Identifying delays in healthcare seeking and provision: The Three Delays-in-Healthcare and mortality among infants and children aged 1–59 months

Delays in illness recognition, healthcare seeking, and in the provision of appropriate clinical care are common in resource-limited settings. Our objective was to determine the frequency of delays in the “Three Delays-in-Healthcare”, and factors associated with delays, among deceased infants and children in seven countries with high childhood mortality. We conducted a retrospective, descriptive study using data from verbal autopsies and medical records for infants and children aged 1–59 months who died between December 2016 and February 2022 in six sites in sub-Saharan Africa and one in South Asia (Bangladesh) and were enrolled in Child Health and Mortality Prevention Surveillance (CHAMPS). Delays in 1) illness recognition in the home/decision to seek care, 2) transportation to healthcare facilities, and 3) the receipt of clinical care in healthcare facilities were categorized according to the “Three Delays-in-Healthcare”. Comparisons in factors associated with delays were made using Chi-square testing. Information was available for 1,326 deaths among infants and under 5 children. The majority had at least one identified delay (n = 854, 64%). Waiting >72 hours after illness recognition to seek health care (n = 422, 32%) was the most common delay. Challenges in obtaining transportation occurred infrequently when seeking care (n = 51, 4%). In healthcare facilities, prescribed medications were sometimes unavailable (n = 102, 8%). Deceased children aged 12–59 months experienced more delay than infants aged 1–11 months (68% vs. 61%, P = 0.018). Delays in seeking clinical care were common among deceased infants and children. Additional study to assess the frequency of delays in seeking clinical care and its provision among children who survive is warranted

Unexplained chronic liver disease in Ethiopia: a cross-sectional study

Background Hepatitis B virus (HBV) infection is assumed to be the major cause of chronic liver disease (CLD) in sub-Saharan Africa. The contribution of other aetiological causes of CLD is less well documented and hence opportunities to modulate other potential risk factors are being lost. The aims of this study were to explore the aetiological spectrum of CLD in eastern Ethiopia and to identify plausible underlying risk factors for its development. Methods A cross-sectional study was undertaken between April 2015 and April 2016 in two public hospitals in Harar, eastern Ethiopia. The study population comprised of consenting adults with clinical and radiological evidence of chronic liver disease. The baseline evaluation included: (i) a semi-structured interview designed to obtain information about the ingestion of alcohol, herbal medicines and local recreational drugs such as khat (Catha edulis); (ii) clinical examination; (iii) extensive laboratory testing; and, (iv) abdominal ultrasonography. Results One-hundred-and-fifty patients with CLD (men 72.0%; median age 30 [interquartile range 25–40] years) were included. CLD was attributed to chronic HBV infection in 55 (36.7%) individuals; other aetiological agents were identified in a further 12 (8.0%). No aetiological factors were identified in the remaining 83 (55.3%) patients. The overall prevalence of daily khat use was 78.0%, while alcohol abuse, defined as > 20 g/day in women and > 30 g/day in men, was rare (2.0%). Histological features of toxic liver injury were observed in a subset of patients with unexplained liver injury who underwent liver biopsy. Conclusion The aetiology of CLD in eastern Ethiopia is largely unexplained. The widespread use of khat in the region, together with histopathological findings indicating toxic liver injury, suggests an association which warrants further investigation

Development and evaluation of a simple treatment eligibility score (HEPSANET) to decentralise hepatitis B care in Africa: a cross-sectional study.

Hepatitis B virus (HBV) elimination requires expanding and decentralising HBV care services. However, peripheral health facilities lack access to diagnostic tools to assess eligibility for antiviral therapy. Through the Hepatitis B in Africa Collaborative Network (HEPSANET), we aimed to develop and evaluate a score using tests generally available at lower-level facilities, to simplify the evaluation of antiviral therapy eligibility in people living with HBV. We surveyed the availability of clinical and laboratory parameters across different health-care levels in sub-Saharan Africa. We used data from the HEPSANET dataset, the largest cross-sectional dataset of treatment-naive people living with HBV in sub-Saharan Africa, to derive and validate the score. Participants from this dataset were included in the analysis if they were aged 18 years or older and had liver fibrosis stages determined by a liver stiffness measurement or liver histopathology. Participants with co-infections or metabolic disorders were excluded. We allocated participants to the derivation and validation sets by geographical site. In the derivation set, we used stepwise logistic regression to identify the best performing parameters for identifying participants that met the 2017 European Association for the Study of the Liver (EASL) criteria. Regression coefficients were converted into integer points to construct simplified algorithms for different health-care levels. In the validation set, we estimated the area under the receiver operating characteristic, sensitivity, and specificity of the simplified algorithm for identifying antiviral therapy eligibility defined by the 2017 EASL criteria. At 11 sites from eight countries that returned surveys, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and platelet count were generally available at district hospital levels, and hepatitis B e antigen and point-of-care HBV DNA tests were available only at regional and provincial hospital levels or above. Among 2895 participants included from the HEPSANET database (1740 [60·1%] male, 1155 [39·9%] female), 409 (14·1%) met EASL antiviral therapy eligibility criteria. In the derivation set, the optimal district-level hospital score was: ALT (IU/L), less than 40 (0 points), 40-79 (+1), 80 or greater (+2); AST (IU/L), less than 40 (0), 40-79 (+1), 80 or greater (+2); and platelet counts (10 /L), less than 100 (+2), 100-149 (+1), 150 or greater (0). When combined with family history and clinical data for decompensated cirrhosis that do not require any biological tests, a cut-off of 2 points or more had a sensitivity and specificity of 82% (95% CI 76-86) and 95% (93-96) to identify treatment-eligible individuals in the derivation set, and 78% (71-85) and 87% (86-89) in the validation set, respectively. Using a score incorporating platelet counts, AST, and ALT, the majority of people living with HBV requiring antiviral therapy can be identified. Our findings suggest that clinical staging can be decentralised down to district hospital level in sub-Saharan Africa. European Association for the Study of the Liver Foundation, John C Martin Foundation. For the French translation of the abstract see Supplementary Materials section

Identifying delays in healthcare seeking and provision: The Three Delays-in-Healthcare and mortality among infants and children aged 1-59 months.

Delays in illness recognition, healthcare seeking, and in the provision of appropriate clinical care are common in resource-limited settings. Our objective was to determine the frequency of delays in the "Three Delays-in-Healthcare", and factors associated with delays, among deceased infants and children in seven countries with high childhood mortality. We conducted a retrospective, descriptive study using data from verbal autopsies and medical records for infants and children aged 1-59 months who died between December 2016 and February 2022 in six sites in sub-Saharan Africa and one in South Asia (Bangladesh) and were enrolled in Child Health and Mortality Prevention Surveillance (CHAMPS). Delays in 1) illness recognition in the home/decision to seek care, 2) transportation to healthcare facilities, and 3) the receipt of clinical care in healthcare facilities were categorized according to the "Three Delays-in-Healthcare". Comparisons in factors associated with delays were made using Chi-square testing. Information was available for 1,326 deaths among infants and under 5 children. The majority had at least one identified delay (n = 854, 64%). Waiting >72 hours after illness recognition to seek health care (n = 422, 32%) was the most common delay. Challenges in obtaining transportation occurred infrequently when seeking care (n = 51, 4%). In healthcare facilities, prescribed medications were sometimes unavailable (n = 102, 8%). Deceased children aged 12-59 months experienced more delay than infants aged 1-11 months (68% vs. 61%, P = 0.018). Delays in seeking clinical care were common among deceased infants and children. Additional study to assess the frequency of delays in seeking clinical care and its provision among children who survive is warranted

Proportion of infants and children who experienced each delay in “Three Delays-in-Healthcare” framework by age group, country site, sex, and site of death.

Proportion of infants and children who experienced each delay in “Three Delays-in-Healthcare” framework by age group, country site, sex, and site of death.</p

Venn diagram of each type of delay among deceased infants and children (N = 1,326).

Venn diagram of each type of delay among deceased infants and children (N = 1,326).</p

CHAMPS consortium members.

Delays in illness recognition, healthcare seeking, and in the provision of appropriate clinical care are common in resource-limited settings. Our objective was to determine the frequency of delays in the “Three Delays-in-Healthcare”, and factors associated with delays, among deceased infants and children in seven countries with high childhood mortality. We conducted a retrospective, descriptive study using data from verbal autopsies and medical records for infants and children aged 1–59 months who died between December 2016 and February 2022 in six sites in sub-Saharan Africa and one in South Asia (Bangladesh) and were enrolled in Child Health and Mortality Prevention Surveillance (CHAMPS). Delays in 1) illness recognition in the home/decision to seek care, 2) transportation to healthcare facilities, and 3) the receipt of clinical care in healthcare facilities were categorized according to the “Three Delays-in-Healthcare”. Comparisons in factors associated with delays were made using Chi-square testing. Information was available for 1,326 deaths among infants and under 5 children. The majority had at least one identified delay (n = 854, 64%). Waiting >72 hours after illness recognition to seek health care (n = 422, 32%) was the most common delay. Challenges in obtaining transportation occurred infrequently when seeking care (n = 51, 4%). In healthcare facilities, prescribed medications were sometimes unavailable (n = 102, 8%). Deceased children aged 12–59 months experienced more delay than infants aged 1–11 months (68% vs. 61%, P = 0.018). Delays in seeking clinical care were common among deceased infants and children. Additional study to assess the frequency of delays in seeking clinical care and its provision among children who survive is warranted.</div

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Tables A, B and Figs A-D. Table A. Summary of DeCoDed causes of death for infants and children aged 1–59 months who died in the CHAMPS network (N = 1,326). Table B. Proportion of deaths that had experienced each delay in the 3 delays model by site, sex, age group, causes of death, and site of death, N = 1,326. Fig A. Highest level of healthcare facilities in which deceased infants and children received clinical (N = 1,326). Fig B. Venn diagram representing the intersectionality of care for infants and children in the CHAMPS Network between outpatient clinical visits, hospital clinical visits and traditional healing (N = 1,326). Fig C. Proportion of delays in the “Three Delays-in-Healthcare” model among deceased infants and children by country site by age. Fig D. Frequencies of delays in the 3 delays model (A) and frequencies of specific challenges (B) for the top ten DeCoDed causes of death anywhere in the causal chain. (DOCX)</p

Demographics of infants and children who died in the Child Health and Mortality Prevention Surveillance network.

Demographics of infants and children who died in the Child Health and Mortality Prevention Surveillance network.</p

Clinical care received by deceased infants and children and their caregivers in the Child Health and Mortality Prevention Surveillance network (N = 1,326).

Clinical care received by deceased infants and children and their caregivers in the Child Health and Mortality Prevention Surveillance network (N = 1,326).</p