4.8. Modelling the cost of injury

The costs of back pain and injuries could not be estimated based on available administrative microdata.

In order to address this data gap, for injury specific costs, a combinatorial approach between a PAF-, microsimulation-, and bottom-up approach was applied.

Injuries associated with the highest burden of disease due to alcohol use are road injuries, unintentional injuries, self-harm, and interpersonal violence. Road injuries, transport injuries (including falls and drowning), and self-harm contribute to the largest proportion of the alcohol-attributable disease injury burden, and, together with the other listed conditions, the largest proportion of alcohol-attributable disease burden. The cost related to injuries affected by inter-personal violence was estimated as well, due to readily available data.

Several countries report on injury costs as part of their reporting on health spending, for the annual Systems of Health Accounts/ National Health Accounts reporting to the OECD. In particular, Hungary, Sweden, Greece, and Estonia, have positively responded to our inquiry and provided injury health spending data per five-year age group (Table 4.7).

Table 4.7 Type of injury costs obtained from countries

Country	Data level and coding	Type of care	Year data available
Estonia	ICD-10 coding, by age and sex	All providers, no drug costs	2015
Sweden	ISHMT coding, by age and sex	Inpatient Injury treatment costs	2016
Greece	Average injury costs, by age and sex	All providers	2013
Hungary	Average injury costs, by age and sex		2014

Note: This table highlights the retrieved data from country statistics offices, reflecting the cost of injury by age and sex, broken down into more detailed injury types and providers, where data are available.

The injury cost data provided to the OECD was either an average cost per case, age group, and sex (i.e. Greece), or a cost per treatment, age, sex, and ICD-Code (Estonia), or based on ISHMT injury groups. The ‘per case’ cost refers to the sum of costs incurred by the same individual under the same diagnosis over the span of one year. For example, if someone incurred an ankle injury and sought multiple physiotherapy treatment sessions, the ‘per case’ cost for the ankle injury reflects the sum of these multiple visits. ‘Per treatment’ cost would only reflect the cost for one single session.

As shown in Table 4.8, the IHME injury groups associated with alcohol use are road injuries, transport injuries, and self-harm. Both ISHMT-codes as well as ICD-10 codes can be related through a set of matrices and weights to these IHME groups.

Table 4.8 Per inpatient injury case cost by gender and age for alcohol-related GBD cause groups – Sweden, 2016

	Road Injury, Transport Injuries		Self-Harm		Interpersonal Violence
	men	women	men	women	men	women
0-4	4837	4816	4008	3815	3772	3536
05-Sep	5686	4417	5864	4019	5328	3746
Oct-14	5140	4586	4554	4083	4282	3774
15-19	6395	5179	4937	3656	5118	3476
20-24	7373	6552	5670	4660	6274	4924
25-29	7201	6366	4894	4539	5536	5288
30-34	8201	5890	6134	4650	7500	4817
35-39	6707	5420	4848	3833	5376	3952
40-44	7074	6541	5336	4834	6382	5459
45-49	7420	6786	5796	5341	6766	5751
50-54	7372	6739	5398	5090	6496	5601
55-59	8048	6334	6670	5244	7297	5589
60-64	7707	5905	6088	4827	7051	5063
65-69	7175	6686	5696	5494	6396	5926
70-74	7306	6593	6048	5483	6301	5697
75-79	7068	6650	5827	5998	6080	5928
80-84	7166	6602	5949	5530	6054	5506
85-89	6670	6432	5397	5327	5455	5287
90-94	6394	6372	5214	5258	5190	5215
>=95	5722	6442	4112	5719	4231	5583

Source: Source: Swedish Ministry of Health Statistics office; data converted to EURO based on OECD statistics and economic data, as well as classified by GBD injury cause groups

Table 4.8 includes information on the relationship between ISHMT codes and IHME injury sequelae; ADDREF depicts the relationship between ICD-10 codes, IHME sequelae, and IHME code names [Vos et al., 2012 [61]]. Information in Table 4.8 was applied to injury data to obtain the per case, age-group, and sex specific injury costs that are then applied to the injury cases in the absence/presence of alcohol use/ under various alcohol policy scenarios.

In addition, since not all countries have cost data for injuries, the extrapolation methods described under Cost extrapolation to other countries were used. In addition, the extrapolation component calibrated the costs based on inpatient, outpatient and pharmaceutical expenditure ratios, and rescale the costs to reflect total population coverage.

Fig. 4.2 and Table 4.8 show the per injury case costs obtained from Greece and Sweden, respectively These data were combined with injury case outputs under various drinking and policy scenarios, obtained from the microsimulation model. With regard to the injury cost data provided by Greece, the data did not differentiate the costs by injuries. Therefore, there is a single age/gender specific cost that was uniformly applied to each alcohol-related injury type. In contrast, the Swedish and Estonian data allowed for differentiation of costs by age, sex, and GBD cause-group level.

Under the third step, the epidemiological output was combined with the per-case health care costs for alcohol related conditions.

Fig. 4.2 Injury cost per age, sex, and per case in Greece, 2013

Source: OECD 2017/18 analysis on Greek injury cost data