Dec 01, 2025
Design and Implementation Protocol for a Neurosurgery-Led Digital Emergency Referral System in Khyber Pakhtunkhwa, Pakistan: A Scalable Model for Low- and Middle-Income Countries
- Muhammad Nawaz Khan1,
- Muhammad Sohaib Khan1,
- Syed Shayan Shah1,
- Bilal Bashir1,
- Ali Talha Khalil1,
- Almas Fasih Khattak1,
- Bipin Churasia2
- 1Lady Reading Hospital Peshawar;
- 2Institute of medical sciences, bharatpuur Nepal
- lady reading hospital peshawar
Protocol Citation: Muhammad Nawaz Khan, Muhammad Sohaib Khan, Syed Shayan Shah, Bilal Bashir, Ali Talha Khalil, Almas Fasih Khattak, Bipin Churasia 2025. Design and Implementation Protocol for a Neurosurgery-Led Digital Emergency Referral System in Khyber Pakhtunkhwa, Pakistan: A Scalable Model for Low- and Middle-Income Countries. protocols.io https://dx.doi.org/10.17504/protocols.io.261gek29yg47/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: September 29, 2025
Last Modified: December 01, 2025
Protocol Integer ID: 228430
Keywords: digital emergency referral system, led digital emergency referral system in khyber pakhtunkhwa, inefficient emergency referral system, emergency referral process, led digital emergency referral system, responsiveness of the emergency referral process, kpk mti referral application, digital referral systems in kpk, based referral platform, referral platform, digital referral system, referral pattern, healthcare system, neurosurgical specialist, quantitative analysis of referral pattern, streamlined referral mechanism, specific referral form, patient triage, neurosurgery, health infrastructure, qualitative feedback from healthcare provider, healthcare facility, unique referral id, time critical specialties like neurosurgery, healthcare provider, unnecessary referral, reduction in unnecessary referral, district hospital, patient mortality, tehsil hospital, receiving facility, many regions in pakistan, delays in patient care, patient, patient care, application
Abstract
Background
Inefficient emergency referral systems in low- and middle-income countries (LMICs) like Pakistan contribute to delays in patient care, miscommunication, and inadequate preparedness at receiving facilities, ultimately worsening health outcomes specially in time critical specialties like Neurosurgery. Khyber Pakhtunkhwa (KPK), like many regions in Pakistan, lacks a streamlined referral mechanism across its healthcare facilities.
Objectives
This study led by neurosurgical specialists, aims to design, implement, and evaluate a digital emergency referral system—the KPK MTI Referral Application—to enhance patient triage, real-time communication, and system-wide monitoring. The goal is to improve the efficiency, transparency, and responsiveness of the emergency referral process across KPK’s healthcare system.
Methods
A user-centered, mobile- and web-based referral platform will be developed, tailored to KPK’s health infrastructure and digital landscape. The mixed-methods study will include quantitative analysis of referral patterns and outcomes, as well as qualitative feedback from healthcare providers and patients across major Medical Teaching Institutions (MTIs), district hospitals, and tehsil hospitals. Key features of the application will include a user-friendly interface, real-time bed availability, automated and specialty-specific referral forms, image upload functionality, instant notifications, unique referral IDs, and dashboards for monitoring and analytics. The study will be conducted in phases, including requirement gathering, development, testing, and deployment. Ethical considerations such as data anonymization, patient confidentiality, and secure storage will be addressed.
Expected Outcomes
The evaluation will focus on measurable improvements including a reduction in unnecessary referrals, improved response times, increased bed utilization rates, decreased patient mortality, cost savings, and enhanced satisfaction among patients and healthcare providers. The study’s findings will inform policy recommendations for broader adoption of digital referral systems in KPK and other LMICs facing similar challenges.
Image Attribution
Nawaz Khattak
Materials
Study instrument: (study proforma /questionnaire shall be provided)
Troubleshooting
Safety warnings
No patient identifiers will be collected, and only operational metrics will be analyzed.
Ethics statement
Ethical considerations such as data anonymization, patient confidentiality, and secure storage will be addressed. Ethical clearance from the NBC-R is mandatory before the project is executed for multicenter/multi-provincial/ and national-level research projects. Single-center research studies do not require NBC-R approval; however, a member of the NBC-R should be co-opted into the TAC to provide ethical insight. Data will be anonymized, and no patient names or identifiers will be stored. Consent will be obtained from the participating clinicians for feedback and interviews. Data security will follow HIPAA-compliant protocols, with access restricted to authorized personnel.
Features and Functional Design of the Digital Referral Platform
Real-Time Bed Availability: Displays current bed occupancy and specialized service availability in all receiving hospitals.
Automated Referral Forms: Specialty-specific forms with fields for patient details, medical history, and reasons for referral.
Image Upload Functionality: Allows attaching of diagnostic images (e.g., X-rays, CT scans).
Instant Notifications: Referral alerts sent to receiving hospitals within a 15-minute timeframe.
Referral ID System: Each referral is assigned a unique ID for traceability, printed on the referral slip.
Reminder and Escalation System: If no response is received within 15 minutes, automated reminders are triggered, and emergency contacts are displayed for follow-up.
Dashboards for Monitoring: Real-time tracking for hospital administrators, emergency managers, and policymakers.
Data Analytics and Reporting: Monthly and quarterly reports highlighting referral patterns, hospital performance, and system bottlenecks.
Web/App Interface Workflow
Homepage – Displays MTI hospital logos; selecting one leads to department listing. (fig:2 and fig:3)
Department Listing Page – Shows all departments in the chosen hospital; selecting one opens the referral form.
Referral Form Page – Includes input fields for patient info, medical history, and upload of diagnostic images.
Dashboards:
Hospital MD Office Dashboard: Tracks incoming/outgoing referrals, response status, and department-wise breakdowns.
Policy Board Dashboard: Aggregated data for strategic oversight, including:
Total referrals (in/out) per MTI
Unplanned referrals
Specialty-wise breakdowns
Most common reasons for referral
Evaluation Parameters
Reduction in Unnecessary Referrals: The number of unnecessary referrals (e.g., cases that could have been managed at district or tehsil hospitals) before and after the portal’s implementation was compared.
Improvement in Response Times: The average time taken for receiving hospitals to respond to referral requests (acceptance or rejection) was measured.
Increase in Bed Utilization Rates: Monitor bed occupancy rates at district and tehsil hospitals before and after the implementation of the portal.
Reduction in Patient Mortality Rates: Track mortality rates for trauma and emergency cases before and after the implementation of the portal.
Cost Savings: Analyze the reduction in out-of-pocket expenses for patients (e.g., travel and accommodation) and the overall healthcare system costs related to patient transfers.
Patient and Provider Satisfaction: Measure patient and healthcare provider satisfaction with the referral process through surveys and interviews.
Reporting and Policy Recommendations: The findings from the evaluation will be compiled into a comprehensive report that will be shared with healthcare administrators, policymakers, and other stakeholders. The report will include the following:
Policy Recommendations: Recommendations for scaling up the referral portal to include all district and tehsil hospitals in KPK, as well as suggestions for further improvements to the system are provided.
Ethical Considerations
Ethical clearance from the NBC-R is mandatory before the project is executed for multicenter/multi-provincial/ and national-level research projects. Single-center research studies do not require NBC-R approval; however, a member of the NBC-R should be co-opted into the TAC to provide ethical insight.
Data will be anonymized, and no patient names or identifiers will be stored. Consent will be obtained from the participating clinicians for feedback and interviews. Data security will follow HIPAA-compliant protocols, with access restricted to authorized personnel.
Timeline and Implementation Plan
The project will be executed in four key phases over a 10-month period, combining application development, system integration, training, deployment, monitoring, and evaluation. Each phase has clearly defined deliverables to ensure smooth implementation and scalability. (Fig:4)
Phase 1: Application Development and Data Preparation (Months 1–5)
Phase 2: Implementation and Integration (Months 3–7)
Phase 3: Monitoring and Data Collection (Months 5–10)
Phase 4: Evaluation and Reporting (Months 8–10)
Data Analysis
Final Report Preparation
Policy Recommendations
Potential Limitations and Mitigation Strategies
The study may face several challenges, including:
Limited smartphone and internet access in rural areas, which could hinder adoption and consistent use of the referral system.
Variability in digital literacy among healthcare providers, potentially affecting the efficient use of the application.
Resistance to change from clinicians accustomed to existing manual workflows, which may delay implementation.
Mitigation strategies include targeted training sessions, simplified user interfaces, phased implementation with continuous support, and engagement with local stakeholders to build ownership and trust in the new system.
Funding
This study will be internally funded by the participating Medical Teaching Institutions (MTIs), with financial support and oversight provided through their respective hospital administrations.
Mobile App Interface
Following is the Mobile App interface
Flowchart of the referral process
Fig:1 Flowchart of the referral process
Fig:2 Mobile App Interface
Fig:3 Mobile App Interface
Fig:4 Timeline of the Project
Protocol references
1. European Commission. Communication from the commission to the European Parliament, the council, the European economic and social committee and the Committee of the Regions Youth Opportunities Initiative. Belgium: European Commission Brussels (2011).
2. Aljerian, N. A., Alharbi, A. A., AlOmar, R. S., Binhotan, M. S., Alghamdi, H. A., Arafat, M. S., Aldhabib, A., 26 Alabdulaali, M. K. (2024). Showcasing the Saudi e-referral system experience: the epidemiology and pattern of referrals utilising nationwide secondary data. Frontiers in Medicine, 11. https://doi.org/10.3389/fmed.2024.1348442
3. Haroon MZ, Thaver IH. An assessment of existing surge capacity of tertiary healthcare system of Khyber Pakhtunkhwa Province of Pakistan using workload indicators for staffing need method. Hum Resour Health. 2022;19(Suppl 1):120. https://human-resources-health.biomedcentral.com/articles/10.1186/s12960-021-00663-3
4. Pakistan population (2025) - Worldometer. (n.d.). Worldometer. https://www.worldometers.info/world-population/pakistan-population/
5. Khan A, Khan H. Measuring Income Inequality Across the Districts of Khyber Pakhtunkhwa. International Journal of Business and Economic Affairs. 2023 Apr 30;8(2):11-9.
6. Mselle L, Sirili N, Anaeli A, Massawe S. Understanding barriers to implementing referral procedures in the rural and semi-urban district hospitals in Tanzania: Experiences of healthcare providers working in maternity units. PloS one. 2021 Aug 26;16(8):e0255475.
7. Home. (n.d.). https://www.pta.gov.pk/
8. Implementation of a Technology-Based Mobile Obstetric Referral Emergency System (MORES): Qualitative Assessment of Health Workers in Rural Liberia. JMIR Mhealth Uhealth. 2024;12(1):e58624. https://mhealth.jmir.org/2024/1/e58624
9. Aljerian NA, Alharbi AA, AlOmar RS, Binhotan MS, Alghamdi HA, Arafat MS, Aldhabib A, Alabdulaali MK. Showcasing the Saudi e-referral system experience: the epidemiology and pattern of referrals utilising nationwide secondary data. Front Med (Lausanne). 2024 Jun 27;11:1348442. doi: 10.3389/fmed.2024.1348442. PMID: 38994943; PMCID: PMC11238632.
10. Sarkar N, Peeters Grietens K, Dillip A. Towards a digitally-enabled, community-based responsive health system in Tanzania: a formative study for the Afya-Tek digitised health initiative. Lancet Glob Health. 2020 Apr;8:S35. doi:10.1016/S2214-109X(20)30176-5.
11. Klingberg A, Wallis LA, Hasselberg M, Yen PY, Fritzell SC. Teleconsultation Using Mobile Phones for Diagnosis and Acute Care of Burn Injuries Among Emergency Physicians: Mixed-Methods Study JMIR Mhealth Uhealth 2018;6(10):e11076 doi: 10.2196/11076 PMID: 30341047 PMCID: 6231743
12. Https://www.healthkp.gov.pk/. (n.d.).
13. Wallenius V. Understanding Health Care Referral Chain Challenges in Kwale County, Kenya: Creating an Optimized Referral Chain Model to Community Clinic
14. Jeffree RL, Unterrainer A, Chaourov A. Lessons from a web-based referral system for acute neurosurgical referrals. Part 1: System features and evaluation. Journal of Clinical Neuroscience. 2025 Jan 1;131:110894.
15. Rusmawatiningtyas D, Oktaria V, Pudjiadi AH, Makrufardi F, Woensel JB. Clinical characteristics and outcome of critically ill children referred to a tertiary hospital in Indonesia: a prospective observational study. BMC pediatrics. 2024 Jul 27;24(1):478.
16. Rathnayake D, Clarke M. The effectiveness of different patient referral systems to shorten waiting times for elective surgeries: systematic review. BMC health services research. 2021 Dec;21:1-3
Acknowledgements
This study will be internally funded by the participating Medical Teaching Institutions (MTIs), with financial support and oversight provided through their respective hospital administrations.