National Assessment of Data Quality and Associated Systems-Level Factors in Malawi

O’Hagan, Richael; Marx, Melissa A.; Finnegan, Karen; Naphini, Patrick; Ng'ambi, Kumbukani; Laija, K.; Wilson, Emily; Park, Lois; Wachepa, Sautso; Smith, Joseph M.; Gombwa, Lewis; Misomali, Amos; Mleme, Tiope; Yosefe, Simeon

doi:10.9745/ghsp-d-17-00177

Cited by 49 publications

(68 citation statements)

References 12 publications

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“…We found that the cost per mobile interview was $10.56 (or 7655 Kwacha), while the cost per in-person interview was $25.48 (18,473 Kwacha). One of the largest drivers of cost in the mobile interview phase stemmed from the airtime used.…”

Section: Feasibilitymentioning

confidence: 81%

“…While health systems usually collect routine data on FP provision that could be used for an ISA, a common challenge is the poor quality of this data at the national and subnational levels [18][19][20]. Another option is collecting primary data on program implementation from each of these health system actors, but the traditional, in-person method can be labor and costintensive.…”

Section: Introductionmentioning

confidence: 99%

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Testing the validity and feasibility of using a mobile phone-based method to assess the strength of implementation of family planning programs in Malawi

Pattnaik

Mohan

Chipokosa³

et al. 2020

BMC Health Serv Res

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Background: To effectively deliver on proposed objectives, it is vital that practitioners, policymakers, and other stakeholders are able to clearly understand how strongly their large-scale program is being implemented. This study sought to test the feasibility, cost-effectiveness, and validity of a phone-based method as an innovative and cost-efficient approach to assessing program implementation strength (through an Implementation Strength Assessment-ISA), alternative to the traditional in-person field methods. Methods: We conducted 701 mobile phone and 356 in-person interviews with facility in-Charges and two types of community health workers who provide family planning services in the Dowa and Ntcheu districts in Malawi. Responses received via the phone interview were validated through in-person review of records and inspections. Sensitivity and specificity were calculated to determine validity. Results: Most indicators at the health facility and community health worker levels were above a 70% threshold for sensitivity. However, there were fewer indicators that met this threshold for specificity. The primary reason for lower specificity was due to poor recordkeeping. Collecting data via mobile phone was found to be feasible and twice as cost-efficient as collecting the same data via in-person inspections. Conclusions: The rapid increase in mobile phone ownership and network availability in lower income countries could offer an alternative, cost-effective avenue to collect data for a better understanding of program implementation. Through rigorous assessment, this study found that using mobile phones could be a low-cost alternative to collect data on health system delivery of services, especially in places where routine data quality is poor and traditional, in-person methods are costly.

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Section: Feasibilitymentioning

confidence: 81%

Section: Introductionmentioning

confidence: 99%

Testing the validity and feasibility of using a mobile phone-based method to assess the strength of implementation of family planning programs in Malawi

Pattnaik

Mohan

Chipokosa³

et al. 2020

BMC Health Serv Res

Self Cite

View full text Add to dashboard Cite

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“…3 Despite substantial investment of time and resources in the DHS programme worldwide, the quality of data arising from these surveys has been variable. 4 Few research studies have attempted to uncover the underlying reasons for this variation 5 and, to date, no randomised trials (the gold standard for research) have been done to improve DHS methodology.…”

Section: Enhancing Routine Surveillance To Improve Stillbirth Datamentioning

confidence: 99%

Enhancing routine surveillance to improve stillbirth data

McClure

2020

The Lancet Global Health

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“…Studies in Sub-Saharan Africa (SSA) have reported challenges with data quality, including poor utilization of HMIS tools, incomplete recording, inconsistency, inaccuracy and untimely reporting [1,[5][6][7][8][9][10][11][12][13]. The concerns about the quality of routine information have undermined data utilization for decision-making in the health sector [9,10,14,15]. Challenges in data quality in SSA are compounded by human, health system (HS) and infrastructure factors [1,2,16].…”

Section: Introductionmentioning

confidence: 99%

“…Limited infrastructure and means to transmit reports from one level to another add more complexity [5,14,[17][18][19]. Data quality assessments need to address these attributes and processes to establish valid conclusions that foster solution-focused thinking [15,16].…”

Section: Introductionmentioning

confidence: 99%

Data quality of the routine health management information system at the primary healthcare facility and district levels in Tanzania

Rumisha

Lyimo

Mremi

et al. 2020

Preprint

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Background Effective planning for disease prevention and control requires accurate, adequately-analysed, interpreted and communicated data. This study assessed the quality of routine Health Management Information System (HMIS) data at healthcare facility (HF) and district levels in Tanzania. Methods HMIS tools used at primary health care facilities (dispensary, health centre, hospital) and district office were reviewed to assess their availability, completeness, and accuracy of collected data. The assessment involved seven health service areas namely, Outpatient department, Inpatient department, Antenatal care, Family Planning, Post-natal care, Labour and Delivery and Provider-initiated Testing and Counselling. Results A total of 115 HFs in 11 districts were assessed. Registers (availability rate = 91.1%; interquartile range (IQR):66.7%-100%) and report forms (86.9%; IQR:62.2%-100%) were the most utilized tools. There was a limited use of tally-sheets (77.8%; IQR:35.6%-100%). Tools availability at dispensary was 91.1%, health-centre 82.2% and hospital 77.8%, and was poor in urban districts. The availability rate at the district level was 65% (IQR:48%-75%). Reports were highly over-represented in comparison to registers’ records, with large differences observed at HF phase of the data journey and more profound in hospitals. Tool availability and data quality varied by service-areas, indicators, facility level, and districts, however, with a remarkable improvement over the years. Conclusion There are high variations and improvements in the tool utilisation and data accuracy at facility and district levels. The routine HMIS is weak and data at district level inaccurately reflects what is available at the HFs. These results highlight the need to design tailored and inter-service strategies for improving data quality.

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National Assessment of Data Quality and Associated Systems-Level Factors in Malawi

Cited by 49 publications

References 12 publications

Testing the validity and feasibility of using a mobile phone-based method to assess the strength of implementation of family planning programs in Malawi

Testing the validity and feasibility of using a mobile phone-based method to assess the strength of implementation of family planning programs in Malawi

Enhancing routine surveillance to improve stillbirth data

Data quality of the routine health management information system at the primary healthcare facility and district levels in Tanzania

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