1. Introduction
The origin of quality of life and cost-effectiveness analyses can be traced back to a study on chronic renal disease published in 1968 [
1], leading to quality-adjusted life years or QALYs being formally defined in 1976 as the output of a utility function ([
2], c.f.
Acknowledgements). This concept gained gradual acceptance over the next three decades for the economic evaluation of healthcare programmes [
3], using metrics such as the incremental cost-effectiveness ratio developed at York [
4], and the disability-adjusted life year (DALY) introduced in 1994 as a related term with age-weighting and discounting [
3,
5].
Disability-adjusted life year (DALY), the loss of equivalent of one year of full health, is a time-based measure which allows the burden of different diseases to be compared objectively [
6]. DALY is a combination of years of life lost due to mortality (YLL), and years of healthy life lost due to disability or living in less than full health (YLD). DALY and DALY rate per 100,000 people in a given region can provide valuable insights to health service providers, public health departments, health economists and policy makers if data is available to compare that region (for example, Grampian in Scotland) with others and the national average – as shown in this communication. Authentic and curated sources of such data in the United Kingdom include the Fingertips for England [
7], the Scottish Burden of Disease [
8], etc.
2. Methods
For this work, we have used the Scottish burden of disease [8, c.f. eight references therein], a population health surveillance system which monitors how diseases, injuries and risk factors prevent the Scottish population from living longer lives in better health. The underlying raw Scottish burden of disease data used by this communication is available as Supplementary Material S1.
3. Results and Discussions
Burden of disease expressed as DALY rate per 100,000 population was calculated for Scotland versus Grampian for the latest year for which data is available (2019), separately for females (
Table 1 and
Table 2) and males (
Table 3 and
Table 4).
It is seen from
Table 1 and
Table 3 that by and large the top 25 diseases for Grampian are also important for Scotland, however their exact order may vary. Ischaemic heart disease, lung cancer, Alzheimer's disease and other dementias significantly affect both Grampian and Scotland (c.f.
Figure 1), so it is important to focus on these national priorities.
We are able to identify those diseases where Grampian’s DALY rate exceeds the Scottish average as local priorities for the region. These include atrial fibrillation and flutter, diabetes and oesophageal cancer for males; breast cancer, cerebrovascular disease, and other cardiovascular and circulatory diseases for females; colorectal cancer and drug use disorders affecting both sexes with worsening trends since 2016 (c.f.
Table 1 and
Table 3).
Table 2 and
Table 4 identify the age groups for these diseases of concern where the burden is especially high. It is important to address these unmet needs through a combination of public health measures (e.g. health promotion, disease prevention) and interventions arising from life sciences, health and medical research and innovation.
The latter is very important as demonstrated by recent reviews of Australia’s hugely important Medical Research Future Fund [
9,
10], in which it was found that 231 grants were awarded during 2016-19 with a total value of AU
$ 574.5 million [
10], but when mapped against 17 disease groups in the Australian burden of disease study 2015 [
11], only a weak association was observed with DALY (
r2 = 0.4359) and no association was observed with disability burden YLD (
r2 = 0.0009) [
10]. Any life sciences, health and medical research and innovation investments into Grampian by public, private or non-profit sectors should take these considerations into account. Realistic medicine approaches [
12] and regional investments should target the local burden of diseases, lest there could be higher opportunity costs and unintentional widening of inequalities. For the Grampian region, disease priorities are summarized under the mnemonic “CICADAS” (
Table 5), with the worst-affected age groups identified from
Table 2 and
Table 4.
As shown in
Figure 1, the Grampian region is in turn comprised of three Health & Social Care Partnerships (viz. Aberdeen City, Aberdeenshire and Moray), so it will be instructive to see if there are any sub-regional variations that these partnerships should be made aware of. From
Table 6, it is seen that Aberdeenshire is close to the Grampian average for diseases in females listed under
Table 2 (except perhaps breast cancer); Aberdeen City has higher DALY rate than Grampian for Alzheimer’s disease and other dementias, lung and colorectal cancers and drug use disorders; while Aberdeenshire has higher DALY rate than Grampian for ischaemic heart disease, cerebrovascular disease and other cardiovascular and circulatory diseases.
From
Table 7, it is seen that Aberdeenshire is again tracking the Grampian average for diseases in males listed under
Table 4 (except perhaps colorectal cancer, atrial fibrillation and flutter); Moray has higher DALY rate than Grampian for lung cancer, atrial fibrillation and flutter; while Aberdeen has higher DALY rate than Grampian for all but atrial fibrillation and flutter. Thus we notice that while some trends are the same for both sexes, there are significant differences too, so we need a nuanced approach.
4. Conclusions, limitation and future work
With health services under increasing pressure across the world, it is important to ensure better alignment between the long-term plans for population health, integrated health and social care. In many developed countries, we have health surveillance data on the public domain. These, especially on burden of diseases, can be mined and analysed by health service providers to serve their populations more effectively and in a targeted manner, as shown in this communication with the Grampian region case study. For example, we were able to identify which diseases have the highest DALY rate burden, which ones are of particular concern to Grampian, and those that are showing a worsening trend. We were also able to gain a nuanced understanding in terms of differences between males and females, age groups, and the three sub-regions that make up Grampian. This will allow targeted medical research investments and coordinated response from public health and health service delivery. The public domain Scottish burden of disease data ends at 2019, and we acknowledge this limitation. However, this communication does provide a useful pre-pandemic baseline for future comparisons, and our methodology and case study will still be very useful across the UK and internationally. We also demonstrate the importance of up-to-date surveillance data being available to health service providers, as well as the need for predictive trends and evidence on the impact of interventions, and it is heartening to note that such forecasting could soon be made available “
to offer insights into future public health challenges in Scotland” [
8].
Supplementary Materials
The following supporting information can be downloaded at the website of this paper posted on Preprints.org, Table S1: Scottish burden of disease underlying dataset.
Author Contributions
Conceptualization, S.S.V. and N.F.; methodology, S.S.V.; software, S.S.V.; validation, S.S.V.; formal analysis, S.S.V.; investigation, S.S.V.; resources, N.F.; data curation, S.S.V.; writing—original draft preparation, S.S.V.; writing—review and editing, S.S.V. and N.F.; visualization, S.S.V.; supervision, N.F.; project administration, S.S.V.; funding acquisition, N.F. Both authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data supporting reported results can be downloaded from the Scottish burden of disease [
8] or Supplementary Material.
Acknowledgments
S.S.V. is grateful for discussions with his past collaborator and co-author Professor Donald S. Shepard of Brandeis University (see for instance [13] and [14]) on QALYs versus DALYs. Donald preferred the term QALY to quality-adjusted citizen years as the latter acronym was felt to be quacky and fowl usage. The authors thank their colleague Professor Shantini Paranjothy for her comments.
Conflicts of Interest
The authors declare no conflict of interest.
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