Why Are Consistent Case Definition, Data Completeness And Quality Important For Injury Surveillance?

BMC Emerg Med. 2016; 16: 24.

Assessing the completeness of coded and narrative data from the Victorian Emergency Minimum Dataset using injuries sustained during fettle activities every bit a case study

Shannon E. Gray

Monash University Accident Research Middle, Monash University, Clayton, Australia

Australian Eye for Inquiry into Sports and its Prevention, Federation University Commonwealth of australia, Ballarat, Commonwealth of australia

Caroline F. Finch

Australian Middle for Enquiry into Sports and its Prevention, Federation University Australia, Ballarat, Australia

Received 2015 Nov 17; Accustomed 2016 Jul 6.

Abstruse

Background

Injury surveillance systems support the ongoing systematic collection, analysis and interpretation of health information vital to the prevention, planning and evaluation of injury prevention strategies. Ane primal measure out of the success of such systems is their reliability. Data completeness is a major component of system reliability, and is an indicator of a system's information quality. The Victorian Emergency Minimum Dataset (VEMD) is a state-broad record of injury presentations to emergency departments in Victoria, Australia. For each case, it provides information on the injury crusade, place of occurrence, action at fourth dimension of injury, body region affected and nature of injury, as well equally a free-text narrative of the injury event. The aim of this written report was to assess the completeness of data in the VEMD using injuries sustained in fitness facilities as a case study.

Methods

Analysis of VEMD coded parent injury variables (nature of injury, injured body region, cause of injury, place where injury occurred, activeness at fourth dimension of injury) and detailed narratives were reviewed for abyss over the ten-year catamenia July 2003 to June 2012, inclusive. Narratives were text analysed manually to determine which items of injury information they contained and compared to the parent injury variables.

Results

There were 2936 identified cases related to injuries sustained during fettle activities. 2 percent of cases had all coded injury variables unspecified. Overall, 95.8 % of narratives had at least one piece of injury information missing. The nature of injury and body region variables were coded in 92.6 and 96.6 % of cases, yet were only mentioned in 27.one and 75.4 % of narratives, respectively. The cause variable was allocated a specified code in 47.7 % of cases and was mentioned in 45.9 % of narratives. The cause was missing in both in 42.8 % of cases. In approximately half of all cases, the activeness and identify were specified in both the coded injury variable and narrative; they were missing in both in 7.4 and 13.6 % of cases, respectively.

Conclusions

The reliability of the VEMD as an injury surveillance arrangement, varied depending on the injury variable being examined.

Keywords: Injury, Surveillance, Quality, Reliability, Emergency department

Background

Injury surveillance systems support the ongoing and systematic collection, analysis, interpretation and dissemination of wellness information [ane, ii]. These systems are usually established to provide regime and international agencies with data to inform their funding decisions and oversight of wellness service commitment systems. They are also useful for health intendance professionals, researchers and the full general public because they tin can provide information on the brunt of injuries and the incidence and characteristics of specific injury types [iii]. Data collected through such systems can therefore be used to: (i) identify populations at run a risk of injury; (ii) identify opportunities for intervention, development and implementation; and (iii) evaluate and monitor intervention programs.

In gild to reduce the frequency and severity of injuries, the 'full movie' of the circumstances of the injury must be known [1]. In particular, it is of import to know details about the concrete environment where the injury occurred, the activity being participated in at time of injury, whether it was unintentional or intentional in nature, and its aetiology [3, 4]. These factors give important clues every bit to why injuries occur and, hence, what issues could be addressed to reduce injury risk in the future. Injury surveillance data can be analysed to determine where intervention is necessary, and how injury surveillance systems might be designed, besides every bit to evaluate the success of prevention programs one time implemented [5]. Hence, the severity and types of injuries that occur, and the part of the body most commonly injured, are likewise useful pieces of information needed to inform the evolution of injury prevention strategies [4].

In Victoria, Commonwealth of australia, there is currently no universal surveillance system to monitor injuries that occur to people who participate in fitness activities [six, seven]. The only known public source of injuries sustained during fettle activities is the Victorian Emergency Minimum Dataset (VEMD), which is a tape of all injury presentations to emergency departments at participating hospitals [half-dozen, 7]. Its purpose is to provide necessary epidemiological, health service planning, policy assessment and formulation, clinical inquiry, and quality improvement information to the state authorities which funds infirmary care in Victoria [8]. Information collected in the ED tin either be in the course of coded variables, free-text narratives, or a combination of the two [ix]. The usefulness of the VEMD in terms of both quality assurance and research relies on its reliability, which can exist affected by a number of factors [x]. Injury surveillance conducted in an emergency department is an instance of passive surveillance in that relevant information is collected in the grade of doing other tasks and not primarily for injury prevention [one].

Co-ordinate to the World Health Organisation (WHO), injury surveillance systems tin can be assessed and evaluated based on their success across vii attributes: reliability, simplicity, flexibility, acceptability, utility, sustainability and timeliness [one]. The attribute of reliability tin can be defined as "the ability to collect, manage and provide information properly without failure" [11]. At that place has been debate regarding whether emergency section injury surveillance data is reliable, as bias can exist introduced by factors such as patient age, sex, ethnic origin, time and geographical location [v, 12].

Highly reliable injury surveillance data is needed to ensure accurate estimates of the injury incidence and therefore better estimates of injury risk, too as providing more detailed data required for development of injury prevention strategies [13]. The development of an epidemiological injury profile and injury prevention strategies could be adversely impacted if relevant cases of a given injury problem are omitted when search criteria or the construction of an injury surveillance system provides incomplete data [14].

The focus of this study was on the abyss (a component of the reliability aspect) of both the coded and narrative (free text) information in the VEMD using data related to injuries sustained during fitness activities equally the case study. The abyss of an injury surveillance arrangement reflects its overall quality and can be measured in terms of the proportion of unknown or missing information recorded in key data fields. College quality data has a lower level of missing or unknown information surrounding the injury [11]. The specific aim of this study was to evaluate the completeness and quality of a subset of the VEMD every bit it relates to injuries sustained during fitness activities as a case report. A secondary aim was to assess whether this dataset could be useful for surveillance of injuries sustained during fitness activities, or if its potential employ is more aligned only to the needs of emergency department staff who collect the information as part of patient triage.

Methods

The Victorian Injury Surveillance Unit of measurement (VISU) has approving from the Human Research Ethics Committee at the Victorian Section of Wellness to supply a de-identified subset of data from the Victorian Emergency Minimum Dataset (VEMD). The supplied subset for this study independent cases relating to fettle-related injuries merely. The VEMD contains state-wide data on injury presentations to all 39 emergency departments (ED) at public Victorian hospitals that accept 24-h access, which has been estimated to record details of approximately eighty % of Victoria's injury ED presentations [10].

Forth with basic demographic and health intendance information, triage staff at these EDs are required to enter injury characteristic data into half-dozen pre-adamant coded injury variables for all injury-related presentations (these will herein be referred to equally the "parent variables"). They also consummate a 250-grapheme-limited narrative that outlines the patient's personal account of the circumstances leading to their injury in farther detail. The six parent variables provide data on the injured trunk region, nature of injury, place (where injury occurred), activeness (at time of injury), human intent (of the injury) and the cause of the injury. For the purposes of this study, the vast bulk of injuries sustained at fettle facilities were expected to exist unintentional. Therefore, the variable human intent was deemed unnecessary and omitted. In order to maintain confidentiality, VISU removed all bones patient demographics and irrelevant data relating to each case prior to providing the subset to authors.

As injuries sustained during fitness activities at fettle facilities were used equally the case report, targeted text searching of the narrative was first performed to identify relevant cases. These cases were extracted by VISU and provided to the authors as a data subset equally previously reported elsewhere [7]. Examples of fitness-related keywords used to select these cases included: treadmill, elliptical trainer, rowing machine, aerobics, weight preparation, barbell and dumbbell [6]. This is a select sample given that the narrative had some degree of abyss in order to be selected.

Figurei shows the steps performed to refine and condense the supplied dataset to remove irrelevant cases that were not related to fitness activities that occurred at fitness facilities, even if they had initially been selected with the text search (e.one thousand. those that occurred at locations or during activities that were clearly non at a fitness facility, such as at home or during work). The initial targeted text search was purposively designed to be very inclusive to ensure high capture of fettle-related cases. The dataset was narrowed to include people aged 15+ years merely every bit most fitness facilities enforce a minimum age limit for membership and use. The dataset was also restricted to the ten-year period July 2003 to June 2012, inclusive.

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The number of cases following each stage of the associated data cleaning process

With the make clean dataset, new variables were created alongside the existing (parent) injury variables to categorise the parent injury variables as informative (specified) or uninformative (other specified or unspecified). All cases with missing data were considered 'unspecified'. Variables originally coded equally 'unspecified' or 'other specified' do not provide any useful information nearly the injury instance and were subsequently deemed uninformative. For example, if the parent cause variable was coded every bit a "fall" the new variable would be coded every bit informative. It would be coded as uninformative if the parent cause variable was coded every bit 'unspecified' or 'other specified'. It is understood that the timing of the coding of nature of injury and trunk region differs between hospitals. These variables can be provisionally coded initially by triage nurses and in certain cases can be updated later, particularly if a procedure is performed on the injured individual as this information is also entered into the VEMD.

According to the VEMD manual, the narrative is intended to identify details not captured past the coded data, and is the patient's personal business relationship of the injury event. The manual advises including the following information: location, activity, product (specific product involved in the injury, where applicable), and any prophylactic equipment used or absent during the injury occurrence [15]. Nature and cause of injuries are recommended every bit beingness additional information that could be included in the narratives but there is no requirement for the injured trunk region to be mentioned. Nevertheless, each text narrative was coded according to whether it independent each particular of information that was also required in the parent injury variables. For case, the new binary variable was coded to one (informative) if the text narrative mentioned the affected body region, just coded to 2 (uninformative) if there was no mention of this. Every bit an instance, the narrative 'confused shoulder at gym' provides information about the body region, nature of injury and place at fourth dimension of injury. Yet, it does not state what fitness activity was existence undertaken at the time of injury (such as lifting dumbbells), nor does it country the cause of the injury (such as the weight was too heavy and the person's arm gave way).

Data were analysed using SPSS Version 21.0. Descriptive frequency tables of the newly created binary injury variables (informative or uninformative) and narrative specification (narratives state or do not state that item injury characteristic) were generated for each of the five parent injury variables (body region, nature of injury, place, action, cause) to show the proportion of cases that were unspecified. Cross-tabulations were performed for each of the v parent injury variables against the newly created binary injury variables and narrative variables.

Farther test of the text narrative was manually performed to compare the torso region mentioned in the narrative directly to what was coded in the parent body region variable. If body regions were nearby each other (such as the elbow and upper arm), they were considered to be consistently coded. Still, if it was clear that in that location was a discrepancy (such as a genu was mentioned in the narrative but the injury was coded to the neck in the parent injury variable trunk region), it was considered inconsistent.

Results

As can exist seen in Table1, fewer than 5 % of cases had a full narrative containing all injury characteristics. In almost ii-thirds of cases, at to the lowest degree one injury variable was uninformative (64.6 %). In approximately 2 % of cases, all parent injury variables were uninformative, meaning that to uncover any information about the injury, the narrative needed to be relied upon solely. Of those cases with all parent injury variables unspecified, only one of these had a narrative with consummate information. As per the instance inclusion criteria, there were no narratives that were completely unspecified, because they would not have been selected in the initial targeted text search.

Table 1

The proportion of missing information in narrative and unspecified injury variables reported in the VEMD

	for Any injury variable		for ALL injury variables
	n	%	north	%
parent coded data 'unspecified'	882	xxx.0	55	1.9
parent coded data uninformative	1896	64.6	56	1.nine
narrative missing some detail	2814	95.8	N/A	N/A
narrative missing particular AND parent coded data 'unspecified'	866	29.5	54	i.8
narrative missing item AND parent coded information uninformative	1851	63.0	55	i.9

Note: there cannot be all of the narrative unspecified, because the case would not accept been selected in the targeted text search inclusion criteria. Cavalcade titles apply to the parent coded data. Uninformative includes both 'unspecified' and 'other specified' parent coded variables

Whilst not necessary for inclusion, the body region injured was mentioned in three-quarters of the narratives (meet Tabular array2). In dissimilarity, the nature of injury was only mentioned in 27.one % of case narratives. Very few cases were unspecified for the torso region injury variable (3.4 %), and just seven.4 % of cases were coded as uninformative ('other specified' or 'unspecified') for the nature of injury variable. In contrast, fewer than half of the cause variables were coded as informative (47.7 %).

Tabular array 2

Completeness of specified parent coding and narratives relating to fettle-related injuries reported in the VEMD

n = 2936	Parent coding						Narrative		Informative				Uninformative
	specified		other specified		unspecified		contained in the text narrative		'specified' or 'other specified' in parent coding and contained in narrative		'unspecified' in parent coding and independent in narrative		'unspecified' in parent coding and not contained in narrative
	due north	%	n	%	n	%	n	%	n	%	n	%	n	%
nature of injury	2718	92.6	88	3.0	130	four.4	797	27.1	771	26.3	26	0.9	104	3.five
body region	2835	96.6	N/A^a	North/A^a	101	3.4	2214	75.4	2134	72.seven	80	two.7	21	0.7
activity	2337	79.half-dozen	170	5.8	429	14.half dozen	1796	61.2	1522	51.8	274	9.three	155	5.3
cause	1400	47.7	1039	35.4	497	16.nine	1349	45.nine	1268	43.two	81	2.vii	416	fourteen.2
place	2209	75.two	268	9.1	459	fifteen.6	1898	64.half dozen	1723	58.7	175	six.0	284	9.seven

Note: ^athe body region variable does non take 'other specified' as an choice to select

There were 975 cases (33.two %) where the body region that was coded in the injury variable did not lucifer to the body region mentioned in the narrative.

Figure2 shows that the parent injury variable and the narrative were jointly specified for more than one-half of cases for trunk region and identify, and in approximately half of the cases for the activeness. For nature of injury, the majority of cases had this detail coded in the parent injury variable, but non mentioned in the narrative. The parent injury variable was not coded nor was the cause of the injury specified in the narrative in 42.viii % of cases, meaning that the causes of injuries associated with fitness activities would be difficult to decide for a large proportion of cases.

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The proportion of specified narratives and informative injury variables for all cases of each of the 5 injury variables (n = 2936 records). Note (for Fig. ii): injury variable informative means that injury variable was 'specified' (and uninformative means injury variable was coded as 'other specified' or 'unspecified'). A 'specified' narrative contained that injury variable information, conversely an 'unspecified' narrative did not contain that data

Discussion

Injury surveillance systems are valuable for obtaining, coding and recording specific information surrounding the circumstances of injuries. This study involved an in-depth review of 2936 identified cases of emergency department presentations for treatment of an injury related to fitness activities over a ten-twelvemonth menstruum July 2003 to June 2012, inclusive. This is but a small-scale proportion of all injury-related ED presentations equally there were at least 200,000 per year of the study period [sixteen]. According to the VEMD transmission, all injury-related presentations to ED are required to exist reported with complete information on all parent injury variables supplemented with a description of the injury event field as a text narrative [8]. When inputting the data into the reporting system, information technology is necessary for ED triage staff to complete all fields equally most systems do not allow incomplete or missing information before a example record is saved. This data tin can then exist altered later on if necessary, particularly if further information is added to the instance record, such as a procedure. The system does non automatically detect unnecessarily unspecified or uninformative entries and then in that location is no prompt for further information.

A possible issue with the VEMD, like all ED collected information, is its reliability [10, 17]. Reliability was assessed in this study, as this is the only injury surveillance system attribute that focuses on the information quality; the other six attributes of an injury surveillance arrangement focus on the system itself. In guild to evaluate all other attributes, full access to the dataset and data collection methods would exist required and should exist the focus of other studies.

Our results show that in that location were some major differences and inconsistencies in what had been written in the narrative, and what was coded in the parent injury variables for body region. Therefore, there are limitations in the completeness of injury characteristics documented in the narrative. At that place were also a number of cases that either had some of their parent injury variable data missing or were lacking some fundamental data in the narrative. Therefore, each injury example was not e'er fully recorded and some pertinent data for injury prevention purposes was missing. Unfortunately, this suggests that the VEMD information is not always complete, and there is potential for information technology to also be inaccurate. Inaccurate data could bear on on both the blueprint and development, and the success, of injury prevention strategies if the injury problem is incorrectly represented [x].

For the parent injury variables, the VEMD coding manual specifies which codes to select from, thereby providing a relevant pick for all cases without the need to code to unspecified or other specified categories, with the exception of place [8]. Referring to the VEMD manual, body region and nature of injury variable fields provide adequate options to comprehend all major body parts and types of injuries [8]. As these variables are more probable to be more than clinically relevant, this may explicate why these were the most successfully coded variables in our instance review. There are several broad crusade of injury categories specified in the VEMD manual that would likely encompass the vast majority of injuries sustained during fettle activities, much more than the 47.vii % that were really specified. The VEMD manual suggests that fitness injuries should exist coded to 'sports' for activity, however triage staff may have assumed that fettle activities do not qualify as a sport, and this could possibly explain why 79.vi % of cases were coded to 'other specified' or 'unspecified' for activity. If this was the case, coding fitness activities to 'other specified' is right, as the activity at the time of injury was specified fifty-fifty if the triage staff fellow member did non deem information technology advisable to allocate the instance to any pre-defined category. The VEMD transmission infers that the place of incidents that lead to injuries at a fitness facility could be coded to either 'athletics and sports area' or 'other specified' for identify. This defoliation could exist responsible for the quarter of cases found to be uninformative for this item, even so a higher proportion of uninformative entries were coded to 'unspecified' than 'other specified'. Incompleteness of activeness and identify coding for sports injuries has already been shown to lead to underestimates of the true incidence of these injuries in infirmary information [14].

While 'other specified' is a legitimate possible category for coding variables in datasets with an authoritative focus, in terms of injury surveillance it remains uninformative as further information regarding the injury or the injury event cannot be adamant using solely coded variables. When parent variables are coded to 'other specified', it then becomes necessary to gain further information from the narrative. Unfortunately, such detail is not always provided in the narrative, making information technology very difficult to determine the full circumstances of the injury. This limits the employ of ED data to inform injury prevention efforts fully.

From a treatment point of view, bold that the information in the injury variables was accurate, injuries withal could exist treated rather successfully given the data necessary to guide handling (i.e. injured body region and nature of injury) in the VEMD information was insufficiently well coded. One time the data has been collected and recorded, the action, place and cause injury variables are unlikely to be referred to once more by treating staff within the ED. Knowing this, the triage staff who do the coding may be less inclined to spend much time in accurately completing these data fields, as they neither affect nor assistance the patient'southward treatment. They may too be unaware of all reasons for why the data is nerveless and its total range of uses, which could influence their mental attitude to completing information technology accurately and completely [x]. Information technology is likewise possible, that detail software systems within some hospitals may update these fields once a diagnosis has been made and entered into the system (as is required for accurate medical records), without likewise updating the narrative description of how the condition occurred in the beginning place.

Around a 3rd of cases mentioned an injured body region in the narrative that did not match with the parent coded body region. The narrative field is the patient'due south personal account of the injury events and is recorded by triage staff to clarify the injury event and place any features not captured by the coded information [eight]. This information is necessary for providing additional relevant information related to the injury [8]. Omitting identifying details, the narrative should include the location, activity, specific product existence used at time of injury (if advisable), whatsoever rubber equipment used, and any boosted data such every bit the nature of the injury and its cause [viii]. As the narrative is the patient's personal account, one would assume that the information provided there is likely to exist more accurate than what is coded in the injury variables. However, this may only be in regards to the injury consequence details, as the triage nurses would potentially have better anatomical and injury knowledge than the patient. Therefore, information technology is possible that what is written in the narrative is unlike to what is provided in the bodily injury characteristic parent codes if the data field is later updated subsequently treatment in the ED, by medical staff. That beingness said, injury variable coding is performed by ED triage staff by selecting the most appropriate reply from drop down boxes; information entry mistakes can sometimes be made leading to incorrect data [10]. It would be less probable that triage staff would input text incorrectly than selecting an wrong option from a drop downwards box and and then information technology could be expected that the action at time of injury, identify of occurrence and cause of injury would be recorded more successfully in the text narrative. A decorated ED or a example requiring urgent medical attending may also affect the level of item of the triage staff in data input [10, xviii].

The VEMD information are collected by a range of ED triage staff (doctors, nurses and clerks) who are not formally trained data coders. It is unknown what level of grooming is given to these staff members, and whether such instruction is extensive and includes data on the levels of detail required for the VEMD and what the data are used for, or whether the bare minimum is given [10]. The main responsibleness of triage staff is to assess the patient and prioritise their care, and combined with other factors such equally their level of grooming, their attitude to completing injury surveillance tasks and the level of staffing, data quality and its completeness could be lacking [10]. The abyss of the data may accept also been affected past other factors such as the number of patients attending the ED, triage status of the patient, time of day, or which hospital was attended. All of these factors could influence the quality of the data collected. A limitation of this written report is that, due to upstanding considerations the authors were not granted access to the full dataset (for privacy reasons simply a subset of the available variables for each example was provided) and therefore these comparisons could not be made.

Being a passive injury surveillance organization, the VEMD is simple, practical, affordable, and sustainable [1]. By providing pre-determined drop down boxes for injury variables, and a short text clarification of the injury effect, the dataset easily allows for the collection of useful data during the course of doing other tasks in a busy healthcare environment. Ongoing development of, and improvements to, the VEMD organisation tin exist somewhat inflexible equally changes require much negotiation betwixt regime departments, software developers and administrators of the datasets [10]. Information technology tin can besides be costly to add a new injury variable option as this must exist first agreed upon and the unabridged operating organisation then updated appropriately inside each hospital. Because the important time-critical work that is performed in EDs, requiring triage staff to spend longer on information entry for each example to ensure more than useful data could poorly affect the outcome of patients. It is possible that providing staff with ongoing training and detailed data on how injury information is utilised, could pb to an improvement in the completeness and quality of VEMD data and more efficient data entry by triage staff. Active surveillance, in which injury cases are sought out and investigated, could perhaps lead to significantly more than reliable and better quality information, but would crave significant resource such as funding and staff [1]. Information technology is postulated that more common activities or causes that take pre-adamant codes (such as working for income or motor vehicle crashes) could have more reliable data due to the frequency with which they present to EDs compared with fitness activity-related injuries, given they comprise merely a small proportion of all ED presentations.

When extracting particular categories of injury cases for detailed review from the VEMD, information extraction is unremarkably performed using parent injury variables rather than keyword searching of text narratives for particular causes of injury, places where injuries occur or activities at time of injury. Systems where a proportion of these parent variables are coded to unspecified or miscoded values could pb to a vast underestimation of the true magnitude of injury incidence and misrepresentation of the injury problem, which is another consequence of incomplete injury surveillance systems [9].

A limitation of this study was that it only examined whether injury variables were coded as uninformative ('other specified' or 'unspecified'), it did not fully assess the nature of any miscoding. Whilst all cases either occurred at a fitness facility or during an action well-nigh commonly performed at fitness facilities, some injury variables were coded to irrelevant places, activities or causes. Future studies could investigate the degree of miscoding in ED data, assuming the narrative is to exist trusted over the coded data [6, seven]. To appraise the caste of miscoding in the data fully, each individual case would need to be reviewed with the patient to determine the total circumstances of the injury, and comparisons with recorded data can be fabricated.

The cases represented by the VEMD are likely to vastly underestimate the number of injuries sustained during fitness activities, every bit a number of injured persons would seek treatment from their full general practitioner, allied wellness professionals, or not at all [6, seven]. Therefore, fifty-fifty if it had 100 % reliability, this dataset would not be appropriate as a sole surveillance organization for fitness activity related injuries, as it does not tape all injuries sustained. Notwithstanding this, for injuries sustained in fitness facilities, ideally the fitness activity and the cause of the injury demand to be provided in the narrative in order for prevention strategies to be developed and implemented.

Conclusions

The abyss of the VEMD was assessed using injuries that occurred during fettle activities as a example study. Its completeness was plant to vary, depending on the injury variable being examined (nature of injury, body region injured, activeness when injured, crusade of injury, place of occurrence). In more than three-quarters of cases, at least one of the injury variables was uninformative (coded to either 'unspecified' or 'other specified'). The completeness of the narrative varied depending on the injury variable (only around a quarter of cases included the nature of injury, whereas 3-quarters of cases included the body region).

Co-ordinate to the WHO injury surveillance guidelines, a reliable system should detect all injury events, fully record these and accurately provide all pertinent information [i]. This study addressed only its completeness. From our results, information technology is articulate that the total circumstances surrounding the injury were not always fully recorded. Moreover, the VEMD gives an underestimation of the injuries sustained in Victoria [10], because not all injury events are able to be identified on the basis of parent coded variables. As this study did not address miscoding, and each injured private was unable to be contacted to verify the VEMD contents, information technology is unknown how accurately information were recorded.

Based on the results of this completeness assessment, the VEMD cannot exist used as a complete or comprehensive injury surveillance organisation to monitor fitness activeness-related injuries. This study has plant that there are gaps in current information systems as not every case provides all injury details in either the coded data or the narrative. In the absence of a universal injury surveillance organization to tape these, notwithstanding, the VEMD has the potential to yield useful and important information to still profile the common characteristics of these injuries [6]. Undertaking further detailed analysis of the narratives could potentially yield activity and crusade information that is necessary for injury prevention strategies [12, nineteen], but would be most useful if the details supplied in the text narratives were supplemented with the parent coded data.

Abbreviations

ED, emergency section; VAED, Victorian admitted episodes dataset; VEMD, Victorian emergency minimum dataset; VISU, Victorian injury surveillance unit of measurement

Acknowledgements

SEG undertook this work equally part of her PhD studies under the supervision of CFF. SEG was supported by an Australian Postgraduate Award Scholarship at Monash University. CFF was supported by a National Health and Medical Research Quango Principal Fellowship (ID: 1058737). Both authors are members of the Australian Centre for Enquiry into Injury in Sport and its Prevention, which is one of nine research centres across the world selected by the International Olympic Commission (IOC) as a fellow member of the IOC Medical Research Network. Angela Clapperton is thanked for her useful comments on a draft version of this manuscript.

Funding

No external funding was obtained for this study.

Authors' contributions

Shannon E Grayness was responsible for the concept, design, data extraction and coding, statistical analysis, estimation of results and writing upward of the manuscript. Caroline F Finch contributed to the concept and design of the study, and the writing of the manuscript. Both authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ideals blessing and consent to participate

The Victorian Injury Surveillance Unit had approving from the Human Enquiry Ethics Committee at the Victorian Department of Health (in Commonwealth of australia) to supply a de-identified subset of data from the Victorian Emergency Minimum Dataset.

Contributor Information

Shannon E. Grayness, E-mail: ude.hsanom@yarg.nonnahs.

Caroline F. Finch, Email: ua.ude.noitaredef@hcnif.c.

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