Hospitalizations for people with type 1 and type 2 diabetes compared with the nondiabetic population of Tayside, Scotland: a retrospective cohort study of resource use.

Donnan, Peter T.; Leese, Graham; Morris, Andrew D.; Audit, Diabetes

doi:10.2337/diacare.23.12.1774

Cited by 119 publications

(111 citation statements)

References 10 publications

(12 reference statements)

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“…The risks for hospitalization associated with type 2 diabetes were previously reported to be 50.7% in a 3-year followup of a Finnish population [1]; 27.1% per year in Tayside, Scotland [3]; and 31.5% in a 4-year follow-up of an English cohort [4]. Age, population characteristics, and the criteria for in-hospital admissions might account for the differences.…”

Section: Discussionmentioning

confidence: 91%

“…The rates of hospitalization of patients with diabetes mellitus have been reported to be higher than those of the general population [1][2][3][4], and the resources used for their inpatient care are estimated to be considerable [5][6][7]. The identification of risk factors for hospitalization of people with diabetes and the selection of subgroups of subjects who could be managed as outpatients might reduce health care costs [4].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Patients with type 2 diabetes had higher rates of hospitalization than the general population

Bo¹,

Ciccone²,

Grassi³

et al. 2004

Journal of Clinical Epidemiology

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Section: Discussionmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Patients with type 2 diabetes had higher rates of hospitalization than the general population

Bo¹,

Ciccone²,

Grassi³

et al. 2004

Journal of Clinical Epidemiology

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“…Several studies also indicate that diabetics are admitted to the hospital more frequently than are nondiabetics (47,48). Thus, it is not surprising that CHA rates are elevated in diabetic populations.…”

Section: Methodsmentioning

confidence: 99%

The importance of population susceptibility for air pollution risk assessment: a case study of power plants near Washington, DC.

Levy

Greco

Spengler

2002

Environ Health Perspect

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In evaluating risks from air pollution, health impact assessments often focus on the magnitude of the impacts without explicitly considering the distribution of impacts across subpopulations. In this study, we constructed a model to estimate the magnitude and distribution of health benefits associated with emission controls at five older power plants in the Washington, DC, area. We used the CALPUFF atmospheric dispersion model to determine the primary and secondary fine-particulate-matter (< 2.5 micro m in aerodynamic diameter) concentration reductions associated with the hypothetical application of "Best Available Control Technology" to the selected power plants. We combined these concentration reductions with concentration-response functions for mortality and selected morbidity outcomes, using a conventional approach as well as considering susceptible subpopulations. Incorporating susceptibility had a minimal effect on total benefits, with central estimates of approximately 240 fewer premature deaths, 60 fewer cardiovascular hospital admissions (CHA), and 160 fewer pediatric asthma emergency room visits (ERV) per year. However, because individuals with lower education appear to have both higher background mortality rates and higher relative risks for air-pollution-related mortality, stratifying by educational attainment implies that 51% of the mortality benefits accrue among the 25% of the population with less than high school education. Similarly, diabetics and African Americans bear disproportionate shares of the CHA and ERV benefits, respectively. Although our ability to characterize subpopulations is constrained by the available information, our analysis demonstrates that incorporation of susceptibility information significantly affects demographic and geographic patterns of health benefits and enhances our understanding of individuals likely to benefit from emission controls.

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“…Many studies have described the economic impact diabetes has on the health system and society (3)(4)(5)(6) and have compared the health care utilization of patients with and without diabetes (7)(8)(9)(10). Only a few studies have assessed the relationship between patient characteristics, complications, and costs using patientlevel data (11)(12)(13)(14)(15)(16) and most have examined the relationship for aggregated end points (12,13,15,16).…”

mentioning

confidence: 99%

The Direct Medical Cost of Type 2 Diabetes

et al. 2003

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OBJECTIVE -To describe the direct medical costs associated with type 2 diabetes, as well as its treatments, complications, and comorbidities.RESEARCH DESIGN AND METHODS -We studied a random sample of 1,364 subjects with type 2 diabetes who were members of a Michigan health maintenance organization. Demographic characteristics, duration of diabetes, diabetes treatments, glycemic control, complications, and comorbidities were assessed by surveys and medical chart reviews. Annual resource utilization and costs were assessed using health insurance claims. The log-transformed annual direct medical costs were fitted by multiple linear regression to indicator variables for demographics, treatments, glycemic control, complications, and comorbidities.RESULTS -The median annual direct medical costs for subjects with diet-controlled type 2 diabetes, BMI 30 kg/m 2 , and no microvascular, neuropathic, or cardiovascular complications were $1,700 for white men and $2,100 for white women. A 10-kg/m 2 increase in BMI, treatment with oral antidiabetic or antihypertensive agents, diabetic kidney disease, cerebrovascular disease, and peripheral vascular disease were each associated with 10 -30% increases in cost. Insulin treatment, angina, and MI were each associated with 60 -90% increases in cost. Dialysis was associated with an 11-fold increase in cost. T he worldwide prevalence of diabetes is increasing (1), as is the demand for and cost of medical care (2). Many studies have described the economic impact diabetes has on the health system and society (3-6) and have compared the health care utilization of patients with and without diabetes (7-10). Only a few studies have assessed the relationship between patient characteristics, complications, and costs using patientlevel data (11-16) and most have examined the relationship for aggregated end points (12,13,15,16). The purpose of this study was to describe the relationship between direct medical costs and individual demographic characteristics, treatments, glycemic control, complications, cardiovascular risk factors, and comorbidities in patients with type 2 diabetes. CONCLUSIONSPrevious models have assigned costs to specific diabetes-related health states (17)(18)(19)(20). This approach is most appropriate for acute health states where interactions with other conditions are absent or clearly identifiable and of limited duration (21). A complex chronic disease like diabetes impacts many other apparently unrelated health problems and the resources used in their treatment. Therefore, it is important to extend the scope of a cost model beyond the direct complications of diabetes to include total direct medical costs. Only in this way can the true economic burden of diabetes be assessed. RESEARCH DESIGN AND METHODS -The study was reviewed and approved by the University of Michigan Institutional Review Board. All subjects were enrolled in commercial, Medicare, or Medicaid managed care programs offered by a large Michigan health maintenance organization (HMO). Subjects thus represented ...

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Hospitalizations for people with type 1 and type 2 diabetes compared with the nondiabetic population of Tayside, Scotland: a retrospective cohort study of resource use.

Cited by 119 publications

References 10 publications

Patients with type 2 diabetes had higher rates of hospitalization than the general population

Patients with type 2 diabetes had higher rates of hospitalization than the general population

The importance of population susceptibility for air pollution risk assessment: a case study of power plants near Washington, DC.

The Direct Medical Cost of Type 2 Diabetes

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