Clinical Decision Support Backend

Clinical Decision Support App Backend Template
Logic-based medication safety checks, prescribing alerts, and clinician review workflows

Q: What is a Clinical Decision Support backend?

A Clinical Decision Support backend provides structured data models and APIs for evaluating prescribing actions against safety rules such as drug interactions and contraindications.

Q: What does this Clinical Decision Support template include?

It includes Patient, Medication, Prescription, InteractionRule, ContraindicationRule, and Alert classes, plus ER diagram, data dictionary, JSON schema, API playground, and an AI Agent prompt.

Q: How does this template help with medication safety?

It centralizes medication data, patient risk context, rule definitions, and alert history so prescribing apps can evaluate unsafe combinations consistently and transparently.

Q: How do I model a pairwise interaction rule?

Use an InteractionRule object with medicationA, medicationB, severity, rationale, recommendation, and active fields. Your evaluation logic should compare new prescriptions against the patient’s active medications.

Q: What patient factors are commonly used for contraindication checks?

Common inputs include allergies, diagnoses, pregnancy status, renal status, age-related considerations, and other structured clinical conditions captured on the Patient record or related objects.

Q: Can I support pharmacist review queues?

Yes. Filter Alert objects by severity, status, or reviewedBy to create pharmacist-oriented triage views and acknowledgment workflows.

Q: How does the AI Agent help with seeding data?

The AI Agent can generate sample patients, medications, prescriptions, interaction rules, contraindications, and alert scenarios so you can test realistic decision support flows quickly.

Q: What is the recommended approach for alert overrides?

Require authorized users, capture overrideReason and reviewedBy, and keep the original rule reference and severity intact so the rationale for the override remains auditable.

Q: How do I expand this template for formularies or lab-based checks?

Add classes for formulary coverage, lab results, or patient observations, then reference them in Cloud Code or rule evaluation services to enrich alert generation.

A production-ready Clinical Decision Support backend on Back4app for medication safety workflows, including prescriptions, interaction rules, contraindications, and alert logging. Use it to accelerate prescribing and review experiences across web and mobile.

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Key Takeaways

This template gives you a safety-focused backend for prescribing workflows: medication logic, patient risk context, and alert records so teams can ship clinical decision support features faster.

Medication safety data model — Model patients, medications, prescriptions, interaction rules, and contraindications in one canonical schema.
Logic-based alert generation — Evaluate active prescriptions against known interaction and contraindication rules to surface actionable alerts.
Severity-aware workflows — Classify alerts by clinical importance so high-risk combinations can be prioritized in dashboards and review queues.
Review and acknowledgment history — Track when alerts were generated, who reviewed them, and whether they were overridden, accepted, or dismissed.
Cross-platform API access — Serve prescribing tools, pharmacy dashboards, and mobile review apps through REST and GraphQL with optional Live Queries.

What Is the Clinical Decision Support App Backend Template?

Back4app is a managed backend for rapid product delivery. The Clinical Decision Support App Backend Template models prescribing context, drug safety rules, and alert outcomes so teams can implement clinical decision support without starting from scratch.

Best for:

Medication safety applicationsPrescribing review toolsPharmacy decision support dashboardsDrug interaction alerting systemsContraindication screening workflowsHealthcare MVPs and internal tools

Overview

Clinical decision support systems help clinicians identify unsafe prescribing combinations before they become harmful events. That requires structured medication data, patient context, and deterministic rule evaluation.

This template defines Patient, Medication, Prescription, InteractionRule, ContraindicationRule, and Alert with permissions and optional Live Queries so teams can implement medication safety workflows quickly and safely.

Core Clinical Decision Support Features

Every technology card in this hub uses the same Clinical Decision Support schema with Patient, Medication, Prescription, InteractionRule, ContraindicationRule, and Alert.

Patient context and risk factors

Track patient identifiers, demographics, allergies, diagnoses, pregnancy status, renal considerations, and other screening inputs.

Medication catalog

Store normalized medication records with generic name, brand, therapeutic class, route, strength, and code mappings.

Prescription management

Prescription objects represent active or proposed orders with patient, medication, dose, frequency, route, and status.

Interaction and contraindication rules

Model pairwise or patient-specific rules with severity, rationale, recommendation text, and triggering conditions.

Generated alerts and review outcomes

Alert records capture what rule fired, which prescription triggered it, severity, message, and clinician response.

Why Build Your Clinical Decision Support Backend with Back4app?

Back4app gives you a secure backend contract for medication safety apps, handling auth, schema management, APIs, and real-time updates so your team can focus on clinical UX and rule quality.

•Prebuilt decision support primitives: Start with structured classes for prescriptions, medications, interaction rules, contraindications, and alerts instead of designing the backend from zero.
•Traceable alert workflows: Persist generated alerts, review outcomes, and override metadata so safety decisions remain inspectable across teams.
•Flexible integration surface: Expose REST and GraphQL APIs for prescribing systems, pharmacy tools, or embedded widgets, while using Live Queries for alert queues that must stay current.

Standardize medication safety workflows across web and mobile with one backend contract and reduce time-to-market for clinical decision support features.

Core Benefits

A medication safety backend that helps you ship faster without losing structure, traceability, or control.

Faster prescribing workflow delivery

Start from a pre-built schema for prescriptions and rules so your team can focus on alert UX, review flows, and integration logic.

Structured medication safety logic

Represent interaction and contraindication logic as first-class backend objects instead of hardcoded rules scattered across clients.

Clear review accountability

Store alert acknowledgment and override metadata so clinical decisions remain attributable and auditable.

Real-time alert queues

Live Queries can push newly created alerts to clinician or pharmacist dashboards as prescribing activity occurs.

Integration-ready APIs

Connect to EHRs, medication knowledge services, or internal prescribing apps using REST or GraphQL endpoints.

AI-assisted scaffolding

Use the AI Agent prompt to scaffold the backend, sample medications, rules, and realistic alert scenarios.

Ready to build medication safety workflows?

Let the Back4app AI Agent scaffold the Clinical Decision Support backend and seed sample medications, contraindications, and alert logs from one prompt.

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Technical Stack

Everything included in this Clinical Decision Support backend template.

Frontend

13+ technologies

Backend

Back4app

Database

MongoDB

Auth

Built-in auth + roles

API

REST and GraphQL

Realtime

Live Queries

ER Diagram

Entity relationship model for the Clinical Decision Support schema.

ER Diagram

View diagram source

Mermaid

erDiagram
    User ||--o{ Allergy : "records"
    User ||--o{ MedicationOrder : "orders"
    User ||--o{ Alert : "acknowledges"
    User ||--o{ AuditLog : "actor_of"
    Patient ||--o{ Allergy : "has"
    Patient ||--o{ MedicationOrder : "receives"
    Patient ||--o{ Alert : "impacted_by"
    Medication ||--o{ MedicationOrder : "prescribed_as"
    Medication ||--o{ InteractionRule : "rule_primary"
    Medication ||--o{ InteractionRule : "rule_secondary"
    MedicationOrder ||--o{ Alert : "triggers"
    InteractionRule ||--o{ Alert : "generates"

    User {
        String objectId PK
        String username
        String email
        String role
        String displayName
        String specialty
        Date createdAt
        Date updatedAt
    }

    Patient {
        String objectId PK
        String medicalRecordNumber
        String fullName
        Date dateOfBirth
        String sex
        Number weightKg
        String renalImpairmentStage
        String pregnancyStatus
        Date createdAt
        Date updatedAt
    }

    Medication {
        String objectId PK
        String name
        String genericName
        String rxNormCode
        String drugClass
        String form
        String strength
        Array contraindicationTags
        Date createdAt
        Date updatedAt
    }

    Allergy {
        String objectId PK
        Pointer patient FK
        String substanceName
        String reaction
        String severity
        String status
        Pointer recordedBy FK
        Date createdAt
        Date updatedAt
    }

    MedicationOrder {
        String objectId PK
        Pointer patient FK
        Pointer medication FK
        Pointer orderedBy FK
        String dose
        String route
        String frequency
        Date startDate
        String status
        String indication
        Date createdAt
        Date updatedAt
    }

    InteractionRule {
        String objectId PK
        String ruleName
        String ruleType
        Pointer medicationA FK
        Pointer medicationB FK
        String contraindicationTag
        String severity
        String messageTemplate
        String recommendedAction
        Boolean isActive
        Date createdAt
        Date updatedAt
    }

    Alert {
        String objectId PK
        Pointer patient FK
        Pointer medicationOrder FK
        Pointer rule FK
        String severity
        String status
        String message
        String recommendedAction
        Pointer acknowledgedBy FK
        Date acknowledgedAt
        String overrideReason
        Date createdAt
        Date updatedAt
    }

    AuditLog {
        String objectId PK
        Pointer actor FK
        String action
        String targetClass
        String targetId
        String details
        Date timestamp
    }

Integration Flow

Auth-to-CRUD flow for clinician login, loading patient medications, creating a prescription, and generating interaction or contraindication alerts.

ER Diagram

View diagram source

Mermaid

sequenceDiagram
  participant User as Clinician
  participant App as Clinical Decision Support App
  participant Back4app as Back4app Cloud

  User->>App: Sign in to medication review workspace
  App->>Back4app: POST /login (username, password)
  Back4app-->>App: Session token + user profile

  User->>App: Open patient medication chart
  App->>Back4app: GET /classes/Patient, /classes/MedicationOrder, /classes/Allergy
  Back4app-->>App: Patient profile, active orders, allergy list

  User->>App: Enter a new medication order
  App->>Back4app: POST /classes/MedicationOrder (patient, medication, dose, route, frequency)
  Back4app-->>App: MedicationOrder created

  App->>Back4app: GET /classes/InteractionRule?where=applicable_to_order
  Back4app-->>App: Matching drug-interaction and contraindication rules
  App->>Back4app: POST /classes/Alert (patient, medicationOrder, rule, severity, message)
  Back4app-->>App: Alert records saved

  Back4app-->>App: Live Query events for new or updated alerts
  App-->>User: Show real-time warnings, acknowledgement, or override options

Data Dictionary

Full field-level reference for every class in the Clinical Decision Support schema.

Field	Type	Description	Required
objectId	String	Auto-generated unique identifier	Auto
username	String	Login username for clinician or pharmacist
email	String	User email address
password	String	Hashed password (write-only)
role	String	Role such as physician, pharmacist, nurse, admin
displayName	String	Full name used in clinical workflows	—
specialty	String	Clinical specialty or department	—
createdAt	Date	Auto-generated creation timestamp	Auto
updatedAt	Date	Auto-generated last-update timestamp	Auto

9 fields in User

Security and Permissions

How ACL, roles, and CLP strategy secure patient data, prescribing logic, and alert workflows.

Role-based access

Use roles such as clinician, pharmacist, reviewer, and admin to scope CRUD operations and UI capabilities across prescriptions, rules, and alerts.

Protected rule authoring

Limit creation and modification of interaction and contraindication rules to trusted reviewers or administrators so alert logic cannot be changed by general client users.

Patient privacy and alert integrity

Restrict patient-linked prescriptions and alert records with ACLs, and preserve review history so acknowledgment and override actions remain attributable.

Schema (JSON)

Raw JSON schema definition ready to copy into Back4app or use as implementation reference.

JSON

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{
  "classes": [
    {
      "className": "User",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "username": {
          "type": "String",
          "required": true
        },
        "email": {
          "type": "String",
          "required": true
        },
        "password": {
          "type": "String",
          "required": true
        },
        "role": {
          "type": "String",
          "required": true
        },
        "displayName": {
          "type": "String",
          "required": false
        },
        "specialty": {
          "type": "String",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "Patient",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "medicalRecordNumber": {
          "type": "String",
          "required": true
        },
        "fullName": {
          "type": "String",
          "required": true
        },
        "dateOfBirth": {
          "type": "Date",
          "required": true
        },
        "sex": {
          "type": "String",
          "required": false
        },
        "weightKg": {
          "type": "Number",
          "required": false
        },
        "renalImpairmentStage": {
          "type": "String",
          "required": false
        },
        "pregnancyStatus": {
          "type": "String",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "Medication",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "name": {
          "type": "String",
          "required": true
        },
        "genericName": {
          "type": "String",
          "required": false
        },
        "rxNormCode": {
          "type": "String",
          "required": false
        },
        "drugClass": {
          "type": "String",
          "required": false
        },
        "form": {
          "type": "String",
          "required": false
        },
        "strength": {
          "type": "String",
          "required": false
        },
        "contraindicationTags": {
          "type": "Array",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "Allergy",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "patient": {
          "type": "Pointer",
          "required": true,
          "targetClass": "Patient"
        },
        "substanceName": {
          "type": "String",
          "required": true
        },
        "reaction": {
          "type": "String",
          "required": false
        },
        "severity": {
          "type": "String",
          "required": true
        },
        "status": {
          "type": "String",
          "required": true
        },
        "recordedBy": {
          "type": "Pointer",
          "required": true,
          "targetClass": "User"
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "MedicationOrder",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "patient": {
          "type": "Pointer",
          "required": true,
          "targetClass": "Patient"
        },
        "medication": {
          "type": "Pointer",
          "required": true,
          "targetClass": "Medication"
        },
        "orderedBy": {
          "type": "Pointer",
          "required": true,
          "targetClass": "User"
        },
        "dose": {
          "type": "String",
          "required": false
        },
        "route": {
          "type": "String",
          "required": true
        },
        "frequency": {
          "type": "String",
          "required": false
        },
        "startDate": {
          "type": "Date",
          "required": true
        },
        "status": {
          "type": "String",
          "required": true
        },
        "indication": {
          "type": "String",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "InteractionRule",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "ruleName": {
          "type": "String",
          "required": true
        },
        "ruleType": {
          "type": "String",
          "required": true
        },
        "medicationA": {
          "type": "Pointer",
          "required": false,
          "targetClass": "Medication"
        },
        "medicationB": {
          "type": "Pointer",
          "required": false,
          "targetClass": "Medication"
        },
        "contraindicationTag": {
          "type": "String",
          "required": false
        },
        "severity": {
          "type": "String",
          "required": true
        },
        "messageTemplate": {
          "type": "String",
          "required": true
        },
        "recommendedAction": {
          "type": "String",
          "required": false
        },
        "isActive": {
          "type": "Boolean",
          "required": true
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "Alert",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "patient": {
          "type": "Pointer",
          "required": true,
          "targetClass": "Patient"
        },
        "medicationOrder": {
          "type": "Pointer",
          "required": true,
          "targetClass": "MedicationOrder"
        },
        "rule": {
          "type": "Pointer",
          "required": true,
          "targetClass": "InteractionRule"
        },
        "severity": {
          "type": "String",
          "required": true
        },
        "status": {
          "type": "String",
          "required": true
        },
        "message": {
          "type": "String",
          "required": true
        },
        "recommendedAction": {
          "type": "String",
          "required": false
        },
        "acknowledgedBy": {
          "type": "Pointer",
          "required": false,
          "targetClass": "User"
        },
        "acknowledgedAt": {
          "type": "Date",
          "required": false
        },
        "overrideReason": {
          "type": "String",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "AuditLog",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "actor": {
          "type": "Pointer",
          "required": true,
          "targetClass": "User"
        },
        "action": {
          "type": "String",
          "required": true
        },
        "targetClass": {
          "type": "String",
          "required": false
        },
        "targetId": {
          "type": "String",
          "required": false
        },
        "details": {
          "type": "String",
          "required": false
        },
        "timestamp": {
          "type": "Date",
          "required": true
        }
      }
    }
  ]
}

Build with AI Agent

Use the Back4app AI Agent to generate a full Clinical Decision Support app from this template, including frontend, backend, auth, medication rules, and alert workflows.

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Create a Clinical Decision Support backend on Back4app with this exact schema and behavior.

Schema:
1. Patient: externalId (String, required), fullName (String, required), dateOfBirth (Date), allergies (Array), diagnoses (Array), pregnancyStatus (String, optional), renalStatus (String, optional), objectId, createdAt, updatedAt (system).
2. Medication: code (String, required), genericName (String, required), brandName (String), therapeuticClass (String), routeOptions (Array), strength (String), active (Boolean), objectId, createdAt, updatedAt.
3. Prescription: patient (Pointer to Patient, required), medication (Pointer to Medication, required), dose (String), frequency (String), route (String), status (String: proposed, active, stopped), prescribedBy (Pointer to User), startDate (Date), endDate (Date, optional), objectId, createdAt, updatedAt.
4. InteractionRule: medicationA (Pointer to Medication, required), medicationB (Pointer to Medication, required), severity (String: low, moderate, high, critical), rationale (String), recommendation (String), active (Boolean), objectId, createdAt, updatedAt.
5. ContraindicationRule: medication (Pointer to Medication, required), conditionType (String), conditionValue (String), severity (String: caution, warning, contraindicated), rationale (String), active (Boolean), objectId, createdAt, updatedAt.
6. Alert: patient (Pointer to Patient, required), prescription (Pointer to Prescription, required), alertType (String: interaction, contraindication), severity (String), message (String), status (String: open, acknowledged, overridden, resolved), ruleRef (Pointer to InteractionRule or ContraindicationRule), reviewedBy (Pointer to User, optional), overrideReason (String, optional), objectId, createdAt, updatedAt.

Security:
- Role-based CLP and ACL: only authorized clinicians and pharmacists can create or review prescriptions and alerts. Only reviewers or admins can change rules. Patient-linked data must be read-restricted.

Auth:
- Clinicians and reviewers sign up and log in via built-in User; roles assigned by admin.

Behavior:
- Authenticate user, load a patient's active prescriptions, create a proposed Prescription, evaluate it against InteractionRule and ContraindicationRule objects, and create Alert records for any matches.

Deliver:
- Back4app app with schema, ACLs, CLPs, Cloud Code validations, seeded sample data, and a frontend scaffold per chosen technology.

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API Playground

Try REST and GraphQL endpoints against the Clinical Decision Support schema. Responses use mock data and do not require a Back4app account.

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Uses the same schema as this template.

Choose Your Technology

Expand each card for integration steps, state patterns, data model examples, and offline notes.

What You Get with Every Technology

Every stack uses the same Clinical Decision Support backend schema and API contracts.

Unified clinical decision support data structure

A comprehensive schema tailored for clinical decision support, ensuring consistency and ease of use.

Real-time drug safety alerts

Instant notifications regarding potential drug interactions or safety concerns during prescribing.

Customizable clinical guidelines

Easily adapt clinical protocols and guidelines to fit specific clinical decision support needs and regulations.

REST/GraphQL APIs for integration

Seamlessly connect with other systems using flexible APIs designed for clinical decision support applications.

Secure patient data sharing

Robust mechanisms for sharing sensitive patient information while maintaining privacy and compliance.

Extensible architecture for growth

Build and scale your clinical decision support solution effortlessly with an architecture that supports future enhancements.

Clinical Decision Support Framework Comparison

Compare setup speed, SDK style, and AI support across all supported technologies.

Framework	Setup Time	Clinical Decision Support Benefit	SDK Type	AI Support
Flutter	~5 min	Single codebase for clinical decision support on mobile and web.	Typed SDK	Full
React	About 5 min	Fast web dashboard for clinical decision support.	Typed SDK	Full
React Native	Under 5 minutes	Cross-platform mobile app for clinical decision support.	Typed SDK	Full
Next.js	~3–7 min	Server-rendered web app for clinical decision support.	Typed SDK	Full
JavaScript	~3–5 min	Lightweight web integration for clinical decision support.	Typed SDK	Full
Android	~5 min	Native Android app for clinical decision support.	Typed SDK	Full
iOS	About 5 min	Native iOS app for clinical decision support.	Typed SDK	Full
Vue	Under 5 minutes	Reactive web UI for clinical decision support.	Typed SDK	Full
Angular	~3–7 min	Enterprise web app for clinical decision support.	Typed SDK	Full
GraphQL	Under 2 min	Flexible GraphQL API for clinical decision support.	GraphQL API	Full
REST API	Quick (2 min) setup	REST API integration for clinical decision support.	REST API	Full
PHP	~3 min	Server-side PHP backend for clinical decision support.	REST API	Full
.NET	Under 5 minutes	.NET backend for clinical decision support.	Typed SDK	Full

Setup time reflects expected duration from project bootstrap to first patient prescription review screen populated with medications and alerts.

Frequently Asked Questions

Common questions about building a Clinical Decision Support backend with this template.

What is a Clinical Decision Support backend?

What does this Clinical Decision Support template include?

How does this template help with medication safety?

How do I model a pairwise interaction rule?

What patient factors are commonly used for contraindication checks?

Can I support pharmacist review queues?

How does the AI Agent help with seeding data?

What is the recommended approach for alert overrides?

How do I expand this template for formularies or lab-based checks?

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Clinical Decision Support App Backend TemplateLogic-based medication safety checks, prescribing alerts, and clinician review workflows

Key Takeaways

What Is the Clinical Decision Support App Backend Template?

Overview

Core Clinical Decision Support Features

Patient context and risk factors

Medication catalog

Prescription management

Interaction and contraindication rules

Generated alerts and review outcomes

Why Build Your Clinical Decision Support Backend with Back4app?

Core Benefits

Faster prescribing workflow delivery

Structured medication safety logic

Clear review accountability

Real-time alert queues

Integration-ready APIs

AI-assisted scaffolding

Ready to build medication safety workflows?

Technical Stack

ER Diagram

Integration Flow

Data Dictionary

Security and Permissions

Role-based access

Protected rule authoring

Patient privacy and alert integrity

Schema (JSON)

Build with AI Agent

API Playground

Choose Your Technology

Flutter Clinical Decision Support Backend

React Clinical Decision Support Backend

React Native Clinical Decision Support Backend

Next.js Clinical Decision Support Backend

JavaScript Clinical Decision Support Backend

Android Clinical Decision Support Backend

iOS Clinical Decision Support Backend

Vue Clinical Decision Support Backend

Angular Clinical Decision Support Backend

GraphQL Clinical Decision Support Backend

REST API Clinical Decision Support Backend

PHP Clinical Decision Support Backend

.NET Clinical Decision Support Backend

What You Get with Every Technology

Unified clinical decision support data structure

Real-time drug safety alerts

Customizable clinical guidelines

REST/GraphQL APIs for integration

Secure patient data sharing

Extensible architecture for growth

Clinical Decision Support Framework Comparison

Frequently Asked Questions

Trusted by healthcare product teams

Ready to Build Your Clinical Decision Support App?

Clinical Decision Support App Backend Template
Logic-based medication safety checks, prescribing alerts, and clinician review workflows