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Meeting the Institute of Medicine's 2030 US Life Expectancy Target.

ABSTRACT: OBJECTIVES:To quantify the improvement in US life expectancy required to reach parity with high-resource nations by 2030, to document historical precedent of this rate, and to discuss the plausibility of achieving this rate in the United States. METHODS:We performed a demographic analysis of secondary data in 5-year periods from 1985 to 2015. RESULTS:To achieve the United Nations projected mortality estimates for Western Europe in 2030, the US life expectancy must grow at 0.32% a year between 2016 and 2030. This rate has precedent, even in low-mortality populations. Over 204 country-periods examined, nearly half exhibited life-expectancy growth greater than 0.32%. Of the 51 US states observed, 8.2% of state-periods demonstrated life-expectancy growth that exceeded the 0.32% target. CONCLUSIONS:Achieving necessary growth in life expectancy over the next 15 years despite historical precedent will be challenging. Much all-cause mortality is structured decades earlier and, at present, older-age mortality reductions in the United States are decelerating. Addressing mortality decline at all ages will require enhanced political will and a strong commitment to equity improvement in the US population.

SUBMITTER: Kindig D

PROVIDER: S-EPMC5719677 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Meeting the Institute of Medicine's 2030 US Life Expectancy Target.

Kindig David D Nobles Jenna J Zidan Moheb M

American journal of public health 20171121 1

<h4>Objectives</h4>To quantify the improvement in US life expectancy required to reach parity with high-resource nations by 2030, to document historical precedent of this rate, and to discuss the plausibility of achieving this rate in the United States.<h4>Methods</h4>We performed a demographic analysis of secondary data in 5-year periods from 1985 to 2015.<h4>Results</h4>To achieve the United Nations projected mortality estimates for Western Europe in 2030, the US life expectancy must grow at 0 ...[more]

PMID: 29161064

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Project description:In this paper, we propose to advance and transform today's healthcare system using a model of networked health care called Cybercare. Cybercare means "health care in cyberspace" - for example, doctors consulting with patients via videoconferencing across a distributed network; or patients receiving care locally - in neighborhoods, "minute clinics," and homes - using information technologies such as telemedicine, smartphones, and wearable sensors to link to tertiary medical specialists. This model contrasts with traditional health care, in which patients travel (often a great distance) to receive care from providers in a central hospital. The Cybercare model shifts health care provision from hospital to home; from specialist to generalist; and from treatment to prevention. Cybercare employs advanced technology to deliver services efficiently across the distributed network - for example, using telemedicine, wearable sensors and cell phones to link patients to specialists and upload their medical data in near-real time; using information technology (IT) to rapidly detect, track, and contain the spread of a global pandemic; or using cell phones to manage medical care in a disaster situation. Cybercare uses seven "pillars" of technology to provide medical care: genomics; telemedicine; robotics; simulation, including virtual and augmented reality; artificial intelligence (AI), including intelligent agents; the electronic medical record (EMR); and smartphones. All these technologies are evolving and blending. The technologies are integrated functionally because they underlie the Cybercare network, and/or form part of the care for patients using that distributed network. Moving health care provision to a networked, distributed model will save money, improve outcomes, facilitate access, improve security, increase patient and provider satisfaction, and may mitigate the international global burden of disease. In this paper we discuss how Cybercare is being implemented now, and envision its growth by 2030.

Project description:BackgroundFew studies have investigated the change in life expectancy (LE) and the healthy lifespan among patients with advanced schistosomiasis. This study was to evaluate the LE and healthy life expectancy (HLE) for patients and assess the mechanism responsible for the LE inequality.MethodsWe utilized data from a dynamic advanced schistosomiasis cohort (10,362 patients) for the period from January 2008 to December 2019 in Hunan Province, China, to calculate the LEs of patients, and made a comparison with that of general population (19,642 schistosomiasis-free individuals) in the schistosomiasis endemic areas. LEs were estimated from 15 years of age by constructing period life tables. Arriaga's decomposition method was applied to quantify the influence of the age structure on the difference in LE. HLE for advanced schistosomiasis patients was calculated by using Sullivan method with age-specific disability weight. The LE and HLE were calculated for both males and females to perform further analyses on gender gap.ResultsThe estimated LE for advanced schistosomiasis patients aged 15-19 was 49.51 years (48.86 years for males and 51.07 years for females), which was 20.14 years lower compared with general population (69.65 years), and the LE gap between patients and general population decreased with age. The largest age-specific mortality contribution to the gap (32.06%) occurred at age 80-84 years. Women had a lower LE and HLE than men at age ≥ 60 years (both gender gaps in LE and HLE < 0). For advanced schistosomiasis patients, the gender gap in LE was largely attributed to the difference in mortality among those under the age of 55; the age-specific mortality in women exerted positive influence on the gap at age 25-64 and 75-79 years, with the contribution rate ranging from 0.59% to 57.02%, and made the negative contribution at other age groups.ConclusionsThe LE of advanced schistosomiasis patients was still much lower compared with general population. Strengthened prevention strategies and targeted treatments are needed to reduce morbidity and mortality due to advanced schistosomiasis, especially for younger population and elderly female patients.

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Meeting the Institute of Medicine's 2030 US Life Expectancy Target.

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Meeting the Institute of Medicine's 2030 US Life Expectancy Target.

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