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- Published on: 21 January 2018
- Published on: 21 January 2018
- Published on: 24 November 2017
- Published on: 18 November 2017
- Published on: 17 November 2017
- Published on: 16 November 2017
- Published on: 16 November 2017
- Published on: 15 November 2017
- Published on: 21 January 2018The increases in population mortality observed in the past few years are more than just the result of an ageing population
Ramsay points out that the UK’s ageing population was predicted to lead to an increase or slower rate of decline in mortality rates. However, our findings suggest that the changes in mortality rate are robust to an ageing population. In Supplementary Table S4, we show that most of the age groups above 60+ have significantly higher-than-expected mortality rates in 2012, 2013, and 2014. In particular, the mortality rates for the 85+ age group is consistently higher than expected for all years. If population mortality rates were expected to spike mostly as the result of an increasing proportion of very old people, we would not see such big spikes within these older age groups.
Conflict of Interest:
None declared. - Published on: 21 January 2018The conclusion that changes in spending are significantly associated with mortality is robust to the source of standardisation for calculating mortality rates
As noted by Black, our use of the 1976 European standard population (ESP) reference instead of the 2013 ESP for age-standardising death rates (ASDR) is the source of the discrepancy between our ASDR and more recently published ONS ASDR.
We calculated ASDr de novo using raw mortality counts and population data since ASDR broken down by sex and specific to England (not England and Wales) were unavailable at the time of data collection and initial data processing (mid-2014). To do this, we used the 1976 ESP data since to our knowledge, the 2013 ESP data were not available at that time.
To demonstrate that the source of standardisation did not affect our conclusion, we re-processed the data using 2013 ESP data and re-ran the time-trend analyses. Despite this difference, we again found that the spending constraints of 2010/11 were linked with a significant increase in ASDR. Comparing the actual and predicted ASDR revealed 12,111 higher than expected number of deaths in 2012 (95% CI 4,912 to 19,309), 23,311 (95% CI 15,994 to 30,628) in 2013, and 20,351 (95% CI 12,865 to 27,838) in 2014 (see Figure 1: http://blogs.bmj.com/bmjopen/files/2018/01/BMJ-Open-Response-Figure-1.jpg). These numbers are all within the corresponding confidence intervals of the results using the 1976 ESP-standardised data.
Furthermore, it is worth noting that our findings that life expectancy was si...
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None declared. - Published on: 24 November 2017Issues with the underlying data
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...
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None declared. - Published on: 18 November 2017Health and social care spending and mortality
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....
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None declared. - Published on: 17 November 2017Strong claims based on questionable methods
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...
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None declared. - Published on: 16 November 2017Private finance initiative and sustainability and transformation partnerships are not working
There can be no doubt that constraints on healthcare spending has an adverse effect upon mortality.
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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...Conflict of Interest:
None declared. - Published on: 16 November 2017Comparing spending to mortality rates
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.
Conflict of Interest:
None declared. - Published on: 15 November 2017Social care spending and mortality
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
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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...Conflict of Interest:
None declared.