FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1977249901> ?p ?o ?g. }

• W1977249901 endingPage "1383" @default.
• W1977249901 startingPage "1382" @default.
• W1977249901 abstract "In 1994, Lawless1 compared the situation of alarms in the intensive care unit (ICU) with the boy who cried wolf in the famous fable by Aesop, alluding to the danger of desensitization of caregivers to true medical device alarms through the overwhelming number of false medical device alarms that he observed on a pediatric ICU. Alarm limits may be set dangerously broad, or alarms may even be completely disabled to reduce the nuisance from false alarms. Even at these settings, clinicians may tolerate an alarm for up to 10 min before taking action.2,3 This situation cries for immediate remedy. The sad reality, although, is that not much seems to have changed over the nearly 15 yr since Lawless' publication. The current literature and ongoing research efforts4,5 (reviewed in Ref. 6) as well as recent data from our own group,7 show that still the vast majority of medical device alarms are false positives. Interestingly, there is no scarcity of research addressing the problem of medical device alarms. Many different approaches have been studied in the fields of statistics and artificial intelligence as well as biomedical and human factors engineering.6 Several approaches have shown efficacy and effectiveness in reducing the rate of false alarms in clinical study. Still, very little has been implemented in commercially available medical devices. In this situation Görges et al.8 promise hope in their article published in this issue of Anesthesia & Analgesia. In their study, they first acquired comprehensive clinical data on medical device alarms and then investigated two approaches to reduce the number of false-positive alarms. The authors must be commended for their efforts, as we know from other researchers and our own experience how much stamina it takes to acquire alarm data and consistently annotate sufficiently large numbers of medical device alarms. Görges et al. confirm that only the minority of medical device alarms are clinically relevant—in their study, 23% of all alarms. They also found that not only were six alarms activated per hour per bed, but also alarms were sounding 3½ min per hour per bed. Extrapolating to a 10-bed ICU, this means that a false alarm is active, i.e., making some noise or “crying,” nearly 50% of the time, day and night, 24/7. These numbers are in line with other studies. If we keep in mind that it took the boy in Aesop's fable only two false alarms to make the shepherds ignore the third but true and deadly alarm, the current situation of medical device alarms seems mindboggling. Of course, the study by Görges et al. has distinct weaknesses, most of which the authors diligently discuss: night shifts were not included in the study, the physical presence of the observer may have induced a Hawthorne effect, clinical annotations of alarms were subjective, and there may have been significant intra- and interobserver variability. Moreover, clinical practice patterns in the study ICU may differ from other institutions, which may further affect the generalizability of the reported results, as may the differences in annotation schemata between different studies, as pointed out by the authors. But this is true for each and every clinical alarm study published as of today. And still, all studies come to similar conclusions despite their differences in methodology and clinical settings, actually strengthening rather than weakening our point about the inadequacy of current device alarms. The promise of hope arising from the study by Görges et al. is based on their suggestions for tackling this problem. Based on two of their observations, they proposed two different approaches to reduce clinically irrelevant alarms. First, they observed that about one third of all alarms just ended without any caregiver intervention. This led them to test whether a short delay may reduce the number of clinically irrelevant alarms. And indeed, a 19-s delay would have removed 67% of all ignored and ineffective alarms. For such a delay not to compromise patient safety, however, we must assume that relevant alarms will not have to be answered in less than the delay period. This approach of alarm delay is not new and has also been implemented in some patient monitors. But the maximum delays in commercially available devices range from 4 to 10 s, and such delays would reduce the number of false alarms only by 9%–35% in this data set. Although the longer time delay proposed by Görges et al. seems effective, the question remains whether it is safe. The answer is probably “yes,” especially if certain type of alarms, such as asystole and apnea, are excluded from this delay, as suggested by the authors. Our data indicate that the vast majority of false alarms stem from pulse oximetry and invasive blood pressure monitoring, for which a delay of up to 20 s may be considered safe. Actually, if the reduction of false alarms by such an approach eventually leads to a resensitization of caregivers toward truly dangerous alarms, patient safety may significantly be improved. On the other hand, established industry norms suggest that alarm delays, from the occurrence of the physiological alarm situation to the actual alarm annunciation, should, for instance, not exceed 10 s for hemodynamic monitors and 17 s for certain ventilator alarms.9,10 Therefore, vendors may be reluctant to introduce longer alarm delays, if only to safeguard themselves against litigation. In any case, determination of acceptable alarm delays may require further research. The second important observation reported by Görges et al. is the large percentage of irrelevant alarms during nursing care for the patient. This finding is consistent with other studies, where up to 70% of all technically false alarms (or one quarter of all alarms) were caused by manipulation.7 Actually, a disproportionate rate of clinically irrelevant alarms occurred while a caregiver was close to the patient. Therefore, the authors propose that a system that could automatically detect information about the patient, such as suctioning, positioning, oral care, or blood draws, could be used to validate device alarms before they are annunciated, and thus further reduce the number of irrelevant alarms. In contrast to the simple and clear recommendation about alarm delays, this approach is vaguer and much more involved. Challenges are the identification and description of clinical context and the communication of this information to the medical device or alarm system. Although some information may be derived from existing signals, e.g., in case of a-line blood draw or flushing, and some information may even be entered manually by the caregiver, e.g., the start and end of nursing procedures, automatic detection of alarm context may require additional sensing and data processing technologies. This may include pressure and vibration sensors in the bedframe or the use of ultrawide band radar technology to detect patient movement and body position. Moreover, closer communication between medical devices will be required. Further advanced research will be needed before truly “context sensitive” device alarms become reality. The study by Görges et al. adds to the body of evidence on medical device alarms in that it further emphasizes the urgent need to improve device alarms. The authors also make one simple and straightforward suggestion that may even be implemented in the near future, namely, alarm delays. Their second suggestion, for context-sensitive device alarms, may even bear greater promise, but will require significant research and development efforts. And in the meantime, the wolf keeps on crying." @default.
• W1977249901 created "2016-06-24" @default.
• W1977249901 creator A5015519778 @default.
• W1977249901 creator A5088596514 @default.
• W1977249901 date "2009-05-01" @default.
• W1977249901 modified "2023-10-18" @default.
• W1977249901 title "The Crying Wolf: Still Crying?" @default.
• W1977249901 cites W1992418075 @default.
• W1977249901 cites W2004487242 @default.
• W1977249901 cites W2022411992 @default.
• W1977249901 cites W2070389865 @default.
• W1977249901 cites W2109197536 @default.
• W1977249901 cites W2160650728 @default.
• W1977249901 cites W2163624457 @default.
• W1977249901 doi "https://doi.org/10.1213/ane.0b013e31819ed484" @default.
• W1977249901 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/19372311" @default.
• W1977249901 hasPublicationYear "2009" @default.
• W1977249901 type Work @default.
• W1977249901 sameAs 1977249901 @default.
• W1977249901 citedByCount "16" @default.
• W1977249901 countsByYear W19772499012012 @default.
• W1977249901 countsByYear W19772499012013 @default.
• W1977249901 countsByYear W19772499012014 @default.
• W1977249901 countsByYear W19772499012016 @default.
• W1977249901 countsByYear W19772499012017 @default.
• W1977249901 countsByYear W19772499012019 @default.
• W1977249901 crossrefType "journal-article" @default.
• W1977249901 hasAuthorship W1977249901A5015519778 @default.
• W1977249901 hasAuthorship W1977249901A5088596514 @default.
• W1977249901 hasBestOaLocation W19772499011 @default.
• W1977249901 hasConcept C118552586 @default.
• W1977249901 hasConcept C2778013503 @default.
• W1977249901 hasConcept C71924100 @default.
• W1977249901 hasConceptScore W1977249901C118552586 @default.
• W1977249901 hasConceptScore W1977249901C2778013503 @default.
• W1977249901 hasConceptScore W1977249901C71924100 @default.
• W1977249901 hasIssue "5" @default.
• W1977249901 hasLocation W19772499011 @default.
• W1977249901 hasLocation W19772499012 @default.
• W1977249901 hasOpenAccess W1977249901 @default.
• W1977249901 hasPrimaryLocation W19772499011 @default.
• W1977249901 hasRelatedWork W1506200166 @default.
• W1977249901 hasRelatedWork W1995515455 @default.
• W1977249901 hasRelatedWork W2048182022 @default.
• W1977249901 hasRelatedWork W2080531066 @default.
• W1977249901 hasRelatedWork W2604872355 @default.
• W1977249901 hasRelatedWork W2748952813 @default.
• W1977249901 hasRelatedWork W2899084033 @default.
• W1977249901 hasRelatedWork W3031052312 @default.
• W1977249901 hasRelatedWork W3032375762 @default.
• W1977249901 hasRelatedWork W3108674512 @default.
• W1977249901 hasVolume "108" @default.
• W1977249901 isParatext "false" @default.
• W1977249901 isRetracted "false" @default.
• W1977249901 magId "1977249901" @default.
• W1977249901 workType "article" @default.