A tool to measure the success of patient handling interventions across the European Union

Patient handling intervention strategies are many and varied. The focus of interventions has primarily been on the health, safety and welfare of care givers. Data from 4 EU focus groups and 2 world-wide expert panels were used to evaluate whether other types of outcomes were perceived as having relative importance. Qualitative and quantitative analysis showed that organisational and patient outcomes were also highly rated by the participants. The data had good agreement between the 4 different EU sources (Kendall’s Concordance significant at 0.005) and the 12 highest rated measures were considered eligible for inclusion in further study. In parallel, a wide ranging analysis of patient handling intervention literature was considered to evaluate the qualities of each individual study. Using the 12 most important outcomes from the initial study and the most appropriate and accessible measurement tools from the literature analysis, the Intervention Evaluation Tool (IET) is proposed. The IET is a single set of measurements that can be used for evaluating all organisational and individual patient handling interventions in healthcare

A tool to compare all patient handling interventions

Patient handling intervention strategies are many and varied. The focus of interventions has primarily been on the health, safety and welfare of care givers. Data from 4 EU focus groups and 2 world-wide expert panels were used to evaluate whether other types of outcomes were perceived as having relative importance. Qualitative and quantitative analysis showed that organisational and patient outcomes were also highly rated by the participants. The data showed 12 outcomes as being of the highest priority with good agreement between the 4 EU sources (Kendall’s Concordance significant at 0.005). In parallel, a systematic analysis of patient handling intervention literature was considered to evaluate the qualities of each study. Using the 12 most important outcomes from the initial study and the most appropriate and accessible measurement tools from the literature analysis, the Intervention Evaluation Tool (IET) is proposed. The IET is a single set of measurements that can be used for evaluating all organisational and individual patient handling interventions. The IET has been trialled at 2 sites in 4 EU countries

Manual handling in healthcare

Patient handling is a known cause of musculoskeletal risk for healthcare staff. A range of ergonomic and other approaches have been used to try to reduce the effects of these tasks, e.g. risk assessment and management, training, equipment provision, culture change. A European collaboration (European Panel on Patient Handling Ergonomics) was formed in 2004 to share information about research on patient handling and develop research ideas for European collaborations. Three collaborations will be described. The first reviewed the implementation of the European Union Directive on Manual handling for patient handling; the second reports the development of a Technical Report (TR ISO/CD 12296) for the manual handling of people in the healthcare sector; and the third describes an Intervention Evaluation Tool that has been produced to allow the evaluation of both single factor and multi-faceted interventions for patient handling

The evaluation of patient handling interventions in healthcare

Patient handling intervention strategies are many and varied. The focus of interventions has primarily been on the health, safety and welfare of care givers. Since 2005 the European Panel of Patient Handling Ergonomics (EPPHE) has been supporting an international research project to develop a tool for the evaluation of patient handling interventions across the EU. 4 European countries were involved in its development. This tool has been used in a number of countries in different healthcare environments. The tool calculates management performance in 12 different outcome areas to evaluate the changes made following a patient handling intervention. It evaluates all types of interventions from management style to equipment supply or training and education interventions. This paper presents a review of the development and evaluation of this tool and suggestions for future validation

An evaluation of the biomechanical risks for a range of methods to raise a patient from supine lying to sitting in a hospital bed

Transferring patients has long been identified as a contributory cause of MSD in healthcare processes. One common action that is known to increase the musculoskeletal risk to healthcare workers is raising a person from supine lying to sitting on the side of the bed (Jordan et al., 2011). Best practice guidelines suggest that this activity should be replaced with mechanical devices e.g. profiling bed or hoist/lifter technology (e.g. Smith ed 2011). Practitioner evidence from many locations indicate that many people are being assisted from supine lying to sitting using manual techniques and healthcare workers are being placed at risk. This study reviewed several different methods using single and paired carers and different assistive devices to complete this transfer. A simulation task was designed as part of a user trial. Patient actors (n=4) were trained to respond as specific client groups who represented 2.5th, to 97.5th %-ile patients. Healthcare workers (n=9) completed 5 methods for raising a person from supine lying to sitting and 3 methods for lowering a person from sitting to lying with (1 and 2 carers). All conditions (n=11) were repeated to ensure a standard method and movements were recorded (n=5 minimum per participant). Data were collected for the biomechanical evaluation by motion capture (CODAmotion) technology, anthropometer data for body size and a Kistler force plate. Additional force measures for analysis of the loading calculations were recorded using a Mecmesin AFG2500N force gauge using staged re-enactments using repeated measures. All participants and patients completed subjective reviews of the transfers reporting effort, security and safety. The results were combined to calculate the musculoskeletal risks during the various transfers. Differences were identified between the movement, positions and the biomechanical loading characteristics of the fully manual methods, the profiling bed assisted methods and a novel assistive device. Practitioner Summary: The biomechanical risks of patient handling activities are well known. Many studies have quantified the risks for full weight lifting activities, which is widely accepted as hazardous and should be replaced by mechanical methods e.g. hoisting. The detailed biomechanical analysis of other patient handling tasks is not so well reported. This study explores the forces required to assist a range of patients from lying to sitting on the side of a bed and vice versa using a series of handling techniques. The results show that simple assistive devices that utilise the body weight of the patient can make a clear difference to the risks of these activities

Using patient handling equipment to manage mobility in and around a bed.

Using patient handling equipment to manage mobility in and around a bed

Development of a framework for the analysis of weak signals within a healthcare environment

Weak signals provide an opportunity for pro-activeness that can assist in improving safety. Through a review of literature and evaluated with three different case studies, this study proposed a framework for the analysis of weak signals in the healthcare environment

Stopping incidents in their tracks: identifying weak signals for error prevention in healthcare

In order to adjust performance to ensure the success of a task and prevent error, it is necessary to anticipate, identify and respond to signals indicating changes in the system. The objectives of this study were to investigate weak signals within two different healthcare case studies by identifying key elements and behaviours of these tasks. This study investigated both Safety-I and Safety-II elements with four expert groups, two from the field of patient handling and two from the field of patient discharge. The Safety-I and Safety-II elements explored included potential errors, influencing factors, weak signals and learning opportunities arising from the investigated situations. The errors identified by the focus groups were related to skill, knowledge, inappropriate equipment, equipment misuse, lack of communication, missing or incomplete information, incorrect technique, and preconditions not being fulfilled. The influencing factors identified by the two case studies included patient-related factors, time and space-related factors as well as organizational and managerial factors such as available resources and safety culture. The weak signals identified in both case studies were analysed using the SEIPS 2.0 model. The sources of the signals were identified as originating from the work system elements “person”, “tasks”, “organization” and “internal environment”. The manifestation forms of the weak signals included the different sensory signals as well as the experience of intuition or “hunches”. Potential learning opportunities to improve signal recognition were identified and included the need for reflection and empowerment, continuous assessment and the sharing of information between the involved systems. The proposed framework and method provide a preliminary basis for the investigation of weak signals and assists in highlighting the role that the weak signals can play in safety behaviour

The evaluation of medical devices with healthy people?

Much of the research of thermal and physical comfort is completed with healthy participants in regular life scenarios. The translation of these findings into clinical settings for people with disease, deficiency or restrictions adds a level of complexity. As an example this study evaluated the effectiveness of a patient warming mattress device on body temperature and ratings of thermal comfort/sensation. Hypothermia has been linked to higher mortality rates in trauma patients admitted to hospital. Patient warming devices have been developed to assist the temperature of the patient and studies on these report varied effects. Laboratory trials with shivering inhibition (Goheen et al, 1997, Greif et al, 2000) found improvements from forced air and resistive blankets but without shivering inhibition (Williams et al, 2005) showed no benefit in warming from 35°C. A physical evaluation of the warming mattress device with a thermal manikin reported an energy contribution to the user (~70W). To support the physical evaluation a user trial was conducted. Nine healthy volunteer participants (27.78+4.99 Years) were exposed to three conditions using a repeated measures counterbalanced design. The participants were cooled in an environment with an air temperature of 0°C (60 minutes) then exposed to 30 minutes of a warming intervention. 1.Hot mattress HM. Mattress preheated to 18°C, under standard blankets 2.Warmed mattress WM. Mattress turned on at start of warming period, under standard blankets 3.Cold mattress CM. Control condition, no power to mattress, under standard blankets. During the cooling phase, aural and mean skin temperature (Tsk) significantly decreased for all conditions (p<0.01). Tsk increased following each warming intervention but aural temperature continued to decline. Significant increase in overall mean thermal comfort was seen during the first ten minutes of the warming phase for HM in comparison to CM and WM (p<0.05) but not at 20 and 30 minutes. This was mirrored by the overall mean thermal sensation rating across the same timeframe. HM increased thermal sensation from very cold to cool with CM and WM showing and increase from very cold to cold. This study revealed the effect of the device (HM) gave short term comfort and sensation gains at the start of the warming phase but the passive insulation provided (CM) also allowed re-warming to occur. This was the expected thermoregulatory response for a group of healthy participants. This group does not necessarily represent the hospital population with pathology that inhibits their normal responses to cold, e.g. circulatory shut-down, shock or trauma. For accurate application, the trial data needs to be closely matched with the limitations of the health condition in the target population. The challenge is now to explore the relationship between data from healthy cohorts and how that can be used for groups of patients with known physical and physiological conditions and limitations. The validity of a patient’s subjective assessment of their condition lying in a hospital bed is currently unclear. Evidence needs to show whether a patient in a hospital bed can accurately report joint position, thermal comfort, skin wettedness, pressure points etc to assist in the management of their condition

Macro and micro ergonomic outcomes in healthcare: unravelling the relationship between patient handling performance and safety climate

The management of risks surrounding patient handling activities continues to be an important factor in healthcare organizations. A great deal of research has been undertaken to investigate the best practices for physical transfers and equipment provision, yet there is less research adopting an organizational systems approach to this problem. In this article we compare two methods for assessing safety climate and patient handling safety performance and argue that a multi-level (mesoergonomic) interpretation of the relationship between the two affords insights into the safety of the system as a whole