DHIMS2 data quality over time.

<div><p>Effective decision-making for malaria prevention and control depends on timely, accurate, and appropriately analyzed and interpreted data. Poor quality data reported into national health management information systems (HMIS) prevent managers at the district level from planning ef...

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Bibliographic Details
Main Author:	Amos Asiedu (4996946) (author)
Other Authors:	Rachel A. Haws (21499756) (author), Wahjib Mohammed (8923664) (author), Joseph Boye-Doe (21499759) (author), Charles Agblanya (21499762) (author), Raphael Ntumy (21499765) (author), Keziah Malm (3408257) (author), Paul Boateng (17912666) (author), Gladys Tetteh (21499768) (author), Lolade Oseni (3841621) (author)
Published:	2025
Subjects:	Biotechnology Science Policy Information Systems not elsewhere classified decreased error rate 0001 ), 77 reported using data third coaching visit primary care facilities improve malaria surveillance service data quality improve data quality ghana &# 8217 national hmis data malaria data recording 231 health facilities second coaching visit coaching visit series data use increased used hmis data data coaching health facilities interpreted data coaching visits malaria programs malaria prevention data completeness reporting increased supportive supervision prevent managers point increase november 2021 managers visualized documented examples district level control depends appropriately analyzed analyzed reports 16 regions 05 ). 001 ); 001 ). 001 ))
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DHIMS2 data quality over time.

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