Submitted:
23 May 2024
Posted:
23 May 2024
Read the latest preprint version here
Abstract
Keywords:
1. Introduction
2. Clinical Background, Current Knowledge, State of the Art
2.1. Clinical Background & Current Knowledge
2.2. State of the Art, including Alternative Treatments
3. The gap in Current Methods
5. Pathpoint® eDerma Platform
5.1. Device Description
5.2. Measurement Methods Possible in Pathpoint® eDerma
5.2. Clinical Benefits and Outcome Parameters of eDerma
| S.No | Clinical Benefits | Outcome Parameters | Way to measure the outcome |
|---|---|---|---|
| 1. | Improvement in patient outcomes | Faster diagnosis | Measure the average time taken from initial consultation to diagnosis before and after using eDerma. |
| Reduced waiting time | Measure the time patients wait for appointments or referrals before and after eDerma implementation. | ||
| Better patient-reported experience measures | Collect patient feedback on their experience with eDerma compared to traditional methods. | ||
| Access to care (rural and urban) | Compare referral rates before and after eDerma introduction in different geographic areas. Analyse changes in population demographics accessing dermatological care. | ||
| 2. | Reduction in unnecessary procedures | Reduction in clinic time | Measure the average time spent per patient in dermatology clinics before and after eDerma. |
| Reduction in the number of trips & clinic appointments | Count the number of follow-up appointments or trips avoided due to eDerma's efficiency. | ||
| Reduction in biopsy* | Track the number of unnecessary biopsies performed before and after eDerma use. | ||
| 3. | Reduction in healthcare cost | Reduction in clinic time | Calculate cost savings associated with reduced clinic time per patient visit. |
| Number of clinic appointments |
Estimate cost savings based on the reduction in the number of clinic visits required per patient. | ||
| 4. | Better documentation | SNOMED-CT Coding results in more transferrable and interpretable information | Assess the accuracy and completeness of documentation using SNOMED-CT coding before and after eDerma adoption. |
| Time spent on documentation | Measure the time healthcare professionals spend on documentation tasks with and without eDerma. | ||
| 5. | Adverse effects | Reliance on clinical information provided by patients themselves | Monitor and report any instances of misdiagnosis or treatment errors due to patient-provided information. |
| Delay in diagnosis due to adding an extra step (dermoscopy) | Evaluate if using dermoscopy through eDerma causes any delays in diagnosis compared to traditional methods. |
5.4. Justification for Measurement Parameters in eDerma Implementation
5.4.1. Faster Diagnosis
5.4.2. Reduced Waiting Time
5.4.3. Patient-reported Experience Measures
5.4.4. Access to Care
5.4.5. Reduction in Unnecessary Procedures
5.4.6. Better Documentation
5.4.7. Adverse Effects
5.4.8. Cost Saving
5.4.9. UK Population Studies
5.4.10. Environmental Impact
6. Clinical Safety, Methods for Analysis
6.1. Safety Parameters
6.2. Risk Management Plan
6.3. Risk Assessment
6.4. Risk Management Report
6.5. Compliance with NHS Digital Toolkit
6.6. Recertification and Annual Review
6.7. Comprehensive User Training and Support
6.8. Adverse Event Monitoring and Management
6.9. Post-Market Surveillance
7. Acceptability of Benefit-Risk-Ratio
7.1. Clinical Benefits Overview
7.2. Risk Mitigation Measures
7.3. Benefit-Risk Analysis
- Enhanced Patient Outcomes vs. Data Security Risks: The significant improvement in patient outcomes through optimised preoperative planning and risk reduction after proper risk management outweighs the manageable risks related to data security, which are mitigated by data security measures.
- Increased Efficiency vs. System Reliability Concerns: The efficiency gains in preoperative processes and resource allocation significantly benefit healthcare providers and patients, overshadowing the minimal risks associated with system downtime, addressed through redundancy systems and regular maintenance.
- Improved Clinical Decision-Making vs. Accuracy of Decision Support: The software's contribution to more accurate and informed clinical decision-making, supported by continuous validation against clinical outcomes, presents a substantial benefit over the minimal risk of decision support inaccuracies, which are continuously monitored and updated.
7.4. Acceptability Conclusion
8. Conclusion
9. Acknowledgements
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