How Often Do Workplace Injuries Go Unreported?

Transcription

1 How Often Do Workplace Injuries Go Unreported? HARVARD CATALYST BIOSTATISTICS PROGRAM SEMINAR MARCH 21, 2012 Les Boden Boston University School of Public Health U.N. Window Washer Bedrich Grunzweig 1

2 Occupational Injury And Illness Estimates of 4-8 million workplace losttime injuries annually, 6,000 deaths Unknown number of illnesses Injury cost $110 billion annually NIH estimates cancer costs: $226 billion Note: incident age much younger for occ. injuries: average 36 years old. 2

3 Motivation for this study Studies in individual work settings and of specific injuries show low reporting 1980s studies of fatal traumatic injuries Multiple sources: death certificates, medical examiner reports, workers comp, etc. Findings? (Stout and Bell 1991) 40-70% of fatal traumatic work-related injuries went unreported 4

4 Reported Workplace Fatalities Catalyst

5 Why Do We Care? Better Surveillance Can Identify hazards Characterize burden of injuries and illnesses Guide prevention strategies 6

6 Participating States Minnesota New Mexico Oregon Washington West Virginia Wisconsin California: in process CHSWC

7 Data Sources State Workers Compensation Data (WC) If medical or cash benefits paid Reported to state WC agency Bureau of Labor Statistics Annual Survey of Injuries and Illnesses (BLS) Stratified probability sample of employers Provides state and national estimates of non-fatal injury incidence 9

8 What We Did Collect BLS and WC injury data Determine which injuries are reported to BLS only, to WC only, & to both Use capture-recapture to estimate the number of unreported injuries 10

9 Important Issues Accurate linking (no lost marks assumption) Harmonizing scope (closed population assumption) Source dependence Population heterogeneity 12

10 Linking cases across data sources Link datasets for specific time frame Deterministic linkage cases match on predetermined number of variables Soundex helps with alternate name spelling Probabilistic linkage Clerical review of indeterminate cases 13

11 Case Linkage Common elements WC SOII Worker first name X X ( or F.I.) Worker last name X X Employer name X X Employer identifier (FEIN) X X Employer address X X Date of injury X X Date of birth X X (or age) Sex X X 14

12 ER_ ID DOB1 DOB2 DOI1 DOI2 ER_NAME1 ER_NAME2 F _ N A M E 1 L_ NAME1 F _ N A M E 2 L_ NAME2 = 12/15/98 12/16/98 GHI GHI T R. T RIVERS ~= 09/28/70 06/22/71 05/08/98 08/05/98 ALP CORP GH CONSTR S JONES S JONES ~= 05/19/65 05/19/65 11/10/98 11/12/98 LAND AUTO BLANK VOLVO J YOUNG J EAST ~= 12/15/64 02/15/64 03/19/01 03/19/01 A1 LOGISTIC A1 LOGISTIC F SMITH F SMITH ~= 06/15/59 06/19/59 01/09/99 01/09/99 AMR A AMBULANCE K RICH K RICH = 05/18/98 05/18/98 JOHNSON JOHNSON INC R BORN R WING. 02/27/67 02/18/99 02/18/99 AA INC AA K BASS C BASS. 01/05/44 10/05/44 04/27/98 04/27/98 A1 CAPITAL HILTON HOTEL I YU I YU. 06/14/69 08/14/59 07/26/00 07/26/00 AUTOZONE AL S PARTS D ACME D ACME ~= 11/22/45 11/22/45 06/29/99 06/29/99 TT BAKING TIPTOP S JOHN J SMITH ~= 04/07/66 08/10/00 08/10/00 AJAX TIRE AJAX TIRE D PENN D PENN ~= 02/12/77 01/16/98 01/16/ JUNK 1800 JUNK G WALSH G WALSH CHSWC

13 Scope of Data Sources Data source Injury or Illness report Inclusion criteria Excluded populations Sampling BLS Employer >=1 work days lost WC Worker or employer No min days, 0-3 days= <4 (if medical costs) Agriculture<10 employees Self-employed, other WC systems Stratified Sample Population 16

14 Harmonizing Scope Restrict BLS to 4+ days Restrict BLS to exclude Longshore and harbor workers Railroad workers Restrict WC to Exclude agriculture < 10 employees Include only establishments sampled by BLS 17

15 Source Dependence Capture-recapture generally assumes that the reporting sources are independent What about in this case? 18

16 Source Independence Unlikely No WC report means BLS report less likely Doctor doesn t diagnose (esp. disease) Worker doesn t report injury Employer doesn t think it s work-related Employer uses WC records to fill out BLS survey => Positive source dependence => Estimates of underreporting lower than actual number of missed cases 19

17 Reporting Completeness Source Independence (OR=1) WA WV OR WI NM MN WC 93% 91% 77% 75% 67% 65% BLS 55% 76% 56% 65% 51% 68% Neither 4% 3% 12% 8% 16% 13% CHSWC

18 Underreporting Estimates Impact of Source Dependence WA WV OR WI NM MN OR=1 4% 3% 12% 8% 16% 13% OR=3 10% 7% 24% 19% 33% 26% OR=5 14% 10% 32% 26% 43% 33% CHSWC

19 Estimation Steps Initially: unadjusted estimates Then model heterogenous capture probabilities Multinomial logit estimation Corrects covariance-induced dependence Informs about factors related to reporting Sensitivity analysis to examine potential effect of source dependence 22

20 Reasons for Underreporting From all data: Injury occurred late in year From WC linked/unlinked data Injury reported after end of the year Dispute over payment of WC benefits Delay between date of injury and date injury reported to employer 23

21 Reasons for Underreporting II From employer survey: Employer didn t think injury was workrelated Employer was unclear about reporting requirements When injury not initially reportable (no lost work) did not add if became reportable later 24

22 Difficult to Quantify Reasons Exclusions: independent contractors Worker afraid to report Worker doesn t know about WC Employer suppresses reporting to avoid WC costs Disadvantage in bidding for contracts Safety bingo 25

23 Difficult to Quantify Reasons II WC law places barriers to benefits Objective evidence of disability Increasing amount of evidence needed to receive benefits Exclude diseases of aging Stigmatization of injured workers Drug testing of those reporting injuries Publicity designed to link WC and fraud 26

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25 Conclusion Capture-recapture can be useful in reducing surveillance bias Accurate linking, identical scope are both important and can be difficult Source dependence is probably important Cannot identify source dependence with only 2 sources 28