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Glob Health Action. 2014 Jul 31;7:24859. doi: 10.3402/gha.v7.24859. eCollection 2014.

Assessing the ability of health information systems in hospitals to support evidence-informed decisions in Kenya.

Author information

1
Ministry of Health, Government of Kenya, Nairobi, Kenya; The Health Services, Implementation Research and Clinical Excellence (SIRCLE) Collaboration, Nairobi, Kenya; Ekihuba@kemri-wellcome.org.
2
KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
3
Ministry of Health, Government of Kenya, Nairobi, Kenya; The Health Services, Implementation Research and Clinical Excellence (SIRCLE) Collaboration, Nairobi, Kenya.
4
The Health Services, Implementation Research and Clinical Excellence (SIRCLE) Collaboration, Nairobi, Kenya; Department of Pharmacy and Phamacognosy, School of Pharmacy, University of Nairobi, Nairobi, Kenya.
5
The Health Services, Implementation Research and Clinical Excellence (SIRCLE) Collaboration, Nairobi, Kenya; Department of Obstetrics and Gynecology, School of Medicine, University of Nairobi, Nairobi, Kenya.
6
Ministry of Health, Government of Kenya, Nairobi, Kenya.
7
The Health Services, Implementation Research and Clinical Excellence (SIRCLE) Collaboration, Nairobi, Kenya; KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya; Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Department of Paediatrics, University of Oxford, Oxford, United Kingdom.

Abstract

BACKGROUND:

Hospital management information systems (HMIS) is a key component of national health information systems (HIS), and actions required of hospital management to support information generation in Kenya are articulated in specific policy documents. We conducted an evaluation of core functions of data generation and reporting within hospitals in Kenya to facilitate interpretation of national reports and to provide guidance on key areas requiring improvement to support data use in decision making.

DESIGN:

The survey was a cross-sectional, cluster sample study conducted in 22 hospitals in Kenya. The statistical analysis was descriptive with adjustment for clustering.

RESULTS:

Most of the HMIS departments complied with formal guidance to develop departmental plans. However, only a few (3/22) had carried out a data quality audit in the 12 months prior to the survey. On average 3% (range 1-8%) of the total hospital income was allocated to the HMIS departments. About half of the records officer positions were filled and about half (13/22) of hospitals had implemented some form of electronic health record largely focused on improving patient billing and not linked to the district HIS. Completeness of manual patient registers varied, being 90% (95% CI 80.1-99.3%), 75.8% (95% CI 68.7-82.8%), and 58% (95% CI 50.4-65.1%) in maternal child health clinic, maternity, and pediatric wards, respectively. Vital events notification rates were low with 25.7, 42.6, and 71.3% of neonatal deaths, infant deaths, and live births recorded, respectively. Routine hospital reports suggested slight over-reporting of live births and under-reporting of fresh stillbirths and neonatal deaths.

CONCLUSIONS:

Study findings indicate that the HMIS does not deliver quality data. Significant constraints exist in data quality assurance, supervisory support, data infrastructure in respect to information and communications technology application, human resources, financial resources, and integration.

KEYWORDS:

data quality; health information system; hospital management information system

PMID:
25084834
PMCID:
PMC4119289
[Indexed for MEDLINE]
Free PMC Article
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