返回榜单
ICD-10-CM 2026: Medical Codes

ICD-10-CM 2026: Medical Codes

VLR Software

Medical免费v4.05
App Store
评分

N/A

星级

☆☆☆☆☆

最近更新

2026年5月9日

发布日期

2015年5月25日

更新内容

v4.05

- Bug fixes and improvements.

应用信息

开发者
VLR Software
分类
Medical
价格
免费
版本
4.05
App ID
723770850

简介

ICD-10-CM 2026: PROFESSIONAL EDITION ▶ STAY COMPLIANT. OWN YOUR DATA. Get the definitive 2026 ICD-10-CM database for a single, one-time purchase. No subscriptions, no hidden monthly fees—just the most reliable coding tool in your pocket. ▶ WHAT’S NEW FOR 2026: FY 2026 READY: Includes all October 2025 and April 2026 code releases. PERMANENT ACCESS: Your purchase grants you lifetime access to the 2026 codeset. ▶ PROFESSIONAL WORKFLOW (PREMIUM)* Speed up your billing and coding with our most requested features: ▶ ICLOUD SYNC Your favorites and custom folders automatically sync across your iPhone and iPad. Start working on one device and pick up right where you left off on another. ▶ UNLIMITED FAVORITES & FOLDERS Tag your most used codes and organize them into custom folders by specialty, clinic, or project for instant access anywhere. ▶ ADVANCED HIGHLIGHTING Visual cues in search results help you distinguish between similar diagnoses rapidly. ▶ CORE CODING TOOLS (INCLUDED): OFFLINE SEARCH: Search-as-you-type engine requires no internet connection. FULL CLINICAL DETAIL: Includes Type 1 & 2 Excludes, Includes, and full tabular descriptions. HIERARCHICAL BROWSE: Navigate by Chapter, Section, and Sub-section with a single tap. ▶ DESIGNED FOR PROFESSIONALS: Optimized for iOS 19 and the latest devices. Clean, high-contrast interface designed for fast use in clinical and billing environments. Terms of Services on: https://www.vlrsoftware.com/app/icd10-medical-codes/terms Privacy Policy: https://www.vlrsoftware.com/app/icd10-medical-codes/privacy *Folder creation and search highlighting are available via a one-time In-App Purchase (IAP).

下载量预测

专业 · 预览

预估总下载量

000
保守估计乐观估计

0

低 / 月

0

预估 / 月

0

高 / 月

基于0 条评分
假设评分率1.4%
应用年龄134 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。