Projects
Background
Cardio-Kidney-Metabolic (CKM) disease is an integrated health concept that recognizes the close relationship between cardiovascular disease (CVD), chronic kidney disease (CKD), type 2 diabetes mellitus (T2DM), obesity, hypertension, and other metabolic disorders. These conditions frequently coexist and interact through shared biological pathways, resulting in accelerated disease progression and an increased risk of cardiovascular events, kidney failure, disability, and premature mortality. In 2023, the American Heart Association (AHA) introduced the CKM health framework to promote a comprehensive approach to the prevention, early detection, risk stratification, and management of these interconnected conditions (Ndumele et al., 2023).
The global burden of CKM disease continues to increase due to population ageing, urbanization, unhealthy diets, physical inactivity, tobacco use, and obesity. According to the World Health Organization (WHO), non-communicable diseases (NCDs) account for approximately 74% of all deaths worldwide, with cardiovascular diseases responsible for the largest proportion. Diabetes and chronic kidney disease also contribute substantially to morbidity, mortality, and healthcare expenditure, particularly in low- and middle-income countries (WHO, 2023).
In Kenya, the prevalence of hypertension, diabetes mellitus, obesity, and chronic kidney disease has increased over the past decade. This epidemiological transition has placed significant pressure on the healthcare system, which continues to face challenges related to early diagnosis, continuity of care, long-term patient monitoring, and coordinated multidisciplinary management. Many patients present with multiple coexisting conditions requiring comprehensive assessment, regular follow-up, and timely clinical interventions.
Effective management of CKM disease depends on the availability of complete, accurate, and standardized clinical information. Healthcare providers require access to longitudinal patient data, including demographic characteristics, medical history, physical examination findings, laboratory investigations, medications, imaging studies, and clinical outcomes. Such information supports clinical decision-making, monitoring of disease progression, evaluation of treatment effectiveness, and identification of patients at increased risk of adverse outcomes.
However, routine clinical documentation in many healthcare facilities remains fragmented. Patient information is often distributed across paper records, laboratory reports, imaging reports, pharmacy records, and independent electronic systems that do not communicate with one another. This fragmentation contributes to incomplete documentation, duplication of data, poor continuity of care, and difficulties in monitoring patients over time. It also limits the ability of healthcare facilities to conduct clinical audits, measure quality indicators, evaluate outcomes, and generate evidence for service improvement.
Clinical registries have become an important component of modern healthcare systems because they provide a structured mechanism for collecting standardized information on patients with specific diseases or health conditions. According to Gliklich, Leavy, and Dreyer (2020), patient registries are organized systems that use observational methods to collect uniform data for evaluating specified outcomes among defined populations. Registry data support routine clinical care, quality improvement, surveillance, health services research, and policy development.
Digital clinical registries provide several advantages over traditional paper-based systems. They improve data completeness, minimize transcription errors, facilitate real-time data entry, enhance accessibility of patient information, support automated reporting, and enable longitudinal follow-up. Digital registries can also improve monitoring of quality indicators, facilitate multidisciplinary care, and generate reliable data for clinical research and healthcare planning (WHO, 2021).
Although disease registries have been successfully implemented for cardiovascular disease, renal disease, diabetes, cancer, and stroke in many countries, there is currently no standardized Digital Cardio-Kidney-Metabolic Clinical Registry specifically designed for integrated CKM care in Coastal Kenya. Existing documentation systems generally focus on individual diseases rather than the broader CKM continuum and therefore do not adequately capture the complexity of patients living with multiple interconnected conditions.
The development of a Digital Cardio-Kidney-Metabolic Clinical Registry represents an opportunity to strengthen routine clinical documentation by providing a standardized platform for collecting comprehensive patient information across the CKM spectrum. Such a registry would support continuity of care, improve data quality, facilitate monitoring of patient outcomes, strengthen quality improvement initiatives, and provide a sustainable foundation for future registry-based clinical and public health research.
This study therefore proposes the development, pilot implementation, and evaluation of a Digital Cardio-Kidney-Metabolic Clinical Registry for routine care in Coastal Kenya. The registry will be designed to capture standardized clinical information, support routine patient management, and improve the quality and accessibility of health information. The pilot evaluation will assess the registry's feasibility, usability, data quality, completeness, and acceptability among healthcare workers during routine clinical practice. The findings will provide evidence to guide future scale-up of CKM registries within Kenya and contribute to strengthening digital health systems for the management of non-communicable diseases.
Problem Statement
Cardio-Kidney-Metabolic (CKM) disease is an emerging public health challenge characterized by the coexistence of cardiovascular disease, chronic kidney disease, diabetes mellitus, hypertension, obesity, and other metabolic disorders. These conditions require lifelong follow-up, multidisciplinary management, and continuous monitoring to reduce disease progression, complications, hospitalization, and premature mortality (Ndumele et al., 2023).
Despite the increasing burden of CKM disease in Kenya, routine clinical documentation remains fragmented and inconsistent. In many health facilities, patient information is recorded using paper-based records or multiple non-integrated electronic systems, resulting in incomplete documentation, duplication of information, poor continuity of care, and limited longitudinal follow-up. Consequently, healthcare providers may not have access to comprehensive patient information required for effective clinical decision-making, monitoring of disease progression, or evaluation of treatment outcomes.
The absence of a standardized Digital Cardio-Kidney-Metabolic Clinical Registry further limits the ability of healthcare facilities to monitor quality of care, measure clinical performance indicators, conduct routine clinical audits, and generate reliable evidence for planning and service improvement. In addition, the lack of standardized patient-level data constrains clinical research and reduces opportunities to evaluate the epidemiology, management, and outcomes of CKM disease in Kenya.
Although digital health technologies are increasingly being adopted to strengthen health information systems, there is limited evidence on the development and implementation of integrated digital clinical registries specifically designed for CKM care in Kenya. Establishing a standardized Digital Cardio-Kidney-Metabolic Clinical Registry may improve the quality of routine clinical documentation, facilitate longitudinal patient follow-up, support multidisciplinary care, and strengthen the use of clinical data for quality improvement and future research.
The burden of cardiovascular disease, diabetes mellitus, chronic kidney disease, hypertension, and obesity continues to increase in Kenya, creating a growing need for integrated systems that support long-term patient management. Effective management of CKM disease depends on accurate, complete, and timely clinical information that enables healthcare providers to monitor disease progression, evaluate treatment outcomes, and coordinate multidisciplinary care.
A Digital Cardio-Kidney-Metabolic Clinical Registry will provide a standardized platform for collecting, storing, and managing patient information throughout the continuum of care. By improving the completeness and quality of clinical documentation, the registry will support evidence-based clinical decision-making, facilitate continuity of care, and strengthen routine monitoring of patient outcomes.
The registry will also enhance quality improvement by enabling healthcare facilities to monitor key performance indicators, conduct clinical audits, identify gaps in service delivery, and evaluate adherence to clinical guidelines. Furthermore, it will establish a sustainable digital database that can support future observational studies, implementation research, and registry-based clinical investigations involving electrocardiography, echocardiography, laboratory monitoring, imaging, and long-term CKM outcomes.
At the health system level, the findings from this study will contribute to strengthening digital health implementation and health information systems for non-communicable diseases. The registry may serve as a scalable model for integrated CKM care in other counties and support national efforts to improve chronic disease surveillance, healthcare planning, and resource allocation. The study therefore has the potential to benefit patients, healthcare providers, health managers, researchers, and policymakers by improving the availability and use of high-quality clinical information for CKM care.
Can a Digital Cardio-Kidney-Metabolic Clinical Registry be developed, pilot implemented, and successfully evaluated to support routine patient care in Coastal Kenya?
To develop, pilot implement, and evaluate a Digital Cardio-Kidney-Metabolic Clinical Registry for routine care in Coastal Kenya.
Cardio-Kidney-Metabolic (CKM) disease is a recently introduced framework that recognizes the biological and clinical interaction between cardiovascular disease (CVD), chronic kidney disease (CKD), type 2 diabetes mellitus (T2DM), obesity, hypertension, and related metabolic disorders. The American Heart Association (AHA) proposed the CKM framework to promote integrated prevention, early detection, risk assessment, and multidisciplinary management of these interconnected conditions (Ndumele et al., 2023).
The CKM framework recognizes that dysfunction in one organ system frequently accelerates disease progression in others. For example, diabetes mellitus increases the risk of chronic kidney disease and cardiovascular disease, while chronic kidney disease independently increases cardiovascular morbidity and mortality. Similarly, obesity contributes to hypertension, insulin resistance, dyslipidaemia, and chronic inflammation, creating a cycle of progressive organ damage.
The integrated nature of CKM disease requires coordinated clinical management supported by comprehensive patient information collected throughout the continuum of care.
Non-communicable diseases are responsible for approximately three-quarters of global deaths, with cardiovascular diseases remaining the leading cause of mortality worldwide (WHO, 2023). The prevalence of hypertension, diabetes, obesity, and chronic kidney disease continues to increase in sub-Saharan Africa due to population growth, urbanization, dietary changes, physical inactivity, tobacco use, and ageing populations.
Kenya is experiencing a similar epidemiological transition. The prevalence of hypertension and diabetes has increased substantially over the last decade, while obesity and chronic kidney disease are becoming increasingly common. These conditions frequently coexist, resulting in complex patients who require long-term multidisciplinary management.
The growing burden of CKM disease has increased demand for healthcare services while highlighting the need for integrated patient management systems capable of supporting longitudinal follow-up.
Clinical registries are organized systems designed to collect standardized information on patients with specific diseases or health conditions for predetermined clinical, scientific, or policy purposes (Gliklich et al., 2020).
Unlike routine hospital records, registries collect predefined data elements using standardized definitions, thereby improving consistency and comparability of information across patients and healthcare facilities.
Disease registries have been widely used in cardiovascular disease, chronic kidney disease, diabetes, stroke, cancer, trauma, and congenital disorders. Registry data support:
Clinical care
Disease surveillance
Quality improvement
Clinical audit
Performance monitoring
Health services research
Guideline implementation
Policy formulation
Several international registries have demonstrated improvements in adherence to clinical guidelines, patient outcomes, and quality of care through continuous monitoring and feedback.
Digital health refers to the application of information and communication technologies to improve healthcare delivery, health information management, and health system performance (WHO, 2021).
Digital clinical registries represent one of the most important applications of digital health because they enable:
Standardized electronic data collection
Real-time data entry
Longitudinal patient tracking
Automated reporting
Clinical decision support
Monitoring of quality indicators
Secure storage of patient information
Data sharing across healthcare teams
Compared with paper-based systems, digital registries improve data completeness, reduce transcription errors, enhance accessibility of patient records, and facilitate continuous monitoring of patient outcomes.
The WHO Global Strategy on Digital Health emphasizes strengthening health information systems through digital technologies to improve healthcare quality, efficiency, and equity (WHO, 2021).
Several disease registries exist for cardiovascular disease, diabetes mellitus, chronic kidney disease, and heart failure. However, these registries generally focus on individual diseases rather than the integrated CKM continuum.
Because CKM disease represents an interaction between multiple chronic conditions, separate disease registries may not adequately capture the complexity of patient care.
An integrated CKM Clinical Registry has the potential to collect comprehensive patient information within a single platform, allowing healthcare providers to monitor cardiovascular, renal, and metabolic health simultaneously.
Such a registry can support multidisciplinary care while facilitating monitoring of disease progression, treatment outcomes, and quality indicators.
Developing a registry alone is insufficient; its performance must also be evaluated to determine whether it is suitable for routine clinical use.
Evaluation commonly includes assessment of:
Data completeness
Data accuracy
Usability
Feasibility
Acceptability
User satisfaction
Timeliness
Sustainability
Implementation science frameworks, including RE-AIM, provide structured approaches for evaluating healthcare innovations. RE-AIM examines five domains:
Reach
Effectiveness
Adoption
Implementation
Maintenance
These domains provide comprehensive information regarding the practical use and long-term sustainability of digital health interventions.
Although numerous disease-specific registries have been developed internationally, there is limited evidence regarding integrated Digital Cardio-Kidney-Metabolic Clinical Registries in low- and middle-income countries.
In Kenya, most healthcare facilities continue to rely on fragmented documentation systems that do not adequately support integrated CKM care. Published literature describing the development, pilot implementation, and evaluation of CKM clinical registries is scarce.
Consequently, healthcare providers have limited access to standardized longitudinal data required for monitoring patient outcomes, conducting quality improvement initiatives, and supporting evidence-based decision-making.
Developing and evaluating a Digital Cardio-Kidney-Metabolic Clinical Registry in Coastal Kenya will address this gap by providing an integrated digital platform capable of improving clinical documentation, continuity of care, data quality, and future registry-based research.
The study is based on the premise that standardized digital clinical documentation improves the quality of patient care and health information.
Inputs
Literature review
Stakeholder engagement
Clinical guidelines
Digital health expertise
Information technology infrastructure
↓
Processes
Identification of the minimum CKM dataset
Registry design
Software development
Healthcare worker training
Pilot implementation
↓
Outputs
Functional Digital CKM Clinical Registry
Standardized electronic clinical documentation
High-quality patient data
Registry reports and dashboards
↓
Outcomes
Improved data completeness
Improved data quality
Better continuity of care
Enhanced multidisciplinary management
Improved monitoring of CKM patients
↓
Long-Term Impact
Strengthened routine CKM care
Improved quality improvement programmes
Enhanced digital health systems
Sustainable registry-based research platform
Better patient outcomes
This study will employ a mixed-methods implementation study comprising three sequential phases: (i) development of a Digital Cardio-Kidney-Metabolic (CKM) Clinical Registry, (ii) pilot implementation of the registry in selected health facilities, and (iii) evaluation of the registry during routine clinical care. The study will combine quantitative and qualitative methods to evaluate the performance and implementation of the registry.
The study will be conducted in selected health facilities providing Cardio-Kidney-Metabolic services in Coastal Kenya. These facilities offer care for patients with hypertension, diabetes mellitus, chronic kidney disease, obesity, dyslipidaemia, and cardiovascular diseases.
The study population will comprise:
Adult patients (≥18 years) diagnosed with one or more Cardio-Kidney-Metabolic conditions and receiving care at participating facilities.
Healthcare professionals involved in CKM care, including physicians, clinical officers, nurses, nutritionists, pharmacists, laboratory personnel, and health records officers who will use the registry.
Participants will be eligible if they:
Are aged 18 years or older.
Have at least one confirmed Cardio-Kidney-Metabolic condition.
Attend one of the participating health facilities during the study period.
Provide written informed consent where required.
Healthcare workers will be eligible if they:
Are directly involved in CKM patient management.
Have received training on the registry.
Consent to participate in the evaluation.
Patients who decline participation or have insufficient clinical information for registration will be excluded. Healthcare workers not directly involved in registry use will not participate in the evaluation.
This phase will involve the design and development of the Digital CKM Clinical Registry.
Activities will include:
Comprehensive literature review.
Review of national and international CKM guidelines.
Review of existing cardiovascular, diabetes, and kidney disease registries.
Identification of the minimum CKM dataset.
Development of standardized data definitions.
Development of electronic data collection forms.
Database design.
User interface development.
Development of a registry user manual.
Development of standard operating procedures (SOPs).
The registry will be introduced into routine clinical practice in selected health facilities.
Activities will include:
Installation of the registry.
Training healthcare workers.
Registration of eligible CKM patients.
Routine electronic data entry.
Technical support and supervision.
Monitoring of registry utilization.
The pilot registry will be evaluated using the RE-AIM Implementation Framework.
The evaluation will assess:
Number of participating facilities.
Number of trained healthcare workers.
Number and proportion of eligible CKM patients enrolled.
Completeness of clinical documentation.
Data quality.
Availability of longitudinal patient information.
Improvement in routine documentation.
Proportion of clinicians routinely using the registry.
Frequency of registry use.
Uptake across different clinical departments.
Ease of use.
Time required for patient registration.
Technical challenges encountered.
Fidelity to registry procedures.
Continued use of the registry during the pilot period.
Intention to continue using the registry after completion of the study.
Recommendations for scale-up.
The registry will collect standardized information including:
Patient identification number
Age
Sex
Residence
Occupation
Diagnosis
Medical history
Smoking status
Alcohol use
Physical activity
Family history
Height
Weight
Body Mass Index
Waist circumference
Blood pressure
Heart rate
Respiratory rate
Oxygen saturation
Blood glucose
HbA1c
Serum creatinine
Estimated glomerular filtration rate (eGFR)
Lipid profile
Urine albumin
Electrocardiography (ECG)
Echocardiography
Spirometry
Carotid duplex ultrasound
Other clinically indicated investigations
Current medications
Lifestyle interventions
Follow-up visits
Hospital admissions
Cardiovascular events
Disease progression
Mortality (where applicable)
Data will be entered directly into the Digital CKM Clinical Registry during routine patient consultations using standardized electronic data collection forms.
Healthcare workers will receive training before implementation to ensure consistency in data entry.
Routine data quality checks will be conducted throughout the study period.
Data quality will be maintained through:
Standardized data definitions.
Mandatory electronic fields.
Validation rules within the registry.
User training.
Routine supervision.
Periodic data quality audits.
Double-checking selected patient records against source documents.
Quantitative data will be analysed using SPSS version 29 (or equivalent statistical software).
Descriptive statistics will include:
Frequencies
Percentages
Means
Standard deviations
Medians
Interquartile ranges
Registry performance indicators such as completeness, adoption, and usability will be summarized using descriptive statistics.
Qualitative data from interviews or questionnaires will be analysed using thematic analysis to identify facilitators, barriers, and recommendations for improving registry implementation.
Ethical approval will be obtained from the appropriate Institutional Research Ethics Committee before commencement of the study.
Administrative approval will also be obtained from participating health facilities.
Participants will provide informed consent where required. Patient confidentiality will be maintained through the use of unique registry identification numbers, password-protected databases, and restricted access to identifiable information.
The registry will comply with applicable national data protection requirements and institutional policies governing the collection, storage, and use of health information.
Study findings will be disseminated through:
Submission of a Master's dissertation.
Presentations at scientific conferences.
Publication in peer-reviewed journals.
Reports to participating health facilities.
Dissemination to relevant stakeholders within the Ministry of Health and other partners to inform future implementation and scale-up of CKM registries.
The study is expected to achieve the following outcomes:
Development of a standardized Digital Cardio-Kidney-Metabolic (CKM) Clinical Registry for routine patient care.
Identification and documentation of a minimum dataset for CKM patient management in Kenya.
Development of standardized electronic clinical documentation forms for CKM care.
Successful pilot implementation of the registry in selected health facilities in Coastal Kenya.
Improved completeness, consistency, and quality of routine CKM clinical documentation.
Improved longitudinal follow-up of CKM patients through standardized electronic records.
Evidence on the usability, feasibility, acceptability, and implementation of the registry among healthcare workers.
Recommendations for scaling up the registry to other healthcare facilities in Kenya.
The proposed study is expected to contribute significantly to clinical practice, digital health, health systems strengthening, and future research.
The registry will improve the quality of routine clinical documentation by providing standardized electronic records for patients with Cardio-Kidney-Metabolic disease. Improved documentation will facilitate continuity of care, multidisciplinary management, monitoring of disease progression, and evidence-based clinical decision-making.
The study will contribute to the implementation of digital health technologies by demonstrating the feasibility of a disease-specific electronic clinical registry in routine healthcare settings. It will provide practical evidence on the implementation of digital health solutions for chronic disease management in resource-limited settings.
The registry will strengthen health information systems by improving data quality, standardization, and accessibility. Reliable patient-level information will support quality improvement programmes, clinical audits, service planning, and performance monitoring.
The registry will establish a sustainable database that can support future observational studies, implementation research, clinical audits, and registry-based studies on cardiovascular, kidney, and metabolic diseases.
The findings will provide evidence that may inform national efforts to strengthen digital health systems and improve the management of non-communicable diseases. The registry may serve as a model for implementation in other counties and healthcare facilities.
The study may encounter several limitations.
The pilot implementation will be conducted in selected health facilities in Coastal Kenya; therefore, the findings may not be immediately generalizable to all healthcare settings in Kenya.
Variations in digital literacy among healthcare workers may influence registry adoption and usability during the pilot phase.
Internet connectivity and availability of computer equipment may affect real-time data entry in some facilities.
Because the study focuses on pilot implementation, it may not assess long-term sustainability or long-term patient outcomes.
Measures such as user training, technical support, standardized operating procedures, and routine supervision will be implemented to minimize these limitations.
| Activity | Month 1 | Month 2 | Month 3 | Month 4 | Month 5 | Month 6 |
|---|---|---|---|---|---|---|
| Literature review | ✓ | ✓ | ||||
| Protocol development | ✓ | ✓ | ||||
| Ethical approval | ✓ | ✓ | ||||
| Registry design | ✓ | ✓ | ||||
| Registry development | ✓ | ✓ | ||||
| Training of healthcare workers | ✓ | |||||
| Pilot implementation | ✓ | ✓ | ||||
| Data quality monitoring | ✓ | ✓ | ||||
| Registry evaluation | ✓ | |||||
| Data analysis | ✓ | |||||
| Report writing | ✓ | |||||
| Dissemination | ✓ |
| Budget Item | Estimated Cost (KES) |
|---|---|
| Literature review | 20,000 |
| Stakeholder consultation meetings | 30,000 |
| Registry design and software development | 70,000 |
| Training of healthcare workers | 40,000 |
| Data collection and monitoring | 30,000 |
| Internet and communication | 10,000 |
| Local transport | 15,000 |
| Data analysis | 15,000 |
| Printing and stationery | 10,000 |
| Report production and dissemination | 10,000 |
| Contingency | 20,000 |
| Total Estimated Budget | 250,000 |
Gliklich, R. E., Leavy, M. B., & Dreyer, N. A. (2020). Registries for Evaluating Patient Outcomes: A User's Guide (4th ed.). Agency for Healthcare Research and Quality.
Institute of Medicine. (2012). Digital Infrastructure for the Learning Health System: The Foundation for Continuous Improvement in Health and Health Care. National Academies Press.
Ministry of Health Kenya. (2023). Kenya Digital Health Strategy 2023–2028. Nairobi, Kenya.
Ndumele, C. E., Rangaswami, J., Chow, S. L., et al. (2023). Cardiovascular-Kidney-Metabolic Health: A Presidential Advisory From the American Heart Association. Circulation, 148(20), e333–e355.
Proctor, E., Silmere, H., Raghavan, R., et al. (2011). Outcomes for implementation research: Conceptual distinctions, measurement challenges, and research agenda. Administration and Policy in Mental Health and Mental Health Services Research, 38(2), 65–76.
World Health Organization. (2021). Global Strategy on Digital Health 2020–2025. Geneva: World Health Organization.
World Health Organization. (2023). Noncommunicable Diseases Progress Monitor 2023. Geneva: World Health Organization.
Appendix I: Minimum Cardio-Kidney-Metabolic Dataset
Appendix II: Digital CKM Clinical Registry Data Dictionary
Appendix III: Patient Registration Form
Appendix IV: Healthcare Worker Questionnaire
Appendix V: Registry Usability Evaluation Questionnaire
Appendix VI: Standard Operating Procedures for Registry Use
Appendix VII: Participant Information Sheet and Informed Consent Form
Appendix VIII: Conceptual Framework
Appendix IX: Data Flow Diagram
Appendix X: Registry Screen Layouts
The conceptual framework illustrates how the development and implementation of a Digital Cardio-Kidney-Metabolic (CKM) Clinical Registry is expected to improve clinical documentation, support routine patient care, and strengthen health information systems. The framework is based on the premise that standardized electronic data collection improves data quality, facilitates longitudinal patient follow-up, and enhances evidence-based clinical decision-making.
HEALTH SYSTEM NEED
Increasing burden of CKM disease
Fragmented clinical documentation
Lack of standardized patient data
Poor continuity of care
Limited quality improvement
Limited research data
│
▼
DEVELOPMENT PHASE
Literature review
Stakeholder consultation
Clinical guidelines
Minimum CKM dataset
Registry design
Software development
│
▼
DIGITAL CKM CLINICAL REGISTRY
│
▼
PILOT IMPLEMENTATION
Training healthcare workers
Patient registration
Electronic documentation
Routine clinical use
Data quality monitoring
│
▼
REGISTRY EVALUATION
(RE-AIM Implementation Framework)
Reach
Effectiveness
Adoption
Implementation
Maintenance
│
▼
EXPECTED OUTCOMES
Improved documentation
Improved data quality
Better continuity of care
Better multidisciplinary care
Improved clinical decision-making
Better quality improvement
Registry-based research
│
▼
LONG-TERM IMPACT
Stronger Digital Health Systems
Improved CKM care
Better patient outcomes
National scale-upThe study begins by identifying the need for an integrated CKM registry due to fragmented documentation and the increasing burden of CKM disease. The registry will be developed using evidence from the literature, stakeholder consultations, and clinical guidelines to define a standardized minimum dataset. After development, the registry will be pilot implemented in selected health facilities and evaluated using the RE-AIM implementation framework. Successful implementation is expected to improve data quality, continuity of care, and clinical decision-making while establishing a sustainable platform for quality improvement and future research.
| Variable | Type |
|---|---|
| Registry ID | Auto-generated |
| Hospital Number | Text |
| National ID | Text |
| Date of Registration | Date |
| Clinic Site | Text |
| Variable |
|---|
| Age |
| Sex |
| Residence |
| Education |
| Occupation |
| Marital Status |
| Variable |
|---|
| Smoking |
| Alcohol |
| Physical Activity |
| Diet |
| Family History |
| Variable |
|---|
| Hypertension |
| Diabetes Mellitus |
| Chronic Kidney Disease |
| Obesity |
| Dyslipidaemia |
| Heart Failure |
| Coronary Artery Disease |
| Stroke |
| Peripheral Artery Disease |
| Variable |
|---|
| Weight |
| Height |
| BMI |
| Waist Circumference |
| Variable |
|---|
| Blood Pressure |
| Heart Rate |
| Respiratory Rate |
| Oxygen Saturation |
| Variable |
|---|
| Fasting Blood Glucose |
| HbA1c |
| Serum Creatinine |
| eGFR |
| Urine Albumin |
| Total Cholesterol |
| LDL Cholesterol |
| HDL Cholesterol |
| Triglycerides |
| Variable |
|---|
| ECG Findings |
| Echocardiography Findings |
| Left Ventricular Ejection Fraction |
| Left Ventricular Hypertrophy |
| Left Atrial Size |
| Variable |
|---|
| CKD Stage |
| Albuminuria Category |
| Renal Ultrasound Findings |
| Variable |
|---|
| Body Mass Index |
| Metabolic Syndrome |
| Obesity Class |
| Variable |
|---|
| Antihypertensives |
| Antidiabetic Drugs |
| Statins |
| Antiplatelets |
| SGLT2 Inhibitors |
| GLP-1 Receptor Agonists |
| Variable |
|---|
| Hospital Admission |
| Cardiovascular Event |
| Dialysis |
| Death |
| Follow-up Status |
Patient Registration
│
▼
Clinical Assessment
│
▼
Laboratory Tests
│
▼
ECG / Echo / Imaging
│
▼
Electronic Data Entry
│
▼
Digital CKM Registry Database
│
├────────► Clinical Dashboard
├────────► Patient Follow-up
├────────► Quality Improvement Reports
├────────► Research Dataset
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