Background: There has been a rapid increase in morbidity and mortality arising from non-communicable diseases (NCDs). The Academic Model Providing Access to Healthcare (AMPATH) program has established a chronic disease management program in collaboration with the Ministry of Health (MoH) in Kenya at over 150 health facilities in western Kenya. The primary health integrated care for chronic (PIC4C) disease project seeks to deliver preventive, promotive, and curative care for diabetes, hypertension, cervical and breast cancers at the primary health care level. We apply the RE-AIM framework to conduct a process evaluation of the integrated PIC4C model. This paper describes the protocol we are using in the PIC4C process evaluation planning and activities. Methods and Analysis: This evaluation utilizes clinic reports as well as primary data collected in two waves. Using mixed methods (secondary data, observation, semi-structured interviews, and focus group discussions), the process evaluation assesses the reach, effectiveness, adoption, implementation and maintenance of the PIC4C model in Busia and Trans Nzoia Kenya. The evaluation captures the PIC4C process, experiences of implementers and users, and the wishes of those using the PIC4C services. We will analyse our data across the RE-AIM dimensions using descriptive statistics and two-sample t-test to compare the mean scores for baseline and end line. Qualitative data will be analyzed thematically. Discussion: The process evaluation of the PIC4C model in Kenya allows implementers and users to reflect and question its implementation, uptake and maintenance. Our experiences thus far suggest practicable strategies to facilitate primary health care can benefit extensively from deliberate process evaluation of the programs undertaken. Furthermore, integrating the RE-AIM framework in the process evaluation of health programs is valuable due to its pragmatic and reporting usefulness.
The PIC4C model delivers preventive, promotive, and curative care for diabetes, hypertension, cervical and breast cancers at the primary health care level. It covers 40 and 33 health facilities in Busia and Trans Nzoia, respectively. Trans Nzoia County lies on the eastern side of Mount Elgon, in western Kenya. As per the 2009 census, Trans Nzoia County has a population of about 818,759 people, and 50% are male. There is one County referral hospital, five Sub-County hospitals, and seven health centers. Busia County is situated in the western part of Kenya and borders Uganda. The County covers an area of 1,694.5 square kilometers and has a population of 953,337 and 47.8% are males. Busia has one County referral hospital, six Sub-County hospitals, and fourteen health centers (14). Primary health facilities are the first level of contact between patients and the health system. They include Health Centers and Dispensaries. They provide ambulatory health services, which are generally preventive, and curative services mostly adapted to local needs. Common services provided as prioritized by the Kenyan government include education on health problems and how to prevent them, nutrition, maternal child healthcare, family planning, basic sanitation, immunization, treatment of common diseases and injuries, and provision of basic medication. Additionally, select primary health care facilities address dental health, mental health, HIV AIDS, and primary eye care. None of the health facilities involved in PIC4C included routine preventive and treatment care for cancers, hypertension, or diabetes. The overarching goal of the evaluation of the PIC4C project is to document the reach, effectiveness, adoption, implementation and sustainability of the integrated chronic care model with the aim of informing the ministry of health policy and scale up of the model. The PIC4C process evaluation uses mixed methods to ensure all aspects of the RE-AIM are well addressed. Supplementary Files 1–6 show the surveys, in-depth interviews and FGDs that were used to collect information from patients, health care workers, and decision makers. This paper describes the protocol we are using in the PIC4C process evaluation planning and activities. Data will be collected in two waves, 18 months apart, using mixed methods: secondary data, semi-structured interviews (SSIs), observation and focus group discussions (FGDs). The secondary data will involve analyses of routinely collected PIC4C care and project activity data including daily registers and the monthly reports. A SSI is a qualitative data generation method, which allows for a natural dialogue around a topic of interest. A predetermined list of questions is used to develop an interview schedule which is used to guide the discussion. There will be 48 SSI sessions involving County leaders including the CEC and Director Health, Non-communicable Diseases Coordinator). While the socio-demographics data will be collected using a structured questionnaire, the rest of the questions will be open-ended. The observation method generates qualitative data on specific activities of interest. In each County (Table 1), we will conduct 16 patient reception and vital signs assessments at health facility level. During these sessions, we will observe how patients are received upon arrival at the health clinic and how vital signs are assessed. The education and screening observation assessment will be done at the community level only during the community screening services led by the Community Health Promoters (CHPs). We aim to make 8 observations in each County. The FGD is a qualitative data collection method involving 6–12 participants with a trained moderator to guide the discussions around a particular topic. It is useful to gain a shared ideas and opinions among participants. A total of 20 FGD sessions will be held as follows (Table 2): Clients/patients 8 FGDs; health care providers (HCPs) 8 FGDs; community health promoters (CHPs) and community health volunteers (CHVs) 4 FGDs. Recruitment for Semi Structured Interviews (SSIs). CEC, County Executive Committee member for Health; HRIO, Health Records Information Officer; NCD, Non-Communicable Diseases; RH, Reproductive Health. Recruitment for Focus Group Discussions (FGDs). CHP, Community Health Volunteer; CHV, Community Health Worker; NCD, Non-communicable Disease; RH, Reproductive Health. The RE-AIM framework will be used and we aim to interview the same study participants at each time point and recruit additional participants where appropriate. In Table 3, the RE-AIM dimensions are applied to specific aspects of the PIC4C project. Indicators to show expected activities and/or outcomes are described. Data sources for required information and relevant data collection methods are also provided. For the reach, absolute number and characteristics of targets of the intervention are described. The absolute number of patients and trainees/mentees engaged will be reported, including their specific characteristics. The reach will also capture the number of people educated, screened, linked, treated and retained for each condition will be captured. Effectiveness covers the impact of the PIC4C interventions with special attention to numbers linked, treated and retained for each condition, and client feedback on the PIC4C services. The following changes will be expected among patients: a drop of 10 systolic blood pressure (SBP) or 5 diastolic blood pressure (DBP); % of diabetes mellitus (DM) patients getting to <8%, or mean drop of 2%; % of positive screened treated for pre- cancer lesions or linked for cancer treatment or those treated for pre-cancer lesions who are cancer free at one year follow up. For those with breast cancer, % of breast lumps biopsied and % of cytology positive linked to care would be of interest. For the trainees/mentees, the evaluation will reveal their change in knowledge, skills, and confidence in providing service for the four conditions, as well as trainees feedback on the PIC4C project. Regarding adoption, the evaluation focusses on patients' adherence to clinic visits and their NHIF uptake. At the health facility, adoption is seen at four levels: (1) Percentage of MoH trained staff offering care in the training area, (2) level of implementation of NHIF, (3) Use of PIC4C initiated information technology systems, and (4) Introduction of MoH tools and % using them. Lastly, at the County level, the number of budgets that include PIC4C strategies for any of the four conditions will be reported. PIC4C process evaluation indicators and data sources. CHV, Community health volunteer; CHP, Community Health Volunteer; FGD, Focus group discussion; MoH, Ministry of Health; NHIF, National Health Insurance Fund; PIC4C, Primary Health Integrated Care for Chronic (PIC4C) disease; SCHMT, Sub-county Health Management Committee; SSI, Semi structured interview; SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; Ca, Cancer; CaCx, Cancer of the cervix. Implementation focusses on the extent to which the PIC4C programs have been delivered as intended and appreciates any deviations/adaptations applied. This includes fidelity to the PIC4C activities, timing and costs. It also captures level of completeness and utilization of PIC4C interventions. The final dimension of the RE-AIM is maintenance, which considers sustained effectiveness of the PIC4C at the individual level and the sustained delivery at the institutional level in Busia and Trans Nzoia. The study participants will be clients, health care workers, and decision makers. The clients will include patients with diabetes, hypertension, cervical and breast cancers. Health care workers will include Community Health Promoters (CHPs), Community Health Volunteers (CHVs) and health care providers (being trainees and mentees). Decision makers are facility in-charges, Sub-county and County leaders. Table 4 provides the study participants and the tools that will be used to interview them. PIC4C process evaluation study participants, tools and analysis plan. BPs, Blood Pressure; BMI, Body Mass Index; CEC, Chief Executive Officer for Health; CHV, Community health volunteer; CHP, Community Health Volunteer; HRIO, Health Records Information Officer; NCD, Non-Communicable Diseases; PIC4C, Primary Health Integrated Care for Chronic (PIC4C) Disease; RBS, Rapid Blood Sugars; RH, Reproductive Health. The FGD and the SSI participants will be selected purposefully in each county based on their health condition (e.g., diabetic or hypertensive patients). The health care providers and decision makers will be selected in each county based on their cadre and level of their facility; County, Sub-County, Health Center or Dispensary. In addition, the sampling for the observations on patient reception and vital signs assessment in each County will be based on the facility level to ensure that each level is represented. The education and screening observation will be based on the number of community health promoters who are leading these sessions. The patient self-report surveys will be based on a sample size calculated to ensure a representation of the patients receiving care and treatment services for the four conditions under the PIC4C project in each of the Counties. Trained research assistants will recruit all study participants using predetermined inclusion criteria. For health care providers, they would have to be working in the designated County, Sub-County or health facility for at least 6 months, and be able to speak in English or Kiswahili. We aim to interview at least 3 individuals at the County level leadership. At Sub-County level, we aim to interview at least 9 individuals including the non-communicable disease (NCD) focal persons, Reproductive Health Coordinators, Medical Officers, Nursing officers, Health Records Officers and Pharmacists. At the facility level, we aim to interview at least 9 healthcare facility in-charges. We aim to have a mixed gender representation at all the recruitment levels (Table 1). For the FGDs (Table 2), the first categories involve clients. We will engage patients who should be mentally stable, living with any of the four NCDs (Diabetes, hypertension, breast cancer, and cervical cancer), aged between 18 and 60 years and be able to speak English or Kiswahili. For the HCP FGDs, participants should be working in the designated facility for at least 6 months. For the CHP and CHVs FGD participants, they should have worked for the PIC4C project for at least 6 months, aged between 18 and 60 years and able to speak English or Kiswahili. We aim to recruit 8–12 participants per FGD session. There will be 8 FGDs with patients (4 per County) and the FGDs on diabetes and hypertension will have mixed gender, while those addressing breast and cervical cancer will have females only. The 8 FGDs for the HCPs (4 per county) will be composed of the trainees and mentees for the NCD conditions and they will be from different cadres (see Table 2). Prior to beginning work in each county and each facility, approvals will be sought accordingly. A PIC4C local contact at the facilities and a research team member will meet with the relevant health facility leadership and discuss the process evaluation of the PIC4C project. At each health facility and prior to conducting consent, one of the RAs/research team members will recruit relevant HCPs, CHPs, and CHVs into the study. The PIC4C RA will approach the health worker individually, share with them the purpose of the data collection session, and confirm interest in participating. For those interested, the RA will schedule the session at a time convenient to the participant. For the patients, they will be identified from the PIC4C database based on their condition. Potential participants will be called and recruited by telephone 1–2 weeks before the FGD sessions that will be held in the nearest health facility and at times that are convenient to participants. The study will use both routinely collected clinic data (e.g., daily registers and the monthly registers/reports) and data that will be specifically collected during the two waves. In wave one, the tools for data collection include: (1) Patient reception and vital signs' assessment checklist (Observation process mapping); (2) Education and screening observation checklist; (3) Written test/Random knowledge test for CHVs, CHPs and Clinicians; (4) Patient self-report/feedback forms; and (5) Health facility questionnaire. In wave two, all wave 1 tools will be administered. In addition, there will be SSIs with facility, Sub-County and county leaders; and FGDs with clients, HCPs, CHPs, and CHVs. Questionnaires will be administered at the facility, at baseline and end line, to compare availability of select drugs for hypertension and diabetes. Data will also capture the time of diagnosis to treatment for diabetes and hypertension care. For lost to follow-up, we shall use the return to clinic date. For those on medication, we shall check if they have defaulted 90 days from the last return to clinic. We shall also check for those on lifestyle modification. Trained research assistants will facilitate semi-structured interviews (SSIs), FGDs and observations. They will ensure all participants provide written consent before they participate in the evaluation. They will observe how patients are received, do process mapping during care, and report on how vital signs are assessed. They will also observe the education and screening activities. Regarding the FGDs, each session will be facilitated by a moderator and a scribe. The scribe will help the moderator by taking notes during the discussions. All sessions will be audio-recorded and conducted in a private space and at a time that will be convenient for participants. The questionnaire administration should take 40 min, while FGD and SSI sessions should take ~1 h. As shown in Table 4, percentage change in knowledge will be calculated as percentage knowledge score at end line minus percentage knowledge score at baseline. Change in percentage of people screened will be calculated as percentage of population sample surveyed ever screened within the past 2 years at end line compared to percentage of population sample surveyed ever screened within the past 2 years at baseline. Percentage change graphs will also be plotted to illustrate the changes over time. We will use a two-sample t-test to compare the mean scores for baseline and end line. The analysis will also include summaries of categorical variables, which include response frequencies for each questionnaire item. An appropriate cut-off for knowledge will be chosen so that characteristics of people who meet the threshold can be compared to those who do not, both at baseline and end line testing. Proportion of community members who accepted screening will be calculated as the total number of people who were screened divided by the total number of people who met the threshold. Linkage to care for diabetes and hypertension will be calculated as the total number of persons treated for diabetes and hypertension divided by the total number of persons referred after screening positive for diabetes and hypertension. Percentage of persons screened through each of the projects screening strategies who were linked to care will be calculated as the number of persons treated after referral from particular screening strategy divided by the total number of people treated after referral from screenings. Percentage of patients with controlled blood pressure will be calculated at end line for care levels 2, 3, and 4 as the proportion of patients >60 years with blood pressure (BP) below 150/90 and patients <60 years with BP below 140/90. The study will also report the percentage of patients with a drop in hemoglobin A1c at end line for levels 2, 3, and 4. Retention rates for treatment of diabetes and hypertension will be calculated as number of patients seen 90 days from their last expected clinic visit divided by the total number of patients in care. Drug affordability will be measured, at baseline and end line, as the percentage of patients able to buy a whole month supply of prescribed select medicines. The audio recordings will be transcribed and consequently coded using NVivo or a similar software. Prior to analysis, a research team member will listen to random sections of the recordings and compare them to the transcripts to verify accurate transcription. Then, three coders will look at the research questions, field notes and transcripts to familiarize themselves with the data. They will be guided by the research questions to develop a codebook through segmentation of thoughts found in the raw text. Each segment will be labeled with a descriptive code and definition that captures the ideas therein. The descriptive code labels will be assessed and similar patterns will be grouped together and labeled thematically. Analytic memos will track decision-making among coders as the codebook and themes are refined through subsequent stages of inductive development of themes. Quotes from transcripts will be used to provide vivid illustrations of the findings.
– The study aims to evaluate the Primary Health Integrated Care for Chronic (PIC4C) disease project in Kenya, which delivers care for diabetes, hypertension, cervical and breast cancers at the primary health care level.
– The evaluation will assess the reach, effectiveness, adoption, implementation, and maintenance of the PIC4C model.
– The findings will inform the Ministry of Health policy and scale-up of the model, addressing the increasing morbidity and mortality from non-communicable diseases in Kenya.
Highlights:
– The study uses the RE-AIM framework to guide the evaluation, which assesses the reach, effectiveness, adoption, implementation, and maintenance of health programs.
– Mixed methods are employed, including secondary data analysis, observation, semi-structured interviews, and focus group discussions.
– Data will be collected in two waves, 18 months apart, to capture changes over time.
– The evaluation involves clients/patients, health care workers, and decision makers as study participants.
– Key indicators include the number of patients educated, screened, linked, treated, and retained for each condition, as well as changes in knowledge, skills, and confidence among health care providers.
– The evaluation also considers adoption at different levels, implementation fidelity, and the sustainability of the PIC4C model.
Recommendations:
– Based on the evaluation findings, recommendations can be made to improve the reach, effectiveness, adoption, implementation, and maintenance of the PIC4C model.
– These recommendations may include strategies to increase patient adherence to clinic visits, improve NHIF uptake, enhance training and support for health care providers, and strengthen the use of information technology systems.
– Budgetary considerations should be made to support the implementation of these recommendations, including funding for training, infrastructure, and the procurement of necessary equipment and supplies.
Key Role Players:
– Ministry of Health: Responsible for policy development and scale-up of the PIC4C model.
– Academic Model Providing Access to Healthcare (AMPATH): Collaborator in the chronic disease management program and implementation of the PIC4C model.
– County and Sub-County Health Management Committees: Involved in the implementation and oversight of the PIC4C model at the local level.
– Health facility in-charges: Responsible for the delivery of care and implementation of the PIC4C model at the facility level.
– Community Health Promoters (CHPs) and Community Health Volunteers (CHVs): Involved in community education, screening, and support for the PIC4C model.
– Research team: Conducts the evaluation and provides recommendations based on the findings.
Cost Items for Planning Recommendations:
– Training and capacity building for health care providers: Includes costs for workshops, materials, and trainers.
– Infrastructure and equipment: Budget for the procurement and maintenance of necessary equipment and supplies for the PIC4C model.
– Information technology systems: Funding for the development, implementation, and maintenance of IT systems to support the PIC4C model.
– Monitoring and evaluation: Resources for data collection, analysis, and reporting to assess the reach, effectiveness, adoption, implementation, and maintenance of the PIC4C model.
– Support services: Budget for administrative support, coordination, and supervision of the PIC4C model.
– Community engagement and awareness: Funding for community education, screening campaigns, and outreach activities to promote the PIC4C model.
– Policy and advocacy: Resources for policy development, advocacy efforts, and stakeholder engagement to support the scale-up of the PIC4C model.
Please note that the provided cost items are general categories and may vary depending on the specific context and needs of the PIC4C model in Kenya.
The strength of evidence for this abstract is 7 out of 10. The evidence in the abstract is strong as it provides a detailed description of the study protocol and methods. The abstract clearly outlines the use of the RE-AIM framework in conducting a process evaluation of the Primary Health Integrated Care (PIC4C) project in Kenya. The methods include mixed methods data collection, such as secondary data analysis, observation, semi-structured interviews, and focus group discussions. The abstract also mentions the specific indicators and data sources that will be used to assess the reach, effectiveness, adoption, implementation, and maintenance of the PIC4C model. However, the abstract could be improved by providing more information on the sample size and selection criteria for study participants, as well as the analysis plan for the collected data.
Background: There has been a rapid increase in morbidity and mortality arising from non-communicable diseases (NCDs). The Academic Model Providing Access to Healthcare (AMPATH) program has established a chronic disease management program in collaboration with the Ministry of Health (MoH) in Kenya at over 150 health facilities in western Kenya. The primary health integrated care for chronic (PIC4C) disease project seeks to deliver preventive, promotive, and curative care for diabetes, hypertension, cervical and breast cancers at the primary health care level. We apply the RE-AIM framework to conduct a process evaluation of the integrated PIC4C model. This paper describes the protocol we are using in the PIC4C process evaluation planning and activities. Methods and Analysis: This evaluation utilizes clinic reports as well as primary data collected in two waves. Using mixed methods (secondary data, observation, semi-structured interviews, and focus group discussions), the process evaluation assesses the reach, effectiveness, adoption, implementation and maintenance of the PIC4C model in Busia and Trans Nzoia Kenya. The evaluation captures the PIC4C process, experiences of implementers and users, and the wishes of those using the PIC4C services. We will analyse our data across the RE-AIM dimensions using descriptive statistics and two-sample t-test to compare the mean scores for baseline and end line. Qualitative data will be analyzed thematically. Discussion: The process evaluation of the PIC4C model in Kenya allows implementers and users to reflect and question its implementation, uptake and maintenance. Our experiences thus far suggest practicable strategies to facilitate primary health care can benefit extensively from deliberate process evaluation of the programs undertaken. Furthermore, integrating the RE-AIM framework in the process evaluation of health programs is valuable due to its pragmatic and reporting usefulness.
The PIC4C model delivers preventive, promotive, and curative care for diabetes, hypertension, cervical and breast cancers at the primary health care level. It covers 40 and 33 health facilities in Busia and Trans Nzoia, respectively. Trans Nzoia County lies on the eastern side of Mount Elgon, in western Kenya. As per the 2009 census, Trans Nzoia County has a population of about 818,759 people, and 50% are male. There is one County referral hospital, five Sub-County hospitals, and seven health centers. Busia County is situated in the western part of Kenya and borders Uganda. The County covers an area of 1,694.5 square kilometers and has a population of 953,337 and 47.8% are males. Busia has one County referral hospital, six Sub-County hospitals, and fourteen health centers (14). Primary health facilities are the first level of contact between patients and the health system. They include Health Centers and Dispensaries. They provide ambulatory health services, which are generally preventive, and curative services mostly adapted to local needs. Common services provided as prioritized by the Kenyan government include education on health problems and how to prevent them, nutrition, maternal child healthcare, family planning, basic sanitation, immunization, treatment of common diseases and injuries, and provision of basic medication. Additionally, select primary health care facilities address dental health, mental health, HIV AIDS, and primary eye care. None of the health facilities involved in PIC4C included routine preventive and treatment care for cancers, hypertension, or diabetes. The overarching goal of the evaluation of the PIC4C project is to document the reach, effectiveness, adoption, implementation and sustainability of the integrated chronic care model with the aim of informing the ministry of health policy and scale up of the model. The PIC4C process evaluation uses mixed methods to ensure all aspects of the RE-AIM are well addressed. Supplementary Files 1–6 show the surveys, in-depth interviews and FGDs that were used to collect information from patients, health care workers, and decision makers. This paper describes the protocol we are using in the PIC4C process evaluation planning and activities. Data will be collected in two waves, 18 months apart, using mixed methods: secondary data, semi-structured interviews (SSIs), observation and focus group discussions (FGDs). The secondary data will involve analyses of routinely collected PIC4C care and project activity data including daily registers and the monthly reports. A SSI is a qualitative data generation method, which allows for a natural dialogue around a topic of interest. A predetermined list of questions is used to develop an interview schedule which is used to guide the discussion. There will be 48 SSI sessions involving County leaders including the CEC and Director Health, Non-communicable Diseases Coordinator). While the socio-demographics data will be collected using a structured questionnaire, the rest of the questions will be open-ended. The observation method generates qualitative data on specific activities of interest. In each County (Table 1), we will conduct 16 patient reception and vital signs assessments at health facility level. During these sessions, we will observe how patients are received upon arrival at the health clinic and how vital signs are assessed. The education and screening observation assessment will be done at the community level only during the community screening services led by the Community Health Promoters (CHPs). We aim to make 8 observations in each County. The FGD is a qualitative data collection method involving 6–12 participants with a trained moderator to guide the discussions around a particular topic. It is useful to gain a shared ideas and opinions among participants. A total of 20 FGD sessions will be held as follows (Table 2): Clients/patients 8 FGDs; health care providers (HCPs) 8 FGDs; community health promoters (CHPs) and community health volunteers (CHVs) 4 FGDs. Recruitment for Semi Structured Interviews (SSIs). CEC, County Executive Committee member for Health; HRIO, Health Records Information Officer; NCD, Non-Communicable Diseases; RH, Reproductive Health. Recruitment for Focus Group Discussions (FGDs). CHP, Community Health Volunteer; CHV, Community Health Worker; NCD, Non-communicable Disease; RH, Reproductive Health. The RE-AIM framework will be used and we aim to interview the same study participants at each time point and recruit additional participants where appropriate. In Table 3, the RE-AIM dimensions are applied to specific aspects of the PIC4C project. Indicators to show expected activities and/or outcomes are described. Data sources for required information and relevant data collection methods are also provided. For the reach, absolute number and characteristics of targets of the intervention are described. The absolute number of patients and trainees/mentees engaged will be reported, including their specific characteristics. The reach will also capture the number of people educated, screened, linked, treated and retained for each condition will be captured. Effectiveness covers the impact of the PIC4C interventions with special attention to numbers linked, treated and retained for each condition, and client feedback on the PIC4C services. The following changes will be expected among patients: a drop of 10 systolic blood pressure (SBP) or 5 diastolic blood pressure (DBP); % of diabetes mellitus (DM) patients getting to 60 years with blood pressure (BP) below 150/90 and patients <60 years with BP below 140/90. The study will also report the percentage of patients with a drop in hemoglobin A1c at end line for levels 2, 3, and 4. Retention rates for treatment of diabetes and hypertension will be calculated as number of patients seen 90 days from their last expected clinic visit divided by the total number of patients in care. Drug affordability will be measured, at baseline and end line, as the percentage of patients able to buy a whole month supply of prescribed select medicines. The audio recordings will be transcribed and consequently coded using NVivo or a similar software. Prior to analysis, a research team member will listen to random sections of the recordings and compare them to the transcripts to verify accurate transcription. Then, three coders will look at the research questions, field notes and transcripts to familiarize themselves with the data. They will be guided by the research questions to develop a codebook through segmentation of thoughts found in the raw text. Each segment will be labeled with a descriptive code and definition that captures the ideas therein. The descriptive code labels will be assessed and similar patterns will be grouped together and labeled thematically. Analytic memos will track decision-making among coders as the codebook and themes are refined through subsequent stages of inductive development of themes. Quotes from transcripts will be used to provide vivid illustrations of the findings.
Based on the provided information, here are some potential innovations that could be recommended to improve access to maternal health:
1. Mobile Health (mHealth) Solutions: Develop and implement mobile applications or text messaging services to provide pregnant women with important health information, reminders for prenatal visits, and access to teleconsultations with healthcare providers.
2. Telemedicine: Establish telemedicine platforms that allow pregnant women in remote or underserved areas to consult with healthcare professionals remotely, reducing the need for travel and improving access to prenatal care.
3. Community Health Workers (CHWs): Train and deploy CHWs to provide maternal health education, prenatal care, and postnatal support in communities where access to healthcare facilities is limited.
4. Maternal Health Vouchers: Implement voucher programs that provide pregnant women with financial assistance to cover the costs of prenatal care, delivery, and postnatal care, ensuring that cost is not a barrier to accessing essential maternal health services.
5. Transportation Support: Develop transportation initiatives, such as community-based transportation services or partnerships with ride-sharing companies, to ensure that pregnant women can easily access healthcare facilities for prenatal visits and delivery.
6. Maternal Health Clinics: Establish dedicated maternal health clinics or maternity waiting homes in underserved areas to provide comprehensive prenatal care, delivery services, and postnatal care in a safe and supportive environment.
7. Task-Shifting and Training: Train and empower non-specialist healthcare providers, such as nurses and midwives, to provide a wider range of maternal health services, including prenatal care, delivery, and postnatal care, to increase the availability of skilled care providers.
8. Health Information Systems: Implement electronic health records and data management systems to improve the tracking and monitoring of maternal health indicators, enabling better decision-making and resource allocation for maternal health services.
9. Public-Private Partnerships: Foster collaborations between public and private healthcare providers to expand access to maternal health services, leveraging the strengths and resources of both sectors to reach more pregnant women.
10. Maternal Health Education and Awareness Campaigns: Develop and implement targeted education and awareness campaigns to empower women with knowledge about the importance of prenatal care, nutrition, and healthy behaviors during pregnancy, as well as the available maternal health services in their communities.
These innovations aim to address barriers to accessing maternal health services, improve the quality of care, and ultimately reduce maternal morbidity and mortality rates.
AI Innovations Description
The recommendation to improve access to maternal health based on the described protocol is to implement the Primary Health Integrated Care for Chronic (PIC4C) model in health facilities in Kenya. The PIC4C model aims to deliver preventive, promotive, and curative care for diabetes, hypertension, cervical and breast cancers at the primary health care level. By integrating the PIC4C model into primary health facilities, maternal health services can be expanded to include routine preventive and treatment care for cancers, hypertension, and diabetes.
The implementation of the PIC4C model should focus on the following aspects:
1. Reach: Ensure that the intervention reaches the target population by providing care and treatment services for diabetes, hypertension, cervical and breast cancers to a large number of individuals. This can be achieved by increasing awareness and education about the services available at primary health facilities.
2. Effectiveness: Monitor the impact of the PIC4C interventions by tracking the number of individuals linked, treated, and retained for each condition. Evaluate client feedback on the quality of the services provided and measure changes in health outcomes, such as blood pressure control and cancer treatment outcomes.
3. Adoption: Encourage patients to adhere to clinic visits and promote uptake of the National Health Insurance Fund (NHIF) to ensure financial access to maternal health services. Train health care providers to offer care for the four conditions and ensure the implementation of PIC4C initiatives, such as information technology systems and the use of Ministry of Health tools.
4. Implementation: Ensure fidelity to the PIC4C activities, including timing and costs. Monitor the completeness and utilization of PIC4C interventions to ensure that they are delivered as intended.
5. Maintenance: Sustain the effectiveness of the PIC4C model at the individual level by providing ongoing care and treatment for diabetes, hypertension, cervical and breast cancers. Ensure the sustained delivery of the model at the institutional level by integrating PIC4C strategies into county budgets and health facility policies.
By implementing the PIC4C model, access to maternal health can be improved by providing comprehensive care and treatment for diabetes, hypertension, cervical and breast cancers at the primary health care level. This will help address the increasing morbidity and mortality arising from non-communicable diseases and contribute to better maternal health outcomes in Kenya.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:
1. Strengthening Primary Health Care Facilities: Enhance the capacity of primary health care facilities to provide comprehensive maternal health services, including antenatal care, skilled birth attendance, and postnatal care. This can be achieved by improving infrastructure, ensuring availability of essential equipment and supplies, and training healthcare providers.
2. Community-Based Maternal Health Programs: Implement community-based programs that focus on raising awareness about maternal health, promoting healthy behaviors during pregnancy, and facilitating access to maternal health services. This can involve training community health workers to provide basic maternal health services and conducting outreach programs in underserved areas.
3. Mobile Health (mHealth) Solutions: Utilize mobile technology to improve access to maternal health information and services. This can include mobile apps or text messaging platforms that provide educational resources, appointment reminders, and emergency helplines for pregnant women.
4. Transportation Support: Address transportation barriers by providing transportation vouchers or subsidies for pregnant women to access maternal health services. This can help overcome geographical barriers and ensure timely access to healthcare facilities.
To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:
1. Define the indicators: Identify specific indicators that reflect improved access to maternal health, such as the number of antenatal care visits, skilled birth attendance rates, or postnatal care coverage.
2. Collect baseline data: Gather data on the selected indicators before implementing the recommendations. This can involve reviewing existing data sources, conducting surveys, or analyzing health facility records.
3. Implement the recommendations: Roll out the recommended interventions, such as strengthening primary health care facilities, implementing community-based programs, or introducing mobile health solutions.
4. Monitor and collect data: Continuously monitor the implementation of the interventions and collect data on the selected indicators. This can involve tracking the number of women accessing maternal health services, conducting surveys to assess awareness and behavior change, or analyzing health facility records for service utilization.
5. Analyze the data: Use appropriate statistical methods to analyze the collected data and assess the impact of the recommendations on the selected indicators. This can involve comparing baseline data with post-intervention data to determine any changes or improvements.
6. Interpret the findings: Interpret the results of the analysis to understand the impact of the recommendations on improving access to maternal health. Identify any trends, patterns, or significant changes in the selected indicators.
7. Communicate the findings: Present the findings in a clear and concise manner to relevant stakeholders, such as policymakers, healthcare providers, and community members. Highlight the successes, challenges, and lessons learned from the implementation of the recommendations.
By following this methodology, stakeholders can gain insights into the effectiveness of the recommended interventions and make informed decisions to further improve access to maternal health.
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