Developing a system that can automatically detect health changes using transfer times of older adults

Baldewijns, Greet; Luca, Stijn; Vanrumste, Bart; Croonenborghs, Tom

doi:10.1186/s12874-016-0124-4

BMC Medical Research Methodology

Table 5 Results Tabular CUSUM, Standardized CUSUM and EWMA (when the dataset contains two trends both trends are evaluated separately)

From: Developing a system that can automatically detect health changes using transfer times of older adults

	Tabular CUSUM (TC)								Standardized CUSUM (SC)								EWMA (E)
	TC		RS^b		RA^c		RSRA^d		SC		RS^b		RA^c		RSRA^d		E		RS^b		RA^c		RSRA^d
Average number of false positive alerts per week
	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd
T r _S ^a	0.01	0.04	0.06	0.08	0.10	0.04	0.04	0.04	0.19	0.16	0.10	0.03	0.09	0.02	0.19	0.14	0.00	0.00	0.14	0.08	0.00	0.00	0.03	0.06
T r _U	0.06	0.08	0.09	0.06	0.11	0.08	0.15	0.12	0.13	0.11	0.15	0.11	0.07	0.05	0.18	0.17	0.00	0.00	0.20	0.15	0.00	0.00	0.05	0.06
T r _SU	0.04	0.02	0.01	0.02	0.07	0.04	0.03	0.04	0.06	0.05	0.05	0.03	0.05	0.02	0.08	0.07	0.01	0.02	0.06	0.04	0.03	0.02	0.08	0.05
T r _US	0.02	0.03	0.02	0.02	0.05	0.03	0.04	0.04	0.04	0.04	0.08	0.08	0.04	0.03	0.06	0.06	0.02	0.04	0.09	0.08	0.02	0.03	0.08	0.04
T r _SUS	0.03	0.02	0.01	0.01	0.05	0.03	0.02	0.02	0.03	0.02	0.02	0.01	0.05	0.03	0.05	0.04	0.01	0.01	0.05	0.03	0.03	0.02	0.01	0.04
T r _USU	0.01	0.02	0.03	0.03	0.03	0.03	0.04	0.02	0.02	0.03	0.03	0.03	0.03	0.02	0.03	0.03	0.01	0.02	0.08	0.07	0.02	0.02	0.08	0.04
Detection rate
T r _SU	10 %		95 %		100 %		100%		40 %		0 %		100 %		25 %		85 %		100 %		100 %		100 %
T r _US	70 %		85 %		95 %		100%		65 %		25 %		45 %		60 %		85 %		100 %		65 %		100 %
T r _SUS
S →U	10 %		95 %		95 %		95%		30 %		0 %		95 %		35 %		75 %		100 %		95 %		100 %
U →S	0 %		0 %		95 %		75%		0 %		0 %		0 %		0 %		0 %		0 %		35 %		100 %
T r _USU
S →U	60 %		70 %		100 %		100%		55 %		25 %		35 %		60 %		85 %		95 %		55 %		95 %
U →S	0 %		0 %		100 %		100%		0 %		0 %		60 %		0 %		5 %		40 %		65 %		100 %
Average Run Length [days]
	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd
T r _SU	2.50	2.12	17.47	4.56	10.30	3.40	16.25	2.99	6.38	4.34	/	/	13.75	4.00	7.20	4.60	2.94	2.36	10.20	3.53	15.85	3.05	10.10	3.39
T r _US	5.29	5.38	16.41	3.39	14.89	3.96	14.00	4.53	14.08	5.89	7.80	7.29	16.89	4.78	12.00	5.41	11.18	4.39	14.05	6.55	23.38	2.79	14.85	6.10
T r _SUS
S →U	4.00	1.41	18.95	2.68	13.00	5.42	16.21	5.14	4.33	3.14	/	/	13.58	4.60	6.29	1.98	2.93	2.25	9.20	4.27	15.79	3.60	10.80	4.27
U →S	/	/	/	/	15.63	3.68	11.20	4.38	/	/	/	/	/	/	/	/	/	/	/	/	24.14	2.14	13.15	5.90
T r _USU
U →S	6.50	6.79	14.64	6.06	16.85	6.06	12.60	5.45	12.27	4.58	10.40	9.34	12.57	4.61	8.58	5.62	11.29	6.57	21.37	5.91	21.55	4.11	14.05	5.35
S →U	/	/	/	/	10.95	3.66	15.65	4.22	/	/	/	/	15.08	3.48	/	/	6.00	0.00	13.88	6.75	20.77	3.14	13.25	4.84

Notes
^aTraining simulation scenarios as described in Table 3
^bControl chart with rational subgroups implemented
^cControl chart with a reinitialization after three consecutive alarm days
^dControl chart with rational subgroups and a reinitialization after three consecutive alarm days

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