Do Reduced Hospital Mortality Rates Lead to Increased Utilization of Inpatient Emergency Care? A Population‐Based Cohort Study

Laudicella, Mauro; Martin, Stephen; Donni, Paolo Li; Smith, Peter

doi:10.1111/1475-6773.12755

Cited by 9 publications

(6 citation statements)

References 34 publications

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“…We found evidence that delaying TTD can explain one quarter of the increment in HCE 3 years after the onset of the initial health shock, while the remaining part can be attributed to an increment in intensity of resource use. The former can be considered a "side effect" of the success of the health system in improving quality of care and reducing mortality rates as shown in this study and elsewhere (Laudicella, Martin, et al, 2018). Although we cannot exclude that the variation in the probability of surviving over time is also affected by other processes, such as increasing longevity due to the slowing down of the process of aging, the latter is likely to play a minor role due to the relatively short interval of time and the specific population examined in this study.…”

Section: Discussionmentioning

confidence: 75%

“…In contrast, HCE might increase if additional life years attracts morbidities and disabilities. Such a scenario might arise when additional life years are gained through new medical technologies and practices that are capable of saving the life of patients, but unable to grant them a full recovery from disease leaving them permanently frailer after the intervention (Gruenberg, 2005; Laudicella et al., 2013; Laudicella, Martin, et al., 2018). In this study, we provide evidence on the impact of delaying TTD that stems from the latter source.…”

Section: Introductionmentioning

confidence: 99%

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Age, morbidity, or something else? A residual approach using microdata to measure the impact of technological progress on health care expenditure

et al. 2022

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High-income countries are experiencing a rapid growth of health care expenditure (HCE) that seems to outpace demographic growth and aging of their population jeopardizing the fiscal sustainability of their health systems (OECD, 2006(OECD, , 2015. The first objective of this study is to measure the effect of non-demographic and non-health related drivers, such as technological progress and change in medical practice, on the increment of HCE over time.

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Section: Discussionmentioning

confidence: 75%

Section: Introductionmentioning

confidence: 99%

Age, morbidity, or something else? A residual approach using microdata to measure the impact of technological progress on health care expenditure

et al. 2022

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“…39 Increased survivorship means more people can expect to live longer in poor health, creating additional demand for health care. 40 The burden of disease (morbidity), as measured by the total number of years lived in disability (YLDs), increased 19% between 2000 and 2017, from around 6.5 million to 7.8 million. 41 The age-standardised rate of morbidity increased by 2.4% over the same period, meaning the burden of morbidity is mainly driven by a larger group of people reaching old age.…”

Section: Demand Has Risen Continuallymentioning

confidence: 99%

The bigger picture

Tallack¹,

Charlesworth²,

Kelly³

et al. 2020

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An understanding of the past helps us to prepare for the future. In this, the REAL Centre's first report, we look back at the care and treatment provided by the NHS in England over the past two decades-as measured by health care activity. Measures of activity-what the NHS does-form the basis of much NHS planning. Together with measures of quality, these are used as proxies for understanding the contribution the NHS makes to population health. Understanding the drivers of this activity is therefore crucial to service and resource planning. In this report, we provide a framework for understanding the drivers of health care activity. We describe how supply and demand side factors interact, and how policy can influence the care the NHS provides. We look at the overall trends in activity and how specific services have changed. Where possible, we estimate the proportion of any change that can be explained by four demographic factors: population size, age, gender, and proximity to death. We then explore what drives the remaining change, unexplained by demography. Although we focus on England, many of the lessons may be relevant to the other countries of the UK. We take an in-depth look at emergency and planned hospital care, mental health, community and primary care, but do not look in detail at areas such as high cost drugs or highly specialised services. Social care, too, is beyond the scope of this initial report but will be the focus of subsequent analysis by the REAL Centre. * This is cost-weighted. See section 3 for further detail. The bigger picture: learning from two decades of changing NHS care in England seen between services, combined with changes to the cost of different activities, have produced a major shift in the composition of spend towards hospital-based care and away from other areas. The expansion in activity means the population receives significantly more health care today, which has contributed to lower mortality rates for a range of conditions and, up until 2010, increasing life expectancy. However, improvements and increases in care have not been uniform over the past two decades. Between 2000/01 and 2010/11 activity rose by 5.3% a year, quality of care improved, and life expectancy grew by nearly 3 months a year for women and almost 4 months a year for men. As funding slowed after 2010 so too did activity. Between 2010/11 and 2017/18 activity grew by 3.6% a year, quality gains slowed and life expectancy has stalled overall and for some groups declined (notably for women younger than 50 in deprived areas). But it is not just life expectancy that has changed. Over the past two decades the amount of life spent living with long-term health conditions has increased and more people are living for prolonged periods with multiple long-term health problems. New technologies, changes in prices, and the increasing availability of information about treatments have increased clinician and public expectations about what the NHS can and should provide. Medical advances have meant more treatments can be provid...

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“…Overcrowding in the ED has been linked with increased inpatient death, increased waiting times, and increased expenditures for admitted patients [ 8 , 9 , 10 , 11 ]. ED wait times and leave-without-treatment (times where patients arrive to the ED but leave prior to getting a medical assessment) are signs of overcrowding.…”

Section: Introductionmentioning

confidence: 99%

E-Triage Systems for COVID-19 Outbreak: Review and Recommendations

Alhaidari

Almuhaideb

Alsunaidi

et al. 2021

Sensors

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With population growth and aging, the emergence of new diseases and immunodeficiency, the demand for emergency departments (EDs) increases, making overcrowding in these departments a global problem. Due to the disease severity and transmission rate of COVID-19, it is necessary to provide an accurate and automated triage system to classify and isolate the suspected cases. Different triage methods for COVID-19 patients have been proposed as disease symptoms vary by country. Still, several problems with triage systems remain unresolved, most notably overcrowding in EDs, lengthy waiting times and difficulty adjusting static triage systems when the nature and symptoms of a disease changes. In this paper, we conduct a comprehensive review of general ED triage systems as well as COVID-19 triage systems. We identified important parameters that we recommend considering when designing an e-Triage (electronic triage) system for EDs, namely waiting time, simplicity, reliability, validity, scalability, and adaptability. Moreover, the study proposes a scoring-based e-Triage system for COVID-19 along with several recommended solutions to enhance the overall outcome of e-Triage systems during the outbreak. The recommended solutions aim to reduce overcrowding and overheads in EDs by remotely assessing patients’ conditions and identifying their severity levels.

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Do Reduced Hospital Mortality Rates Lead to Increased Utilization of Inpatient Emergency Care? A Population‐Based Cohort Study

Abstract: The success of hospitals in improving survival from unplanned admissions can be an important contributory factor to the increase in subsequent admissions.

Cited by 9 publications

References 34 publications

Age, morbidity, or something else? A residual approach using microdata to measure the impact of technological progress on health care expenditure

Age, morbidity, or something else? A residual approach using microdata to measure the impact of technological progress on health care expenditure

The bigger picture

E-Triage Systems for COVID-19 Outbreak: Review and Recommendations

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