Can Emergency Department, Hospital Discharge, and Death Data Be Used to Monitor Burden of Drug Overdose in Rhode Island?
Bibliographic record
Abstract
CONTEXT: Drug overdoses are a growing public health problem in the United States. Rhode Island is also confronted with a serious epidemic of drug overdose deaths and ranks sixth worst in the United States for age-adjusted drug overdose death rate. OBJECTIVE: To monitor trends of drug overdose-related emergency department (ED) visits, hospitalizations, and deaths and classify the drug overdoses by demographics, discharge status, intent, and specific drug involved to plan for health care resource allocation, mental health services, drug abuse treatment, prevention, and policies. DESIGN: Cross-sectional study. SETTING: The 2005-2014 ED, hospital discharge, and death data were used for this study. MAIN OUTCOME MEASURE: Age-adjusted rates were calculated by using age-specific Rhode Island 2010 standard population. Healthcare Cost and Utilization Project cost-to-charge ratios were used to convert total hospital charges to costs. The descriptive analysis was performed. RESULTS: Hospitalizations generally represent the most severe cases; there are substantially fewer cases than are seen in the ED, and their characteristics are different from ED visits. More than half of the ED cases were an unintentional injury by drug overdose, but more than half of the hospital discharge data cases were a suicide/self-inflicted injury by drug overdose. There were typically much more females than males that result in a hospital admission. In Rhode Island, there were 249 drug overdose deaths in 2014. Drug overdose fatalities were more likely to be young, male, white, and those who reside in suburban regions. IMPLICATIONS: Nonfatal and fatal drug overdose data are important for understanding the scope, incidence, and breadth of this public health epidemic and can guide overdose intervention efforts. In Rhode Island, policy makers can use drug overdose data to target high-risk subpopulations to reduce overdose injuries and fatalities. The Rhode Island study can be shared with other states. CONCLUSIONS: Regardless of the type of drug, overdoses remain a public health crisis in Rhode Island. It is a dynamic epidemic and needs partnership among public health, behavioral health, public safety, clinic, pharmacy, and communities. The ability to track drug overdose in real time will be an essential tool to respond to the constantly evolving drug overdose epidemic in Rhode Island quickly and effectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".