Development of a disease-based hospital-level diagnostic intensity index

Michael I. Ellenbogen; Leonard S. Feldman; Laura Prichett; Junyi Zhou; Daniel J. Brotman

doi:10.1515/dx-2023-0184

Article

Development of a disease-based hospital-level diagnostic intensity index

Michael I. Ellenbogen , Leonard S. Feldman , Laura Prichett , Junyi Zhou and Daniel J. Brotman

Published/Copyright: April 22, 2024

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From the journal Diagnosis Volume 11 Issue 3

Abstract

Objectives

Low-value care is associated with increased healthcare costs and direct harm to patients. We sought to develop and validate a simple diagnostic intensity index (DII) to quantify hospital-level diagnostic intensity, defined by the prevalence of advanced imaging among patients with selected clinical diagnoses that may not require imaging, and to describe hospital characteristics associated with high diagnostic intensity.

Methods

We utilized State Inpatient Database data for inpatient hospitalizations with one or more pre-defined discharge diagnoses at acute care hospitals. We measured receipt of advanced imaging for an associated diagnosis. Candidate metrics were defined by the proportion of inpatients at a hospital with a given diagnosis who underwent associated imaging. Candidate metrics exhibiting temporal stability and internal consistency were included in the final DII. Hospitals were stratified according to the DII, and the relationship between hospital characteristics and DII score was described. Multilevel regression was used to externally validate the index using pre-specified Medicare county-level cost measures, a Dartmouth Atlas measure, and a previously developed hospital-level utilization index.

Results

This novel DII, comprised of eight metrics, correlated in a dose-dependent fashion with four of these five measures. The strongest relationship was with imaging costs (odds ratio of 3.41 of being in a higher DII tertile when comparing tertiles three and one of imaging costs (95 % CI 2.02–5.75)).

Conclusions

A small set of medical conditions and related imaging can be used to draw meaningful inferences more broadly on hospital diagnostic intensity. This could be used to better understand hospital characteristics associated with low-value care.

Keywords: low-value care; overuse; diagnostic testing; hospital variation

Corresponding author: Michael I. Ellenbogen, MD, Assistant Professor of Medicine, Department of Medicine, Johns Hopkins School of Medicine, 600 N Wolfe St, Meyer 8-134, Baltimore, MD 21287, USA, Phone: 443-287-4362, Fax: 410-502-0923, E-mail: mellenb6@jhmi.edu

Funding source: Agency for Healthcare Research and Quality

Award Identifier / Grant number: 1K08HS028673-01A1

Funding source: Johns Hopkins Hospitalist Innovation Grant

Research ethics: Research involving human subjects complied with all relevant national regulations, institutional policies and is in accordance with the tenets of the Helsinki Declaration (as revised in 2013), and has been approved by Authors’ Institutional Review Board (nr 07/2019).
Informed consent: Informed consent was not required because we did not perform additional biochemical analysis. Confidentiality was guaranteed and no interventions were performed beyond ordinary good and standard clinical practices.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interests: The authors state no conflict of interest.
Research funding: Dr. Ellenbogen is supported by AHRQ 1K08HS028673-01A1 and a Johns Hopkins Hospitalist Innovation Grant.
Data availability: The raw data cannot be obtained on request from the corresponding author because of a data use agreement.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/dx-2023-0184).

Received: 2023-12-30

Accepted: 2024-04-01

Published Online: 2024-04-22

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Articles in the same Issue

https://doi.org/10.1515/dx-2023-0184

Keywords for this article

low-value care; overuse; diagnostic testing; hospital variation