Strategies to Improve External Cause-of-Injury Coding in
State-Based Hospital Discharge and Emergency Department
Recommendations of the CDC Workgroup for Improvement of
External Cause-of-Injury Coding
Joseph L. Annest, PhD1
Lois A. Fingerhut, MA2
Susan S. Gallagher, MPH3
David C. Grossman, MD4
Holly Hedegaard, MD5
Renee L. Johnson, MSPH1
Mel Kohn, MD6
Donna Pickett, MPH2
Karen E. Thomas, MPH1
Roger B. Trent, PhD7
1National Center for Injury Prevention and Control, CDC
2National Center for Health Statistics, CDC
3Tufts University School of Medicine, Boston, Massachusetts
4Group Health Cooperative, Seattle, Washington
5Colorado Department of Public Health and Environment, Denver, Colorado
6Oregon Department of Human Services, Portland, Oregon
7California Department of Public Health, Sacramento, California
The material in this report originated in the National Center for Injury Prevention and Control, Ileana Arias, PhD, Director; and the Office of Statistics
and Programming, Joseph L. Annest, PhD, Director; and the National Center for Health Statistics, Ed Sondik, PhD, Director; and the Office of Analysis
and Epidemiology, Linda Bilheimer, PhD, Director.
Corresponding preparer: Joseph L. Annest, PhD, National Center for Injury Prevention and Control, 4770 Buford
Highway, N.E., MS F-62, Atlanta, GA 30341-3717. Telephone: 770-488-4804; Fax: 770-488-1665;
Each year, an estimated 50 million persons in the United States experience injuries that require medical attention.
A substantial number of these persons are treated in an emergency department (ED) or a hospital, which collects their
health-care data for administrative purposes. State-based morbidity data systems permit analysis of information on the mechanism
and intent of injury through the use of external cause-of-injury coding (Ecoding). Ecoded state morbidity data can be used
to monitor temporal changes and patterns in causes of unintentional injuries, assaults, and self-harm injuries and to set
priorities for planning, implementing, and evaluating the effectiveness of injury-prevention programs. However, the quality of
Ecoding varies substantially from state to state, which limits the usefulness of these data in certain states.
This report discusses the value of using high-quality Ecoding to collect data in state-based morbidity data
systems. Recommendations are provided to improve communication regarding Ecoding among stakeholders, enhance the
completeness and accuracy of Ecoding, and make Ecoded data more useful for injury surveillance and prevention activities at the
local, state, and federal levels. Implementing the recommendations outlined in this report should result in substantial
improvements in the quality of external cause-of-injury data collected in hospital discharge and ED data systems in the United States and
Each year, an estimated 50 million persons in the United States experience injuries that require medical
attention, resulting in lifetime costs of more than $400 billion
(1). In 2004, injuries in the United States resulted in an
estimated 167,000 deaths, 1.9 million injury-related discharges from short-stay hospitals, and 31 million initial emergency
(ED) visits (2--4). These injuries, which represent 7% of deaths from all causes, 6% of hospitalizations, and 32% of ED
visits, constitute a substantial public health burden. During 2004--2006, an estimated 48% of injured persons requiring
medical attention received care in settings other than a hospital or an ED (e.g., outpatient clinics or physicians'
offices) (CDC, unpublished data, 2007).
Population-based injury data assist public health authorities in identifying and tracking patterns and trends in
the external causes of fatal and nonfatal injuries and in designing and implementing effective injury-prevention strategies
(5). External cause-of-injury coding (Ecoding) in statewide mortality and morbidity data systems is the standard method used
to classify injury incidents by intent (e.g., unintentional,
homicide/assault, suicide/self-harm, or undetermined) and
mechanism (e.g., motor vehicle, fall, struck by/against, firearm, or poisoning). For example, in the case of a hospitalization for which
the principal diagnosis is a femur fracture, the Ecode identifies how the fracture was caused (e.g., the person was
pushed intentionally or fell unintentionally from a ladder). Accurate information on the mechanism of injury is critical for
informing prevention programs. Because trends and patterns of injury differ from state to state, state health department_based
injury-prevention programs need state-specific data to understand and respond effectively to injury problems in their jurisdictions.
Injury mortality data are collected by the National Vital Statistics System, which is operated by CDC. Information
on Ecodes is based on the International Statistical Classification of Diseases and Related Health Problems, Tenth
Revision (ICD-10) (6,7). Mortality data are compiled each year by NCHS as a census of all deaths reported to state vital statistics
departments (7). In the United States, Ecoding has been consistently more complete for mortality data than for morbidity data
because states require that the external cause of death be listed as the underlying cause on a death certificate issued for an
injury-related death. For example, if a person were in a fatal car crash and suffered a severe traumatic brain injury, the underlying
cause-of-death would be the motor-vehicle crash rather than the brain
injury. The Ecode for a fatal injury is assigned by state
and federal vital records programs on the basis of cause-of-death information submitted on death certificates. If a death
certificate is submitted without the information needed to assign a code, state vital records programs return the certificate to the
certifier who submitted it and request more information. This quality-control process ensures that Ecodes are assigned for all
deaths from injury. During 1999--2004, the underlying cause of death was coded as "unspecified cause" for only 6% of all
Although external cause-of-injury mortality data can be helpful for setting priorities and making policy
decisions regarding injury prevention, these data are not a good surrogate for injury morbidity data
(4,8). The leading causes of nonfatal injury-related ED visits, injury hospitalizations, and injury deaths differ substantially
(Table 1 and Figure 1). Whereas motor-vehicle crashes are the leading cause of injury deaths, falls are the leading cause of injury hospitalizations and ED visits
(Figure 1). In addition, the distributions of fatal
and nonfatal injuries and the number of nonfatal injuries relative to deaths vary
by external cause of injury (Table 1). For
instance, the ratio of nonfatal ED visits to deaths differs for motor-vehicle traffic
injuries (90 nonfatal ED visits per death) compared with poisonings (40 nonfatal ED visits per death).
For injury morbidity data, information on external causes of injury is coded using the
International Classification of Diseases, Ninth Revision, Clinical
Modification (ICD-9-CM) (9) and entered into the state's electronic hospital discharge data
system (HDDS) or hospital ED data system (HEDDS). However, not all states have such data systems. For those with these
data systems, the completeness and specificity of Ecodes for injury-related hospitalizations and ED visits vary substantially
across states, limiting the usefulness of the Ecoded data available for certain states
(10). Lack of Ecoding in state morbidity
data also affects national injury statistics from federal data systems that derive their data from a sample of U.S. hospitals, such
as the National Hospital Discharge Survey (i.e., 37% of injury hospital discharges with missing Ecodes) and the
National Hospital Ambulatory Medical Care Survey (i.e., 10% of injury ED visits with missing Ecodes)
(Table 1 and Figure 1). In contrast, certain states (e.g., Massachusetts and New York) have almost complete Ecoding for hospitalizations and ED
visits, ensuring that useful data on both fatal and nonfatal injuries are available for prevention program planning and
evaluation (Tables 2 and 3).
Although state HDDS and HEDDS data are used primarily for administrative and billing purposes, these systems
provide the best available data sources on external cause of injury for measuring the impact of nonfatal injury on society. For
example, falls are the leading cause of injury morbidity among persons aged
>65 years (2,4). As the U.S. population continues to
age, states can benefit from monitoring fall-related morbidity among older persons to assess changes in health-care use and
cost and in the effectiveness of fall-prevention strategies
This report discusses the role of Ecodes in injury prevention and practical strategies to improve Ecoding in statewide
HDDS and HEDDS data systems. The CDC workgroup recommendations contained in this report outline feasible steps
jurisdictions can take to improve the collection and availability of complete, specific, and high-quality Ecodes for use in injury
surveillance and prevention efforts within all states, the District of Columbia, and U.S. territories. Implementing these recommendations
can enhance the usefulness of state-level injury morbidity data for injury prevention program planning and implementation,
priority setting, and policy setting for government and nongovernment organizations. Previous studies have demonstrated that the
public health benefits will substantially outweigh the estimated economic costs of Ecoding
Initial efforts to improve Ecoding in statewide hospital discharge data systems were made in the early to mid-1990s,
but progress toward complete and accurate Ecoding in all states has been limited
(10,17,18). In 2007, the Council of State
and Territorial Epidemiologists (CSTE), the Injury Control and Emergency Health Services Section of the American Public
Health Association (APHA-ICEHS), the State and Territorial Injury Prevention Directors Association (STIPDA), the Society for
the Advancement of Violence and Injury Research (SAVIR), and the Association of State and Territorial Health
Officers (ASTHO) issued position statements calling on CDC to develop strategies to improve Ecoding completeness and
specificity in state hospital discharge databases
CSTE asked CDC to take a leadership role in assembling an expert workgroup to recommend strategies to improve
Ecoding in state hospital discharge databases. A workgroup of injury data experts from CDC, Tufts Medical School,
state health departments, and other health professionals was established to provide recommendations for practical strategies
for improving Ecoding. Members of the workgroup are associated with CSTE, SAVIR, and STIPDA. Because multiple
states have indicated interest in establishing HEDDS in addition to HDDS, the workgroup decided to include in this report
efforts to improve Ecoding in both statewide hospital discharge and ED data systems.
CDC has a history of working in collaboration with CSTE, SAVIR, and STIPDA on Ecoding and other projects
to improve the usefulness of statewide HDDS and HEDDS data. STIPDA, in collaboration with CDC, CSTE, and SAVIR,
has endorsed efforts to improve Ecoding by providing guidelines for injury surveillance in state health departments
(24,25). The most recent STIPDA report provided a comprehensive guide that addresses key aspects of injury surveillance,
including coding issues, data base management, quality assurance, data linkage, data reporting and dissemination, staffing, training,
and partnerships (25). That report made recommendations regarding measures to establish and maintain ongoing state
injury surveillance but did not discuss specific strategies for improving Ecoding and subsequent Ecoded data. The
strategies outlined in this report will therefore extend and help in the implementation of STIPDA's recommendations.
The CDC workgroup used a consensus process to develop recommended strategies for improving Ecoding. First,
the workgroup reviewed key recommendations in the most
recent STIPDA report (25) and those in earlier position
statements (19--23). Next, the workgroup developed a detailed outline of the report with draft strategies. The workgroup co-chairs
wrote a first draft of the manuscript, which was sent to workgroup members for review and comment. The report sections
and recommended strategies then were extensively discussed via e-mail and conference calls during August and September 2007
to arrive at a consensus. The final draft of the report was then reviewed by other state public health officials and
other surveillance experts at CDC. Minor modifications were made as a result of these additional reviews before the report
E-Coding in Morbidity Data Systems
ICD-9-CM is the standard classification system used for morbidity reporting in the United States
(9). ICD-9-CM is used to classify all diseases, injuries, and their external causes in health-care records and surveys so they can be reported
uniformly across institutions and jurisdictions. ICD-9-CM codes assigned in health-care records for diseases, injuries, and
health conditions also are used as the basis for prospective payment to hospitals, other health-care facilities, and health-care
providers. Nationally and in the majority of states, Ecodes are not used in determining reimbursement.
The U.S. Department of Health and Human Services (DHHS) has developed ICD-9-CM guidelines for assigning
diagnosis and Ecodes (9). These guidelines are reviewed
annually by the cooperating parties (the American Hospital Association,
American Health Information Management Association, the Centers for Medicare and Medicaid Services [CMS], and
CDC). Certain states (e.g., California and New York) with mandated Ecoding have developed additional guidelines, which are
not always consistent with the national guidelines.
In hospital settings, health information specialists are
responsible for assigning Ecodes on the basis of the
national guidelines or those mandated by their state. Certain states (e.g., California, Minnesota, and South Carolina) have
ongoing quality-assurance practices, in certain cases tied to reimbursement or penalties, aimed at monitoring and maintaining
the completeness and validity of Ecodes in their statewide HDDS and HEDDS systems. However, the majority of states
lack policies or adequate resources to implement ongoing quality-assurance practices that would ensure high quality Ecoding.
Ecodes are structured to capture information on the intent and mechanism of injury. These circumstances usually
are designated in the first three digits of the code (e.g., E884: unintentional fall from one level to another). For certain causes,
the three-digit code is followed by a decimal and a fourth digit (e.g., E884.0: unintentional fall from playground equipment)
that identifies more specific circumstances of the
ICD-9-CM external cause-of-injury classification guidelines for an injury specify that health information specialists assign
as many Ecodes as necessary to explain the cause, intent, and place of occurrence of the injury incident fully
(26). However, in practice, Ecoding of hospital records often is incomplete, and the Ecodes that are assigned lack specificity because
of insufficient documentation in the medical chart and lack of designated fields for recording Ecodes in electronic data
systems. To ensure that the Ecodes assigned are as specific as allowed by the ICD-9-CM Ecode set and coding guidelines,
the physician or other health-care provider must provide
adequate documentation in the medical record of details
regarding the incident (e.g., mechanism, intent, location, and activity at time of injury), the hospital health information specialist must
view that information and assign specific Ecodes, and the Ecodes must be recorded
accurately and appropriately in the database. Injury experts have recognized that this process could be facilitated by
including designated fields for at least three Ecodes
(for the immediate cause, the precipitating cause [i.e., the cause that started the chain of events that led to the injury, such as
being struck by an object that precipitated a fall or vise versa], and the place of occurrence [e.g., at home or on the street
or highway]) in the software used to capture medical information in these data systems
(25). However, the majority of states currently have only one designated field in their HDDS for
recording Ecodes; a few states have two designated fields; and
a few states have no designated Ecode field and record E-codes in the existing
diagnosis fields only (10). Experts also
have recognized that because a trend exists in the United States toward uniform use of electronic health and patient records
for administrative and billing purposes, creating a designated space on electronic forms to record a brief but informative
narrative by physicians and other health-care providers regarding the circumstances of the injury incident could facilitate good
E-Coding in States
Information on the status of Ecoding in state data systems has been published previously
(10) and was updated in October 2007 (STIPDA, unpublished data, 2007). In 2007, only five U.S. states (Alabama, Idaho, Missouri, North Dakota, and
South Dakota) did not have a statewide HDDS database in place. The District of Columbia (DC) and 41 states routinely
collect some level of Ecodes; 26 (63%) states and DC mandated Ecoding in their statewide HDDS database
(Figure 2), and 27 (54%) states and DC had an HEDDS database. DC and 25 (93%) states reported routine collection of some level of
Ecodes, and 18 (72%) states mandated Ecoding in their statewide HEDDS
Ecoding in the majority of state databases is incomplete. A survey conducted in 2004 reported that of 32 states that
evaluated hospital records, 14 (44%) had Ecoded
>90% of their injury-related hospitalizations; results varied for the other 18 states
(range: 51%--89%) (10). Even among states with a high percentage of Ecoded hospital records, assigned Ecodes
often lack specificity. If health-care providers do not understand why specific information needed for Ecoding is
important, documentation in the medical record can be inadequate; this can lead to overuse of the unspecified Ecodes, such as those for unspecified fall
(E888.9) or a motor-vehicle traffic accident of an unspecified nature (E819)
(28). Unspecified Ecodes do not provide adequate
detail needed for injury prevention.
Despite limitations associated with lack of completeness and specificity of Ecoding, CDC and certain states,
in collaboration with CSTE, STIPDA and state partners, have published annual state injury indicator reports that contain
injury mortality and morbidity data from participating states' data systems
(29--31). States with injury program
grants from CDC are required to submit statewide HDDS data annually for inclusion in the annual report. All other
states and territories are invited and encouraged to participate; 34 states participated in the most recent annual report
(31). These reports have been used for comparison of injury patterns among states and have resulted in improved communication
among states regarding injury-prevention efforts and efforts to improve statewide HDDS and HEDDS Ecoding
(31). On the basis of data from annual state injury indicators reports
(31), four states (Hawaii, Kansas, Oklahoma, and
Oregon) increased completeness of external cause coding
>20% during 1999--2004 (Table 4). Impetuses for improvement in these states
included legislative initiatives, policy changes at hospitals, training of medical records coders, and increased awareness of
health-care providers and health information specialists
regarding the value of high-quality Ecoded data.
Certain states without Ecoding mandates from either state legislatures or hospital associations (e.g., Colorado,
Minnesota, and Oregon) have relatively high rates of external cause coding (i.e., >84% completeness) (Table 2). Colorado serves as
an example of how factors other than mandates can improve
the completeness and accuracy of external cause coding.
Colorado's HDDS is managed by the Colorado Health and Hospital Association (CHHA). In 1997, state health
department staff began working with CHHA to encourage hospitals to assign Ecodes to appropriate hospital discharge records. CHHA
approached medical records coders through their trade organization to outline how injury prevention
activities conducted by state and local health departments and local groups could benefit by having access to Ecoded data. CHHA also pointed out to
hospital chief executive officers that submitting Ecoded data would meet the hospital's
requirement to report various conditions to the health
department. For example, Colorado requires hospitals to
report data to the statewide trauma registry. For
certain hospitals, reporting Ecoded hospital discharge data to the state hospital association would meet the state's trauma
registry reporting requirement, thereby saving the hospital from the need to develop an additional system for reporting
injured patients to the trauma registry. During the next several years, CHHA staff, the state epidemiologist, and staff from
the injury epidemiology program at the state health department met regularly with medical records coders to discuss
the completeness and accuracy of Ecodes. The hospital association newsletter reported rates of Ecoded data by hospital
and highlighted the hospitals that showed the most improvement. In 2003, when a comprehensive report on injury in Colorado
was prepared, health department staff reviewed the results in advance with members of the hospital association and coders'
trade organization. The contributions of the medical records coders and hospitals in providing complete and comprehensive
Ecodes for data analysis were acknowledged in the report.
Challenges to Improving the Quality and Accessibility of E-Coded Data
Strategies are needed to improve quality assurance (QA) procedures used by states to evaluate Ecoding. QA practices
vary by state; the majority of states do not evaluate Ecoded HDDS and HEDDS data routinely for completeness, specificity,
and accuracy (10). Ongoing evaluation of the quality of Ecodes is needed to ensure consistency in completeness, specificity,
and accuracy of Ecoding among all participating hospitals over time. States have increasing interest in using electronic health
and patient records and in integrating medical care and billing data systems. This trend might encourage vendors to
develop standard QA procedures and adapt them into database management software that would provide automated systems to
assist coders in assigning Ecodes.
One problem with the quality of Ecoding in state databases is accuracy, as measured by percentage agreement in
codes based on record reabstraction studies. Accuracy of ICD9CM Ecodes in hospital discharge records has been examined in
the United States and internationally. The level of inaccurate coding for Ecodes (i.e., those with at least four digits) was 13%
in the hospital discharge data system in Washington state in 1996
(28), 18% in the National Minimum Data Set in
New Zealand during 1996--1998 (32), and 16% for the
Victorian Inpatient Minimum Database in Australia during
1993--1994 (33). Although Ecodes were found to be reliable for reporting injury data by broad groupings (e.g., falls,
motor vehicle traffic, poisoning, assault, and self-harm), a substantial lack of accuracy was reported in that part of the Ecode that identifies
specific circumstances of an injury incident. The New Zealand study determined that the level of incorrect coding was similar for
large and small hospitals (32). A recently published study of accuracy of Ecoding in an ED setting determined that coding
was accurate for 65% of probable work-related injuries and 57% of nonwork-related
A study conducted in Oregon to assess methods for
improving the quality of Ecoding and to identify potential
barriers indicated that certain hospitals reported not having enough space on the electronic billing form to document circumstances
of the injury event adequately. The majority of hospitals included in the study used software purchased from commercial
that was not modifiable to capture the information needed to assign specific Ecodes. Hospital reimbursement also was
a potential deterrent to adequate Ecoding; not all hospitals understood the need for accurate Ecoding because Ecoding
does not affect reimbursement. Hospital administrators also expressed concern that reporting Ecodes might alert an
insurance company to the possibility that a third party was liable for the cost of care, possibly triggering an investigation that
would delay payment to the hospital. Another issue that researchers initially thought could be a barrier was the cost of
assigning Ecodes; however, the study indicated that the cost of Ecoding was minimal (an estimated $0.08 per Ecode
assigned) (Oregon Department of Human Services, unpublished data, 2002).
As discussed earlier in this report, accurate and specific Ecoding requires that medical records contain
sufficient detail regarding injury circumstances (e.g., "fell down stairs while working and hit head" rather than simply "hit
head"). However, anecdotal evidence indicates that health-care providers might not record these details because they 1) see no
reason to do so (care not being affected by these details), 2) have no financial incentive to do so (the information not
being required for reimbursement), 3) are concerned about stigmatizing the patient (e.g., by documented suicidal behavior or drug use), or
4) do not understand the importance of documenting injury circumstance information in the chart for public health
purposes. In addition, sometimes health-care providers simply are unable to determine the details of the circumstances. For example,
a person who is discovered unconscious on the ground might not be able to provide any information as to how a head
In certain states, Ecoded data are not easily accessible. Certain HDDS and HEDDS databases are operated
by nongovernment organizations that view these data as proprietary and do not necessarily wish to provide ready access
to statewide administrative data by state health department officials or prevention program directors
(10). In other states, these systems are operated by state health departments, which are willing to provide ready access to Ecoded injury data but
might not have adequate resources to prepare and manage public-use data files and web-based query systems
Uses of ECoded Data for Injury Prevention Decision Making
States with quality Ecoded HDDS data provide public health authorities with key data on the injury burden that help
to facilitate better decision making for injury prevention
(35). Collection and ready access to complete and reliable
Ecoded injury data have assisted federal, state, and local public
health authorities in making data-driven decisions regarding
public health policy and in setting priorities
(8). Public health authorities have used high-quality injury morbidity data on
health-care use and costs associated with specific external causes of injury to estimate the impact of targeted, cause-specific prevention
efforts on the health-care system and society
Local hospital community health programs have used
external cause-of-injury data to target the causes of specific injuries
in their communities and make strategic decisions regarding
where services should be offered. For example, in 1989,
the Massachusetts Department of Health partnered with Cape Code Hospital, which had a high level of Ecoding, to
summarize hospital discharge data by age. Falls among older adults were the primary cause of hospitalization in this area, which had
a high percentage of retirees. Hospital staff met with staff of local organizations that provided services to older adults
to integrate prevention of falls into the routine services of these agencies. In addition, on the basis of an analysis of the data,
the state health department channelled funds from an Office of Disability Prevention grant to a local agency to conduct
home visits focused on fall prevention among older adults (Holly Hackman, MD, Massachusetts Department of Health,
personnel communication, 2007).
Health officials in local jurisdictions have used population-based injury morbidity data to evaluate injury
prevention efforts (14). The California Department of Public Health has used Ecoded HDDS data to describe nonfatal drowning
in swimming pools and spas among toddlers. Ecoded data were used in 1995 to describe nonfatal drowning rates,
demographic risk factors, and hospital charges
(38). A later study compared drowning deaths with hospitalized nonfatal drowning cases
to calculate a fatality-to-case ratio of 1:3.5
(39). Partly as a result of these and other uses of Ecoded HDDS data, cities,
counties, and the state began enacting pool safety requirements. For instance, in 1998, California enacted the Swimming Pool Safety Act
to create a uniform statewide construction standard for safety devices for family pools and spas.
Beginning in 1998, the Colorado Department of Public Health and Environment (CDPHE) used Ecoded data on
deaths and hospitalizations to analyze the burden of suicide and nonfatal self-harm injuries, leading to the establishment of an
Office of Suicide Prevention (OSP) within CDPHE in 2000
(40). In 2006, OSP used information from Ecoded data in
federal funding for suicide prevention work, including funds from the Garrett Lee Smith Memorial Act. The analysis
of Ecoded data identified differences in the populations at risk for suicide compared with nonfatal self-harm
hospitalizations. In Colorado, for example, the suicide rate was determined to be highest for men aged
>65 years, whereas the rate of nonfatal
self-harm hospitalization was determined to be highest for women aged 18--24 years (Colorado Department of Public Health
and Environment, unpublished data, 2007) (2).
Quality Ecoded data in statewide HDDS and HEDDS also have been used by federal agencies that collect and use
state injury data to monitor trends, set priorities for funding prevention programs, and assess program effectiveness
in reducing nonfatal injuries. For example, CDC uses Ecoded injury data from statewide HDDSs in its annual state
injury indicators report to measure improvements in injury surveillance capacity of state grantees
(29--31). CDC also collects external cause-of-injury data in national morbidity data systems used widely by federal and state agencies for public
health policy decisions, including the National Hospital Discharge Survey, the National Hospital Ambulatory Medical Care
Survey, and the National Health Interview Survey
(4). The Agency for Healthcare Research and Quality (AHRQ) has established
a nationwide inpatient sample and makes available statewide hospital discharge and ED data sets as part of its Healthcare
Cost and Utilization Project (HCUP) (41). These surveys and data sets include Ecodes (with the same limitations of
accuracy, specificity and completeness as statewide HDDSs and HEDDSs) and are made available for analysis by public
health researchers, medical researchers, economists, and others interested in health-care utilization, patient safety, and medical
care cost issues (12,42). The Health Resources and Services Administration (HRSA) Maternal and Child Health Bureau
uses available Ecoded data at the state and national levels to set program objectives targeting injury prevention among
children (43). The National Highway Traffic Safety
Administration (NHTSA) collects Ecoded data from ED and hospital
discharge records as part of its state-based Crash Outcome Data Evaluation System (CODES) to help make policy decisions aimed
at reducing motor-vehicle traffic-related injuries
Professional organizations and other nonprofit entities (e.g., the American College of Emergency Physicians, the
American College of Surgeons [ACS], the American Academy of Pediatrics, the American Medical Association, the National
Safety Council, the Suicide Prevention Action Network, Safe Kids, the Home Safety Council, the American Trauma Society,
CSTE, STIPDA, and SAVIR]) use Ecoded data in their injury prevention activities. For example, ACS has established a
National Trauma Data Bank (NTDB) that contains trauma registry data from approximately 700 U.S. trauma center hospitals
located across the country (45). Participating trauma centers routinely collect Ecodes in their trauma registries, and these
external cause-of-injury data are required for submission to NTDB
(45). CDC also has worked with the ACS Committee on
Trauma to establish a national sample of trauma centers that submit data to NTDB
(45). CDC data are made available to medical
and injury researchers to assess the quality of trauma care and to characterize injured patients, injury circumstances, injury
severity, and health outcomes. The uses of Ecoded data in statewide HDDS and HEDDS complements those from trauma
registries of severe trauma patients treated in trauma centers by characterizing a broader representation of the
injured patient population.
Ecodes also have been used by automobile insurance companies, health plans, health-care purchasers, and other
private entities interested in injury prevention and safety issues (e.g., identifying causes associated with injuries to workers in
the workplace and their families outside of the workplace and causes associated with injuries in motor-vehicle crashes).
Ecoded statewide HDDS and HEDDS data have been used to help identify key causes of injuries requiring medical attention
that could be addressed by implementing safety measures and policies, which has resulted in cost savings to these companies.
For example, hospital discharge data from the Healthcare Cost and Utilization Project -- Nationwide Inpatient Sample
(HCUP-NIS) were used to estimate the cost of fall-related hospitalizations in the United States
Recommended Strategies for Improving ECoding
The workgroup made the following recommendations to improve Ecoding in statewide HDDS and HEDDS databases.
Improve Communication Among Stakeholders Regarding ECodes
CDC should facilitate a federal effort involving agencies with relevant research, programmatic, and regulatory activities
in injury prevention (e.g., AHRQ, CMS, the National Institutes of Health, HRSA, NHTSA, the Bureau of Labor Statistics,
the U.S. Fire Administration, the U.S. Department of Defense, and the Veteran's Administration) to
- discuss the need and uses of high-quality Ecoded nonfatal injury data for interagency collaborative efforts in
injury prevention, and
- assess the inclusion of Ecodes in federal morbidity data systems, surveys, and data standards to facilitate routine
collection of high-quality Ecodes in statewide HDDS and HEDDS databases.
In collaboration with CMS and state health departments, CDC should explore the possibility of linking Ecodes
to uniform billing procedures used for reimbursement in
government health insurance systems.
CDC should facilitate a meeting of state and federal injury surveillance and prevention experts with representatives from
the health plan industry; medical, nursing, and hospital
administrators' professional associations; and other
health-care professional organizations to
- discuss how Ecoding and injury surveillance can be
better used to drive injury prevention efforts in health-care settings,
at work, and at home;
- solicit ideas and facilitate dialogue with these representatives regarding the efforts needed to improve Ecoding in HDDS
- discuss efforts to make narrative documentation and
coding of external cause of injury required data elements in
electronic health and patient record systems and associated forms and software;
- discuss how to work with electronic health record vendors to facilitate integration of plain language Ecode dictionaries
into software for easy point of care coding; and
- demonstrate the potential business case for Ecoding, from a health-care provider and purchaser perspective, such as
using Ecoded data to assess health-care system demands and costs of care associated with specific causes of injury (e.g., falls
among older adults in nursing homes);
In collaboration with STIPDA and CSTE, CDC should help facilitate implementation of the new STIPDA
Injury Surveillance Workgroup recommendations for injury surveillance in all state and territorial health departments
- examining the use of financial incentives, enforcements, and mandates to improve the completeness and specificity of Ecoding, and
- developing methods to track improvement in the completeness, accuracy, and specificity of Ecodes in HDDS and
HEDDS among states and territories.
CDC, through the International Collaborative Effort on Injury Statistics, a group of international data experts whose
focus is on the standardization of injury data
(46), should communicate and share ideas and methodologies on improving
external cause coding in morbidity data system with
international injury data experts and researchers, WHO
injury prevention program representatives, and other interested groups.
Improve Collection of ECodes
In collaboration with STIPDA and CSTE, CDC should develop uniform methods to improve Ecoding through
cost-effective quality assurance practices and evaluation, considering effective approaches already in place in certain states.
Activities should include the following:
- CDC should develop uniform quality assurance practices (e.g., methods for ongoing evaluation to monitor
completeness, accuracy and specificity of Ecodes) to ensure high-quality Ecodes and require demonstration of these practices in
injury surveillance capacity-building cooperative agreements with states.
- State injury prevention programs should conduct
ongoing evaluation to assess the completeness, accuracy, and specificity
of Ecoding in hospitals within their jurisdiction.
- State injury prevention programs should provide feedback to data providers regarding the quality and usefulness of Ecoded data (e.g., reports of the completeness and
accuracy of Ecoded data from their hospital; written
reports to clinicians, coders, and hospital administrators showing how the data are being used).
CDC, in collaboration with STIPDA and CSTE, should develop training curricula for use in educational institutions
(e.g., medical schools, nursing programs, health information specialist programs) and hospitals (e.g., continuing education)
aimed at raising the awareness of physicians, nurses, health information specialists, and health plan and hospital
administrators regarding their role in improving external cause-of-injury data, including training curricula for
- physicians and nurses on methods to document circumstances (i.e., who, what, when, where, and how) of injury incidents
in the medical record,
- health information specialists with specific examples of how Ecodes are used and the need for accuracy and
specificity in Ecoding, and
- hospital and health plan administrators regarding the importance of high quality Ecoded data for injury- and
violence-related public health surveillance and prevention activities, and the need for hospital policies aimed at
requiring high quality Ecoded data.
CDC, in collaboration with STIPDA and CSTE, should work with professional organizations of clinicians, nurses,
medical records specialists, and health plan and hospital
administrators to develop incentives and approaches to training their
members on their role in collecting high quality external
Improve the Usefulness of ECoded Data for Injury Prevention Efforts
CDC should engage in activities with state epidemiologists and state injury prevention directors to educate
health-care workers, hospital association members, health plan staff, and the public regarding the uses of Ecoded data for
State health departments should work with local health
departments to develop and implement approaches,
using local nonfatal injury data, to highlight injury as a public health concern and the importance of injury prevention in
All state health departments with an existing statewide HDDS should participate in CDC's Injury Indicators Project to
help improve communication among states on the use of Ecoded data for injury prevention efforts.
State health departments should develop and implement methods for timely and easy access to Ecoded data by
policy makers, program planners, researchers, and the public through the internet (e.g., reports, slide sets, fact sheets, and
web-based query systems) (25).
Ecodes can provide data to guide public health decisions to reduce injuries and health-care costs in the United
States. Improving Ecoding in state-based hospital discharge and ED data systems is likely to help overcome current limitations
of external cause-of-injury data in many states as a result of
inadequate completeness and specificity. The strategies
recommended in this report could facilitate communication among federal, state, and nongovernment stakeholders
to determine collaborative approaches and methods for improving Ecoding in these administrative data systems. These
strategies are designed to improve data collection, coding, QA practices, analysis, reporting, and dissemination of Ecoded data to
policy makers, public health professionals, and the public. The goal is to have high-quality morbidity data by external cause of
injury from all states and U.S. territories for use in monitoring trends, characterizing patterns, setting priorities for injury
prevention programs, and assessing health-care costs to reduce the burden of injury in the United States.
Lessons learned in efforts to improve the quality and usefulness of Ecoded data from state-based morbidity data
systems have pertinence to the World Health Organization's (WHO) Health Metrics Network (HMN) and its global
initiatives to improve health data systems in developing countries
(47). QA practices that have been demonstrated to be effective
in collecting high-quality Ecoded data in statewide HDDS and HEDDS databases could be recommended for inclusion in
the HMN global initiatives.
This report is based, in part, on data contributed by H Hackman, MD, Division of Violence and Injury Prevention,
Massachusetts Dept of Public Health; B Hume, MPH, M McKenna, MPH, Injury Surveillance Program, Massachusetts Dept of Public
Health; M Bauer, MS, S Hardman, Bur of Injury Prevention, New York State Dept of Health.
- Corso P, Finkelstein E, Miller T, Fiebelkorn I, Zaloshnja E. Incidence and lifetime costs of injuries in the United States. Inj Prev 2006;12:212--8.
- CDC. Web-based Injury Statistics Query and Reporting System
(WISQARS). Atlanta, GA: US Department of Health and Human
Services, CDC; 2007. Available at
- Kozak LJ, DeFrances CJ, Hall MJ. National hospital discharge survey: 2004. Annual summary with detailed diagnosis and procedure data.
Vital Health Stat 2006;13(162):38.
- Bergen G, Chen L, Warner M, Fingerhut LA. Injury in the United States, 2007 chartbook. Hyattsville, MD: US Department of Health
and Human Services, CDC, National Center for Health Statistics; 2008.
- CDC. Surveillance for fatal and nonfatal injuries -- United States, 2001. In: Surveillance Summaries, September 3, 2004. MMWR 2004;53 (No. SS-7).
- World Health Organization. International statistical classification of diseases and related health problems. Vol. 1. 10th Rev. Geneva,
Switzerland: World Health Organization; 1992.
- Miniño AM, Heron MP, Murphy SL, Kochanek KD. Deaths: final data for 2004. Natl Vital Stat Rep 2007;55:1--120.
- US Department of Health and Human Services. Healthy people 2010 (conference ed. in 2 vols). Washington, DC: US Department of Health
and Human Services; 2000. Available at http://www.healthypeople.gov.
- CDC. Clinical modification, (ICD-9-CM). In: International classification of diseases. 6th ed. 9th rev. Hyattsville, MD: US Department of
Health and Human Services, CDC; 2007. Available at
- Abellera J, Annest JL, Conn JM, et al. How states are collecting and using cause of injury data: 2004 update to the 1997 report. Atlanta,
GA: Council of State and Territorial Epidemiologists; 2004. Available at
- CDC. Fatalities and injuries from falls among older adults -- United States, 1993--2003 and 2001--2005. MMWR, 2006;55:1221--4.
- Stevens JA, Corso PS, Finkelstein EA, Miller TR. The costs of fatal and non-fatal falls among older adults. Inj Prev 2006;12:290--5.
- CDC. Falls among older adults: figures and maps. Atlanta, GA: US Department of Health and Human Services, CDC; 2006. Available at
- Wadman MC, Muelleman RL, Coto JA, Kellermann AL. The pyramid of injury: using ecodes to accurately describe the burden of injury.
Ann Emerg Med 2003;42:468--78.
- Rivara FP, Morgan F, Bergman AB, Maier RV. Cost estimates for statewide reporting of injuries by E coding hospital discharge abstract data
base systems. Public Health Rep 1990;105:635--8.
- Bonnie RJ, Fulco CE, Liverman CT, eds. Reducing the burden of injury: advancing prevention and treatment. Washington, DC: National Academy Press; 1999.
- Annest JL, Conn JC, McLoughlin E, Fingerhut LA, Pickett D, Gallagher S. How states are collecting and using cause of injury data.
American Public Health Association; 1998.
- Gallagher S. E codes: the missing link in injury prevention. Newton, MA: EDC; 1994.
- Council of State and Territorial Epidemiologists. Position statement 07-INJ-01 Improving external cause coding in hospital discharge data.
- American Public Health Association. Position statement: improving external cause coding in hospital discharge data. Washington, DC:
American Public Health Association. 2008. Available at
- State and Territorial Injury Prevention Directors Association. Policy resolution; improving external cause coding in hospital discharge data.
Marietta, GA: State and Territorial Injury Prevention Directors Association.; 2007. Available at
- Society for the Advancement of Violence and Injury Research. Policy resolution: improving external cause coding in hospital discharge
data. Washington, DC: Society for the Advancement of Violence and Injury Research; 2008. Available at
- Association of State and Territorial Health Officers. Position statement: improving external cause coding in hospital discharge data. Arlington,
VA: Association of State and Territorial Health Officers. Available at
- State and Territorial Injury Prevention Directors' Association. Consensus recommendations for injury surveillance in state health
departments. Marietta, GA: State and Territorial Injury Prevention Directors' Association; 1999. Available at
- State and Territorial Injury Prevention Directors' Association. Consensus recommendations for injury surveillance in state health
departments. Marietta, GA: State and Territorial Injury Prevention Directors' Association; 2007. Available at
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2007. Available at
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- Minnesota Department of Health. Minnesota Data Access System (MIDAS). St. Paul, MN: Minnesota Department of Health; 2007. Available
- Public Health Data Standards Consortium. Using external cause of injury codes: states' compelling stories. Baltimore, MD: Public Health
Data Standards Consortium; 2006. Available at
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the California Endowment with the Urban Institute; 2007. Available at
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Government, May 1, 2000.
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- Coben JH, Steiner CA, Barrrett M, Merrill CT, Adamson D. Completeness of cause of injury coding in healthcare administrative databases in
the United States, 2001. Inj Prev 2006;12:199--201.
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Health Resources and Services Administration; 2006. Available at
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Traffic Safety Administration; 2007. Available at
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Acronyms Used in This Report
||American College of Surgeons
||Agency for Healthcare Research and Quality
||Injury Control and Emergency Health Services Section of the American Public Health Association
||Association of State and Territorial Health Officers
||Colorado Department of Public Health and Environment
||Colorado Health and Hospital Association
||Centers for Medicare and Medicaid Services
||Crash Outcome Data Evaluation System
||Council of State and Territorial Epidemiologists
||Department of Health and Human Services
||External cause-of-injury coding
||Healthcare Cost and Utilization Project
||Hospital discharge data system
||Hospital ED data system
||Health Metrics Network
||Health Resources and Services Administration
||International Statistical Classification of Diseases and Related Health Problems, Tenth Revision
||International Classification of Diseases, Ninth Revision, Clinical Modification
||National Center for Health Statistics
||National Center for Injury Prevention and Control
||Nationwide Inpatient Sample
||National Trauma Data Bank
||Office of Suicide Prevention
||Office of Suicide Prevention
||Society for the Advancement of Violence and Injury Research
||State and Territorial Injury Prevention Directors
||World Health Organization
CDC Workgroup for Improvement of External Cause-of-Injury Coding
Co-chairs: Joseph L. Annest, PhD, National Center for Injury Prevention and Control, CDC; Lois A. Fingerhut,* MA, National Center for
Health Statistics, CDC.
Members: Susan S. Gallagher, MPH, Tufts University School of Medicine, Boston, Massachusetts; David C. Grossman, MD, Group
Health Cooperative, Seattle, Washington; Holly Hedegaard, MD, Colorado Department of Public Health and Environment, Denver, Colorado; Renee
L. Johnson,§ MSPH, National Center for Injury Prevention and Control, CDC; Mel
Kohn,§ MD, Oregon Department of Human Services,
Portland, Oregon; Donna Pickett, MPH, National Center for Health Statistics, CDC; Karen E. Thomas, MPH, National Center for Injury Prevention
and Control, CDC; Roger B. Trent,¶
PhD, California Department of Public Health, Sacramento, California.
* Member, Council of State and Territorial Epidemiologists (CSTE), State and Territorial Injury Prevention Directors Association (STIPDA), and Society
for the Advancement of Violence and Injury Research (SAVIR).
Member, STIPDA and SAVIR.
§ Member, CSTE and STIPDA.
¶ Member, STIPDA.
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Date last reviewed: 3/17/2008