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Cost-of-Illness Studies: An Updated Review of Current Methods

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Abstract

Introduction

Cost-of-illness (COI) studies provide policy-relevant information for cross-country, longitudinal, and other cost comparisons. Prior studies have called for standardization in COI methods. We investigated trends, identified factors associated with variation in COI estimation methods, and characterized reporting of heterogeneity in COI estimates.

Methods

The review of COI studies was implemented following (i) a structured search of PubMed, SCOPUS and EMBASE; (ii) a review of abstracts; (iii) a full-text review; and (iv) classification of articles according to six COI estimation methods: Sum_All Medical, Sum_Diagnosis Specific, Matched, Regression, Other_Total and Other_Incremental. Descriptive and multivariable regression analyses were conducted.

Results

Of the 993 studies included in the full-text review, 186 (18.7 %) were Sum_All Medical, 458 (46.1 %) were Sum_Diagnosis Specific, 96 (9.7 %) were Matched, 97 (9.8 %) were Regression, 70 (7.1 %) were Other_Incremental, and 68 (6.9 %) were Other_Total. Compared with the early period, publications in the middle and late period were associated with lower odds of using Sum_All Medical compared with Sum_Diagnosis Specific (adjusted odds ratio [AOR]middle 0.14; 95 % CI 0.07–0.28; AORlate 0.44; 95 % CI 0.29–0.67). Overall, 640 articles (64 %) reported COI estimates across patient groups defined by patient-level factors, while 247 articles (25 %) reported COI estimates across patient groups defined by non-patient-level factors.

Conclusion

The disease-specific total costing method (Sum_Diagnosis Specific) was most commonly used and its use increased over the time period covered by this review. The investigation of subgroup heterogeneity in COI estimates represents an area for future research.

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Acknowledgments

The authors wish to thank Sohani Patel, Amy Howard, Jacinda Tran, and Mercedes Wilkes for their assistance with the review of article abstracts and data cleaning. Any errors in the interpretation and reporting of the results are the sole responsibility of the authors.

Author contributions

The interpretation and reporting of these data are the sole responsibility of the authors. Eberechukwu Onukwugha contributed to the study design, data collection, conduct and interpretation of the statistical analysis, and drafted and revised the manuscript with input from all co-authors. Jacquelyn McRae contributed to the study design, data collection, interpretation of the analysis, and drafted, revised and commented on/edited all drafts of the manuscript. Alex Kravetz and Stefan Varga contributed to the data collection, interpretation of the analysis, and reviewed and commented on/edited all drafts of the manuscript. Rahul Khairnar contributed to the data collection, data cleaning, conduct and interpretation of the analysis, and reviewed and commented on/edited all drafts of the manuscript. Daniel Mullins contributed to the study design and interpretation of the analysis, and reviewed and commented on/edited all drafts of the manuscript.

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Authors and Affiliations

  1. Department of Pharmaceutical Health Services Research, School of Pharmacy, University of Maryland, 220 Arch Street, Baltimore, MD, 21201, USA

    Eberechukwu Onukwugha, Alex Kravetz, Rahul Khairnar & C. Daniel Mullins

  2. College of Pharmacy, Mercer University, Atlanta, GA, USA

    Jacquelyn McRae

  3. School of Pharmacy, Notre Dame of Maryland University, Baltimore, MD, USA

    Stefan Varga

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  1. Eberechukwu Onukwugha
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  2. Jacquelyn McRae
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  3. Alex Kravetz
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  5. Rahul Khairnar
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  6. C. Daniel Mullins
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Corresponding author

Correspondence to Eberechukwu Onukwugha.

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Funding

No funding was received for the conduct of this study.

Conflict of interest

Dr. Onukwugha has received consulting income from AstraZeneca and Janssen Analytics, and Dr. Mullins has received consulting income from Regeneron, Novartis, Daiichi-Sankyo, Bayer, Bristol-Myers Squibb, Mundi Pharma, and Pfizer. Jacquelyn McRae, Alex Kravetz, Stefan Varga, and Rahul Khairnar have no conflicts of interest to declare.

Appendix

Appendix

See Figs. 4 and 5 and Tables 5 and 6.

Fig. 4
figure 4

Distribution of reviewed abstracts based on the database source (N = 8299)

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Fig. 5
figure 5

Exclusion categories and associated article abstracts

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Table 5 Search strings utilized for the cost-of-illness review study
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Table 6 Original and assigned ICD10 groups
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Onukwugha, E., McRae, J., Kravetz, A. et al. Cost-of-Illness Studies: An Updated Review of Current Methods. PharmacoEconomics 34, 43–58 (2016). https://doi.org/10.1007/s40273-015-0325-4

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  • DOI: https://doi.org/10.1007/s40273-015-0325-4

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