Accidents and Drug Treatment in a Psychiatric Hospital

Ballinger, Brian R.; Ramsay, Anne

doi:10.1192/bjp.126.5.462

Cited by 18 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Two studies reported that fallers received psychotropic medication within 24 hours before the fall but did not differentiate between acute changes in medication or chronically administered medication. 15 , 25 Chan et al 21 reported that changes to medication within 24 hours were associated with falling but did not specify which kind of medication. Vaughn et al 19 reported that involuntary hospitalized patients fell more than voluntary patients.…”

Section: Resultsmentioning

confidence: 99%

“…Extrinsic risk factors concern medication and environmental factors like clothing, place, time of day, walking aids, and nearby staff. Studies reporting on medication found general psychotropic medication to be associated with falling 9,12,15,16,21 with some studies specifically reporting mood stabilizers, 10,16,21,23 lithium, 19,23 and benzodiazepines 16,22,23 as a risk factor. Specific somatic medication was reported as well, like laxatives, 16 antihypertensives, [21][22][23]25 and alpha blockers.…”

Section: Extrinsic Risk Factorsmentioning

confidence: 99%

See 1 more Smart Citation

Falls Among Psychiatric Inpatients: A Systematic Review of Literature

Carpels¹,

Smet²,

Desplenter³

et al. 2022

ALPHA PSYCHIATRY

View full text Add to dashboard Cite

Background: Falls among psychiatric inpatients are common and have significant health consequences. The purpose of this study is to systematically review the published research on risk factors and consequences. Methods: PubMed and Embase were searched for relevant studies. A total of 18 studies were included in this systematic review. The heterogeneity and low quality of the reviewed studies limit the generalizability of the results. Results: Several intrinsic and extrinsic factors are reported. Some of these factors are unique to psychiatric inpatients such as acute mental state, psychotic symptoms, and bipolar disorder leading to cognitive distortions and risk-taking; psychotropic medications inducing side effects like sedation and orthostatic hypotension; while others are similar to those found among general medical inpatients. Conclusion: Given the clinical importance of a fall and its implication on residential treatment, there is a need for targeted fall prevention programs. In order to further identify and quantify these risks and consequences, prospective research and additional study designs, describing and recording risk factors in a systematic and standardized way with the underlying etiological processes in mind, are needed.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Extrinsic Risk Factorsmentioning

confidence: 99%

Falls Among Psychiatric Inpatients: A Systematic Review of Literature

Carpels¹,

Smet²,

Desplenter³

et al. 2022

ALPHA PSYCHIATRY

View full text Add to dashboard Cite

show abstract

“…Our results confirmed it is possible to predict inpatient falls using text analysis of nursing records in a hospital EMR system, with an AUC of 0.834 across an average of five independent experiments. In many previous studies, the prediction of falls was based on specified risk factors, such as the use of psychotropic drugs [28][29][30][31][32], mental state (eg, disorientation, confusion, and delirium) [4,5,30,[33][34][35], impaired motor function (eg, unstable gait and muscle weakness) [4,5,29,32,35], and excretory condition (eg, incontinence and frequent toileting) [5,33,35]. Additionally, the usefulness of nursing records for inpatient fall prediction was discussed recently [36], and it was shown that nursing records contained words known as risk factors for inpatient falls and interventions used in daily practice using NLP analysis.…”

Section: Principal Resultsmentioning

confidence: 99%

Predicting Inpatient Falls Using Natural Language Processing of Nursing Records Obtained From Japanese Electronic Medical Records: Case-Control Study

Nakatani

Nakao

Uchiyama³

et al. 2020

JMIR Med Inform

View full text Add to dashboard Cite

Background Falls in hospitals are the most common risk factor that affects the safety of inpatients and can result in severe harm. Therefore, preventing falls is one of the most important areas of risk management for health care organizations. However, existing methods for predicting falls are laborious and costly. Objective The objective of this study is to verify whether hospital inpatient falls can be predicted through the analysis of a single input—unstructured nursing records obtained from Japanese electronic medical records (EMRs)—using a natural language processing (NLP) algorithm and machine learning. Methods The nursing records of 335 fallers and 408 nonfallers for a 12-month period were extracted from the EMRs of an acute care hospital and randomly divided into a learning data set and test data set. The former data set was subjected to NLP and machine learning to extract morphemes that contributed to separating fallers from nonfallers to construct a model for predicting falls. Then, the latter data set was used to determine the predictive value of the model using receiver operating characteristic (ROC) analysis. Results The prediction of falls using the test data set showed high accuracy, with an area under the ROC curve, sensitivity, specificity, and odds ratio of mean 0.834 (SD 0.005), mean 0.769 (SD 0.013), mean 0.785 (SD 0.020), and mean 12.27 (SD 1.11) for five independent experiments, respectively. The morphemes incorporated into the final model included many words closely related to known risk factors for falls, such as the use of psychotropic drugs, state of consciousness, and mobility, thereby demonstrating that an NLP algorithm combined with machine learning can effectively extract risk factors for falls from nursing records. Conclusions We successfully established that falls among hospital inpatients can be predicted by analyzing nursing records using an NLP algorithm and machine learning. Therefore, it may be possible to develop a fall risk monitoring system that analyzes nursing records daily and alerts health care professionals when the fall risk of an inpatient is increased.

show abstract

“…Other categories showed no difference. It is thought that this finding is of great importance, because although other researchers have indicated a relationship between drugs and nosokomial accidents (Ballinger & Ramsay 1975, McLennan 1976, Ray et al 1989 Creason 1989) they have not identified which drugs contribute to falling.…”

Section: Drugsmentioning

confidence: 89%

Risk Factors Responsible for Patients' Falls

Plati

Lanara

Mantas

1992

Scandinavian Caring Sciences

View full text Add to dashboard Cite

The study determined intrinsic factors which contributed to the falls of adults hospitalized in a general hospital during 1987-88. Two hundred and fourteen patients were studied in two groups. Group A consisted of 108 patients who fell during their hospitalization and control Group B consisted of 106 patients with the same characteristics also hospitalized during the same period who did not fall. Of the 23 variables which have been analyzed by the multivariate logistic regression method, seven present statistically significant incidence and increased risk of patients' falls: (1) gender: the number of accidents occurring among male patients was higher than that among females (p = 0.0022); (2) age: the majority of accidents occurred in the 65 greater than or equal to years old age group (p = 0.00426); (3) general pathological conditions: mostly patients with cardiac problems (p = 0.0062); (4) neoplasms (p = 0.0334); (5) anaemias (p = 0.0128); (6) post-operative conditions (p = 0.0063); and the taking of hypnotic/tranquilizer drugs (p = 0.0486). Other significant findings were: the highest incidence of falls occurred during the first 4 days of the patients' admission to hospital and most during the early morning hours (5-6 am). Injuries incurred were bruises (32.4%), minor injuries (24%), major injuries (16.7%) and fractures (10.2%). The high correlation between patients' falls and (1) specific diseases, namely neoplasms, anaemias, cardiac and post-operative conditions and (2) the taking of hypnotic/tranquilizer drugs are risk factors in relation to patients' falls in general hospitals.

show abstract

Accidents and Drug Treatment in a Psychiatric Hospital

Cited by 18 publications

References 0 publications

Falls Among Psychiatric Inpatients: A Systematic Review of Literature

Falls Among Psychiatric Inpatients: A Systematic Review of Literature

Predicting Inpatient Falls Using Natural Language Processing of Nursing Records Obtained From Japanese Electronic Medical Records: Case-Control Study

Risk Factors Responsible for Patients' Falls

Contact Info

Product

Resources

About