Improving quality of medical certification of causes of death in health facilities in Tanzania 2014-2019.

Causes of death Civil Registration and vital statistics Continuing professional development DHIS2 Data quality assessment ICD-10 Medical certification Mortality data Start-up mortality list Tanzania eHealth

Journal

BMC health services research
ISSN: 1472-6963
Titre abrégé: BMC Health Serv Res
Pays: England
ID NLM: 101088677

Informations de publication

Date de publication:
13 Sep 2021
Historique:
received: 11 02 2021
accepted: 18 02 2021
entrez: 13 9 2021
pubmed: 14 9 2021
medline: 15 9 2021
Statut: epublish

Résumé

Monitoring medically certified causes of death is essential to shape national health policies, track progress to Sustainable Development Goals, and gauge responses to epidemic and pandemic disease. The combination of electronic health information systems with new methods for data quality monitoring can facilitate quality assessments and help target quality improvement. Since 2015, Tanzania has been upgrading its Civil Registration and Vital Statistics system including efforts to improve the availability and quality of mortality data. We used a computer application (ANACONDA v4.01) to assess the quality of medical certification of cause of death (MCCD) and ICD-10 coding for the underlying cause of death for 155,461 deaths from health facilities from 2014 to 2018. From 2018 to 2019, we continued quality analysis for 2690 deaths in one large administrative region 9 months before, and 9 months following MCCD quality improvement interventions. Interventions addressed governance, training, process, and practice. We assessed changes in the levels, distributions, and nature of unusable and insufficiently specified codes, and how these influenced estimates of the leading causes of death. 9.7% of expected annual deaths in Tanzania obtained a medically certified cause of death. Of these, 52% of MCCD ICD-10 codes were usable for health policy and planning, with no significant improvement over 5 years. Of certified deaths, 25% had unusable codes, 17% had insufficiently specified codes, and 6% were undetermined causes. Comparing the before and after intervention periods in one Region, codes usable for public health policy purposes improved from 48 to 65% within 1 year and the resulting distortions in the top twenty cause-specific mortality fractions due to unusable causes reduced from 27.4 to 13.5%. Data from less than 5% of annual deaths in Tanzania are usable for informing policy. For deaths with medical certification, errors were prevalent in almost half. This constrains capacity to monitor the 15 SDG indicators that require cause-specific mortality. Sustainable quality assurance mechanisms and interventions can result in rapid improvements in the quality of medically certified causes of death. ANACONDA provides an effective means for evaluation of such changes and helps target interventions to remaining weaknesses.

Sections du résumé

BACKGROUND BACKGROUND
Monitoring medically certified causes of death is essential to shape national health policies, track progress to Sustainable Development Goals, and gauge responses to epidemic and pandemic disease. The combination of electronic health information systems with new methods for data quality monitoring can facilitate quality assessments and help target quality improvement. Since 2015, Tanzania has been upgrading its Civil Registration and Vital Statistics system including efforts to improve the availability and quality of mortality data.
METHODS METHODS
We used a computer application (ANACONDA v4.01) to assess the quality of medical certification of cause of death (MCCD) and ICD-10 coding for the underlying cause of death for 155,461 deaths from health facilities from 2014 to 2018. From 2018 to 2019, we continued quality analysis for 2690 deaths in one large administrative region 9 months before, and 9 months following MCCD quality improvement interventions. Interventions addressed governance, training, process, and practice. We assessed changes in the levels, distributions, and nature of unusable and insufficiently specified codes, and how these influenced estimates of the leading causes of death.
RESULTS RESULTS
9.7% of expected annual deaths in Tanzania obtained a medically certified cause of death. Of these, 52% of MCCD ICD-10 codes were usable for health policy and planning, with no significant improvement over 5 years. Of certified deaths, 25% had unusable codes, 17% had insufficiently specified codes, and 6% were undetermined causes. Comparing the before and after intervention periods in one Region, codes usable for public health policy purposes improved from 48 to 65% within 1 year and the resulting distortions in the top twenty cause-specific mortality fractions due to unusable causes reduced from 27.4 to 13.5%.
CONCLUSION CONCLUSIONS
Data from less than 5% of annual deaths in Tanzania are usable for informing policy. For deaths with medical certification, errors were prevalent in almost half. This constrains capacity to monitor the 15 SDG indicators that require cause-specific mortality. Sustainable quality assurance mechanisms and interventions can result in rapid improvements in the quality of medically certified causes of death. ANACONDA provides an effective means for evaluation of such changes and helps target interventions to remaining weaknesses.

Identifiants

pubmed: 34511104
doi: 10.1186/s12913-021-06189-7
pii: 10.1186/s12913-021-06189-7
pmc: PMC8436444
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

214

Informations de copyright

© 2021. The Author(s).

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Auteurs

Trust Nyondo (T)

Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania.

Gisbert Msigwa (G)

Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania.
Bloomberg Philanthropies Data for Health Initiative, Vital Strategies, New York, NY, USA.

Daniel Cobos (D)

Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland.

Gregory Kabadi (G)

Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania.
Bloomberg Philanthropies Data for Health Initiative, Vital Strategies, New York, NY, USA.

Tumaniel Macha (T)

Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania.

Emilian Karugendo (E)

National Bureau of Statistics, Dodoma, Tanzania.

Joyce Mugasa (J)

Muhimbili National Hospital, Dar es Salaam, Tanzania.

Geofrey Semu (G)

Muhimbili National Hospital, Dar es Salaam, Tanzania.

Francis Levira (F)

Ifakara Health Institute, Dar es Salaam, Tanzania.

Carmen Sant Fruchtman (CS)

Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland.

James Mwanza (J)

Bloomberg Philanthropies Data for Health Initiative, Vital Strategies, New York, NY, USA.

Isaac Lyatuu (I)

Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland.
Ifakara Health Institute, Dar es Salaam, Tanzania.
Africa Academy for Public Health, Dar es Salaam, Tanzania.

Martin Bratschi (M)

Bloomberg Philanthropies Data for Health Initiative, Vital Strategies, New York, NY, USA.

Claud J Kumalija (CJ)

Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania.

Philip Setel (P)

Bloomberg Philanthropies Data for Health Initiative, Vital Strategies, New York, NY, USA.

Don de Savigny (D)

Bloomberg Philanthropies Data for Health Initiative, Vital Strategies, New York, NY, USA. d.desavigny@swisstph.ch.
Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland. d.desavigny@swisstph.ch.

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