A prediction model of military combat and training exposures on VA service-connected disability: a CENC study

References

• US Department of Veterans Affairs. Veterans benefits administration. Annual Benefits Report Fiscal Year 2016 [accessed January 15, 2018]. https://www.benefits.va.gov/REPORTS/abr/ABR-All_Sections_FY16_06292017.pdf.
   Google Scholar
• Fried DA, Helmer D, Halperin WE, Passannante M, Holland BK. Health and health care service utilization among U.S. Veterans Denied VA service-connected disability compensation: a review of the literature. Mil Med. 2015;180(10):1034–40. doi:10.7205/MILMED-D-14-00435.
   PubMed Web of Science ®Google Scholar
• Spoont MR, Sayer NA, Nelson DB, Nugent S. Does filing a post-traumatic stress disorder disability claim promote mental health care participation among veterans? Mil Med. 2007;172(6):572–75. doi:10.7205/milmed.172.6.572.
   PubMed Web of Science ®Google Scholar
• Maynard C, Batten A, Liu C-F, Nelson K, Fihn SD. The burden of mental illness among veterans: use of VHA health care services by those with service-connected conditions. Med Care. 2017;55(11):965–69. doi:10.1097/MLR.0000000000000806.
   PubMed Web of Science ®Google Scholar
• Silva A, Tarlov E, French DD, Huo Z, Martinez RN, Stroupe KT. Veterans affairs health system enrollment and health care utilization after the affordable care act: initial insights. Mil Med. 2016;181(5):469–75. doi:10.7205/MILMED-D-15-00210.
   PubMed Web of Science ®Google Scholar
• Maciejewski ML, Liu C-F, Kavee AL, Olsen MK. How price responsive is the demand for specialty care? Health Econ. 2012;21:902–12. doi:10.1002/hec.1759.
   PubMed Web of Science ®Google Scholar
• Grubaugh AL, Elhai JD, Ruggiero KJ, Egede LE, Naifeh JA, Frueh BC. Equity in Veterans Affairs disability claims adjudication in a national sample of veterans. Mil Med. 2009;174(12):1241–46. doi:10.7205/milmed-d-09-00070.
   PubMed Web of Science ®Google Scholar
• Walker WC, Carne W, Franke LM, Nolen T, Dikmen SD, Cifu DX, Wilson K, Belanger HG, Williams R. The chronic effects of neurotrauma consortium (CENC) multi-centre observational study: description of study and characteristics of early participants. Brain Inj. 2016;30(12):1469–80. doi:10.1080/02699052.2016.1219061.
   PubMed Web of Science ®Google Scholar
• Vanderploeg RD, Cooper DB, Belanger HG, Donnell AJ, Kennedy JE, Hopewell CA, Scott SG. Screening for postdeployment conditions: development and cross-validation of an embedded validity scale in the Neurobehavioral Symptom Inventory. J Head Trauma Rehabil. 2014;29(1):1–10. doi:10.1097/HTR.0b013e318281966e.
   PubMed Web of Science ®Google Scholar
• Cooper DB, Nelson L, Armistead-Jehle P, Bowles AO. Utility of the Mild Brain Injury Atypical Symptoms Scale as a screening measure for symptom over-reporting in Operation Enduring Freedom/Operation Iraqi Freedom service members with postconcussive complaints. Arch Clin Neuropsychol. 2011;26:718–27. doi:10.1093/arclin/acr070.
   PubMed Web of Science ®Google Scholar
• Hastie T, Tibshirani R, Friedman J. The elements of statistical learning, data mining,inference, and prediction. New York: Springer; 2009.
   Google Scholar
• Breiman L. Statistical modeling: The two cultures. Stat Sci. 2001;16(3):199–215. doi:10.1214/ss/1009213726.
   Web of Science ®Google Scholar
• Shmueli G. To explain or to predict? Stat Sci. 2010;25(3):289–310. doi:10.1214/10-STS330.
   Web of Science ®Google Scholar
• Kuhn M, Johnson K. Applied predictive modeling. New York: Springer; 2013.
   Google Scholar
• Godsey B. Think like a data scientist, tackle the data science process step-by-step. Shelter Island (NY): Manning; 2017.
   Google Scholar
• Géron A. Hands-on machine-learning with scikit-learn & tensorflow, concepts, tools, and techniques to build intelligent systems. Sebastopol (CA): O’Reilly; 2017.
   Google Scholar
• Steyerberg EW. Clinical prediction models, a practical approach to development, validation, and updating. New York (NY): Springer; 2010.
   Google Scholar
• Zumel N, Mount J. Practical data science. R.Shelter Island (NY): Manning Publications; 2014.
   Google Scholar
• U.S. Congressional Budget Office. Veterans disability compensation: trends and policy options.  Washington (DC): Veterans’ Disability Compensation: Trends and Policy Options; 2014.http://www.cbo.gov/sites/default/files/cbofiles/attachments/45615-VADisability_1.pdf.
   Google Scholar
• Corrigan J, Bogner J. Initial reliability and validity of the ohio state university TBI identification method. J Head Trauma Rehabil. 2007;22(6):318–29. doi:10.1097/01.HTR.0000300227.67748.77.
   PubMed Web of Science ®Google Scholar
• Walker WC, Cifu DX, Hudak AM, Goldberg G, Kunz RD, Sima AP. Structured interview for mild traumatic brain injury after military blast: Inter-rater agreement and development of diagnostic algorithm. J Neurotrauma. 2015 Apr 1;32(7):464–73. doi:10.1089/neu.2014.3433.
   PubMed Web of Science ®Google Scholar
• DoD/VA Code Proposal: DOD/VA common definition of TBI [Internet]. [accessed 2012]. http://www.cdc.gov/nchs/data/icd9/Sep08TBI.pdf.
   Google Scholar
• Vogt DS, Smith BN, King LA, King DW, Knight JA, Vasterling JJ. Deployment Risk and Resilience Inventory-2 (DRRI-2): An updated tool for assessing psychosocial risk and resilience factors among service members and Veterans (PDF). J Trauma Stress. 2013;26:710–17. doi: 10.1002.jts.21868. PILOTS ID: 87988.
   PubMed Web of Science ®Google Scholar
• Kroenke K, Spitzer RL, Williams JBW. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16:606–13. doi:10.1046/j.1525-1497.2001.016009606.x.
   PubMed Web of Science ®Google Scholar
• Tsao JW, Stentz LA, Rouhanian M, Howard RS, Perry BN, Haran FJ, Pasquina PF, Wolde M, Taylor CE, Lizardo R, et al. Effect of concussion and blast exposure on symptoms after military deployment. Neurology. 2017;89:2010–16. doi:10.1212/WNL.0000000000004616.
   PubMed Web of Science ®Google Scholar
• Tate CM, Wang KK, Eonta S, Zhang Y, Carr W, Tortella FC, Hayes RL, Kamimori GH. Serum brain biomarker level, neurocognitive performance, and self-reported symptom changes in soldiers repeatedly exposed to low-level blast: a breacher pilot study. J Neurotrauma. 2013;30:1620–30. doi:10.1089/neu.2012.2683.
   PubMed Web of Science ®Google Scholar
• Kamimori GH, LaValle CR, Eonta SE, Carr W, Tate C, Wang KKW. Longitudinal investigation of neurotrauma serum biomarkers, behavioral characterization, and brain imaging in soldiers following repeated low-level blast exposure (New Zealand Breacher Study). Mil Med. 2018;183(Suppl 1):28–33. doi:10.1093/milmed/usx186.
   PubMedGoogle Scholar
• Kamimori GH, Reilly LA, LaValle CR, Olaghere Da Silva UB. Occupational overpressure exposure of breachers and military personnel. Shock Waves. 2017;27:837–47. doi:10.1007/s00193-017-0738-4.
   Web of Science ®Google Scholar
• Dismuke-Greer CE, Nolen TL, Nowak K, Hirsch S, Pogoda TK, Agyemang AA, Carlson KF, Belanger HG, Kenney K, Troyanskaya M, et al. Understanding the impact of mild traumatic brain injury on veteran service-connected disability: results from Chronic Effects of Neurotrauma Consortium. Brain Inj. 2018;32(10):1178–87. doi:10.1080/02699052.2018.1482428. Epub 2018 Jun 11. PubMed PMID: 29889561.
   PubMed Web of Science ®Google Scholar
• Mac Donald CL, Barber J, Jordan M, Johnson AM, Dikmen S, Fann JR, Temkin N. Early clinical predictors of 5-year outcome after concussive blast traumatic brain injury. JAMA Neurol. 2017;74(7):821–29. doi:10.1001/jamaneurol.2017.0143.
   PubMed Web of Science ®Google Scholar
• Denning JH, Shura RD. Cost of malingering mild traumatic brain injury-related cognitive deficits during compensation and pension evaluations in the veterans benefits administration. Appl Neuropsychol. 2019. Published online 17 Aug 2017;26(1):1–16. doi:10.1080/23279095.2017.1350684
   Web of Science ®Google Scholar
• McCulloch C, Searle SR. Generalized, linear, and mixed models. New York (NY): Wiley Interscience; 2001.
   Google Scholar
• Strobl C, Malley J, Tutz G. An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests. Psychol Methods. 2009;14(4):323–48. doi:10.1037/a0016973.
   PubMed Web of Science ®Google Scholar
• Berk R. An introduction to ensemble methods for data analysis. Sociol Methods Res. 2006;34(3):263–95. doi:10.1177/0049124105283119.
   Web of Science ®Google Scholar
• Buchner F, Wasem J, Schillo S. Regression trees identify relevant interactions: can this improve the predictive performance of risk adjustment? Health Econ. 2017;26:74–85. doi:10.1002/hec.3277.
   PubMed Web of Science ®Google Scholar