The DOI matches its Crossref record; 82 of the 99 references it cites were found in a registry or an index.
Review of statistical methods for analysing healthcare resources and costs
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“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]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Regression Analysis of Count Data: Author Index
Cameron, A., & Trivedi, P. (1998) · Cambridge University Press eBooks · doi:10.1017/cbo9780511814365 · Cited by 6,406
Hilbe, J. M. (2011) · Cambridge University Press eBooks · doi:10.1017/cbo9780511973420 · Cited by 3,352
Smearing Estimate: A Nonparametric Retransformation Method
Duan, N.-H. (1983) · Journal of the American Statistical Association · doi:10.1080/01621459.1983.10478017 · Cited by 2,289 · cited 4×
“The four-part model in Duan (1983) (see Section 3.1.6) is also in essence a data components model.”
BackgroundMethodInfluentialEconometric models based on count data. Comparisons and applications of some estimators and tests
Cameron, A., & Trivedi, P. (1986) · Journal of Applied Econometrics · doi:10.1002/jae.3950010104 · Cited by 1,991 · cited 1×
“Extended approaches based on the Poisson distribution by Cameron and colleagues (Cameron and Johansson, 1997; Cameron and Trivedi, 1986) (negative binomial and variance linear in the mean, Poisson polynomial model) and Grootendorst (1995) (zero-inflated Poisson and negative binomial) are used to…”
MethodEstimating log models: to transform or not to transform?
Manning, W. G., & Mullahy, J. (2001) · Journal of Health Economics · doi:10.1016/s0167-6296(01)00086-8 · Cited by 1,790 · cited 14×
“tion of the variance function could lead to inefficiencies, the mean function estimates are usually robust (Manning and Mullahy, 2001).”
InfluentialA Comparison of Alternative Models for the Demand for Medical Care
Duan, N.-H., Manning, W., Morris, C., & Newhouse, J. (1983) · Journal of Business and Economic Statistics · doi:10.1080/07350015.1983.10509330 · Cited by 1,410 · cited 13×
“mishandling of both non-users and significant users of health services) (Duan et al., 1983).”
BackgroundMethodInfluentialThe logged dependent variable, heteroscedasticity, and the retransformation problem.
Manning, W. (1998) · Journal of Health Economics · doi:10.1016/s0167-6296(98)00025-3 · Cited by 959
Buntin, M., & Zaslavsky, A. (2004) · Journal of Health Economics · doi:10.1016/j.jhealeco.2003.10.005 · Cited by 792 · cited 5×
“…reviewed included an informal comparison of different methods and approaches applied to the same data (Austin et al., 2003; Briggs and Gray, 1998; Buntin and Zaslavsky, 2004; Chen and Zhou, 2006; Cooper et al., 2007; Lipscomb et al., 1998; Manning and Mullahy, 2001; O’Hagan and Stevens, 2003;…”
BackgroundMethodInfluentialMuch ado about two: reconsidering retransformation and the two-part model in health econometrics.
Mullahy, J. (1998) · Journal of Health Economics · doi:10.1016/s0167-6296(98)00030-7 · Cited by 791 · cited 2×
“In this regard, Mullahy (1998) proposes two estimators using exponential conditional mean specifications.”
MethodHow should cost data in pragmatic randomised trials be analysed?
Thompson, S. G. (2000) · BMJ · doi:10.1136/bmj.320.7243.1197 · Cited by 772 · cited 2×
“Two common approaches to directly evaluate uncertainty in costs, effects and/or cost-effectiveness in randomised trials are the Central Limit Theorem and the bootstrap approach (Barber and Thompson, 2000; O’Hagan and Stevens, 2003; Thompson and Barber, 2000).”
BackgroundMethodSelf-citation
Flagged first, then by citations
17 of the 99 references couldn’t be matched to a known paper.
Research works printed but not linked: 20
- Arrow KJ, 1970, Uncertainty and the evaluation of public investment decisions, The American Economic Review, 60, 364
- Basu A, 2005, Extended generalised linear models: simultaneous estimation of flexible link and variance functions, The Stata Journal, 5, 501, 10.1177/1536867X0500500402 · DOI
- Cameron AC, 2009, Microeconometrics Using Stata
- 10.1198/07350010152596673 · DOI
- 10.1002/(SICI)1099-1255(199705)12:3<313::AID-JAE440>3.0.CO;2-G · DOI
- 10.2307/1391852 · DOI
- 10.2307/1391711 · DOI
- 10.1016/j.jhealeco.2003.09.008 · DOI
- 10.1002/(SICI)1099-1255(199705)12:3<225::AID-JAE445>3.0.CO;2-Y · DOI
- 10.2307/1391710 · DOI
- 10.1017/CBO9780511811852 · DOI
- Jones AM, 2000, North‐Holland Handbook of Health Economics
- Maddala GS, 1985, Advances in Health Economics and Health Services Research
- Marazzi A, 2003, Robust parametric means of asymmetric distributions: estimation and testing, Estadistica, 54, 47
- 10.1111/1475-3995.00428 · DOI
- 10.1002/(SICI)1099-1255(199705)12:3<337::AID-JAE438>3.0.CO;2-G · DOI
- 10.1016/S0304-4076(01)00059-8 · DOI
- van de Ven WPMM, 1981, Health, Economics, and Health Economics
- 10.1016/j.jspi.2004.07.009 · DOI
- 10.1016/j.csda.2004.12.001 · DOI
Cited by
Sorted by citations
Antibiotic resistance threats in the United States, 2019
(U.S.), C. F. D. C. A. P. (2019) · doi:10.15620/cdc:82532 · Cited by 5,782
Belotti, F., Deb, P., Manning, W., & Norton, E. (2015) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x1501500102 · Cited by 588
Health-related quality of life measured using the EQ-5D–5L: South Australian population norms
McCaffrey, N., Kaambwa, B., Currow, D. C., & Ratcliffe, J. (2016) · Health and Quality of Life Outcomes · doi:10.1186/s12955-016-0537-0 · Cited by 478
“This model controls for skewness and heteroscedasticity and approximates the distribution of the data based on the modified Park test [53, 54].”
MethodAutomated Identification of Adults at Risk for In-Hospital Clinical Deterioration
Escobar, G. J., Liu, V. X., Schuler, A., Lawson, B., Greene, J. D., & Kipnis, P. (2020) · New England Journal of Medicine · doi:10.1056/nejmsa2001090 · Cited by 314
Economic evaluation alongside randomised controlled trials: design, conduct, analysis, and reporting
Petrou, S., & Gray, A. (2011) · British medical journal · doi:10.1136/bmj.d1548 · Cited by 313
“Although cost data are often right skewed because a few patients use very high amounts of resource, producing a distribution that may violate the assumptions of standard statistical tests, it is not clear that the many alternative approaches suggested, such as bootstrapping, provide more reliable test results.”
BackgroundStatistical models for the analysis of skewed healthcare cost data: a simulation study
Malehi, A. S., Pourmotahari, F., & Angali, K. A. (2015) · Health Economics Review · doi:10.1186/s13561-015-0045-7 · Cited by 260
“The general consensus is that estimating the mean cost using a logarithmic regression model leads to biased estimation [2,4-6].”
BackgroundResultInfluentialNelson, R., Hatfield, K. M., Wolford, H. M., Samore, M., Scott, R., Reddy, S. C., Olubajo, B., Paul, P., Jernigan, J., & Baggs, J. (2021) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa1581 · Cited by 256
Comparison of the Financial Burden of Survivors of Head and Neck Cancer With Other Cancer Survivors
Massa, S. T., Osazuwa‐Peters, N., Boakye, E. A., Walker, R. J., & Ward, G. M. (2019) · JAMA Otolaryngology–Head & Neck Surgery · doi:10.1001/jamaoto.2018.3982 · Cited by 145
Stokes, M., Ye, X., Shah, M., Mercaldi, K., Reynolds, M., Rupnow, M., & Hammond, J. (2011) · BMC Health Services Research · doi:10.1186/1472-6963-11-135 · Cited by 239
Reeves, D., Blickem, C., Vassilev, I., Brooks, H., Kennedy, A., Richardson, G., & Rogers, A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0098340 · Cited by 213
“To account for this, we followed a recommendation to apply standard regression using a bootstrap estimate of standard error, and to repeat the analysis with and without the extreme values [49].”
MethodMarson, A., Burnside, G., Appleton, R., Smith, D., Leach, J. P., Sills, G., Tudur-Smith, C., Plumpton, C., Hughes, D. A., Williamson, P., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(21)00247-6 · Cited by 208
The extra resource burden of in‐hospital falls: a cost of falls study
Morello, R., Barker, A. L., Watts, J. J., Haines, T. P., Zavarsek, S., Hill, K., Brand, C. A., Sherrington, C., Wolfe, R. S., Bohensky, M. A., et al. (2015) · The Medical Journal of Australia · doi:10.5694/mja15.00296 · Cited by 212
Medication Nonadherence in Diabetes
Egede, L. E., Gebregziabher, M., Dismuke, C. E., Lynch, C. P., Axon, R. N., Zhao, Y., & Mauldin, P. D. (2012) · Diabetes Care · doi:10.2337/dc12-0572 · Cited by 195
“In addition, most analyses fail to appropriately account for the shared correlation among cost variables (11).”
BackgroundCosts of multimorbidity: a systematic review and meta-analyses
Tran, P. B., Kazibwe, J., Nikolaidis, G. F., Linnosmaa, I., Rijken, M., & van Olmen, J. (2022) · BMC Medicine · doi:10.1186/s12916-022-02427-9 · Cited by 208
Costs to Health Services and the Patient of Treating Tuberculosis: A Systematic Literature Review
Laurence, Y. V., Griffiths, U., & Vassall, A. (2015) · PharmacoEconomics (Auckland) · doi:10.1007/s40273-015-0279-6 · Cited by 180
“We also extracted whether any measures of dispersion, such as standard deviation (SD), around the mean cost values were given [22].”
MethodEconomic evaluation of a task-shifting intervention for common mental disorders in India
Buttorff, C., Hock, R., Weiss, H., Naik, S., Araya, R., Kirkwood, B., Chisholm, D., & Patel, V. (2012) · Bulletin of the World Health Organization · doi:10.2471/blt.12.104133 · Cited by 175
Marson, A. G., Burnside, G., Appleton, R. E., Smith, D., Leach, J. P., Sills, G. J., Smith, C. T., Plumpton, C., Hughes, D. A., Williamson, P. R., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(21)00246-4 · Cited by 222
Health literacy and the use of healthcare services in Belgium
Vandenbosch, J., den Broucke, S. V., Vancorenland, S., Avalosse, H., Verniest, R., & Callens, M. G. (2016) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2015-206910 · Cited by 192
Markle‐Reid, M., Ploeg, J., Fraser, K. D., Fisher, K., Bartholomew, A., Griffith, L. E., Miklavcic, J. J., Gafni, A., Thabane, L., & Upshur, R. E. G. (2017) · Journal of the American Geriatrics Society · doi:10.1111/jgs.15173 · Cited by 163
“Cost data are often substantially positively skewed (as in this study) and have traditionally been handled using nonparametric methods such as rank-order statistics.(45) We used the nonparametric Mann–Whitney U-test to evaluate differences in median costs between the two groups.”
MethodHealth Care Costs Associated With Incident Complications in Patients With Type 2 Diabetes in Germany
Kähm, K., Laxy, M., Schneider, U., Rogowski, W. H., Lhachimi, S. K., & Holle, R. (2018) · Diabetes Care · doi:10.2337/dc17-1763 · Cited by 141
“In line with literature recommendations, we can assume a near normality of the sample means, as the sample size is sufficiently large and the proportion of zero costs relatively small (,2%) (30).”
BackgroundQuality of life profile of general Vietnamese population using EQ-5D-5L
Nguyen, L., Tran, B., Le, Q. H., Tran, T., & Latkin, C. (2017) · Health and Quality of Life Outcomes · doi:10.1186/s12955-017-0771-0 · Cited by 125
“Generalized linear model (GLM), which could manage skewness and heteroscedasticity, was employed to explore relationships between potential covariates and EQ5D utility scores as well as VAS scores [39, 40].”
MethodBurn, E., Edwards, C., Murray, D., Silman, A., Cooper, C., Arden, N., Pinedo-Villanueva, R., & Prieto-Alhambra, D. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-019146 · Cited by 123
“As both length of stay and hospital reimbursement are non-negative and right-skewed, generalised linear models with a gamma distribution and a log-link were specified.(16) For continuous variables, non-linearity was incorporated using restricted cubic splines.”
Mallucci, C., Jenkinson, M., Conroy, E., Hartley, J., Brown, M., Dalton, J., Kearns, T., Moitt, T., Griffiths, M., Culeddu, G., et al. (2019) · The Lancet · doi:10.1016/s0140-6736(19)31603-4 · Cited by 120
The impact of severe haemophilia and the presence of target joints on health-related quality-of-life
O'Hara, J., Walsh, S., Camp, C., Mazza, G., Carroll, L., Hoxer, C., & Wilkinson, L. (2018) · Health and Quality of Life Outcomes · doi:10.1186/s12955-018-0908-9 · Cited by 117
“A confirmatory analysis of the family and link functions was conducted using the modified Park test [21, 22].”
MethodAmin, A. P., Patterson, M. E., House, J. A., Giersiefen, H., Spertus, J. A., Baklanov, D. V., Chhatriwalla, A. K., Safley, D. M., Cohen, D. J., Rao, S. V., et al. (2017) · JACC: Cardiovascular Interventions · doi:10.1016/j.jcin.2016.11.049 · Cited by 113
“Costs were trimmed back to the 99th percentile to remove extreme outliers (27,28).”
MethodNelson, R., Hyun, D. Y., Jezek, A., & Samore, M. (2021) · Clinical Infectious Diseases · doi:10.1093/cid/ciab696 · Cited by 113
“This pooled dataset was then used to run multivariable generalized estimating equation (GEE) models with a gamma family and log link [28] to estimate the per-infection attributable cost as measured by an adjusted risk difference between infection patients and their uninfected controls.”
MethodCoping with the economic consequences of ill health in Indonesia.
Sparrow, R., van de Poel, E., Hadiwidjaja, G., Yumna, A., Warda, N., & Suryahadi, A. (2014) · Health Economics · doi:10.1002/hec.2945 · Cited by 112
Methods of sample size calculation in descriptive retrospective burden of illness studies
Johnston, K., Lakzadeh, P., Donato, B., & Szabo, S. (2019) · BMC Medical Research Methodology · doi:10.1186/s12874-018-0657-9 · Cited by 109
Pickard, R., Lam, T., Maclennan, G., Starr, K., Kilonzo, M., McPherson, G., Gillies, K., McDonald, A., Walton, K., Buckley, B., et al. (2012) · Health Technology Assessment · doi:10.3310/hta16470 · Cited by 105
Cortaredona, S., & Ventelou, B. (2017) · BMC Medicine · doi:10.1186/s12916-017-0978-2 · Cited by 103
“In our two-stage model, the first part P (cost > 0) was modelled using a logit model; then, conditional on the healthcare spending being positive, the value of the spending was modelled using gamma regressions with log link [28, 29].”
MethodThe First Episode Rapid Early Intervention for Eating Disorders ‐ Upscaled study: Clinical outcomes
Austin, A., Flynn, M., Shearer, J., Long, M., Allen, K., Mountford, V. A., Glennon, D., Grant, N., Brown, A., Franklin‐Smith, M., et al. (2022) · Early Intervention in Psychiatry · doi:10.1111/eip.13139 · Cited by 101
“compared between groups using generalized linear modelling (gamma family, identity link) as recommended to account for the highly skewed nature of cost data (Mihaylova et al., 2011).”
MethodResultTweedie distributions for fitting semicontinuous health care utilization cost data
Kurz, C. F. (2016) · BMC Medical Research Methodology · doi:10.1186/s12874-017-0445-y · Cited by 97
“[15] and the literature already mentioned.”
Butler, A. M., Brown, D. S., Durkin, M. J., Sahrmann, J. M., Nickel, K. B., O’Neil, C. A., Olsen, M. A. A., Hyun, D. Y., Zetts, R. M., & Newland, J. G. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.14153 · Cited by 119
Boulton, A. J., & Williford, A. (2018) · Journal of the Society for Social Work and Research · doi:10.1086/701235 · Cited by 91
“Although more research is needed to provide actionable guidance for applied researchers (Mihaylova et al., 2011; Neelon et al., 2016), understanding the nature of the zeros in the data, using theory to distinguish between a single or two-part data-generating process, and reviewing fit diagnostics…”
BackgroundMethodHealthcare Cost and Impact of Persistent Orofacial Pain
Durham, J., Shen, J., Breckons, M., Steele, J., Araújo‐Soares, V., Exley, C., & Vale, L. D. (2016) · Journal of Dental Research · doi:10.1177/0022034516648088 · Cited by 92
Ying, M., Wang, S.-J., Bai, C., & Li, Y. (2020) · PLoS ONE · doi:10.1371/journal.pone.0240194 · Cited by 89
“In a review study, Mihaylova and colleagues recommended that the two-part model be used for modeling expenditure data with excessive zeros [47].”
Sadatsafavi, M., Rousseau, R., Chen, W., Zhang, W., Lynd, L., & Fitzgerald, J. (2014) · Chest · doi:10.1378/chest.13-1619 · Cited by 89
The impact of inappropriate use of short acting beta agonists in asthma.
Fitzgerald, J. M., Tavakoli, H., Lynd, L., Al-Efraij, K., & Sadatsafavi, M. (2017) · Respiratory Medicine · doi:10.1016/j.rmed.2017.08.014 · Cited by 87
The Economic Costs of Childhood Disability: A Literature Review
Shahat, A., & Greco, G. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18073531 · Cited by 80
“Different statistical techniques have been used for presenting the cost results in mean costs including bootstrapping and using the gamma distribution [29,54].”
MethodWeichle, T. W., Hynes, D. M., Durazo-Arvizú, R., Tarlov, E., & Zhang, Q. (2013) · SpringerPlus · doi:10.1186/2193-1801-2-614 · Cited by 82
Determinants of societal costs in Alzheimer's disease: GERAS study baseline results
Dodel, R., Belger, M., Reed, C., Wimo, A., Jones, R. W., Happich, M., Argimón, J., Bruno, G., Vellas, B., & Haro, J. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2015.02.005 · Cited by 79
“For the base case analysis, generalized linear models (GLMs) were developed using the gamma distribution with a log-link function [26].”
MethodMoran, J. L., & Solomon, P. J. (2012) · BMC Medical Research Methodology · doi:10.1186/1471-2288-12-68 · Cited by 86
“” [69] and an identity link [12,15] may be analytically sufficient seems not to be the case with our data, although the LMM and log-OLS models were relatively easy to fit and interpret.”
BackgroundMethodResultInfluentialAndersson, E., Persson, S., Hallén, N., Ericsson, Å., Thielke, D., Lindgren, P., Carlsson, K. S., & Jendle, J. (2020) · Diabetologia · doi:10.1007/s00125-020-05277-3 · Cited by 78
Chestnutt, I. G., Hutchings, S., Playle, R., Morgan-Trimmer, S., Fitzsimmons, D., Aawar, N., Angel, L., Derrick, S., Drew, C., Hoddell, C., et al. (2017) · Health Technology Assessment · doi:10.3310/hta21210 · Cited by 75
Ocagli, H., Cella, N., Stivanello, L., Degan, M., & Canova, C. (2020) · Journal of Advanced Nursing · doi:10.1111/jan.14708 · Cited by 74
Vlahiotis, A., Griffin, B., Stavros, A. T., & Margolis, J. M. (2018) · ClinicoEconomics and Outcomes Research · doi:10.2147/ceor.s150260 · Cited by 81
“(Authors’ note: Health care cost data have long been observed to exhibit substantial skewness with long right-sided tails, commonly resulting in large SDs often approaching or exceeding the value of the mean.(26))”
BackgroundReinius, P., Johansson, M., Fjellner, A., Werr, J., Ohlén, G., & Edgren, G. (2013) · European journal of emergency medicine · doi:10.1097/mej.0b013e328358bf5a · Cited by 73
Bang, J. Y., Lakhtakia, S., Thakkar, S. J., Buxbaum, J. L., Waxman, I., Sutton, B. S., Memon, S. F. F., Singh, S., Basha, J., Singh, A., et al. (2023) · The Lancet. Gastroenterology & hepatology · doi:10.1016/s2468-1253(23)00331-x · Cited by 102
Lage, M. J., & Boye, K. S. (2020) · Current Medical Research and Opinion · doi:10.1080/03007995.2020.1787971 · Cited by 83
Masiye, F., & Kaonga, O. (2016) · International Journal of Health Policy and Management · doi:10.15171/ijhpm.2016.65 · Cited by 71
Egede, L. E., Walker, R. J., Bishu, K., & Dismuke, C. E. (2016) · Journal of General Internal Medicine · doi:10.1007/s11606-016-3650-1 · Cited by 70
Statistical Methods for Cost-Effectiveness Analyses That Use Data from Cluster Randomized Trials
Gomes, M., Grieve, R., Nixon, R. M., & Edmunds, W. J. (2011) · Medical Decision Making · doi:10.1177/0272989x11407341 · Cited by 64
“Likewise, for CEAs that use end points from CRTs as parameters in a decision model, any probabilistic sensitivity analysis should carefully justify the distributional assumptions of these input parameters.(26,54) To summarize, statistical methods in CEAs that use CRT have to recognize clustering and correlation, as we…”
MethodDuggleby, W., Ploeg, J., McAiney, C., Peacock, S., Fisher, K., Ghosh, S., Markle-Reid, M., Swindle, J., Williams, A., Triscott, J. A., et al. (2018) · Journal of Medical Internet Research · doi:10.2196/10484 · Cited by 67
“Cost data are substantially positively skewed and have traditionally been handled using nonparametric methods [42].”
MethodPopulation Cost Prediction on Public Healthcare Datasets
Sushmita, S., Newman, S., Marquardt, J., Ram, P., Prasad, V., Cock, M. D., & Teredesai, A. (2015) · Digital Health · doi:10.1145/2750511.2750521 · Cited by 67
“It is well recognized that statistical analysis of healthcare cost data poses a number of di culties [16].”
BackgroundImpact of Inpatient Harms on Hospital Finances and Patient Clinical Outcomes
Adler, L. M., Yi, D. K., Li, M., McBroom, B., Hauck, L. D., Sammer, C. E., Jones, C., Shaw, T., & Classen, D. C. (2015) · Journal of Patient Safety · doi:10.1097/pts.0000000000000171 · Cited by 85
EFFECTS OF NCMS ON ACCESS TO CARE AND FINANCIAL PROTECTION IN CHINA
Hou, Z., de Poel, E. V., van Doorslaer, E. K. A., Yu, B., & Meng, Q. (2013) · Health Economics · doi:10.1002/hec.2965 · Cited by 66
Wijeysundera, H., Wang, X.-S., Tomlinson, G., Ko, D. T., & Krahn, M. (2012) · ClinicoEconomics and Outcomes Research · doi:10.2147/ceor.s31552 · Cited by 66
Verberne, W. R., Dijkers, J., Kelder, J. C., Geers, A. B., Jellema, W. T., Vincent, H. H., van Delden, J. J. M., & Bos, W. J. W. (2018) · BMC Nephrology · doi:10.1186/s12882-018-1004-4 · Cited by 84
Leung, M. Y. M., Pollack, L. M., Colditz, G. A., & Chang, S. (2014) · Diabetes Care · doi:10.2337/dc14-1453 · Cited by 72
“0%) had zeromedical expenditures, the age-, race-, sex-, and BMI-specific annual health care expenditures for both patients with diabetes and those without diabetes were estimated using a twopart model (29,30).”
MethodBedson, E., Bell, D., Carr, D. F., Carter, B., Hughes, D. A., Jorgensen, A., Lewis, H., Lloyd, K. R., McCaddon, A., Moat, S. J., et al. (2014) · Health Technology Assessment · doi:10.3310/hta18480 · Cited by 63
Direct medical costs of COPD--an excess cost approach based on two population-based studies.
Menn, P., Heinrich, J., Huber, R., Jörres, R., John, J., Karrasch, S., Peters, A., Schulz, H., & Holle, R. (2012) · Respiratory Medicine · doi:10.1016/j.rmed.2011.10.013 · Cited by 63
Zhu, Y., Zhao, Z., Guo, J., Wang, Y., Zhang, C., Zheng, J., Zou, Z., & Liu, W. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20043139 · Cited by 77
“The skewness and kurtosis of the sample data met the normal distribution criteria [50,51].”
BackgroundMethods of coke quality prediction: A review
North, L., Blackmore, K. L., Nesbitt, K. V., & Mahoney, M. R. (2018) · Fuel · doi:10.1016/j.fuel.2018.01.090 · Cited by 72
Graves, J. M., Mackelprang, J., Moore, M., Abshire, D., Rivara, F., Jimenez, N., Fuentes, M., & Vavilala, M. (2018) · Health Services Research · doi:10.1111/1475-6773.13096 · Cited by 60
Estimating Costs of an Implementation Intervention
Wagner, T. H., Yoon, J., Jacobs, J. C., So, A., Kilbourne, A. M., Yu, W., & Goodrich, D. E. (2020) · Medical Decision Making · doi:10.1177/0272989x20960455 · Cited by 59
Home‐based pulmonary rehabilitation for COPD using minimal resources: An economic analysis
Burge, A. T., Holland, A. E., McDonald, C. F., Abramson, M. J., Hill, C. J., Lee, A. L., Cox, N. S., Moore, R., Nicolson, C., O’Halloran, P., et al. (2019) · Respirology · doi:10.1111/resp.13667 · Cited by 68
Tibuakuu, M., Okunrintemi, V., Jirru, E., Echouffo-Tcheugui, J. B., Orimoloye, O. A., Mehta, P. K., DeFilippis, A. P., Blaha, M. J., & Michos, E. D. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.4585 · Cited by 67
The relationship between target joints and direct resource use in severe haemophilia
O'Hara, J., Walsh, S., Camp, C., Mazza, G., Carroll, L., Hoxer, C., & Wilkinson, L. (2018) · Health Economics Review · doi:10.1186/s13561-018-0185-7 · Cited by 59
“1) suitable for nonparametric dependent variables [19, 20].”
MethodDirect costs in diabetic and non diabetic people: the population-based Turin study, Italy.
Bruno, G., Picariello, R., Petrelli, A., Panero, F., Costa, G., Cavallo-Perin, P., Demaria, M., & Gnavi, R. (2012) · NMCD. Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2011.04.007 · Cited by 59
“where Y represents the cost and X represents the vector of covariates [18].”
BackgroundMethodLi, C., Zhou, R., Yao, N., Cornwell, T., & Wang, S. (2020) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2020.02.010 · Cited by 58
Kreif, N., Grieve, R., Radice, R., & Sekhon, J. S. (2013) · Health Services and Outcomes Research Methodology · doi:10.1007/s10742-013-0109-2 · Cited by 54
“For each subject, continuous confounders (Z1; Z2; Z3; Z4) were generated from bivariate normal distributions with the following means, standard deviations and correlation: Z1 Z2 N 2 4 ; 1 0:2 0:2 1 Z3 Z4 N 2 4 ; 1 0:2 0:2 1 : The treatment indicator t was randomly generated from a Bernoulli distribution with parameter…”
Methodinteractive effects of dementia severity and comorbidities on medicare expenditures
Zhu, C. W., Cosentino, S., Ornstein, K. A., Gu, Y., Andrews, H., & Stern, Y. (2017) · Journal of Alzheimer’s Disease · doi:10.3233/jad-161077 · Cited by 55
Pagano, E., Rosa, M. D. D., Rossi, E., Cinconze, E., Marchesini, G., Miccoli, R., Vaccaro, O., Bonora, E., & Bruno, G. (2016) · NMCD. Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2016.05.002 · Cited by 54
Economic Burden of Reported Lyme Disease in High-Incidence Areas, United States, 2014–2016
Hook, S. A., Jeon, S., Niesobecki, S. A., Hansen, A. P., Meek, J. I., Bjork, J., Dorr, F., Rutz, H., Feldman, K., White, J. L., et al. (2022) · Emerging Infectious Diseases · doi:10.3201/eid2806.211335 · Cited by 52
“As is typical for healthcare cost data, the distribution of total cost was highly skewed, resulting in heteroskedasticity of the residuals in the model (10).”
BackgroundDeb, A., Sambamoorthi, U., Thornton, J. D., Schreurs, B. G., & Innes, K. E. (2017) · Aging & Mental Health · doi:10.1080/13607863.2017.1286454 · Cited by 62
Dismuke, C., & Egede, L. (2011) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2011.03.014 · Cited by 52
“The Heckman [27] model does not address skewness specifically; however, with a large-enough sample, the central limit theorem should provide confidence that sample means will be close to normal [29].”
BackgroundSpoilt for choice: implications of using alternative methods of costing hospital episode statistics.
Geue, C., Lewsey, J., Lorgelly, P., Govan, L., Hart, C., & Briggs, A. (2012) · Health Economics · doi:10.1002/hec.1785 · Cited by 51
“For a comprehensive review of statistical methods to analyse HCE data, see also Dodd et al. (2006) and Mihaylova et al. (2011).”
MethodSelf-citationThe Evolution of Health Care Utilisation and Costs for Inflammatory Bowel Disease Over Ten Years.
Pillai, N., Dusheiko, M., Maillard, M., Rogler, G., Brüngger, B., Bähler, C., & Pittet, V. (2019) · Journal of Crohn's & Colitis · doi:10.1093/ecco-jcc/jjz003 · Cited by 50
Wallace, K., Zhao, X., Misra, R., & Sambamoorthi, U. (2018) · Journal of Diabetes Research · doi:10.1155/2018/4842520 · Cited by 50
“, high positive skewness and heteroscedasticity), we used generalized linear models with a log link function and gamma family distribution for expenditure outcomes [27].”
MethodA transition care coordinator model reduces hospital readmissions and costs
Kripalani, S. B., Chen, G., Ciampa, P. J., Theobald, C. N., Cao, A., McBride, M., Dittus, R. S., & Speroff, T. (2019) · Contemporary Clinical Trials · doi:10.1016/j.cct.2019.04.014 · Cited by 59
“Cost outcomes were modeled using two-part models due to excessive zero cost (16, 17).”
MethodExcess medical costs in patients with asthma and the role of comorbidity
Chen, W., Lynd, L., Fitzgerald, J., Marra, C., Balshaw, R., To, T., Tavakoli, H., & Sadatsafavi, M. (2016) · European Respiratory Journal · doi:10.1183/13993003.01141-2016 · Cited by 49
The influence of obesity and overweight on medical costs: a panel data perspective
Mora, T., Gil, J., & Sicras-Mainar, A. (2013) · European Journal of Health Economics · doi:10.1007/s10198-014-0562-z · Cited by 49
“’s [29] literature review confirms that 2PM models perform better.”
An Educational Review About Using Cost Data for the Purpose of Cost-Effectiveness Analysis
Franklin, M., Lomas, J., Walker, S., & Young, T. (2019) · PharmacoEconomics (Auckland) · doi:10.1007/s40273-019-00771-y · Cited by 48
Flórez-Tanus, Á., Padilla, D. P., Zakzuk, J., Caraballo, L. R., & Alvis‐Guzmán, N. (2018) · World Allergy Organization Journal · doi:10.1186/s40413-018-0205-4 · Cited by 52
Atopic dermatitis: the relationship to temperature and seasonality in the United States
Fleischer, A. B. (2018) · International Journal of Dermatology · doi:10.1111/ijd.14289 · Cited by 48
Vecchia, M. D. D., Regis, R., Cunha, T. R., de Andrade, I. M., da Matta, J. C. S., & de Souza, R. D. (2014) · Journal of Prosthodontics · doi:10.1111/jopr.12090 · Cited by 47
Medical Costs and Productivity Loss Due to Mild, Moderate, and Severe Asthma in the United States
Song, H., Blake, K., Wilson, D. L., Winterstein, A., & Park, H. (2020) · Journal of Asthma and Allergy · doi:10.2147/jaa.s272681 · Cited by 46
Elizondo, J. V., Salami, J., Osondu, C. U., Ogunmoroti, O., Arrieta, A., Spatz, E. S., Younus, A., Rana, J. S., Virani, S. S., Blankstein, R., et al. (2016) · Journal of the American Heart Association · doi:10.1161/jaha.116.003614 · Cited by 52
“Because of the right-skewedness of expenditures data (ie, most expenditures are seen in only a small proportion of the population), twopart models were utilized to study expenditures.(27) Two-part models are often used to model health care expenditures, and are the product of: (1) the probability that any given indivi…”
MethodValero-Elizondo, J., Salami, J. A., Ogunmoroti, O., Osondu, C. U., Aneni, E. C., Malik, R., Spatz, E. S., Rana, J. S., Virani, S. S., Blankstein, R., et al. (2016) · Circulation: Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.115.002616 · Cited by 51
“Because of the right skewedness of expenditures data (ie, most expenditures are seen in only a small proportion of the population), 2-part models were used to study expenditures.(21) Two-part models are often used to model healthcare expenditures and are the product of: (1) the probability that any given individual ha…”
MethodOut-of-pocket expenses experienced by rural Western Australians diagnosed with cancer
Newton, J. C., Johnson, C. E., Hohnen, H., Bulsara, M., Ives, A., McKiernan, S., Platt, V., Mcconigley, R., Slavova-Azmanova, N., & Saunders, C. (2018) · Supportive Care in Cancer · doi:10.1007/s00520-018-4205-2 · Cited by 45
Sickness and Death: Economic Consequences and Coping Strategies of the Urban Poor in Bangladesh
Khan, F., Bedi, A., & Sparrow, R. (2015) · doi:10.1016/j.worlddev.2015.03.008 · Cited by 45
“We therefore use a fixed effects Poisson model (FEP) in order to deal with these distributions and also avoid retransformation problems of taking natural logs of the outcome variables (Manning and Mullahy 2001, Buntin and Zaslavsky 2004, Mihaylova et al. 2011, Sparrow et al. 2014).”
MethodZhou, Y.-L., Zhao, K., Han, J., Zhao, S.-D., & Cao, J. (2022) · Tropical Medicine and Infectious Disease · doi:10.3390/tropicalmed7100292 · Cited by 44
“and there is a growing number of papers on regression model analysis and cost-benefit comparative analysis based on statistics [36,37].”
BackgroundRitchwood, T. D., Bishu, K. G., & Egede, L. (2017) · International Journal for Equity in Health · doi:10.1186/s12939-017-0683-y · Cited by 44
“The total medical healthcare expenditure is a sum of office-based medical provider expenditure, hospital outpatient expenditure, emergency room expenditure, inpatient hospital (including zero night stays) expenditure, prescription medicine expenditure, dental expenditure, home health care expenditure and other medical…”
BackgroundInfluentialCost-Effectiveness of Cancer Screening: Health and Costs in Life Years Gained.
Ratushnyak, S., Hoogendoorn, M., & van Baal, P. V. (2019) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2019.07.027 · Cited by 43
“To estimate the per capita age-specific quality of life losses and healthcare expenditures for the competing diseases, two-part regression models were fitted, because the distributions of both outcomes were skewed.(24,25) The first part of the model predicted the probability of the outcome variable being 1 (for the qu…”
MethodRaza, W., van de Poel, E., Bedi, A., & Rutten, F. (2015) · Health Economics · doi:10.1002/hec.3307 · Cited by 43
“FEP models are well suited to dealing with such outcomes (Mihaylova et al., 2011; Buntin and Zaslavsky, 2004; Manning and Mullahy, 2001).”
BackgroundJi, Y.-B., Puri, R., Lakhtakia, S., Thakkar, S., Waxman, I., Siddiqui, I. J., Arnold, K., Chaudhary, A., Mehta, S., Singh, A., et al. (2025) · Gut · doi:10.1136/gutjnl-2025-336339 · Cited by 42
Park, S. (2021) · BMC Health Services Research · doi:10.1186/s12913-021-06881-8 · Cited by 42
“Because the out-of-pocket spending data is skewed to the right and was not normally distributed, a generalized linear model (GLM) with a log-link function using a gamma distribution was applied, which is the most suitable option for cost data analysis analyzing both mean and variance functions and adjusting the right-…”
MethodLeininger, B. D., McDonough, C. M., Evans, R., Tosteson, T. D., Tosteson, A. N. A., & Brønfort, G. (2016) · The Spine Journal · doi:10.1016/j.spinee.2016.06.014 · Cited by 48
“Generalized estimating equations specifying a poisson distribution and identity link were used to estimate mean costs over the year.[40, 41] Separate models were performed to estimate cost rates for medication use (one week) and lost productivity (one month).”
MethodEconomic burden of multimorbidity in patients with severe asthma: a 20-year population-based study
Chen, W., Safari, A., Fitzgerald, J., Sin, D. D., Tavakoli, H., & Sadatsafavi, M. (2019) · Thorax · doi:10.1136/thoraxjnl-2019-213223 · Cited by 41
Dixon, P., Hollinghurst, S. P., Edwards, L., Thomas, C., Gaunt, D., Foster, A., Large, S., Montgomery, A. A., & Salisbury, C. (2016) · BMJ Open · doi:10.1136/bmjopen-2016-012352 · Cited by 39
“The cost-effectiveness analysis used seemingly unrelated regression (SUR), for which we rely on the near normality of differences in sample means and differences in sample variances in large samples.(31) 32 We implemented SUR using the—sureg—command in”
Method
Metadata
- 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
- PMC
- PMC3470917
- 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
- bronze
- doi.org
- Licence
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
