Australian Health Review Australian Health Review Society
Journal of the Australian Healthcare & Hospitals Association
RESEARCH ARTICLE

The prevalence of pre-existing mental health, drug and alcohol conditions in major trauma patients

Tu Q. Nguyen A B , Pamela M. Simpson A and Belinda J. Gabbe A
+ Author Affiliations
- Author Affiliations

A Monash University, Department of Epidemiology and Preventive Medicine, The Alfred Centre, 99 Commercial Road, Melbourne, Vic. 3004, Australia. Email: pamela.simpson@monash.edu; belinda.gabbe@monash.edu

B Corresponding author. Email: tu.nguyen@monash.edu

Australian Health Review 41(3) 283-290 https://doi.org/10.1071/AH16050
Submitted: 23 February 2016  Accepted: 23 May 2016   Published: 15 July 2016

Abstract

Objective Capturing information about mental health, drug and alcohol conditions in injury datasets is important for improving understanding of injury risk and outcome. This study describes the prevalence of pre-existing mental health, drug and alcohol conditions in major trauma patients based on routine discharge data coding.

Methods Data were extracted from the population-based Victorian State Trauma Registry (July 2005 to June 2013, n = 16 096).

Results Seventeen percent of major trauma patients had at least one mental health condition compared with the Australian population prevalence of 21%. The prevalence of mental health conditions was similar to the Australian population prevalence in men (19% v. 18%), but lower in women (14% v. 25%) and across all age groups. Mental health conditions were more prevalent in intentional self-harm cases (56.3%) compared with unintentional (13.8%) or other intentional (31.2%) cases. Substance use disorders were more prevalent in major trauma patients than the general population (15% v. 5%), higher in men than women (17% v. 10%) and was highest in young people aged 25–34 years (24%).

Conclusions Under-reporting of mental health conditions in hospital discharge data appears likely, reducing the capacity to characterise the injury population. Further validation is needed.

What is known about the topic? Medical record review, routine hospital discharge data and self-report have been used by studies previously to characterise mental health, drug and alcohol conditions in injured populations, with medical record review considered the most accurate and reliance on self-report measures being considered at risk of recall bias. The use of routinely collected data sources provides an efficient and standardised method of characterising pre-existing conditions, but may underestimate the true prevalence of conditions.

What does this paper add? No study to date has explored the prevalence of Abbreviated Injury Scale and International Classification of Diseases and Health Related Problems, Tenth Revision, Australian Modification (ICD-10-a.m)-coded mental health, alcohol and drug conditions in seriously injured populations. The results of this study show the incidence of mental health conditions appeared to be under-reported in major trauma patients, suggesting limitations in the use of ICD-10-a.m. to measure mental health comorbidities.

What are the implications for practitioners? In order to achieve improvements in measuring mental health, drug and alcohol comorbidities, we suggest the use of a series of different diagnostic systems to be used in conjunction with ICD-10-a.m., such as medical record review and self-reporting as well as linkage to other datasets. When applied simultaneously, diagnosis and outcomes of mental health may be compared and validated across diagnostic systems and deviations in diagnoses could be more readily accounted for.


References

[1]  Peden M, McGee K, Krug E. Injury: a leading cause of the global burden of disease. Geneva: World Health Organization; 2000.

[2]  Vos T, Barber RM, Bell B, Bertozzi-Villa A, Biryukov S, Bolliger I, Charlson F, David A, Degenhardt L, Dicker D, Duan L, Erskine H, Feigin VL, Ferrari AJ, Fitzmaurice C, Fleming T. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015; 386 743–800.
Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013.CrossRef |

[3]  Krug EG, Sharma GK, Lozano R. The global burden of injuries. Am J Public Health 2000; 90 523–6.
The global burden of injuries.CrossRef | 1:STN:280:DC%2BD3c3hslOltw%3D%3D&md5=5a996b9a525bdccfaf628330ac342727CAS | 10754963PubMed |

[4]  Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, et al Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380 2095–128.
Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.CrossRef | 23245604PubMed |

[5]  World Health Organization. The global burden of disease: 2004 update. Geneva: World Health Organization; 2008.

[6]  Pointer S. Trends in hospitalised injury 1999–00 to 2010–11. Canberra: AIHW; 2013.

[7]  Peden M, McGee K, Sharma G. The injury chart book: a graphical overview of the global burden of injuries. Geneva: World Health Organization; 2002.

[8]  Cohen L, Miller T, Sheppard MA, Gordon E, Gantz T, Atnafou R. Bridging the gap: bringing together intentional and unintentional injury prevention efforts to improve health and well being. J Safety Res 2003; 34 473–83.
Bridging the gap: bringing together intentional and unintentional injury prevention efforts to improve health and well being.CrossRef | 14733980PubMed |

[9]  Cornwell EE, Belzberg H, Velmahos G, Chan LS, Demetriades D, Stewart BM, Oder DB, Kahaku DRN, Chan D, Asensio JA, Berne TV. The prevalence and effect of alcohol and drug abuse in cohort-matched critically injured patients. Am Surg 1998; 64 461–5.
| 9585786PubMed |

[10]  Griggs W, Caldicott D, Pfeiffer J, Edwards N, Pearce A, Davey M. The impact of drugs on road crashes, assaults and other trauma – a prospective trauma toxicology study. National Drug Law Enforcement Research Fund Report No.: 1449–7476. Adelaide: Trauma Service, Royal Adelaide Hospital; 2007.

[11]  Field CA, O’Keefe G. Behavioral and psychological risk factors for traumatic injury. J Emerg Med 2004; 26 27–35.
Behavioral and psychological risk factors for traumatic injury.CrossRef | 14751475PubMed |

[12]  O’Donnell ML, Creamer M, Elliott P, Bryant R, McFarlane A, Silove D. Prior trauma and psychiatric history as risk factors for intentional and unintentional injury in Australia. J Trauma 2009; 66 470–6.
Prior trauma and psychiatric history as risk factors for intentional and unintentional injury in Australia.CrossRef | 19204523PubMed |

[13]  Wan JJ, Morabito DJ, Khaw L, Knudson MM, Dicker RA. Mental illness as an independent risk factor for unintentional injury and injury recidivism. J Trauma 2006; 61 1299–304.
Mental illness as an independent risk factor for unintentional injury and injury recidivism.CrossRef | 17159669PubMed |

[14]  Langley J, Davie G, Wilson S, Lilley R, Ameratunga S, Wyeth E, Derrett S. Difficulties in functioning 1 year after injury: the role of preinjury sociodemographic and health characteristics, health care and injury-related factors. Arch Phys Med Rehabil 2013; 94 1277–86.
Difficulties in functioning 1 year after injury: the role of preinjury sociodemographic and health characteristics, health care and injury-related factors.CrossRef | 23439409PubMed |

[15]  Derrett S, Wilson S, Samaranayaka A, Langley J, Wyeth E, Ameratunga S, Lilley R, Davie G, Mauiliu M. Prevalence and predictors of disability 24 months after injury for hospitalised and non-hospitalised participants: results from a longitudinal cohort study in New Zealand. PLoS One 2013; 8 e80194
Prevalence and predictors of disability 24 months after injury for hospitalised and non-hospitalised participants: results from a longitudinal cohort study in New Zealand.CrossRef | 24278258PubMed |

[16]  Morris JA, MacKenzie EJ, Edelstein SL. The effect of preexisting conditions on mortality in trauma patients. JAMA 1990; 263 1942–6.
The effect of preexisting conditions on mortality in trauma patients.CrossRef | 2313871PubMed |

[17]  Holtslag HR, van Beeck EF, Lindeman E, Leenen LP. Determinants of long-term functional consequences after trauma. J Trauma 2007; 62 919–27.
Determinants of long-term functional consequences after trauma.CrossRef | 17426549PubMed |

[18]  Thompson HJ, Rivara FP, Nathens R, Wang J, Jurkovich GJ, Mackenzie EJ. Development and validation of the mortality risk for trauma comorbidity index. Ann Surg 2010; 252 370–5.
Development and validation of the mortality risk for trauma comorbidity index.CrossRef | 20622665PubMed |

[19]  Henderson T, Shepheard J, Sundararajan V. Quality of diagnosis and procedure coding in ICD-10 administrative data. Med Care 2006; 44 1011–9.
Quality of diagnosis and procedure coding in ICD-10 administrative data.CrossRef | 17063133PubMed |

[20]  Boyd NF, Pater JL, Ginsburg AD, Myers RE. Observer variation in the classification of information from medical records. J Chronic Dis 1979; 32 327–32.
Observer variation in the classification of information from medical records.CrossRef |

[21]  Haagsma JA, van Beeck EF, Polinder S, Toet H, Panneman M, Bonsel GJ. The effect of comorbidity on health-related quality of life for injury patients in the first year following injury: comparison of three comorbidity adjustment approaches. Popul Health Metr 2011; 9 10
The effect of comorbidity on health-related quality of life for injury patients in the first year following injury: comparison of three comorbidity adjustment approaches.CrossRef | 21513572PubMed |

[22]  Ash A, Porell F, Gruenberg L, Sawitz E, Beiser A. Adjusting Medicare capitation payments using prior hospitalization data. Health Care Financ Rev 1989; 10 17–29.
| 1:STN:280:DyaL1MznvFagsw%3D%3D&md5=fc42487ebaf25b9e514da14b3d41b8c2CAS | 10313277PubMed |

[23]  Graham JE, Ripsin CM, Deutsch A, Kuo YF, Markello S, Granger CV, Ottenbacher KJ. Relationship between diabetes codes that affect Medicare reimbursement (tier comorbidities) and outcomes in stroke rehabilitation. Arch Phys Med Rehabil 2009; 90 1110–6.
Relationship between diabetes codes that affect Medicare reimbursement (tier comorbidities) and outcomes in stroke rehabilitation.CrossRef | 19577023PubMed |

[24]  Goldman LS, Nielsen NH, Champion HC. Awareness, diagnosis, and treatment of depression. J Gen Intern Med 1999; 14 569–80.
Awareness, diagnosis, and treatment of depression.CrossRef | 1:STN:280:DyaK1MvitFyktg%3D%3D&md5=c30e5ee88bb80823f2cb2a54152b09e3CAS | 10491249PubMed |

[25]  Baker SP, O’Neill B, Haddon W, Long WB. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma 1974; 14 187–96.
The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care.CrossRef | 1:STN:280:DyaE2c7gslGisg%3D%3D&md5=2c1af5a20a03634567bfa6b7299b2409CAS | 4814394PubMed |

[26]  Australian Bureau of Statistics. National Survey of Mental Health and Wellbeing: summary of results. Canberra: Australian Bureau of Statistics; 2008. Available at: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/4326.02007?OpenDocument [verified 8 April 2014].

[27]  Copes WS, Champion HR, Sacco WJ, Lawnick MM, Keast SL, Bain LW. The Injury Severity Score revisited. J Trauma 1988; 28 69–77.
The Injury Severity Score revisited.CrossRef | 1:STN:280:DyaL1c7hvFSmtg%3D%3D&md5=b4e876b6ea3424b989ea9156f4e38957CAS | 3123707PubMed |

[28]  Cameron PA, Finch CF, Gabbe BJ, Collins LJ, Smith KL, McNeil JJ. Developing Australia’s first statewide trauma registry: what are the lessons? Aust N Z J Surg 2004; 74 424–8.
Developing Australia’s first statewide trauma registry: what are the lessons?CrossRef |

[29]  Eldridge D. Injury among young Australians. Cat. no. AUS 102. Canberra: Australian Institute of Health and Welfare; 2008.

[30]  Udry RJ. Why are males injured more than females? Inj Prev 1998; 4 94–5.
Why are males injured more than females?CrossRef | 1:STN:280:DyaK1czjtVOruw%3D%3D&md5=e40910cd2940379ffe9e3f9a0c6a4d80CAS |

[31]  lezzoni LI, Foley SM, Daley J, Hughes J, Fisher ES, Heeren T. Comorbidities, complications, and coding bias: does the number of diagnosis codes matter in predicting in-hospital mortality? JAMA 1992; 267 2197–203.
Comorbidities, complications, and coding bias: does the number of diagnosis codes matter in predicting in-hospital mortality?CrossRef |

[32]  Moden B, Ohlsson H, Merlo J, Rosvall M. Risk factors for diagnosed intentional self-injury: a total population-based study. Eur J Public Health 2013; 24 286–97.
Risk factors for diagnosed intentional self-injury: a total population-based study.CrossRef | 23748850PubMed |

[33]  Harrison J. The National Injury Prevention and Safety Promotion Plan: 2004–2014. Canberra: National Public Health Partnership; 2005.

[34]  Milne B, Bell J, Lampropoulos B, Towns S. Alcohol, drugs and Australian young people. Int J Adolesc Med Health 2007; 19 245–53.
Alcohol, drugs and Australian young people.CrossRef | 17937140PubMed |

[35]  Kim HM, Smith EG, Stano CM, Ganoczy D, Zivin K, Walters H, et al Validation of key behaviourally based mental health diagnoses in administrative data: suicide attempt, alcohol abuse, illicit drug abuse and tobacco use. BMC Health Serv Res 2012; 12 18
Validation of key behaviourally based mental health diagnoses in administrative data: suicide attempt, alcohol abuse, illicit drug abuse and tobacco use.CrossRef | 22270080PubMed |

[36]  Gabbe BJ, Harrison JE, Lyons RA, Edwards ER, Cameron PA, Victorian Orthopaedic Trauma Outcomes Registry Comparison of measures of comorbidity for predicting disability 12-months post-injury. BMC Health Serv Res 2013; 13 30
Comparison of measures of comorbidity for predicting disability 12-months post-injury.CrossRef | 23351376PubMed |

[37]  O’Malley KJ, Cook KF, Price MD, Wildes KR, Hurdle JF, Ashton CM. Measuring diagnoses: ICD code accuracy. Health Serv Res 2005; 40 1620–39.
Measuring diagnoses: ICD code accuracy.CrossRef | 16178999PubMed |

[38]  Fiest KM, Jette N, Quan H, St Germaine-Smith C, Metcalfe A, Patten SB, et al Systematic review and assessment of validated case definitions for depression in administrative data. BMC Psychiatry 2014; 14 289
Systematic review and assessment of validated case definitions for depression in administrative data.CrossRef | 25322690PubMed |



Export Citation