this could be a good thing, since hospital is not most people's preferred place of death. Since the authors do not present results for all deaths, we do not know if the main effect is shifting deaths from hospitals to other places.
Table 1 reports the number of observations as 28. So there are 14 data points for male mortality and 14 data points for female mortality. But the explanatory variables, expenditure on health and social care, are not reported separately for males and females. So the same values of these variables are used twice!
The associations between spending and mortality reported in the paper are clearly not causal relationships. Nevertheless, the authors claim that around £25 to £30 billion additional spending are required to close the gap.
The description of the methods are misleading. The authors describe their models as fixed effects regression models but what they actually do is a long way from a fixed effects model traditionally used by economists to control for area-specific unobserved effects. In fact, the authors have only one area - England - and their fixed effect seems to be gender, which as described above, does not make much sense since there are no separate figures for female and male health and social care expenditure.
The authors goal of demonstrating the negative impacts of austerity is laudable, but they need to do so using valid scientific methods.
There can be no doubt that constraints on healthcare spending has an adverse effect upon mortality.
If we analyse several key areas required for the safe and effective functioning of a hospital then it is clear to see that the reduction in real term funding has had a multifactorial effect upon some of the following:
• Staffing: There are now record numbers of rota gaps. Shortages of doctors across all medical specialties is the norm. Trusts are routinely staffing rota gaps with internal locums or leaving posts vacant, resulting in certain services being dangerously understaffed or closing down. Rota gaps save trusts thousands of pounds, relying on the goodwill of the remaining staff to fill the void.
• Equipment: Essential equipment is frequently defective, out of date or unsafe. Operating theatres have to contend with instruments that are ill maintained (owing to outsourcing) leading to increased operating time and putting lives at risk.
• Medications: Health care authorities are rationing oncological medications despite NICE guidelines. We have a post code lottery for cancer and reproductive services.
• Buildings and maintenance: Hospitals are ill maintained. Heating and ventilation failures are common in theatre. Money spent on PFI repayments could be used for building maintenance.
• Study budgets: Cuts in study budgets have a negative impact upon training and education. Maintaining up to date skills is essential. Cutting study budget...
There can be no doubt that constraints on healthcare spending has an adverse effect upon mortality.
If we analyse several key areas required for the safe and effective functioning of a hospital then it is clear to see that the reduction in real term funding has had a multifactorial effect upon some of the following:
• Staffing: There are now record numbers of rota gaps. Shortages of doctors across all medical specialties is the norm. Trusts are routinely staffing rota gaps with internal locums or leaving posts vacant, resulting in certain services being dangerously understaffed or closing down. Rota gaps save trusts thousands of pounds, relying on the goodwill of the remaining staff to fill the void.
• Equipment: Essential equipment is frequently defective, out of date or unsafe. Operating theatres have to contend with instruments that are ill maintained (owing to outsourcing) leading to increased operating time and putting lives at risk.
• Medications: Health care authorities are rationing oncological medications despite NICE guidelines. We have a post code lottery for cancer and reproductive services.
• Buildings and maintenance: Hospitals are ill maintained. Heating and ventilation failures are common in theatre. Money spent on PFI repayments could be used for building maintenance.
• Study budgets: Cuts in study budgets have a negative impact upon training and education. Maintaining up to date skills is essential. Cutting study budgets prevents the updating of evidence based practices.
• Morale: Although difficult to quantify, the over burdening of staff caused by an erosion of pay, facilities, pharmacological and investigative armamentarium has led to a decrease in staff morale. Trainees are no longer applying for run through training whilst they analyse their options, resulting in the loss of enthusiastic middle grade staff that were once essential for the delivery of first class health care.
We therefore have the perfect storm and with it the adverse effect upon mortality is clear. Funding must be increased if we are to avoid the unnecessary and preventable loss of life..
A very nice study with focused vision for future. Read it and appreciate with acknowledgement to bring this entire study to us. Would like to highlight a follow up of the said subjects as per their genetic makeup in this era of personalised medicine. Hypoxia and level of venous hypoxia as a key factor is missing to be aligned with calories intake and other factors which will define change the entire scope of study beside its implementation. The genes associated with obesity and involved in energy hemostasis must be considered at least as per study performed.
This study appears to be flawed. This is due to the fact that although spending may have gone down, the number of nurses and care workers may have gone up. The rate of care may also have increased within a year that had less spending, factors which do not appear to have been addressed.
The increase in mortality since 2011 has been an intriguing area of inquiry. I have already published several papers on this topic which suggest that social care spending is not the major contributory factor [1-18]. Several other papers are in press [19-24]. The issues raised in these papers have sadly been missed in this study. It would appear that further research is required on this important topic to disentangle cause and effect.
References
1. Jones R (2014) Infectious-like Spread of an Agent Leading to Increased Medical Admissions and Deaths in Wigan (England), during 2011 and 2012. British Journal of Medicine and Medical Research 4(28): 4723-4741. doi: 10.9734/BJMMR/2014/10807
2. Jones R, Beauchant S (2015) Spread of a new type of infectious condition across Berkshire in England between June 2011 and March 2013: Effect on medical emergency admissions. British Journal of Medicine and Medical Research 6(1): 126-148. doi: 10.9734/BJMMR/2015/14223
3. Jones R (2015) Unexpected and Disruptive Changes in Admissions Associated with an Infectious-like Event Experienced at a Hospital in Berkshire, England around May of 2012. British Journal of Medicine and Medical Research 6(1): 56-76. doi: 10.9734/BJMMR/2015/13938
4. Jones R (2015) A previously uncharacterized infectious-like event leading to spatial spread of deaths across England and Wales: Characteristics of the most recent event and a time series for past events. Brit J Medicine and...
The increase in mortality since 2011 has been an intriguing area of inquiry. I have already published several papers on this topic which suggest that social care spending is not the major contributory factor [1-18]. Several other papers are in press [19-24]. The issues raised in these papers have sadly been missed in this study. It would appear that further research is required on this important topic to disentangle cause and effect.
References
1. Jones R (2014) Infectious-like Spread of an Agent Leading to Increased Medical Admissions and Deaths in Wigan (England), during 2011 and 2012. British Journal of Medicine and Medical Research 4(28): 4723-4741. doi: 10.9734/BJMMR/2014/10807
2. Jones R, Beauchant S (2015) Spread of a new type of infectious condition across Berkshire in England between June 2011 and March 2013: Effect on medical emergency admissions. British Journal of Medicine and Medical Research 6(1): 126-148. doi: 10.9734/BJMMR/2015/14223
3. Jones R (2015) Unexpected and Disruptive Changes in Admissions Associated with an Infectious-like Event Experienced at a Hospital in Berkshire, England around May of 2012. British Journal of Medicine and Medical Research 6(1): 56-76. doi: 10.9734/BJMMR/2015/13938
4. Jones R (2015) A previously uncharacterized infectious-like event leading to spatial spread of deaths across England and Wales: Characteristics of the most recent event and a time series for past events. Brit J Medicine and Medical Research 5(11): 1361-1380. doi: 10.9734/BJMMR/2015/14285
5. Jones R (2015) Are emergency admissions contagious? Brit J Healthcare Management 21(5): 227-235.
6. Jones R (2015) Recurring Outbreaks of an Infection Apparently Targeting Immune Function, and Consequent Unprecedented Growth in Medical Admission and Costs in the United Kingdom: A Review. British Journal of Medicine and Medical Research 6(8): 735-770. doi: 10.9734/BJMMR/2015/14845
7. Jones R (2015) A new type of infectious outbreak? SMU Medical Journal 2(1): 19-25. http://smu.edu.in/content/dam/manipal/smu/documents/Journal%20Issue%203/...
8. Jones R (2015) Small area spread and step-like changes in emergency medical admissions in response to an apparently new type of infectious event. Fractal Geometry and Nonlinear Analysis in Medicine and Biology 1(2): 42-54. doi: 10.15761/FGNAMB.1000110
9. Jones R (2015) Infectious-like spread of an agent leading to increased medical hospital admission in the North East Essex area of the East of England. Fractal Geometry and Nonlinear Analysis in Medicine and Biology 1(3): 98-111. doi: 10.15761/FGNAMB.1000117
10. Jones R (2015) Simulated rectangular wave infectious-like events replicate the diversity of time-profiles observed in real-world running 12 month totals of admissions or deaths. FGNAMB 1(3): 78-79. doi: 10.15761/FGNAMB.1000114
11. Jones R (2015) A time series of infectious-like events in Australia between 2000 and 2013 leading to extended periods of increased deaths (all-cause mortality) with possible links to increased hospital medical admissions. International Journal of Epidemiologic Research 2(2): 53-67. http://ijer.skums.ac.ir/article_12869_2023.html
12. Jones R (2016) Deaths in English Lower Super Output Areas (LSOA) show patterns of very large shifts indicative of a novel recurring infectious event. SMU Medical Journal 3(2): 23-36. https://pdfs.semanticscholar.org/c3aa/71a1b78e053cba4a871093dd43aa896d9e...
13. Jones R (2016) A presumed infectious event in England and Wales during 2014 and 2015 leading to higher deaths in those with
neurological and other disorders. Journal of Neuroinfectious Diseases 7(1): 1000213 doi: 10.4172/2314-7326.1000213
14. Jones R (2016) Unusual trends in NHS staff sickness absence. BJHCM 22(4): 239-240.
15. Jones R (2016) A regular series of unexpected and large increases in total deaths (all-cause mortality) for male and female residents of mid super output areas (MSOA) in England and Wales: How high level analysis can miss the contribution from complex small-area spatial spread of a presumed infectious agent. Fractal Geometry and Nonlinear Analysis in Medicine and Biology 2(2): 1-13. doi: 10.15761/FGNAMB.1000129
16. Jones R (2017) Outbreaks of a Presumed Infectious Agent Associated with Changes in Fertility, Stillbirth, Congenital Abnormalities and the Gender Ratio at Birth. British Journal of Medicine and Medical Research 20(8): 1-36. doi: 10.9734/BJMMR/2017/32372
17. Jones R (2017) Outbreaks of a presumed infectious pathogen creating on/off switching in deaths. SDRP Journal of Infectious Diseases Treatment and Therapy 1(1): 1-6. http://www.openaccessjournals.siftdesk.org/articles/pdf/Outbreaks-of-a-p...
18. Jones R (2017) Year-to-year variation in deaths in English Output Areas (OA), and the interaction between a presumed infectious agent and influenza in 2015. SMU Medical Journal 4(2): 37-69. http://smu.edu.in/content/dam/manipal/smu/smims/Volume4No2July2017/SMU%2...(July%202017)%20-%204.pdf
19. Jones R (2017) A reduction in acute thrombotic admissions during a period of unexplained increased deaths and medical admissions in the UK. European Journal of Internal Medicine doi: http://dx.doi.org/10.1016/j.ejim.2017.09.007
20. Jones R (2017) Deaths and medical admissions in the UK show an unexplained and sustained peak after 2011. European Journal of Internal Medicine (in press). http://www.ejinme.com/article/S0953-6205(17)30370-9/fulltext
21. Jones R (2017) Periods of unexplained higher deaths and medical admissions have occurred previously – but were apparently ignored, misinterpreted or not investigated. European Journal of Internal Medicine (in press)
22. Jones R (2017) Age-specific and year of birth changes in hospital admissions during a period of unexplained higher deaths in England. European Journal of Internal Medicine (in press) http://www.sciencedirect.com/science/article/pii/S0953620517304053
23. Jones R (2017) Role of social group and gender in outbreaks of a novel agent leading to increased deaths, with insights into higher international deaths in 2015. Fractal Geometry and Nonlinear Analysis in Medicine and Biology 3(1): in press.
24. Jones R (2017) Different patterns of male and female deaths in 2015 in English and Welsh local authorities question the role of austerity as the primary force behind higher deaths. Fractal Geometry and Nonlinear Analysis in Medicine and Biology 3(2): in press.
In the recent article by Myers, et al., the authors stated that Emergency Medicine (EM) was not a recognized specialty in Kenya, which was highlighted as a key step for the development of acute care in Kenya. During the review process for publication of this paper, the Kenya Medical Practitioners and Dentists Board (KMPDB) formally recognized EM as a new “medical specialty” in May 2017.(1) The paper also highlights the volume and diversity of patient presentations to Kenyatta National Hospital, the national referral hospital. The majority of patient complaints were either undifferentiated, or were due to trauma and non-communicable diseases. These high acuity, multi-disciplinary patients represent a case mix that an EM residency– trained practitioner is ideally suited to manage. Although Kenya currently lacks EM residency training programs, the recognition of the specialty is a step forward for the development of EM care in Kenya.
Dear editorial board of BMJ Open,
In article e015983, http://bmjopen.bmj.com/content/7/11/e015983, and registration information, http://www.chictr.org.cn/showprojen.aspx?proj=17715, of its RCT, it was claimed that this RCT, ChiCTR-IOR-1701039, is running and funded by 3 projects of National Natural Science Foundation of China, namely 81202849, 30600834 and 81603659.
However, none of these three projects could fund this RCT. The first project has been closed in 2015, see http://npd.nsfc.gov.cn/projectDetail.action?pid=81202849. The second project also has been closed in 2009, see http://npd.nsfc.gov.cn/projectDetail.action?pid=30600834. But the RCT in article e015983 is running from 2017-1-1 to 2018-1-1. Time difference results in that the first 2 projects were impossible to fund this RCT.
The third project is only one project listed which could fund this RCT because it is to be implemented from 2016 to 2018. But content of project 81603659 is prevention and treatment of cognitive impairment in epileptic rats, not a human RCT. Although the content of project 81603659 is still not revealed, this fact can be confirmed on web site of National Natural Science Foundation of China,...
Show MoreAside form many of the concerns about the imputed causality of the conclusions in this paper, there are some simple issues with the data. It would be helpful to clarify them.
The biggest issue is the disparity between the age standardised death rates (ASDR) used in the paper (calculated by the authors) and the ASDR as published by the ONS. The paper claims to use the ONS template to perform their own calculations, but the numbers are very different from the actual numbers published by the ONS. The ASDR for England and Wales in the ONS stats is a little over 1,000 per 100,000 in 2016 but the figures used in the paper seem to be around 500.
At first glance this looks like the paper has used the 1976 standard European population instead of the more recent and more reliable 2013 population (see a comparison of the two here https://www.nrscotland.gov.uk/files/statistics/age-standardised-death-ra... ). It is unclear whether this makes a huge difference to the results, but the reason for the disparity should have been noticed and mentioned or it casts a serious shadow over the results. And, why do your own calculations when the results of that calculation are actually available from a reliable source like the ONS? This is a strange choice.
Also, in assuming that the key relevant causes are primarily related to health and soci...
Show MoreDear Editor
We thank Prof. Helio S. A. Camargo Jr, a respected author of a handbook on breast image exams, for his letter, which presents an opportunity to make our points clearer. We agree that “having a mammogram is not the same thing as being screened with mammography”. According to Tomazelli et al (2017), based on the National Breast Cancer Control Information System (Sismama), 96.2% of the mammograms in Brazil were for screening (performed in asymptomatic women) and 3.8% were diagnostic (in patients with suspicious breast cancer signs and/or symptoms), in the period they analyzed (2010-2011) (1).
Show MoreThat means that less than 1 in 25 mammograms in Brazil were diagnostic, which must be one of the lowest rates in the world. The proportion of screening over diagnostic mammography must have further increased, with the expansion in coverage of breast screening in the last five years (2). The distribution of the mammographies for reasons other than screening are, therefore, diluted in the municipalities, without forming specific clusters.
We also agree that “death certificates in Brazil do not always reflect the actual cause of death” and we recognized this limitation in our study. But is noteworthy the Brazilian health information system has improved dramatically in last decades since the creation of SUS (Public Health System) in 1988, in terms of quality and completeness. The analysis of data quality collected by the Mortality Information System indicates t...
Further to my earlier response to this article, it is probably appropriate to add some further clarifying detail. The principal problem lies in the fact that the detailed trends in deaths do not conform to the assumed calendar year breaks assumed in this study. The international evidence indicates that deaths (and medical admissions) have for many years shown on/off switching along with single-year-of-age specific changes.
Indeed deaths and medical admissions are not the only health factors to be affected and the gender ratio at birth along with admissions for certain conditions during pregnancy and childbirth also simultaneously change. The ratio of female to male admissions also show unexplained and simultaneous changes (and have done so for many years). It is difficult to pin these changes on a simple spending explanation.
Hospital bed occupancy likewise undergoes unexplained changes. It has also been my experience from a 25-year career in healthcare analysis that delayed discharges of care always increase during these unexplained periods of higher deaths and medical admissions.
Rather than citing all the individual studies can I refer the reader to over 200 studies on this topic published over the past 9 years. These can be found at http://www.hcaf.biz/2010/Publications_Full.pdf
I hope this will lead to the further fruitful investigation of this enigmatic and recurring phenomena....
Show MoreI do not refute the hypothesis that spending constraints had adverse health impacts. However, the authors do not provide convincing evidence to support their hypothesis. For example, it does not seems sensible to investigate separately the association between spending and number of deaths by place of deaths. Surely, what we care about is the total number of deaths? If we find more deaths at home and in care homes and fewer deaths in hospital, this could be a good thing, since hospital is not most people's preferred place of death. Since the authors do not present results for all deaths, we do not know if the main effect is shifting deaths from hospitals to other places.
Table 1 reports the number of observations as 28. So there are 14 data points for male mortality and 14 data points for female mortality. But the explanatory variables, expenditure on health and social care, are not reported separately for males and females. So the same values of these variables are used twice!
The associations between spending and mortality reported in the paper are clearly not causal relationships. Nevertheless, the authors claim that around £25 to £30 billion additional spending are required to close the gap.
The description of the methods are misleading. The authors describe their models as fixed effects regression models but what they actually do is a long way from a fixed effects model traditionally used by economists to control for area-specific unobserved e...
Show MoreThere can be no doubt that constraints on healthcare spending has an adverse effect upon mortality.
Show MoreIf we analyse several key areas required for the safe and effective functioning of a hospital then it is clear to see that the reduction in real term funding has had a multifactorial effect upon some of the following:
• Staffing: There are now record numbers of rota gaps. Shortages of doctors across all medical specialties is the norm. Trusts are routinely staffing rota gaps with internal locums or leaving posts vacant, resulting in certain services being dangerously understaffed or closing down. Rota gaps save trusts thousands of pounds, relying on the goodwill of the remaining staff to fill the void.
• Equipment: Essential equipment is frequently defective, out of date or unsafe. Operating theatres have to contend with instruments that are ill maintained (owing to outsourcing) leading to increased operating time and putting lives at risk.
• Medications: Health care authorities are rationing oncological medications despite NICE guidelines. We have a post code lottery for cancer and reproductive services.
• Buildings and maintenance: Hospitals are ill maintained. Heating and ventilation failures are common in theatre. Money spent on PFI repayments could be used for building maintenance.
• Study budgets: Cuts in study budgets have a negative impact upon training and education. Maintaining up to date skills is essential. Cutting study budget...
A very nice study with focused vision for future. Read it and appreciate with acknowledgement to bring this entire study to us. Would like to highlight a follow up of the said subjects as per their genetic makeup in this era of personalised medicine. Hypoxia and level of venous hypoxia as a key factor is missing to be aligned with calories intake and other factors which will define change the entire scope of study beside its implementation. The genes associated with obesity and involved in energy hemostasis must be considered at least as per study performed.
This study appears to be flawed. This is due to the fact that although spending may have gone down, the number of nurses and care workers may have gone up. The rate of care may also have increased within a year that had less spending, factors which do not appear to have been addressed.
The government ONS also predicted in 2004 that due to the ageing population and steadily declining mortality rate, this would lead to an increase, expected to start within 2010/2011.
http://webarchive.nationalarchives.gov.uk/20160108034023/http://www.ons....
Change in population also doesn't appear to have been taken into consideration as well as reasons for death.
The increase in mortality since 2011 has been an intriguing area of inquiry. I have already published several papers on this topic which suggest that social care spending is not the major contributory factor [1-18]. Several other papers are in press [19-24]. The issues raised in these papers have sadly been missed in this study. It would appear that further research is required on this important topic to disentangle cause and effect.
References
1. Jones R (2014) Infectious-like Spread of an Agent Leading to Increased Medical Admissions and Deaths in Wigan (England), during 2011 and 2012. British Journal of Medicine and Medical Research 4(28): 4723-4741. doi: 10.9734/BJMMR/2014/10807
Show More2. Jones R, Beauchant S (2015) Spread of a new type of infectious condition across Berkshire in England between June 2011 and March 2013: Effect on medical emergency admissions. British Journal of Medicine and Medical Research 6(1): 126-148. doi: 10.9734/BJMMR/2015/14223
3. Jones R (2015) Unexpected and Disruptive Changes in Admissions Associated with an Infectious-like Event Experienced at a Hospital in Berkshire, England around May of 2012. British Journal of Medicine and Medical Research 6(1): 56-76. doi: 10.9734/BJMMR/2015/13938
4. Jones R (2015) A previously uncharacterized infectious-like event leading to spatial spread of deaths across England and Wales: Characteristics of the most recent event and a time series for past events. Brit J Medicine and...
Dear Editor,
In the recent article by Myers, et al., the authors stated that Emergency Medicine (EM) was not a recognized specialty in Kenya, which was highlighted as a key step for the development of acute care in Kenya. During the review process for publication of this paper, the Kenya Medical Practitioners and Dentists Board (KMPDB) formally recognized EM as a new “medical specialty” in May 2017.(1) The paper also highlights the volume and diversity of patient presentations to Kenyatta National Hospital, the national referral hospital. The majority of patient complaints were either undifferentiated, or were due to trauma and non-communicable diseases. These high acuity, multi-disciplinary patients represent a case mix that an EM residency– trained practitioner is ideally suited to manage. Although Kenya currently lacks EM residency training programs, the recognition of the specialty is a step forward for the development of EM care in Kenya.
(1)Gazetted Specialties [Internet]. Kenya Medical Practitioners and Dentists Board. 2017. Available from: http://medicalboard.co.ke/resources_page/gazetted-specialties/
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