Figures & Tables
Figures
- FIGURE 1.
Number of Facilities in Tanzania Using the EIR (top) and Percentage of Facilities Using the EIR (bottom)
Abbreviation: EIR, electronic immunization registry.
- FIGURE 2.
Facility Average Percentage of Active Weeks of EIR Use by District, Tanzania, 2016–2018
Abbreviation: EIR, electronic immunization registry.
- FIGURE 3.
Number of Facilities in Southern Province, Zambia Using the EIR (top) and Percentage of Facilities Using the EIR (bottom)
Abbreviation: EIR, electronic immunization registry.
- FIGURE 4.
Facility Average Percentage of Active Weeks of EIR Use by District, Southern Province, Zambia, 2017–2018
Abbreviation: EIR, electronic immunization registry.
Tables
- TABLE 1.
Hypotheses on Impact of Facility Characteristics on EIR Use Aligned to PRISM Framework
PRISM Framework Determinant Variable Hypotheses Organizational Paperless reporting If a facility transitions to paperless reporting (only using the EIR as the official system), it will be more likely to use the EIR. Facility volume If a facility has a larger patient population, HCWs may have a busier daily patient load, therefore less time for data entry and will be less likely to use the EIR.
OR, if a facility has a larger patient population, HCWs may see more value in using the EIR to manage their patient population and will be more likely to use the EIR.Facility type If a facility is a hospital or health center, it may have more resources (e.g., equipment, skilled HCWs) compared to a dispensary and may be more likely to use the EIR. Ownership type If a facility is public, HCWs may feel greater ownership of the decision to adopt the EIR and/or feel more accountable to use the EIR than in private facilities and thus may be more likely to use the EIR. Distance to district health office If a facility is located closer to the district health office, it will be more likely to receive in-person support from district health officials. Training strategy (Tanzania only) If a facility received the second training strategy (i.e., district staff provided additional support and training), it will be more likely to use the EIR than facilities who received the first training strategy, which relied on BID project staff. Number of immunization sessions per week If a facility provides more immunization sessions per week, they will be more likely to enter data into the EIR each week. Technical Primary power source If a facility has a consistent electricity connection, it will be more likely to use the EIR. Internet connectivity If a facility has a consistent internet connection, it will be more likely to use the EIR. Behavioral Number of HCWs trained per facility If a facility has more HCWs trained, it will be more likely to use the EIR. Weeks since EIR introduction As the length of time since EIR introduction increases, facilities will be less likely to use the EIR. Abbreviations: EIR, electronic immunization registry; HCW, health care worker; PRISM, Performance of Routine Information System Management.
- TABLE 2.
Description of the Datasets Extracted From the Tanzania Immunization Registry and Zambia Electronic Immunization Registry
Tanzania Zambia Arusha Region Kilimanjaro Region Tanga Region Southern Province Number of districts 6 6 8 13 Number of facilities 283 292 330 551 (static and outreach sites) Number of unique individuals 137,130 35,084 89,740 96,617 Number of records 1,606,776 206,871 671,562 1,323,264 Date range of EIR records (including back-entered data) January 2015 – April 2018 January 2015 – April 2018 January 2015 – April 2018 January 2015 – August 2018 Date range of EIR introduction June 2016 – March 2017 December 2017 – February 2018 July 2017 – August 2017 July 2017 – March 2018 Abbreviation: EIR, electronic immunization registry.
- TABLE 3.
Description of the Facility Characteristics Included in the Regression Models for EIR Use, Tanzania and Zambia
Tanzania Zambia Arusha Kilimanjaro Tanga All Regions Southern
ProvinceNumber of districts 6 6 8 20 13 Number of facilities 278 285 326 889 282 Organizational Paper-based records 100.0% 100.0% 89.9% 96.3% 100.0% Paperless records 0.0% 0.0% 10.1% 3.7% 0.0% Number of monthly vaccine doses delivered, mean (SD) 341.3 (529.1) 206.2 (246.5) 323.3 (314.3) 288.8 (372.5) – Annual child health clinic attendance, mean (SD) – – – – 5351.7 (4220.5) Facility type Dispensary 78.4% 79.3% 86.5% 81.7% 0.0% Health center 16.9% 15.8% 0.0% 10.3% 76.1% Hospital 4.7% 4.9% 2.5% 3.9% 1.8% Hospital affiliated center 0.0% 0.0% 0.0% 0.0% 4.4% Missing 0.0% 0.0% 11.0% 4.0% 17.6% Ownership type Private 32.4% 24.6% 12.0% 22.4% – Public 65.1% 70.5% 85.6% 74.4% – Missing 2.5% 4.9% 2.5% 3.3% – Distance to DHO, km, mean (SD) 37.2 (31.0) 61.8 (171.5) 23.4 (14.4) 35.9 (68.8) 46.7 (39.7) On-the-job training by BID Initiative staff 71.6% 0.0% 0.0% 22.4% – Additional support and training by district staff 28.4% 100.0% 100.0% 77.6% – Number of immunization sessions per week 1 or more – – – – 77.4% Less than 1 – – – – 11.0% Missing information – – – – 11.6% Technical Primary power source Grid 36.7% 79.3% 0.0% 36.9% 43.6% Solar 31.3% 7.7% 0.0% 12.3% 1.8% None 4.0% 0.0% 0.0% 1.2% 51.1% Missing 28.1% 13.0% 100% 49.6% 3.5% Internet connectivity Yes 60.8% – – – – No 6.8% – – – – Missing 32.4% – – – – Behavioral Number of HCWs trained per facility, mean (SD) 2.2 (0.9) 2.1 (1.2) 2.5 (1.1) 2.3 (1.1) – Abbreviations: DHO, district health office; EIR, electronic immunization registry; HCW, health care worker; SD standard deviation.
Variable Estimate (odds ratio) Robust Standard Error P-Value Organizational Paperless (compared to using parallel systems)a 2.72 0.83 .001 Facility Type (compared to dispensary) Health centera 1.61 0.33 .02 Hospitala 3.82 1.13 <.001 Behavioral Number of HCWs traineda 1.35 0.09 <.001 Weeks since EIR introductiona 0.98 <0.01 <.001 District (Region)b Tanga CC (Tanga)a 2.89 1.07 .004 Karatu DC (Arusha)a 2.45 0.81 .007 Mkinga DC (Tanga) 1.83 0.64 .09 Pangani DC (Tanga) 1.56 0.54 .20 Longido DC (Arusha) 1.53 0.65 .32 Ngorongoro DC (Arusha) 1.53 0.56 .24 Handeni TC (Tanga) 1.32 0.70 .60 Korogwe TC (Tanga) 1.19 0.62 .74 Siha DC (Kilimanjaro) 1.12 0.50 .80 Meru DC (Arusha) 1.11 0.43 .79 Handeni DC (Tanga) 1.05 0.46 .92 Monduli DC (Arusha) 1.00 0.54 .99 Rombo DC (Kilimanjaro) 0.99 0.34 .97 Arusha DC (Arusha) 0.90 0.45 .84 Bumbuli DC (Tanga) 0.82 0.31 .61 Korogwe DC (Tanga) 0.70 0.23 .30 Lushoto DC (Tanga) 0.65 0.22 .20 Moshi MC (Kilimanjaro) 0.62 0.24 .22 Hai DC (Kilimanjaro) 0.58 0.20 .18 Mwanga DC (Kilimanjaro) 0.53 0.20 .10 Same DC (Kilimanjaro)a 0.51 0.17 .05 Muheza DC (Tanga)a 0.49 0.17 .04 Kilindi DC (Tanga)a 0.35 0.13 .005 Moshi DC (Kilimanjaro)a 0.29 0.09 <.001 Abbreviations: CC, city council; DC, district council; EIR, electronic immunization registry; HCW, health care worker; MC, municipal council; TC, town council.
↵a Statistically significant at alpha=.05 level.
↵b Compared to Arusha city council, which was selected as it was the pilot implementation district and contains the capital and largest city in Arusha region.
Variable Estimate (odds ratio) Robust Standard Error P-Value Organizational Less than 1 immunization day/week 0.82 0.31 .60 Distance from DHO, compared to 1st quartile 2nd quartilea 0.46 0.15 .015 3rd quartilea 0.41 0.14 .007 4th quartilea 0.32 0.11 .001 Behavioral Weeks since EIR introductiona 0.88 <0.01 <.001 Districtb Zimba 1.16 0.50 .74 Kazungula 0.97 0.48 .95 Mazabuka 0.91 0.40 .83 Livingstone 0.73 0.40 .57 Gwembea 0.33 0.17 .03 Kalomoa 0.30 0.12 .003 Namwalaa 0.19 0.08 <.001 Sinazongwea 0.14 0.08 .001 Pembaa 0.10 0.04 <.001 Monzea 0.08 0.03 <.001 Chikankataa 0.05 0.03 <.001 Siavongaa 0.03 0.03 <.001
In this issue
Statistics from Altmetric.com
Jump to section
Related Articles
Cited By...
- Impact of Electronic Immunization Registries and Electronic Logistics Management Information Systems in four Low-and Middle-Income Countries: Guinea, Honduras, Rwanda, and Tanzania
- Design, Development, and Deployment of an Electronic Immunization Registry: Experiences From Vietnam, Tanzania, and Zambia
- Behavioral Determinants of Routine Health Information System Data Use in Senegal: A Qualitative Inquiry Based on the Integrated Behavioral Model