SPARCS Hospital Inpatient Economics Dataset

Columns

• Year: The calendar year in which the discharges occurred.
• Facility Id: A unique identifier for the facility.
• Facility Name: The name of the facility where services were performed, based on the Permanent Facility Identifier (PFI).
• APR DRG Code: The All Payer Refined Diagnosis Related Group (APR-DRG) Classification Code.
• APR Severity of Illness Code: A numerical code indicating severity (1 to 4).
• APR DRG Description: The text description corresponding to the APR-DRG Classification Code (e.g., Diabetes).
• APR Severity of Illness Description: Description of the severity level: Minor, Moderate, Major, or Extreme.
• APR Medical Surgical Code: Classification indicating if the discharge was Medical (M), Surgical (P), or Other (NA).
• APR Medical Surgical Description: The specific text description of the medical or surgical classification.
• Discharges: The total number of discharges recorded.
• Mean Charge: The average charge per discharge.
• Median Charge: The median charge per discharge.
• Mean Cost: The average cost per discharge.
• Median Cost: The median cost per discharge.

Distribution

• Format: CSV
• Size: 154.79 MB
• Structure: The dataset consists of approximately 1.08 million records (rows) and 14 columns.

Usage

• Healthcare Cost Analysis: Benchmarking hospital charges and costs across different facilities and regions.
• Policy Research: Evaluating the economic impact of specific diagnoses and treatments over time.
• Market Transparency: Assisting insurers and patients in understanding cost variations for medical and surgical procedures.
• Operational Efficiency: Analysing discharge volumes and severity levels to optimise hospital resource allocation.

Coverage

• Geographic Scope: New York State, covering 282 hospitals.
• Time Range: Data spans from 2009 to 2017.
• Demographic/Scope: Includes Article 28 hospitals; covers various severity levels (Minor to Extreme) and classifications (Medical and Surgical).

License

Who Can Use It

• Health Economists: For analysing trends in inpatient costs and pricing structures.
• Policy Makers: To monitor compliance with transparency goals and assess statewide health expenditure.
• Hospital Administrators: For competitive benchmarking and strategic planning.
• Data Scientists: To build predictive models regarding hospital discharges and costs.
• General Public: For gaining insight into hospital fees and transparency.

Dataset Name Suggestions

• NYS Hospital Inpatient Cost & Discharge Metrics (2009-2017)
• New York State Article 28 Hospital Cost Transparency Data
• NYS Inpatient Charges, Costs, and Severity Analysis
• SPARCS Hospital Inpatient Economics Dataset

Attributes