Application of machine learning methodology to assess the performance of DIABETIMSS program for patients with type 2 diabetes in family medicine clinics in Mexico

Table 1 Characteristics of family medicine clinics and number of diabetic patients included in the analysis

Clinic Mask N = 11	Group	Consulting Rooms^a (n)	People affiliated (n)	People with type 2 diabetes with at least one medical consultation during the analyzed year					People referred and attend to DIABETIMSS program at least once
				2012	2013	2014	2015	2016	2012	2013	2014	2015	2016
				(n)	(n)	(n)	(n)	(n)	(n)	(n)	(n)	(n)	(n)
A	Diabetimss	16	76800	3602	3476	3636	4333	4315	290	249	198	344	529
B	Diabetimss	21	100800	6098	6237	6372	6603	6785	613	1755	2223	1916	1510
C	Diabetimss	25	120000	8960	9366	9749	10183	10436	2119	1818	1566	2000	1918
D	Diabetimss	12	57600	4009	4125	4194	4334	4480	534	1274	1752	1777	1588
E	Diabetimss	10	48000	2217	2443	2560	2684	2846	512	531	496	423	407
F	Diabetimss	10	48000	2440	2691	2964	3049	3238	334	390	418	363	144
G	Conventional	29	139200	7664	7862	8068	8246	8579	0	0	0	0	0
H	Conventional	30	144000	8169	8324	8338	9081	9333	0	0	0	0	0
I	Conventional	12	57600	3005	3349	3441	3611	3950	0	0	0	0	0
J	Conventional	10	48000	2867	2988	3040	3260	3247	0	0	0	0	0
K	Conventional	10	48000	2475	2537	2599	2738	3031	0	0	0	0	0
Total		185	888000	51506	53398	54961	58122	60240	4402	6017	6653	6823	6,096

^aEach consulting room works two shifts and provides healthcare to approximately 4800 affiliates

ISSN: 1472-6947