Prehospital Protocols Reducing Long Spinal Board Use Are Not Associated with a Change in Incidence of Spinal Cord Injury.

Introduction: Many emergency medical services (EMS) agencies have de-emphasized or eliminated the use of long spinal boards (LSB) for patients with possible spinal injury. We sought to determine if implementation of spinal motion restriction (SMR) protocols, which reduce LSB use, was associated with an increase in spinal cord injury (SCI). Methods: This retrospective observational study includes EMS encounters from January 1, 2013 to December 31, 2015 submitted by SMR-adopting ground-based agencies to a state EMS database with hospital discharge data. Encounters were excluded if SMR implementation date was unknown, occurred during a 3-month run-in period, or were duplicates. Study samples include patients with traumatic injury (TI), possible spinal trauma (P-ST), and verified spinal trauma (V-ST) using hospital discharge ICD-9/10 diagnosis codes. The incidence of SCI before and after implementation of SMR was compared using Chi-squared and logistic regression. Results: From 1,005,978 linked encounters, 104,315 unique encounters with traumatic injury and known SMR implementation date were identified with 51,199 cases of P-ST and 5,178 V-ST cases. The incidence of SCI in the pre-SMR and post-SMR interval for each group was: TI, 0.20% vs. 0.22% (p = 0.390); P-ST, 0.40% vs. 0.45% (p = 0.436); and V-ST, 4.04% vs. 4.37% (p = 0.561). Age and injury severity adjusted odds ratio of SCI in the highest risk cohort of patients with V-ST was 1.097 after SMR implementation (95% CI 0.818-1.472). Conclusion: In this limited study, no change in the incidence of SCI was identified following implementation of SMR protocols. Prospective evaluation of this question is necessary to evaluate the safety of SMR protocols.

Improving the Continuum of Care by Bridging the Gap between Prehospital and Hospital Discharge Data through Stepwise Deterministic Linkage.

Objective: To describe the process, benefits, and challenges of linking Arizona's prehospital registry to hospital discharge data. Methods: Data were queried from the Arizona Prehospital Information and Emergency Medical Services Registry System (AZ-PIERS) and the Arizona Hospital Discharge Database (HDD) for the calendar year 2015. To maximize the number of matched records, the databases were deterministically linked in 17 steps using different combinations/variations of patient personal identifiers. Random samples of at least 1% of matched pairs from each of 16 linkage steps (excluding Step 1) were manually reviewed to assess the rate of false positive matches. Results: A total of 626,413 records were reported to AZ-PIERS in 2015. Of those, 503,715 qualified for linkage. These records were matched against 3,125,689 discharge records reported to the HDD in 2015. The first step, which involved exact matching on first name, last name, date of birth, gender, and date of incident/date of admission, yielded a linkage of 64.6% (n = 325,156). The 16 successive steps yielded a further linkage of 26.6% (n = 134,006) for a total linkage of 91.2% (n = 459,162). The manual review indicated an overall false positive match rate for the 16 reviewed steps of 6.96% (n = 99). The 2 steps with the highest false positive match rates were Step 16 (43.02%, n = 77) and Step 17 (31.43%, n = 11). Conclusion: It is feasible to link prehospital and hospital data using stepwise deterministic linkage; this method returns a high linkage rate with a low false positive error rate. Data linkage is vital to identifying and bridging gaps in the continuum of care and is a useful tool in statewide and agency-specific research and quality improvement.

Racial/Ethnic Disparities in Rates of Traumatic Injury in Arizona, 2011-2012.

OBJECTIVE: The purpose of this study was to compare the rates of traumatic injury among five racial/ethnic groups in Arizona and to identify which mechanisms and intents of traumatic injury were predominant in each group. METHODS: We obtained 2011 and 2012 data on traumatic injury from Arizona's trauma registry and data on mortality from Arizona's death registry. We calculated location- and age-adjusted rates (aRs) of traumatic injury and rates of mortality per 100,000 Arizona residents and rate ratios (RRs) for each racial/ethnic group. We also calculated race/ethnicity specific aRs and RRs by mechanism of injury, intent of injury, and alcohol use. RESULTS: We analyzed data on 58,034 cases of traumatic injury. After adjusting for age and location, American Indians/Alaska Natives (AI/ANs) had the highest overall rate of traumatic injury (n = 6,287; aR = 729) and Asian Americans/Pacific Islanders had the lowest overall rate of traumatic injury (n = 553; aR = 141). By intent, AI/ANs had the highest rate of homicide/assault-related traumatic injury (n = 2,170; aR = 221) and by mechanism, non-Hispanic black/African American people had the highest rate of firearm-related traumatic injury (n = 265; aR = 40). In 2011-2012, 8,868 deaths in Arizona were related to traumatic injury. AI/ANs had the highest adjusted mortality rate (n = 716; aR = 95). CONCLUSION: Racial/ethnic disparities in traumatic injuries persisted after adjusting for age and injury location. Understanding how these disparities differ by mechanism, intent, and alcohol use may lead to the development of more effective initiatives to prevent traumatic injury.

Association of insurance status with health outcomes following traumatic injury: statewide multicenter analysis.

INTRODUCTION: Recognizing disparities in definitive care for traumatic injuries created by insurance status may help reduce the higher risk of trauma-related mortality in this population. Our objective was to understand the relationship between patients' insurance status and trauma outcomes. METHODS: We collected data on all patients involved in traumatic injury from eight Level I and 15 Level IV trauma centers, and four non-designated hospitals through Arizona State Trauma Registry between January 1, 2008 and December 31, 2011. Of 109,497 records queried, we excluded 29,062 (26.5%) due to missing data on primary payer, sex, race, zip code of residence, injury severity score (ISS), and alcohol or drug use. Of the 80,435 cases analyzed, 13.3% were self-pay, 38.8% were Medicaid, 13% were Medicare, and 35% were private insurance. We evaluated the association between survival and insurance status (private insurance, Medicare, Medicaid, and self-pay) using multiple logistic regression analyses after adjusting for race/ethnicity (White, Black/African American, Hispanic, and American Indian/Alaska Native), age, gender, income, ISS and injury type (penetrating or blunt). RESULTS: The self-pay group was more likely to suffer from penetrating trauma (18.2%) than the privately insured group (6.0%), p<0.0001. There were more non-White (53%) self-pay patients compared to the private insurance group (28.3%), p<0.0001. Additionally, the self-pay group had significantly higher mortality (4.3%) as compared to private insurance (1.9%), p<0.0001. A simple logistic regression revealed higher mortality for self-pay patients (crude OR= 2.32, 95% CI [2.07-2.67]) as well as Medicare patients (crude OR= 2.35, 95% CI [2.54-3.24]) as compared to private insurance. After adjusting for confounding, a multiple logistic regression revealed that mortality was highest for self-pay patients as compared to private insurance (adjusted OR= 2.76, 95% CI [2.30-3.32]). CONCLUSION: These results demonstrate that after controlling for confounding variables, self-pay patients had a significantly higher risk of mortality following a traumatic injury as compared to any other insurance-type groups. Further research is warranted to understand this finding and possibly decrease the mortality rate in this population.

Public health surveillance for coccidioidomycosis in Arizona.

Coccidioidomycosis or Valley Fever is a fungal disease that occurs primarily in the southwestern United States. Of the estimated 150,000 U. S. coccidioidomycosis infections per year, approximately 60% occur in Arizona, making this state the focal point for investigation of the disease. In this manuscript, we describe the epidemiology of coccidioidomycosis reported in Arizona over the last decade, hypotheses for the findings, and Arizona's response to the rising epidemic. Coccidioidomycosis surveillance data in Arizona consist of basic demographics of all laboratory and physician-diagnosed cases, the reporting of which has been mandated by law since 1997. The rate of reported coccidioidomycosis has more than quadrupled over the last decade from 21 cases per 100,000 population in 1997 to 91 cases per 100,000 in 2006 (P < 0.001). Case rates in older age groups (>/=65 years old) have more than doubled since 2000 (P < 0.001). These data demonstrate the rising coccidioidomycosis epidemic in Arizona, especially among the elderly. The increase in the numbers of reported cases can be partially explained by the institution of mandatory laboratory reporting in 1997, but the cause of the persistent rise after 1999 is unknown. Further investigation of coccidioidomycosis will not only assist with the development of public health interventions to control this disease in Arizona and the southwestern United States, but will also provide important information to prepare for a bioterrorism event caused by this select agent.