National assessment of data quality and associated systems-level factors in Malawi

Richael O’Hagan, Melissa Hewett-Marx, Karen E. Finnegan, Patrick Naphini, Kumbukani Ng’ambi, Kingsley Laija, Emily B Wilson, Lois Park, Sautso Wachepa, Joseph Smith, Lewis Gombwa, Amos Misomali, Tiope Mleme, Simeon Yosefe

Research output: Contribution to journalArticle

Abstract

Background: Routine health data can guide health systems improvements, but poor quality of these data hinders use. To address concerns about data quality in Malawi, the Ministry of Health and National Statistical Office conducted a data quality assessment (DQA) in July 2016 to identify systems-level factors that could be improved. Methods: We used 2-stage stratified random sampling methods to select health centers and hospitals under Ministry of Health auspices, included those managed by faith-based entities, for this DQA. Dispensaries, village clinics, police and military facilities, tertiary-level hospitals, and private facilities were excluded. We reviewed client registers and monthly reports to verify availability, completeness, and accuracy of data in 4 service areas: antenatal care (ANC), family planning, HIV testing and counseling, and acute respiratory infection (ARI). We also conducted interviews with facility and district personnel to assess health management information system (HMIS) functioning and systems-level factors that may be associated with data quality. We compared systems and quality factors by facility characteristics using 2-sample t tests with Welch’s approximation, and calculated verification ratios comparing total entries in registers to totals from summarized reports. Results: We selected 16 hospitals (of 113 total in Malawi), 90 health centers (of 466), and 16 district health offices (of 28) in 16 of Malawi’s 28 districts. Nearly all registers were available and complete in health centers and district hospitals, but data quality varied across service areas; median verification ratios comparing register and report totals at health centers ranged from 0.78 (interquartile range [IQR]: 0.25, 1.07) for ARI and 0.99 (IQR: 0.82, 1.36) for family planning to 1.00 (IQR: 0.96, 1.00) for HIV testing and counseling and 1.00 (IQR: 0.80, 1.23) for ANC. More than half (60%) of facilities reported receiving a documented supervisory visit for HMIS in the prior 6 months. A recent supervision visit was associated with better availability of data (P=.05), but regular district- or central-level supervision was not. Use of data by the facility to track performance toward targets was associated with both improved availability (P=.04) and completeness of data (P=.02). Half of facilities had a full-time statistical clerk, but their presence did not improve the availability or completeness of data (P=.39 and P=.69, respectively). Conclusion: Findings indicate both strengths and weaknesses in Malawi’s HMIS performance, with key weaknesses including infrequent data quality checks and unreliable supervision. Efforts to strengthen HMIS in low- and middle-income countries should be informed by similar assessments.

Original languageEnglish (US)
Pages (from-to)367-381
Number of pages15
JournalGlobal Health Science and Practice
Volume5
Issue number3
DOIs
StatePublished - Sep 1 2017

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Malawi
Management Information Systems
Health Information Systems
Health
Prenatal Care
Family Planning Services
Respiratory Tract Infections
Counseling
Military Facilities
HIV
Data Accuracy
District Hospitals
Police
Quality Improvement
Tertiary Care Centers
Interviews

ASJC Scopus subject areas

  • Health Policy
  • Public Health, Environmental and Occupational Health

Cite this

National assessment of data quality and associated systems-level factors in Malawi. / O’Hagan, Richael; Hewett-Marx, Melissa; Finnegan, Karen E.; Naphini, Patrick; Ng’ambi, Kumbukani; Laija, Kingsley; Wilson, Emily B; Park, Lois; Wachepa, Sautso; Smith, Joseph; Gombwa, Lewis; Misomali, Amos; Mleme, Tiope; Yosefe, Simeon.

In: Global Health Science and Practice, Vol. 5, No. 3, 01.09.2017, p. 367-381.

Research output: Contribution to journalArticle

O’Hagan, R, Hewett-Marx, M, Finnegan, KE, Naphini, P, Ng’ambi, K, Laija, K, Wilson, EB, Park, L, Wachepa, S, Smith, J, Gombwa, L, Misomali, A, Mleme, T & Yosefe, S 2017, 'National assessment of data quality and associated systems-level factors in Malawi', Global Health Science and Practice, vol. 5, no. 3, pp. 367-381. https://doi.org/10.9745/GHSP-D-17-00177
O’Hagan, Richael ; Hewett-Marx, Melissa ; Finnegan, Karen E. ; Naphini, Patrick ; Ng’ambi, Kumbukani ; Laija, Kingsley ; Wilson, Emily B ; Park, Lois ; Wachepa, Sautso ; Smith, Joseph ; Gombwa, Lewis ; Misomali, Amos ; Mleme, Tiope ; Yosefe, Simeon. / National assessment of data quality and associated systems-level factors in Malawi. In: Global Health Science and Practice. 2017 ; Vol. 5, No. 3. pp. 367-381.
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abstract = "Background: Routine health data can guide health systems improvements, but poor quality of these data hinders use. To address concerns about data quality in Malawi, the Ministry of Health and National Statistical Office conducted a data quality assessment (DQA) in July 2016 to identify systems-level factors that could be improved. Methods: We used 2-stage stratified random sampling methods to select health centers and hospitals under Ministry of Health auspices, included those managed by faith-based entities, for this DQA. Dispensaries, village clinics, police and military facilities, tertiary-level hospitals, and private facilities were excluded. We reviewed client registers and monthly reports to verify availability, completeness, and accuracy of data in 4 service areas: antenatal care (ANC), family planning, HIV testing and counseling, and acute respiratory infection (ARI). We also conducted interviews with facility and district personnel to assess health management information system (HMIS) functioning and systems-level factors that may be associated with data quality. We compared systems and quality factors by facility characteristics using 2-sample t tests with Welch’s approximation, and calculated verification ratios comparing total entries in registers to totals from summarized reports. Results: We selected 16 hospitals (of 113 total in Malawi), 90 health centers (of 466), and 16 district health offices (of 28) in 16 of Malawi’s 28 districts. Nearly all registers were available and complete in health centers and district hospitals, but data quality varied across service areas; median verification ratios comparing register and report totals at health centers ranged from 0.78 (interquartile range [IQR]: 0.25, 1.07) for ARI and 0.99 (IQR: 0.82, 1.36) for family planning to 1.00 (IQR: 0.96, 1.00) for HIV testing and counseling and 1.00 (IQR: 0.80, 1.23) for ANC. More than half (60{\%}) of facilities reported receiving a documented supervisory visit for HMIS in the prior 6 months. A recent supervision visit was associated with better availability of data (P=.05), but regular district- or central-level supervision was not. Use of data by the facility to track performance toward targets was associated with both improved availability (P=.04) and completeness of data (P=.02). Half of facilities had a full-time statistical clerk, but their presence did not improve the availability or completeness of data (P=.39 and P=.69, respectively). Conclusion: Findings indicate both strengths and weaknesses in Malawi’s HMIS performance, with key weaknesses including infrequent data quality checks and unreliable supervision. Efforts to strengthen HMIS in low- and middle-income countries should be informed by similar assessments.",
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T1 - National assessment of data quality and associated systems-level factors in Malawi

AU - O’Hagan, Richael

AU - Hewett-Marx, Melissa

AU - Finnegan, Karen E.

AU - Naphini, Patrick

AU - Ng’ambi, Kumbukani

AU - Laija, Kingsley

AU - Wilson, Emily B

AU - Park, Lois

AU - Wachepa, Sautso

AU - Smith, Joseph

AU - Gombwa, Lewis

AU - Misomali, Amos

AU - Mleme, Tiope

AU - Yosefe, Simeon

PY - 2017/9/1

Y1 - 2017/9/1

N2 - Background: Routine health data can guide health systems improvements, but poor quality of these data hinders use. To address concerns about data quality in Malawi, the Ministry of Health and National Statistical Office conducted a data quality assessment (DQA) in July 2016 to identify systems-level factors that could be improved. Methods: We used 2-stage stratified random sampling methods to select health centers and hospitals under Ministry of Health auspices, included those managed by faith-based entities, for this DQA. Dispensaries, village clinics, police and military facilities, tertiary-level hospitals, and private facilities were excluded. We reviewed client registers and monthly reports to verify availability, completeness, and accuracy of data in 4 service areas: antenatal care (ANC), family planning, HIV testing and counseling, and acute respiratory infection (ARI). We also conducted interviews with facility and district personnel to assess health management information system (HMIS) functioning and systems-level factors that may be associated with data quality. We compared systems and quality factors by facility characteristics using 2-sample t tests with Welch’s approximation, and calculated verification ratios comparing total entries in registers to totals from summarized reports. Results: We selected 16 hospitals (of 113 total in Malawi), 90 health centers (of 466), and 16 district health offices (of 28) in 16 of Malawi’s 28 districts. Nearly all registers were available and complete in health centers and district hospitals, but data quality varied across service areas; median verification ratios comparing register and report totals at health centers ranged from 0.78 (interquartile range [IQR]: 0.25, 1.07) for ARI and 0.99 (IQR: 0.82, 1.36) for family planning to 1.00 (IQR: 0.96, 1.00) for HIV testing and counseling and 1.00 (IQR: 0.80, 1.23) for ANC. More than half (60%) of facilities reported receiving a documented supervisory visit for HMIS in the prior 6 months. A recent supervision visit was associated with better availability of data (P=.05), but regular district- or central-level supervision was not. Use of data by the facility to track performance toward targets was associated with both improved availability (P=.04) and completeness of data (P=.02). Half of facilities had a full-time statistical clerk, but their presence did not improve the availability or completeness of data (P=.39 and P=.69, respectively). Conclusion: Findings indicate both strengths and weaknesses in Malawi’s HMIS performance, with key weaknesses including infrequent data quality checks and unreliable supervision. Efforts to strengthen HMIS in low- and middle-income countries should be informed by similar assessments.

AB - Background: Routine health data can guide health systems improvements, but poor quality of these data hinders use. To address concerns about data quality in Malawi, the Ministry of Health and National Statistical Office conducted a data quality assessment (DQA) in July 2016 to identify systems-level factors that could be improved. Methods: We used 2-stage stratified random sampling methods to select health centers and hospitals under Ministry of Health auspices, included those managed by faith-based entities, for this DQA. Dispensaries, village clinics, police and military facilities, tertiary-level hospitals, and private facilities were excluded. We reviewed client registers and monthly reports to verify availability, completeness, and accuracy of data in 4 service areas: antenatal care (ANC), family planning, HIV testing and counseling, and acute respiratory infection (ARI). We also conducted interviews with facility and district personnel to assess health management information system (HMIS) functioning and systems-level factors that may be associated with data quality. We compared systems and quality factors by facility characteristics using 2-sample t tests with Welch’s approximation, and calculated verification ratios comparing total entries in registers to totals from summarized reports. Results: We selected 16 hospitals (of 113 total in Malawi), 90 health centers (of 466), and 16 district health offices (of 28) in 16 of Malawi’s 28 districts. Nearly all registers were available and complete in health centers and district hospitals, but data quality varied across service areas; median verification ratios comparing register and report totals at health centers ranged from 0.78 (interquartile range [IQR]: 0.25, 1.07) for ARI and 0.99 (IQR: 0.82, 1.36) for family planning to 1.00 (IQR: 0.96, 1.00) for HIV testing and counseling and 1.00 (IQR: 0.80, 1.23) for ANC. More than half (60%) of facilities reported receiving a documented supervisory visit for HMIS in the prior 6 months. A recent supervision visit was associated with better availability of data (P=.05), but regular district- or central-level supervision was not. Use of data by the facility to track performance toward targets was associated with both improved availability (P=.04) and completeness of data (P=.02). Half of facilities had a full-time statistical clerk, but their presence did not improve the availability or completeness of data (P=.39 and P=.69, respectively). Conclusion: Findings indicate both strengths and weaknesses in Malawi’s HMIS performance, with key weaknesses including infrequent data quality checks and unreliable supervision. Efforts to strengthen HMIS in low- and middle-income countries should be informed by similar assessments.

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