ICD-10 Coding for Long Term Care 2018: Exploring Trends with National Inpatient Sample Data

The landscape of healthcare is constantly evolving, and understanding trends in patient care is crucial for policymakers, researchers, and healthcare providers alike. A key aspect of this understanding lies in the effective use and analysis of healthcare data, particularly concerning coding systems like ICD-10, which is vital for classifying diagnoses and procedures. For those focusing on long-term care in 2018, examining national datasets becomes indispensable for grasping the broader context of patient care and healthcare utilization. One such invaluable resource is the National Inpatient Sample (NIS).

The NIS, maintained by the Agency for Healthcare Research and Quality (AHRQ) as part of the Healthcare Cost and Utilization Project (HCUP), serves as a powerful tool for generating national estimates of hospital care in the United States. Researchers and policymakers leverage NIS data to gain insights into healthcare utilization patterns, costs, quality of care, and patient outcomes. Importantly, the NIS encompasses data from all types of hospital stays, irrespective of the expected payer, providing a comprehensive view of the inpatient healthcare landscape. With data available from 1988 up to 2022, the NIS allows for in-depth trend analysis over extended periods.

The NIS is derived from State Inpatient Databases (SID) and includes all inpatient data contributed to HCUP, encompassing a wide range of states, from an initial 8 to the current 47 states, plus the District of Columbia. This broad geographical coverage ensures that the NIS provides a robust representation of national inpatient care.

A significant redesign of the NIS occurred starting with the 2012 data year, refining its methodology to enhance the accuracy of national estimates. This redesign shifted the NIS to approximate a 20-percent stratified sample of all discharges from U.S. community hospitals, specifically excluding rehabilitation and long-term acute care hospitals to better focus on general community hospital trends. This change was marked by AHRQ renaming it from the “Nationwide Inpatient Sample” to the “National Inpatient Sample” to emphasize this design evolution.

The 2012 redesign incorporated three major improvements:

  • Sample Design Revisions: The NIS transitioned to sampling discharge records from all HCUP-participating hospitals, moving away from sampling hospitals and retaining all discharges.
  • Hospital Definition Revisions: The NIS adopted hospital and discharge definitions provided by statewide data organizations contributing to HCUP, aligning with state-level data standards rather than relying on the AHA Annual Survey definitions.
  • Confidentiality Enhancements: State and hospital identifiers were removed, along with other data elements not uniformly available across states, to bolster patient privacy and confidentiality.

This refined sampling strategy significantly enhances the precision of estimates by minimizing sampling error. For many calculations, the confidence intervals under the new design are approximately half the length compared to the previous NIS design, leading to more reliable statistical inferences.

Key features of the most recent NIS data (2022) highlight its strengths:

  • Broad Coverage: Drawn from all HCUP-participating states, the NIS covers over 97 percent of the U.S. population, ensuring national representativeness.
  • Representative Sample: It approximates a 20-percent stratified sample of discharges from U.S. community hospitals, excluding rehabilitation and long-term acute care facilities for targeted analysis.
  • Self-Weighting Design: The new NIS design reduces the margin of error and provides more stable and precise estimates compared to earlier versions.
  • Patient Confidentiality: Protection of patient privacy is ensured through the removal of State and hospital identifiers.
  • Large Sample Size: The NIS retains a substantial sample size, facilitating the analysis of rare conditions, uncommon treatments, and specific patient populations that might be relevant to long-term care settings when considered within community hospitals.

While the 2012 NIS redesign improved national estimates, it’s important to note the impact on certain types of analyses. The removal of hospital identifiers means that hospital linkages are no longer possible with the NIS. Furthermore, the sampling of discharges means that analyses requiring a complete census of discharges from sampled hospitals, such as hospital volume analysis, are no longer feasible using the NIS alone. For analyses requiring a census of discharges from individual hospitals, local market areas, or states, state inpatient data available through the HCUP Central Distributor can be utilized.

For a comprehensive understanding of the 2012 NIS redesign, the 2012 NIS Redesign Report provides detailed information. Additional details regarding the 2022 NIS can be found in the Introduction to the NIS, 2022 (PDF file, 1.3 MB). Archived information for previous years of the NIS is available in prior editions of the Introduction to the NIS at https://www.hcup-us.ahrq.gov/db/nation/nis/nisarchive.jsp.

By utilizing resources like the NIS and understanding the nuances of data collection and coding systems like ICD-10, stakeholders can gain valuable insights into the evolving healthcare landscape and make informed decisions concerning patient care and resource allocation, including within the context of long-term care considerations in 2018 and beyond.

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