When the Cost Curve Bent — Pre-Recession Moderation in Health Care Spending

Roehrig, Charles; Turner, Ani; Hughes-Cromwick, Paul; Miller, George

doi:10.1056/nejmp1205958

Cited by 28 publications

(22 citation statements)

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“…7 In addition, health reform; changes in payment methodologies, such as the use of more global payments; and the transformation of the delivery system's organization could all have long-lasting effects. These trends, too, may cause the slowdown in spending growth to be more permanent.…”

Section: Resultsmentioning

confidence: 99%

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The Slowdown In Health Care Spending In 2009–11 Reflected Factors Other Than The Weak Economy And Thus May Persist

et al. 2013

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During and immediately after the recent recession, national health expenditures grew exceptionally slowly. During 2009-11 per capita national health spending grew about 3 percent annually, compared to an average of 5.9 percent annually during the previous ten years. Policy experts disagree about whether the slower health spending growth was temporary or represented a long-term shift. This study examined two factors that might account for the slowdown: job loss and benefit changes that shifted more costs to insured people. Based on an examination of data covering more than ten million enrollees with health care coverage from large firms in 2007-11, we found that these enrollees' out-of-pocket costs increased as the benefit design of their employer-provided coverage became less generous in this period. We conclude that such benefit design changes accounted for about one-fifth of the observed decrease in the rate of growth. However, we also observed a slowdown in spending growth even when we held benefit generosity constant, which suggests that other factors, such as a reduction in the rate of introduction of new technology, were also at work. Our findings suggest cautious optimism that the slowdown in the growth of health spending may persist-a change that, if borne out, could have a major impact on US health spending projections and fiscal challenges facing the country.

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Section: Resultsmentioning

confidence: 99%

“…3,6 In addition, a study conducted by Charles Roehrig and coauthors 7 found that the slowdown in spending growth began before the recession, supporting the notion of a more persistent change in spending growth that may remain even after the economy recovers.…”

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confidence: 96%

The Slowdown In Health Care Spending In 2009–11 Reflected Factors Other Than The Weak Economy And Thus May Persist

et al. 2013

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“…[2][3][4][5][6][7][8][9] Although cyclical (i.e., recessionrelated) factors could result in the observed income-related trends in health spending, the divergence in spending appears to pre-date the Great Recession by several years. 1 Some structural changes, including greater provider efficiency and fewer expensive "blockbuster" pharmaceuticals entering the market, would be expected to affect all income groups uniformly. Other structural changes -particularly increased cost-sharing for the privately insured -would be expected to have a greater impact on low-and middle-income people, consistent with our findings.…”

Section: Discussionmentioning

confidence: 99%

“…medical spending growth, which for decades has outpaced Gross Domestic Product growth, slowed starting in 2004. 1 Much discussion of the slowdown in health spending has focused on whether it is due primarily to structural or to cyclical factors, 2-9 XX23456789and prior studies have attributed 37% to 77% of the slowdown to the lingering effects of the Great Recession. 2,8,9 These estimates imply that between one fourth and two-thirds of the spending slowdown may be due to durable changes in the health care system, such as improved provider efficiency or less rapid diffusion of expensive medical technology and pharmaceuticals.…”

Section: Introduction Imentioning

confidence: 99%

Health Spending For Low-, Middle-, And High-Income Americans, 1963–2012

et al. 2016

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“…Secondary healthcare systems around the world are under increasing pressure ( [1,2] and specific working groups ( [20]); examples of such work include [21] and [22]. In this paper, we explore the use of electronic task-management for the study of OoH workload in secondary facilities.…”

Section: Introductionmentioning

confidence: 99%

Out of hours workload management: Bayesian inference for decision support in secondary care

Perez

Brown

Pinchin

et al. 2016

Artificial Intelligence in Medicine

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Objective: In this paper, we aim to evaluate the use of electronic technologies in Out of Hours (OoH) task-management for assisting the design of effective support systems in health care; targeting local facilities, wards or specific working groups. In addition, we seek to draw and validate conclusions with relevance to a frequently revised service, subject to increasing pressures.Methods and Material : We have analysed 4 years of digitised demand-data extracted from a recently deployed electronic task-management system, within the Hospital at Night setting in two jointly coordinated hospitals in the United Kingdom. The methodology employed relies on Bayesian inference methods and parameter-driven state-space models for multivariate series of count data.Results: Main results support claims relating to (i) the importance of datadriven staffing alternatives and (ii) demand forecasts serving as a basis to intelligent scheduling within working groups. We have displayed a split in workload patterns across groups of medical and surgical specialities, and sustained assertions regarding staff behaviour and work-need changes according to shifts or days of the week. Also, we have provided evidence regarding the relevance of day-to-day planning and prioritisation.Conclusions: The work exhibits potential contributions of electronic tasking alternatives for the purpose of data-driven support systems design; for scheduling, prioritisation and management of care delivery. Response to reviewersGeneral Comments: We are grateful to all reviewers for taking the time to review our paper and make a number of helpful comments that we believe have significantly improved the quality of the manuscript. All comments have been, according to their nature, merged, described and addressed here: 5Comment 1: The major concern shared by reviewers relates to a lack practical relevance of the results presented; for instance, managerial conclusions are not well exploited, the paper lacks a managerial perspective of the output from professionals involved in the study, or results do not extrapolate to different settings neither is it clear why they support the decision making. 10Response to Comment 1: The authors agree that the previous version of the manuscript offered a mostly descriptive study of the data and lacked relevant interpretations and conclusions drawn from results. In addition, we believe we were not successful in clearly conveying the aims and scope of our work; yet, we have made the efforts to undertake the alterations necessary in order to correct 15 these problems.Nationwide hospital settings are indeed subject to disparate workload pressures; these may drastically vary within distant geographical regions and in relation to specialities covered by each facility. The focus of our research team and this work relates to support systems for effective management that can 20 target local facilities and working groups. This is indeed a great problem, in that policy alterations and intelligent design of support systems (for instan...

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When the Cost Curve Bent — Pre-Recession Moderation in Health Care Spending

Cited by 28 publications

References 0 publications

The Slowdown In Health Care Spending In 2009–11 Reflected Factors Other Than The Weak Economy And Thus May Persist

The Slowdown In Health Care Spending In 2009–11 Reflected Factors Other Than The Weak Economy And Thus May Persist

Health Spending For Low-, Middle-, And High-Income Americans, 1963–2012

Out of hours workload management: Bayesian inference for decision support in secondary care

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