Modeling the Socioeconomic Impact of Osteoporosis-Related Hip Fractures in Switzerland

Sendi, Pedram; Palmer, Andrew J.

doi:10.1007/s001980050011

Cited by 8 publications

(5 citation statements)

References 17 publications

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“…While models are generally characterized by a reduction in complexity compared to reality, some simplifications in the present case were dictated by an anticipated lack of appropriate input data. For example, we relied on a set of Markov states that solely described fracture event history, in contrast to some osteoporosis models that incorporated functional status or type of residence at the disease state level [8,10,16]. Owing to a lack of detailed fracture incidence data that distinguished between persons without and with osteoporosis, modeling of fracture entries was not based on the absence or presence of the underlying disease [10].…”

Section: Discussionmentioning

confidence: 99%

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A model of osteoporosis impact in Switzerland 2000–2020

et al. 2004

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The aim of our study was to develop a modeling framework suitable to quantify the incidence, absolute number and economic impact of osteoporosis-attributable hip, vertebral and distal forearm fractures, with a particular focus on change over time, and with application to the situation in Switzerland from 2000 to 2020. A Markov process model was developed and analyzed by Monte Carlo simulation. A demographic scenario provided by the Swiss Federal Statistical Office and various Swiss and international data sources were used as model inputs. Demographic and epidemiologic input parameters were reproduced correctly, confirming the internal validity of the model. The proportion of the Swiss population aged 50 years or over will rise from 33.3% in 2000 to 41.3% in 2020. At the total population level, osteoporosis-attributable incidence will rise from 1.16 to 1.54 per 1,000 person-years in the case of hip fracture, from 3.28 to 4.18 per 1,000 person-years in the case of radiographic vertebral fracture, and from 0.59 to 0.70 per 1,000 person-years in the case of distal forearm fracture. Osteoporosis-attributable hip fracture numbers will rise from 8,375 to 11,353, vertebral fracture numbers will rise from 23,584 to 30,883, and distal forearm fracture numbers will rise from 4,209 to 5,186. Population-level osteoporosis-related direct medical inpatient costs per year will rise from 713.4 million Swiss francs (CHF) to CHF946.2 million. These figures correspond to 1.6% and 2.2% of Swiss health care expenditures in 2000. The modeling framework described can be applied to a wide variety of settings. It can be used to assess the impact of new prevention, diagnostic and treatment strategies. In Switzerland incidences of osteoporotic hip, vertebral and distal forearm fracture will rise by 33%, 27%, and 19%, respectively, between 2000 and 2020, if current prevention and treatment patterns are maintained. Corresponding absolute fracture numbers will rise by 36%, 31%, and 23%. Related direct medical inpatient costs are predicted to increase by 33%; however, this estimate is subject to uncertainty due to limited availability of input data.

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Section: Discussionmentioning

confidence: 99%

“…Forecasts of future fracture incidences and impact were based on these data and did not apply upto-date modeling techniques [14,15]. A Swiss Markov model, addressing the socioeconomic impact of hip fracture, has been published as a short report only [16]. A clear lack of planning data has been recognized by the health authorities.…”

Section: Introductionmentioning

confidence: 99%

A model of osteoporosis impact in Switzerland 2000–2020

et al. 2004

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“…In addition to numerous conventional pathways, there is evidence that socioeconomic discrepancy is an important contributor to disparities in disability at older ages (Engstrom et al 2002;Freedman 2011;Jang et al 2010;Turrell et al 2002). It is well known that lower socioeconomic status (SES) increases the incidence of some disabilityrelated diseases (Grundy and Holt 2001), such as cardiovascular disease (Mieczkowska and Mosiewicz 2008), musculoskeletal disease (Sendi and Palmer 2000), and comorbid conditions (Macleod, Mitchell, Black, and Spence 2004). Research also shows that the linear correlation between poverty and disability rates among U.S. older adults is 0.93 (Schoeni et al 2008) and that better financial resources may reduce disability by enabling individuals to purchase assistive technology, healthful foods, exercise equipment, safe homes in safe neighborhoods, and personal and medical care (Freedman 2011).…”

Section: (R)esourcesmentioning

confidence: 99%

Studying Disability Trends in Aging Populations

Gómez-Redondo

Dupre

2014

J Cross Cult Gerontol

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This article reviews the current literature on disability trends in aging populations and proposes a framework for studying disability trends built upon existing models of disablement. In addition to considering disablement and its associated factors, our framework also includes factors at population level and the interplays among personal resources and health behaviors, intervention programs, technological advances, and the consequences of disability trends in the context of life course and socio-ecological perspective. The framework is abbreviated FE-BRIT-SE to denote individual-level (F)ixed attributes, including genetic factors, personality, age, sex, and earlier life conditions, and the (E)nvironment; individual (B)ehaviors, (R)esources, (I)nterventions, (T)echnology; and (S)ocioeconomic and (E)cological consequences of disability trends. The overview offers an integrated framework for understanding the disablement process, trends and their complex milieu of causes and consequences.

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“…175 000 Krankenhaustage pro Jahr [3]. Die durchschnittlichen medizinischen Einzelkosten in der Schweiz einer einzigen Hüftfraktur werden auf Euro 39 000 bis Euro 49 000 geschätzt [29].…”

Section: Physiotherapy Interventions In Osteoporosisunclassified