Acute Medical Ward (acute + medical_ward)

Distribution by Scientific Domains


Selected Abstracts


A Comparative Study of the Use of Four Fall Risk Assessment Tools on Acute Medical Wards

JOURNAL OF AMERICAN GERIATRICS SOCIETY, Issue 6 2005
Michael Vassallo FRCP
Objectives: To compare the effectiveness of four falls risk assessment tools (STRATIFY, Downton, Tullamore, and Tinetti) by using them simultaneously in the same environment. Design: Prospective, open, observational study. Setting: Two acute medical wards admitting predominantly older patients. Participants: One hundred thirty-five patients, 86 female, mean ageħstandard deviation 83.8ħ8.01 (range 56,100). Measurements: A single clinician prospectively completed the four falls risk assessment tools. The extent of completion and time to complete each tool was recorded. Patients were followed until discharge, noting the occurrence of falls. The sensitivity, specificity, negative predictive accuracy, positive predictive accuracy, and total predictive accuracy were calculated. Results: The number of patients that the STRATIFY correctly identified (n=90) was significantly higher than the Downton (n=46; P<.001), Tullamore (n=66; P=.005), or Tinetti (n=52; P<.001) tools, but the STRATIFY had the poorest sensitivity (68.2%). The STRATIFY was also the only tool that could be fully completed in all patients (n=135), compared with the Downton (n=130; P=.06), Tullamore (n=130; P=.06), and Tinetti (n=17; P<.001). The time required to complete the STRATIFY tool (average 3.85 minutes) was significantly less than for the Downton (6.34 minutes; P<.001), Tinetti (7.4 minutes; P<.001), and Tullamore (6.25 minutes; P<.001). The Kaplan-Meier test showed that the STRATIFY (log rank P=.001) and Tullamore tools (log rank P<.001) were effective at predicting falls over the first week of admission. The Downton (log rank P=.46) and Tinetti tools (log rank P=.41) did not demonstrate this characteristic. Conclusion: Significant differences were identified in the performance and complexity between the four risk assessment tools studied. The STRATIFY tool was the shortest and easiest to complete and had the highest predictive value but the lowest sensitivity. [source]


Heights of occupied patient beds: a possible risk factor for inpatient falls

JOURNAL OF CLINICAL NURSING, Issue 11 2008
Huey-Ming Tzeng PhD
Aims., The aim of this study was to ascertain the average height of occupied patient beds in a general medical ward and to investigate the relationship between staff working-height for patient beds, time and whether the patient was on fall precaution. Background., The height of occupied patient beds can be an overlooked contributor to inpatient falls. Better physical design of hospital equipment such as patient beds may reduce patient falls and injuries. Methods., This study took place in an acute medical ward of a Michigan medical center. One researcher collected all the data and used the same metric for all the measurements. Univariate analyses were performed. Results., The average staff working-height measurement taken at the weekend was significantly higher than that taken on weekdays. The average height of patient beds on fall precaution was significantly higher than of those not on fall precaution. Conclusions., A higher patient/nurse ratio at weekends than on weekdays may result in fewer bedside nursing hours and nurses being less conscientious about keeping beds in the low position after treatments. In an effort to prevent high-fall-risk patients from falling, nurses may have consciously or unconsciously kept their beds in higher positions. Relevance to clinical practice., If the patient bed can be manually or automatically adjusted, nurses must lower the height of the bed to the lowest position after completing treatments or tasks. This after-procedure activity should be enforced and monitored regularly as part of a hospital's patient fall prevention programme. Low beds should be used for patients at high risk of falling. Future research should investigate patients' and staff's views on hospital equipment to provide evidence-based information for policy-makers determining the design-regulation standard for hospital bedframes. [source]


A study of the criteria used by healthcare professionals, managers and patients to represent and evaluate quality care

JOURNAL OF NURSING MANAGEMENT, Issue 2 2001
M. Attree msc, bnurs
Aim,To explore the perceptions of and criteria used by healthcare professionals, managers, patients and relatives to represent and evaluate their concept of quality care. Methods A qualitative approach using grounded theory was adopted in thisexploratory descriptive study. Data collected by semi-structured interviews from a purposive sample of nurses, doctors, managers (n = 36), patients (n = 34) and relatives (n = 7) from one acute medical ward, were subjected to content, question and thematic analysis, using an inductive categorizing scheme. Findings Three categories of criteria relating to Care Resources, Processes and Outcomes were identified by healthcare professionals, managers, patients and relatives. Resource criteria included Human Resources: staff numbers, ratio to patients, skill mix; as well as Environmental/Physical and Financial Resources. Process criteria included Care Functions, Practices and Standards as well as Interpersonal Processes. Outcome criteria were either patient-focused: feeling comfort, happy, informed and satisfied; or health-related: maintenance or progress with health problems and goals. Conclusions The criteria used by healthcare stakeholders in this study were notunusual; virtually all were supported by the literature, a proportion of which was evidence-based. The criteria identified in this study are however consensual, agreed upon by healthcare professionals, managers, patients and relatives as representing their view of quality care. These consensual criteria could be used as unifying constructs for the development and testing of more comprehensive, reliable and valid methods of evaluating quality care which represent its multiple dimensions and perspectives. [source]


A Comparative Study of the Use of Four Fall Risk Assessment Tools on Acute Medical Wards

JOURNAL OF AMERICAN GERIATRICS SOCIETY, Issue 6 2005
Michael Vassallo FRCP
Objectives: To compare the effectiveness of four falls risk assessment tools (STRATIFY, Downton, Tullamore, and Tinetti) by using them simultaneously in the same environment. Design: Prospective, open, observational study. Setting: Two acute medical wards admitting predominantly older patients. Participants: One hundred thirty-five patients, 86 female, mean ageħstandard deviation 83.8ħ8.01 (range 56,100). Measurements: A single clinician prospectively completed the four falls risk assessment tools. The extent of completion and time to complete each tool was recorded. Patients were followed until discharge, noting the occurrence of falls. The sensitivity, specificity, negative predictive accuracy, positive predictive accuracy, and total predictive accuracy were calculated. Results: The number of patients that the STRATIFY correctly identified (n=90) was significantly higher than the Downton (n=46; P<.001), Tullamore (n=66; P=.005), or Tinetti (n=52; P<.001) tools, but the STRATIFY had the poorest sensitivity (68.2%). The STRATIFY was also the only tool that could be fully completed in all patients (n=135), compared with the Downton (n=130; P=.06), Tullamore (n=130; P=.06), and Tinetti (n=17; P<.001). The time required to complete the STRATIFY tool (average 3.85 minutes) was significantly less than for the Downton (6.34 minutes; P<.001), Tinetti (7.4 minutes; P<.001), and Tullamore (6.25 minutes; P<.001). The Kaplan-Meier test showed that the STRATIFY (log rank P=.001) and Tullamore tools (log rank P<.001) were effective at predicting falls over the first week of admission. The Downton (log rank P=.46) and Tinetti tools (log rank P=.41) did not demonstrate this characteristic. Conclusion: Significant differences were identified in the performance and complexity between the four risk assessment tools studied. The STRATIFY tool was the shortest and easiest to complete and had the highest predictive value but the lowest sensitivity. [source]