scholarly journals Use of technology for public health surveillance reporting: opportunities, challenges and lessons learnt from Kenya

2019 ◽  
Author(s):  
Ian Njeru ◽  
David Kareko ◽  
Ngina Kisangau ◽  
Daniel Langat ◽  
Nzisa Liku ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Intervention Group ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Control Group ◽  
Percentage Points ◽  
Reporting Rates ◽  
The Impact

Abstract Background Infectious diseases remain one of the greatest threats to public health globally. Effective public health surveillance systems are therefore needed to provide timely and accurate information for early detection and response. In 2016, Kenya transitioned its surveillance system from a standalone web-based surveillance system to the more sustainable and integrated District Health Information System 2(DHIS2). As part of Global Health Security Agenda(GHSA) initiatives in Kenya, training on use of the new system was conducted among surveillance officers. We evaluated the surveillance indicators during the transition period in order to assess the impact of this training on surveillance metrics and identify challenges affecting reporting rates.Methods From February to May 2017, we analysed surveillance data for 13 intervention and 13 control counties. An intervention county was defined as one that had received a refresher training on DHIS2 while a control county was one that had not received training. We evaluated the impact of the training by analysing completeness and timeliness of reporting 15 weeks before and 12 weeks after the training. A chi-square test was used to compare the reporting rates between the two groups. A structured questionnaire was administered to the training participants to assess the challenges affecting surveillance reporting. A Likert scale was used to grade the challenges.Results The completeness of reporting increased after the training by 17 percentage points (from 45% to 62%) for the intervention group compared to 3 percentage points (49% to 52%) for the control group. Timeliness of reporting increased by 21 percentage points (from 30% to 51%) for the intervention group compared to 7 percentage points (from 31% to 38%) for the control group. Major challenges identified for the low reporting rates included lack of budget support from government, lack of airtime for reporting, health workers strike, health facilities not sending surveillance data, use of wrong denominator to calculate reporting rates and surveillance officers being given other competing tasks.Conclusions Training plays an important role in improving public health surveillance reporting. However, to improve surveillance reporting rates to the desired national targets, other challenges affecting reporting must be identified and addressed accordingly.

scholarly journals Use of technology for public health surveillance reporting: opportunities, challenges and lessons learnt from Kenya

2020 ◽  
Author(s):  
Ian Njeru ◽  
David Kareko ◽  
Ngina Kisangau ◽  
Daniel Langat ◽  
Nzisa Liku ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Comparison Group ◽  
Intervention Group ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Percentage Points ◽  
Reporting Rates ◽  
The Impact

Abstract Background: Infectious diseases remain one of the greatest threats to public health globally. Effective public health surveillance systems are therefore needed to provide timely and accurate information for early detection and response. In 2016, Kenya transitioned its surveillance system from a standalone web-based surveillance system to the more sustainable and integrated District Health Information System 2 (DHIS2). As part of Global Health Security Agenda (GHSA) initiatives in Kenya, training on use of the new system was conducted among surveillance officers. We evaluated the surveillance indicators during the transition period in order to assess the impact of this training on surveillance metrics and identify challenges affecting reporting rates. Methods: From February to May 2017, we analysed surveillance data for 13 intervention and 13 comparison counties. An intervention county was defined as one that had received refresher training on DHIS2 while a comparison county was one that had not received training. We evaluated the impact of the training by analysing completeness and timeliness of reporting 15 weeks before and 12 weeks after the training. A chi-square test of independence was used to compare the reporting rates between the two groups. A structured questionnaire was administered to the training participants to assess the challenges affecting surveillance reporting. Results: The completeness of reporting increased significantly after the training by 17 percentage points (from 45% to 62%) for the intervention group compared to 3 percentage points (49% to 52%) for the comparison group. Timeliness of reporting increased significantly by 21 percentage points (from 30% to 51%) for the intervention group compared to 7 percentage points (from 31% to 38%) for the comparison group. Major challenges identified for the low reporting rates included lack of budget support from government, lack of airtime for reporting, health workers strike, health facilities not sending surveillance data, use of wrong denominator to calculate reporting rates and surveillance officers being given other competing tasks. Conclusions: Training plays an important role in improving public health surveillance reporting. However, to improve surveillance reporting rates to the desired national targets, other challenges affecting reporting must be identified and addressed accordingly.

scholarly journals Use of technology for public health surveillance reporting: opportunities, challenges and lessons learnt from Kenya

2020 ◽  
Author(s):  
Ian Njeru ◽  
David Kareko ◽  
Ngina Kisangau ◽  
Daniel Langat ◽  
Nzisa Liku ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Comparison Group ◽  
Transition Period ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Percentage Points ◽  
Reporting Rates ◽  
The Impact

Abstract Background: Effective public health surveillance systems are crucial for early detection and response to outbreaks. In 2016, Kenya transitioned its surveillance system from a standalone web-based surveillance system to the more sustainable and integrated District Health Information System 2 (DHIS2). As part of Global Health Security Agenda (GHSA) initiatives in Kenya, training on use of the new system was conducted among surveillance officers. We evaluated the surveillance indicators during the transition period in order to assess the impact of this training on surveillance metrics and identify challenges affecting reporting rates. Methods: From February to May 2017, we analysed surveillance data for 13 intervention and 13 comparison counties. An intervention county was defined as one that had received refresher training on DHIS2 while a comparison county was one that had not received training. We evaluated the impact of the training by analysing completeness and timeliness of reporting 15 weeks before and 12 weeks after the training. A chi-square test of independence was used to compare the reporting rates between the two groups. A structured questionnaire was administered to the training participants to assess the challenges affecting surveillance reporting. Results: The average completeness of reporting for the intervention counties increased from 45% to 62%, i.e. by 17 percentage points (95% CI 16.14 -17.86) compared to an increase from 49% to 52% for the comparison group, i.e. by 3 percentage points (95% CI 2.23 -3.77). The timeliness of reporting increased from 30% to 51%, i.e. by 21 percentage points (95% CI 20.16 - 21.84) for the intervention group, compared to an increase from 31% to 38% for the comparison group, i.e.by 7 percentage points (95% CI 6.27-7.73). Major challenges for the low reporting rates included lack of budget support from government, lack of airtime for reporting, health workers strike, health facilities not sending surveillance data, use of wrong denominator to calculate reporting rates and surveillance officers having other competing tasks. Conclusions: Training plays an important role in improving public health surveillance reporting. However, to improve surveillance reporting rates to the desired national targets, other challenges affecting reporting must be identified and addressed accordingly.

scholarly journals Use of technology for public health surveillance reporting: opportunities, challenges and lessons learnt from Kenya

2020 ◽  
Author(s):  
Ian Njeru ◽  
David Kareko ◽  
Ngina Kisangau ◽  
Daniel Langat ◽  
Nzisa Liku ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Comparison Group ◽  
Transition Period ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Percentage Points ◽  
Reporting Rates ◽  
The Impact

Abstract Background: Effective public health surveillance systems are crucial for early detection and response to outbreaks. In 2016, Kenya transitioned its surveillance system from a standalone web-based surveillance system to the more sustainable and integrated District Health Information System 2 (DHIS2). As part of Global Health Security Agenda (GHSA) initiatives in Kenya, training on use of the new system was conducted among surveillance officers. We evaluated the surveillance indicators during the transition period in order to assess the impact of this training on surveillance metrics and identify challenges affecting reporting rates. Methods: From February to May 2017, we analysed surveillance data for 13 intervention and 13 comparison counties. An intervention county was defined as one that had received refresher training on DHIS2 while a comparison county was one that had not received training. We evaluated the impact of the training by analysing completeness and timeliness of reporting 15 weeks before and 12 weeks after the training. A chi-square test of independence was used to compare the reporting rates between the two groups. A structured questionnaire was administered to the training participants to assess the challenges affecting surveillance reporting. Results: The average completeness of reporting for the intervention counties increased from 45% to 62%, i.e. by 17 percentage points (95% CI 16.14 - 17.86) compared to an increase from 49% to 52% for the comparison group, i.e. by 3 percentage points (95% CI 2.23-3.77). The timeliness of reporting increased from 30% to 51%, i.e. by 21 percentage points (95% CI 20.16 - 21.84) for the intervention group, compared to an increase from 31% to 38% for the comparison group, i.e.by 7 percentage points (95% CI 6.27-7.73). Major challenges for the low reporting rates included lack of budget support from government, lack of airtime for reporting, health workers strike, health facilities not sending surveillance data, use of wrong denominator to calculate reporting rates and surveillance officers having other competing tasks. Conclusions: Training plays an important role in improving public health surveillance reporting. However, to improve surveillance reporting rates to the desired national targets, other challenges affecting reporting must be identified and addressed accordingly.

scholarly journals Use of technology for public health surveillance reporting: opportunities, challenges and lessons learnt from Kenya

2020 ◽  
Author(s):  
Ian Njeru ◽  
David Kareko ◽  
Ngina Kisangau ◽  
Daniel Langat ◽  
Nzisa Liku ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Comparison Group ◽  
Transition Period ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Percentage Points ◽  
Reporting Rates ◽  
The Impact

Abstract Background: Effective public health surveillance systems are crucial for early detection and response to outbreaks. In 2016, Kenya transitioned its surveillance system from a standalone web-based surveillance system to the more sustainable and integrated District Health Information System 2 (DHIS2). As part of Global Health Security Agenda (GHSA) initiatives in Kenya, training on use of the new system was conducted among surveillance officers. We evaluated the surveillance indicators during the transition period in order to assess the impact of this training on surveillance metrics and identify challenges affecting reporting rates. Methods: From February to May 2017, we analysed surveillance data for 13 intervention and 13 comparison counties. An intervention county was defined as one that had received refresher training on DHIS2 while a comparison county was one that had not received training. We evaluated the impact of the training by analysing completeness and timeliness of reporting 15 weeks before and 12 weeks after the training. A chi-square test of independence was used to compare the reporting rates between the two groups. A structured questionnaire was administered to the training participants to assess the challenges affecting surveillance reporting. Results: The average completeness of reporting for the intervention counties increased from 45% to 62%, i.e. by 17 percentage points (95% CI 16.14 -17.86) compared to an increase from 49% to 52% for the comparison group, i.e. by 3 percentage points (95% CI 2.23 -3.77). The timeliness of reporting increased from 30% to 51%, i.e. by 21 percentage points (95% CI 20.16 - 21.84) for the intervention group, compared to an increase from 31% to 38% for the comparison group, i.e.by 7 percentage points (95% CI 6.27-7.73). Major challenges for the low reporting rates included lack of budget support from government, lack of airtime for reporting, health workers strike, health facilities not sending surveillance data, use of wrong denominator to calculate reporting rates and surveillance officers having other competing tasks. Conclusions: Training plays an important role in improving public health surveillance reporting. However, to improve surveillance reporting rates to the desired national targets, other challenges affecting reporting must be identified and addressed accordingly.

scholarly journals Evaluation of Measles Surveillance Systems in Ginnir District, Bale Zone, Southeast Ethiopia: A Concurrent Embedded Mixed Quantitative/Qualitative Study 

2020 ◽  
Author(s):  
Falaho Sani ◽  
Mohammed Hasen ◽  
Mohammed Seid ◽  
Nuriya Umer
Keyword(s):  
Public Health ◽  
Qualitative Study ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Health Facilities ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Southeast Ethiopia ◽  
Bale Zone

Abstract Background: Public health surveillance systems should be evaluated periodically to ensure that the problems of public health importance are being monitored efficiently and effectively. Despite the widespread measles outbreak in Ginnir district of Bale zone in 2019, evaluation of measles surveillance system has not been conducted. Therefore, we evaluated the performance of measles surveillance system and its key attributes in Ginnir district, Southeast Ethiopia.Methods: We conducted a concurrent embedded mixed quantitative/qualitative study in August 2019 among 15 health facilities/study units in Ginnir district. Health facilities are selected using lottery method. The qualitative study involved purposively selected 15 key informants. Data were collected using semi-structured questionnaire adapted from Centers for Disease Control and Prevention guidelines for evaluating public health surveillance systems through face-to-face interview and record review. The quantitative findings were analyzed using Microsoft Excel 2016 and summarized by frequency and proportion. The qualitative findings were narrated and summarized based on thematic areas to supplement the quantitative findings.Results: The structure of surveillance data flow was from the community to the respective upper level. Emergency preparedness and response plan was available only at the district level. Completeness of weekly report was 95%, while timeliness was 87%. No regular analysis and interpretations of surveillance data, and the supportive supervision and feedback system was weak. The participation and willingness of surveillance stakeholders in implementation of the system was good. The surveillance system was found to be useful, easy to implement, representative and can accommodate and adapt to changing conditions. Report documentation and quality of data was poor at lower level health facilities. Stability of the system has been challenged by shortage of budget and logistics, staff turnover and lack of update trainings.Conclusions: The surveillance system was acceptable, useful, simple, flexible and representative. Data quality, timeliness and stability of the system were attributes that require improvement. The overall performance of measles surveillance system in the district was poor. Hence, regular analysis of data, preparation and dissemination of epidemiological bulletin, capacity building and regular supervision and feedback are recommended to enhance performance of the system.

Abstract P146: Public Health Surveillance Reveals an Increase in Health Care Utilization for Generic versus Brand-name Warfarin Users

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Jacinthe Leclerc ◽  
Claudia Blais ◽  
Louis Rochette ◽  
Denis Hamel ◽  
Line Guénette ◽  
...  
Keyword(s):  
Public Health ◽  
Health Care ◽  
Health Care Utilization ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Care Utilization ◽  
Brand Name ◽  
Before And After ◽  
The Impact

Background: Even with many direct oral anticoagulant options, brand-name or generic warfarin is still widely used to prevent atherothrombotic events in cardiology. Federal standards regulate bioequivalence of generic vs. brand-name drugs through comparative bioavailability studies but does not regulate clinical equivalence nor tolerability in a “real-life” settings. Through public health surveillance, we have evaluated the impact of the generic warfarin commercialization on health care utilization: emergency room (ER) consultations or hospitalizations. Methods: We used an interrupted time series analysis using the Quebec Integrated Chronic Disease Surveillance System, a surveillance system from the second populous province in Canada (~8.3 million in 2017). Rates of health care utilization for warfarin users (n=280,158) aged ≥ 66 years were calculated for 6-month periods, 5 years before up to 15 years after warfarin commercialization (from January 1996 to January 2016). Periods before and after generic warfarin commercialization were compared by negative binomial segmented regression models for all users with a specific variable for generic or brand-name users. Sensitivity analyses were also conducted. Results: Generic warfarin analogs (n=5) were commercialized from January 2001. There was an approximated mean rate of 1134 ER or hospitalizations for 1000 brand-name and generic users per 6-month period, similar before and after generics commercialization. After generics commercialization, there was an immediate increase in rates of health care utilization for generic (9.9%) vs. brand-name users (0%), a statistically significant difference (9.9% [95% confidence interval: 4.4% to 15.5%], p = 0.0001). Rates of health care utilization remained stable and higher for generic vs. brand-name users throughout the period after generics commercialization. Conclusion: Among generic warfarin users, we observed an increased rates of health care utilization soon after generics commercialization. Risk and survival analysis studies controlling for potential confounders are required to deepen this pharmacovigilance signal as stricter licensing process may be required.

scholarly journals Building Electronic Disease Surveillance Capacity in the Peruvian Navy with SAGES

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Shraddha Patel ◽  
Miles Stewart ◽  
Martina Siwek
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Open Source ◽  
Open Source Software ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Resource Limited ◽  
Reporting Rates

ObjectiveTo introduce SMS-based data collection into the Peruvian Navy’s public health surveillance system for increased reporting rates and timeliness, particularly from remote areas, as well as improve capabilities for analysis of surveillance data by decision makers.IntroductionIn the past 15 years, public health surveillance has undergone a revolution driven by advances in information technology (IT) with vast improvements in the collection, analysis, visualization, and reporting of health data. Mobile technologies and open source software have played a key role in advancing surveillance techniques, particularly in resource-limited settings. Johns Hopkins University Applied Physics Laboratory (JHU/APL) is an internationally recognized leader in the area of electronic disease surveillance. In addition to the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) used by several state and local jurisdictions and the CDC in the U.S., JHU/APL has also developed the Suite for Automated Global Electronic bioSurveillance (SAGES). SAGES is a collection of modular, open-source software tools designed to meet the challenges of electronic disease surveillance in resource-limited settings.JHU/APL is working with the Peruvian Navy health system to improve their electronic disease surveillance capabilities. The Peruvian Navy currently uses a SAGES-based system called Alerta DISAMAR that was implemented several years ago in an effort supported by the Armed Forces Health Surveillance Branch, and in collaboration with the Naval Medical Research Unit No. 6 (NAMRU-6). The system uses both web-based and IVR-based (interactive voice response) data collection from several Navy health facilities in Peru. For the present effort, JHU/APL is implementing a new SMS-based data collection capability for the Peruvian Navy.MethodsJHU/APL is engaged with the Peruvian Navy Health System to upgrade the existing SAGES-based Alerta DISAMAR surveillance system which relies on remote data collection using IVR (interactive voice recording) technology, with a SAGES-based system that uses SMS (short message service) text messages for remote data collection. Based on Peruvian Navy requirements, JHU/APL created mobile data entry forms for Android smartphones using the SAGES mCollect application. SAGES mCollect is built using Open Data Kit open source tools along with added features such as 128-bit encryption and quality checks.The JHU/APL team engages closely with end users and other stakeholders to determine system requirements and to deploy the system, as well as to train end users and the system administrators who will need to maintain the system once it is deployed. The JHU/APL team, consisting of both information technology and public health expertise, conduct a country-level capabilities and needs assessment to address design considerations and operational end user requirements. This assessment takes into account the requirements and objectives of the Peruvian Navy, while keeping in mind infrastructure, cost, and personnel constraints. A pilot test of SMS-based data collection is currently underway with 10 health clinics within the Navy.ResultsMany challenges exist when implementing electronic disease surveillance tools in resource-limited settings, but using a tailored approach to implementation in which specific needs, constraints, and expectations are identified with stakeholders helps increase the overall adoption and sustainment of the system. JHU/APL believes SMS-based data collection will be more sustainable than IVR-based data collection for the Peruvian Navy.ConclusionsJHU/APL is deploying a SAGES-based electronic disease surveillance system for the Peruvian Navy that has great potential to increase reporting rates from its health facilities as well as improve data quality and timeliness, thus resulting in greater awareness and enhanced public health decision making. 

Residential address errors in public health surveillance data: A description and analysis of the impact on geocoding

2010 ◽  
Vol 1 (2-3) ◽  
pp. 163-168 ◽  
Author(s):  
Kate Zinszer ◽  
Christian Jauvin ◽  
Aman Verma ◽  
Lucie Bedard ◽  
Robert Allard ◽  
...  
Keyword(s):  
Public Health ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Residential Address ◽  
Health Surveillance Data ◽  
The Impact

scholarly journals A COVID ‐19‐ready public health surveillance system: The FDA 's Sentinel System

2021 ◽  
Author(s):  
Noelle M. Cocoros ◽  
Candace C. Fuller ◽  
Sruthi Adimadhyam ◽  
Robert Ball ◽  
Jeffrey S. Brown ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Public Health Surveillance System
Sign in / Sign up

Export Citation Format

Share Document