Disinvestment in the presence of uncertainty: Description of a novel, multi-group, disinvestment trial design and protocol for an application to reduce or cease use of mobilisation alarms for preventing falls in hospitals.

Disinvestment is the removal or reduction of previously provided practices or services, and has typically been undertaken where a practice or service has been clearly shown to be ineffective, inefficient and/or harmful. However, practices and services that have uncertain evidence of effectiveness, efficiency and safety can also be considered as candidates for disinvestment. Disinvestment from these practices and services is risky as they may yet prove to be beneficial if further evidence becomes available. A novel research approach has previously been described for this situation, allowing disinvestment to take place while simultaneously generating evidence previously missing from consideration. In this paper, we describe how this approach can be expanded to situations where three or more conditions are of relevance, and describe the protocol for a trial examining the reduction and elimination of use of mobilisation alarms on hospital wards to prevent patient falls. Our approach utilises a 3-group, concurrent, non-inferiority, stepped wedge, randomised design with an embedded parallel, cluster randomised design. Eighteen hospital wards with high rates of alarm use (≥3%) will be paired within their health service and randomly allocated to a calendar month when they will transition to a "Reduced" (<3%) or "Eliminated" (0%) mobilisation alarm condition. Dynamic randomisation will be used to determine which ward in each pair will be allocated to either the reduced or eliminated condition to promote equivalence between wards for the embedded parallel, cluster randomised component of the design. A project governance committee will set non-inferiority margins. The primary outcome will be rates of falls. Secondary clinical, process, safety, and economic outcomes will be collected and a concurrent economic evaluation undertaken.

Mobilisation alarm triggers, response times and utilisation before and after the introduction of policy for alarm reduction or elimination: A descriptive and comparative analysis.

BACKGROUND: Mobilisation alarms are a falls prevention strategy used in hospitals to alert staff when an at risk patient is attempting to mobilise. Mobilisation alarms have an estimated annual cost of $AUD58MIL in Australia. There is growing evidence from randomised controlled trials indicating mobilisation alarms are unlikely to prevent falls. AIM: The primary aim of this study was to describe the rate of mobilisation alarm false triggers and staff response time across different health services. The secondary aim was to compare pre to post mobilisation alarm utilisation following the introduction of policy to reduce or eliminate mobilisation alarms. METHODS: This descriptive and comparative study was conducted through Monash Partners Falls Alliance across six health services in Melbourne, Australia. This study described true and false alarm triggers and trigger response times across three health services and usual care mobilisation alarm utilisation across six health services; and then compared alarm utilisation across two health services following the introduction of policy to reduce (<2.5%) or eliminate (0.0%) mobilisation alarms in the acute and rehabilitation settings. RESULTS: The most frequent observation was a false alarm (n = 74, 52%), followed by a true alarm (n = 67, 47%) and no alarm (n = 3, 2%). Time to respond to the true and false alarms was an average of 37 seconds (SD 92) and this included 61 occasions of 0 seconds as a member of staff was present when the alarm triggered. If the 61 occasions of staff being present when the alarm triggered were removed, the average time to respond was 65 seconds (SD114). Usual care mobilisation alarm utilisation in acute was 7% (n = 171/2,338) and in rehabilitation was 11% (n = 286/2,623). Introducing policy for reduced and eliminated mobilisation alarm conditions was successful with a reduced utilisation rate of 1.8% (n = 11/609) and an eliminated utilisation rate of 0.0% (n = 0/521). CONCLUSION: Half of mobilisation alarm triggers are false and when alarms trigger without staff present, staff take about a minute to respond. While usual care has one in fourteen patients in acute and one in nine patients in rehabilitation using a mobilisation alarm, it is possible to introduce policy which will change practice to reduce or eliminate the use of mobilisation alarms, providing evidence of feasibility for future disinvestment effectiveness studies that it is feasible to disinvest in the alarms.

Where are falls prevention resources allocated by hospitals and what do they cost? A cross sectional survey using semi-structured interviews of key informants at six Australian health services.

BACKGROUND: Falls are a major problem for patients and hospitals, resulting in death, disability and increased costs of healthcare. OBJECTIVES: This study aimed to estimate the resource allocation across a partnership of large health services, in an attempt to understand the amount and variability of resource allocation to various falls prevention activities. DESIGN: A cross sectional survey using semi-structured interviews. SETTING: Six tertiary health services in Australia. PARTICIPANTS: A collaboration of six health services, spanning twenty-eight hospitals, was formed to investigate falls prevention resource allocation. We interviewed 186 health service staff who were involved in falls prevention activities, such as projects, audits and risk management, clinical and operational managers responsible for falls prevention resource allocation and clinical staff on targeted acute, subacute and mental health wards. METHODS: This study used a mixed methods, cross sectional, observational design. To collect data, we used key informant interviews with a purposive and snowball sampled group of people working in the included health services. During interviews, study participants were asked where and how falls prevention resources and equipment were utilised and to estimate the time allocated to performing falls prevention activities. The opportunity cost of each activity was estimated. All costs were reported in Australian dollars. RESULTS: We estimate the annual opportunity cost of health service attempts to prevent in-hospital falls across the six health services to be AU$46,478,014. If we extrapolate this to a national level, health services would be consuming AU$590 million per year in resources trying to prevent falls in hospital. The areas of greatest resource consumption were physiotherapy (18%), continuous patient observers (14%), falls assessments (12%) and screens (8%), and falls prevention alarms (11%). Falls prevention alarms and falls risk assessment screening tools were also used only for falls prevention, and are potentially ineffective falls prevention strategies. CONCLUSIONS: Health services are investing considerable amounts of resource in attempting to prevent falls. However much of this resource is consumed in activities with weak or little evidence of effectiveness. Health services may be better served by considering tighter targeting, reduction or disinvestment in this area. This may release time and resources which could be used to provide interventions with a stronger evidence base, such as patient education using a structured patient education program or in other areas of practice where evidence of benefit exist.