Improved accuracy and efficiency of primary care fall risk screening of older adults using a machine learning approach.

BACKGROUND: While many falls are preventable, they remain a leading cause of injury and death in older adults. Primary care clinics largely rely on screening questionnaires to identify people at risk of falls. Limitations of standard fall risk screening questionnaires include suboptimal accuracy, missing data, and non-standard formats, which hinder early identification of risk and prevention of fall injury. We used machine learning methods to develop and evaluate electronic health record (EHR)-based tools to identify older adults at risk of fall-related injuries in a primary care population and compared this approach to standard fall screening questionnaires. METHODS: Using patient-level clinical data from an integrated healthcare system consisting of 16-member institutions, we conducted a case-control study to develop and evaluate prediction models for fall-related injuries in older adults. Questionnaire-derived prediction with three questions from a commonly used fall risk screening tool was evaluated. We then developed four temporal machine learning models using routinely available longitudinal EHR data to predict the future risk of fall injury. We also developed a fall injury-prevention clinical decision support (CDS) implementation prototype to link preventative interventions to patient-specific fall injury risk factors. RESULTS: Questionnaire-based risk screening achieved area under the receiver operating characteristic curve (AUC) up to 0.59 with 23% to 33% similarity for each pair of three fall injury screening questions. EHR-based machine learning risk screening showed significantly improved performance (best AUROC = 0.76), with similar prediction performance between 6-month and one-year prediction models. CONCLUSIONS: The current method of questionnaire-based fall risk screening of older adults is suboptimal with redundant items, inadequate precision, and no linkage to prevention. A machine learning fall injury prediction method can accurately predict risk with superior sensitivity while freeing up clinical time for initiating personalized fall prevention interventions. The developed algorithm and data science pipeline can impact routine primary care fall prevention practice.

Cost of Inpatient Falls and Cost-Benefit Analysis of Implementation of an Evidence-Based Fall Prevention Program.

Importance: There is insufficient research on the costs of patient falls in health care systems, a leading source of nonreimbursable adverse events. Objective: To report the costs of inpatient falls and the cost savings associated with implementation of an evidence-based fall prevention program. Design, Setting, and Participants: In this economic evaluation, a matched case-control study used the findings from an interrupted time series analysis that assessed changes in fall rates following implementation of an evidence-based fall prevention program to understand the cost of inpatient falls. An economic analysis was then performed to assess the cost benefits associated with program implementation across 2 US health care systems from June 1, 2013, to August 31, 2019, in New York, New York, and Boston, Massachusetts. All adults hospitalized in participating units were included in the analysis. Data analysis was performed from October 2021 to November 2022. Interventions: Evidence-based fall prevention program implemented in 33 medical and surgical units in 8 hospitals. Main Outcomes and Measures: Primary outcome was cost of inpatient falls. Secondary outcome was the costs and cost savings associated with the evidence-based fall prevention program. Results: A total of 10 176 patients who had a fall event (injurious or noninjurious) with 29 161 matched controls (no fall event) were included in the case-control study and the economic analysis (51.9% were 65-74 years of age, 67.1% were White, and 53.6% were male). Before the intervention, there were 2503 falls and 900 injuries; after the intervention, there were 2078 falls and 758 injuries. Based on a 19% reduction in falls and 20% reduction in injurious falls from the beginning to the end of the postintervention period, the economic analysis demonstrated that noninjurious and injurious falls were associated with cost increases of $35 365 and $36 776, respectively. The implementation of the evidence-based fall prevention program was associated with $14 600 in net avoided costs per 1000 patient-days. Conclusions and Relevance: This economic evaluation found that fall-related adverse events represented a clinical and financial burden to health care systems and that the current Medicare policy limits reimbursement. In this study, costs of falls only differed marginally by injury level. Policies that incentivize organizations to implement evidence-based strategies that reduce the incidence of all falls may be effective in reducing both harm and costs.

Development and Validation of a Fall Prevention Efficiency Scale.

OBJECTIVES: Fall TIPS (Tailoring Interventions for Patient Safety) is an evidence-based fall prevention program that led to a 25% reduction in falls in hospitalized adults. Because it would be helpful to assess nurses' perceptions of burdens imposed on them by using Fall TIPS or other fall prevention program, we conducted a study to learn benefits and burdens. METHODS: A 3-phase mixed-method study was conducted at 3 hospitals in Massachusetts and 3 in New York: (1) initial qualitative, elicited and categorized nurses' views of time spent implementing Fall TIPS; (2) second qualitative, used nurses' quotes to develop items, research team inputs for refinement and organization, and clinical nurses' evaluation and suggestions to develop the prototype scale; and (3) quantitative, evaluated psychometric properties. RESULTS: Four "time" themes emerged: (1) efficiency, (2) inefficiency, (3) balances out, and (4) valued. A 20-item prototype Fall Prevention Efficiency Scale was developed, administered to 383 clinical nurses, and reduced to 13 items. Individual items demonstrated robust stability with Pearson correlations of 0.349 to 0.550 and paired t tests of 0.155 to 1.636. Four factors explained 74.3% variance and provided empirical support for the scale's conceptual basis. The scale achieved excellent internal consistency values (0.82-0.92) when examined with the test, validation, and paired (both test and retest) samples. CONCLUSIONS: This new scale assess nurses' perceptions of how a fall prevention program affects their efficiency, which impacts the likelihood of use. Learning nurses' beliefs about time wasted when implementing new programs allows hospitals to correct problems that squander time.

Use of a perceived efficacy tool to evaluate the FallTIPS program.

BACKGROUND/OBJECTIVES: To assess nurses' opinions of the efficacy of using the FallTIPS (Tailoring Interventions for Patient Safety) fall prevention program. DESIGN: Survey research. SETTING: Seven adult acute-care hospitals in 2 hospital centers located in Boston and NYC. PARTICIPANTS: A total of 298 medical-surgical nurses on 14 randomly selected units. INTERVENTION: Three-step FallTIPS fall prevention program that had been in use as a clinical program for a minimum of 2 years in each hospital. MEASUREMENTS: Fall Prevention Efficiency Scale (FPES), range 13-52; four-factorilly derived subscales: valued, efficiency, balances out and inefficiency; and 13 psychometrically validated individual items. RESULTS: Nurses perceived the FallTIPS fall prevention program to be efficacious. The FPES mean score of 38.55 (SD = 5.05) and median of 39 were well above the lowest possible score of 13 and scale midpoint of 32.5. Most nurses (N = 270, 90.6%) scored above 33. There were no differences in FPES scores between nurses who had only used FallTIPS and nurses who had previously used a different fall prevention program. CONCLUSION: The nurses who used FallTIPS perceived that efficiencies in patient care compensated for the time spent on FallTIPS. Nurses valued the program and findings confirmed the importance of patient and family engagement with staff in the fall prevention process. Regardless of the fall prevention program used, organizations should examine staff perceptions of their fall prevention program because programs that are not perceived as being useful, efficient, and valuable will lead to nonadherence over time and then will not reduce falls and injuries. The recently developed FPES used in this study is a brief tool available for organizations to assess nurses' perceptions of the efficacy of their fall prevention program. Additional FPES research is needed with larger and more diverse samples.

Classification of Injurious Fall Severity in Hospitalized Adults.

BACKGROUND: Many hospital systems in the United States report injurious inpatient falls using the National Database of Nursing Quality Indicators categories: None, Minor, Moderate, Major, and Death. The Major category is imprecise, including injuries ranging from a wrist fracture to potentially fatal subdural hematoma. The purpose of this project was to refine the Major injury classification to derive a valid and reliable categorization of the types and severities of Major inpatient fall-related injuries. METHODS: Based on published literature and ranking of injurious fall incident reports (n = 85) from a large Academic Medical Center, we divided the National Database of Nursing Quality Indicators Major category into three subcategories: Major A-injuries that caused temporary functional impairment (eg, wrist fracture), major facial injury without internal injury (eg, nasal bone fracture), or disruption of a surgical wound; Major B-injuries that caused long-term functional impairment or had the potential risk of increased mortality (eg, multiple rib fractures); and Major C-injuries that had a well-established risk of mortality (eg, hip fracture). Based on the literature and expert opinion, our research team reached consensus on an administration manual to promote accurate classification of Major injuries into one of the three subcategories. RESULTS: The team tested and validated each of the categories which resulted in excellent interrater reliability (kappa = .96). Of the Major injuries, the distribution of Major A, B, and C was 40.3%, 16.1%, and 43.6%, respectively. CONCLUSIONS: These subcategories enhance the National Database of Nursing Quality Indicators categorization. Using the administration manual, trained personnel can classify injurious fall severity with excellent reliability.

The role of play themes in non-directive play therapy.

Describing the processes underlying play therapy is important for evidence based practice in child therapy. Employing play themes to describe children's play session contents is in widespread use by practitioners, but an adequate classification of these themes for non-directive play therapy practice has not yet been established. This article sets out to fill this gap by first describing how themes can be distinguished and distilled from the contents of play therapy contents. Second, a classification of main themes and sub-themes with exemplars to illustrate these concepts which is compatible with non-directive play therapy practice is set out. Finally a pilot project with experienced play therapists to test this classification in practice is suggested, along with the research questions that will need to be investigated in the shorter and longer terms.

Therapeutic limits from an attachment perspective.

This article applies attachment theory and relevant research to therapeutic limit setting and focuses particularly on child-centred, non-directive play therapy (NDPT) practice. We review the role of limits in therapeutic change and examine whether therapeutic limit setting exhibits properties similar to those evident in typical adult-child relationships, a topic not previously considered in the literature. The first section identifies properties considered inherent in optimal attachment relationships from a limit setting perspective, drawing particularly on Heard and Lake's (1997) extension of Bowlby's attachment theory. The next section discusses therapists' use of limit setting from an attachment standpoint, distinguishing features of therapeutic limit setting which reflect properties evident in sensitive adult-child attachments. Finally, implications for further research and practice in child therapy are explored.

Evaluating clinical practice: using play-based techniques to elicit children's views of therapy.

Children's services' drive towards accountability, and children's rights advocates' desire to truthfully represent children's views, are leading to more evaluation of child therapy services. The challenge is to find methods that accurately reflect children's views of their therapy. In this article we argue that play therapy skills have an important place in evaluating child therapy practice. We discuss four different directive play therapy techniques three of which have been piloted in the first author's practice to help children express their views of therapy at the end of their interventions. These are: 'The expert show', the miniature playroom technique and puppet and large doll evaluations. Explanations and examples are given from pilot research with 12 children. The issues and challenges inherent in play-based evaluations also are explored. We argue that expressive therapists are in a prime position to evaluate children's services and that children appear well able to express their views of therapy with these child-centred techniques.