# VigilCare Records

## A Clinical Guide to Paper Chart Digitization and Governance

**Audience:** Physicians, nurse leaders, hospital administrators, and healthcare partners evaluating the platform  
**Purpose:** Explain how paper-based clinical records become trusted digital clinical data—without requiring software engineering knowledge

---

## Table of Contents

1. [Executive Summary](#1-executive-summary)
2. [Why Clinical Digitization Matters](#2-why-clinical-digitization-matters)
3. [End-to-End Clinical Workflow](#3-end-to-end-clinical-workflow)
4. [System Data Flow](#4-system-data-flow)
5. [Safety and Governance](#5-safety-and-governance)
6. [Dashboard and Workstation Walkthrough](#6-dashboard-and-workstation-walkthrough)
7. [Clinical Examples](#7-clinical-examples)
8. [High-Level Architecture](#8-high-level-architecture)
9. [Relationship to Clinical Care](#9-relationship-to-clinical-care)
10. [Complete Patient Journey](#10-complete-patient-journey)

---

## 1. Executive Summary

**VigilCare Records** is a clinical records digitization and governance platform for hospitals and clinics that still rely on paper charts. It converts handwritten and printed clinical documents into structured electronic patient data—but only after that data has been checked by people, not machines alone.

### What problem does it solve?

Many district hospitals, island health systems, and smaller facilities still keep vital signs, laboratory results, allergies, and medication lists on paper. When those facilities introduce electronic monitoring or early warning systems, they face a hard question:

> *How do we know the numbers in the computer are the same numbers that were written on the chart?*

Without a governed digitization process, transcription errors, incomplete identity matching, and unreviewed OCR guesses can flow into clinical alerts and decision support. That puts patients at risk and undermines clinician trust.

### What VigilCare Records does

The platform provides a controlled pathway from paper to permanent electronic record:

1. A paper chart section is **scanned and stored securely**
2. A data entry clerk **transcribes** demographics, encounters, and observations into structured drafts
3. A second person **verifies** every field against the original scan
4. For high-stakes content (vitals, labs, medications, encounters), a **clinical approver** authorizes promotion
5. Only then does the information become part of the patient’s **live clinical record**

**Unapproved drafts never reach clinical monitoring, early warning scores, or clinician dashboards.**

VigilCare Records is not a full electronic medical record (EMR) and does not diagnose patients. It is the governed intake layer that ensures clinical information entering downstream systems is complete, verified, and trustworthy.

---

## 2. Why Clinical Digitization Matters

### Challenges of paper charts

| Challenge | Clinical impact |
|---|---|
| Charts live in folders, ward books, or index cards | Information is hard to find across shifts and transfers |
| Handwriting varies in clarity | Values may be misread under time pressure |
| Timestamps are often imprecise or missing | Trends and deterioration timelines become unreliable |
| Encounter boundaries are unclear | “The patient” is not distinguished from “this admission” |
| Charts can be misplaced between wards | Continuity of care is interrupted |

### Risks of transcription errors

Moving from paper to digital without safeguards introduces new hazards:

- **Decimal misplacement** — potassium recorded as `52` instead of `5.2`
- **Wrong patient folder** — values linked to the incorrect medical record
- **Unit confusion** — temperature or glucose entered in the wrong scale
- **Silent “correction”** — someone overwrites a value with no record of what changed

These errors matter most when digital values drive alerts, scoring, or handover decisions.

### Delayed access to patient information

Paper charts travel with the patient or sit on the ward. Consultants, night staff, and remote reviewers may wait for physical retrieval. Digitized, verified records make the same information available wherever clinical monitoring and care coordination require it—without discarding the original scan as the legal source document.

### Regulatory and audit requirements

Healthcare facilities must often demonstrate:

- Who entered a clinical value
- Who checked it
- When it became part of the permanent record
- Whether it was later corrected—and how

VigilCare Records maintains an **append-only audit history** for every digitization batch, so reviewers can reconstruct the chain from scan to live record.

### How structured digital records improve care

Once verified information is promoted into the live clinical database:

| Benefit | Why it matters |
|---|---|
| **Continuity of care** | Prior vitals, labs, allergies, and medications follow the patient across encounters |
| **Clinical monitoring** | Downstream systems can score early warning signals on trustworthy observations |
| **Interoperability** | Standard FHIR representations support exchange with other clinical systems |
| **Research and quality** | Structured, timestamped data supports audit, morbidity review, and outcome analysis |

Structured records do not replace clinical judgment. They give judgment better raw material.

---

## 3. End-to-End Clinical Workflow

### Overview of the pathway

Paper chart digitization in VigilCare Records follows a deliberate sequence. Each stage has a clear clinical purpose.

```
Paper chart received
        ↓
Scan uploaded (secure storage)
        ↓
Digitization batch created
        ↓
Data entry (structured drafts)
        ↓
Verification (second human checks against scan)
        ↓
Clinical approval (when required for the document type)
        ↓
Promotion into the live clinical record
        ↓
Available for clinical monitoring and ongoing care
```

There are two operational tracks:

| Track | When used | Gate model |
|---|---|---|
| **Track A — Backfill** | Historical charts, bulk digitization, past encounters | Full dual-human verification, then clinical approval |
| **Track B — Live capture** | Bedside vitals entered by a credentialed clinician | Clinician attestation replaces the dual queue; still fully audited |

The remainder of this section focuses on Track A, which is the primary pathway for paper charts.

### Stage-by-stage walkthrough

#### 1. Paper chart received

Ward or medical records staff deliver a chart section—for example a nursing observation sheet, laboratory printout, admission face sheet, allergy note, or medication list.

#### 2. Scan uploaded

An **Intake Clerk** scans the page(s) and uploads the image or PDF. The system:

- Stores the scan in secure document storage
- Computes a fingerprint (hash) so the same document is not accidentally uploaded twice for the same patient within a short window
- Creates a **digitization batch**—one unit of work for that chart section

Optional cover sheets with QR codes can pre-classify batch type and patient for high-volume intake.

#### 3. Batch created and assigned

The batch is typed according to clinical content:

| Batch type | Typical content |
|---|---|
| Patient registration | Demographics, contacts, blood type |
| Encounter summary | Admission/discharge context, department, bed |
| Vitals sheet | Heart rate, blood pressure, SpO₂, temperature, etc. |
| Lab results | Laboratory observations with chart timestamps |
| Medication list | Current medications |
| Allergy update | Documented allergies and sensitivities |
| Mixed | Combined chart sections |

A data entry clerk is assigned so two people do not work the same scan at once.

#### 4. Data entry

The **Data Entry Clerk** works in a split-pane workstation:

- **Left:** the scan (zoom, pan, rotate)
- **Right:** structured forms for patient, encounter, and observations

Timestamps for observations come from the **chart**, not the time of scanning. Built-in plausibility checks catch many transcription mistakes (for example, an impossible potassium value) before the batch leaves the entry desk.

If optional OCR assistance is enabled, the system may pre-fill fields with confidence scores. The clerk still reviews every value against the image. OCR never replaces human entry or verification.

#### 5. Verification

A **Verifier**—a different person from the entry clerk—compares each drafted field to the scan. Fields are checked one by one. If anything is wrong, the batch is **rejected** with a reason and returns for correction. If everything matches, verification passes.

#### 6. Clinical approval (when required)

Site configuration decides which document types need an additional clinical gate after verification:

| Usually requires clinical sign-off | Usually proceeds after verify to approver queue without the extended physician review path |
|---|---|
| Encounter summaries | Patient registration |
| Vitals sheets | Allergy updates |
| Lab results | |
| Medication lists | |
| Mixed batches | |

In all Track A cases, a **Clinical Approver** must still authorize promotion. For high-stakes types, that review is explicit in a dedicated clinical approval queue.

#### 7. Promotion into the live clinical record

On approval, draft patient, encounter, and observation data are written into the live clinical database in a single, all-or-nothing step (**atomic promotion**). Either the whole approved set becomes live, or nothing does—avoiding half-updated patient records.

#### 8. Availability for monitoring and care

Promoted observations become visible to the companion clinical monitoring platform (VigilCareClinical). Historical backfill typically **does not** page clinicians for old critical values unless the facility deliberately enables retroactive alerts for that batch. Live bedside capture, by contrast, can alert immediately when clinically appropriate.

### Roles and responsibilities

| Role | Primary responsibilities | Clinical accountability |
|---|---|---|
| **Intake Clerk** | Receive charts, scan/upload, classify batch type, optionally link patient or cover sheet, assign entry work | Ensures the correct document enters the pipeline and is stored intact |
| **Data Entry Clerk** | Transcribe demographics, encounters, observations; correct rejected batches | Ensures structured fields faithfully represent the scan |
| **Verifier** | Field-level comparison of draft vs scan; pass or reject | Independent quality check—cannot verify own entry |
| **Clinical Approver** | Authorize promotion for verified batches; review high-stakes content | Clinical governance gate before data becomes permanent |
| **Clinician** | Track B live capture with attestation; may use promoted data in care | Attests that bedside values are accurate at the time of entry |
| **Administrator** | Users, site routing, queues, cancellation, supervisor oversight, interoperability browsing | Operational integrity of the digitization program |

**Staffing note:** In a small facility one person may perform intake and entry. The system still **never** allows the same person to both enter and verify the same batch. Minimum staffing for Track A is two people.

---

## 4. System Data Flow

The diagrams below show how information moves through VigilCare Records and into clinical care systems.

### Diagram 1 — Paper Record Digitization

```mermaid
flowchart LR
    A[Paper Chart] --> B[Scan Upload]
    B --> C[Secure Storage]
    C --> D[Draft Patient Data]
    D --> E[Draft Encounter]
    E --> F[Draft Observations]
    F --> G[Verification]
    G --> H[Clinical Approval]
    H --> I[Promotion]
    I --> J[Live Clinical Database]
```

**Reading the diagram clinically:** Everything to the left of Promotion is **working copy / draft**. It can be corrected, rejected, or cancelled. Only after promotion does information become part of the patient’s permanent electronic clinical record used by monitoring systems.

### Diagram 2 — Governance Workflow

```mermaid
flowchart TD
    U[Upload] --> AS[Assignment]
    AS --> DE[Data Entry]
    DE --> V[Verification]
    V -->|Pass| AP[Approval]
    V -->|Reject| DE
    AP --> AT[Audit Trail]
    AP --> PCR[Permanent Clinical Record]
    AT --> PCR
```

Every transition records **who acted, what changed, and when**. Rejection sends work back to entry with a reason; it does not erase the scan or the audit history.

### Diagram 3 — Downstream Integration

```mermaid
flowchart LR
    L[Live Patient Record] --> M[Clinical Monitoring System]
    M --> E[Early Warning Scores]
    E --> A[Alert Generation]
    A --> D[Clinician Dashboard]
```

### Critical invariant

```
Draft / unverified / unapproved information
                ✕
        never reaches
                ✕
Clinical monitoring · Early warning scores · Alert generation · Clinician dashboards
```

This separation is intentional. Digitization speed must not outrun clinical trust.

---

## 5. Safety and Governance

Patient safety in digitization is less about “faster scanning” and more about **who may change what, and whether the chain of custody is reconstructable**.

### Separation of duties

The person who enters a batch cannot verify it. The person who entered or verified cannot approve promotion of that same batch. The system blocks these conflicts automatically.

**Why it matters:** Dual control reduces the chance that a single transcription error—or a single person’s assumption about illegible handwriting—becomes permanent clinical fact.

### Dual-human verification

Track A requires two humans: one to enter, one to check against the original image. Verification is field-level, not a rubber stamp on the whole form.

### Clinical approval routing

High-stakes document types can be routed through an explicit clinical approval queue so a designated approver reviews content before it becomes live. Facilities configure which batch types require this extended path.

### Immutable audit history

Status changes, document views, rejections, OCR assists, and promotions are recorded in an append-only event history. Auditors and clinical leaders can answer: *What was entered? Who checked it? When did it go live?*

### Controlled corrections using supersession

Once promoted, values are **not silently edited**. A correction creates a new digitization batch linked to the original. After the new batch passes the full pipeline, corrected observations are added and originals are marked **superseded**—still visible historically, no longer treated as current.

**Why it matters:** Regulators and morbidity reviews need the correction story, not a rewritten past.

### Document integrity verification

Each scan is stored with an integrity fingerprint. Rejecting a batch does not delete the scan. Duplicate uploads of the same document for the same patient within a defined window are blocked to reduce accidental double-entry.

### Patient matching and duplicate detection

On promotion, the system matches patients carefully (for example by name and date of birth) and warns when a near-duplicate may already exist. New patients receive a stable medical record number (MRN). This reduces split charts and merged-identity hazards.

### Atomic promotion into live records

Patient, encounter, and observation updates for an approved batch succeed together or not at all. Partial promotion—which could leave an encounter without its labs, or labs without a patient—is avoided by design.

### Plausibility checks at entry

Numeric ranges catch physically impossible values early (for example SpO₂ above 100%, or potassium far outside a plausible laboratory range). These are **digitization safety nets**, not clinical alert thresholds.

### Why these controls are essential

In clinical environments:

- Alerts and scores amplify whatever data they receive
- Silent edits destroy forensic and educational value of the record
- Single-person pipelines concentrate risk on the most fatigued shift
- Paper remains the source of truth until humans have reconciled digital drafts to the scan

Governance is not bureaucracy for its own sake—it is how a paper-to-digital program earns the right to drive monitoring and care coordination.

---

## 6. Dashboard and Workstation Walkthrough

Each workstation is designed around one job. Users see only the queues and actions appropriate to their role.

### Intake workstation

**Who:** Intake Clerk, Administrator  

**What they see:** Upload form, batch type selection, track (backfill vs live), optional patient search, optional cover-sheet barcode entry.

**Decisions:**
- Is this the correct document type?
- Should this link to an existing patient MRN or wait for registration?
- Who should perform data entry?

**Outcome:** A batch in secure storage, ready for transcription.

### Data entry screen

**Who:** Data Entry Clerk, Administrator  

**What they see:** Split view—scan on one side, structured fields on the other. Observation rows with codes, values, units, and chart timestamps. Optional OCR confidence highlights when enabled.

**Decisions:**
- What does the handwriting actually say?
- Are encounter details complete for this visit?
- Are all required sections for this batch type filled?

**Outcome:** Draft patient / encounter / observations submitted for verification—or returned to entry after rejection.

### Verification screen

**Who:** Verifier (and roles permitted to review the verification queue)  

**What they see:** Same scan viewer plus checkboxes or field-level status for each drafted value, with progress toward complete review.

**Decisions:**
- Does each field match the scan?
- If not, what rejection reason will help the entry clerk fix it?

**Outcome:** Verified (or awaiting clinical approval) — or rejected for rework.

### Clinical approval queue

**Who:** Clinical Approver, Administrator  

**What they see:** Batches awaiting promotion authorization; scan plus structured summary; option related to retroactive alerting for backfill when clinically appropriate.

**Decisions:**
- Is this content ready to become part of the permanent record?
- For historical values, should downstream alerting be enabled?

**Outcome:** Approval triggers promotion, or rejection returns the work with reason.

### Patient history

**Who:** Authenticated clinical and administrative users  

**What they see:** Timeline of digitization batches for a patient, correction chains (which batch superseded which), and audit events.

**Decisions:**
- Has this patient’s paper record been fully backfilled?
- Was a value corrected, and when?

**Outcome:** Situational awareness for governance and continuity—not a replacement for the full clinical charting EMR.

### Supervisor dashboard

**Who:** Administrator  

**What they see:** Work-queue overview—counts by status, aging work, rejection patterns, bottlenecks in entry vs verification vs approval.

**Decisions:**
- Where should staffing be redirected today?
- Is rejection rate signaling scan quality or training issues?
- Which batches need cancellation or reassignment?

### FHIR Explorer

**Who:** Administrator  

**What they see:** A browser for promoted clinical data exposed in HL7 FHIR R4 form (Patient, Encounter, Observation), including standard search and patient “everything” views.

**Decisions:**
- Can partner systems consume our promoted record correctly?
- Do observation codes map as expected for interoperability testing?

**Outcome:** Technical assurance for exchange—still based only on **promoted** data.

### Live capture (clinician workstation)

**Who:** Clinician  

**What they see:** Bedside entry for current encounter vitals/observations, with attestation and password confirmation.

**Decisions:**
- Are these values measured now, for this active encounter?
- Do I attest that they are accurate?

**Outcome:** Immediate promotion with full audit; may trigger synchronous clinical alerts when thresholds are crossed.

---

## 7. Clinical Examples

### Example A — New patient registration

**Situation:** A new admission arrives with a handwritten face sheet.

1. Intake scans the face sheet as **Patient registration**
2. Entry clerk transcribes name, date of birth, sex, blood type, emergency contact
3. Verifier confirms each demographic field against the scan
4. Clinical approver authorizes promotion
5. Live patient record is created with a new MRN (for example `VCR-000042`)

Subsequent vitals and labs can now link to a stable identity.

### Example B — Historical paper chart backfill

**Situation:** Before turning on ward alerting, the hospital digitizes 200 active paper charts.

1. Intake uploads vitals sheets and lab reports as **Backfill** batches
2. Entry and verification proceed through the dual-human gate
3. High-stakes types route through clinical approval
4. On promotion, historical observations enter the live database with **chart timestamps**
5. By default, a potassium of 6.2 from three days ago does **not** page today’s on-call clinician

Backfill builds a trustworthy baseline without flooding the ward with retrospective noise.

### Example C — Laboratory result digitization

**Situation:** A paper lab report shows potassium `5.2 mEq/L`.

1. Intake uploads as **Lab results**
2. Entry clerk records potassium with the laboratory’s reported time
3. If `52` is typed by mistake, plausibility validation blocks the impossible value
4. Verifier confirms `5.2` against the scan
5. Clinical approver authorizes promotion
6. The observation becomes available to monitoring—still subject to facility alert policy for backfill vs live

### Example D — Vital signs entry

**Situation:** Nursing observation chart for an inpatient with pneumonia.

1. Vitals sheet batch created and assigned
2. Entry clerk records heart rate, SpO₂, temperature, respiratory rate, blood pressure with times from the chart
3. Verifier checks each row
4. Clinical approval and promotion follow
5. Scores such as NEWS2 in the companion monitoring system can use these observations once live

### Example E — Medication reconciliation (list digitization)

**Situation:** Ward medication list must be captured before transfer.

1. Intake uploads **Medication list**
2. Entry captures the structured medication set from the scan
3. Verification and clinical approval treat this as high-stakes content
4. On promotion, medications merge into the live patient context used for ongoing care review

### Example F — Allergy updates

**Situation:** Chart documents Codeine, iodine contrast, and latex allergies.

1. **Allergy update** batch is digitized
2. Entry and verification confirm the allergy list against the scan
3. After approval and promotion, allergies are part of the live patient record visible to downstream care workflows

(Default site routing may treat allergy updates as lower complexity than labs/vitals for the extended clinical queue, but promotion still requires authorized approval.)

### Example G — Correcting an already promoted record

**Situation:** SpO₂ was promoted as `94%`; the chart clearly shows `95%`.

1. A **correction batch** is created linked to the original promoted batch
2. Correct values are entered, verified, and approved through the full pipeline
3. New live observations are inserted; originals are marked **superseded**
4. Patient history shows both the original error and the correction, with actors and times

No one “quietly fixes” the permanent record. The clinical story remains auditable.

---

## 8. High-Level Architecture

Think of VigilCare Records as several cooperating parts, each with a clinical reason to exist.

| Component | What it is (plain language) | Why it exists |
|---|---|---|
| **Secure document storage** | Locked vault for scans (PDF/JPEG/PNG) | Preserves the image everyone verifies against; supports integrity checks |
| **Structured clinical database** | Organized tables for drafts and live patients, encounters, observations | Separates “working drafts” from “permanent clinical facts” |
| **Digitization workflow engine** | Rules for statuses, roles, queues, and allowed transitions | Prevents skipping safety gates or approving out of order |
| **User workstations** | Role-specific screens for intake, entry, verify, approve, live capture | Puts the right decisions in front of the right people |
| **Audit system** | Permanent diary of actions and document access | Supports governance, training, and regulatory review |
| **Optional OCR assistance** | Computer suggestion of text from the scan | Speeds entry when enabled; never replaces human review |
| **HL7 FHIR interface** | Standard read-only clinical data format | Lets other systems retrieve promoted Patient / Encounter / Observation data |
| **Integration with clinical monitoring** | Handoff of promoted data to VigilCareClinical | Powers early warning, alerts, and ward views—only after approval |

```
┌──────────────────────────────────────────────────────────┐
│                 VigilCare Records                        │
│  Scan → Enter → Verify → Approve → Promote               │
│           Drafts (never alert)                           │
└───────────────────────────┬──────────────────────────────┘
                            │ approved data only
                            ▼
┌──────────────────────────────────────────────────────────┐
│              Clinical Monitoring Platform                │
│  Live record → Scores → Alerts → Clinician dashboard     │
└──────────────────────────────────────────────────────────┘
```

Implementation details (servers, containers, programming languages) matter to IT teams. Clinicians need only know that **drafts and live records are separated by design**, and that promotion is the controlled bridge between them.

---

## 9. Relationship to Clinical Care

### What VigilCare Records supports

| Clinical need | How the platform helps |
|---|---|
| **Accurate patient histories** | Demographics and prior observations are verified against source documents before they become permanent |
| **Reliable clinical observations** | Dual review, plausibility checks, and approval reduce garbage-in / garbage-out |
| **Better continuity of care** | Structured encounters and observations remain available across shifts and services |
| **Clinical decision support systems** | Downstream scoring and alerts receive only promoted data |
| **Future interoperability** | FHIR representations of promoted records support partner exchange |
| **Research-quality data** | Timestamped, coded observations with known provenance |
| **Regulatory compliance** | Audit trails, supersession, separation of duties, retained scans |

### What the platform does not do

VigilCare Records:

- Does **not** diagnose disease
- Does **not** replace bedside clinical judgment
- Does **not** replace a full EMR for billing, scheduling, or comprehensive charting
- Does **not** allow unapproved drafts to drive alerts or surveillance

Its clinical contribution is foundational: **ensure that what enters electronic care systems is complete, verified, and trustworthy.**

---

## 10. Complete Patient Journey

The following narrative follows one patient from paper chart to ongoing digital care.

### Maria Santos — pneumonia admission

**Day 0 — Paper chart creation**  
Maria Santos is admitted to Internal Medicine with community-acquired pneumonia. Nursing staff record vital signs on a paper observation chart. The laboratory prints a white blood cell count onto a paper report. The face sheet lists demographics and emergency contacts. All of this lives in a physical folder at the bedside and nursing station.

**Hospital intake for digitization**  
As the facility prepares to activate electronic clinical monitoring, Medical Records and ward clerks assemble Maria’s active chart sections for digitization. An Intake Clerk scans the face sheet, a recent vitals page, and the lab report. Each upload becomes its own digitization batch in secure storage. Where a patient already exists, intake links the MRN; for first-time digitization, registration proceeds first.

**Scanning and identity**  
The scans are fingerprint-checked and retained. Cover sheets may accelerate classification on busy digitization days. Nothing clinical has entered the live database yet—only documents and empty or pre-filled draft shells awaiting human work.

**Data entry**  
A Data Entry Clerk opens Maria’s vitals batch. On the left, the handwritten chart; on the right, structured fields. Heart rate, SpO₂, temperature, and other observations are entered with the times written on the chart. A separate lab batch captures the white blood cell count. If OCR suggested values, the clerk corrects any misreads before submitting.

**Verification**  
A Verifier who did not enter the data opens the same scans. Each field is compared. A misread SpO₂ would be rejected with a clear reason. When all fields match, verification passes. Vitals and labs route into the clinical approval pathway appropriate for high-stakes observations.

**Clinical approval**  
A Clinical Approver reviews the structured content against the scans and authorizes promotion. For historical backfill, retroactive alerting remains off unless the facility explicitly chooses otherwise—Maria’s yesterday values should not create today’s false urgency.

**Promotion into the electronic record**  
In one governed step, Maria’s patient identity, encounter context, and observations become live clinical data. She now has a stable MRN and a digitization history that records every actor in the chain.

**Availability in the clinical monitoring platform**  
Promoted observations are visible to VigilCareClinical. Early warning scores and alert logic can use them according to facility policy. Unfinished drafts from other patients still in the entry queue remain invisible to scoring.

**Use during ongoing patient care**  
On subsequent rounds, physicians and nurses consult the clinician dashboard and patient history with greater confidence that electronic vitals and labs match the paper source that was verified. If SpO₂ was later found to be one point off, a correction batch supersedes the error without erasing the audit trail. When a clinician measures new vitals at the bedside (Track B), attestation promotes them immediately for real-time monitoring.

**Closing the loop**  
Maria’s care still depends on clinical judgment. What VigilCare Records contributed was quieter but essential: her paper chart did not leap unchecked into electronic alerting. It crossed a governed bridge—scan, entry, verification, approval, promotion—so that digital care rests on information the organization is prepared to defend.

---

## Appendix A — Status vocabulary (clinical reading)

| Status | Meaning in practice |
|---|---|
| Uploaded | Scan received; awaiting or ready for entry |
| In entry | Clerk actively drafting structured data |
| Pending verification | Submitted; waiting for second-person check |
| Rejected | Returned to entry with a reason |
| Verified | Passed data-quality check; awaiting promotion authorization |
| Awaiting clinical approval | High-stakes path; in clinical approver queue |
| Approved | Authorized; promotion in progress or completing |
| Promoted | Live in the permanent clinical database (terminal success) |
| Cancelled | Permanently stopped before promotion (terminal) |

---

## Appendix B — Quick reference for clinical leaders

| Question | Answer |
|---|---|
| Can OCR alone put labs in the chart? | No. Humans must review; verification still required. |
| Can the entry clerk verify their own work? | No. Separation of duties is enforced. |
| Do drafts trigger NEWS2 or sepsis screens? | No. Only promoted live observations do. |
| Can we fix a promoted wrong value by editing it? | No. Use a correction (supersession) batch. |
| Will backfilling old critical labs page the ward? | Not by default. Retroactive alerts are opt-in per batch. |
| Is this a full EMR? | No. It is the governed digitization precursor to clinical monitoring. |

---

*This guide is intended for clinical and administrative audiences evaluating VigilCare Records. For operator step-by-step instructions, see [digitization-workstation-guide.md](digitization-workstation-guide.md). For product requirements and implementation status, see [vigilcare-records-prd.md](vigilcare-records-prd.md).*
