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10.1016/j.ijmedinf.2021.104413 http://scihub22266oqcxt.onion/10.1016/j.ijmedinf.2021.104413 33652259!ä!33652259 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 332.4 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 332.4 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 332.4 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Med+Inform 2021 ; 149 (ä): 104413 Nephropedia Template TP {{tp|p=33652259|t=2021. Using a low-cost, real-time electronic immunization registry in Pakistan to demonstrate utility of data for immunization programs and evidence-based decision making to achieve SDG-3: Insights from analysis of Big Data on vaccines |pdf=|usr=}}{{33652259}} gab.com Text Using a low-cost, real-time electronic immunization registry in Pakistan to demonstrate utility of data for immunization programs and evidence-based decision making to achieve SDG-3: Insights from analysis of Big Data on vaccines JO: Int J Med Inform http://www.kidney.de/pget.php?&tw=1&pmid=33652259 #FOAvip BACKGROUND: Despite the proliferation of digital interventions such as Electronic Immunization Registries (EIR), currently, there is little evidence regarding the use of EIR data to improve immunization outcomes in resource-constrained settings. To achieve the Sustainable Development Goal (SDG) of ensuring healthy lives and well-being for all ages, particularly for newborns and children under the age of 5 (goal 3b), it is essential to generate and use quality data for evidence-based decision making to overcome barriers inherent in immunization systems. In Pakistan, only 66 % of children receive all basic vaccinations, and in Sindh province, the number is even lower at 49 %. In 2012, IRD developed and piloted Zindagi Mehfooz (Safe Life; ZM) ElR, an Android-based platform that records and analyses individual-level child data in real-time. In 2017 in collaboration with Expanded Programme for Immunization (EPI) Sindh, ZM was scaled-up across the entire Sindh province and is currently being used by 2521 government vaccinators in 1539 basic health facilities, serving >48 million population. OBJECTIVE: The study aims to demonstrate how big immunization data from the ZM-EIR is being leveraged in Sindh, Pakistan for actionable decision making via three use cases (a) improving performance management of vaccinators to increase geographical coverage, (b) quantifying the impact of provincial accelerated outreach activities, and (c) examining the impact of the COVID-19 pandemic on routine immunization coverage to help devise a tailored approach for future efforts. METHODS: From October 2017 to April 2020, more than 2.9 million children and 0.9 million women have been enrolled, and more than 22 million immunization events have been recorded in the ZM-EIR. We extracted de-identified data from ZM-EIR for January 1, 2019 - April 20, 2020, period. Given the needs of each use case, monthly and daily indicators on vaccinator performance (attendance and compliance), daily immunization visits, and the number of antigens administered were calculated. Geo-coordinate data of antigen administration was extracted and displayed on geographic maps using QGIS. All generated reports were shared at fixed frequency with various stakeholders, such as partners at EPI-Sindh, for utilization in decision making and informing policy. RESULT: Our use-cases demonstrate the use of EIR data for data-driven decision making. From January - December 2019, the monthly monitoring of program indicators helped increase the vaccinator attendance from 44% to 88%, while an 85 % increase in geographical coverage was observed in a polio-endemic super high-risk union council (SHRUC) in Karachi. The analysis of daily average antigens administered during accelerated outreach efforts (AOE) as compared to routine activities showed an increase in average daily Pentavalent-3, Measles-1, and Measles-2 vaccines administered by 103%, 154%, and 180% respectively. These findings helped decide to continue the accelerated effort in high-risk areas (compared to the entire province) rather than discontinuing the activity due to high costs. During COVID-19 lockdown, the daily average number of child immunizations reduced from 16,649 to 4335 per day, a decline of 74% compared to 6 months preceding COVID-19 lockdown. ZM-EIR data is currently helping to shape the planning and implementation of critical strategies to mitigate the impact of the COVID-19 pandemic. CONCLUSION: The big data for vaccines generated through EIRs is a powerful tool to monitor immunization work-force and ensure chronically missed communities are identified and covered through targeted strategies. Geospatial data availability and analysis is changing the way EPI review meetings occur with stakeholders, taking data-driven decisions for better planning and resource allocation. In the fight against COVID-19 pandemic, as governments gradually begin to shift from containing the outbreak to strategizing a plan for sustaining the essential health services, the countries that will emerge most successful are likely the ones who can best use technology and real-time data for targeted efforts. Twit Text FOAVip Using a low-cost, real-time electronic immunization registry in Pakistan to demonstrate utility of data for immunization programs and evidence-based decision making to achieve SDG-3: Insights from analysis of Big Data on vaccines ????Int J Med Inform http://www.kidney.de/pget.php?&tw=1&pmid=33652259 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33652259 #FOAvip English Wikipedia <ref>{{Cite pmid|33652259}}</ref> Using a low-cost, real-time electronic immunization registry in Pakistan to demonstrate utility of data for immunization programs and evidence-based decision making to achieve SDG-3: Insights from analysis of Big Data on vaccines #MMPMID33652259 Siddiqi DA; Abdullah S; Dharma VK; Shah MT; Akhter MA; Habib A; Khan AJ; Chandir S Int J Med Inform 2021[May]; 149 (ä): 104413 PMID33652259show ga BACKGROUND: Despite the proliferation of digital interventions such as Electronic Immunization Registries (EIR), currently, there is little evidence regarding the use of EIR data to improve immunization outcomes in resource-constrained settings. To achieve the Sustainable Development Goal (SDG) of ensuring healthy lives and well-being for all ages, particularly for newborns and children under the age of 5 (goal 3b), it is essential to generate and use quality data for evidence-based decision making to overcome barriers inherent in immunization systems. In Pakistan, only 66 % of children receive all basic vaccinations, and in Sindh province, the number is even lower at 49 %. In 2012, IRD developed and piloted Zindagi Mehfooz (Safe Life; ZM) ElR, an Android-based platform that records and analyses individual-level child data in real-time. In 2017 in collaboration with Expanded Programme for Immunization (EPI) Sindh, ZM was scaled-up across the entire Sindh province and is currently being used by 2521 government vaccinators in 1539 basic health facilities, serving >48 million population. OBJECTIVE: The study aims to demonstrate how big immunization data from the ZM-EIR is being leveraged in Sindh, Pakistan for actionable decision making via three use cases (a) improving performance management of vaccinators to increase geographical coverage, (b) quantifying the impact of provincial accelerated outreach activities, and (c) examining the impact of the COVID-19 pandemic on routine immunization coverage to help devise a tailored approach for future efforts. METHODS: From October 2017 to April 2020, more than 2.9 million children and 0.9 million women have been enrolled, and more than 22 million immunization events have been recorded in the ZM-EIR. We extracted de-identified data from ZM-EIR for January 1, 2019 - April 20, 2020, period. Given the needs of each use case, monthly and daily indicators on vaccinator performance (attendance and compliance), daily immunization visits, and the number of antigens administered were calculated. Geo-coordinate data of antigen administration was extracted and displayed on geographic maps using QGIS. All generated reports were shared at fixed frequency with various stakeholders, such as partners at EPI-Sindh, for utilization in decision making and informing policy. RESULT: Our use-cases demonstrate the use of EIR data for data-driven decision making. From January - December 2019, the monthly monitoring of program indicators helped increase the vaccinator attendance from 44% to 88%, while an 85 % increase in geographical coverage was observed in a polio-endemic super high-risk union council (SHRUC) in Karachi. The analysis of daily average antigens administered during accelerated outreach efforts (AOE) as compared to routine activities showed an increase in average daily Pentavalent-3, Measles-1, and Measles-2 vaccines administered by 103%, 154%, and 180% respectively. These findings helped decide to continue the accelerated effort in high-risk areas (compared to the entire province) rather than discontinuing the activity due to high costs. During COVID-19 lockdown, the daily average number of child immunizations reduced from 16,649 to 4335 per day, a decline of 74% compared to 6 months preceding COVID-19 lockdown. ZM-EIR data is currently helping to shape the planning and implementation of critical strategies to mitigate the impact of the COVID-19 pandemic. CONCLUSION: The big data for vaccines generated through EIRs is a powerful tool to monitor immunization work-force and ensure chronically missed communities are identified and covered through targeted strategies. Geospatial data availability and analysis is changing the way EPI review meetings occur with stakeholders, taking data-driven decisions for better planning and resource allocation. In the fight against COVID-19 pandemic, as governments gradually begin to shift from containing the outbreak to strategizing a plan for sustaining the essential health services, the countries that will emerge most successful are likely the ones who can best use technology and real-time data for targeted efforts. |*COVID-19[MESH] |*Vaccines[MESH] |Big Data[MESH] |Child[MESH] |Communicable Disease Control[MESH] |Decision Making[MESH] |Electronics[MESH] |Female[MESH] |Humans[MESH] |Immunization[MESH] |Immunization Programs[MESH] |Infant, Newborn[MESH] |Pakistan[MESH] |Pandemics[MESH] |Registries[MESH] |SARS-CoV-2[MESH] |Sustainable Development[MESH]Using a low-cost, real-time electronic immunization registry in Pakist(epmc).pdf DeepDyve Pubget Overpricing