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Coverage of routine reporting on malaria parasitological testing in Kenya, 2015–2016

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Coverage of routine reporting on malaria parasitological testing in Kenya, 2015–2016. / Maina, Joseph K.; Macharia, Peter M.; Ouma, Paul O. et al.
In: Global Health Action, Vol. 10, No. 1, 1413266, 31.12.2017.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Maina, JK, Macharia, PM, Ouma, PO, Snow, RW & Okiro, EA 2017, 'Coverage of routine reporting on malaria parasitological testing in Kenya, 2015–2016', Global Health Action, vol. 10, no. 1, 1413266. https://doi.org/10.1080/16549716.2017.1413266

APA

Maina, J. K., Macharia, P. M., Ouma, P. O., Snow, R. W., & Okiro, E. A. (2017). Coverage of routine reporting on malaria parasitological testing in Kenya, 2015–2016. Global Health Action, 10(1), Article 1413266. https://doi.org/10.1080/16549716.2017.1413266

Vancouver

Maina JK, Macharia PM, Ouma PO, Snow RW, Okiro EA. Coverage of routine reporting on malaria parasitological testing in Kenya, 2015–2016. Global Health Action. 2017 Dec 31;10(1):1413266. Epub 2017 Dec 20. doi: 10.1080/16549716.2017.1413266

Author

Maina, Joseph K. ; Macharia, Peter M. ; Ouma, Paul O. et al. / Coverage of routine reporting on malaria parasitological testing in Kenya, 2015–2016. In: Global Health Action. 2017 ; Vol. 10, No. 1.

Bibtex

@article{6bec0df585a04307882e3ee290055b26,
title = "Coverage of routine reporting on malaria parasitological testing in Kenya, 2015–2016",
abstract = "Background: Following the launch of District Health Information System 2 across facilities in Kenya, more health facilities are now capable of carrying out malaria parasitological testing and reporting data as part of routine health information systems, improving the potential value of routine data for accurate and timely tracking of rapidly changing disease epidemiology at fine spatial resolutions. Objectives: This study evaluates the current coverage and completeness of reported malaria parasitological testing data in DHIS2 specifically looking at patterns in geographic coverage of public health facilities in Kenya. Methods: Monthly facility level data on malaria parasitological testing were extracted from Kenya DHIS2 between November 2015 and October 2016. DHIS2 public facilities were matched to a geo-coded master facility list to obtain coordinates. Coverage was defined as the geographic distribution of facilities reporting any data by region. Completeness of reporting was defined as the percentage of facilities reporting any data for the whole 12-month period or for 3, 6 and 9 months. Results: Public health facilities were 5,933 (59%) of 10,090 extracted. Fifty-nine per Cent of the public facilities did not report any data while 36, 29 and 22% facilities had data reported at least 3, 6 and 9 months, respectively. Only 8% of public facilities had data reported for every month. There were proportionately more hospitals (86%) than health centres (76%) and dispensaries/clinics (30%) reporting. There were significant geographic variations in reporting rates. Counties along the malaria endemic coast had the lowest reporting rate with only 1% of facilities reporting consistently for 12 months. Conclusion: Current coverage and completeness of reporting of malaria parasitological diagnosis across Kenya{\textquoteright}s public health system remains poor. The usefulness of routine data to improve our understanding of sub-national heterogeneity across Kenya would require significant improvements to the consistency and coverage of data captured by DHIS2.",
keywords = "DHIS2, geographic coverage, malaria risk mapping, Routine data",
author = "Maina, {Joseph K.} and Macharia, {Peter M.} and Ouma, {Paul O.} and Snow, {Robert W.} and Okiro, {Emelda A.}",
year = "2017",
month = dec,
day = "31",
doi = "10.1080/16549716.2017.1413266",
language = "English",
volume = "10",
journal = "Global Health Action",
issn = "1654-9716",
publisher = "Taylor & Francis",
number = "1",

}

RIS

TY - JOUR

T1 - Coverage of routine reporting on malaria parasitological testing in Kenya, 2015–2016

AU - Maina, Joseph K.

AU - Macharia, Peter M.

AU - Ouma, Paul O.

AU - Snow, Robert W.

AU - Okiro, Emelda A.

PY - 2017/12/31

Y1 - 2017/12/31

N2 - Background: Following the launch of District Health Information System 2 across facilities in Kenya, more health facilities are now capable of carrying out malaria parasitological testing and reporting data as part of routine health information systems, improving the potential value of routine data for accurate and timely tracking of rapidly changing disease epidemiology at fine spatial resolutions. Objectives: This study evaluates the current coverage and completeness of reported malaria parasitological testing data in DHIS2 specifically looking at patterns in geographic coverage of public health facilities in Kenya. Methods: Monthly facility level data on malaria parasitological testing were extracted from Kenya DHIS2 between November 2015 and October 2016. DHIS2 public facilities were matched to a geo-coded master facility list to obtain coordinates. Coverage was defined as the geographic distribution of facilities reporting any data by region. Completeness of reporting was defined as the percentage of facilities reporting any data for the whole 12-month period or for 3, 6 and 9 months. Results: Public health facilities were 5,933 (59%) of 10,090 extracted. Fifty-nine per Cent of the public facilities did not report any data while 36, 29 and 22% facilities had data reported at least 3, 6 and 9 months, respectively. Only 8% of public facilities had data reported for every month. There were proportionately more hospitals (86%) than health centres (76%) and dispensaries/clinics (30%) reporting. There were significant geographic variations in reporting rates. Counties along the malaria endemic coast had the lowest reporting rate with only 1% of facilities reporting consistently for 12 months. Conclusion: Current coverage and completeness of reporting of malaria parasitological diagnosis across Kenya’s public health system remains poor. The usefulness of routine data to improve our understanding of sub-national heterogeneity across Kenya would require significant improvements to the consistency and coverage of data captured by DHIS2.

AB - Background: Following the launch of District Health Information System 2 across facilities in Kenya, more health facilities are now capable of carrying out malaria parasitological testing and reporting data as part of routine health information systems, improving the potential value of routine data for accurate and timely tracking of rapidly changing disease epidemiology at fine spatial resolutions. Objectives: This study evaluates the current coverage and completeness of reported malaria parasitological testing data in DHIS2 specifically looking at patterns in geographic coverage of public health facilities in Kenya. Methods: Monthly facility level data on malaria parasitological testing were extracted from Kenya DHIS2 between November 2015 and October 2016. DHIS2 public facilities were matched to a geo-coded master facility list to obtain coordinates. Coverage was defined as the geographic distribution of facilities reporting any data by region. Completeness of reporting was defined as the percentage of facilities reporting any data for the whole 12-month period or for 3, 6 and 9 months. Results: Public health facilities were 5,933 (59%) of 10,090 extracted. Fifty-nine per Cent of the public facilities did not report any data while 36, 29 and 22% facilities had data reported at least 3, 6 and 9 months, respectively. Only 8% of public facilities had data reported for every month. There were proportionately more hospitals (86%) than health centres (76%) and dispensaries/clinics (30%) reporting. There were significant geographic variations in reporting rates. Counties along the malaria endemic coast had the lowest reporting rate with only 1% of facilities reporting consistently for 12 months. Conclusion: Current coverage and completeness of reporting of malaria parasitological diagnosis across Kenya’s public health system remains poor. The usefulness of routine data to improve our understanding of sub-national heterogeneity across Kenya would require significant improvements to the consistency and coverage of data captured by DHIS2.

KW - DHIS2

KW - geographic coverage

KW - malaria risk mapping

KW - Routine data

U2 - 10.1080/16549716.2017.1413266

DO - 10.1080/16549716.2017.1413266

M3 - Journal article

C2 - 29261450

AN - SCOPUS:85044613837

VL - 10

JO - Global Health Action

JF - Global Health Action

SN - 1654-9716

IS - 1

M1 - 1413266

ER -