Developing and refining methods to measure hospital-level diagnostic intensity, identify outlier hospitals, and characterize the relationship between diagnostic intensity and missed diagnoses
Project Number1K08HS028673-01A1
Former Number1K08HS028673-01
Contact PI/Project LeaderELLENBOGEN, MICHAEL
Awardee OrganizationJOHNS HOPKINS UNIVERSITY
Description
Abstract Text
PROJECT SUMMARY/ABSTRACT
The provision of low-value medical services contributes to high healthcare costs in the US. Studies showing
regional variation in the intensity of healthcare provision within the US that are not explained by differences in
medical complexity and not associated with differences in outcomes demonstrate that low-value healthcare is
not homogenously distributed throughout the country. However, variation in healthcare intensity at the hospital
level has not been well-studied. Well-calibrated and validated hospital-level measures of diagnostic intensity
are lacking. Effective methods to identify outlier hospitals with respect to diagnostic intensity will allow a better
understanding of the drivers of low-value care and diagnostic overuse. Additionally, this will allow for better
characterization of the relationship between diagnostic intensity and quality of care, specifically missed
diagnoses. It will also allow identification of hospitals with lower levels of diagnostic testing and yet low rates of
missed diagnoses so their care processes can be studied and replicated.
The candidate is a hospitalist physician and junior investigator at Johns Hopkins University. He has recently
published a manuscript describing the development of a hospital-level diagnostic intensity index which utilizes
non-specific diagnosis codes paired with specific diagnostic tests as a proxy for diagnostic yield. He has
assembled a mentoring/advising team with expertise in evaluating the strength of evidence, measuring low-
value care, and identifying diagnostic errors. The candidate’s long-term goal is to become an independent
investigator with expertise in understanding the drivers of low-value health, the relationship between diagnostic
intensity and quality, and ultimately developing interventions to help low-performing hospital systems minimize
overuse without compromising quality.
This work will characterize hospital-level diagnostic intensity such that outlier hospitals can be identified and
the relationship between diagnostic intensity and missed diagnoses at the hospital level can be elucidated. The
project includes three aims: 1) Perform a systematic review of the literature characterizing hospital-level
diagnostic intensity, 2) Apply the hospital-level diagnostic intensity index to Medicare claims data and develop
and test an augmented diagnostic intensity index, 3) Utilize this index to characterize the relationship between
diagnostic intensity and missed diagnoses. Aims 2 and 3 will use Medicare 100% limited dataset claims.
In addition to executing these aims, the candidate will take courses, learn from directed readings by his
mentors and advisor, attend seminars and national conferences, and meet with his mentoring team regularly.
He will learn the skills necessary to conduct systematic reviews, gain expertise in analyzing large claims
datasets, and develop a better understanding of how to measure quality. This mentored research and career
development will help him achieve his goal of becoming an independent investigator.
Public Health Relevance Statement
Project Narrative:
Overuse of diagnostic testing in hospitalized adults is an important contributor to
unsustainably high healthcare costs and also has harmful effects on individual
patients. Methods to identify hospitals with high levels of diagnostic intensity,
potentially associated with diagnostic overuse, are lacking. I propose to (1) perform a
systematic review of published studies evaluating hospital-level diagnostic overuse,
(2) use a hospital-level diagnostic intensity index, with hospital claims data from the
Medicare program, to identify hospitals with high levels of diagnostic intensity, and (3)
evaluate the relationship between diagnostic intensity and quality of care, specifically
missed diagnoses.
No Sub Projects information available for 1K08HS028673-01A1
Publications
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