Dataset Information

Lessons Learned From Implementing CDC's STEADI Falls Prevention Algorithm in Primary Care.

ABSTRACT: BACKGROUND:Falls lead to a disproportionate burden of death and disability among older adults despite evidence-based recommendations to screen regularly for fall risk and clinical trials demonstrating the effectiveness of multifactorial interventions to reduce falls. The Centers for Disease Control and Prevention developed STEADI (Stopping Elderly Accidents, Deaths, and Injuries) to assist primary care teams to screen for fall risk and reduce risk of falling in older adults. PURPOSE OF THE STUDY:This paper describes a practical application of STEADI in a large academic internal medicine clinic utilizing the Kotter framework, a tool used to guide clinical practice change. DESIGN AND METHODS:We describe key steps and decision points in the implementation of STEADI as they relate to the recommended strategies of the Kotter framework. Strategies include: creating a sense of urgency, building a guiding coalition, forming a strategic vision and initiative, enlisting volunteers, enabling success by removing barriers, generating short-term wins, sustaining change, and instituting change. RESULTS:Fifty-six patients were screened during pilot testing; 360 patients were screened during the first 3 months of implementation. Key to successful implementation was (a) the development of electronic health record (EHR) tools and workflow to guide clinical practice and (b) the proactive leadership of clinical champions within the practice to identify and respond to barriers. IMPLICATIONS:Implementing falls prevention in a clinical setting required support and effort across multiple stakeholders. We highlight challenges, successes, and lessons learned that offer guidance for other clinical practices in their falls prevention efforts.

SUBMITTER: Casey CM

PROVIDER: S-EPMC5940581 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Lessons Learned From Implementing CDC's STEADI Falls Prevention Algorithm in Primary Care.

Casey Colleen M CM Parker Erin M EM Winkler Gray G Liu Xi X Lambert Gwendolyn H GH Eckstrom Elizabeth E

The Gerontologist 20160429 4

<h4>Background</h4>Falls lead to a disproportionate burden of death and disability among older adults despite evidence-based recommendations to screen regularly for fall risk and clinical trials demonstrating the effectiveness of multifactorial interventions to reduce falls. The Centers for Disease Control and Prevention developed STEADI (Stopping Elderly Accidents, Deaths, and Injuries) to assist primary care teams to screen for fall risk and reduce risk of falling in older adults.<h4>Purpose o ...[more]

PMID: 27130270

Similar Datasets

Project description:BackgroundType 2 diabetes mellitus is preventable through lifestyle intervention. Diabetes prevention programmes (DPPs) aim to deliver prevention-based behaviour change interventions to reduce incidence. Such programmes vary from usual primary care in terms of where, how, and by whom they are delivered. Implementation is therefore likely to face new commissioning, incentive and delivery challenges. We report on the implementation of a national DPP in NHS England, and identify lessons learned in addressing the implementation challenges.MethodsIn 2017/18, we conducted 20 semi-structured telephone interviews covering 16 sampled case sites with the designated lead(s) responsible for local implementation of the programme. Interviews explored the process of implementation, including organisation of the programme, expectations and attitudes to the programme, funding, target populations and referral and clinical pathways. We drew on constant comparative methods to analyse the data and generate over-arching themes. We complemented our qualitative data with a survey focused on variation in the financial incentives used across sites to ensure usual primary care services recruited patients to new providers.ResultsWe identified five over-arching areas of learning for implementing this large-scale programme: 1) managing new providers; 2) promoting awareness of services; 3) recruiting patients; 4) incentive payments; and 5) mechanisms for sharing learning. In general, tensions appeared to be caused by a lack of clear roles/responsibilities between hierarchical actors, and lack of communication. Both local sites and the national NHS coordination team gained experience through learning by doing. Initial tensions with roles and expectations have been worked out during implementation.ConclusionsImplementing a national disease prevention programme is a major task, and one that will be increasingly faced by health systems globally as they aim to adjust to demand pressures. We provide practical learning opportunities for the wider uptake and sustainability of prevention programmes. Future implementers might wish to define clear responsibilities for each actor prior to implementation, ensure early engagement with new providers, offer mechanisms/forums for sharing learning, generate evidence and provide advice on incentive payments, and prioritise public and professional awareness of the programme.

Project description:Background:Screening, Brief Intervention and Referral to Treatment (SBIRT) is a public health framework approach used to identify and deliver services to those at risk for substance-use disorders, depression, and other mental health conditions. Primary care is the first entry to the healthcare system for many patients, and SBIRT offers potential to identify these patients early and assist in their treatment. There is a need for pragmatic "best practices" for implementing SBIRT in primary care offices geared toward frontline providers and office staff. Methods:Ten primary care practices were awarded small community grants to implement an SBIRT program in their location. Each practice chose the conditions for which they would screen, the screening tools, and how they would provide brief intervention and referral to treatment within their setting. An evaluation team communicated with each practice throughout the process, collecting quantitative and qualitative data regarding facilitators and barriers to SBIRT success. Using the editing method, the qualitative data were analyzed and key strategies for success are detailed for implementing SBIRT in primary care. Results:The SBIRT program practices included primary care offices, federally qualified health centers, school-based health centers, and a safety-net emergency department. Conditions screened for included alcohol abuse, drug abuse, depression, anxiety, child safety, and tobacco use. Across practices, 49,964 patients were eligible for screening and 36,394 pre-screens and 21,635 full screens were completed. From the qualitative data, eight best practices for primary care SBIRT are described: Have a practice champion; Utilize an interprofessional team; Define and communicate the details of each SBIRT step; Develop relationships with referral partners; Institute ongoing SBIRT training; Align SBIRT with the primary care office flow; Consider using a pre-screening instrument, when available; and Integrate SBIRT into the electronic health record. Conclusions and implications:SBIRT is an effective tool that can empower primary care providers to identify and treat patients with substance use and mental health problems before costly symptoms emerge. Using the pragmatic best practices we describe, primary care providers may improve their ability to successfully create, implement, and sustain SBIRT in their practices.

Project description:BackgroundPhysical activity (PA) preserves mobility, but few practices screen older adults for mobility impairment or counsel on PA.Design"Promoting Active Aging" (PAA) was a mixed-methods randomized-controlled pilot, to test the feasibility and acceptability of a video-based PA counseling tool and implementation into practice of two mobility assessment tools.SettingThree primary care practices affiliated with Wake Forest Baptist Health.ParticipantsAdults aged 65 years and older who presented for primary care follow-up and were willing and able to answer self-report questions and walk 4 meters (n = 59).InterventionVideo-based PA counseling intervention versus control video, "Healthy Eating."MeasurementsPotential participants completed mobility assessments: self-report (Mobility Assessment Tool-short form (MAT-sf)) and performance based (4-meter walk test). We assessed PAA's implementation-feasibility, acceptability, and value-via interviews and surveys. Effectiveness was measured via participant attendance at a PA information session.ResultsOf 92 patients approached, 89 (96.7%) agreed to mobility assessment. Eighty-nine completed MAT-sf, and 97.8% (87/89) completed 4-meter walk test. Sixty-seven (75%) met eligibility criteria, and 59 (88%) consented to be randomized either to the PA counseling intervention (Video-PA) or to active control (Video-C). Most participants viewed the walk test positively (51/59; 86.4%). Staff reported that completion of patient surveys, MAT-sf, and videos required significant staff time and support (median = 26 minutes for all), resulting in low acceptability of MAT-sf and the videos. Attendance at a PA information session did not differ by randomization group (Video-PA = 11/29 (37.9%); Video-C = 12/30 (40%); 95% confidence interval for difference in proportion = -0.29 to 0.25).ConclusionsMobility assessment, particularly a 4-meter walk test, was feasible in primary care. Tablet-based assessment (MAT-sf) and video counseling tools, selected to reduce staff effort, instead required significant time to implement. Future work to promote PA should identify effective ways to facilitate adoption of PA in sedentary older adults that do not burden staff.

Dataset Information

Lessons Learned From Implementing CDC's STEADI Falls Prevention Algorithm in Primary Care.

Publications

Lessons Learned From Implementing CDC's STEADI Falls Prevention Algorithm in Primary Care.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets