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Introduction: Tracking adaptations during implementation can help assess and interpret outcomes. The framework for reporting adaptations and modifications-expanded (FRAME) provides a structured approach to characterize adaptations. We applied the FRAME across multiple health services projects, and developed an analytic approach to assess the impact of adaptations. Methods: Mixed methods analysis of research diaries from seven quality improvement (QI) and research projects during the early stages of the COVID-19 pandemic. Using the FRAME as a codebook, discrete adaptations were described and categorized. We then conducted a three-step analysis plan: (1) calculated the frequency of adaptations by FRAME categories across projects;(2) qualitatively assessed the impact of adaptations on project goals;and (3) qualitatively assessed relationships between adaptations within projects to thematically consolidate adaptations to generate more explanatory value on how adaptations influenced intervention progress and outcomes. Results: Between March and July 2020, 42 adaptations were identified across seven health services projects. The majority of adaptations related to training or evaluation (52.4%) with the goal of maintaining the feasibility (66.7%) of executing projects during the pandemic. Five FRAME constructs offered the most explanatory benefit to assess the impact of adaptations on program and evaluation goals, providing the basis for creating an analytic approach dubbed the "A-FRAME,” analysis of FRAME data. Using the A-FRAME, the 42 adaptations were consolidated into 17 succinct adaptations. Two QI projects discontinued altogether. Intervention adaptations related to staffing, training, or delivery, while evaluation adaptations included design, recruitment, and data collection adjustments. Conclusions: By sifting qualitative data about adaptations into the A-FRAME, implementers and researchers can succinctly describe how adaptations affect interventions and their evaluations. The simple and concise presentation of information using the A-FRAME matrix can help implementers and evaluators account for the influence of adaptations on program outcomes. © 2023 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.
ABSTRACT
S45 Figure 1Population pyramids (left) and Kaplan-Meier survival curves (right) for IL-6, Troponin, and CRP by quintile[Figure omitted. See PDF]ConclusionsRaised levels of IL-6 and TT on admission are associated with a significantly increased risk of inpatient mortality in those hospitalised with COVID-19, however, raised inflammatory markers at the time of hospital admission show no association with residual symptom burden at 3-month follow-up in surviving patients.
ABSTRACT
Background: The objective of this study was to determine whether a learning collaborative for hemodialysis providers improved delivery of supportive care best practices. Methods: Ten U.S. hemodialysis centers participated in a hybrid implementationeffectiveness pre-post study targeting seriously ill patients between April 2019 and September 2020. The collaborative educational bundle consisted of learning sessions, communication training and implementation support. The primary outcome was change in proportion of seriously ill patients with complete advance care planning (ACP) documentation. Healthcare utilization was a secondary outcome and implementation was assessed qualitatively. Results: One center dropped out during the COVID-19 pandemic. Among the remaining nine centers, 22.9% (320/1395) of patients were identified as seriously ill in the pre-intervention period and 18.0% (226/1254) were identified in the post-intervention period. From the pre-intervention to post-intervention period, the proportion of patients with complete ACP documentation increased, and hospitalizations and emergency department visits decreased (Table). There was no difference in mortality, palliative dialysis, hospice referral or dialysis discontinuation. Screening for serious illness was widely and sustainably adopted. Goals of care discussions were adopted with variable integration and sustainment. Conclusions: Supportive care best practices were feasible to implement in hemodialysis centers and largely sustained during the COVID-19 pandemic. We observed increased documentation of ACP and lower healthcare utilization after the intervention which could reflect a combination of collaborative and pandemic effects. (Table Presented) .