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Karen L Scott

Publications and source records attributed to Karen L Scott.

3 recordsLinked to original sources

Carboxyhemoglobin measurement by hospitals: implications for the diagnosis of carbon monoxide poisoning.

Most case definitions for carbon monoxide (CO) poisoning include demonstration of an elevated blood carboxyhemoglobin (COHb) concentration. Further, it is generally believed that treatment of CO poisoning is more effective when performed as soon as possible after the exposure. This suggests that a hospital's inability to measure blood COHb could lead to delayed or missed diagnosis or treatment. This study evaluated the ability of hospitals in the Pacific Northwest to measure COHb levels. The clinical laboratory of every acute care hospital in Washington, Idaho, Montana, and Alaska was surveyed regarding the ability to measure COHb levels, the method utilized and the time required. If they could not measure COHb, they were asked whether samples are sent elsewhere, the location of the referral laboratory, and time required. Results were then compared to the list of hospitals referring CO-poisoned patients to a regional center for hyperbaric oxygen therapy from 2003-2004. In the four states, only 44% of acute care hospitals have the capability to measure COHb. The remaining 56% send blood samples to other laboratories. The average time to get a result is 10 +/- 10 min in hospitals with co-oximetry and 904 +/- 1360 min in those without, a difference of 15 h (p < 0.0001). When samples are sent out, the average distance is 121 miles, often bypassing a hospital with CO-oximetry capability. Over 90% of CO-poisoned patients referred for hyperbaric treatment came from hospitals able to measure COHb. Fewer than one-half of acute care hospitals in a four-state region have the capability to measure COHb levels. This has the potential to significantly impact diagnosis or treatment of patients with acute CO poisoning.

Alaska↗

Use of a noninvasive pulse CO-oximeter to measure blood carboxyhemoglobin levels in bingo players.

BACKGROUND: Though smokers are known to have elevated blood carboxyhemoglobin (COHb), due to inhalation of carbon monoxide (CO) in cigarette smoke, limited data exist regarding COHb levels in nonsmokers exposed to secondhand smoke. METHODS: COHb was measured using a new noninvasive pulse CO-oximeter (Rad-57, Masimo, Irvine, California) in 38 subjects entering a bingo hall where smoking was allowed, then again as they exited 3 hours later. RESULTS: The mean +/- SD baseline COHb for the entire group was 3.3 +/- 1.8%, for the 23 nonsmokers it was 2.2 +/- 0.7%, and for the 15 smokers it was 4.9 +/- 1.9%. The nonsmokers' mean COHb was unchanged, at 2.2 +/- 0.8%, whereas the smokers' mean COHb fell to 3.2 +/- 1.9%. CONCLUSIONS: The nonsmokers were not significantly exposed to CO from secondhand smoke in the setting we tested. The smokers probably consumed fewer cigarettes while playing bingo than they did prior to arrival. The Rad-57 pulse CO-oximeter is easy to use in the ambulatory setting.

Blood Gas Monitoring, Transcutaneous↗

Implementing a commercial rule base as a medication order safety net.

A commercial rule base (Cerner Multum) was used to identify medication orders exceeding recommended dosage limits at five hospitals within BJC HealthCare, an integrated health care system. During initial testing, clinical pharmacists determined that there was an excessive number of nuisance and clinically insignificant alerts, with an overall alert rate of 9.2%. A method for customizing the commercial rule base was implemented to increase rule specificity for problematic rules. The system was subsequently deployed at two facilities and achieved alert rates of less than 1%. Pharmacists screened these alerts and contacted ordering physicians in 21% of cases. Physicians made therapeutic changes in response to 38% of alerts presented to them. By applying simple techniques to customize rules, commercial rule bases can be used to rapidly deploy a safety net to screen drug orders for excessive dosages, while preserving the rule architecture for later implementations of more finely tuned clinical decision support.

Clinical Pharmacy Information Systems↗