msos is a formatted text - messaging system that enables communications between healthcare facility workers and ministry of health managers and uses a web - based portal to monitor disease notifications and response actions taken by health managers ( figure 1 ; online technical appendix , http://wwwnc.cdc.gov/eid/article/22/4/15-1459-techapp1.pdf ) . in our trial , health workers used msos for 6 months to send information about suspected cases or health events that required notification within 24 hours .
twelve diseases and conditions were selected for the study ( online technical appendix table 1 ) .
before msos was implemented , we conducted a 1-day refresher training course on idsr for in - charges ( i.e. , medical officers in charge ) of 135 participating health facilities ; the training focused on case definitions of notifiable diseases and on paper - based reporting . during the training
, facilities were randomized into intervention and control groups ; the intervention group received an additional day of training on msos .
paper - based reporting continued throughout the study period for both groups , so the intervention group would report cases 2 ways . structure and communication flow of a mobile short - message - service
* the table does not show data for busia county because values will be inverse of data for kajiado county ( i.e. , n minus
the intervention group is the group of facility in - charges who were exposed to idsr and msos training and to the msos intervention ; the control group is the group of in - charges who were exposed to idsr training only .
fbo , faith - based organization ; idsr , integrated disease surveillance and response ; in - charge , medical officer in charge of facility ; iqr , interquartile range ; ngo , nongovernment organization . 
wilcoxon mann whitney test was used to compare medians between control and intervention groups ( i.e. , age of in - charges ) .
the p value is shown for the postintervention period only .  standardized idsr paper - based reporting form for immediately notifiable diseases
denominator excludes 3 facilities with missing values in the preintervention control group and 1 facility with missing values for each of the remaining 3 study groups .
our primary outcome was determining how many of the cases that required immediate notification were reported within the time specified .
our secondary outcome was determining , from among the cases for which notifications were sent , the proportion for which response actions were taken . for evaluation purposes , data from health facilities were collected for 6-month periods before and after the intervention launch ( i.e. , idsr and msos training and use of msos for 6 months ) .
cases detected , notifications submitted , and responses undertaken were extracted from facility records in both study groups .
our primary analysis was intention - to - treat ( i.e. , analysis of cases from all health facilities as they were randomized , regardless of intervention exposure ) .
our secondary analysis was per - protocol ( i.e. , our trial protocol ) and was restricted to cases reported by facilities whose in - charges had received training ( i.e. , idsr training for control group ; idsr and msos training for intervention group ; figure 2 ) .
profile of control and intervention health facilities and exclusions during the course of a study of a mobile short - message - service  based disease outbreak alert system ( msos ) in kenya .
characteristics of health facilities and in - charges were similar ; data from preintervention and postintervention surveys showed no significant differences between control and intervention groups ( table 1 ) .
follow - up surveys conducted 6 months after the intervention showed that 34 ( 51.6% ) of 66 intervention group in - charges received msos and idsr training and 32 ( 49.2% ) of 65 control group in - charges received idsr training ( figure 2 ; online technical appendix ) .   a retrospective review of the baseline ( preintervention ) surveys showed that 36 cases ( 19 for intervention group , 17 for control group ) , all measles , required immediate notification . of these 36 cases , only 1 immediately notifiable case was reported ( from a control facility using paper forms ) . during the 6-month period after the intervention , 169 immediately notifiable cases ( 130 for the intervention group , 39 for the control group )
were detected : 160 measles , 6 anthrax , 2 q fever , and 1 guinea worm .
of the 39 cases detected in the control group , notification of only 1 case ( 2.6% ) , which was measles , was sent .
of the 130 immediately notifiable cases detected in the intervention group , 25 ( 19.2% ) were reported to disease surveillance coordinators at the subcounty , county , and national levels .
this proportion of cases reported was significantly higher than that reported by the control group ( % difference 16.7 , 95% ci  2.7125.07 ; table 2 ) .  
* intention - to - treat analysis indicates analysis of treatment groups as they were randomized , regardless of the intervention exposure ; per - protocol analysis indicates restricted analysis of groups that completed the entire study according to the trial protocol .
all 25 cases for which notifications were sent from the intervention group were measles cases reported through msos ; 2 cases were also reported with paper forms .
for these 25 msos notifications , the threshold for a measles outbreak response ( 5 suspected cases ) was met once , and disease surveillance coordinators at the subcounty level responded to this event .
furthermore , 24 ( 96% ) of the 25 suspected measles cases were reported within 24 hours .   in the per - protocol analysis ,
the percentage of cases for which notification was sent was greater in the intervention group than in the control group ( 27.3% vs. 4.8% ) , but the difference was of borderline statistical significance ( % difference 22.5 , 95% ci  0.32 to 34.13 by wilson procedure with continuity correction ) .
similar differences were found when the analysis was restricted to health facilities that stocked paper - based tools ( i.e. , control group , 1/18 [ 5.6% ] vs. intervention group , 22/78 [ 22.6% ] ; % difference 17.0 , 95% ci  2.93 to 35.30 ) .
this study showed that sms intervention significantly increased timely notifications ; however , despite a relatively large improvement , response remained suboptimal , with timely notifications of only one fifth of detected cases .
these findings mirror results of a study in tanzania , which showed that sms considerably increased vital registration coverage but fell far short of reporting actual birth and death events in the community ( 12 ) .
our study has implications for health managers who implement interventions to improve disease surveillance in resource - limited settings .
this effect was observed in both intervention and control groups but was higher in the group using sms ; this group had a 7-fold increase in detected cases compared with baseline findings .
idsr refresher training may have contributed to increased case detection , and the combined interventions , including the technology component , resulted in a greater detection effect .
second , expecting health workers to complete paper - based forms and deliver them without incentive within 24 hours is ineffective for ensuring notification of cases , with or without exposure to the refresher training .
third , we observed a large drop - out rate ( 47.4% ) for health facility in - charges participating in the study .
the study took place during a period of health management decentralization in kenya , resulting in 47 new counties and in health worker transfers .
lack of on - the - job training for staff who did not attend the training and lack of support through posttraining follow - up and supportive supervision were weaknesses in the intervention .
these systemic challenges , reported in other idsr ( 13 ) and mhealth surveillance ( 14 ) projects , must be addressed to avoid compromising the sustainability of such interventions .
finally , attrition of health workers exposed to the intervention and lack of paper - based tools explain only part of our results .
the short duration of the training deployed ( 15 ) and the possibly suboptimal quality of the training delivered ( 3 ) may have contributed to the unrealized full potential of the intervention . despite its limitations ( online technical appendix ) , this study shows how technology in the form of msos can increase the rate of notifications of suspected disease outbreaks and enhance ihr compliance in resource - limited settings .
further investigation into ways to optimize the quality of delivery of msos interventions in countries with weak healthcare systems is justified .
technical appendix . methods and additional details of a study of a mobile short - message - service  based disease outbreak alert system in kenya .
 we conducted a randomized , controlled trial to test the effectiveness of a text - messaging system used for notification of disease outbreaks in kenya . 
 health facilities that used the system had more timely notifications than those that did not ( 19.2% vs. 2.6% ) , indicating that technology can enhance disease surveillance in resource - limited settings . 
The Study
Conclusions
None