scholarly journals COVID-19 – exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study

2021 ◽  
Vol 5 ◽  
pp. 75
Author(s):  
Peter Hanlon ◽  
Fergus Chadwick ◽  
Anoop Shah ◽  
Rachael Wood ◽  
Jon Minton ◽  
...  
Keyword(s):  
Care Home ◽  
Life Tables ◽  
Years Of Life Lost ◽  
Limited Data ◽  
Long Term Conditions ◽  
Healthcare Data ◽  
Estimate Life Expectancy ◽  
Before And After ◽  
Wide Variability

Background: COVID-19 is responsible for increasing deaths globally. As most people dying with COVID-19 are older with underlying long-term conditions (LTCs), some speculate that YLL are low. We aim to estimate YLL attributable to COVID-19, before and after adjustment for number/type of LTCs, using the limited data available early in the pandemic. Methods: We first estimated YLL from COVID-19 using WHO life tables, based on published age/sex data from COVID-19 deaths in Italy. We then used aggregate data on number/type of LTCs in a Bayesian model to estimate likely combinations of LTCs among people dying with COVID-19. We used routine UK healthcare data from Scotland and Wales to estimate life expectancy based on age/sex/these combinations of LTCs using Gompertz models from which we then estimate YLL. Results: Using the standard WHO life tables, YLL per COVID-19 death was 14 for men and 12 for women. After adjustment for number and type of LTCs, the mean YLL was slightly lower, but remained high (11.6 and 9.4 years for men and women, respectively). The number and type of LTCs led to wide variability in the estimated YLL at a given age (e.g. at ≥80 years, YLL was >10 years for people with 0 LTCs, and <3 years for people with ≥6). Conclusions: Deaths from COVID-19 represent a substantial burden in terms of per-person YLL, more than a decade, even after adjusting for the typical number and type of LTCs found in people dying of COVID-19. The extent of multimorbidity heavily influences the estimated YLL at a given age. More comprehensive and standardised collection of data (including LTC type, severity, and potential confounders such as socioeconomic-deprivation and care-home status) is needed to optimise YLL estimates for specific populations, and to understand the global burden of COVID-19, and guide policy-making and interventions.

scholarly journals COVID-19 – exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study

2020 ◽  
Vol 5 ◽  
pp. 75 ◽  
Author(s):  
Peter Hanlon ◽  
Fergus Chadwick ◽  
Anoop Shah ◽  
Rachael Wood ◽  
Jon Minton ◽  
...  
Keyword(s):  
Policy Making ◽  
Life Tables ◽  
Years Of Life Lost ◽  
Long Term Conditions ◽  
Healthcare Data ◽  
Estimate Life Expectancy ◽  
Before And After ◽  
Wide Variability ◽  
The Mean

Background: The COVID-19 pandemic is responsible for increasing deaths globally. Most estimates have focused on numbers of deaths, with little direct quantification of years of life lost (YLL) through COVID-19.  As most people dying with COVID-19 are older with underlying long-term conditions (LTCs), some have speculated that YLL are low. We aim to estimate YLL attributable to COVID-19, before and after adjustment for number/type of LTCs. Methods: We first estimated YLL from COVID-19 using standard WHO life tables, based on published age/sex data from COVID-19 deaths in Italy. We then used aggregate data on number/type of LTCs to model likely combinations of LTCs among people dying with COVID-19. From these, we used routine UK healthcare data to estimate life expectancy based on age/sex/different combinations of LTCs. We then calculated YLL based on age, sex and type of LTCs and multimorbidity count. Results: Using the standard WHO life tables, YLL per COVID-19 death was 14 for men and 12 for women. After adjustment for number and type of LTCs, the mean YLL was slightly lower, but remained high (13 and 11 years for men and women, respectively). The number and type of LTCs led to wide variability in the estimated YLL at a given age (e.g. at ≥80 years, YLL was >10 years for people with 0 LTCs, and <3 years for people with ≥6). Conclusions: Deaths from COVID-19 represent a substantial burden in terms of per-person YLL, more than a decade, even after adjusting for the typical number and type of LTCs found in people dying of COVID-19. The extent of multimorbidity heavily influences the estimated YLL at a given age. More comprehensive and standardised collection of data on LTCs is needed to better understand and quantify the global burden of COVID-19 and to guide policy-making and interventions.

scholarly journals COVID-19 – exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study

2021 ◽  
Vol 5 ◽  
pp. 75
Author(s):  
Peter Hanlon ◽  
Fergus Chadwick ◽  
Anoop Shah ◽  
Rachael Wood ◽  
Jon Minton ◽  
...  
Keyword(s):  
Life Tables ◽  
Years Of Life Lost ◽  
Long Term Conditions ◽  
Healthcare Data ◽  
Estimate Life Expectancy ◽  
Sex Type ◽  
Before And After ◽  
Wide Variability ◽  
The Mean

Background: COVID-19 is responsible for increasing deaths globally. Estimates focused on numbers of deaths, do not quantify potential years of life lost (YLL) through COVID-19.  As most people dying with COVID-19 are older with underlying long-term conditions (LTCs), some speculate that YLL are low. We aim to estimate YLL attributable to COVID-19, before and after adjustment for number/type of LTCs. Methods: We first estimated YLL from COVID-19 using WHO life tables, based on published age/sex data from COVID-19 deaths in Italy. We then used aggregate data on number/type of LTCs inform a Bayesian model for likely combinations of LTCs among people dying with COVID-19. From these, we used routine UK healthcare data from Scotland and Wales to estimate life expectancy based on age/sex/ combinations of LTCs using Gompertz models. We then calculated YLL based on age, sex, type of LTCs and multimorbidity count. Results: Using the standard WHO life tables, YLL per COVID-19 death was 14 for men and 12 for women. After adjustment for number and type of LTCs, the mean YLL was slightly lower, but remained high (11.6 and 9.4 years for man and women, respectively). The number and type of LTCs led to wide variability in the estimated YLL at a given age (e.g. at ≥80 years, YLL was >10 years for people with 0 LTCs, and <3 years for people with ≥6). Conclusions: Deaths from COVID-19 represent a substantial burden in terms of per-person YLL, more than a decade, even after adjusting for the typical number and type of LTCs found in people dying of COVID-19. The extent of multimorbidity heavily influences the estimated YLL at a given age. More comprehensive and standardised collection of data on LTCs is needed to better understand and quantify the global burden of COVID-19 and to guide policy-making and interventions.

scholarly journals Different approaches to quantify years of life lost from COVID-19

2021 ◽  
Author(s):  
Tamás Ferenci
Keyword(s):  
Years Of Life Lost ◽  
Expected Number ◽  
Long Term Conditions ◽  
Developed Country ◽  
Individual Patient Level ◽  
Level Data ◽  
Parametric Survival Model ◽  
Epidemiologic Risk ◽  
Parametric Survival

AbstractThe burden of an epidemic is often characterized by death counts, but this can be misleading as it fails to acknowledge the age of the deceased patients. Years of life lost is therefore widely used as a more relevant metric, however, such calculations in the context of COVID-19 are all biased upwards: patients dying from COVID-19 are typically multimorbid, having far worse life expectation than the general population. These questions are quantitatively investigated using a unique Hungarian dataset that contains individual patient level data on comorbidities for all COVID-19 deaths in the country. To account for the comorbidities of the patients, a parametric survival model using 11 important long-term conditions was used to estimate a more realistic years of life lost. As of 12 May, 2021, Hungary reported a total of 27,837 deaths from COVID-19 in patients above 50 years of age. The usual calculation indicates 10.5 years of life lost for each death, which decreases to 9.2 years per death after adjusting for 11 comorbidities. The expected number of years lost implied by the life table, reflecting the mortality of a developed country just before the pandemic is 11.1 years. The years of life lost due to COVID-19 in Hungary is therefore 12% or 1.3 years per death lower when accounting for the comorbidities and is below its expected value, but how this should be interpreted is still a matter of debate. Further research is warranted on how to optimally integrate this information into epidemiologic risk assessments during a pandemic.

Extending the Comfort Zone: Building Resilience in Older People With Long-Term Conditions

2017 ◽  
Vol 38 (6) ◽  
pp. 825-848 ◽  
Author(s):  
Mark Robinson ◽  
Esmée Hanna ◽  
Gary Raine ◽  
Steve Robertson
Keyword(s):  
Older People ◽  
Peer Support ◽  
Social Engagement ◽  
Well Being ◽  
Significant Drop ◽  
Long Term Conditions ◽  
Before And After ◽  
And Gender ◽  
Ongoing Support

This article examines how a 6-week mental health resilience course for people with long-term conditions (LTCs; diabetes, heart disease, and arthritis) increased perceived resilience of older participants. This article examines how peer support assisted participants to develop resilience, considers gender issues, examines the importance of course activities, and explores how resilience enhances quality of life. A mixed methods approach was used. A before-and-after questionnaire was administered 3 times, including 3-month follow-up. Interviews were held with 24 program participants, aged 45 to 80 years. Diaries were kept by participants over 3 months. Survey findings showed significant gains in perceived resilience, at the end of the course, with no significant drop-off after 3 months. Interview and diary narratives highlighted positive experiences around well-being, condition management, and social engagement. Peer support was key to effective processes. Challenges concern ongoing support in communities, and considering age and gender variables when researching what improved resilience means to older people with LTCs.

scholarly journals Impact of a public policy restricting staff mobility between long-term care homes in Ontario, Canada during the COVID-19 pandemic

2020 ◽  
Author(s):  
Aaron Jones ◽  
Alexander G. Watts ◽  
Salah Uddin Khan ◽  
Jack Forsyth ◽  
Kevin A. Brown ◽  
...  
Keyword(s):  
Public Policy ◽  
Long Term Care ◽  
Care Home ◽  
Relative Difference ◽  
Care Staff ◽  
Care Homes ◽  
Term Care ◽  
Undirected Network ◽  
Before And After

AbstractObjectivesTo assess changes in the mobility of staff between long-term care homes in Ontario, Canada before and after enactment of public policy restricting staff from working at multiple homes.DesignPre-post observational study.Setting and Participants623 long-term cares homes in Ontario, Canada between March 2020 and June 2020.MethodsWe used anonymized mobile device location data to approximate connectivity between all 623 long-term care homes in Ontario during the 7 weeks before (March 1 – April 21) and after (April 22 – June 13) the policy restricting staff movement was implemented. We visualized connectivity between long-term care homes in Ontario using an undirected network and calculated the number of homes that had a connection with another long-term care home and the average number of connections per home in each period. We calculated the relative difference in these mobility metrics between the two time periods and compared within-home changes using McNemar’s test and the Wilcoxon rank-sum test.ResultsIn the period preceding restrictions, 266 (42.7%) long-term care homes had a connection with at least one other home, compared to 79 (12.7%) homes during the period after restrictions, a drop of 70.3% (p <0.001). The average number of connections in the before period was 3.90 compared to 0.77 in after period, a drop of 80.3% (p < 0.001). In both periods, mobility between long-term care homes was higher in homes located in larger communities, those with higher bed counts, and those part of a large chain.Conclusions and ImplicationsMobility between long-term care homes in Ontario fell sharply after an emergency order by the Ontario government limiting long-term care staff to a single home, though some mobility persisted. Reducing this residual mobility should be a focus of efforts to reduce risk within the long-term care sector during the COVID-19 pandemic.

scholarly journals Depression and ability to work after vestibular schwannoma surgery: a nationwide registry-based matched cohort study on antidepressants, sedatives, and sick leave

2021 ◽  
Author(s):  
Erik Thurin ◽  
Petter Förander ◽  
Jiri Bartek ◽  
Sasha Gulati ◽  
Isabelle Rydén ◽  
...  
Keyword(s):  
Sick Leave ◽  
Neurological Deficits ◽  
Tumor Control ◽  
Limited Data ◽  
Tumor Registry ◽  
Nationwide Registry ◽  
Before And After ◽  
Antidepressant Use ◽  
Sedative Drugs

Abstract Background In patients with vestibular schwannomas (VS), tumor control is often achieved, and life expectancy is relatively good. The main risks of surgical treatment are hearing loss and facial nerve function. The occurrence of mood and sleeping disorders in relation to surgery is an important aspect of health that has rarely been studied. Similarly, only limited data exist on the rate of sick leave for patients with VS. In this nationwide registry-based study, we define the use of antidepressants and sedatives and the sick leave pattern before and after VS surgery. Methods Adult patients with histopathologically verified VS were identified in the Swedish Brain Tumor Registry (SBTR) and clinical data were linked to relevant national registries after assigning five matched controls to each patient. We studied patterns of dispensed antidepressants and sedative drugs as well as patterns of sick leave compared to respective controls at 2 years before and 2 years following surgery. Results We identified 333 patients and 1662 matched controls. The rate of antidepressant use was similar between patients and controls 2 years before surgery (6.0% vs 6.3%) and 2 years after surgery (10.1% vs 7.5%). The rate of sedative use was also similar 2 years before surgery (3.9% vs 4.3%) and 2 years after surgery (4.8% vs 5.3%). The rate of sick leave was similar at baseline between patients and controls, but at 2 years after surgery, 75% of patients vs 88% of controls (p < 0.01) had no registered sick leave. Long-term sick leave after surgery was predicted by use of sedatives (OR 0.60, 95% CI 0.38–0.94, p = 0.03), more preoperative sick leave (OR 0.91, 95% CI 0.89–0.93, p < 0.001), and new-onset neurological deficits after surgery (OR 0.42, 95% CI 0.24–0.76, p = 0.004). Conclusion This nationwide study shows no significant differences in the use of antidepressants and sedatives between patients and controls, while the rate of postoperative sick leave was higher in patients than in controls after VS surgery. Our findings underpin the importance of avoiding surgical sequelae and facilitating return to normal professional life.

scholarly journals Estimation of age of transition from children's to adult healthcare for young people with long term conditions using linked routinely collected healthcare data

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Stuart William Jarvis ◽  
Gerry Richardson ◽  
Kate Flemming ◽  
Lorna Fraser
Keyword(s):  
Young People ◽  
Transition Point ◽  
Long Term Conditions ◽  
Transition Age ◽  
Healthcare Data ◽  
Misclassification Bias ◽  
Healthcare Transition ◽  
Reduce Risk ◽  
Nationally Representative

IntroductionHealthcare transitions, including from paediatric to adult services, can be disruptive and cause a lack of continuity in care. Existing research on the paediatric-adult healthcare transition often uses a simple age cut-off to assign transition status. This risks misclassification bias, reducing observed changes at transition (adults are included in the paediatric group and vice versa) possibly to differing extents between groups that transition at different ages. ObjectiveTo develop and assess methods for estimating the transition point from paediatric to adult healthcare from routine healthcare records. MethodsA retrospective cohort of young people (12 to 23 years) with long term conditions was constructed from linked primary and secondary care data in England. Inpatient and outpatient records were classified as paediatric or adult based on treatment and clinician specialities. Transition point was estimated using three methods based on record classification (First Adult: the date of first adult record; Last Paediatric: date of last paediatric record; Fitted: a date determined by statistical fitting). Estimated transition age was compared between methods. A simulation explored impacts of estimation approaches compared to a simple age cut-off when assessing associations between transition status and healthcare events. ResultsSimulations showed using an age-based cut-off at 16 or 18 years as transition point, common in research on transition, may underestimate transition-associated changes. Many health records for those aged 14 years were classified as adult, limiting utility of the First Adult approach. The Last Paediatric approach is least sensitive to this possible misclassification and may best reflect experience of the transition. ConclusionsEstimating transition point from routine healthcare data is possible and offers advantages over a simple age cut-off. These methods, adapted as necessary for data from other countries, should be used to reduce risk of misclassification bias in studies of transition in nationally representative data.

scholarly journals Effective behavior change in hand hygiene practices among boys residing at foster care home in Bengaluru city: An interventional study

2020 ◽  
Vol 0 ◽  
pp. 1-6
Author(s):  
Advaita Santhosh ◽  
V. Chaithra ◽  
B. Anuradha ◽  
Deepa Bullappa
Keyword(s):  
Foster Care ◽  
Hand Hygiene ◽  
Behavior Change ◽  
Care Home ◽  
Personal Hygiene ◽  
Post Intervention ◽  
Foster Home ◽  
Hygiene Practices ◽  
Before And After

Objective: Handwashing is the best defense against communicable infections due to lack of good personal hygiene practices. The objective of the study is to evaluate the change in knowledge and practice of hand hygiene among the children living in a foster care home of Bengaluru city. Material and Methods: A pre-tested, closed-ended, and structured questionnaire was administered in local language among 98 children, aged 8–16 years, residing in a foster home for boys in Bengaluru city to assess their knowledge and hand hygiene practices before and after a community-based intervention of handwashing technique which was done. Results: The present study showed a significant improvement in knowledge among majority of the children regarding hand hygiene before and after meals, usage of toilet post-intervention. About 96.9% of the children started practicing handwashing using handwash solution and water. Conclusion: Behavior change through communication campaigns improves safe hand hygiene practices on long term.

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