. Author manuscript; available in PMC: 2016 Aug 18.

Published in final edited form as: J Am Geriatr Soc. 2016 Jun 16;64(8):1668–1673. doi: 10.1111/jgs.14201

TABLE 2.

Comparing Regression Models with Different Multimorbidity Indicators as Predictors of Acute Care Utilization

	ED^a Visit in 1 Year				Hospital Admission in 1-year

Model^b	DF^c	Wald χ²	p value	C- statistic^d	DF	Wald χ²	p value	C- statistic
Model 1				0.627				0.667
Multimorbidity Class	5	260.5	<0.001		5	470.0	<0.001

Model 2				0.639^e				0.678^e
Morbidity Count	1	325.1	<0.001		1	533.3	<0.001

Model 3				0.640^e				0.682^e
Multimorbidity Class	5	10.9	0.05		5	32.4	<0.001
Morbidity Count	1	74.9	<0.001		1	94.4	<0.001

ED = emergency department

All models are adjusted for age, race, sex, and education level

DF = degrees of freedom

The c-statistics for Models 2 and 3 were unchanged, regardless of whether “morbidity count” was treated as a continuous vs. class variable. Parameters presented here are taken from analyses that treated morbidity count as a continuous variable (possible range 0–13); multimorbidity class was treated as a nominal class variable with 6 levels.

C-statistic is significantly different (p<0.001) from the c-statistic for Model 1, as assessed by the DeLong test¹⁹. C-statistics of Models 2 and 3 were not significantly different from each other (p=0.861 for outcome of ED visits; p=0.170 for outcome of hospital admission).