{"doc_desc":{"title":"GECO_Study","idno":"DDI-KEN-APHRC-GEGO-2021-v1.0","producers":[{"name":"African Population and Health Research Center","abbreviation":"APHRC","affiliation":"","role":"DDI Documentation"}],"prod_date":"2024-09-02","version_statement":{"version":"Version 1.0 (September 2024)"}},"study_desc":{"title_statement":{"idno":"DDI-KEN-APHRC-GEGO-2021-v1.0","title":"Healthcare and Socio-economic Impacts of COVID-19 on Patients with Diabetes in Selected Counties in Kenya","sub_title":"GECO-Kenya","alt_title":"GECO-Kenya"},"authoring_entity":[{"name":"Gershim Asiki,MD,Phd","affiliation":"a. African Population and Health Research Center (APHRC)"}],"production_statement":{"producers":[{"name":"Richard Sanya, MBChB, MMed, PhD","affiliation":"a. African Population and Health Research Center (APHRC)","role":"Co-Investigator"},{"name":"Shukri Mohamed, PharmD, MPH, PhD","affiliation":"a. African Population and Health Research Center (APHRC)","role":"Co-Investigator"},{"name":"Maurine Ng\u2019oda, BSc, MPH","affiliation":"a. African Population and Health Research Center (APHRC)","role":"Co-Investigator"},{"name":"Lyagamula Kisia, BSc","affiliation":"a. African Population and Health Research Center (APHRC)","role":"Co-Investigator"},{"name":"Sally Mtenga, PhD","affiliation":"Ifakara Health Institute (IHI)","role":"Work Package Associate"},{"name":"Grace Mhalu, PhD","affiliation":"Ifakara Health Institute (IHI)","role":"Work Package Associate"},{"name":"Prof. Cindy Gray, PhD","affiliation":"University of Glasgow","role":"Work Package Associates"},{"name":"Prof. Francis Mayer, MD, PhD","affiliation":"University of Glasgow","role":"Work Package Associate"},{"name":"Christopher Bunn, PhD","affiliation":"University of Glasgow","role":"Work Package Associate"},{"name":"Elenor Gieve, PhD","affiliation":"University of Glasgow","role":"Work Package Associate"},{"name":"Muhuyi Erick, BSc","affiliation":"a. African Population and Health Research Center (APHRC)","role":"Data Documentation specialist"},{"name":"Bonface Ingumba,","affiliation":"a. African Population and Health Research Center (APHRC)","role":"Data Governance Officer"}],"copyright":"Copyright \u00a9 APHRC, 2024","funding_agencies":[{"name":"National Institute for Health Research","abbreviation":"NIHR","role":"Funder"}]},"series_statement":{"series_name":"Demographic and Health Survey [hh\/dhs]","series_info":"N\/A"},"version_statement":{"version_date":"2021-09-16","version_notes":"N\/A"},"study_info":{"keywords":[{"keyword":"COVID-19","vocab":"","uri":""},{"keyword":"Type 2 Diabetes","vocab":"","uri":""},{"keyword":"Socioeconomic impact","vocab":"","uri":""},{"keyword":"Healtcare access","vocab":"","uri":""},{"keyword":"Self management","vocab":"","uri":""},{"keyword":"Rural and Urban Kenya","vocab":"","uri":""},{"keyword":"Healt prividers","vocab":"","uri":""},{"keyword":"Health education","vocab":"","uri":""},{"keyword":"Economic burden","vocab":"","uri":""},{"keyword":"Social determinant of health","vocab":"","uri":""}],"abstract":"Background\n\nThe COVID-19 pandemic has resulted in socioeconomic hardships and disrupted healthcare for people with type 2 diabetes (T2D) particularly in sub-Saharan Africa. The project aims to explore the experiences of people with T2D and healthcare providers on managing T2D during COVID-19. \n\nMethods\nThis is a mixed methods cross-sectional study which will be delivered through five interrelated work packages (WPs).  In WP1 we will administer questionnaires (N=500) and in-depth interviews (N=30) to T2D patients to explore their experiences of healthcare access, and T2D self-management, socio-economic challenges and knowledge, attitude and practices related to COVID-19 in rural and urban Kenya. WP2 will use a desk review and field research on individual and societal economic burden of T2D. WP3 will explore the perspectives of local healthcare providers (N=30) on T2D management during COVID-19. WP4 will analyze policy landscape using desk review and key informant interviews to identify policy gaps and action for T2D during the pandemic. WP5 will synthesize evidence from WPs1-4 to develop policy recommendations and health education messages for T2D management during COVID-19 using a multi-stage participatory process. Quantitative analysis will determine differences between rural and urban settings using descriptive statistics and a hierarchical modelling using WHO framework on social determinants of health and wellbeing will be employed to explore factors associated with care disruption. A thematic content analysis will be used for qualitative data. For policy analysis Walt and Gilson's policy triangle framework, will be used.","coll_dates":[{"start":"2021-09-16","end":"2023-02-28","cycle":"18 months"}],"nation":[{"name":"Kenya","abbreviation":"KEN"},{"name":"","abbreviation":""}],"geog_coverage":"National: The study was conducted across four counties in Kenya: Nairobi, Kiambu, Nyeri, and Vihiga.","analysis_unit":"Individula;\n-People with type 2 diabetes (T2D) in rural and urban areas of Kenya.\n-Healthcare providers managing T2D patients.","universe":"The survey covered all individuals diagnosed with type 2 diabetes (T2D) receiving care at selected health facilities in Kenya, including both urban and rural residents, as well as healthcare providers involved in the management of T2D patients.","notes":"The scope of the survey include:\n- SOCIO-DEMOGRAPHIC VARIABLES: age, gender, place of current residence, marital status, education, occupation, diabetes history, household head religion.\n- PERCIEVED RISK AND ACTIONS IN RESPONSE TO COVID-19: Heard, close contact with infected person, symptoms, infromed by health worker, test outcomes, vaccinated.\n- HEALTHCARE RESOURCES USE AND EXPENDITURE: Place of blood sugar test, changes, how the test was done, how often, cost of test, mode of payment during COVID and pre-COVID period.\n- MEDICATION: type of medication, medication prescribed, use of medication, frequency, cost of medication, ability to obtain all medication, reasons for not being able to afford.\n- HOSPITAL ADMISIONS AND OUTPATIENT VISITS: hospital and outpatient visits, admisions, number of admisions, number of nights spent, type of hospital facility, reasons for admision, cover for medication during and before COVID.\n- NON-HOSPITAL VISITS: Healthcare recieved, non-hospital visits to the special doctor, primary care doctor, nurse, pharmacit, health educator, medical assistant, community health worker and traditional healer or faith dwelling, the number of visits, type of institution, total fees, charges, reasons for visiting, the cover for medication during and after COVID-19 period.\n- DIABETES SELF-CARE: Factors affecting diabetes self-care.\n- ACCESS TO HEALTHCARE: Type and level of healthcare facilityl, succesful visits, phone and in-person consultations, reason for not seeing the healthcare providers, journey to the facility, mode of transport, paid for transport during and before COVID-19.\n- IMPACT OF COVID-19 ON INCOME, IMPOVERISHMENT AND AVAILABILITY OF FOOD: health insurance cover, type, reasons for joining an insurance scheme, income, cost of healthcare, effect of COVID-19, laws on access to healthcare, household necesities, financial hardship during and pre-COVID period.\n- IMPACT OF COVID ON PRODUCTIVITY: Days, mised work, work at home or school, changes in activities during COVID and pre-COVID period.\n- IMPACT OF COVID ON FORMAL AND INFORMAL CARE: Hire formal and infromal caregiver, changes, amount paid, caregiving days spent before and during COVID.","study_scope":"The scope of the survey include:\n- SOCIO-DEMOGRAPHIC VARIABLES: age, gender, place of current residence, marital status, education, occupation, diabetes history, household head religion.\n- PERCIEVED RISK AND ACTIONS IN RESPONSE TO COVID-19: Heard, close contact with infected person, symptoms, infromed by health worker, test outcomes, vaccinated.\n- HEALTHCARE RESOURCES USE AND EXPENDITURE: Place of blood sugar test, changes, how the test was done, how often, cost of test, mode of payment during COVID and pre-COVID period.\n- MEDICATION: type of medication, medication prescribed, use of medication, frequency, cost of medication, ability to obtain all medication, reasons for not being able to afford.\n- HOSPITAL ADMISIONS AND OUTPATIENT VISITS: hospital and outpatient visits, admisions, number of admisions, number of nights spent, type of hospital facility, reasons for admision, cover for medication during and before COVID.\n- NON-HOSPITAL VISITS: Healthcare recieved, non-hospital visits to the special doctor, primary care doctor, nurse, pharmacit, health educator, medical assistant, community health worker and traditional healer or faith dwelling, the number of visits, type of institution, total fees, charges, reasons for visiting, the cover for medication during and after COVID-19 period.\n- DIABETES SELF-CARE: Factors affecting diabetes self-care.\n- ACCESS TO HEALTHCARE: Type and level of healthcare facilityl, succesful visits, phone and in-person consultations, reason for not seeing the healthcare providers, journey to the facility, mode of transport, paid for transport during and before COVID-19.\n- IMPACT OF COVID-19 ON INCOME, IMPOVERISHMENT AND AVAILABILITY OF FOOD: health insurance cover, type, reasons for joining an insurance scheme, income, cost of healthcare, effect of COVID-19, laws on access to healthcare, household necesities, financial hardship during and pre-COVID period.\n- IMPACT OF COVID ON PRODUCTIVITY: Days, mised work, work at home or school, changes in activities during COVID and pre-COVID period.\n- IMPACT OF COVID ON FORMAL AND INFORMAL CARE: Hire formal and infromal caregiver, changes, amount paid, caregiving days spent before and during COVID."},"method":{"data_collection":{"sampling_procedure":"500 patients with T2D were recruited from health facilities across four counties (Nairobi, Kiambu, Nyeri, Vihiga). The sample was selected based on existing patient databases from these facilities, ensuring representation from both urban and rural populations.","sampling_deviation":"N\/A","coll_mode":"Face-to-face [f2f]","research_instrument":"The questionnaires were the T2D patient experience and Healthcare providers perspective questionnaires. \n\nThe T2D patient experience questionnaire assessed the patients expereince, acess to healthcare, self-management practices and the challenges they faced during and before COVID-19. The healthcare providers questionnaire assessed the view on how the healthcare managed the patients with type 2 diabetes, the challenges and strategies employed.\n\nThe questionnaires were written in English and Swahili to accomodate the linguistic diversity of the respondents.\n\nThe questionnaires were developed based on the standard model questionnaire for chronic disease management, adding elements from previous studies on diabetes care. The process was reviewed by stakeholders and feedback was provided on the draft version. The questionnaires were piloted prior to the main study to ensure clarity and relevance.\n \nAll questionnaire and module are provided as external resources.","act_min":"Enumerators were organized in teams that included experienced research assistants. Each team had supervisors overseeing data collection. The main roles of the supervisors included ensuring data quality and adherence to protocols. There was no specific mention of upper management visits to the field.","weight":"N\/A","cleaning_operations":"Data was collected electronically using the SurveyCTO program. After each interview, the data was synchronized to the APHRC servers. Data quality checks included spot checks and automated routines to ensure completeness and consistency. There was no specific mention of hot deck or cold deck techniques used for data editing.","method_notes":"N\/A"},"analysis_info":{"response_rate":"The sample size was adjusted for non-response by oversampling by 30%, leading to a total sample size of 500.","sampling_error_estimates":"N\/A"}},"data_access":{"dataset_use":{"contact":[{"name":"African Population and Health Research Center(APHRC)","affiliation":"","email":"datarequests@aphrc.org","uri":"https:\/\/microdataportal.aphrc.org\/index.php\/catalog"}],"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n- the Identification of the Primary Investigator\n- the title of the survey (including country, acronym and year of implementation)\n- the survey reference number\n- the source and date of download","conditions":"Data access agreement\nThe representative of the Receiving Organization agrees to comply with the following conditions:\n\n1. Access to the restricted data will be limited to the Lead Researcher and other members of the research team listed in this request.\n2. Copies of the restricted data or any data created on the basis of the original data will not be copied or made available to anyone other than those mentioned in this Data Access Agreement, unless formally authorized by the Data Archive.\n3. The data will only be processed for the stated statistical and research purpose. They will be used for solely for reporting of aggregated information, and not for investigation of specific individuals or organizations. Data will not in any way be used for any administrative, proprietary or law enforcement purposes.\n4. The Lead Researcher must state if it is their intention to match the restricted microdata with any other micro-dataset. If any matching is to take place, details must be provided of the datasets to be matched and of the reasons for the matching. Any datasets created as a result of matching will be considered to be restricted and must comply with the terms of this Data Access Agreement.\n5. The Lead Researcher undertakes that no attempt will be made to identify any individual person, family, business, enterprise or organization. If such a unique disclosure is made inadvertently, no use will be made of the identity of any person or establishment discovered and full details will be reported to the Data Archive. The identification will not be revealed to any other person not included in the Data Access Agreement.\n6. The Lead Researcher will implement security measures to prevent unauthorized access to licensed microdata acquired from the Data Archive. The microdata must be destroyed upon the completion of this research, unless the Data Archive obtains satisfactory guarantee that the data can be secured and provides written authorization to the Receiving Organization to retain them. Destruction of the microdata will be confirmed in writing by the Lead Researcher to the Data Archive.\n7. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the Data Archive will cite the source of data in accordance with the citation requirement provided with the dataset.\n8. An electronic copy of all reports and publications based on the requested data will be sent to the Data Archive.\n9. The original collector of the data, the Data Archive, and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.\n10. This agreement will come into force on the date that approval is given for access to the restricted dataset and remain in force until the completion date of the project or an earlier date if the project is completed ahead of time.\n11. If there are any changes to the project specification, security arrangements, personnel or organization detailed in this application form, it is the responsibility of the Lead Researcher to seek the agreement of the Data Archive to these changes. Where there is a change to the employer organization of the Lead Researcher this will involve a new application being made and termination of the original project.\n12. Breaches of the agreement will be taken seriously and the Data Archive will take action against those responsible for the lapse if willful or accidental. Failure to comply with the directions of the Data Archive will be deemed to be a major breach of the agreement and may involve recourse to legal proceedings. The Data Archive will maintain and share with partner data archives a register of those individuals and organizations which are responsible for breaching the terms of the Data Access Agreement and will impose sanctions on release of future data to these parties.","disclaimer":"Disclaimer: The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}}}