This patient journey shows how weak documentation and fragmented communication can affect both patient care and cancer reporting in a LMIC setting. It also reflects many of the challenges seen in primary healthcare systems in Nigeria, especially where paper based records are still majorly used for the sake of operability amongst untrained and unequipped healthcare delivery settings.
A. Mapping the Data Flow
i. What data is created at each step of the patient’s journey?
1. Registration Unit
At registration, basic demographic information is collected and written in the paper register.
Patient’s name, Age, Home address, Date of visit, with this information we create the patient’s identity within the hospital system.
2. Clinical Consultation
During consultation, the clinician records clinical information in the patient’s paper file, such as: Symptoms (breast lump, pain, discharge, duration), Medical history, Physical examination findings, Referral information, Initial diagnosis or suspicion of cancer, Request for biopsy; then with this generate the main clinical data needed for diagnosis and treatment planning.
3. Pathology Laboratory Process
The biopsy sample is sent to another facility for pathological analysis. Data created here includes: Biopsy request details, Specimen identification, Histology findings, Cancer confirmation, Tumor type and possibly stage.
Then this pathology report is later returned on paper after two weeks.
4. Cancer Staging and Treatment Discussion
After receiving the pathology result, the clinician verbally discusses cancer staging and management with the patient. Data that should ideally be documented includes: Confirmed diagnosis, Cancer stage, Treatment plan, Follow-up appointment date
5. Follow-up Stage
Three months later, the patient misses follow up. Ideally, data here should include:
Appointment attendance status, Missed appointment record and Follow up communication attempts
But there is no tracking system, so no new data is captured.
6. Cancer Registry Reporting
When preparing cancer registry data, staff attempt to extract information from records. Data required includes: Patient demographics, Diagnosis, Cancer type, Stage, Treatment details, Outcome/follow-up status
Because earlier documentation was incomplete, important fields are missing.
ii. Which step depends on data from a previous step?
Almost every stage depends on information collected earlier.
- The clinician depends on registration data to identify the patient correctly.
2. The pathology laboratory depends on accurate biopsy request information from the clinician.
3. Cancer staging depends on pathology findings.
4. Follow up care depends on proper documentation of diagnosis and appointment plans.
5. Cancer registry reporting depends on complete information from all earlier stages.
If data is poorly recorded at one step, the next stage becomes weaker or incomplete.
B. Identifying Data Gaps
i. What information is missing, delayed, or unclear?
Several important gaps are present:
- The pathology result is delayed because the laboratory is located elsewhere.
2. Cancer stage is discussed verbally but not clearly documented.
3. Follow up appointment details are poorly tracked.
4. There is no system for identifying patients who miss appointments.
5. Registry data fields are incomplete.
6. Communication between facilities relies heavily on paper transfer. These gaps show weaknesses in continuity of care and documentation practices.
ii. How do these gaps affect patient care and reporting?
Effect on Patient Care
Poor documentation can directly affect the patient’s treatment outcome.
- Delayed pathology results may delay diagnosis and treatment initiation.
2. Missing staging information can lead to inappropriate treatment decisions.
3. Loss to follow up means the patient may progress to advanced disease without care. Lack of continuity makes it difficult for another doctor to understand the patient’s history.
4. Cancer registry data becomes inaccurate.
5. The hospital may underestimate cancer burden.
6. Policymakers may not allocate enough resources for cancer services.
7. Research and national cancer control planning become less reliable.
C. Health System Factors
i. Which parts of the system contribute most to the data breakdown?
People
- Health workers will definitely be overworked and document incompletely.
2. Staff may not fully understand the importance of accurate cancer documentation. 3. Communication between clinicians and records staff may be weak.
This connects strongly to my thesis topic on knowledge gaps and training needs among healthcare workers. In many low resource settings, health workers may not receive adequate training on documentation, cancer data management, or continuity of care.
There is no structured follow up system, Referral and pathology communication processes are slow, Cancer staging is discussed verbally instead of systematically documented, Heavy dependence on paper records increases the risk of missing or damaged information, No reminder or tracking tools exist for missed appointments, Separate facilities may use different documentation methods.
ii. How does the use of paper records affect data flow?
Paper records slow down communication and increase the likelihood of errors.
Some common problems include:
- Files can be lost or incomplete.
2. Handwriting may be unclear.
3. Information may not be updated consistently.
4. Data retrieval for reporting becomes difficult and time consuming.
4. Sharing records between facilities is slow.
Paper systems also make patient tracking very difficult, especially for chronic diseases like cancer that require long term follow up.
D. Practical Improvement
i. One realistic improvement that could strengthen data flow without major funding or new technology
One practical and realistic improvement would be the introduction of a standardized cancer patient follow up and documentation checklist on excel spreadsheet .
The checklist could include:
- Confirmed diagnosis
2. Cancer stage
3. Biopsy date and result
4. Treatment plan
5. Follow up appointment date
6. Missed appointment tracking section
This does not require expensive technology or major funding. Staff can implement it using excel/google spreadsheets and brief training sessions.
This simple intervention could: Improve completeness of records, Reduce missing cancer registry data, Improve continuity of care, Help clinicians quickly understand patient history, Encourage better follow-up practices
Relating this to my thesis, strengthening healthcare worker training on proper cancer documentation and follow up systems may significantly improve both patient outcomes and health information quality in low resource/ LMICs healthcare settings.
