BACKGROUND: As cost-effectiveness analyses (CEAs) are increasingly used to inform policy decisions, there is a need for more information on how different cost determination methods affect cost estimates and the degree to which the resulting cost-effectiveness ratios (CERs) may be affected. The lack of specificity of diagnosis-related groups (DRGs) could mean that they are ill-suited for costing applications in CEAs. Yet, the implications of using International Classification of Diseases-9th edition (ICD-9) codes or a form of disease-specific risk group stratification instead of DRGs has yet to be clearly documented. OBJECTIVE: To demonstrate the implications of different disease coding mechanisms on costs and the magnitude of error that could be introduced in head-to-head comparisons of resulting CERs. METHODS: We based our analyses on a previously published Markov model for HIV/AIDS therapies. We used the Healthcare Cost and Utilisation Project Nationwide Inpatient Sample (HCUP-NIS) data release 6, which contains all-payer data on hospital inpatient stays from selected states. We added costs for the mean number of hospitalisations, derived from analyses based on either DRG or ICD-9 codes or risk group stratification cost weights, to the standard outpatient and prescription drug costs to yield an estimate of total charges for each AIDS-defining illness (ADI). Finally, we estimated the Markov model three times with the appropriate ADI cost weights to obtain CERs specific to the use of either DRG or ICD-9 codes or risk group. RESULTS: Contrary to expectations, we found that the choice of coding/grouping assumptions that are disease-specific by either DRG codes, ICD-9 codes or risk group resulted in very similar CER estimates for highly active antiretroviral therapy. The large variations in the specific ADI cost weights across the three different coding approaches was especially interesting. However, because no one approach produced consistently higher estimates than the others, the Markov model's weighted cost per event and resulting CERs were remarkably close in value to one another. CONCLUSION: Although DRG codes are based on broader categories and contain less information than ICD-9 codes, in practice the choice of whether to use DRGs or ICD-9 codes may have little effect on the CEA results in heterogeneous conditions such as HIV/AIDS.
BACKGROUND: As cost-effectiveness analyses (CEAs) are increasingly used to inform policy decisions, there is a need for more information on how different cost determination methods affect cost estimates and the degree to which the resulting cost-effectiveness ratios (CERs) may be affected. The lack of specificity of diagnosis-related groups (DRGs) could mean that they are ill-suited for costing applications in CEAs. Yet, the implications of using International Classification of Diseases-9th edition (ICD-9) codes or a form of disease-specific risk group stratification instead of DRGs has yet to be clearly documented. OBJECTIVE: To demonstrate the implications of different disease coding mechanisms on costs and the magnitude of error that could be introduced in head-to-head comparisons of resulting CERs. METHODS: We based our analyses on a previously published Markov model for HIV/AIDS therapies. We used the Healthcare Cost and Utilisation Project Nationwide Inpatient Sample (HCUP-NIS) data release 6, which contains all-payer data on hospital inpatient stays from selected states. We added costs for the mean number of hospitalisations, derived from analyses based on either DRG or ICD-9 codes or risk group stratification cost weights, to the standard outpatient and prescription drug costs to yield an estimate of total charges for each AIDS-defining illness (ADI). Finally, we estimated the Markov model three times with the appropriate ADI cost weights to obtain CERs specific to the use of either DRG or ICD-9 codes or risk group. RESULTS: Contrary to expectations, we found that the choice of coding/grouping assumptions that are disease-specific by either DRG codes, ICD-9 codes or risk group resulted in very similar CER estimates for highly active antiretroviral therapy. The large variations in the specific ADI cost weights across the three different coding approaches was especially interesting. However, because no one approach produced consistently higher estimates than the others, the Markov model's weighted cost per event and resulting CERs were remarkably close in value to one another. CONCLUSION: Although DRG codes are based on broader categories and contain less information than ICD-9 codes, in practice the choice of whether to use DRGs or ICD-9 codes may have little effect on the CEA results in heterogeneous conditions such as HIV/AIDS.
Authors: J L Meynard; M Guiguet; A Rachline; N Boukli; D Bollens; C Gentil; J Frottier; L Morand-Joubert Journal: Presse Med Date: 2001-01-13 Impact factor: 1.228
Authors: Rachael A Callcut; Kit N Simpson; Sarah Baraniuk; Erin E Fox; Barbara C Tilley; John B Holcomb Journal: Transfusion Date: 2020-05-01 Impact factor: 3.157