1
|
Beynon F, Langet H, Bohle LF, Awasthi S, Ndiaye O, Machoki M’Imunya J, Masanja H, Horton S, Ba M, Cicconi S, Emmanuel-Fabula M, Faye PM, Glass TR, Keitel K, Kumar D, Kumar G, Levine GA, Matata L, Mhalu G, Miheso A, Mjungu D, Njiri F, Reus E, Ruffo M, Schär F, Sharma K, Storey HL, Masanja I, Wyss K, D’Acremont V. The Tools for Integrated Management of Childhood Illness (TIMCI) study protocol: a multi-country mixed-method evaluation of pulse oximetry and clinical decision support algorithms. Glob Health Action 2024; 17:2326253. [PMID: 38683158 PMCID: PMC11060010 DOI: 10.1080/16549716.2024.2326253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 02/25/2024] [Indexed: 05/01/2024] Open
Abstract
Effective and sustainable strategies are needed to address the burden of preventable deaths among children under-five in resource-constrained settings. The Tools for Integrated Management of Childhood Illness (TIMCI) project aims to support healthcare providers to identify and manage severe illness, whilst promoting resource stewardship, by introducing pulse oximetry and clinical decision support algorithms (CDSAs) to primary care facilities in India, Kenya, Senegal and Tanzania. Health impact is assessed through: a pragmatic parallel group, superiority cluster randomised controlled trial (RCT), with primary care facilities randomly allocated (1:1) in India to pulse oximetry or control, and (1:1:1) in Tanzania to pulse oximetry plus CDSA, pulse oximetry, or control; and through a quasi-experimental pre-post study in Kenya and Senegal. Devices are implemented with guidance and training, mentorship, and community engagement. Sociodemographic and clinical data are collected from caregivers and records of enrolled sick children aged 0-59 months at study facilities, with phone follow-up on Day 7 (and Day 28 in the RCT). The primary outcomes assessed for the RCT are severe complications (mortality and secondary hospitalisations) by Day 7 and primary hospitalisations (within 24 hours and with referral); and, for the pre-post study, referrals and antibiotic. Secondary outcomes on other aspects of health status, hypoxaemia, referral, follow-up and antimicrobial prescription are also evaluated. In all countries, embedded mixed-method studies further evaluate the effects of the intervention on care and care processes, implementation, cost and cost-effectiveness. Pilot and baseline studies started mid-2021, RCT and post-intervention mid-2022, with anticipated completion mid-2023 and first results late-2023. Study approval has been granted by all relevant institutional review boards, national and WHO ethical review committees. Findings will be shared with communities, healthcare providers, Ministries of Health and other local, national and international stakeholders to facilitate evidence-based decision-making on scale-up.Study registration: NCT04910750 and NCT05065320.
Collapse
Affiliation(s)
- Fenella Beynon
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Faculty of Science, University of Basel, Basel, Switzerland
| | - Hélène Langet
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Faculty of Science, University of Basel, Basel, Switzerland
| | - Leah F. Bohle
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Faculty of Science, University of Basel, Basel, Switzerland
| | - Shally Awasthi
- Department of Paediatrics, King George’s Medical University, Lucknow, India
| | - Ousmane Ndiaye
- Faculté de médecine, Université Cheikh Anta Diop, Dakar, Senegal
| | | | | | - Susan Horton
- School of Public Health and Health Systems, University of Waterloo, Waterloo, Canada
| | | | - Silvia Cicconi
- Faculty of Science, University of Basel, Basel, Switzerland
- Department of Medicine, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
| | | | - Papa Moctar Faye
- Faculté de médecine, Université Cheikh Anta Diop, Dakar, Senegal
| | - Tracy R. Glass
- Faculty of Science, University of Basel, Basel, Switzerland
- Department of Medicine, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
| | - Kristina Keitel
- Department of Medicine, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Division of Pediatric Emergency Medicine, Department of Pediatrics,Inselspital, University of Bern, Bern, Switzerland
| | - Divas Kumar
- Department of Paediatrics, King George’s Medical University, Lucknow, India
| | - Gaurav Kumar
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Faculty of Science, University of Basel, Basel, Switzerland
| | - Gillian A. Levine
- Faculty of Science, University of Basel, Basel, Switzerland
- Department of Medicine, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
| | - Lena Matata
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Faculty of Science, University of Basel, Basel, Switzerland
- Health Systems, Impact Evaluation and Policy, Ifakara Health Institute, Dar es Salaam, Tanzania
| | - Grace Mhalu
- Health Systems, Impact Evaluation and Policy, Ifakara Health Institute, Dar es Salaam, Tanzania
| | | | | | - Francis Njiri
- College of Health Sciences, University of Nairobi, Nairobi, Kenya
| | - Elisabeth Reus
- Faculty of Science, University of Basel, Basel, Switzerland
- Department of Medicine, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
| | | | - Fabian Schär
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Faculty of Science, University of Basel, Basel, Switzerland
| | | | | | - Irene Masanja
- Health Systems, Impact Evaluation and Policy, Ifakara Health Institute, Dar es Salaam, Tanzania
| | - Kaspar Wyss
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Faculty of Science, University of Basel, Basel, Switzerland
| | - Valérie D’Acremont
- Department of Medicine, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Digital Global Health Department, Centre for Primary Care and PublicHealth (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - TIMCI Collaborator Group
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Faculty of Science, University of Basel, Basel, Switzerland
- Department of Paediatrics, King George’s Medical University, Lucknow, India
- Faculté de médecine, Université Cheikh Anta Diop, Dakar, Senegal
- College of Health Sciences, University of Nairobi, Nairobi, Kenya
- Directorate, Ifakara Health Institute, Dar es Salaam, Tanzania
- School of Public Health and Health Systems, University of Waterloo, Waterloo, Canada
- PATH
- Department of Medicine, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Division of Pediatric Emergency Medicine, Department of Pediatrics,Inselspital, University of Bern, Bern, Switzerland
- Health Systems, Impact Evaluation and Policy, Ifakara Health Institute, Dar es Salaam, Tanzania
- Digital Global Health Department, Centre for Primary Care and PublicHealth (Unisanté), University of Lausanne, Lausanne, Switzerland
| |
Collapse
|
2
|
Tan R, Kavishe G, Luwanda LB, Kulinkina AV, Renggli S, Mangu C, Ashery G, Jorram M, Mtebene IE, Agrea P, Mhagama H, Vonlanthen A, Faivre V, Thabard J, Levine G, Le Pogam MA, Keitel K, Taffé P, Ntinginya N, Masanja H, D'Acremont V. A digital health algorithm to guide antibiotic prescription in pediatric outpatient care: a cluster randomized controlled trial. Nat Med 2024; 30:76-84. [PMID: 38110580 PMCID: PMC10803249 DOI: 10.1038/s41591-023-02633-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 10/06/2023] [Indexed: 12/20/2023]
Abstract
Excessive antibiotic use and antimicrobial resistance are major global public health threats. We developed ePOCT+, a digital clinical decision support algorithm in combination with C-reactive protein test, hemoglobin test, pulse oximeter and mentorship, to guide health-care providers in managing acutely sick children under 15 years old. To evaluate the impact of ePOCT+ compared to usual care, we conducted a cluster randomized controlled trial in Tanzanian primary care facilities. Over 11 months, 23,593 consultations were included from 20 ePOCT+ health facilities and 20,713 from 20 usual care facilities. The use of ePOCT+ in intervention facilities resulted in a reduction in the coprimary outcome of antibiotic prescription compared to usual care (23.2% versus 70.1%, adjusted difference -46.4%, 95% confidence interval (CI) -57.6 to -35.2). The coprimary outcome of day 7 clinical failure was noninferior in ePOCT+ facilities compared to usual care facilities (adjusted relative risk 0.97, 95% CI 0.85 to 1.10). There was no difference in the secondary safety outcomes of death and nonreferred secondary hospitalizations by day 7. Using ePOCT+ could help address the urgent problem of antimicrobial resistance by safely reducing antibiotic prescribing. Clinicaltrials.gov Identifier: NCT05144763.
Collapse
Affiliation(s)
- Rainer Tan
- Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
- Ifakara Health Institute, Dar es Salaam, United Republic of Tanzania.
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland.
- University of Basel, Basel, Switzerland.
| | - Godfrey Kavishe
- National Institute of Medical Research - Mbeya Medical Research Centre, Mbeya, United Republic of Tanzania
| | - Lameck B Luwanda
- Ifakara Health Institute, Dar es Salaam, United Republic of Tanzania
| | - Alexandra V Kulinkina
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Sabine Renggli
- Ifakara Health Institute, Dar es Salaam, United Republic of Tanzania
| | - Chacha Mangu
- National Institute of Medical Research - Mbeya Medical Research Centre, Mbeya, United Republic of Tanzania
| | - Geofrey Ashery
- Ifakara Health Institute, Dar es Salaam, United Republic of Tanzania
| | - Margaret Jorram
- Ifakara Health Institute, Dar es Salaam, United Republic of Tanzania
| | | | - Peter Agrea
- National Institute of Medical Research - Mbeya Medical Research Centre, Mbeya, United Republic of Tanzania
| | - Humphrey Mhagama
- National Institute of Medical Research - Mbeya Medical Research Centre, Mbeya, United Republic of Tanzania
| | - Alan Vonlanthen
- Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Vincent Faivre
- Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Julien Thabard
- Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Gillian Levine
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Marie-Annick Le Pogam
- Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Kristina Keitel
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
- Pediatric Emergency Department, Department of Pediatrics, University Hospital Bern, Bern, Switzerland
| | - Patrick Taffé
- Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Nyanda Ntinginya
- National Institute of Medical Research - Mbeya Medical Research Centre, Mbeya, United Republic of Tanzania
| | - Honorati Masanja
- Ifakara Health Institute, Dar es Salaam, United Republic of Tanzania
| | - Valérie D'Acremont
- Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| |
Collapse
|
3
|
Beynon F, Guérin F, Lampariello R, Schmitz T, Tan R, Ratanaprayul N, Tamrat T, Pellé KG, Catho G, Keitel K, Masanja I, Rambaud-Althaus C. Digitalizing Clinical Guidelines: Experiences in the Development of Clinical Decision Support Algorithms for Management of Childhood Illness in Resource-Constrained Settings. Glob Health Sci Pract 2023; 11:e2200439. [PMID: 37640492 PMCID: PMC10461705 DOI: 10.9745/ghsp-d-22-00439] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 06/13/2023] [Indexed: 08/31/2023]
Abstract
Clinical decision support systems (CDSSs) can strengthen the quality of integrated management of childhood illness (IMCI) in resource-constrained settings. Several IMCI-related CDSSs have been developed and implemented in recent years. Yet, despite having a shared starting point, the IMCI-related CDSSs are markedly varied due to the need for interpretation when translating narrative guidelines into decision logic combined with considerations of context and design choices. Between October 2019 and April 2021, we conducted a comparative analysis of 4 IMCI-related CDSSs. The extent of adaptations to IMCI varied, but common themes emerged. Scope was extended to cover a broader range of conditions. Content was added or modified to enhance precision, align with new evidence, and support rational resource use. Structure was modified to increase efficiency, improve usability, and prioritize care for severely ill children. The multistakeholder development processes involved syntheses of recommendations from existing guidelines and literature; creation and validation of clinical algorithms; and iterative development, implementation, and evaluation. The common themes surrounding adaptations of IMCI guidance highlight the complexities of digitalizing evidence-based recommendations and reinforce the rationale for leveraging standards for CDSS development, such as the World Health Organization's SMART Guidelines. Implementation through multistakeholder dialogue is critical to ensure CDSSs can effectively and equitably improve quality of care for children in resource-constrained settings.
Collapse
Affiliation(s)
- Fenella Beynon
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | | | | | - Torsten Schmitz
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Rainer Tan
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
- Digital and Global Health Unit, Unisanté, Center for Primary Care and Public Health, Lausanne, Switzerland
- Ifakara Health Institute, Dar es Salaam, Tanzania
| | - Natschja Ratanaprayul
- Department of Digital Health and Innovations, World Health Organization, Geneva, Switzerland
| | - Tigest Tamrat
- UNDP/UNFPA/UNICEF/World Bank Special Program of Research, Development and Research Training in Human Reproduction (HRP), Department of Sexual and Reproductive Health and Research, World Health Organization, Geneva, Switzerland
| | | | - Gaud Catho
- Division of Infectious Diseases, Geneva University Hospital and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Global Health Institute, University of Geneva, Geneva, Switzerland
| | - Kristina Keitel
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
- Department of Pediatric Emergency Medicine, Department of Pediatrics, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
| | | | | |
Collapse
|
4
|
Trottet C, Vogels T, Keitel K, Kulinkina AV, Tan R, Cobuccio L, Jaggi M, Hartley MA. Modular Clinical Decision Support Networks (MoDN)-Updatable, interpretable, and portable predictions for evolving clinical environments. PLOS Digit Health 2023; 2:e0000108. [PMID: 37459285 PMCID: PMC10351690 DOI: 10.1371/journal.pdig.0000108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 06/12/2023] [Indexed: 07/20/2023]
Abstract
Clinical Decision Support Systems (CDSS) have the potential to improve and standardise care with probabilistic guidance. However, many CDSS deploy static, generic rule-based logic, resulting in inequitably distributed accuracy and inconsistent performance in evolving clinical environments. Data-driven models could resolve this issue by updating predictions according to the data collected. However, the size of data required necessitates collaborative learning from analogous CDSS's, which are often imperfectly interoperable (IIO) or unshareable. We propose Modular Clinical Decision Support Networks (MoDN) which allow flexible, privacy-preserving learning across IIO datasets, as well as being robust to the systematic missingness common to CDSS-derived data, while providing interpretable, continuous predictive feedback to the clinician. MoDN is a novel decision tree composed of feature-specific neural network modules that can be combined in any number or combination to make any number or combination of diagnostic predictions, updatable at each step of a consultation. The model is validated on a real-world CDSS-derived dataset, comprising 3,192 paediatric outpatients in Tanzania. MoDN significantly outperforms 'monolithic' baseline models (which take all features at once at the end of a consultation) with a mean macro F1 score across all diagnoses of 0.749 vs 0.651 for logistic regression and 0.620 for multilayer perceptron (p < 0.001). To test collaborative learning between IIO datasets, we create subsets with various percentages of feature overlap and port a MoDN model trained on one subset to another. Even with only 60% common features, fine-tuning a MoDN model on the new dataset or just making a composite model with MoDN modules matched the ideal scenario of sharing data in a perfectly interoperable setting. MoDN integrates into consultation logic by providing interpretable continuous feedback on the predictive potential of each question in a CDSS questionnaire. The modular design allows it to compartmentalise training updates to specific features and collaboratively learn between IIO datasets without sharing any data.
Collapse
Affiliation(s)
- Cécile Trottet
- Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Thijs Vogels
- Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Kristina Keitel
- Division of Pediatric Emergency Medicine, Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Alexandra V. Kulinkina
- Digital Health Unit, Swiss Center for International Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Rainer Tan
- Clinical Research Unit, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Ifakara Health Institute, Ifakara, Tanzania
- Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland
| | - Ludovico Cobuccio
- Clinical Research Unit, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
| | - Martin Jaggi
- Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Mary-Anne Hartley
- Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Laboratory of Intelligent Global Health Technologies, Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, USA
| |
Collapse
|