UCLA

Background

COPD exacerbations occur more frequently with disease progression and are associated with worse prognosis and higher healthcare expenditure.

Purpose

To utilize a networked system, optimized with statistical process control (SPC), for remote patient monitoring (RPM) and to identify potential predictors of COPD exacerbations.

Methods

Seventeen subjects, mean (SD) age of 69.7 (7.2) years, with moderate to severe COPD received RPM. Over 2618 patient-days (7.17 patient-years) of monitoring, we obtained daily symptom scores, treatment adherence, self-reported activity levels, daily spirometry (SVC, FEV₁, FVC, PEF), inspiratory capacity (IC), and oxygenation (SpO₂). These data were used to identify predictors of exacerbations defined using Anthonisen and other criteria.

Results

After implementation of SPC, concordance analysis showed substantial agreement between FVC (decrease below the 7-day rolling average minus 1.645 SD) and self-reported healthcare utilization events (κ=0.747, P<0.001) as well as between increased use of inhaled short-acting bronchodilators and exacerbations defined by two Anthonisen criteria (κ=0.611, P<0.001) or modified Anthonisen criteria (κ=0.622, P<0.001). There was a moderate agreement between FEV₁ (decrease >1.645 SD below the 7-day rolling average) and self-reported healthcare utilization events (κ=0.475, P<0.001) and between SpO₂ less than 90% and exacerbations defined by two Anthonisen criteria (κ=0.474, P<0.001) or modified Anthonisen criteria (κ=0.564, P<0.001).

Conclusion

Exacerbations were best predicted by FVC and FEV₁ below the one-sided 95% confidence interval derived from SPC but also by increased use of inhaled short-acting bronchodilators and fall in oxygen saturation. An RPM program that captures these parameters may be used to guide appropriate interventions aimed at reducing healthcare utilization in COPD patients.