Context

The Healthcare Common Procedure Coding System (HCPCS, often pronounced by its acronym as "hick picks") is a set of health care procedure codes based on the American Medical Association's Current Procedural Terminology (CPT).

HCPCS includes three levels of codes: Level I consists of the American Medical Association's Current Procedural Terminology (CPT) and is numeric. Level II codes are alphanumeric and primarily include non-physician services such as ambulance services and prosthetic devices, and represent items and supplies and non-physician services, not covered by CPT-4 codes (Level I). Level III codes, also called local codes, were developed by state Medicaid agencies, Medicare contractors, and private insurers for use in specific programs and jurisdictions. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) instructed CMS to adopt a standard coding systems for reporting medical transactions. The use of Level III codes was discontinued on December 31, 2003, in order to adhere to consistent coding standards.

Content

Classification of procedures performed for patients is important for billing and reimbursement in healthcare. The primary classification system used in the United States is Healthcare Common Procedure Coding System (HCPCS), maintained by Centers for Medicare and Medicaid Services (CMS). This system is divided into two levels: level I and level II.

Level I HCPCS codes classify services rendered by physicians. This system is based on Common Procedure Terminology (CPT), a coding system maintained by the American Medical Association (AMA). Level II codes, which are the focus of this public dataset, are used to identify products, supplies, and services not included in level I codes. The level II codes include items such as ambulance services, durable medical goods, prosthetics, orthotics and supplies used outside a physician’s office.

Given the ubiquity of administrative data in healthcare, HCPCS coding systems are also commonly used in areas of clinical research such as outcomes based research.

Update Frequency: Yearly

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Acknowledgements

https://bigquery.cloud.google.com/table/bigquery-public-data:cms_codes.hcpcs

https://cloud.google.com/bigquery/public-data/hcpcs-level2

Dataset Source: Center for Medicare and Medicaid Services. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

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Inspiration

What are the descriptions for a set of HCPCS level II codes?

We present the INSPIRE dataset, a publicly available research dataset in perioperative medicine, which includes approximately 130,000 cases (50% of all surgical cases) who underwent anesthesia for surgery at an academic institution in South Korea between 2011 and 2020. This comprehensive dataset includes patient characteristics such as age, sex, American Society of Anesthesiologists physical status classification, diagnosis, surgical procedure code, department, and type of anesthesia. It also includes vital signs in the operating theatre, general wards, and intensive care units (ICUs), laboratory results from six months before admission to six months after discharge, and medication during hospitalization. Complications include total hospital and ICU length of stay and in-hospital death. We hope this dataset will inspire collaborative research and development in perioperative medicine and serve as a reproducible external validation dataset to improve surgical outcomes.

Classification of procedures performed for patients is important for billing and reimbursement in healthcare. The primary classification system used in the United States is Healthcare Common Procedure Coding System (HCPCS), maintained by Centers for Medicare and Medicaid Services (CMS). This system is divided into two levels: level I and level II. Level I HCPCS codes classify services rendered by physicians. This system is based on Common Procedure Terminology (CPT), a coding system maintained by the American Medical Association (AMA). Level II codes, which are the focus of this public dataset, are used to identify products, supplies, and services not included in level I codes. The level II codes include items such as ambulance services, durable medical goods, prosthetics, orthotics and supplies used outside a physician’s office. Given the ubiquity of administrative data in healthcare, HCPCS coding systems are also commonly used in areas of clinical research such as outcomes based research. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

Evaluation metrics of the 6 most (top 6 rows) and least (bottom 6 rows) common CPT codes (among 100) across the classification models with TF IDF consistently performing better.

📰 Related paper

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:mortar_board: Related course for classification tasks

Design, Train & Test deep CNN for Image Classification. Join the course & enjoy new opportunities to get deep learning skills: https://www.udemy.com/course/convolutional-neural-networks-for-image-classification/

https://github.com/sichkar-valentyn/1-million-images-for-Traffic-Signs-Classification-tasks/blob/main/images/slideshow_classification.gif?raw=true%20=470x516" alt="CNN Course" title="CNN Course">

🗺️ Concept Map of the Course

https://github.com/sichkar-valentyn/1-million-images-for-Traffic-Signs-Classification-tasks/blob/main/images/concept_map.png?raw=true%20=570x410" alt="Concept map" title="Concept map">

👉 Join the Course

https://www.udemy.com/course/convolutional-neural-networks-for-image-classification/

:triangular_flag_on_post: About the dataset

The dataset to be pre-processed is taken from "light" version of the following dataset: https://www.kaggle.com/valentynsichkar/traffic-signs-1-million-images-for-classification

Find the detailed procedure on how the dataset is pre-processed in the notebook here (the description is for "original" version, but the procedure is the same): https://www.kaggle.com/valentynsichkar/pre-processing-of-traffic-signs-dataset/

Light version

classes indexes: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42]

classes frequency: [3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010
 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010
 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010 3010
 3010]

Shape of 'x_train' and 'y_train'
(129430, 48, 48, 3)
(129430,)

Resulted pre-processed 4 files are as following: - dataset_ts_gray_255_mean_light.hdf5 Gray TS images /255.0 Normalization, Mean Normalization - dataset_ts_gray_255_mean_std_light.hdf5 Gray TS images /255.0 Normalization, Mean Normalization, Standard Deviation - dataset_ts_rgb_255_mean_light.hdf5 RGB TS images /255.0 Normalization, Mean Normalization - dataset_ts_rgb_255_mean_std_light.hdf5 RGB TS images /255.0 Normalization, Mean Normalization, Standard Deviation

Experiment classification online here: https://valentynsichkar.name/traffic_signs.html

Acknowledgements

Initial data is The German Traffic Sign Recognition Benchmarks (GTSRB).

Inspiration

Which Neural Network do you use?

Procedure for classification L 214-17 of the Environmental Code The decrees classifying rivers as List 1 and List 2 under Article L.214-17 of the Environmental Code were signed on 10 July 2012 by the Loire-Bretagne Basin Coordinating Prefect and published in the Official Journal on 22 July. The procedure conducted by the Loire-Bretagne Basin Coordinating Prefect was launched in April 2010. This new ranking of watercourses contributes to the implementation of the Sdage 2010-2015, integrating the challenges linked to ecological continuity and framing the various European regulations. The definition of this new classification was first marked by departmental consultations with water stakeholders and a study of the impact of classifications on uses, which enabled us to understand the economic and environmental costs and benefits, both commercial and non-market, brought by the classification. As a second step, and after harmonisation at basin level, the draft classification was submitted for consultation with the General Councils, the Regions, the Regional Public Establishments of Basin and the Local Water Commissions.

Model performance metrics for predicting the top 100 common CPT codes from operative notes.

This dataset provides supplementary methods and a supplementary table for an article entitled: “High rates of potentially unnecessary topical antifungal prescribing in a large commercial health insurance claims database, United States.” The supplementary table provides International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and Current Procedural Terminology (CPT) codes used to identify diagnoses and procedures of interest.

This dataset contains the information on the International Classification of Diseases, Clinical Modification, New And Revised ICD-10-PCS Codes FY 2018 file, ICD-10-PCS. These 2018 ICD-10-PCS codes are to be used for discharges occurring from October 1, 2017 through September 30, 2018.

CPT Complexity: This table lists the top 5 least and most common CPTs along with their descriptions.

ICD-10-GM codes for the identification of SSI and designated NRZ classification.