Cited by 767Health Systems, Economic Evaluations, Quality of LifeStatistical Methods and Bayesian InferenceStatistical Methods in Clinical Trials

Review of statistical methods for analysing healthcare resources and costs

Open access
Mihaylova, Borislava, Briggs, Andrew, O'Hagan, Anthony, Thompson, Simon G.·2011·Health Economics

Abstract

We review statistical methods for analysing healthcare resource use and costs, their ability to address skewness, excess zeros, multimodality and heavy right tails, and their ease for general use. We aim to provide guidance on analysing resource use and costs focusing on randomised trials, although methods often have wider applicability. Twelve broad categories of methods were identified: (I) methods based on the normal distribution, (II) methods following transformation of data, (III) single-distribution generalized linear models (GLMs), (IV) parametric models based on skewed distributions outside the GLM family, (V) models based on mixtures of parametric distributions, (VI) two (or multi)-part and Tobit models, (VII) survival methods, (VIII) non-parametric methods, (IX) methods based on truncation or trimming of data, (X) data components models, (XI) methods based on averaging across models, and (XII) Markov chain methods. Based on this review, our recommendations are that, first, simple methods are preferred in large samples where the near-normality of sample means is assured. Second, in somewhat smaller samples, relatively simple methods, able to deal with one or two of above data characteristics, may be preferable but checking sensitivity to assumptions is necessary. Finally, some more complex methods hold promise, but are relatively untried; their implementation requires substantial expertise and they are not currently recommended for wider applied work.

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  • Exponential weighting has previously been used in both medical and non-medical error/risk analysis.

    “exponential weighting has previously been used in both medical42–44 and non-medical45 46 error/risk analysis.”

    From Clinical AI Scribes in primary care: accuracy, error severity and implications for clinical practice (2025) · cites this paper as [43]

    Section 3.1 discusses exponential conditional mean models and variance weighting in analyses of healthcare costs, but neither passage describes exponential weighting in error or risk analysis. Searches for “exponential weighting” and “weighting error risk analysis” found no passage establishing the claimed prior use in medical or non-medical settings. (LLM, conf=0.74)

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Authors
Mihaylova, B., Briggs, A., O'Hagan, A., & Thompson, S. G.
Affiliations
  • University of Oxford (GB)
  • University of Glasgow (GB)
  • Department of Probability and Statistics, University of Sheffield, Sheffield, UK
  • MRC Biostatistics Unit (GB)
Corresponding author
Mihaylova, Borislava
Venue
Health Economics
Publisher
Wiley
Published
2010-08-27
Volume
20
Issue
8
Pages
897-916
ISSN
  • 1057-9230 (ISSN-L)
  • 1099-1050
OpenAlex
W2041616439
Cited by
767
References
99
Citations by year
2026: 35 · 2025: 47 · 2024: 51 · 2023: 48 · 2022: 79 · 2021: 85 · 2020: 77 · 2019: 67 · 2018: 58 · 2017: 47 · 2016: 41 · 2015: 39 · 2014: 30 · 2013: 26 · 2012: 23
FWCI
5.09
Type
journal article
Language
en
Open access
Locations
  • Health Economics (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (submittedVersion)
Funders
British Heart Foundation (RG/08/014/24067)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Keywords
health care utilization, health care costs, skewed data, excess zeros, multimodality, generalized linear models, mixture distributions, two-part model, Tobit model, survival analysis, non-parametric methods, data truncation, model averaging, Markov chain analysis, randomised trials, statistical method selection
MeSH terms
Data Interpretation, Statistical, Health Resources, Markov Chains, Linear Models, Randomized Controlled Trials as Topic, Health Care Costs

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