Mobile Health Case Management System for Reducing Pediatric Treatment Abandonment
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|ClinicalTrials.gov Identifier: NCT03677128|
Recruitment Status : Recruiting
First Posted : September 19, 2018
Last Update Posted : June 17, 2020
|Condition or disease||Intervention/treatment||Phase|
|Burkitt Lymphoma Retinoblastoma||Other: mNavigator||Not Applicable|
Each year, approximately 220,000 children globally are newly diagnosed with cancer. Over 85% of these new diagnoses are made in low- and middle-income countries (LMICs). Survival rates in LMICs are 5-25% compared to 80% in high-income countries (HICs). One of the primary contributors to the discrepancy in survival outcomes between LMICs and HICs is a high rate of treatment abandonment, defined as refusal to initiate or failure to complete curative treatment. Treatment abandonment rate in Tanzania is higher than in other LMICs (40% compared to 10-25%), directly impacting patient survival. In HICs, protocol-driven treatment for children with cancer has led to increased treatment compliance and large improvements in survival. However, it is often not feasible or appropriate to use protocol-driven treatment in LMICs without necessary supportive care, human resources and infrastructure. Not surprisingly, protocol-related compliance is lower in LMICs compared to HICs. Digital technologies for health (i.e., digital health) can facilitate implementation of and compliance with standardized pediatric oncology protocols through step-by-step decision support algorithms, reminders and alerts related to patient visits, and timely data for health service coordination with allied health providers (e.g., nurses, pharmacists etc.). This multidisciplinary team from Duke University and Dimagi Inc. in USA, and Bugando Medical Center (BMC) in Tanzania, proposes to adapt, implement, and evaluate a digital case management system, called mNavigator, at BMC to improve health provider compliance with standardized pediatric oncology protocols.
For Aim 1, mNavigator development will initially focus on the two nationally-approved protocols for Burkitt lymphoma and retinoblastoma. Using principles of persuasive system design and the Consolidated Framework for Implementation Research (CFIR), prompts that guide users through protocol implementation will be used as behavioral triggers to assist with perceived ease of use.
For Aim 2, allied health providers at BMC will receive training on using mNavigator as part of an in-country workshop led by the M-PIs. This training will be followed by supported implementation. Following this training period, mNavigator will be used to enroll pediatric patients at BMC with pre-clinical diagnosis of BL or Rb, over a period of 1 year and manage their care for the duration of treatment (up to 3 months for BL and 4 months for Rb). BMC receives and treats approximately 150 patients every year, with an estimated 50 patients with Burkitt lymphoma (BL) and Rb. To review historic compliance, files of patients diagnosed after 2015 with BL and Rb (when protocols were introduced) will be abstracted by trained research assistants. Compliance with protocol-driven treatment will be monitored using mNavigator. System functionality will be assessed. Semi-structured assessments of provider system acceptance and usability will be conducted along with elucidating caregiver reported barriers to treatment completion.
Secondary objective is to describe factors that facilitate or inhibit implementation of mNavigator.
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||65 participants|
|Intervention Model:||Parallel Assignment|
|Intervention Model Description:||Effects on outcomes when using mNaviagtor will be compared to historical controls (preceding mNavigator use). Number of participants below references those who will be consented prospectively to participate in the study.|
|Masking:||None (Open Label)|
|Primary Purpose:||Health Services Research|
|Official Title:||A Mobile Health (mHealth) Case Management System for Reducing Pediatric Cancer Treatment Abandonment|
|Actual Study Start Date :||July 23, 2019|
|Estimated Primary Completion Date :||June 30, 2021|
|Estimated Study Completion Date :||June 30, 2021|
Allied health providers will use mNavigator to guide diagnosis and treatment for pediatric cancer patients at Bugando Medical Centre (BMC).
Allied health providers at BMC will use mNavigator to facilitate compliance with protocol-driven treatment and reduce patient abandonment for patients diagnosed with Burkitt lymphoma or retinoblastoma.
No Intervention: Historical controls
BL/Rb retrospective patients (treated between 2015-2019) when standardized treatment protocols for BL and Rb were introduced at BMC.
- Protocol compliance [ Time Frame: Approximately 1 year ]Percentage difference in protocol compliance with mNavigator and historical compliance.
- Time to diagnosis (in days) [ Time Frame: Approximately 1 year ]The number of days to diagnosis using mNavigator compared to historical controls. Time to diagnosis is computed as the duration (in days) from registration to diagnosis.
- Treatment abandonment [ Time Frame: Approximately 1 year ]Calculated as the difference in proportion of patients registered in mNavigator who abandon treatment compared to historical controls who abandon treatment. Treatment abandonment is defined as missing 4 or more consecutive weeks of treatment or follow-up while on therapy.
- Treatment completion [ Time Frame: Approximately 1 year ]Calculated as the proportion of patients registered in mNavigator who completed treatment (excludes patient deaths).
- System usability scale score [ Time Frame: Approximately 1 year ]System usability scale (SUS) score ranging from 0-100 measured using a 10-point validated system usability scale. A SUS score above 68 is considered above average usability.
- Monthly utilization of mNavigator [ Time Frame: Approximately 1 year ]Number of forms submitted using mNavigator, stratified, by users, per month of implementation.
- Number of patients registered in mNavigator during study period [ Time Frame: Approximately 1 year ]Number of patients registered in mNavigator during study period
- Number of instances of mNavigator failure per month (all-causes) [ Time Frame: Approximately 1 year ]Number of instances of mNavigator failure per month (all-causes)
- Number of instances of CommCare failure per month (all-causes) [ Time Frame: Approximately 1 year ]Number of instances of CommCare failure per month (all-causes)
- Number of instances of device failure per month (all-causes) [ Time Frame: Approximately 1 year ]Number of instances of device failure per month (all-causes)
- Number of hours of initial training as well as hours of ongoing support provided during the first month of implementation [ Time Frame: Approximately 1 year ]Number of hours of initial training as well as hours of ongoing support provided during the first month of implementation
- Number of users who are proficient in use of mNavigator within first month of implementation [ Time Frame: Approximately 1 year ]Number of users who are proficient in use of mNavigator within first month of implementation
- Average time in minutes spent completing each form, stratified by form [ Time Frame: Approximately 1 year ]Average time in minutes spent completing each form, stratified by form
- Time per patient [ Time Frame: Approximately 1 year ]Total time in minutes spent entering patient data in mNavigator, from time of registration until an outcome is recorded. Calculated by summing time for completing each form, by patient.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03677128
|Contact: Christina Makarushka, MPHemail@example.com|
|Contact: Kristin Schroeder, MD MPHfirstname.lastname@example.org|
|Bugando Medical Centre||Recruiting|
|Mwanza, Lake Zone, Tanzania|
|Contact: Nestory Masalu, MD|
|Principal Investigator:||Kristin Schroeder, MD MPH||Duke University|
|Principal Investigator:||Lavanya Vasudevan, PhD||Duke University|