Use of routinely collected data in reporting falls in hospitals in a local health district in New South Wales, Australia

Trinh, Lieu Thi Thuy; Achat, Helen M; Assareh, Hassan

doi:10.1177/1833358316653490

Cited by 10 publications

(13 citation statements)

References 16 publications

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“…In Sweden, as in many other countries, all healthcare professionals are required by law to report incidents and yet our result showed a large discrepancy between the fall numbers identi ed in the EPR and the incident reporting system. This result is in accordance with other studies [14,17,20,22] and con rms that incident reporting systems do not provide a valid measure of in-hospital falls. There are several reasons why professionals do not report incidents, such as falls.…”

Section: Discussionsupporting

confidence: 91%

“…Data collection methods and sources to compare fall outcomes differ between validation studies and, to the best of our knowledge, a similar study cannot be found. Methods used to validate falls and/or fallers include text mining followed by record review versus the incident reporting systems [17], diagnostic codes found in routinely collected administrative hospitalization data versus record review [18], nursesé stimates versus fall incident reports [19], participants' self-report, participants' case notes versus the hospital reporting systems [14], incident information management system versus the health information exchange using diagnostic codes [20], record review versus the hospital's formal registry of adverse events [21], and a fall evaluation service versus incident reports [22]. In most studies, in concurrence with our study, the incident reporting systems were found not to be accurate to identify fall.…”

Section: Discussionmentioning

confidence: 99%

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Validation of Nursing Documentation Regarding in-hospital Falls: A Cohort Study

Franzén‐Dahlin

Krakau

Andersson

et al. 2020

Preprint

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BackgroundIn-hospital fall incidents are common and sensitive to nursing care. It is therefore important to have easy access to valid patient data to evaluate and follow-up nursing care. The aim of the study was to validate the nursing documentation, using a specific term in the registered nurses´ (RNs´) discharge note, regarding inpatient falls according to the outcome of a digitalized data extraction tool and the discharge note itself.MethodsAt a teaching hospital, 31,571 episodes of care were eligible for inclusion in this cohort study. A stratified sampling including five groups was used, two with random sampling and three with total sampling. In total, 1,232 episodes of care were reviewed in the electronic patient record using a study-specific protocol. Descriptive statistics were used. ResultsIn total, 590 episodes of care in the study cohort included 712 falls. When adjusted for the stratified sampling the cumulative incidence for the study population was 1.9%.The positive predictive value in total for the data extraction tool regarding the presence of any fall, in comparison with the record review, was 87.4%. Discrepancies found were, for example, that the RNs, at discharge, stated that the patient had fallen but no documented evidence of that could be detected during admission. It could also be the opposite, that the RNs correctly had documented that no fall had occurred, but the data extraction tool made an incorrect selection. When the latter had been withdrawn, the positive predictive value was 91.5%.Information about minor injuries due to the fall was less accurate. In the group where RNs had stated that the patient had fallen without injury, minor injuries had actually occurred in 28.3% of the episodes of care. Conclusions The use of a specific term regarding fall in the RNs´ discharge note seems to be a valid and reliable data measurement and can be used continuously to evaluate and follow-up nursing care.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Validation of Nursing Documentation Regarding in-hospital Falls: A Cohort Study

Franzén‐Dahlin

Krakau

Andersson

et al. 2020

Preprint

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“…In the clinical environment, reported that the introduction of a dedicated instrumental vaginal deliveries form improved the accuracy and completeness of clinical documentation. Trinh et al (2017), in their comparison of two routinely collected datasets (Incident Information Management System and the health information exchange in hospitals in New South Wales, Australia), found these two methods captured vastly different data on the incidence of falls.…”

Section: Accuracymentioning

confidence: 99%

Data quality: “Garbage in – garbage out”

Kilkenny

Robinson

2018

HIM J

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“…9 In addition, medical record review provides quality assurance for routine incident reporting. 10 A previous study 11 in NSW linked the IIMS and MRCD datasets in the adult population, but did not review medical records. There are no published studies where the IIMS and MRCD datasets have been linked to examine the quality of paediatric hospital falls data in the Australian context.…”

Section: Introductionmentioning

confidence: 99%

Falling short: examination of the validity of methods used to identify paediatric hospital falls in NSW, Australia

Feuerlicht¹,

Agaliotis²,

Hinchcliff³

2020

Public Healt Res Pract

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Objective: Hospital falls are a major cause of costly harm. This descriptive epidemiological study reports the results of a data linkage and medical record review to examine the relative utility of these methods for identifying paediatric in-hospital falls. Type of program or service:The study was conducted across two tertiary and quaternary specialist paediatric hospitals in New South Wales (NSW), Australia.Methods: A retrospective audit was conducted of paediatric falls occurring in hospital between 1 July 2015 and 30 June 2016. Falls were identified using two systems: the Incident Information Management System (IIMS) and medical records coded data (MRCD). These data were linked, and falls were verified using medical record review. Results:Of the 146 in-hospital falls identified, only 28 (19%) were included in both systems. The IIMS identified 137 falls, with five excluded. The MRCD identified 63 admissions in which falls occurred, with 27 excluded, and screening of clinical notes found 42 falls in the remaining 36 admissions. Lessons learnt:There was a discrepancy in the number of falls identified in the two administrative datasets due to different inclusion criteria. The medical record review provided additional practice-relevant information that was unavailable within the two datasets. This descriptive epidemiological study highlights the value of combining data linkage with medical record review, but also the need for more critical reflection on the methods used to collect and report falls data in Australian hospitals, so that comprehensive and accurate data can be used to inform quality and safety interventions. This analysis will inform improvements to data capture methods and provide data to advise paediatric falls prevention strategies within the NSW paediatric hospital context.Falling short: examination of the validity of methods used to identify paediatric hospital falls in NSW, Australia

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Use of routinely collected data in reporting falls in hospitals in a local health district in New South Wales, Australia

Abstract: IIMS captured the vast majority of falls in hospitals but failed to report one-third of falls recorded in HIE.

Cited by 10 publications

References 16 publications

Validation of Nursing Documentation Regarding in-hospital Falls: A Cohort Study

Validation of Nursing Documentation Regarding in-hospital Falls: A Cohort Study

Data quality: “Garbage in – garbage out”

Falling short: examination of the validity of methods used to identify paediatric hospital falls in NSW, Australia

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