Cost-of-Illness Studies

Abstract

The number of cost-of-illness (COI) studies has expanded considerably over time. One outcome of this growth is that the reported COI estimates are inconsistent across studies, thereby raising concerns over the validity of the estimates and methods. Several factors have been identified in the literature as reasons for the observed variation in COI estimates. To date, the variation in the methods used to calculate costs has not been examined in great detail even though the variations in methods are a major driver of variation in COI estimates. The objective of this review was to document the variation in the methodologies employed in COI studies and to highlight the benefits and limitations of these methods. The review of COI studies was implemented following a four-step procedure: (i) a structured literature search of MEDLINE, JSTOR and EconLit; (ii) a review of abstracts using pre-defined inclusion and exclusion criteria; (iii) a full-text review using pre-defined inclusion and exclusion criteria; and (iv) classification of articles according to the methods used to calculate costs. This review identified four COI estimation methods (Sum_All Medical, Sum_Diagnosis Specific, Matched Control and Regression) that were used in categorising articles. Also, six components of direct medical costs and five components of indirect/non-medical costs were identified and used in categorising articles.365 full-length articles were reflected in the current review following the structured literature search. The top five cost components were emergency room/inpatient hospital costs, outpatient physician costs, drug costs, productivity losses and laboratory costs. The dominant method, Sum_Diagnosis Specific, was a total costing approach that restricted the summation of medical expenditures to those related to a diagnosis of the disease of interest. There was considerable variation in the methods used within disease subcategories. In several disease subcategories (e.g. asthma, dementia, diabetes mellitus), all four estimation methods were represented, and in other cases (e.g. HIV/AIDS, obesity, stroke, urinary incontinence, schizophrenia), three of the four estimation methods were represented. There was also evidence to suggest that the strengths and weaknesses of each method were considered when applying a method to a specific illness. Comparisons and assessments of COI estimates should consider the method used to estimate costs both as an important source of variation in the reported COI estimates and as a marker of the reliability of the COI estimate.

Epidemiology and cost of hospital care for Lyme borreliosis in Germany: Lessons from a health care utilization database analysis

“…In the absence of any clinical information, the completeness and accuracy of documentation and coding is crucial (Farhan et al, 2005). Reliability of such billing data has to be considered and the results as presented here share the general strengths and limitations of similar secondary data analyses (Schlomer and Copp, 2014;Hoffmann et al, 2008) and cost-ofillness-studies (Akobundu et al, 2006). However, the validity of inpatient data is generally considered higher than that of conventional outpatient data (Grobe, 2008) and despite some limitations, the analysis of claims data remains a very valuable tool to study routine clinical care at the population level.…”

Estimates of costs for modelling return on investment from smoking cessation interventions

“…One advantage of the current study has been to identify this methodological heterogeneity between the sources of cost data. It is not uncommon to estimate cost‐of‐illness using different approaches 86, but it is only when applying a standardized checklist that one could identify what causes the variation. The wage rates as well as the intensity of support were the cost drivers for the behavioural interventions.…”

Health technology assessment of hyperphosphatemia management among hemodialysis patients in Lebanon

“…Another limitation of this review is the adopted cost-effectiveness threshold of US$50,000-a conveniently cited value in the USA [20]. Cost-effectiveness thresholds are influenced by healthcare resources, reimbursement mechanisms, cultural and social factors, and thus differ between countries [53]; however, due to the heterogeneity in results, changing the threshold would not have affected our conclusion.…”

“…Also, the wide variation of cost estimates raises serious questions regarding the accuracy and validity of COI studies, consequently hindering their use in healthcare decision making [47,48]. For COI studies to be more robust and useful, closer agreement among researchers and strict adherence to available recommendations around "best practices" is a worthy first step [37,[49][50][51][52][53] while waiting for guidelines on the methodology and reporting of COI studies to be published [54]. These awaited guidelines, coupled with improvement in data availability and quality, may enhance the credibility and validity of COI studies and increase their use by policy makers [48,54].…”

“…It is essential, however, to acknowledge the limitations of using COI studies in public health policy making [53]. While these studies can present a useful opportunity for communicating with the public and policy makers on the relative importance of an illness, and can foster policy debate and stimulate research and policy initiatives aiming at more cost-effective treatment and prevention of illness, without other information they cannot guide decisions on the allocation of scarce health resources [36].…”