Comparison of the predictive validity of three fall risk assessment tools and analysis of fall‐risk factors at a tertiary teaching hospital

2020 ◽  
Vol 29 (17-18) ◽  
pp. 3482-3493
Author(s):  
Eun Hee Cho ◽  
Yun Jung Woo ◽  
Arum Han ◽  
Yoon Chung Chung ◽  
Yeon Hee Kim ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Predictive Validity ◽  
Teaching Hospital ◽  
Fall Risk ◽  
Assessment Tools ◽  
Fall Risk Factors ◽  
Tertiary Teaching ◽  
Risk Assessment Tools ◽  
Tertiary Teaching Hospital

scholarly journals POPULATION- SPECIFIC FALL RISK ASSESSMENT TOOLS FOR ADULT INPATIENTS: A SYSTEMISED LITERATURE REVIEW

2020 ◽  
pp. 62-63
Author(s):  
Priya Padmanabhan ◽  
Salumon Chandrasekaran
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Literature Review ◽  
Fall Risk ◽  
Assessment Tool ◽  
Cleveland Clinic ◽  
Assessment Tools ◽  
Fall Risk Assessment ◽  
Specific Risk ◽  
Risk Assessment Tools

Fall is one of the most commonly reported adverse events from the hospitals and around one-third of them result in injury. A carefully tailored fall reduction program begins with the identification of the “at-risk” population. Commonly used adult fall risk assessment tools do not take into consideration the risk factors of some of the vulnerable patient populations. This paper provides a systemised literature review of the need and availability of population-specific risk assessment tools. One of the most commonly used tools - Morse Fall Scale- does not assess the effect of certain medications and population-specific risk factors. The Cleveland Clinic – Capone- Albert (CC-CA) Fall Risk Score is a tool that is specifically developed for cancer patients. Similarly, Obstetric Fall Risk Assessment Tool (OFRAS) helps in identifying the fall risk factors in perinatal women. Usage of such population-specific tools help in focused identification of risks, distinct implementation of interventions and thus, results in reducing the incidents of falls and injuries thereof.

Suicide risk assessment in a large public mental health service: do suicide risk classifications identify those at risk?

2021 ◽  
pp. 103985622098403
Author(s):  
Marianne Wyder ◽  
Manaan Kar Ray ◽  
Samara Russell ◽  
Kieran Kinsella ◽  
David Crompton ◽  
...  
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Risk Assessment ◽  
High Risk ◽  
Suicide Risk ◽  
Public Mental Health ◽  
Assessment Tools ◽  
Suicide Risk Assessment ◽  
Public Mental Health Service ◽  
Risk Assessment Tools

Introduction: Risk assessment tools are routinely used to identify patients at high risk. There is increasing evidence that these tools may not be sufficiently accurate to determine the risk of suicide of people, particularly those being treated in community mental health settings. Methods: An outcome analysis for case serials of people who died by suicide between January 2014 and December 2016 and had contact with a public mental health service within 31 days prior to their death. Results: Of the 68 people who had contact, 70.5% had a formal risk assessment. Seventy-five per cent were classified as low risk of suicide. None were identified as being at high risk. While individual risk factors were identified, these did not allow to differentiate between patients classified as low or medium. Discussion: Risk categorisation contributes little to patient safety. Given the dynamic nature of suicide risk, a risk assessment should focus on modifiable risk factors and safety planning rather than risk prediction. Conclusion: The prediction value of suicide risk assessment tools is limited. The risk classifications of high, medium or low could become the basis of denying necessary treatment to many and delivering unnecessary treatment to some and should not be used for care allocation.

Analysis of Cerebral Vascular Lesion Pools in Ischemic Stroke Based on the Analysis and the Prognostic Assessment of Risk Factors in Patients with Primary and Recurrent Ischemic Stroke

2016 ◽  
pp. 65-68
Author(s):  
Oksana Mikitey
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Ischemic Stroke ◽  
Recurrent Stroke ◽  
Significant Risk ◽  
Vascular Lesion ◽  
Assessment Tools ◽  
Vascular Lesions ◽  
Global Risk ◽  
Risk Assessment Tools

Stroke is an important medical and social problem, and stroke risk assessment tools have difficulty on the interaction of risk factors and the effects of certain risk factors with analysis by age, gender, race, because this information fully available to global risk assessment tools. In addition, these tools tend to be focused and usually do not include the entire range of possible factors contributing. The aim of the study was to conduct a comparison of brain vascular lesions pool with ischemic stroke (II) based predictive analysis and assessment of the main risk factors in patients with primary and recurrent ischemic stroke. Prognostically significant risk factors for recurrent ischemic stroke is not effective antihypertensive therapy, multiple stenoses any one pool vascular brain, duration of hypertension (AH) over 5 years and regular smoking patients (p<0.001). In the initial localization in the second vertebrobasilar recurrent stroke was significantly (p<0.05) more developed in the same pool in women than in men; and the localization of the primary carotid AI in the pool, re-developed stroke often unreliable in the same pool in women than in men.

scholarly journals Novel Approach to Inpatient Fall Risk Prediction and Its Cross-Site Validation Using Time-Variant Data (Preprint)

2018 ◽  
Author(s):  
Insook Cho ◽  
Eun-Hee Boo ◽  
Eunja Chung ◽  
David W. Bates ◽  
Patricia Dykes
Keyword(s):  
Risk Assessment ◽  
Error Rate ◽  
Fall Risk ◽  
Assessment Tool ◽  
Assessment Tools ◽  
Fall Risk Assessment ◽  
C Statistic ◽  
Risk Assessment Tools ◽  
Hospital Days ◽  
Cross Site

BACKGROUND Electronic medical records (EMRs) contain a considerable amount of information about patients. The rapid adoption of EMRs and the integration of nursing data into clinical repositories have made large quantities of clinical data available for both clinical practice and research. OBJECTIVE In this study, we aimed to investigate whether readily available longitudinal EMR data including nursing records could be utilized to compute the risk of inpatient falls and to assess their accuracy compared with existing fall risk assessment tools. METHODS We used 2 study cohorts from 2 tertiary hospitals, located near Seoul, South Korea, with different EMR systems. The modeling cohort included 14,307 admissions (122,179 hospital days), and the validation cohort comprised 21,172 admissions (175,592 hospital days) from each of 6 nursing units. A probabilistic Bayesian network model was used, and patient data were divided into windows with a length of 24 hours. In addition, data on existing fall risk assessment tools, nursing processes, Korean Patient Classification System groups, and medications and administration data were used as model parameters. Model evaluation metrics were averaged using 10-fold cross-validation. RESULTS The initial model showed an error rate of 11.7% and a spherical payoff of 0.91 with a c-statistic of 0.96, which represent far superior performance compared with that for the existing fall risk assessment tool (c-statistic=0.69). The cross-site validation revealed an error rate of 4.87% and a spherical payoff of 0.96 with a c-statistic of 0.99 compared with a c-statistic of 0.65 for the existing fall risk assessment tool. The calibration curves for the model displayed more reliable results than those for the fall risk assessment tools alone. In addition, nursing intervention data showed potential contributions to reducing the variance in the fall rate as did the risk factors of individual patients. CONCLUSIONS A risk prediction model that considers longitudinal EMR data including nursing interventions can improve the ability to identify individual patients likely to fall.

scholarly journals Classification of stillbirth by relative condition at death (Re Co De) at various trimesters of pregnancy: a rural tertiary teaching hospital based study

2017 ◽  
Vol 6 (8) ◽  
pp. 3550 ◽  
Author(s):  
V. Meera Rajagopal ◽  
Kalpana Betha ◽  
Satya Priya G.
Keyword(s):  
Risk Factors ◽  
Teaching Hospital ◽  
Rural Areas ◽  
Gestational Hypertension ◽  
Economic Status ◽  
Mode Of Delivery ◽  
Middle Income ◽  
Low Middle Income Countries ◽  
Tertiary Teaching ◽  
Tertiary Teaching Hospital

Background: New global health figures show India to have the highest rates of stillbirth in the world. While maternal and under 5 child mortality rates have halved, stillbirth remains a neglected global endemic. To reduce stillbirths, the prevalence, risk factors and causes must be known. The aim of the present study is to know the prevalence and classify stillbirths by ReCoDe classification system at different trimesters of pregnancy.Methods: This was a retrospective study done between January 2013 to March 2017 at MediCiti Institute of Medical Sciences, a rural tertiary teaching hospital, Telangana, India. A total of 112 cases of stillbirths were included. Data was obtained on demographic variables, risk factors such as preeclampsia, etc. Data regarding mode of delivery, fetal asphyxia, were recorded.Results: Stillbirth rate was 12.1/1000 births. Fifty four percent of the women were unbooked. Preterm stillbirths were a majority (67%). The intra-partum still birth rate was low (15.1%) contrary to what is seen in low middle-income countries. Gestational hypertension/Pre-eclampsia, abruptio placenta, fetal growth restriction and oligohydramnios were the leading causes of stillbirths.Conclusions: Pregnant women from rural background with low socio-economic status are prone for stillbirths. As stillbirths were more among unbooked cases, the study highlights the importance of counselling, creating awareness in the rural areas regarding the importance of regular antenatal checkups. Identifying risk factors like pre-eclampsia, anemia etc., at early weeks will enable us to initiate appropriate strategies to improve pregnancy outcome.

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