Browsing by Author "Carver, M. Colette"

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  • Improving Care Transitions Through Risk Reduction with Machine Learning Support
    Carver, M. Colette; Jones, Nate; Djuric, Dan; Butt, Caroline; Markham, Carla; Brookman, Jeremy; Reece, Chanda; Smith, Jamie (2020-04-15)
    Problem: The ambulatory care management team at Carilion Clinic lacked the necessary tools to demonstrate readmission risk reduction for patients undergoing care transitions. Purpose: This quality improvement project aimed to determine if implementing a real-time workflow management system which supported the prioritization, intervention tracking, and coordination of transitions of care, would result in readmission avoidance through risk reduction. Background: The Accountable Care Strategies team implemented an electronic Transition Tracking Tool (T3), as one aspect of Carilion’s readmission reduction program. Evidence from the literature: Approximately 20% of Medicare beneficiaries are readmitted within 30 days following hospital or facility-based care (Fischer et al., 2014). Many health systems across the country have developed strategies to reduce hospital readmissions after the passage of the Patient Protection and Affordable Care Act and its requirement for the implementation of a Hospital Readmissions Reduction Program (ACA, 2010). While there are a variety of readmission risk stratification tools used to identify patients, the predictive performance of these tools, according to Kansagara et al., (2011), has been marginal due in part to the complex factors contributing to a readmission. These researchers recommend incorporating a larger data set to include social determinants of health (Kansagara et al., 2011). Patient’s social determinants have a significant impact on their readmission risk, thus ambulatory programs which address these factors are essential (Calvillo-King et al., 2013). EBP Question: (1) Is there an impact on readmission for a patient who undergoes risk reduction strategies by a nurse using an automated patient prioritization tool with predictive interventions? Methods: The ambulatory care management team uses a relationship-based model, partnering with patients in self-care which is grounded in Dorothea Orem’s Theory of Self-Care (Petiprin, 2016). The aim is to support personal agency in the achievement of effective self-management. A tool was needed to replace a manual system, which could identify and prioritize at risk patients and track interventions and readmissions. A real-time data system was implemented called T3, it aggregates patients from both in and out of network hospitals. T3 also ingests information from Jvion, a machine learning platform that provides a readmission risk scoring and associated interventions. A dashboard displays patients and their risk scores, along with recommended interventions. Ambulatory nurses working remotely select a patient for outreach, review machine-recommended interventions and use nursing judgement for a patient-centric approach. Readmissions prevented are recorded using specific criteria. Outcomes: On average 2200 patient were managed each month and received risk reduction interventions. Over 11 months 212 patients had a readmission prevented. With the average cost of a hospital stay at $11,200.00, these 212 prevented readmission would have cost well over 2 million dollars. Most importantly the team saved patients from sustaining additional health complications due to a readmission. Implications for practice: Health systems focusing on readmission reduction need to consider using a predictive tool which incorporates social determinants of health and recommends targeted interventions. Prioritizing discharged patients, managing and tracking interventions, and recording readmissions prevented by ambulatory nurses will demonstrate improved quality of care transitions. References: (avail)
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    Lessons learned from implementing the patient-centered medical home
    Green, Ellen P.; Wendland, John; Carver, M. Colette; Hughes Rinker, Cortney; Mun, Seong K. (Hindawi, 2012)
    The Patient-Centered Medical Home (PCMH) is a primary care model that provides coordinated and comprehensive care to patients to improve health outcomes. This paper addresses practical issues that arise when transitioning a traditional primary care practice into a PCMH recognized by the National Committee for Quality Assurance (NCQA). Individual organizations' experiences with this transition were gathered at a PCMH workshop in Alexandria, Virginia in June 2010. An analysis of their experiences has been used along with a literature review to reveal common challenges that must be addressed in ways that are responsive to the practice and patients' needs. These are: NCQA guidance, promoting provider buy-in, leveraging electronic medical records, changing office culture, and realigning workspace in the practice to accommodate services needed to carry out the intent of PCMH. The NCQA provides a set of standards for implementing the PCMH model, but these standards lack many specifics that will be relied on in location situations. While many researchers and providers have made critiques, we see this vagueness as allowing for greater flexibility in how a practice implements PCMH.
  • Protecting Teams Through the Pandemic
    Carver, M. Colette; Frazier, Tricia (2022-04-28)
    Leading with TEAM - mantra Protect our team - Protect our patients - Protect our business Consistent foundational support focused on the team 1. Wellbeing 2. Bidirectional communication 3. Workforce planning and development FCM tailwinds going into pandemic High functioning leadership team at all levels Well positioned clinics geographically - Family Medicine, Internal Medicine, Urgent Care Centers Serve as regional: COVID-19 vaccination hubs COVID-19 Testing and Infusion centers
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    Socializing the evidence for diabetes control to develop “mindlines”: a qualitative pilot study
    Epling, John W.; Rockwell, Michelle S.; Miller, Allison D.; Carver, M. Colette (2021-09-07)
    Background Evidence on specific interventions to improve diabetes control in primary care is available, but this evidence is not always well-implemented. The concept of “mindlines” has been proposed to explain how clinicians integrate evidence using specifics of their practices and patients to produce knowledge-in-practice-in-context. The goal of this pilot study was to operationalize this concept by creating a venue for clinician-staff interaction concerning evidence. The research team attempted to hold “mindlines”-producing conversations in primary care practices about evidence to improve diabetes control. Methods Each of four primary care practices in a single health system held practice-wide conversations about a simple diabetes intervention model over a provided lunch. The conversations were relatively informal and encouraged participation from all. The research team recorded the conversations and took field notes. The team analyzed the data using a framework adapted from the “mindlines” research and noted additional emergent themes. Results While most of the conversation concerned barriers to implementation of the simple diabetes intervention model, there were examples of practices adopting and adapting the evidence to suit their own needs and context. Performance metrics regarding diabetes control for the four practices improved after the intervention. Conclusion It appears that the type of conversations that “mindlines” research describes can be generated with facilitation around evidence, but further research is required to better understand the limitations and impact of this intervention.