Limited research has characterized nonfatal injury/illness in Alaska's hazardous fishing industry. This study aimed to determine (a) the utility of linking datasets to conduct surveillance, and (b) injury/illness patterns during 2012-2016. Data were obtained from the Alaska Trauma Registry (ATR), Fishermen's Fund (FF), and US Coast Guard (USCG). Datasets were coded to identify patterns in injury/illness characteristics and circumstances. Probabilistic linkage methods were utilized to identify unique incidents that appeared in more than one dataset. After linking datasets, 3,014 unique injury/illness cases were identified. By dataset, 2,365 cases appeared only in FF, 486 only in USCG, 110 only in ATR, 25 in ATR and FF, 15 in ATR and USCG, 10 in USCG and FF, and 3 in all datasets. FF mainly captured claims submitted by small, independently-owned vessels in Southcentral and Southeastern Alaska. In contrast, USCG mainly captured reports from large, company-owned vessels in Western Alaska. By nature, cases were most frequently sprains, strain, and tears (27%), cuts (15%), and fractures (11%). Across fleets, injuries/illnesses most frequently resulted from contact with objects and equipment (41%), overexertion and bodily reaction (27%), and slips, trips, and falls (20%). Work processes associated with traumatic injuries were most frequently hauling gear (18%) and walking, climbing, and descending (18%). Half of all injuries were of moderate severity (53%). Linking datasets, which capture different segments of Alaska's fishing industry, provides the most comprehensive understanding of nonfatal injury/illness to date. These results, stratified by fleet and severity, will inform prevention strategies.
Keywords: Probabilistic linkage; occupational safety and health.