| Literature DB >> 26077600 |
Hisahiro Ishijima1,2, Martin Mapunda3, Mathew Mndeme4, Felix Sukums5, Violeth Solomon Mlay6.
Abstract
BACKGROUND: The establishment of a functional information system for human resource for health (HRH) was one of the major challenges for the Tanzanian health sector. In 2008, the Ministry of Health and Social Welfare developed the HRH Strategic Plan, in which establishment of computerized information systems were one of the strategic objectives. In response to this objective, the Ministry developed two information systems, namely the Human Resource for Health Information System (HRHIS) and the Training Institution Information System (TIIS), to capture information from both the public and private sectors. CASE DESCRIPTION: The national rollout of HRHIS and TIIS was carried out in four phases during a 6 year period between 2009 and 2014. Together with other activities, the rollout process included conducting system operation training and data utilization training for evidence-based planning, development and management of HRH and social welfare workers and health training institutions. DISCUSSION: HRHIS was rolled out in all 25 regions of the Tanzanian mainland, including 171 districts, and TIIS was rolled out in all 154 health training institutions and universities. Information is captured from both the private and public health sectors with high-data coverage. The authors identified several key factors for the achievements such as using local experts for developing the systems, involvement of system users, positive attitudes among users, focusing on routine work of the system users and provision of operations and data utilization trainings. However, several challenges were also identified such as getting a consensus on sustainable HR information systems among stakeholders, difficulty in obtaining baseline HRH information, inadequate computer skills and unsatisfactory infrastructure for information and communication technology. We learned that detailed situation analysis and understanding of the reality on the ground helped to reduce the "design-reality gap" and contributed to establishing user-friendly systems and to improve sustainability of the systems.Entities:
Mesh:
Year: 2015 PMID: 26077600 PMCID: PMC4477301 DOI: 10.1186/s12960-015-0043-1
Source DB: PubMed Journal: Hum Resour Health ISSN: 1478-4491
Fig. 1National rollout process for HRHIS and TIIS
Fig. 2The HRHIS dashboard showing its modules
Fig. 3The TIIS dashboard showing its modules
Data elements collected for HRHIS and TIIS employees module
| Sq no. | Data elements | Sq no. | Data elements |
|---|---|---|---|
| 1 | First name | 17 | Profession |
| 2 | Middle name | 18 | Present designation |
| 3 | Surname | 19 | Superlative substantive position |
| 4 | Date of birth | 20 | Department |
| 5 | Sex | 21 | Salary scale |
| 6 | Marital status | 22 | Monthly basic salary |
| 7 | Nationality | 23 | Date of first appointment |
| 8 | Religion | 24 | Date of confirmation |
| 9 | Basic education level | 25 | Date of last promotion |
| 10 | Profession education level | 26 | Employer |
| 11 | Number of children/dependents | 27 | Employment status |
| 12 | District of domicile | 28 | Registered disability |
| 13 | Check number | 29 | Contacts of employee |
| 14 | Employer’s file number | 30 | Next of kin |
| 15 | Registration number | 31 | Relationship to next of kin |
| 16 | Terms of employment | 32 | Contacts of next of kin |
Fig. 4Relations among different organizations and HRHIS/TIIS
Fig. 5Supportive supervision of HRHIS/TIIS
Result of pre-post-assessment of data utilization training
| DUT by regions | Mean | Std. dev. | 95 % CI |
|
| Effect size | Δ score | ||
|---|---|---|---|---|---|---|---|---|---|
| Low | High | ||||||||
| Arusha | Pre | 36.48 | 4.00 | 35.0 | 37.9 | −7.762 | <0.001 | 1.15 | |.80| ≦ large |
| Post | 41.09 | 3.00 | 40.0 | 42.1 | |||||
| Dar es Salaam | Pre | 66.42 | 13.67 | 62.0 | 70.7 | −5.291 | <0.001 | 0.80 | |.80| ≦ large |
| Post | 77.40 | 9.35 | 74.4 | 80.3 | |||||
| Dodoma | Pre | 66.10 | 13.08 | 59.7 | 72.4 | −3.195 | <0.005 | 0.83 | |.80| ≦ large |
| Post | 76.94 | 8.87 | 72.6 | 81.2 | |||||
| Iringa | Pre | 63.72 | 10.57 | 59.6 | 67.7 | −4.837 | <0.005 | 0.86 | |.80| ≦ large |
| Post | 72.82 | 7.51 | 69.9 | 75.6 | |||||
| Kagera | Pre | 71.09 | 10.19 | 67.9 | 74.1 | −9.752 | <0.001 | 1.20 | |.80| ≦ large |
| Post | 83.27 | 6.94 | 81.1 | 85.3 | |||||
| Kilimanjaro | Pre | 45.32 | 29.46 | 38.3 | 52.3 | −3.829 | <0.001 | 0.56 | |.50| < medium < |.80| |
| Post | 61.80 | 25.08 | 55.8 | 67.7 | |||||
| Kigoma | Pre | 68.80 | 12.71 | 38.3 | 52.3 | −3.829 | <0.001 | 0.81 | |.80| ≦ large |
| Post | 79.06 | 9.60 | 55.8 | 67.7 | |||||
| Lindi | Pre | 64.34 | 9.52 | 61.2 | 67.4 | −5.801 | <0.001 | 0.89 | |.80| ≦ large |
| Post | 72.76 | 7.71 | 70.2 | 75.3 | |||||
| Manyara | Pre | 74.96 | 10.71 | 70.7 | 79.2 | −6.460 | <0.001 | 0.67 | |.50| < medium < |.80| |
| Post | 82.11 | 6.80 | 79.4 | 84.8 | |||||
| Mara | Pre | 66.32 | 11.98 | 61.9 | 70.7 | −3.549 | <0.001 | 0.51 | |.50| < medium < |.80| |
| Post | 72.38 | 10.60 | 68.4 | 76.2 | |||||
| Mbeya | Pre | 67.86 | 9.48 | 64.3 | 71.4 | −4.648 | <0.001 | 0.80 | |.80| ≦ large |
| Post | 75.40 | 6.37 | 73.0 | 77.7 | |||||
| Morogoro | Pre | 54.15 | 23.48 | 46.6 | 61.6 | −10.263 | <0.001 | 0.30 | |.20| ≦ small < |.50| |
| Post | 61.17 | 23.91 | 53.5 | 68.8 | |||||
| Mtwara | Pre | 70.00 | 10.53 | 64.3 | 75.6 | −2.953 | <0.010 | 0.69 | |.50| < medium < |.80| |
| Post | 77.25 | 6.48 | 73.7 | 80.7 | |||||
| Mwanza | Pre | 67.76 | 13.85 | 64.3 | 71.1 | −6.639 | <0.001 | 0.56 | |.50| < medium < |.80| |
| Post | 75.52 | 10.68 | 72.9 | 78.1 | |||||
| Rukwa | Pre | 65.20 | 7.57 | 61.6 | 68.7 | −2.972 | <0.010 | 0.93 | |.80| ≦ large |
| Post | 72.20 | 9.40 | 67.8 | 76.5 | |||||
| Ruvuma | Pre | 68.75 | 9.26 | 63.8 | 73.6 | −2.226 | 0.041 | 0.57 | |.50| < medium < |.80| |
| Post | 74.00 | 9.35 | 69.0 | 78.9 | |||||
| Shinyanga | Pre | 68.48 | 11.95 | 63.9 | 73 | −8.705 | <0.001 | 1.20 | |.80| ≦ large |
| Post | 82.75 | 7.27 | 79.9 | 85.5 | |||||
| Singida | Pre | 70.10 | 10.53 | 66.0 | 74.1 | −8.428 | <0.001 | 1.45 | |.80| ≦ large |
| Post | 85.34 | 8.26 | 82.1 | 88.4 | |||||
| Tabora | Pre | NA | NA | NA | NA | NA | NA | NA | NA |
| Post | NA | NA | NA | NA | |||||
| Tanga | Pre | 60.70 | 13.97 | 53.5 | 67.8 | −4.428 | <0.001 | 0.86 | |.80| ≦ large |
| Post | 72.76 | 6.84 | 69.2 | 76.2 | |||||
Fig. 6HRHIS data coverage
Fig. 7TIIS data coverage