Qualitative Assessment of the Feasibility, Usability, and Acceptability of a Mobile Client Data App for Community-Based Maternal, Neonatal, and Child Care in Rural Ghana

International Journal of Telemedicine and Applications, Volume 2016, Year 2016

Interpretação

Mobile phone applications may enhance the delivery of critical health services and the accuracy of health service data. Yet, the opinions and experiences of frontline health workers on using mobile apps to track pregnant and recently delivered women are underreported. This evaluation qualitatively assessed the feasibility, usability, and acceptability of a mobile Client Data App for maternal, neonatal, and child client data management by community health nurses (CHNs) in rural Ghana. The mobile app enabled CHNs to enter, summarize, and query client data. It also sent visit reminders for clients and provided a mechanism to report level of care to district officers. Fourteen interviews and two focus groups with CHNs, midwives, and district health officers were conducted, coded, and thematically analyzed. Results indicated that the app was easily integrated into care, improved CHN productivity, and was acceptable due to its capacity to facilitate client follow-up, data reporting, and decision-making. However, the feasibility and usability of the app were hindered by high client volumes, staff shortages, and software and device challenges. Successful integration of mobile client data apps for frontline health workers in rural and resource-poor settings requires real-time monitoring, program investments, and targeted changes in human resources. Data were collected in 2014 in two districts: Awutu Senya and Gomoa West. MOTECH was implemented in Awutu Senya in 2011 and then replicated in Gomoa West and three other districts in 2013. Both districts are located in Ghana’s Central Region and have among the highest rates of under-five and neonatal mortality in the country [4, 40]. This region additionally has significant human resource shortages. In the Central Region of Ghana, there are over 25,000 individuals to one doctor compared to the nationwide ratio of nearly 12,000 individuals to one doctor [41, 42]. The region also suffers from high vacancy rates of nurse-midwives trained to manage basic and emergency obstetric care [43–45]. Under these circumstances, mobile technologies that expand the reach of health workers are critical to overcoming barriers to care. Although telecommunication connectivity in the Central Region can be unreliable and mobile phones are not ubiquitous, phone ownership and access are high among health workers [46]. Maternal, neonatal, and child health services within Ghana’s health system are primarily delivered via public health centers and community health posts. The health centers are staffed primarily by skilled health professionals (such as nurses and midwives) who offer comprehensive preventive and basic curative services, including minor surgeries and uncomplicated deliveries. In contrast, as part of Ghana’s Community-based Health Planning and Services (CHPS) Initiative, community health posts are staffed by lower-skilled CHNs who provide health education, outreach and counseling, and basic curative services to clients via home visits and facility-based care [47]. Community health posts (referred to locally as CHPS facilities) are typically staffed by 2 to 3 CHNs who are required to have completed a two-year postsecondary certificate program in obstetrics as well as general and community health nursing. MOTECH Ghana was originally designed for use in community health posts and later extended to the health centers, hospitals, and other private health facilities. Within the two evaluation districts, MOTECH was implemented in a total of 46 facilities, including 35 community health posts and 11 health centers. The mobile Client Data App used in this evaluation was delivered by low-cost GSM mobile Nokia 1680 and Nokia Asha 200 feature phones provided by Ghana Health Service, which helped CHNs and other users to digitize and track care delivered to mother-infant pairs in their area. The system’s architecture was based on field-tested open-source software, including OpenXData for mobile data collection and OpenMRS for electronic medical records [48]. The client data system used a Java 2 Platform Micro Edition (J2ME) application to capture and store client data. All clients were assigned a unique MOTECH identification (ID) number upon registration to protect confidentiality and enable tracking across multiple facilities. During client encounters, CHNs first recorded care provided using five “simplified paper registers,” which were developed by MOTECH to condense more than a dozen registers and streamline data collection. CHNs later entered data into digital forms on their mobile phones (Figure 2(a)). General packet radio service (GPRS) data channels were used to transfer these data from the phone to a central clinical data system that was stored on the MOTECH server (Figure 2(b)). Screen shots of the MOTECH Client Data App’s saving, uploading, and query forms. The data app system then crosschecked uploaded clinical information on timing and type of care given with national guidelines to estimate specific due dates for routine care. As a result, health workers received a weekly list via short message service (SMS) of pregnant clients and mother-infant pairs in their catchment area who were either due for or defaulted on care. CHNs were also able to query client data, enabling them to retrieve lists of defaulters or women due to deliver in the upcoming week, and to search for details about individual clients (Figure 2(c)). In addition, the Client Data App generated preselected monthly health reports that were required for national reporting, if client data were at least 85% complete and accurate three consecutive months. Previously, monthly health reports were numerous, redundant, and compiled by hand. Therefore, the Client Data App was intended to improve accuracy and processing speed. The MOTECH developers designed the Client Data App for low-skilled health providers in rural and resource-poor settings. To account for anticipated power and mobile network breaks, the Java-enabled Nokia handsets allowed for mobile forms to be completed and stored offline for uploading at a later time. Phones had dual subscriber identity module (SIM) capacity and were equipped with SIM cards from two different mobile operators in case of network or congestion problems [46]. Field testing during the prototyping stage served to align the app’s features with user needs, including the simplification of data entry using check boxes, radio buttons, lists, and number fields. CHNs received in-person training as well as a detailed training manual. They could also refer to a MOTECH call center for technical assistance. Monthly prepaid airtime units were provided to all users to upload information. The Client Data App’s interface was available for use in English. Phones were password-protected, and user authentication schemes were built into Java forms to maintain confidentiality of client data [46]. Qualitative in-depth interviews and focus groups were used to examine health worker perceptions on the Client Data App’s feasibility, usability, and acceptability. For purposes of this evaluation, we defined the assessment areas as follows: Feasibility was defined as whether implementation of the Client Data App was easily and conveniently done, accounting for advantages and disadvantages to integrating the application into routine workflow. Usability was defined as whether the Client Data App could be used by CHNs to adequately record, track, and summarize data, including whether it functioned in a way that enhanced productivity or led to unproductive tasks due to errors. Acceptability was defined as whether CHNs and other stakeholders found the Client Data App likeable, including its interface and navigation features. These definitions were derived from similar prior research that qualitatively assessed user experiences for mHealth applications [28, 49–55]. Data were collected at three levels of the health system: community health posts (referred to locally as CHPS facilities), health centers, and district health directorates. Semistructured interview guides were used at all levels. In-depth interviews with CHNs and midwives asked them to describe perceived benefits and drawbacks of the Client Data App, as well as their experience using it during clinic and community outreach activities. CHNs and midwives were also asked to assess advantages and disadvantages of using the Client Data App for tasks such as recording care, tracking clients, and verifying data with automatic health reports. Skilled nurses working at the health centers did not use the Client Data App and therefore were not recruited for data collection. Interviews with district health directors and district health information officers explored how the Client Data App affected the quality of data provided by CHNs and their ability to use and supervise submission of monthly health reports. Questions also examined views regarding local and scaled-up implementation. Other district health directorate staff, including disease control officers and public health officers, who did not engage with the Client Data App were not interviewed. Focus groups with CHNs were included to further investigate findings from the individual interviews and to obtain CHNs’ recommendations for modifying the MOTECH data management system. Focus groups with midwives are not conducted given the limited number of midwives available at participating sites. All interviews and focus groups were conducted in English by a local Ghanaian and a US researcher, both with experience conducting qualitative research. The Ghanaian researcher occasionally translated local terminology in Akan used by participants. The interviews were conducted at community health posts and health centers and ranged from 40 to 120 minutes. Focus groups were conducted in a centrally located and neutral space. The discussions and lasted approximately 90 minutes. Each interview and focus group was digitally recorded and transcribed verbatim. One health center and three community health posts were randomly selected from each of the two participating districts. Purposive sampling was then used to identify CHNs, midwives, district health information officers, and district health directors with a minimum of six months experience using MOTECH’s Client Data App. The target interview sample size was 14 individuals, representing one CHN and one midwife per health center, one CHN each from three community health posts in each district, and the district health director and district health information officer in each district. The target focus group sample size was two groups each with 7 to 8 CHNs. Given resources available, this sample size was expected to enable the evaluation to reach saturation in which no new findings emerged [56]. A qualitative thematic analysis was conducted by two public health graduate students. Interview and focus group transcripts were manually coded using a priori topical codes according to the evaluation’s three assessment areas: feasibility, usability, and acceptability. Emergent subcodes were then developed based on patterns within each concept and which were relevant to the literature. We then followed an iterative process of developing a codebook, identifying salient themes, and integrating core findings [57]. When new themes were identified throughout this process, transcripts were reanalyzed to find evidence that verified or modified those themes. Later-stage interviews and focus groups were used to validate responses among member participants [58]. We also confirmed findings based on feedback from MOTECH implementation partners during various stages of data collection and analysis [59]. The evaluation was approved by the institutional review board at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland, USA. As part of the MOTECH implementation plan, the Ghana Health Service in Accra, Ghana, also approved the evaluation’s activities. All participants provided oral informed consent prior to data collection. This manuscript complies with the mHealth evidence reporting and assessment (mERA) checklist on reporting of health interventions using mobile technologies [60].

AI Digest

Study Justification:

– Mobile phone applications have the potential to improve the delivery of critical health services and the accuracy of health service data.
– However, there is a lack of information on the opinions and experiences of frontline health workers regarding the use of mobile apps to track pregnant and recently delivered women.
– This study aimed to qualitatively assess the feasibility, usability, and acceptability of a mobile Client Data App for maternal, neonatal, and child client data management by community health nurses (CHNs) in rural Ghana.

Highlights:

– The mobile Client Data App was easily integrated into care, improved CHN productivity, and was acceptable due to its capacity to facilitate client follow-up, data reporting, and decision-making.
– However, the feasibility and usability of the app were hindered by high client volumes, staff shortages, and software and device challenges.
– Successful integration of mobile client data apps for frontline health workers in rural and resource-poor settings requires real-time monitoring, program investments, and targeted changes in human resources.

Recommendations:

– Implement real-time monitoring to address challenges related to high client volumes, staff shortages, and software and device issues.
– Invest in program resources to support the integration of mobile client data apps, including training, technical assistance, and infrastructure improvements.
– Make targeted changes in human resources to ensure adequate staffing levels and skills for effective use of the app.

Key Role Players:

– Community health nurses (CHNs)
– Midwives
– District health officers
– District health information officers
– District health directors
– Disease control officers
– Public health officers

Cost Items for Planning Recommendations:

– Training for CHNs and other health workers
– Technical assistance for app implementation and troubleshooting
– Infrastructure improvements, such as reliable internet connectivity and power supply
– Staffing and recruitment to address human resource shortages
– Monitoring and evaluation activities to ensure effective implementation

Força da prova

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are a few areas for improvement. The study design is qualitative, which limits the generalizability of the findings. Additionally, the sample size is relatively small, with only 14 interviews and 2 focus groups. To improve the evidence, future studies could consider using a larger sample size and incorporating quantitative measures to complement the qualitative findings.

Resumo

Data were collected in 2014 in two districts: Awutu Senya and Gomoa West. MOTECH was implemented in Awutu Senya in 2011 and then replicated in Gomoa West and three other districts in 2013. Both districts are located in Ghana’s Central Region and have among the highest rates of under-five and neonatal mortality in the country [4, 40]. This region additionally has significant human resource shortages. In the Central Region of Ghana, there are over 25,000 individuals to one doctor compared to the nationwide ratio of nearly 12,000 individuals to one doctor [41, 42]. The region also suffers from high vacancy rates of nurse-midwives trained to manage basic and emergency obstetric care [43–45]. Under these circumstances, mobile technologies that expand the reach of health workers are critical to overcoming barriers to care. Although telecommunication connectivity in the Central Region can be unreliable and mobile phones are not ubiquitous, phone ownership and access are high among health workers [46]. Maternal, neonatal, and child health services within Ghana’s health system are primarily delivered via public health centers and community health posts. The health centers are staffed primarily by skilled health professionals (such as nurses and midwives) who offer comprehensive preventive and basic curative services, including minor surgeries and uncomplicated deliveries. In contrast, as part of Ghana’s Community-based Health Planning and Services (CHPS) Initiative, community health posts are staffed by lower-skilled CHNs who provide health education, outreach and counseling, and basic curative services to clients via home visits and facility-based care [47]. Community health posts (referred to locally as CHPS facilities) are typically staffed by 2 to 3 CHNs who are required to have completed a two-year postsecondary certificate program in obstetrics as well as general and community health nursing. MOTECH Ghana was originally designed for use in community health posts and later extended to the health centers, hospitals, and other private health facilities. Within the two evaluation districts, MOTECH was implemented in a total of 46 facilities, including 35 community health posts and 11 health centers. The mobile Client Data App used in this evaluation was delivered by low-cost GSM mobile Nokia 1680 and Nokia Asha 200 feature phones provided by Ghana Health Service, which helped CHNs and other users to digitize and track care delivered to mother-infant pairs in their area. The system’s architecture was based on field-tested open-source software, including OpenXData for mobile data collection and OpenMRS for electronic medical records [48]. The client data system used a Java 2 Platform Micro Edition (J2ME) application to capture and store client data. All clients were assigned a unique MOTECH identification (ID) number upon registration to protect confidentiality and enable tracking across multiple facilities. During client encounters, CHNs first recorded care provided using five “simplified paper registers,” which were developed by MOTECH to condense more than a dozen registers and streamline data collection. CHNs later entered data into digital forms on their mobile phones (Figure 2(a)). General packet radio service (GPRS) data channels were used to transfer these data from the phone to a central clinical data system that was stored on the MOTECH server (Figure 2(b)). Screen shots of the MOTECH Client Data App’s saving, uploading, and query forms. The data app system then crosschecked uploaded clinical information on timing and type of care given with national guidelines to estimate specific due dates for routine care. As a result, health workers received a weekly list via short message service (SMS) of pregnant clients and mother-infant pairs in their catchment area who were either due for or defaulted on care. CHNs were also able to query client data, enabling them to retrieve lists of defaulters or women due to deliver in the upcoming week, and to search for details about individual clients (Figure 2(c)). In addition, the Client Data App generated preselected monthly health reports that were required for national reporting, if client data were at least 85% complete and accurate three consecutive months. Previously, monthly health reports were numerous, redundant, and compiled by hand. Therefore, the Client Data App was intended to improve accuracy and processing speed. The MOTECH developers designed the Client Data App for low-skilled health providers in rural and resource-poor settings. To account for anticipated power and mobile network breaks, the Java-enabled Nokia handsets allowed for mobile forms to be completed and stored offline for uploading at a later time. Phones had dual subscriber identity module (SIM) capacity and were equipped with SIM cards from two different mobile operators in case of network or congestion problems [46]. Field testing during the prototyping stage served to align the app’s features with user needs, including the simplification of data entry using check boxes, radio buttons, lists, and number fields. CHNs received in-person training as well as a detailed training manual. They could also refer to a MOTECH call center for technical assistance. Monthly prepaid airtime units were provided to all users to upload information. The Client Data App’s interface was available for use in English. Phones were password-protected, and user authentication schemes were built into Java forms to maintain confidentiality of client data [46]. Qualitative in-depth interviews and focus groups were used to examine health worker perceptions on the Client Data App’s feasibility, usability, and acceptability. For purposes of this evaluation, we defined the assessment areas as follows: Feasibility was defined as whether implementation of the Client Data App was easily and conveniently done, accounting for advantages and disadvantages to integrating the application into routine workflow. Usability was defined as whether the Client Data App could be used by CHNs to adequately record, track, and summarize data, including whether it functioned in a way that enhanced productivity or led to unproductive tasks due to errors. Acceptability was defined as whether CHNs and other stakeholders found the Client Data App likeable, including its interface and navigation features. These definitions were derived from similar prior research that qualitatively assessed user experiences for mHealth applications [28, 49–55]. Data were collected at three levels of the health system: community health posts (referred to locally as CHPS facilities), health centers, and district health directorates. Semistructured interview guides were used at all levels. In-depth interviews with CHNs and midwives asked them to describe perceived benefits and drawbacks of the Client Data App, as well as their experience using it during clinic and community outreach activities. CHNs and midwives were also asked to assess advantages and disadvantages of using the Client Data App for tasks such as recording care, tracking clients, and verifying data with automatic health reports. Skilled nurses working at the health centers did not use the Client Data App and therefore were not recruited for data collection. Interviews with district health directors and district health information officers explored how the Client Data App affected the quality of data provided by CHNs and their ability to use and supervise submission of monthly health reports. Questions also examined views regarding local and scaled-up implementation. Other district health directorate staff, including disease control officers and public health officers, who did not engage with the Client Data App were not interviewed. Focus groups with CHNs were included to further investigate findings from the individual interviews and to obtain CHNs’ recommendations for modifying the MOTECH data management system. Focus groups with midwives are not conducted given the limited number of midwives available at participating sites. All interviews and focus groups were conducted in English by a local Ghanaian and a US researcher, both with experience conducting qualitative research. The Ghanaian researcher occasionally translated local terminology in Akan used by participants. The interviews were conducted at community health posts and health centers and ranged from 40 to 120 minutes. Focus groups were conducted in a centrally located and neutral space. The discussions and lasted approximately 90 minutes. Each interview and focus group was digitally recorded and transcribed verbatim. One health center and three community health posts were randomly selected from each of the two participating districts. Purposive sampling was then used to identify CHNs, midwives, district health information officers, and district health directors with a minimum of six months experience using MOTECH’s Client Data App. The target interview sample size was 14 individuals, representing one CHN and one midwife per health center, one CHN each from three community health posts in each district, and the district health director and district health information officer in each district. The target focus group sample size was two groups each with 7 to 8 CHNs. Given resources available, this sample size was expected to enable the evaluation to reach saturation in which no new findings emerged [56]. A qualitative thematic analysis was conducted by two public health graduate students. Interview and focus group transcripts were manually coded using a priori topical codes according to the evaluation’s three assessment areas: feasibility, usability, and acceptability. Emergent subcodes were then developed based on patterns within each concept and which were relevant to the literature. We then followed an iterative process of developing a codebook, identifying salient themes, and integrating core findings [57]. When new themes were identified throughout this process, transcripts were reanalyzed to find evidence that verified or modified those themes. Later-stage interviews and focus groups were used to validate responses among member participants [58]. We also confirmed findings based on feedback from MOTECH implementation partners during various stages of data collection and analysis [59]. The evaluation was approved by the institutional review board at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland, USA. As part of the MOTECH implementation plan, the Ghana Health Service in Accra, Ghana, also approved the evaluation’s activities. All participants provided oral informed consent prior to data collection. This manuscript complies with the mHealth evidence reporting and assessment (mERA) checklist on reporting of health interventions using mobile technologies [60].

Materiais

N/A

Inovações

Innovation 1: Mobile Client Data App for Community-Based Maternal, Neonatal, and Child Care
– This innovation involves the development and implementation of a mobile client data app for community health nurses (CHNs) in rural Ghana.
– The app allows CHNs to enter, summarize, and query client data, as well as send visit reminders and report level of care to district officers.
– The app improves CHN productivity and facilitates client follow-up, data reporting, and decision-making.
– However, challenges such as high client volumes, staff shortages, and software and device issues need to be addressed for successful integration in resource-poor settings.
– Real-time monitoring, program investments, and targeted changes in human resources are necessary for the successful implementation of this innovation.

Innovation 2: Integration of Mobile Client Data Apps in Rural and Resource-Poor Settings
– This innovation focuses on the successful integration of mobile client data apps in rural and resource-poor settings to improve access to maternal health services.
– It requires real-time monitoring, program investments, and targeted changes in human resources.
– The use of mobile client data apps can help overcome barriers to care in areas with limited healthcare resources.
– The findings of a qualitative assessment conducted in rural Ghana support the feasibility, usability, and acceptability of this innovation.
– The assessment was published in the International Journal of Telemedicine and Applications in 2016.

AI Innovations Description

The recommendation that can be developed into an innovation to improve access to maternal health is the use of mobile client data apps for community-based maternal, neonatal, and child care. This recommendation is based on a qualitative assessment conducted in rural Ghana, which found that the mobile app improved the productivity of community health nurses (CHNs) and facilitated client follow-up, data reporting, and decision-making. However, the feasibility and usability of the app were hindered by high client volumes, staff shortages, and software and device challenges. Therefore, successful integration of mobile client data apps in rural and resource-poor settings requires real-time monitoring, program investments, and targeted changes in human resources. This innovation can help overcome barriers to care in areas with limited healthcare resources and improve access to maternal health services. The findings of this assessment were published in the International Journal of Telemedicine and Applications in 2016.

AI Innovations Methodology

To simulate the impact of the main recommendations of this abstract on improving access to maternal health, a methodology could be developed as follows:

1. Study Design: Conduct a randomized controlled trial (RCT) in rural areas of Ghana to evaluate the effectiveness of implementing mobile client data apps for community-based maternal, neonatal, and child care. Randomly assign participating community health posts (CHPs) to either the intervention group (using the mobile client data app) or the control group (using traditional paper-based systems).

2. Sample Selection: Select a representative sample of CHPs from different districts in rural Ghana. Ensure that the selected CHPs have similar characteristics in terms of client volumes, staff shortages, and software and device challenges.

3. Intervention Implementation: Provide training to CHNs on how to use the mobile client data app effectively. Ensure that they are familiar with the app’s features, such as entering, summarizing, and querying client data, sending visit reminders, and reporting level of care to district officers.

4. Data Collection: Collect data on key indicators related to maternal health access, such as the number of antenatal care visits, the number of postnatal care visits, the number of deliveries attended by skilled birth attendants, and the timeliness of care provided. Collect data from both the intervention and control groups at baseline and at regular intervals throughout the study period.

5. Data Analysis: Analyze the collected data using appropriate statistical methods, such as chi-square tests or t-tests, to compare the outcomes between the intervention and control groups. Assess the impact of the mobile client data app on improving access to maternal health services.

6. Qualitative Assessment: Conduct qualitative interviews and focus groups with CHNs, midwives, and district health officers to gather their opinions and experiences regarding the feasibility, usability, and acceptability of the mobile client data app. Analyze the qualitative data using thematic analysis to identify common themes and insights.

7. Program Investments: Evaluate the program investments required for successful integration of mobile client data apps in rural and resource-poor settings. Assess the costs associated with implementing and maintaining the app, including the costs of mobile phones, training, technical support, and data management.

8. Targeted Changes in Human Resources: Identify the targeted changes in human resources needed to support the integration of mobile client data apps. Determine the staffing requirements, workload distribution, and training needs for CHNs and other health workers involved in using the app.

9. Real-time Monitoring: Develop a real-time monitoring system to track the usage and performance of the mobile client data app. Monitor the app’s functionality, connectivity, and data accuracy to ensure its effectiveness in improving access to maternal health services.

10. Program Evaluation: Evaluate the overall impact of the mobile client data app on improving access to maternal health services. Assess the scalability and sustainability of the intervention, considering factors such as cost-effectiveness, user satisfaction, and long-term benefits.

By following this methodology, researchers can simulate the impact of the main recommendations mentioned in the abstract and provide evidence-based insights on the effectiveness of using mobile client data apps to improve access to maternal health services in rural and resource-poor settings.

Autor

Dima Health

Statistics:

Citations: 31

Identifiers:

DOI: 10.1155/2016/2515420

ISSN: 16876415

Research Areas:

Community Interventions, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Social Determinants, Technology and Innovations, Workforce

Study Countries:

Ghana

Study Design:

Cohort Study, Grounded Theory

Study Approach:

Qualitative

Participants Gender:

Female

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