The Nursing Home Severity Index and Application to Pressure Injury Risk: Measure Development and Validation Study
Bibliographic record
Abstract
BACKGROUND: An assessment tool is needed to measure the clinical severity of nursing home residents to improve the prediction of outcomes and provide guidance in treatment planning. OBJECTIVE: This study aims to describe the development of the Nursing Home Severity Index, a clinical severity measure targeted for nursing home residents with the potential to be individually tailored to different outcomes, such as pressure injury. METHODS: A retrospective nonexperimental design was used to develop and validate the Nursing Home Severity Index using secondary data from 9 nursing homes participating in the 12-month preintervention period of the Turn Everyone and Move for Ulcer Prevention (TEAM-UP) pragmatic clinical trial. Expert opinion and clinical literature were used to identify indicators, which were grouped into severity dimensions. Index performance and validation to predict risk of pressure injury were accomplished using secondary data from nursing home electronic health records, Minimum Data Sets, and Risk Management Systems. Logistic regression models including a resident's Worst-Braden score with/without severity dimensions generated propensity scores. Goodness of fit for overall models was assessed using C statistic; the significance of improvement of fit after adding severity components to the model was determined using the likelihood ratio chi-square test. The significance of each component was assessed with odds ratios. Validation based on randomly selected 65% training and 35% validation data sets was used to confirm the reliability of the severity measure. Finally, the discriminating ability of models was evaluated using propensity stratification to evaluate which model best discriminated between residents with/without pressure injury. RESULTS: Data from 1015 residents without pressure injuries on admission were used for the Nursing Home Severity Index-Pressure Injury and included laboratory, weights/vitals/pain, underweight, and locomotion severity dimensions. Logistic regression C statistic measuring predictive accuracy increased by 19.3% (from 0.627 to 0.748; P<.001) when adding four severity dimensions to Worst-Braden scores. Significantly higher odds of developing pressure injuries were associated with increasing dimension scores. The use of the three highest propensity deciles predicting the greatest risk of pressure injury improved predictive accuracy by detecting 21 more residents who developed pressure injury (n=58, 65.2% vs n=37, 42.0%) when both severity dimensions and Worst-Braden score were included in prediction modeling. CONCLUSIONS: The clinical Nursing Home Severity Index-Pressure Injury was successfully developed and tested using the outcome of pressure injury. Overall predictive capacity was enhanced when using severity dimensions in combination with Worst-Braden scores. This index has the potential to significantly impact the quality of care decisions aimed at improving individual pressure injury prevention plans. TRIAL REGISTRATION: ClinicalTrials.gov NCT02996331; http://clinicaltrials.gov/ct2/show/NCT02996331.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".