TABLE 4.
Implementation Outcomes for the Use of Data Science in Critical Care
| CFIR Outcomes Addendum Implementation Outcome Domains | CFIR Outcomes Addendum Implementation Outcome Constructs | Suggested Measures |
|---|---|---|
| Antecedent assessments | Acceptability | Acceptability of intervention measure (67) |
| Appropriateness | Intervention appropriateness measure (67) | |
| Feasibility | Feasibility of intervention measure (67) | |
| Implementation readiness | Various measures of implementation readiness (e.g., Texas Christian University Organizational Readiness for Change) (68) and implementation climate (e.g., adaptations of Klein and Sorra’s construct developed within the context of information technology implementation) (69) | |
| Implementation climate | ||
| Implementation outcomes | Anticipated and actual | Penetration (70) of Critical Care Data Dictionary common data elements |
| Adoptability and adoption | Penetration (70) and maintenance of Discovery Critical Care Datahub | |
| Implementability and implementation | Maintenance of annual Society of Critical Care Medicine datathons | |
| Sustainability and sustainment | Publication of peer-reviewed articles related to data science in critical care | |
| Innovation outcomes | Equitable population impact on: | |
| Decision-makers (e.g., administrators) | Institute of Medicine service outcomes (70): | |
| Efficiency | ||
| Safety | ||
| Effectiveness | ||
| Equity | ||
| Patient-centeredness | ||
| Timeliness | ||
| Deliverers (e.g., researchers, data scientists, clinicians) | “Quadruple Aim” outcomes (71) pertaining to health care deliverers, including: | |
| Reduced burnout | ||
| Improved work experience | ||
| Recipients (e.g., patients) | Barr’s health/effectiveness outcomes (72): | |
| Family and surrogate well-being/quality of life | ||
| Physical functioning | ||
| Post-ICU trajectory | ||
| Psychologic well-being | ||
| Satisfaction | ||
CFIR = Consolidated Framework for Implementation Research.