Agreement between cause of death assignment by computer-coded verbal autopsy methods and physician coding of verbal autopsy interviews in South Africa

被引：0

作者：

Groenewald, Pam ^{[1
,8
]}

Thomas, Jason ^{[2
]}

Clark, Samuel J. ^{[2
]}

Morof, Diane ^{[3
,4
]}

Joubert, Jane D. ^{[1
]}

Kabudula, Chodziwadziwa ^{[5
]}

Li, Zehang ^{[6
]}

Bradshaw, Debbie ^{[1
,7
]}

机构：

[1] South African Med Res Council, Burden Dis Res Unit, Cape Town, South Africa

[2] Ohio State Univ, Dept Sociol, Columbus, OH USA

[3] CDCP, Div Global HIV & TB, Durban, South Africa

[4] US Publ Hlth Serv Commissioned Corps, Rockville, MD USA

[5] Univ Witwatersrand, MRC Wits Rural Publ Hlth & Hlth Transit Res Unit A, Johannesburg, South Africa

[6] Univ Calif Santa Cruz, Dept Stat, Santa Cruz, CA USA

[7] Univ Cape Town, Sch Publ Hlth, Div Publ Hlth Med, Cape Town, South Africa

[8] South African Med Res Council, Francie van Zijl Dr, ZA-7501 Cape Town, South Africa

来源：

GLOBAL HEALTH ACTION | 2023年 / 16卷 / 01期

关键词：

Physician-coded; computer-coded; verbal autopsy; agreement; MORTALITY;

D O I：

10.1080/16549716.2023.2285105

中图分类号：

R1 [预防医学、卫生学];

学科分类号：

1004 ; 120402 ;

摘要：

BackgroundThe South African national cause of death validation (NCODV 2017/18) project collected a national sample of verbal autopsies (VA) with cause of death (COD) assignment by physician-coded VA (PCVA) and computer-coded VA (CCVA).ObjectiveThe performance of three CCVA algorithms (InterVA-5, InSilicoVA and Tariff 2.0) in assigning a COD was compared with PCVA (reference standard).MethodsSeven performance metrics assessed individual and population level agreement of COD assignment by age, sex and place of death subgroups. Positive predictive value (PPV), sensitivity, overall agreement, kappa, and chance corrected concordance (CCC) assessed individual level agreement. Cause-specific mortality fraction (CSMF) accuracy and Spearman's rank correlation assessed population level agreement.ResultsA total of 5386 VA records were analysed. PCVA and CCVAs all identified HIV/AIDS as the leading COD. CCVA PPV and sensitivity, based on confidence intervals, were comparable except for HIV/AIDS, TB, maternal, diabetes mellitus, other cancers, and some injuries. CCVAs performed well for identifying perinatal deaths, road traffic accidents, suicide and homicide but poorly for pneumonia, other infectious diseases and renal failure. Overall agreement between CCVAs and PCVA for the top single cause (48.2-51.6) indicated comparable weak agreement between methods. Overall agreement, for the top three causes showed moderate agreement for InterVA (70.9) and InSilicoVA (73.8). Agreement based on kappa (-0.05-0.49)and CCC (0.06-0.43) was weak to none for all algorithms and groups. CCVAs had moderate to strong agreement for CSMF accuracy, with InterVA-5 highest for neonates (0.90), Tariff 2.0 highest for adults (0.89) and males (0.84), and InSilicoVA highest for females (0.88), elders (0.83) and out-of-facility deaths (0.85). Rank correlation indicated moderate agreement for adults (0.75-0.79).ConclusionsWhilst CCVAs identified HIV/AIDS as the leading COD, consistent with PCVA, there is scope for improving the algorithms for use in South Africa.

引用

页数：13

共 37 条

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