Add first pass at pre-appointment questionnaire

Author: edwardhorsford

app/filters.js

@@ -12,30 +12,30 @@ module.exports = function (env) { /* eslint-disable-line func-names,no-unused-va
 
   // Get all files from utils directory
   const utilsPath = path.join(__dirname, 'lib/utils');
+  const filtersPath = path.join(__dirname, 'filters');
+
+  const folderPaths = [utilsPath, filtersPath]
 
   try {
-    // Read all files in the utils directory
-    const files = fs.readdirSync(utilsPath);
-
-    files.forEach(file => {
-      // Only process .js files
-      if (path.extname(file) === '.js') {
-        // Get the utils module
-        const utils = require(path.join(utilsPath, file));
-        
-        // Add each exported function as a filter
-        Object.entries(utils).forEach(([name, func]) => {
-          // Only add if it's a function
-          if (typeof func === 'function') {
-            filters[name] = func;
-          }
-        });
-      }
+    folderPaths.forEach(folderPath => {
+      const files = fs.readdirSync(folderPath);
+      
+      files.forEach(file => {
+        if (path.extname(file) === '.js') {
+          const module = require(path.join(folderPath, file));
+          
+          Object.entries(module).forEach(([name, func]) => {
+            if (typeof func === 'function') {
+              filters[name] = func;
+            }
+          });
+        }
+      });
     });
-  } catch (err) {
-    console.warn('Error loading filters from utils:', err);
+  } 
+  catch (err) {
+    console.warn('Error loading filters:', err);
   }
 
-
   return filters;
 };

app/filters/formatting.js

@@ -0,0 +1,35 @@
+/**
+ * Format a yes/no/not answered response with optional additional details
+ * @param {string|boolean} value - The response value to format
+ * @param {Object} [options] - Formatting options
+ * @param {string} [options.yesValue] - Additional details to show after "Yes -" for positive responses
+ * @param {string} [options.noText="No"] - Text to show for negative responses
+ * @param {string} [options.notAnsweredText="Not answered"] - Text to show when no response given
+ * @param {string} [options.yesPrefix="Yes"] - Text to show for positive responses (before any yesValue)
+ * @returns {string} Formatted response text
+ * @example
+ * formatAnswer("yes", { yesValue: "Details here" }) // Returns "Yes - Details here"
+ * formatAnswer("no") // Returns "No"
+ * formatAnswer(null) // Returns "Not answered"
+ * formatAnswer("yes", { yesPrefix: "Currently" }) // Returns "Currently"
+ */
+const formatAnswer = (value, options = {}) => {
+  const {
+    yesValue = null,
+    noText = "No",
+    notAnsweredText = "Not answered",
+    yesPrefix = "Yes"
+  } = options;
+
+  // Handle null/undefined/empty string
+  if (!value || value === "no" || value === "false") {
+    return noText;
+  }
+  
+  // For any truthy value (includes "yes", true, etc)
+  return yesValue ? `${yesPrefix} - ${yesValue}` : yesPrefix;
+};
+
+module.exports = {
+  formatAnswer
+};

app/lib/generators/participant-generator.js

@@ -63,6 +63,103 @@ const generateNHSNumber = () => {
   return `${baseNumber}${finalCheckDigit}`;
 };
 
+// New medical history generators
+const generateMedicalHistorySurvey = () => {
+  // 50% chance of having completed the survey
+  if (Math.random() > 0.5) {
+    return null;
+  }
+
+  return {
+    completedAt: faker.date.past({ years: 1 }).toISOString(),
+    
+    // Non-cancerous procedures/diagnoses
+    nonCancerousProcedures: generateNonCancerousProcedures(),
+    
+    // Current hormone therapy (if they had previous cancer)
+    onHormoneTherapy: Math.random() < 0.3, // 30% of those with cancer history
+    
+    // Other medical history
+    otherMedicalHistory: Math.random() < 0.3 ? 
+      faker.helpers.arrayElements([
+        "Type 2 diabetes - diet controlled",
+        "High blood pressure - medication",
+        "Osteoarthritis",
+        "Previous shoulder surgery",
+        "Rheumatoid arthritis"
+      ], { min: 1, max: 2 }) : 
+      null
+  };
+};
+
+const generateNonCancerousProcedures = () => {
+  const procedures = [];
+  
+  const possibleProcedures = {
+    'benign_lump': {
+      probability: 0.15,
+      details: () => ({
+        dateDiscovered: faker.date.past({ years: 5 }).toISOString(),
+        position: faker.helpers.arrayElement(['Left breast', 'Right breast']),
+        wasRemoved: Math.random() < 0.7,
+        pathology: 'Fibroadenoma'
+      })
+    },
+    'cyst_aspiration': {
+      probability: 0.1,
+      details: () => ({
+        date: faker.date.past({ years: 3 }).toISOString(),
+        location: faker.helpers.arrayElement(['Left breast', 'Right breast']),
+        notes: 'Simple cyst, fluid aspirated'
+      })
+    },
+    'non_implant_augmentation': {
+      probability: 0.02,
+      details: () => ({
+        date: faker.date.past({ years: 5 }).toISOString(),
+        procedure: 'Fat transfer procedure',
+        hospital: 'General Hospital'
+      })
+    },
+    'breast_reduction': {
+      probability: 0.03,
+      details: () => ({
+        date: faker.date.past({ years: 5 }).toISOString(),
+        notes: 'Bilateral breast reduction',
+        hospital: 'City Hospital'
+      })
+    },
+    'previous_biopsy': {
+      probability: 0.08,
+      details: () => ({
+        date: faker.date.past({ years: 2 }).toISOString(),
+        result: 'Benign',
+        location: faker.helpers.arrayElement(['Left breast', 'Right breast'])
+      })
+    },
+    'skin_lesion': {
+      probability: 0.05,
+      details: () => ({
+        date: faker.date.past({ years: 3 }).toISOString(),
+        type: faker.helpers.arrayElement(['Seborrheic keratosis', 'Dermatofibroma']),
+        location: faker.helpers.arrayElement(['Left breast', 'Right breast'])
+      })
+    }
+  };
+
+  Object.entries(possibleProcedures).forEach(([type, config]) => {
+    if (Math.random() < config.probability) {
+      procedures.push({
+        type,
+        ...config.details()
+      });
+    }
+  });
+
+  return procedures;
+};
+
+
 const generateParticipant = ({ ethnicities, breastScreeningUnits }) => {
   const id = generateId();
 
@@ -101,7 +198,8 @@ const generateParticipant = ({ ethnicities, breastScreeningUnits }) => {
       nhsNumber: generateNHSNumber(),
       riskFactors: generateRiskFactors(),
       familyHistory: generateFamilyHistory(),
-      previousCancerHistory: generatePreviousCancerHistory()
+      previousCancerHistory: generatePreviousCancerHistory(),
+      medicalHistorySurvey: generateMedicalHistorySurvey()
     },
     currentHealthInformation: {
       isPregnant: false,
@@ -114,6 +212,31 @@ const generateParticipant = ({ ethnicities, breastScreeningUnits }) => {
 };
 
 
+// Modified family history generator to add more detail
+const generateFamilyHistory = () => {
+  if (Math.random() > 0.15) return null; // 15% chance of family history
+
+  const affectedRelatives = faker.helpers.arrayElements(
+    [
+      { relation: 'mother', age: faker.number.int({ min: 35, max: 75 }) },
+      { relation: 'sister', age: faker.number.int({ min: 30, max: 70 }) },
+      { relation: 'daughter', age: faker.number.int({ min: 25, max: 45 }) },
+      { relation: 'grandmother', age: faker.number.int({ min: 45, max: 85 }) },
+      { relation: 'aunt', age: faker.number.int({ min: 40, max: 80 }) }
+    ],
+    { min: 1, max: 3 }
+  );
+
+  return {
+    hasFirstDegreeHistory: affectedRelatives.some(r => 
+      ['mother', 'sister', 'daughter'].includes(r.relation)
+    ),
+    affectedRelatives,
+    additionalDetails: Math.random() < 0.3 ? 
+      'Multiple occurrences on maternal side' : null
+  };
+};
+
 const generateRiskFactors = () => {
   const factors = [];
   const possibleFactors = {
@@ -133,34 +256,43 @@ const generateRiskFactors = () => {
   return factors;
 };
 
-const generateFamilyHistory = () => {
-  if (Math.random() > 0.15) return null; // 15% chance of family history
-
-  return {
-    hasFirstDegreeHistory: Math.random() < 0.7, // 70% of those with family history
-    affectedRelatives: faker.helpers.arrayElements(
-      ['mother', 'sister', 'daughter', 'grandmother', 'aunt'],
-      { min: 1, max: 3 }
-    )
-  };
-};
 
+// Modified previous cancer history to include more detail
 const generatePreviousCancerHistory = () => {
   if (Math.random() > 0.02) return null; // 2% chance of previous cancer
 
+  const treatments = faker.helpers.arrayElements(
+    [
+      { type: 'surgery', details: 'Wide local excision' },
+      { type: 'radiotherapy', details: '15 fractions' },
+      { type: 'chemotherapy', details: '6 cycles' },
+      { type: 'hormone_therapy', details: '5 years tamoxifen' }
+    ],
+    { min: 1, max: 3 }
+  );
+
   return {
     yearDiagnosed: faker.date.past({ years: 20 }).getFullYear(),
     type: faker.helpers.arrayElement([
       'ductal_carcinoma_in_situ',
       'invasive_ductal_carcinoma',
       'invasive_lobular_carcinoma'
     ]),
-    treatment: faker.helpers.arrayElements([
-      'surgery',
-      'radiotherapy',
-      'chemotherapy',
-      'hormone_therapy'
-    ], { min: 1, max: 3 })
+    position: faker.helpers.arrayElement([
+      'Left breast - upper outer quadrant',
+      'Right breast - upper outer quadrant',
+      'Left breast - lower inner quadrant',
+      'Right breast - lower inner quadrant'
+    ]),
+    treatments,
+    hospital: faker.helpers.arrayElement([
+      'City General Hospital',
+      'Royal County Hospital',
+      'Memorial Cancer Centre',
+      'University Teaching Hospital'
+    ]),
+    additionalNotes: Math.random() < 0.3 ? 
+      'Regular follow-up completed' : null
   };
 };