Critical Illness
Conditions
Keywords
Critical Illness, Patient Safety, Delivery of Health Care, Electronic Health Records
Brief summary
Diagnostic error and delay remain a leading cause of preventable harm and death in the United States. Using a learning laboratory structure, researchers will implement mixed-methods research approaches to identify the systemic weaknesses that contribute to diagnostic error and delay in the hospital setting. The knowledge gained from research innovative will allow researchers to design, develop, implement, and refined a suite of human-centered tools that can be deployed to reduce the risk of diagnostic error and delay in both community and academic hospital settings.
Detailed description
Despite the recognition that diagnostic errors an delays are a major contributor to preventable deaths in the USA, little progress has been made to reduce mortality outcomes from this known killer. An effective strategy leading to meaningful reduction in diagnostic error and delay rates has not made its way into practice. This proposal is unique and novel and combines mixed-methods research approaches with systems engineering research approaches to understand the interplay of the multiple factors contributing to diagnostic error and delay. The knowledge gained from this holistic approach will then be used within the learning laboratory to inform the design, development, evaluation, and refinement of the solutions to diagnostic error and delay. Control Tower will be the staging ground for the in situ learning laboratory and will be built on top of a well-established clinical informatics infrastructure and hospital environment open to innovation and practice change.
Interventions
None listed
Sponsors
Study design
Eligibility
Inclusion criteria
* For EMR review all adults admitted to the hospital ages 18 and older with research authorization * For survey-clinicians including physicians, advanced care practitioners * For focus groups and interviews-clinicians including physicians, advanced care practitioners
Exclusion criteria
* Age \<18 years old * No research authorization * Refusal to give consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Validation of automated phenotypes | 1 year | Use data from the patient electronic medical record to identify the number of diagnostic error or delay to validate clinical environment automated phenotypes |
| Adoption (Number of time the Control Tower used during the clinical encounters) | 1 year | Standardized process tracking sheets to track each time the control tower system is triggered and used. |
| Implementation Acceptability | 1 year | Focused questions about beliefs, attitudes, usability by healthcare providers |
Countries
United States