Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Health management information systems (HMIS) produce large amounts of data about health service provision and population health, and provide opportunities for data-based decision-making in decentralized health systems. Yet the data are little-used locally. A well-defined approach to district-level decision-making using health data would help better meet the needs of the local population. In this second of four papers on district decision-making for health in low-income settings, our aim was to explore ways in which district administrators and health managers in low- and lower-middle-income countries use health data to make decisions, to describe the decision-making tools they used and identify challenges encountered when using these tools. A systematic literature review, following PRISMA guidelines, was undertaken. Experts were consulted about key sources of information. A search strategy was developed for 14 online databases of peer reviewed and grey literature. The resources were screened independently by two reviewers using pre-defined inclusion criteria. The 14 papers included were assessed for the quality of reported evidence and a descriptive evidence synthesis of the review findings was undertaken. We found 12 examples of tools to assist district-level decision-making, all of which included two key stages-identification of priorities, and development of an action plan to address them. Of those tools with more steps, four included steps to review or monitor the action plan agreed, suggesting the use of HMIS data. In eight papers HMIS data were used for prioritization. Challenges to decision-making processes fell into three main categories: the availability and quality of health and health facility data; human dynamics and financial constraints. Our findings suggest that evidence is available about a limited range of processes that include the use of data for decision-making at district level. Standardization and pre-testing in diverse settings would increase the potential that these tools could be used more widely.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009221 | PMC |
http://dx.doi.org/10.1093/heapol/czv124 | DOI Listing |
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