Parenteral nutrition insecurity: ASPEN survey to assess the extent and severity of parenteral nutrition access and reimbursement issues
Bibliographic record
Abstract
BACKGROUND: Parenteral nutrition (PN) shortages and lack of qualified professional staff to manage PN impact safe, efficacious care and costs of PN. This American Society for Parenteral and Enteral Nutrition (ASPEN)-sponsored survey assessed the frequency and extent to which PN access affects PN delivery to patients. METHODS: Healthcare professionals involved with PN were surveyed. Questions were developed to characterize the respondent population and determine the extent and severity of PN access issues to components, devices, and healthcare professionals, as well as their effects on discharge and transfer issues. Reimbursement issues included cost, adequacy of therapy, and healthcare professional reimbursement. Burdens were types and frequency of errors, adverse events, and nutrition problems resulting from PN access issues. Impact on professionals and organizations was determined. RESULTS: Respondents (N = 350) worked in hospitals (75%) and home infusion (25%). Per day, clinicians cared for <15 patients receiving PN. All age populations were represented. Respondents reported shortages of macronutrients (72%, 233 of 324) and micronutrients (91%, 297 of 324). Issues with access to healthcare workers were observed. PN access issues contribute to increased costs of PN, and knowledge regarding the current rate of PN reimbursement is limited. Respondents (75%, 197 of 261) observed an error due to PN access issues. Adverse events (57%, 149 of 259) were observed leading to temporary or permanent harm (24%, 61 of 259) as well as near death (4%, 9 of 259) and death (1%, 2 of 259). Providers reported time away from other job responsibilities and workplace stress. CONCLUSION: PN access issues result in "PN insecurity" that negatively impacts patients and healthcare providers and leads to adverse events including death in patients receiving PN.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".