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. 2018 May;66(5):930-936.
doi: 10.1111/jgs.15324. Epub 2018 Mar 2.

Predicting Potential Adverse Events During a Skilled Nursing Facility Stay: A Skilled Nursing Facility Prognosis Score

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Predicting Potential Adverse Events During a Skilled Nursing Facility Stay: A Skilled Nursing Facility Prognosis Score

Robert E Burke et al. J Am Geriatr Soc. 2018 May.

Abstract

Objectives: To derive a risk prediction score for potential adverse outcomes in older adults transitioning to a skilled nursing facility (SNF) from the hospital.

Design: Retrospective analysis.

Setting: Medicare Current Beneficiary Survey (2003-11).

Participants: Previously community-dwelling Medicare beneficiaries who were hospitalized and discharged to SNF for postacute care (N=2,043).

Measurements: Risk factors included demographic characteristics, comorbidities, health status, hospital length of stay, prior SNF stays, SNF size and ownership, treatments received, physical function, and active signs or symptoms at time of SNF admission. The primary outcome was a composite of undesirable outcomes from the patient perspective, including hospital readmission during the SNF stay, long SNF stay (≥100 days), and death during the SNF stay.

Results: Of the 2,043 previously community-dwelling beneficiaries hospitalized and discharged to a SNF for post-acute care, 589 (28.8%) experienced one of the three outcomes, with readmission (19.4%) most common, followed by mortality (10.5%) and long SNF stay (3.5%). A risk score including 5 factors (Barthel Index, Charlson-Deyo comorbidity score, hospital length of stay, heart failure diagnosis, presence of an indwelling catheter) demonstrated very good discrimination (C-statistic=0.75), accuracy (Brier score=0.17), and calibration for observed and expected events.

Conclusion: Older adults frequently experience potentially adverse outcomes in transitions to a SNF from the hospital; this novel score could be used to better match resources with patient risk.

Keywords: discharge; post-acute care; skilled nursing facility; transitions.

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Conflict of interest statement

Conflict of interest: The authors have no personal, financial, or potential conflicts of interest.

Figures

Figure 1
Figure 1
Receiver operating characteristic curve for final model The receiver operating characteristic curve with labeled Youden’s Index (best trade-off of sensitivity and specificity), including corresponding values for: Se (sensitivity), Sp (specificity), PPV (positive predictive value), NPV (negative predictive value), LR+ (positive likelihood ratio), LR− (negative likelihood ratio). This figure also displays the distribution of events in a histogram at top.
Figure 2
Figure 2
Calibration of SNF prognosis score The calibration plot demonstrates observed outcomes compared to expected outcomes across the range of probabilities; perfect calibration is demonstrated by the “Ideal” dotted line while our initial results are indicated by the “Apparent” line; “Bias-corrected” refers to the performance after bootstrap resampling.
Figure 3
Figure 3
Nomogram for SNF prognosis score Scoring for the continuous predictors (Barthel Index, Charlson Deyo and previous inpatient length of stay), may be determined by finding the value of the predictor on the top of the scale, and then reading the points below the line (Figure 3A). For example, a Barthel Index score of 20 would contribute 80 points to the total score. Points for indwelling catheter and/or CHF are added if the patient has the condition. Points from each of the five predictors are added and the total points are used to determine the predicted probability of the composite outcome; the example from the Results section is displayed in the bottom Figure (3B).

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References

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