Table 1.

Summary of High-priority Research and Policy Recommendations, With Examples of Solutions and Potential Pitfalls to Implementation or Adoption

Recommendation	Examples	Pitfalls
1. Develop improved methods for cross-platform identification and linkage of patients	Global unique identifier (GUID)	Security/privacy
2. Create central, deidentified, open access databases	NIH -omics repositories	Unfunded mandates, system maintenance
3. Improve methodologies for visualization and analysis of intensively sampled data	Continuous telemetry, fitness trackers	File size, data storage, proprietary restrictions
4. Develop methods to identify and standardize electronic medical record data quality	Identification of template overuse, prevention of illogical data entry	Evolving, unreliable history
5. Improve and utilize natural language processing	Leverage richness of natural language over discrete data fields	Clinician level and regional variations
6. Develop and utilize syndrome or complaint-based based taxonomies of disease	Chest pain rather than gastroesophageal reflux disease	Billing tied to diagnosis codes
7. Develop a practical and ethical framework to leverage electronic systems for controlled trials	Patient level or site clustered randomization	Overreliance on statistical modeling and inference
8. Explore technologies to help enable clinical trials in the emergency setting	National database of preencounter consent	Practical framework, time sensitivity
9. Train emergency care clinicians in data science and data scientists in emergency care medicine	K08, K23, and K24 mechanisms	Dissociation of clinical practicalities from data analysis