Identifying Medication Misadventures: Poor Agreement Among Medical Record, Physician, Nurse, and Patient Reports

Abstract

Little overlap was noted among the individual medication misadventure reporting methods, suggesting the need to use multiple complementary methods to identify medication misadventures in hospitalized patients. These findings have important implications for development of surveillance systems, design of prevention initiatives, and future medication safety research.

Can patients report patient safety incidents in a hospital setting? A systematic review

“…However, the terminology used to describe such incidents did vary considerably across papers (see table 3). Four papers were concerned only with issues related to medication or treatment 25 28 30 32. Where a broader perspective was taken, papers were split between those only concerned with adverse events as categorised by physician review,23 26 31 33 and those that widened this categorisation to also include near miss/close calls, and medical error with minimal or no risk of harm 17 24 29.…”

“…Of the remaining eight papers, five used physicians only to undertake the classification of PSIs,17 23 24 26 33 two used physicians and nurses,29 31 and one reported classification by both physicians and pharmacists 25. Three of these papers did not report the number of patient reported PSIs, but only those which after review had been categorised as PSIs.…”

“…Three of these papers did not report the number of patient reported PSIs, but only those which after review had been categorised as PSIs. In the five papers that did report on both,17 24 25 29 33 there was wide variation in the degree to which patient reports were judged to constitute classified PSIs (17%–100% $\stackrel{true–}{x}$=51%).…”

Detecting adverse drug events through data mining

“…4 An additional challenge to successfully detecting ADEs is that each reporting method detects a unique subset of events. 5 The importance of medical record review and the necessity to consider other sources when gathering ADE The answer to these questions relies on the ability to create an automated algorithm for medical record review. Research has increasingly focused on algorithms since the first model was reported in 1991.…”

“…We conducted a data-mining pilot study that took advantage of an ADE database from a previously completed study at the University of Iowa Hospitals and Clinics, which compared ADE reporting rates of physicians, nurses, and patients with a standard medical record review. 5 In that study, events were classified as ADEs (injuries resulting from the administration of a drug), potential ADEs (incidents with the potential for injury related to a drug), or medication errors (errors in the process of ordering or delivering medication). The study examined 132 consecutive hospital admissions and detected a combined total of 106 ADEs.…”