Incidence of chronic respiratory conditions among oil spill responders: Five years of follow-up in the Deepwater Horizon Oil Spill Coast Guard Cohort study

To examine potential sources of errors at each step of the described inpatient International Classification of Diseases (ICD) coding process. The use of disease codes from the ICD has expanded from classifying morbidity and mortality information for statistical purposes to diverse sets of applications in research, health care policy, and health care finance. By describing a brief history of ICD coding, detailing the process for assigning codes, identifying where errors can be introduced into the process, and reviewing methods for examining code accuracy, we help code users more systematically evaluate code accuracy for their particular applications. We summarize the inpatient ICD diagnostic coding process from patient admission to diagnostic code assignment. We examine potential sources of errors at each step and offer code users a tool for systematically evaluating code accuracy. Main error sources along the "patient trajectory" include amount and quality of information at admission, communication among patients and providers, the clinician's knowledge and experience with the illness, and the clinician's attention to detail. Main error sources along the "paper trail" include variance in the electronic and written records, coder training and experience, facility quality-control efforts, and unintentional and intentional coder errors, such as misspecification, unbundling, and upcoding. By clearly specifying the code assignment process and heightening their awareness of potential error sources, code users can better evaluate the applicability and limitations of codes for their particular situations. ICD codes can then be used in the most appropriate ways.

Background This paper examines the association between use of protective devices, frequency of acute health problems and health-protection information received by participants engaged in the Prestige oil spill clean-up in Asturias and Cantabria, Spain. Methods We studied 133 seamen, 135 bird cleaners, 266 volunteers and 265 paid workers selected by random sampling, stratified by type of worker and number of working days. Information was collected by telephone interview conducted in June 2003. The association of interest was summarized, using odds ratios (OR) obtained from logistic regression. Results Health-protection briefing was associated with use of protective devices and clothing. Uninformed subjects registered a significant excess risk of itchy eyes (OR:2.89; 95%CI:1.21–6.90), nausea/vomiting/dizziness (OR:2.25; 95%CI:1.17–4.32) and throat and respiratory problems (OR:2.30; 95%CI:1.15–4.61). There was a noteworthy significant excess risk of headaches (OR:3.86: 95%CI:1.74–8.54) and respiratory problems (OR:2.43; 95%CI:1.02–5.79) among uninformed paid workers. Seamen, the group most exposed to the fuel-oil, were the worst informed and registered the highest frequency of toxicological problems. Conclusion Proper health-protection briefing was associated with greater use of protective devices and lower frequency of health problems. Among seamen, however, the results indicate poorer dissemination of information and the need of specific guidelines for removing fuel-oil at sea.

To provide a hazard prioritisation for reported chemical constituents of cigarette smoke using toxicological risk assessment principles and assumptions. The purpose is to inform prevention efforts using harm reduction. International Agency for Research on Cancer Monographs; California and US Environmental Protection Agency cancer potency factors (CPFs) and reference exposure levels; scientific journals and government reports from the USA, Canada, and New Zealand. This was an inclusive review of studies reporting yields of cigarette smoke constituents using standard ISO methods. Where possible, the midpoint of reported ranges of yields was used. Data on 158 compounds in cigarette smoke were found. Of these, 45 were known or suspected human carcinogens. Cancer potency factors were available for 40 of these compounds and reference exposure levels (RELs) for non-cancer effects were found for 17. A cancer risk index (CRI) was calculated by multiplying yield levels with CPFs. A non-cancer risk index (NCRI) was calculated by dividing yield levels with RELs. Gas phase constituents dominate both CRI and NCRI for cigarette smoke. The contribution of 1,3-butadiene (BDE) to CRI was more than twice that of the next highest contributing carcinogen (acrylonitrile) using potencies from the State of California EPA. Using those potencies from the USEPA, BDE ranked third behind arsenic and acetaldehyde. A comparison of CRI estimates with estimates of smoking related cancer deaths in the USA showed that the CRI underestimates the observed cancer rates by about fivefold using ISO yields in the exposure estimate. The application of toxicological risk assessment methods to cigarette smoke provides a plausible and objective framework for the prioritisation of carcinogens and other toxicant hazards in cigarette smoke. However, this framework does not enable the prediction of actual cancer risk for a number of reasons that are discussed. Further, the lack of toxicology data on cardiovascular end points for specific chemicals makes the use of this framework less useful for cardiovascular toxicity. The bases for these priorities need to be constantly re-evaluated as new toxicology information emerges.