Objectives: To implement a large-scale multifaceted intervention consisting of physician education, profiling, and a financial incentive, to improve treatment quality for acute sinusitis.
Study Design: Cohort trial using a historical control of treatment patterns among approximately 500 internists, 200 family practitioners, and 200 pediatricians in a northeastern community-wide individual practice association.
Participants and Methods: Episode treatment group methods were adapted to identify cases (episodes) and to assess care patterns for acute sinusitis among 420 000 health maintenance organization patients seen between January 1, 1999, and December 31, 2001. The intervention consisted of care pathway development, physician and patient education, physician profiling, and a financial incentive.
Results: A statistical process control chart showed a shift toward recommended treatment patterns after our intervention. The rate of exceptions per episode of acute sinusitis decreased 20%, from 326 exceptions per 1000 episodes between January 1, 1999, and October 31, 2000, to 261 between November 1, 2000, and December 31, 2001. Decreased use of less effective or inappropriate antibiotics accounted for most of the change (199 to 136 exceptions per 1000 episodes [32% change]). Azithromycin use decreased 30%, from 97 to 68 prescriptions per 1000 episodes. Firstline antibiotic (amoxicillin and doxycycline) use increased 14%, from 451 to 514 prescriptions per 1000 episodes. Inappropriate radiology use decreased 20%, from 15 to 12 per 1000 episodes. These changes were significant at P < .005.
Conclusion: A multifaceted program, including education, physician profiling with actionable recommendations, and a financial incentive, significantly increased physicians' adherence to a community-developed care pathway and was successful at improving adherence to recommended patterns of antibiotic use in acute sinusitis.
(Am J Manag Care. 2004;10:670-678)
For the past decade, the healthcare industry has
struggled to identify methods to significantly
modify clinical practice. A recent review of typical
educational programs confirms the inability of traditional
continuing medical education to change clinical
behavior.1 Introducing evidence-based clinical guidelines
also has failed to improve clinical care.2,3
The need to identify reliable ways to improve clinical
care has led several teams to prepare and test new types
of interventions. Avorn and Solomon3 identified specific
interventions that improved appropriate antibiotic
use. These approaches included reminders at the point
of care, academic detailing, and order entry programs.
In 2001, Grol4 argued that the complexity of changing
clinical practice behaviors requires more than a single
intervention such as an educational program, financial
incentive, or practice profile. To promote successful
practice outcomes and adherence to guidelines, Grol
proposed creating an integrated combination of self-reinforcing
interventions such as evidence-based guidelines,
professional education, assessment and
accountability, patient empowerment, and total quality
management. Bodenheimer, Wagner, and Grumbach5,6
also recently endorsed a multiple intervention, multilevel
model for improving chronic disease care.
The primary aim of this study was to demonstrate
the ability of such a multifaceted intervention program
to improve the evaluation and management (E&M) of
acute sinusitis, especially in regards to appropriate
antibiotic prescribing. Interventions included physician
education, a locally developed acute sinusitis care pathway,
feedback through a physician profiling system, a
financial incentive for adherence to our care pathway,
and patient education. The intervention was applied to
a community-wide panel of more than 900 primary care
physicians covering 420 000 health maintenance organization
(HMO) members. The high penetrance of the
HMO in the local market allowed us to examine and profile
individual physicians on large numbers of cases
without needing to pool data among multiple payers.
This project evolved from a collaboration between
the Rochester Individual Practice Association, Inc
(RIPA) and BlueCross BlueShield of the Rochester
Area's HMO, Blue Choice. (BlueCross BlueShield of the
Rochester Area has since been renamed Excellus
BlueCross BlueShield of the Rochester Region.) The
baseline measurement period was January 1, 1999,
through October 31, 2000. The intervention period
started November 1, 2000, and was measured through
December 31, 2001. In 2000, RIPA was a communitywide
panel of approximately 3000 practitioners and 900
primary care physicians (500 internists, 200 family
practitioners, and 200 pediatricians) serving 420 000
HMO subscribers. Rochester Individual Practice
Association, Inc, physicians were located in the 9-county
region surrounding Rochester. The region includes
urban, suburban, and rural communities.
Credentialing information was used to identify all
internists, family physicians, and pediatricians. All credentialed
physicians actively seeing patients were
included in the program. Cases of acute sinusitis seen
by nurse practitioners or physician assistants were
assigned to their supervising physician.
Analysis included all HMO patients treated by the
identified physicians or their nurse practitioners and
physician assistants. The HMO provided an administrative
data set with scrambled patient identification numbers.
Because neither patient-specific information nor
reviewed medical records were used, informed consent
was not obtained.
Episode treatment group (ETG) methods were
applied to claims data to identify cases, or "episodes," of
acute sinusitis without sinus surgery and their related
services (Episode Treatment Grouper, version 4.0;
Symmetry Health Data Systems, Inc, Phoenix, Ariz; incorporated
in Episode Profiler, version 4.6, CareEnhance
Resource Management Software; McKesson Health
Solutions, LLC, Cambridge, Mass). In the ETG model, an
episode consists of a series of healthcare services related
to a group of specific diagnoses for 1 patient. An episode
of care may contain single or multiple services, including
office visits, diagnostic tests, therapeutic interventions,
emergency department visits, and prescribed medications.
Episode treatment groups are structured so that
each contains 1 disease entity (as is the case for acute
sinusitis) or clinically similar diseases.
Analysis of each episode began by finding an anchoring
E&M service. The anchoring E&M service could have
an International Classification of Diseases, Ninth
Revision (ICD-9-CM) code for acute sinusitis or for a
more general illness such as a "viral upper respiratory
tract infection." The software examined each subsequent
claim by procedure per Current Procedural Terminology
codes, by diagnosis per ICD-9 codes, or by medication
generic code number and national drug code. It also
searched backward 1 month for antibiotics prescribed
before the initial patient encounter. The software then
decided whether to add the claim to the current episode
of care and, if so, whether the episode should remain in
the current ETG or be assigned to another ETG. For
example, if the episode began with a viral upper respiratory
tract infection and then later had an E&M service for
acute sinusitis, it was removed from the former ETG into
the sinusitis ETG. If sinus surgery occurred subsequent
to the anchoring visit, the episode was transferred to the
ETG for sinusitis with surgery. An episode was considered
completed when no additional services were billed
for the ETG for a fixed period (the "clean" period).
Acute sinusitis was ETG 0333 in the Symmetry
grouper. The following ICD-9 codes classified E&M services
as acute sinusitis: 461, 461.0, 461.2, 461.3, 461.8,
and 461.9. The clean period for ETG 0333 was 60 days.
The episode grouping software examined the complete
database of all inpatient and outpatient claims
paid by the HMO for its members between January 1,
1999, and December 31, 2001. After December 31,
2001, we used a 2-month claims run-out period, corresponding
to the episode's clean period, to capture late
claims for services provided within the study period.
Episodes were analyzed by the month and year of their
first service. An independent practice association
(IPA)–HMO profiling team reviewed all identified problems
regarding data accuracy, collection, and analysis
so that the system could be improved continuously.
Developing an Acute Sinusitis Care Pathway
In early 2000, an IPA multidisciplinary task force
was convened to create a local acute sinusitis care pathway.
The acute sinusitis task force included pediatricians,
family practitioners, internists, otolaryngologists,
an allergist, and an infectious disease specialist. The
task force was charged with identifying the most important
evidence-based elements of quality care that could
be measured using an administrative database. Table 1
shows pathway elements generated by the task force.
Lists of suggested firstline and secondline antibiotics, as
well as nonrecommended less effective or inappropriate
antibiotics, were published (Table 2). The task force
based many of its recommendations on a 2000 report by
the Sinus and Allergy Health Partnership,7 modified by
local experience and antibiotic resistance patterns.8 For
example, doxycycline was listed as an alternative firstline
antibiotic for patients older than 8 years who were
allergic to amoxicillin.
Creating a Pathway Scoring Measure
A second software program, the Referral Profiler
Customization Utility (version 4.6, McKesson), was
adapted to analyze the acute sinusitis care pathway.
The presence or absence of services, and their correct
sequence, defined the rate of pathway adherence.
Complete and incomplete episodes of care were analyzed
based on the type and sequence of initial services,
rather than the length or total cost of the episode.
The referral profiler generated the number of deviations
from the care pathway for each episode.
Variations from the pathway were termed exceptions to
recommended care. The total number of exceptions
divided by the number of episodes gives the exceptions
per episode, the metric used as the core physician profiling
measure. Table 3 summarizes the acute care services
identified by the referral profiler customization.