Comparison of six statistical methods for interrupted time series studies: empirical evaluation of 190 published series

Table 2 Characteristics of interrupted time series studies and series

Study level characteristics	All ITS studies (n = 200)		ITS studies with available data (n = 166)
Study level characteristics	n	%	n	%
Type of interruption
Exposure^a	12	6	10	6
Intervention	188	94	156	94
Intervention type
Policy change	104	52	82	49
Practice change	40	20	36	22
Communication	29	15	24	14
Organisation of care	13	7	12	7
Clinical intervention	2	1	2	1
Time interval type
Daily	3	2	2	1
Weekly	9	5	6	4
Two weekly	1	1	1	1
Monthly	120	60	96	58
Quarterly	31	16	28	17
Six monthly	3	2	3	2
Annually	20	10	17	10
Other	12	6	12	7
Can't determine	1	1	1	1
Series level characteristics	ITS (n = 230)		ITS with available data (n = 190)
Series level characteristics	median	IQR	median	IQR
Number of time points per series	48	(30, 100)	41	(25, 71)
Number of time points in the segments used to calculate estimates for the first interruption	18	(10, 34)	16	(10, 28)

Abbreviations: ITS Interrupted time series, IQR Inter-quartile range
^aOur definition of an exposure is limited to exposures or events that are not under investigator control (e.g. earthquakes, financial crises, tsunamis, environmental chemicals). We use the term ‘investigator’ loosely to include researchers, clinicians and policy makers

ISSN: 1471-2288