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Average medical cost of fatal and non-fatal injuries by type in the USA

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Objective To estimate the average medical care cost of fatal and non-fatal injuries in the USA comprehensively by injury type. Methods The attributable cost of injuries was estimated by mechanism (eg, fall), intent (eg, unintentional), body region (eg, head and neck) and nature of injury (eg, fracture) among patients injured from 1 October 2014 to 30 September 2015. The cost of fatal injuries was the multivariable regression-adjusted average among patients who died in hospital emergency departments (EDs) or inpatient settings as reported in the Healthcare Cost and Utilization Project Nationwide Emergency Department Sample and National Inpatient Sample, controlling for demographic (eg, age), clinical (eg, comorbidities) and health insurance (eg, Medicaid) factors. The 1-year attributable cost of non-fatal injuries was assessed among patients with ED-treated injuries using MarketScan medical claims data. Multivariable regression models compared total medical payments (inpatient, outpatient, drugs) among non-fatal injury patients versus matched controls during the year following injury patients’ ED visit, controlling for demographic, clinical and insurance factors. All costs are 2015 US dollars. Results The average medical cost of all fatal injuries was approximately $6880 and $41 570 per ED-based and hospital-based patient, respectively (range by injury type: $4764–$10 289 and $31 912–$95 295). The average attributable 1-year cost of all non-fatal injuries per person initially treated in an ED was approximately $6620 (range by injury type: $1698–$80 172). Conclusions and relevance Injuries are costly and preventable. Accurate estimates of attributable medical care costs are important to monitor the economic burden of injuries and help to prioritise cost-effective public health prevention activities.
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Average medical cost of fatal and non-fatal injuries by type in
the USA
Cora Peterson1, Likang Xu2, Curtis Florence2
1National Center for Injury Prevention and Control, Centers for Disease Control and Prevention,
Atlanta, Georgia, USA.
2National Center for Injury Prevention and Control, Centers for Disease Control and Prevention,
Atlanta, Georgia, USA.
Abstract
Objective—To estimate the average medical care cost of fatal and non-fatal injuries in the USA
comprehensively by injury type.
Methods—The attributable cost of injuries was estimated by mechanism (eg, fall), intent (eg,
unintentional), body region (eg, head and neck) and nature of injury (eg, fracture) among patients
injured from 1 October 2014 to 30 September 2015. The cost of fatal injuries was the
multivariable regression-adjusted average among patients who died in hospital emergency
departments (EDs) or inpatient settings as reported in the Healthcare Cost and Utilization Project
Nationwide Emergency Department Sample and National Inpatient Sample, controlling for
demographic (eg, age), clinical (eg, comorbidities) and health insurance (eg, Medicaid) factors.
The 1-year attributable cost of non-fatal injuries was assessed among patients with ED-treated
injuries using MarketScan medical claims data. Multivariable regression models compared total
medical payments (inpatient, outpatient, drugs) among non-fatal injury patients versus matched
controls during the year following injury patients’ ED visit, controlling for demographic, clinical
and insurance factors. All costs are 2015 US dollars.
Results—The average medical cost of all fatal injuries was approximately $6880 and $41 570
per ED-based and hospital-based patient, respectively (range by injury type: $4764–$10 289 and
$31 912–$95 295). The average attributable 1-year cost of all non-fatal injuries per person initially
treated in an ED was approximately $6620 (range by injury type: $1698–$80 172).
Conclusions and relevance—Injuries are costly and preventable. Accurate estimates of
attributable medical care costs are important to monitor the economic burden of injuries and help
to prioritise cost-effective public health prevention activities.
Correspondence to Dr Cora Peterson, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention,
Atlanta, Georgia, USA; cora.peterson@cdc.hhs.gov.
Contributors CP led the study design and interpretation of results and drafted the manuscript. LX and CP conducted data analysis.
LX and CF assisted with the study design and interpretation of results. All authors edited the manuscript and approved the final
manuscript as submitted.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data sources are publicly available through third parties.
Competing interests None declared.
HHS Public Access
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Published in final edited form as:
Inj Prev
. 2021 February ; 27(1): 24–33. doi:10.1136/injuryprev-2019-043544.
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INTRODUCTION
Injuries are a leading cause of mortality and morbidity in the USA. In clinical and public
health terms, injuries comprise a range of unintentional and violence-related outcomes, for
example, MVCs, drug poisoning, falls, suicide and assaults. Unintentional injuries are the
third leading cause of death, and along with suicide contributed to decreases in overall life
expectancy during 2016 and 2017.1 There are 30 million emergency department (ED) visits
for non-fatal injuries each year,2 and US medical expenditures for injury and poisoning
exceed $133 billion annually.3
Medical care cost estimates are important to monitor the economic burden of injuries and
help to prioritise cost-effective public health prevention activities. Existing comprehensive
estimates of medical care cost for injuries by injury type—mechanism (eg, fall), intention
(eg, unintentional), body region (eg, head and neck) and nature of injury (eg, fracture)—
were calculated using primarily hospital-based data from 2010,4 and have been applied in
numerous assessments of the economic and public health impact of violence and
unintentional injuries.5-10 The aim of this study was to estimate the average medical care
cost of fatal and non-fatal injuries in the USA comprehensively by injury type.
METHODS
Medical cost estimates from the perspective of the healthcare payer for fatal and non-fatal
injuries treated from 1 October 2014 to 30 September 2015 were derived from two publicly
available data sources—Healthcare Cost and Utilization Project (HCUP) (www.hcup-
us.ahrq.gov) hospital discharge databases (figure 1) and MarketScan (www.ibm.com)
medical claims databases (figure 2). The time horizon for fatal costs was the ED visit or
hospitalisation which ended in death, and the time horizon for non-fatal costs was 1 year.
Medical costs were estimated by injury mechanism and intent11 (table 1 for fatal and table 2
for non-fatal) and body region and nature of injury12 (table 3 for fatal and table 4 for non-
fatal) using established classifications based on the International Classification of Diseases,
Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes11 and External Cause of
Injury codes (E-codes). Both types of injury classification—mechanism/intent and body
region/nature of injury—are important in different contexts, and costs per injury type are not
comparable across classifications. For example, patients with different injury types by body
region (eg, torso vs head) can have the same injury type by mechanism (eg, motor vehicle
traffic) or vice versa. Transition to ICD-10-CM coding for medical payments occurred
outside the study period, on 1 October 2015.12 ICD-10-CM injury classification frameworks
are proposed and will be finalised in the future (www.cdc.gov/nchs/injury). Costs are
presented in 2015 US dollars (not inflated from 2014 to 2015 data source values).
Fatal injuries
Data—The medical cost of fatal injuries was assessed among patients with a primary
diagnosis of injury11 who died in a hospital ED or inpatient setting as reported in the HCUP
Nationwide Emergency Department Sample (HCUP-NEDS) and National Inpatient Sample
(HCUP-NIS) (figure 1). These data sources can produce nationally representative estimates
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of ED visits and inpatient admissions to community hospitals. HCUP-NEDS and HCUP-
NIS demonstrate hospital facility charges per ED visit or admission, edited to exclude
extreme dollar values.
Hospital charges are distinct from payments hospitals receive from individuals or health
insurance companies and typically do not include physician (or professional) fees,
ambulance fees, nor coroner/medical examiner (C/ME) fees—each separately estimated for
this study. The estimated medical cost per fatal injury in an ED or inpatient hospital was
calculated as the facility charge value from HCUP-NEDS or HCUP-NIS multiplied by an
HCUP hospital-specific cost-to-charge ratio (CCR) and a diagnosis-specific professional fee
ratio (PFR), plus estimated ambulance and C/ME costs—each element as detailed below.
Annual, all-payer, hospital-specific, inpatient CCRs are calculated by the US Centers for
Medicare and Medicaid Services and published for use with HCUP-NIS (www.hcup-
us.ahrq.gov). When hospital-specific CCR was unavailable (approximately 2% of HCUP-
NIS analysed injury records; data not shown), the authors used multiple imputation to
estimate CCR based on selected hospital characteristics (regional and urban/rural location,
teaching status and bed size).13 This yielded an average inpatient CCR of 0.337 (data not
shown), suggesting hospitals’ facility cost was approximately 34% of the facility charge
value among analysed records. HCUP does not publish CCR for NEDS data.14 The authors
estimated CCR for HCUP-NEDS records by applying the average inpatient CCR among
analysed HCUP-NIS records based on the aforementioned hospital characteristics; for
example, an injury ED visit at an urban teaching hospital in the Midwest was assigned the
average inpatient CCR for all hospitals in the HCUP-NIS analysis sample with those criteria.
13 The average CCR applied to HCUP-NEDS records was 0.396 (data not shown). PFR was
assigned to injury records by primary three-digit ICD-9-CM code and primary payer
(Medicare and Medicaid were assigned Medicaid-specific PFR, and private insurance, self-
pay, no charge, other and missing payers were assigned commercial insurance-specific PFR)
separately for ED visits and admissions using published estimates (from 2012, the most
recent available).15 If PFR was not available for a given ICD-9-CM code, the authors
applied the all-diagnosis, payer-specific adjusted average PFR.15
Each fatal injury in an ED or inpatient setting was also assigned an estimated average cost of
ambulance transport and C/ME (including autopsy) costs. An average ambulance cost of $70
was based on national survey data (2015 National Hospital Ambulatory Medical Care
Survey, the most recent available) indicating 15.1% of ED visits (all diagnoses) have
ambulance transport16 at a nationwide estimated cost of $463 per ambulance transport
(inflated17 from the reported 2010 US dollar cost of $429).18 Majority of US states require
death investigation for deaths due to injury/casualty, suicide or violence.19 An average C/ME
cost estimate of $929 (inflated20 from the reported 2004 US dollar cost of $752) was based
on a nationwide survey of C/ME offices indicating a combined annual budget of $718.5
million in 2004, when such offices were referred 956 000 deaths.21
Analysis—The authors used SAS V.9.4 to derive patient samples and Stata V.14 for
regression models. The adjusted average cost per fatal injury in an ED or inpatient setting
was estimated using generalised linear models (GLM) (Stata V.14
svy glm family(gamma)
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link(log)
) with postestimation calculation of the average of model-predicted values (in dollar
units, using Stata V.14
margins
) per injury type (ie, by mechanism, intent, body region and
nature of injury). With total ED or admission (including any preceding ED) estimated
medical cost as the dependent variable, the regression models controlled for patients’ sex
(male, female), age (years), race/ethnicity (hospitalisations only; white, black, Hispanic,
Asian or Pacific Islander, Native American, other, unknown), number of comorbidities (0, 1,
2+) diagnosed on the visit or admission record (based on Elixhauser Comorbidity Software
V.3.7; www.hcup-us.ahrq.gov) and primary payer (Medicare, Medicaid, private insurance,
self-pay, other (e.g., worker’s compensation, other government programmes), no charge,
unknown). Injury type elements were included as covariates as relevant (eg, the model of
costs among all patients with fatal cut/pierce (mechanism) injuries controlled for injury
intent—unintentional, self-inflicted, assault, undetermined, other or unknown). Based on
standard US death certificate reporting on place of death, adjusted average costs per injury
type are reported here in terms of whether a patient died in an ED or inpatient setting (table
1 for mechanism and intent and table 2 for body region and nature of injury). The number of
analysed records, estimated simple mean cost and 95% CI for simple and regression-
adjusted mean costs per injury type are reported in online supplementary tables S1-S4.
Non-fatal injuries
Data—The estimated attributable 1-year medical cost of non-fatal injuries was assessed
among patients with ED-treated injuries as reported in the MarketScan Outpatient Services
(primarily treat-and-release) and Inpatient Services (hospitalisation following ED treatment)
databases. MarketScan includes hundreds of millions of covered lives based on data from
large employers, health plans, and government and public organisations, including some
state Medicaid payers, and is not nationally representative. Patients with commercial health
insurance (including Medicare supplemental plans for enrollees >64 years old) and Medicaid
were analysed based on their first chronological ED visit during the study period with a
primary visit diagnosis of injury--or, index injury ED visit (figure 2). Because these
databases can have more than one primary diagnosis listed per patient per ED visit, the
primary visit diagnosis was defined as the primary diagnosis on the ED claim record to
which facility charges for the visit were assigned. Patients admitted following the index
injury ED visit were identified by an admission record (ie, MarketScan Inpatient Admissions
database) on the date of or day following the index injury ED visit. The total 1-year medical
payments were the sum of medical claims (reported in Market-Scan Outpatient Services,
Inpatient Admissions—an aggregated version of Inpatient Services data—and Outpatient
Pharmaceutical Claims databases) during the 365 days following (and including) each injury
patient’s index injury ED visit date (ie, varying observation dates during 2014–2016 per
patient with injury). Negative dollar value payments can exist in medical claims data (eg,
adjustments). The authors excluded injury patients with ≤$0 total payments for the total 1-
year observation period, as well as patients with capitated insurance payment plans (fee-for-
service payments are presumed to reflect the cost of care associated with particular
diagnoses in medical claims databases, while payments for patients with capitated plans
likely do not).
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To estimate the combined cost of acute and follow-up medical care attributable to non-fatal
injuries, the total 1-year medical payments of patients with injury were compared with total
1-year payments among control enrollees with no injuries during the observation period.
Patients with injury were matched to controls (SAS V.9.4
gmatch
) 1:5 using MarketScan
Enrollment Detail tables (match methods in figure 2 notes). Health insurance enrollees with
$0 medical payments can exist in medical claims data—for example, no medical visits
during a given observation period—and enrollees observed for a specific period can have
negative total payment values (eg, adjustments for services prior to the observation period).
The total 1-year medical payments for control enrollees were set to a minimum of $0.
Among combined patients with injury and controls, the 99th percentile for the total 1-year
medical payments was $117 414 and the highest value was $4.8 million; therefore, the top
one percentile was top-coded to the 99th percentile value for analysis.22Top-coding is a
common approach when medical payments—sometimes highly skewed due to a small
number of patients with very high costs—are dependent variables in a regression model.22
Analysis—The 1-year attributable cost of non-fatal injuries was estimated using individual
two-part models (Stata V.14
twopm firstpart(logit) secondpart (glm, family (gamma)
link(log)) vce (robust)
) per injury type (mechanism, intent, body region and nature of
injury), with injury patients’ and matched controls’ total 1-year medical payments starting
from the injury patient’s index injury ED visit date as the dependent variable. A two-part
model accommodated control enrollees with $0 medical payments during the observation
period—in the first part, a logistic regression model predicts the probability of >$0 medical
payments, and in the second part a GLM model assesses costs among patients with >$0
payments. The regression models controlled for all matching factors (eg, patient age, sex and
so on) as covariates in both the logistic and GLM parts. Because all patients with injury had
>$0 total 1-year medical payments, the two-part model can accommodate an injury covariate
(ie, identifying patients with injury) in the GLM, but not logistic, part of the modelling
approach. The regression-adjusted marginal cost of non-fatal injuries by type was estimated
as the marginal effect of the injury covariate (in dollar units, using postestimation Stata V.14
margins, dydx (injury
)) among all observations (patients with injury and controls).
Results are reported by injury type (table 3 for mechanism and intent and table 4 for body
region and nature of injury). The number of analysed patients with injury and controls,
simple mean and 95% CIs for total 1-year medical payments, and modelled injury cost are
reported in online supplementary tables S5 and S6. The online supplementary file also
demonstrates results for two mutually exclusive subgroups of patients with injury: patients
treated and released (T&R) from the index injury ED visit and patients admitted after the
index injury ED visit (patient counts in figure 2) (online supplementary tables S7-S10).
Group characteristics of patients with injury versus matched controls (eg, average age) are
also reported (online supplementary table S11).
RESULTS
The estimated average attributable medical cost of fatal injuries (all types combined) in ED
and inpatient settings was approximately $6880 and $41 570, respectively—these are
median values between the modestly different cost results observed among the same patients
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(n=9929 and n=40 650 survey-weighted) depending on whether costs per injury type were
modelled by mechanism and intent (table 1; $6884 and $41 605) or body region and nature
of injury (table 2; $6885 and $41 541). The cost per injury fatality in an ED ranged from
$4764 (95% CI 3913 to 5615; system-wide injuries) to $10 289 (95% CI 8210 to 12 368;
blood vessel injuries), and the range per injury fatality in inpatient settings was $31 912
(95% CI 29 123 to 34 702; unspecified head and neck injuries) to $95 295 (95% CI 74 733
to 115 857; other or multiple injuries) (tables 1 and 2 for point estimates; online
supplementary tables S1-S4 for 95% CIs).
The estimated average 1-year attributable medical cost of non-fatal injuries (all types
combined) initially treated in an ED was approximately $6620—again, this is the median for
this measure among the same patients (n=818 053 injury, n=3 975 125 control) depending
on whether costs per injury type were modelled by mechanism and intent (table 3; $6658) or
body region and nature of injury (table 4; $6587). The cost per non-fatal injury type ranged
from $1698 (95% CI 421 to 2974; other specified, classifiable injuries of undetermined
intent) to $80 172 (95% CI 46 917 to 113 427; spinal cord fractures) (tables 3 and 4 for point
estimates; online supplementary tables S5-S6 for 95% CIs). The comparable costs among
ED T&R versus ED then admitted patients were approximately $5580 and $49 670,
respectively (online supplementary tables S7-S10). Comparable ranges by injury type
among ED T&R patients were $1484 (95% CI 281 to 2687; other specified, classifiable
injuries of undetermined intent) to $40 373 (95% CI 24 874 to 55 873; lower extremity
amputations) and from $15 607 (95% CI 7805 to 23 409; upper extremity dislocation) to
$107 400 (95% CI 49 706 to 165 094; firearm assault) among admitted patients (online
supplementary tables S7-S10).
DISCUSSION
This study generated updated medical care cost estimates for US fatal and non-fatal injuries
comprehensively by injury type. Where sample size permitted, costs were estimated for each
type in two common injury classifications—mechanism/intent and body region/nature of
injury. This breadth and specificity of estimated costs were made possible through large,
nationally representative (HCUP) or multistate (MarketScan) databases containing
information on tens to hundreds of thousands (survey-weighted) of patients with injury, as
well as computing power to facilitate hundreds of consecutive regression models using
different patient samples to estimate attributable average costs. Where previous estimates of
medical costs by injury type4 relied primarily on 1 year of hospital-based data, this study
observed medical care payments for all clinical settings for 1 year among patients with non-
fatal ED-treated injuries, and compared such payments with non-injury insurance enrollees
to estimate the total 1-year attributable cost of injuries.
The range of injury types depicted in the two injury classification schemes and the range of
outcomes (fatal and non-fatal) assessed here created a broad range of estimated average
medical cost values by injury type—from approximately $1700 (non-fatal, ED-treated other
specified, classifiable, injuries of undetermined intent; table 2) to approximately $95 300
(fatal, inpatient-treated other or multiple/unclassifiable by site injuries; table 3). For context,
in 2016 the estimated simple average costs of an ED visit and hospital admission (all
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diagnoses, all dispositions) were $1917 and $20 929, respectively, reflecting the nationally
representative cost among patients aged <65 years with employer-sponsored health
insurance.23 The higher estimated costs in this study for some injury ED visits and
admissions are likely due to injury severity among visits and admissions ending in death, the
longer duration and scope of assessed services and costs for non-fatal injuries, this study’s
inclusion of older (>64 years) patients, and presumably the higher prevalence of surgical
services among patients with injury (the 2016 average cost of surgery admission from the
aforementioned comparative source was more than double the cost of medical admission23).
In presenting estimated costs for the two injury classification schemes in their entirety
(tables 1-4), this study’s results highlight that many injury types are uncommon, and
therefore medical costs for such types may be best approximated through aggregated
categories, for example, combined intent categories for a given mechanism. In such
instances, this analysis has provided regression-adjusted estimates for aggregated injury
categories (eg, cut/pierce, all intent; Tables 1 and 2), controlling for injury attributes (eg,
intent) when sample sizes even in the large databases assessed for this analysis did not
permit stratification by detailed injury type.
Limitations
This study did not investigate factors associated with higher injury costs among patients with
the same injury type and did not present estimates by geography within the USA. There is
some evidence that inpatient CCR may underestimate ED CCR.14 Patients with non-fatal
injury were classified by their first chronological injury during the observation period;
subsequent injuries during were not classified. This analysis assessed fatal injury medical
costs using hospital discharge data, which do not capture non-hospital medical costs among
patients who die in nursing homes or non-hospital hospice settings following hospital
treatment. Previous injury cost estimates assumed nursing home and hospice location injury
deaths each incurred the cost of hospital admission plus an average cost of nursing home
care; for example, the nursing home semiprivate room median cost per day ($220 in 2015
US dollars24) multiplied by the median duration of nursing home care before death (5
months25; all diagnoses, not separately available for injury diagnoses), or $33 458 per
patient for nursing home location deaths and $11 5062627 per hospice location death.4 Non-
fatal injury costs were assessed over the subsequent 1 year following an index injury ED
visit, which underestimates medical costs for injuries resulting in long-term physical
disability—for example, traumatic brain injuries and spinal cord injuries—as well as injuries
such as violent assault that result in long-term mental health consequences.91028
CONCLUSION
Fatal and non-fatal injuries in the USA are preventable and incur substantial medical costs.
Accurate information on the medical cost of injuries is important to monitor the economic
burden of injuries and help to prioritise cost-effective public health prevention activities.
Supplementary Material
Refer to Web version on PubMed Central for supplementary material.
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Acknowledgments
Funding The authors have not declared a specific grant for this research from any funding agency in the public,
commercial or not-for-profit sectors.
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What is already known on the subject
Injuries are formally classified into hundreds of types—by mechanism (eg,
fall), intent (eg, unintentional), body region (eg, head and neck) and nature of
injury (eg, fracture).
Accurate estimates of attributable medical care costs are important to monitor
the economic burden of injuries and help to prioritise cost-effective public
health prevention activities.
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Author Manuscript Author Manuscript Author Manuscript Author Manuscript
What this study adds
This study estimated average medical care costs due to fatal and non-fatal
injuries in the USA comprehensively by injury type.
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Figure 1.
Sample selection of emergency department visits and admissions for fatal injuries in the
Healthcare Cost and Utilization Project National Inpatient Sample and Nationwide
Emergency Department Sample, from 1 October 2014 to 30 September 2015. aSurvey-
weighted number of admissions or ED visits. bInjury diagnosis for the emergency
department visit (HCUP-NEDS) or inpatient admission (HCUP-NIS) defined by an injury
code (ICD-9-CM) in the primary diagnosis field. Complete data for analysis included
admission or ED visit charges, sex (male, female), age, race/ethnicity (white, black,
Hispanic, Asian or Pacific Islander, Native American, other, unknown; HCUP-NIS records
only, not reported in HCUP-NEDS), and primary payer for admission or ED visit (Medicare,
Medicaid, private insurance, self-pay, other (e.g., worker’s compensation, other government
programmes), no charge, unknown). Data sets were reweighted following exclusion of
records with missing data (eg, charges) to maintain data set representativeness. HCUP-
NEDS, Healthcare Cost and Utilization Project Nationwide Emergency Department Sample;
HCUP-NIS, Healthcare Cost and Utilization Project National Inpatient Sample; ICD-9-CM,
International Classification of Diseases, Ninth Revision, Clinical Modification.
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Figure 2.
Sample selection of patients with non-fatal ED-treated injuries in MarketScan, from 1
October 2014 to 30 September 2015. aDefined as ICD-9-CM injury diagnosis in the primary
diagnosis field from 1 October 2014 to 30 September 2015 during ED visit (variable:
SVCSCAT=xxx20) plus facility payment (variable: FACPROF) attributed to the injury
diagnosis as identified in MarketScan Outpatient Services (ie, primarily treat-and-release
patients) and Inpatient Services (ie, patients with hospitalisation following ED visits)
databases (https://www.ibm.com/us-en/marketplace/marketscanresearch-databases).
bComplete data for analysis included medical cost in the 12 months following ED injury
visit (including index injury date) >$0 (patients with injury only), sex (male, female), age
(years), race/ethnicity (white, black, Hispanic, Asian or Pacific Islander, Native American,
other, unknown; Medicaid enrollees only), region of residence (based on metropolitan
statistical area; records with ‘unknown’ but not missing value included; commercial
insurance and Medicare supplemental enrollees only), type of health plan (eg, health
management organisation) and basis for Medicaid eligibility (eg, foster care; Medicaid
enrollees only). cTo ensure controls had the appropriate observation timeline—24 months
surrounding injury patients’ index visit month—all potential control enrollees (non-injury)
in the 2015 MarketScan Enrolment Detail table were first randomly assigned an index month
(ie, values 1–12) and excluded if lacking 24 months of insurance enrolment surrounding that
index month. Next, 1:5 injury patient to control enrollee match (SAS V.9.4
gmatch
) was
requested based on index month (ie, month of index injury ED visit for patients with injury
and randomly assigned monthly for control enrollees), insurance type (commercial,
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Medicare or Medicaid), enrollee age (as reported in the data source for commercial
insurance and Medicare supplemental patients, and for Medicaid enrollees based on reported
year of birth), sex (male/female), race/ethnicity (reported in the data source for Medicaid
enrollees only), region of residence (reported in the data source for commercial insurance
and Medicare supplemental enrollees only), type of health plan, mental health and substance
abuse treatment coverage (commercial insurance enrollees only), drug coverage, Medicare
dual eligibility (Medicaid enrollees only), comorbidity count (0, 1, 2+ diagnosed in the 12
months prior to the index injury date (based on Elixhauser Comorbidity Software V.3.7) in
any clinical location reported in MarketScan), and basis for Medicaid eligibility (Medicaid
enrollees only). ED, emergency department; Hosp, hospitalised (inpatient); ICD-9-CM,
International Classification of Diseases, Ninth Revision, Clinical Modification; T&R, treated
and released.
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Table 1
Adjusted mean cost of ED visits and admissions for fatal injuries by mechanism and intent (total n=40 650 survey-weighted)
Mechanism Fatality location Unintentional Self-inflicted Assault undetermined Other Unknown All intents
Cut/pierce ED $6782 $7115
Hospital $44 244 $51 946 $52 110
Drowning/submersion ED $6351 $6462
Hospital $55 968 $59 294
Fall ED $7207 $7317
Hospital $36 568 $36 440
Fire/burn ED
Hospital $41 682 $41 985
Fire/flame ED
Hospital $42 203 $42 452
Hot object/substance ED
Hospital $38 399 $38 735
Firearm ED $6660 $6966 $6682 $6726 $6644
Hospital $51 197 $42 179 $50 636 $44 845 $44 887
Machinery ED
Hospital
Motor vehicle traffic ED $6989 $7160
Hospital $46 063 $48 157
Occupant ED $7138 $7316
Hospital $45 841 $47 934
Motorcyclist ED $6793 $6957
Hospital $47 249 $49 549
Pedal cyclist ED
Hospital $49 305 $51 420
Pedestrian ED $6947 $7117
Hospital $45 195 $46 901
Unspecified motor vehicle ED $6650 $6824
Hospital $47 129 $49 861
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Mechanism Fatality location Unintentional Self-inflicted Assault undetermined Other Unknown All intents
Other pedal cyclist ED
Hospital $46 237 $47 073
Other pedestrian ED
Hospital $40 626 $41 629
Other transport ED $7007 $7224
Hospital $45 024 $46 663
Natural/environmental ED $6903 $6987
Hospital $47 517 $48 894
Bites and stings ED
Hospital
Overexertion ED
Hospital
Poisoning ED $7163 $7113 $7199 $6507
Hospital $50 853 $48 210 $51 490 $40 646
Struck by/against ED $7220
Hospital $42 392 $52 043 $50 987
Suffocation ED $6662 $6590 $6155
Hospital $40 550 $56 838 $40 043
Other specified, classifiable ED $6897 $6609 $6537
Hospital $43 067 $39 961 $63 521 $48 203
Other specified, NEC ED
Hospital $40 694 $51 297 $48 954
Unspecified ED $6997 $7176
Hospital $44 179 $56 071 $50 569
Adverse effects ED
Hospital $39 254 $65 409
E-code missing ED $6776 $7017
Hospital $41 812 $43 541
All mechanisms ED $7150 $5890 $6921 $6106 $7961 $7004 $6884
Hospital $41 082 $34 958 $52 787 $32 255 $65 525 $43 215 $41 605
Number of records, survey-weighted number, and simple mean, SE and 95% CI for all cost estimates reported in online supplementary tables S1 and S3.
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Blank cells indicate average cost not calculated due to low number of observations (zero visits or admissions or relative SE >30% or SE=0) in the data source. ‘All mechanisms’ model controlled for
mechanism. ‘All intents’ model controlled for intent. ‘All’/’All’ model controlled for both.
Source data: Healthcare Cost and Utilization Project National Inpatient Sample and Nationwide Emergency Department Sample. Injury classification in this table based on the ICD-9-CM E-code matrix
(www.cdc.gov/nchs/injury/injury_tools.htm).
E-code, External Cause of Injury code; ED, emergency department; ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; NEC, not elsewhere classifiable; SE,
Standard error.
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Table 2
Adjusted mean cost of ED visits and admissions for fatal injuries by body region and nature of injury (total n=40 650 survey-weighted)
Body region Fatality
location Fracture Internal Open
wound Blood
vessels Contusion or
superficial Crush Burns unspecified
System-
wide and
late effects All nature of
injury
Head and neck Traumatic brain
injury ED $7001 $6986 $9141
Hospital $44 739 $40 273 $42 545
Other head, face,
neck ED $6735 $7044 $5608
Hospital $43 473 $44 642 $50 111 $43 217 $32 886 $73 042
Total ED $5843 $5954 $5597 $5937 $6373
Hospital $42 274 $38 586 $41 984 $47 074 $40 455 $31 912 $41 345
Spine and back Spinal cord ED
Hospital $42 284 $44 007 $44 731
Vertebral column ED $6341
Hospital $36 799 $39 685
Total ED $6353
Hospital $36 846 $42 494 $40 710
Torso Torso ED $7400 $6937 $6644 $7362 $6821 $8374
Hospital $35 514 $44 941 $45 456 $36 863 $44 722 $47 001
Extremities Upper
extremities ED $6577 $5671
Hospital $36 332 $45 049 $52 325
Lower
extremities ED $7125 $6818
Hospital $35 123 $33 378 $45 280 $38 832
Total ED $6334 $5583 $5965
Hospital $34 151 $38 660 $46 554 $33 368 $42 562 $39 682
Unclassifiable by
site Other or multiple ED $6540 $6818 $5643
Hospital $42 684 $95 295
System-wide ED $6861 $4764
Hospital $50 300 $32 934
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Body region Fatality
location Fracture Internal Open
wound Blood
vessels Contusion or
superficial Crush Burns unspecified
System-
wide and
late effects All nature of
injury
Total ED $5343 $5749 $5659 $4915
Hospital $40 850 $46 534 $34 123
All All body regions ED $7656 $8695 $6759 $10 289 $6419 $6693 $5872 $4782 $6885
Hospital $41 517 $43 047 $52 886 $63 067 $41 660 $68
670 $61 036 $55 398 $33 081 $41 541
Number of records, survey-weighted number, and simple mean, SE and 95% CI for all cost estimates reported in online supplementary tables S2 and S4.
Blank cells indicate average cost not calculated due to low number of observations (zero visits or admissions or relative SE >30% or SE=0) in the data source. Some nature of injury categories not shown in
this table due to no data: dislocation, sprains and strains, amputations, nerves. ‘All body regions’ model controlled for body region. ‘All nature of injury’ model controlled for nature of injury. ‘All’/’All’
model controlled for both.
Source data: Healthcare Cost and Utilization Project National Inpatient Sample and Nationwide Emergency Department Sample. Injury classification in this table based on the ICD-9-CM Barell matrix
(www.cdc.gov/nchs/injury/injury_tools.htm). ED, emergency department; ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; SE, Standard error.
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Table 3
Estimated 12-month attributable cost of medical care following emergency department treatment for all patients with non-fatal injuries by mechanism and
intent (n=818 053 injury; n=3 975 125 control)
Mechanism Unintentional Self-inflicted Assault Undetermined Other Unknown All intents
Cut/pierce $3119 $17 320 $17 709 $3435 $3322
Drowning/submersion $12 940 $13 355
Fall $9399 $5406 $9399
Fire/burn $7260 $14 002 $7431
Fire/flame $11 552 $12 325
Hot object/substance $6200 $6224
Firearm $22 805 $37 435 $21 030 $24 859
Machinery $5340 $5340
Motor vehicle traffic $9403 $9408
Occupant $7396 $7396
Motorcyclist $20 415 $20 415
Pedal cyclist $14 193 $14 193
Pedestrian $19 440 $19 440
Unspecified motor vehicle $12 054 $12 054
Other pedal cyclist $6109 $6109
Other pedestrian $9484 $9484
Other transport $11 089 $11 090
Natural/environmental $5838 $5833
Bites and stings $3307 $3307
Overexertion $5251 $5251
Poisoning $9723 $17 563 $13 521 $12 783
Struck by/against $3989 $6828 $10 293 $4146
Suffocation $8331 $19 579 $8904
Other specified, classifiable $4185 $4670 $1698 $4207
Other specified, NEC $5295 $11 121 $6294 $5508 $5411
Unspecified $7032 $26 868 $9047 $8746 $7434
Adverse effects $15 428 $15 428
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Mechanism Unintentional Self-inflicted Assault Undetermined Other Unknown All intents
E-code missing $6508 $6508
All mechanisms $6712 $18 331 $7460 $10 217 $13 967 $6508 $6658
Number of records, survey-weighted number, and simple mean and 95% CI for all cost estimates demonstrated in online supplementary table 5 S5.
Blank cells indicate average cost not calculated due to low number of observations (<21 patients with injury) in the data source. ‘All mechanisms’ model controlled for mechanism. ‘All intents’ model
controlled for intent. ‘All’/’All’ model controlled for both.
Source data: MarketScan (Inpatient Services, Inpatient Admissions, Outpatient Services, Outpatient Pharmaceutical Claims). Injury classification in this table based on the ICD-9-CM E-code matrix
(www.cdc.gov/nchs/injury/injury_tools.htm).
E-code, External Cause of Injury code; ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; NEC, not elsewhere classifiable.
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Table 4
Estimated 12-month attributable cost of medical care following emergency department treatment for all patients with non-fatal injuries by body region
and nature of injury (n=818 053 injury; n=3 975 125 control)
Body region Body
region Fracture dislocation
Sprains
and
strains Internal Open
wound Amputations Blood
vessels
Contusion
or
superficial Crush Burns Nerves Unspecified
System-
wide
and late
effects
All
nature
of
injury
Head and
neck Traumatic
brain $40 454 $7832 $9339
injury
Other
head, face, $14 334 $4697 $8767 $3790 $14
693 $4497 $11
034 $6379 $6058 $4948
neck
Total $18 751 $4697 $8767 $7832 $3790 $14
693 $4497 $11
034 $4849 $6058 $5565
Spine and
back Spinal cord $80 172 $34 546 $51
317
Vertebral
column $30 584 $22 263 $5080 $7311
Total $30 957 $22 263 $5080 $34 546 $7395
Torso Torso $19 254 $10 055 $4711 $35 223 $6424 $6306 $11
219 $6232 $8906
Extremities Upper
extremities $9936 $6010 $4214 $3416 $8531 $11
505 $4143 $2775 $4961 $9259 $4305 $5853
Lower
extremities $16 075 $13 393 $5035 $4202 $46 251 $14
161 $5397 $5829 $8894 $6419 $7218
Total $12 128 $7535 $4760 $3668 $10 025 $11
011 $4767 $3429 $5912 $9259 $5336 $6468
Unclassifiable
by site Other or
multiple $11 590 $12 502 $4990 $11 707 $6721 $4438 $5918 $3893 $7620 $6694
System-
wide $7630 $7630
Total $11 590 $12 502 $4990 $11 707 $6721 $4438 $5918 $3893 $7620 $7630 $7407
All body
regions All body
regions $13 856 $7597 $4878 $9297 $3856 $9876 $20
129 $4892 $3465 $7395 $7365 $5869 $7630 $6587
Number of records (patients with injury and control enrollees), and simple mean and 95% CI for all cost estimates demonstrated in online supplementary table 6.
Blank cells indicate average cost not calculated due to low number of observations (<21 patients with injury) in the data source. ‘All nature of injury’ model controlled for nature of injury. ‘All body
regions’ model controlled for body region of injury. ‘All/All’ model controlled for nature and body region of injury.
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Source data: MarketScan (Inpatient Services, Inpatient Admissions, Outpatient Services, Outpatient Pharmaceutical Claims). Injury classification in this table based on the ICD-9-CM Barell matrix
(www.cdc.gov/nchs/injury/injury_tools.htm). ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification.
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... Aggregated medical costs (e.g., combined intents by mechanism or combined mechanisms by place of death) from reference sources were assigned when specific estimates by intent or mechanism were not available. The average medical cost among 2019 injury deaths was approximately $15,400 † † ; however, many injury deaths had lower costs because the deaths occurred outside a health care setting (2). The cost of injury mortality includes value of statistical life, a monetary estimate of the collective value that persons place on mortality risk reduction as derived in research studies through revealed preferences (e.g., observed wage differences for dangerous occupations) or stated preferences from surveys of persons' willingness to pay for mortality risk reduction (3). ...
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Unintentional and violence-related injury fatalities, including suicide, homicide, overdoses, motor vehicle crashes, and falls, were among the 10 leading causes of death for all age groups in the United States in 2019.* There were 246,041 injury deaths in 2019 (unintentional injury was the most frequent cause of death after heart disease and cancer) with an economic cost of $2.2 trillion (1). Extending a national analysis (1), CDC examined state-level economic costs of fatal injuries based on medical care costs and the value of statistical life assigned to 2019 injury records from the CDC's Web-based Injury Statistics Query and Reporting System (WISQARS).† West Virginia had the highest per capita cost ($11,274) from fatal injury, more than twice that of New York, the state with the lowest cost ($4,538). The five areas with the highest per capita total fatal injury costs were West Virginia, New Mexico, Alaska, District of Columbia (DC), and Louisiana; costs were lowest in New York, California, Minnesota, Nebraska, and Texas. All U.S. states face substantial avoidable costs from injury deaths. Individual persons, families, organizations, communities, and policymakers can use targeted proven strategies to prevent injuries and violence. Resources for best practices for preventing injuries and violence are available online from the CDC's National Center for Injury Prevention and Control.§.
... A kórházi ellátásra szoruló térd-és lábszársérülést szenvedőknek a kórházat elhagyva általában további, akár éveken át tartó gondozásra, kezelésre is szükségük lehet. A hosszas ápolási és rehabilitációs idő mind a fiatal, mind az időskorú lakosság tekintetében további költségeket generálhat [3,21,35,36]. A járóbeteg-szakellátási forma esetében az előző évben műtéten átesett betegek is bejelentésre kerülhetnek, ezért vizsgálatunkban az aktívfekvőbeteg-szakellátás betegforgalmi és egészségbiztosítási adatait tekintettük meghatározónak. ...
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Context Costs related to criminal justice are an important component of the economic burden of injuries; such costs could include police involvement, judicial and corrections costs, among others. If the literature has sufficient information on the criminal justice costs related to injury, it could be added to existing estimates of the economic burden of injury. Objective To examine research on injury-related criminal justice costs, and what extent cost information is available by type of injury. Data sources Medline, PsycINFO, Sociological Abstracts ProQuest, EconLit and National Criminal Justice Reference Service were searched from 1998 to 2021. Data extraction Preferred Reporting Items for Systematic reviews and Meta-Analyses was followed for data reporting. Results Overall, 29 studies reported criminal justice costs and the costs of crime vary considerably. Conclusions This study illustrates possible touchpoints for cost inputs and outputs in the criminal justice pathway, providing a useful conceptualisation for better estimating criminal justice costs of injury in the future. However, better understanding of all criminal justice costs for injury-related crimes may provide justification for prevention efforts and potentially for groups who are disproportionately affected. Future research may focus on criminal justice cost estimates from injuries by demographics to better understand the impact these costs have on particular populations.
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Aim Since 2011 the Centers for Disease Control and Prevention’s Web-based Injury Statistics Query and Reporting System (WISQARS) has demonstrated per-injury average and population total medical and non-medical costs of injuries by type (such as unintentional cut/pierce) in the USA. This article describes the impact of data and methods changes in the newest version of WISQARS Cost of Injury. Methods Data sources and methods were compared for the legacy version of the WISQARS Cost of Injury website (available 2011–2021; most recent prior update was published in 2014 with 2010 injury incidence and costs) and the new version (published 2021; 2015-present injury incidence and costs). Cost data sources were updated for the new website and the basis for medical costs and non-fatal injury work loss costs changed from mathematical modelling (combined estimates from multiple data sources) in the legacy website to statistical modelling of actual injury-related medical and work loss financial transactions in the new website. Monetary valuation of non-medical costs for injury deaths changed from lost employment income and household work in the legacy website to value of statistical life. Quality of life loss costs were added for non-fatal injuries. Per-injury average medical and non-medical costs by injury type (mechanism and intent) and total population injury costs were compared for years 2010 (legacy website data) and 2020 (new website data) to illustrate the impact of data and methods changes on reported costs in the context of changed annual injury incidence. Results Owing to more comprehensive cost capture yielding higher per-injury average costs for most injury types—including those with high incidence in 2020 such as unintentional poisoning and unintentional falls—reported total US medical and non-medical injury costs were substantially higher in 2020 (US$4.6 trillion) compared with 2010 (US$693 billion) (both 2020 USD). Conclusions and relevance New data and methods increased the injury costs reported in WISQARS Cost of Injury. Researchers and public health professionals can use this information to proficiently communicate the burden of injuries and violence in terms of economic cost.
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Visual and vestibular deficits, as measured by a visio-vestibular exam (VVE), are markers of concussion in youth. Little is known about VVE evolution post-injury, nor influence of age or sex on trajectory. The objective was to describe the time trend of abnormal VVE elements after concussion. Two cohorts, 11-18 years, were enrolled; healthy adolescents (n=171) from a high school with VVE assessment prior to or immediately after their sport seasons and; concussed participants (n=255) from a specialty care concussion program, with initial assessment <=28 days from injury and VVE repeated throughout recovery during clinical visits. The primary outcome, compared between groups, is the time course of recovery of the VVE exam, defined as the probability of an abnormal VVE (>2/9 abnormal elements) and modelled as a cubic polynomial of days after injury. We explored whether probability trajectories differed by: age (<14 years vs 14+ years), sex, concussion history (0 versus 1+), and days from injury to last assessment (<28 days vs 29+ days). Overall, abnormal VVE probability peaked at 0.57 at day 8 post-injury, compared to an underlying prevalence of 0.083 for uninjured adolescents. Abnormal VVE probability peaked higher for those 14+ years, female, with a concussion history and whose recovery course was longer than 28 days post- injury, compared with their appropriate strata subgroups. Females and those <14 years demonstrated slower resolution of VVE abnormalities. VVE deficits are common in adolescents after concussion and the trajectory of resolution varies by age, sex and concussion history. These data provide insight to clinicians managing concussions on the timing of deficit resolution after injury.
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New York State's nonfatal shooting initiative provided support to police departments and district attorney's offices in two cities, Newburgh and Utica, NY: two investigators and a crime analyst dedicated to nonfatal shooting investigations, training and technical assistance, and timely forensic laboratory analysis of evidence. Evaluation findings show that the initiative positively affected the processes and outcomes of nonfatal shooting investigations. The immediate effect of the initiative was dramatic in Newburgh and less pronounced but noteworthy in Utica. In both sites, however, clearance rates declined over time, as caseloads grew. The initiative consisted of several components: a commitment to evidence‐based prosecutions; investigative personnel dedicated to nonfatal shooting cases; collaboration between investigative and prosecutorial actors. The immediate effects of the initiative suggest how successful nonfatal shooting investigations can be when they are better resourced, while the decay in the impacts over time illustrate the need to ensure that the resources are commensurate with the caseload.
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Background All data systems used for non-fatal injury surveillance and research have strengths and limitations that influence their utility in understanding non-fatal injury burden. The objective of this paper was to compare characteristics of major data systems that capture non-fatal injuries in the USA. Methods By applying specific inclusion criteria (eg, non-fatal and non-occupational) to well-referenced injury data systems, we created a list of commonly used non-fatal injury data systems for this study. Data system characteristics were compiled for 2018: institutional support, years of data available, access, format, sample, sampling method, injury definition/coding, geographical representation, demographic variables, timeliness (lag) and further considerations for analysis. Results Eighteen data systems ultimately fit the inclusion criteria. Most data systems were supported by a federal institution, produced national estimates and were available starting in 1999 or earlier. Data source and injury case coding varied between the data systems. Redesigns of sampling frameworks and the use of International Classification of Diseases, 9th Revision, Clinical Modification/International Classification of Diseases, 10th Revision, Clinical Modification coding for some data systems can make longitudinal analyses complicated for injury surveillance and research. Few data systems could produce state-level estimates. Conclusion Thoughtful consideration of strengths and limitations should be exercised when selecting a data system to answer injury-related research questions. Comparisons between estimates of various data systems should be interpreted with caution, given fundamental system differences in purpose and population capture. This research provides the scientific community with an updated starting point to assist in matching the data system to surveillance and research questions and can improve the efficiency and quality of injury analyses.
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Introduction Alcohol use remains a significant contributing factor in traumatic injuries in the United States, resulting in substantial patient morbidity and societal cost. Because of this, the American College of Surgeons Verification, Review, and Consultation Program requires the screening of 80% of trauma admissions. Multiple studies suggest that patients who use alcohol are subject to stigma by health care providers and may ultimately face legal and financial ramifications of a positive alcohol screening test. There is also evidence that sociodemographic factors may dictate drug and alcohol screening patterns among patients. Because this screening target is often not uniformly achieved among all patients presenting with injury, we sought to investigate whether there are any discrepancies in screening across sociodemographic groups. Methods We investigated the Trauma Quality Program Participant User File for all trauma cases admitted during 2017 and compared the rates of the serum alcohol screening test across different demographic factors, including race and ethnicity. We then performed an adjusted multivariable logistic regression to determine the odds ratio (OR) for receiving a test based on these demographic factors adjusted for hospital and clinical factors. Results There were 729,174 traumas included in the study. Of this group, 345,315 (47.4%) were screened with a serum alcohol test. Screening rates varied by injury mechanism and were highest among motorcycle crashes (66.0% of patients screened) and lowest among falls (32.8% of patients screened). Overall, Asian and Pacific Islander (52.5% screened), Black (57.7% screened), and other race (58.4% screened) had higher rates of alcohol screening than White patients (43.7% screened, P < 0.001). Similarly, Hispanic patients were screened at higher rates than non-Hispanic patients (56.4% screening versus 46.2% screening, P < 0.001). These differences persisted across nearly all injury categories. In multivariable logistic regression, Asian and Pacific Islanders were associated with the highest odds of being screened (OR 1.34, P < 0.001) followed by other race (OR 1.25, P < 0.001) in comparison to White patients. Conclusions There are consistent and significant differences in alcohol screening rates across race and ethnicity, despite accounting for injury mechanism and comorbidities.
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Unintentional and violence-related injuries, including suicide, homicide, overdoses, motor vehicle crashes, and falls, were among the top 10 causes of death for all age groups in the United States and caused nearly 27 million nonfatal emergency department (ED) visits in 2019.*,† CDC estimated the economic cost of injuries that occurred in 2019 by assigning costs for medical care, work loss, value of statistical life, and quality of life losses to injury records from the CDC's Web-based Injury Statistics Query and Reporting System (WISQARS).§ In 2019, the economic cost of injury was $4.2 trillion, including $327 billion in medical care, $69 billion in work loss, and $3.8 trillion in value of statistical life and quality of life losses. More than one half of this cost ($2.4 trillion) was among working-aged adults (aged 25-64 years). Individual persons, families, organizations, communities, and policymakers can use targeted proven strategies to prevent injuries and violence. Resources for best practices for preventing injuries and violence are available online from CDC's National Center for Injury Prevention and Control.¶.
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This report presents final 2017 U.S. mortality data on deaths and death rates by demographic and medical characteristics. These data provide information on mortality patterns among U.S. residents by variables such as sex, race and ethnicity, and cause of death. Life expectancy estimates, age-specific death rates, age-adjusted death rates by race and ethnicity and sex, 10 leading causes of death, and 10 leading causes of infant death were analyzed by comparing 2017 and 2016 final data (1). All material appearing in this report is in the public domain and may be reproduced or copied without permission; citation as to source, however, is appreciated.
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Child maltreatment incurs a high lifetime cost per victim and creates a substantial US population economic burden. This study aimed to use the most recent data and recommended methods to update previous (2008) estimates of 1) the per-victim lifetime cost, and 2) the annual US population economic burden of child maltreatment. Three ways to update the previous estimates were identified: 1) apply value per statistical life methodology to value child maltreatment mortality, 2) apply monetized quality-adjusted life years methodology to value child maltreatment morbidity, and 3) apply updated estimates of the exposed population. As with the previous estimates, the updated estimates used the societal cost perspective and lifetime horizon, but also accounted for victim and community intangible costs. Updated methods increased the estimated nonfatal child maltreatment per-victim lifetime cost from $210,012 (2010 USD) to $830,928 (2015 USD) and increased the fatal per-victim cost from $1.3 to $16.6 million. The estimated US population economic burden of child maltreatment based on 2015 substantiated incident cases (482,000 nonfatal and 1670 fatal victims) was $428 billion, representing lifetime costs incurred annually. Using estimated incidence of investigated annual incident cases (2,368,000 nonfatal and 1670 fatal victims), the estimated economic burden was $2 trillion. Accounting for victim and community intangible costs increased the estimated cost of child maltreatment considerably compared to previous estimates. The economic burden of child maltreatment is substantial and might off-set the cost of evidence-based interventions that reduce child maltreatment incidence.
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Introduction: This study estimated the U.S. lifetime per-victim cost and economic burden of intimate partner violence. Methods: Data from previous studies were combined with 2012 U.S. National Intimate Partner and Sexual Violence Survey data in a mathematical model. Intimate partner violence was defined as contact sexual violence, physical violence, or stalking victimization with related impact (e.g., missed work days). Costs included attributable impaired health, lost productivity, and criminal justice costs from the societal perspective. Mean age at first victimization was assessed as 25 years. Future costs were discounted by 3%. The main outcome measures were the mean per-victim (female and male) and total population (or economic burden) lifetime cost of intimate partner violence. Secondary outcome measures were marginal outcome probabilities among victims (e.g., anxiety disorder) and associated costs. Analysis was conducted in 2017. Results: The estimated intimate partner violence lifetime cost was $103,767 per female victim and $23,414 per male victim, or a population economic burden of nearly $3.6 trillion (2014 US$) over victims' lifetimes, based on 43 million U.S. adults with victimization history. This estimate included $2.1 trillion (59% of total) in medical costs, $1.3 trillion (37%) in lost productivity among victims and perpetrators, $73 billion (2%) in criminal justice activities, and $62 billion (2%) in other costs, including victim property loss or damage. Government sources pay an estimated $1.3 trillion (37%) of the lifetime economic burden. Conclusions: Preventing intimate partner violence is possible and could avoid substantial costs. These findings can inform the potential benefit of prioritizing prevention, as well as evaluation of implemented prevention strategies.
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Objectives: To estimate medical expenditures attributable to older adult falls using a methodology that can be updated annually to track these expenditures over time. Design: Population data from the National Vital Statistics System (NVSS) and cost estimates from the Web-based Injury Statistics Query and Reporting System (WISQARS) for fatal falls, quasi-experimental regression analysis of data from the Medicare Current Beneficiaries Survey (MCBS) for nonfatal falls. Setting: U.S. population aged 65 and older during 2015. Participants: Fatal falls from the 2015 NVSS (N=28,486); respondents to the 2011 MCBS (N=3,460). Measurements: Total spending attributable to older adult falls in the United States in 2015, in dollars. Results: In 2015, the estimated medical costs attributable to fatal and nonfatal falls was approximately $50.0 billion. For nonfatal falls, Medicare paid approximately $28.9 billion, Medicaid $8.7 billion, and private and other payers $12.0 billion. Overall medical spending for fatal falls was estimated to be $754 million. Conclusion: Older adult falls result in substantial medical costs. Measuring medical costs attributable to falls will provide vital information about the magnitude of the problem and the potential financial effect of effective prevention strategies.
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Health care expenditures and use are challenging to model because these dependent variables typically have distributions that are skewed with a large mass at zero. In this article, we describe estimation and interpretation of the effects of a natural experiment using two classes of nonlinear statistical models: one for health care expenditures and the other for counts of health care use. We extend prior analyses to test the effect of the ACA's young adult expansion on three different outcomes: total health care expenditures, office-based visits, and emergency department visits. Modeling the outcomes with a two-part or hurdle model, instead of a single-equation model, reveals that the ACA policy increased the number of office-based visits but decreased emergency department visits and overall spending. Expected final online publication date for the Annual Review of Public Health Volume 39 is April 1, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Introduction: This study estimated the per-victim U.S. lifetime cost of rape. Methods: Data from previous studies was combined with current administrative data and 2011 U.S. National Intimate Partner and Sexual Violence Survey data in a mathematical model. Rape was defined as any lifetime completed or attempted forced penetration or alcohol- or drug-facilitated penetration, measured among adults not currently institutionalized. Costs included attributable impaired health, lost productivity, and criminal justice costs from the societal perspective. Average age at first rape was assumed to be 18 years. Future costs were discounted by 3%. The main outcome measures were the average per-victim (female and male) and total population discounted lifetime cost of rape. Secondary outcome measures were marginal outcome probabilities among victims (e.g., suicide attempt) and perpetrators (e.g., incarceration) and associated costs. Analysis was conducted in 2016. Results: The estimated lifetime cost of rape was $122,461 per victim, or a population economic burden of nearly $3.1 trillion (2014 U.S. dollars) over victims' lifetimes, based on data indicating >25 million U.S. adults have been raped. This estimate included $1.2 trillion (39% of total) in medical costs; $1.6 trillion (52%) in lost work productivity among victims and perpetrators; $234 billion (8%) in criminal justice activities; and $36 billion (1%) in other costs, including victim property loss or damage. Government sources pay an estimated $1 trillion (32%) of the lifetime economic burden. Conclusions: Preventing sexual violence could avoid substantial costs for victims, perpetrators, healthcare payers, employers, and government payers. These findings can inform evaluations of interventions to reduce sexual violence.
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Importance: It is important to understand the magnitude and distribution of the economic burden of prescription opioid overdose, abuse, and dependence to inform clinical practice, research, and other decision makers. Decision makers choosing approaches to address this epidemic need cost information to evaluate the cost effectiveness of their choices. Objective: To estimate the economic burden of prescription opioid overdose, abuse, and dependence from a societal perspective. Design, setting, and participants: Incidence of fatal prescription opioid overdose from the National Vital Statistics System, prevalence of abuse and dependence from the National Survey of Drug Use and Health. Fatal data are for the US population, nonfatal data are a nationally representative sample of the US civilian noninstitutionalized population ages 12 and older. Cost data are from various sources including health care claims data from the Truven Health MarketScan Research Databases, and cost of fatal cases from the WISQARS (Web-based Injury Statistics Query and Reporting System) cost module. Criminal justice costs were derived from the Justice Expenditure and Employment Extracts published by the Department of Justice. Estimates of lost productivity were based on a previously published study. Exposure: Calendar year 2013. Main outcomes and measures: Monetized burden of fatal overdose and abuse and dependence of prescription opioids. Results: The total economic burden is estimated to be $78.5 billion. Over one third of this amount is due to increased health care and substance abuse treatment costs ($28.9 billion). Approximately one quarter of the cost is borne by the public sector in health care, substance abuse treatment, and criminal justice costs. Conclusions and relevance: These estimates can assist decision makers in understanding the magnitude of adverse health outcomes associated with prescription opioid use such as overdose, abuse, and dependence.
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What is already known on this topic? Each year, approximately 3 million persons are hospitalized and 27 million are treated and released in emergency departments (EDs) in the United States because of violence and unintentional injuries. Medical and work-loss costs associated with these injuries create a substantial economic burden for the health care system and the general public. What is added by this report? During 2013, the rate of nonfatal injuries treated in U.S. hospital EDs that resulted in hospitalization was 951 per 100,000, and the rate of nonfatal injuries that were treated and released was 8,549 per 100,000. Nonfatal injuries accounted for approximately $456 billion in medical and work-loss costs. The vast majority of ED-treated nonfatal injuries were unintentional. The majority of medical and work-loss costs associated with ED-treated nonfatal injuries were from falls (37% of costs) and transportation-related injuries (21% of costs). What are the implications for public health practice? Injury and violence prevention strategies can reduce a substantial source of morbidity and financial burden in the United States. Understanding how the cost burden is distributed across different mechanisms and segments of the population can allow prevention interventions to be targeted where they will have the greatest impact. The concentration of costs from falls (primarily among older adults) and transportation-related injuries suggests that a substantial proportion of costs can be avoided by implementation of prevention strategies that address these mechanisms and age groups. © 2015, Department of Health and Human Services. All rights reserved.
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Background: Violent-related (assault) injuries are a leading cause of death and disability in the United States. Many violent injury victims seek treatment in the emergency department (ED). Our objectives were to: (1) estimate rates of violent-related injuries evaluated in United States EDs; (2) estimate linear trends in ED visits for violent-related injuries from 2000 to 2010; and (3) to determine the associated healthcare and work-loss costs. Methods: We examined adults 18 years of age and older from a nationally representative survey (the National Hospital Ambulatory Medical Care Survey) of ED visits, from 2000 to 2010. Violent injury was defined using International Classification of Diseases, Ninth Revision, diagnosis and mechanism of injury codes. We calculated rates of ED visits for violent injuries. Medical and work-loss costs accrued by these injuries were calculated for 2005, inflation-adjusted to 2011 dollars using the WISQARS Cost of Injury Reports. Results: An annual average of 1.4 million adults were treated for violent injuries in EDs from 2000-2010, comprising 1.6% (95% CI: [1.5%, 1.6%]) of all U.S. adult ED visits. Young adults (18-25 years), males, non-whites, uninsured or publically insured patients, and those residing in high poverty urban areas were at increased risk for ED visits for violent injury. The one-year, inflation-adjusted medical and work-loss cost of violent inflicted injuries in adults in the United States was $49.5 billion. Conclusions: Violent injuries account for over one million ED visits annually among adults, with no change in rates over the past decade. Young black males are at especially increased risk for ED visits for violent injuries. Overall, violent-related injuries resulted in substantial financial and societal costs. Level of evidence: Level III, Epidemiological study.
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Between 2007 and 2015, Medicare hospice spending rose by 52 percent, from $10.4 billion to $15.8 billion. The rise was driven primarily by an increase in the number of patients in hospice care. Medicare spending on hospice care was $642 million, or 4.2 percent, higher in 2015 than it was in 2014. Spending and spending growth varied by geographic region and diagnosis.