Defining Alcoholism Treatment Episodes from Mental Health ... · Web viewDefining Alcoholism...
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Defining Alcoholism Treatment Episodes from Mental Health Care Utilization Records
Kurt D. Stromberg, M. S. Melanie M. Wall, Ph.D.Sandra Pothoff, Ph.D.Robert L. Kane, M.D.
From the University of Minnesota School of Public Health, Division of Biostatistics (KS, MW),Division of Health Services Research and Policy (RK), Carlson School of Management (SP)
Corresponding author: Melanie M. Wall, Ph.D.University of Minnesota School of Public Health
Mayo Mail Code 303420 Delaware St. SE
Minneapolis, MN 55455612-625-2138
612-626-0660 (fax)[email protected]
This work was supported by a grant from the National Institute of Alcohol Abuse and Addiction (No. 1 R01 AA11781). The opinions are soley those of the authors and do not reflect official government positions.
Brief title: Defining Alcoholism Treatment EpisodesNumber of words: 3,838
COMPLETE AUTHOR INFORMATION
Corresponding author: Melanie M. Wall, Ph.D.University of Minnesota School of Public Health
Mayo Mail Code 303420 Delaware St. SE
Minneapolis, MN 55455612-625-2138
612-626-0660 (fax)[email protected]
Expertise: Biostatistics
Kurt D. Stromberg, M.S.University of Minnesota School of Public Health
Mayo Mail Code 303420 Delaware St. SE
Minneapolis, MN [email protected]: Biostatistics
Sandra Potthoff, PhDDepartment of Healthcare Management3-140 Carlson School of Management
321 19th Avenue SouthMinneapolis, MN 55455
[email protected]: Outcomes research, Healthcare management for alcoholism
Robert L. Kane, M.D.University of Minnesota School of Public Health
Mayo Mail Code 197420 Delaware St. SE
Minneapolis, MN [email protected]
Expertise: Outcomes research, Healthcare management for alcoholism
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Defining Alcoholism Treatment Episodes from Mental Health Care Utilization Records
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Word count of Abstract: 143
Defining Alcoholism Treatment Episodes from Mental Health Care Utilization Records
Abstract
Objective: A method for defining and empirically validating episodes of alcoholism treatment
from health care utilization records is introduced.
Subjects: Utilization records from a large managed behavioral care company for a 96 month period
from 1991 to 1998 are used and include 88,188 patients having at least one alcoholism encounter
during the 8 years.
Methods: Treatment episodes are defined as a minimum number of alcoholism encounters with the
behavioral care company prior to a ``clear zone'' of no encounters. Statistical procedures to select a
subset of episode definitions from a number of candidate definitions are presented.
Methods for assessing both the convergent and criterion validity of different definitions of episodes
of alcoholism treatment are demonstrated.
Results: Based on these validation techniques a definition for alcoholism treatment episode that
requires at least 3 alcoholism encounters before a “clear zone” of 3 months is chosen.
Key Words: alcoholism, validation techniques, statistical applications,
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Defining Alcoholism Treatment Episodes from Mental Health Care Utilization Records
Introduction
An episode of care is defined in the literature as a sequence or cluster of health care services
related to a particular condition or disease [1,2]. Elements required to delimit a specific episode of
care include diagnostic information, well defined starting and stopping points, and a particular
course or dosage of treatment [1,2]. Hornbrook et. al. [1] and others have advocated the use of an
episode of care methodology in health outcomes research because “the episode defines the
boundaries of a particular health care process and a means in which to sum the total number of
health care inputs occurring during a specified illness or problem”. The episode of care
methodology can be useful in identifying clusters of services related to a particular health condition
and provides an ideal tool for comparing pre- and post-episode health outcomes. Since the episode
of care approach facilitates the aggregation of all medical inputs related to a condition or disease it
provides a mechanism to measure the effectiveness of care in treating the health problem.
In order to define an episode of care, the boundaries of the episode must first be established
[1]. The first element in identifying the boundaries of an episode of care is to determine the point
at which it begins. Criteria for establishing the beginning of an episode include the first encounter
of a patient with the health care provider related to a particular health care problem (e.g. [2]) or
point in time where medical care expenditures related to an illness first exceed levels prior to
illness (e.g.[3]). Next, the end of an episode of care must be identified. Often the end of an
episode of care can be established by a “clear zone”, or period of time where no subsequent health
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care encounters occur [2,4]. All health care encounters between the start of the episode, or index
case, and the end of the episode completely describe the episode of care.
In this study, an episode of care methodology is used to define distinct episodes of inpatient
and outpatient alcoholism treatment from health care utilization records from a large managed
behavioral care company. Previous alcoholism treatment research has either focused on narrowly
defined alcoholism treatment regimes [5] or simply used the first observed alcoholism treatment
claim (from a medical claims database) as the beginning of treatment without specification of an
end or a required minimum number of encounters for the episode (e.g. [6]). Previous non-alcohol
related studies have successfully constructed episodes of care from health care claims databases
[2,7,8]. Furthermore, the episode of care methodology has been used to evaluate resource
utilization by particular demographic groups [4], evaluate differences in health utilization resulting
from trauma [7], investigate psychiatric care utilization [4], and investigate cost effectiveness of
new treatment interventions [9].
Construction of episodes of care from health care utilization records facilitates the
investigation of health outcomes research at the population level. However, researchers have
shown that results based on comparisons made using episodes constructed from claims data can be
highly sensitive to the episode definition [3,9]. Currently, most studies employing an episode of
care methodology applied to medical claims databases lack sufficient validity checking and
sensitivity analysis. This paper presents a method for creating episodes of inpatient and outpatient
alcoholism treatment from health care utilization records and describes statistical methods for
assessing the validity of such episode definitions. The goal of this study is to define a suitable
subset of valid episode definitions based on a minimum number of inpatient and outpatient
encounters and length of clear zone. Finally, the validity of creating episodes of alcoholism
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treatment from utilization records is established using data on patient functioning collected at the
start of treatment.
Methods
Data source
Eight years of behavioral care utilization data for 88,188 patients with a DSM-IV
(American Psychiatric Association, 1994) alcohol diagnosis (291-alcoholic psychoses, 303-alcohol
dependence syndrome, 305.0-alcohol abuse) were obtained from a large national managed
behavioral care company. All utilization records with a DSM-IV alcohol diagnosis were extracted
for each of the patients from January 1, 1991 to December 31, 1998. In total, approximately 1.2
million encounters were considered. Inpatient (IP) encounters were defined as those encounters in
the utilization database of type “inpatient”, “inpatient attending physician”, “partial
hospitalization”, and “residential”. Outpatient (OP) encounters were defined as those encounters in
the utilization database of type “outpatient individual and family therapy”, “outpatient group
therapy”, and “structured program”. In the original database, IP encounters were stored both as
single records for an entire hospital stay or as individual records for each day of inpatient care. To
facilitate comparison of IP encounters, all IP records were restructured so each day of inpatient care
was stored as one individual inpatient day of care. Billing adjustments were common in the
database; to ensure that utilization records were counted only once, only one record of each
encounter type was allowed on a particular day. The data was restructured to show the number of
IP and OP encounters occurring for each patient during each of the 96 months of the study period.
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For a subset of 8,080 patients, a baseline interview to assess patient functioning had been
conducted upon entry into an alcohol treatment program as part of an outcome monitoring
program. These data were matched with the behavioral care utilization records using a unique
patient identifier. The baseline questionnaire contained patient demographic information, questions
relating to severity of alcohol and other substance abuse problems, and questions relating to
motivation of patients seeking alcohol treatment. These data were used to validate the episode
definitions as described below. Patient demographic information for both the complete dataset and
for the subset of patients who completed the baseline questionnaire is shown in Table 1.
--------------------------Table 1 here------------------------------
Treatment episode algorithm
The diversity in encounter profiles over the entire study period among patients suggests that
any method to create episodes of care from utilization records must be flexible and allow the
researcher to explore different conditions for constructing episodes of care. For example, the
outpatient encounter profile for nine randomly selected alcoholism patients with at least one
outpatient encounter is shown in Figure 1. Outpatient encounter profiles of patients in panels A,
B, C, and E have very prominent regions of high alcoholism treatment utilization, while profiles in
panels D and F have two pronounced areas of utilization that the researcher may or may not want to
combine into one episode of treatment (Fig. 1). Patients shown in panels G, H, and I appear to
have very few outpatient encounters and may not have made a serious commitment to outpatient
alcoholism treatment (Fig. 1). Thus, a suitable mechanism for constructing episodes of care should
allow the user to explore different definitions of alcoholism treatment and evaluate the performance
of each definition.
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-----------------Figure 1 here -----------------------------------
In this study, an algorithm is developed to choose the beginning and end of a treatment
episode according to three parameters inputs: 1. the minimum number of OP encounters required to
constitute an OP episode, 2. the minimum number of IP encounters required to constitute an IP
episode, and 3. the length of the clear zone (i.e. cluster of months with no encounters) for a
particular episode definition. The algorithm indicates whether each patient is treated or not
according to the specified inputs and it designates when the individual's treatment started and
ended, how many encounters it included, and whether it was an OP or IP treatment
episode. The algorithm is flexible to allow multiple treatment episodes across time within an
individual.
-----------------Table 2 here -----------------------------------
To illustrate the algorithm, Table 2 shows the outpatient alcohol encounters for three
patients for a portion of the study period between January 1995 (month 49) and April 1996 (month
64). Thus, for example, if the minimum outpatient treatment episode is defined as 3 outpatient
encounters prior to an OP-clear zone of 3 months, then patient 1 would have a single episode of OP
treatment lasting from month 50 to month 54 and containing 6 outpatient alcohol encounters. The
second patient would have a single outpatient episode lasting from month 53 to month 57
containing 56 outpatient alcohol encounters. The third patient would have two separate OP
episodes, one from month 51 to 54 containing 9 OP encounters and the second from month 61 to
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62 containing 7 OP encounters. However, if the minimum outpatient episode is defined as 3
outpatient alcohol encounters prior to an OP-clear zone of only 2 months then the first patient will
now have two outpatient treatment episodes: the first during month 50 containing 3 OP encounters
and the second from month 53 to 54 containing 3 OP encounters (because of the gap of 2 zero
months between months 50 and 53). Under this second minimum OP episode definition the second
and third patients' OP episodes remain unchanged.
Impact of episode definition on number of patients with episode
The treatment episode is defined by three different parameters that can vary. Specifically,
the minimum number of IP encounters required for an IP episode was varied from 2 to 6, the
minimum number of OP encounters required for an OP episode of treatment ranged from 2 to 6,
and the length of the clear zone (IP and OP) necessary to end an episode of treatment ranged from 1
to 6 months. A minimum of 2 encounters was used because clinicians indicated that 1 OP
encounter usually means a patient was assessed but not treated, and 1 day of IP care typically
means the patient likely received only detox. Hence, 5 5 6 = 150 different episode definitions
are considered.
We first consider how each of these parameters impacts the total percentage of patients
receiving at least one episode of alcoholism treatment (IP or OP). Clearly the more restrictive
episode definitions will tend to result in fewer patients treated, however, we want to investigate
how much influence each of the parameters has on changing the percent of patients considered
treated. An ANOVA is used to quantify the variability associated with each factor in the episode
definition. The proportion of variation explained by each parameter in the episode definition is the
value of R2 associated with each component in the ANOVA. A parameter with a large R2 implies
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that it has a substantial influence on the outcome (i.e. proportion of patients with at least one
episode of alcohol treatment).
Validation of episode definition
Several methods to validate the episode of care methodology were employed in this study
using the subset of patients who completed a baseline questionnaire. The baseline questionnaire
provided information regarding reasons patients sought alcoholism treatment, patient motivation
level, and whether patients received previous alcoholism treatment. This information provides a
mechanism to measure both convergent and criterion validity.
An episode definition with high convergent validity should be highly associated with
patient information known to be correlated with commitment to alcoholism treatment. For
example, patients wishing to achieve abstinence from alcohol generally have been shown to have
higher commitment to alcoholism treatment programs than those wishing only to control alcohol
use [10,11]. Thus, episode definitions with high convergent validity should indicate a strong
association between the probability of patients receiving either type of episode (IP or OP) and
whether patients sought to achieve abstinence from alcohol consumption. On the patient baseline
questionnaire, patients indicated whether they sought alcoholism treatment for legal reasons, health
reasons, to achieve abstinence, or control alcohol use. Odds ratios provide a measure of the
association between each of the reasons patients sought treatment and the probability a patient
received at least one episode of alcoholism treatment (IP or OP) under each of the different episode
definitions.
Patients also rated their motivation for completing a course of alcoholism treatment as poor,
fair, good, or excellent on the baseline questionnaire. Patients with high motivation for completing
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a course of alcoholism treatment upon entry into a treatment program are more likely to stay
engaged in alcoholism treatment [12]. Thus, episode definitions with high convergent validity
should also show an increase in the likelihood of having at least one episode of alcoholism
treatment (IP or OP) as patient motivation level increases. The odds ratio of having at least one
treatment episode of either type for each motivation level (using poor motivation as the reference
group) are summarized across the different definitions.
The criterion validity of each episode definition considered was established by examining
whether treatment episodes are identified when treatments are known to have occurred. During the
baseline interview, patients were asked to report if they had previous alcoholism treatment. Based
on patient responses clinicians determined whether patients had received past treatment. Clinician
decisions on whether treatment occurred or not was considered the most accurate way of
determining treatment history. Baseline interviews did not start until 1993 (month 29 of study) and
continued until 1997 (month 85), while alcoholism utilization records were available from 1991-
1998. Thus, both positive and negative predictivity [13] provide measurements of the criterion
validity of each episode definition. Specifically, positive predictivity can be measured for each
episode definition by determining the proportion of patients who report a previous episode of
treatment when the treatment episode algorithm identifies an episode of treatment prior to baseline.
Likewise, negative predictivity is measured by determining the proportion of patients not reporting
a previous episode of treatment when the treatment episode algorithm does not indicate an episode
of treatment prior to baseline. Thus, treatment episode definitions with high criterion validity
should have both high positive and high negative predictivity.
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Results
Impact of episode definition on number of patients with episode
Table 3 shows the total percentage of patients receiving at least one treatment episode of
any type (IP or OP) for a subset of 25 treatment definitions when the clear zone is held fixed at
three months. As the number of encounters required for an episode of treatment increases, the
percentage of patients receiving at least one treatment episode of any type decreases (Table 3). For
example, with a clear zone of 3 months, when only 2 IP or 2 OP encounters are required for an
episode of IP or OP treatment respectively, 68.49% of the patients would be considered treated.
However, when 6 IP or 6 OP encounters are required for an episode of IP or OP treatment
respectively, only 43.59% of the patients are considered treated. Furthermore, the decrease in the
percentage of patients with at least one alcohol treatment episode decreases faster when the number
of OP encounters increases than when the number of IP encounters increases (Table 3).
-----------------------Table 3 here ------------------
The standard deviation in the percentage of patients receiving at least one episode of either
type of treatment (IP or OP) among all the 150 episode definitions is 6.8%. An
ANOVA was used to quantify the amount of this variability explained by each of the parameters in
the definition. The proportion of variation explained by both the minimum number of OP
encounters required for an OP episode and the minimum number of IP encounters required for an
episode of IP treatment is extremely high (R2=0.995), while the clear zone accounts for less than
0.5% of the variability. This suggested that the clear zone contributes very little to the overall
variability found in the % of individuals treated so it could be fixed. In order to choose an
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appropriate length of the clear zone, a residual plot from the reduced ANOVA without clear zone
included was examined. This plot shows that there is a relationship between the residuals and clear
zone length but that it is best centered around zero when clear zone is three months (Fig. 2). Thus,
in subsequent analyses, the clear zone was held fixed at three months reducing the number of
episode definitions from 150 to 25.
-----------------------Table 4 here ------------------
-----------------------Figure 2 here ------------------
Validation of episode definition
Optimal treatment episode definitions should be strongly related to validation variables.
Thus, the next step in selecting good episode definitions was to measure both the convergent and
criterion validity for each of the 25 episode definitions considered. The 25 episode definitions
arose from fixing the clear zone length at 3 months, allowing the number of OP encounters
required for an episode of OP treatment to range from 2 to 6, and allowing the number of IP
encounters required for an episode of IP treatment to range from 2 to 6.
-------------------------Figure 3 here ---------------------
Figure 3 shows the marginal odds ratio (OR) of a patient receiving at least one episode of
alcoholism treatment (IP or OP) associated with four possible reasons patients sought alcoholism
treatment for all 25 episode definitions considered. The average ORs across the 25 episode
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definitions are 1.15 for legal reasons, 1.12 for health reasons, 1.78 for abstinence reasons, and 0.80
for control reasons. Thus, patients seeking treatment to achieve abstinence from alcohol
consumption were on average more likely (OR = 1.78) to receive at least one episode of alcoholism
treatment (IP or OP) than those patients not seeking treatment to achieve abstinence. Likewise,
patients indicating they were seeking alcoholism treatment only to control alcohol use were on
average less likely (OR = 0.80) to receive an episode of treatment across all 25 episode definitions
considered. Furthermore there was a strong association between patient motivation level and the
probability of receiving a treatment episode. Specifically, under all definitions patients with
excellent motivation had higher probability of being treated followed by good motivation,
followed by fair motivation.
None of the point estimates of the ORs for any of the four reasons patients sought
alcoholism treatment varied substantially among the 25 different episode definitions considered.
Consequently there is no clear winner based only on Figure 3 in terms of convergent validity (i.e.
clearly larger OR for all variables), but closer inspection of the general trends finds that the
definitions with 2 or 6 OP encounters are never best for any of the four variables. Consequently,
definitions with 3,4, or 5 OP encounters have slightly better convergent validity. Furthermore, the
definitions requiring only 2 or 3 IP encounters have slightly larger OR for all four variables and
thus better convergent validity.
----------------Figure 4 here --------------------
Calculation of the positive and negative predictivity of previous alcoholism treatment for
each of the 25 different episode definitions served as a method to compare the criterion validity for
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each of the 25 treatment episodes. An episode definition with high criterion validity should have
both a positive and negative predictivity close to one. The positive predictivity for the 25 episode
definitions ranges from 0.66 to 0.79 and generally increases as the restrictiveness of the episode
definitions increase (Fig. 4A). The positive predictivity increases most sharply when the minimum
number of OP encounters required for an episode of OP treatment increases from 2 to 3 and then
remains relatively constant. Negative predictivity is nearly constant across the 25 episode
definitions and only ranges from 0.729 to 0.740 (Fig. 4B).
Discussion
Episode definitions based on utilization data facilitate the comparison of health outcomes
across clinical sites and across time since definitions of treatment may vary spatially and
temporally. Previous researchers have often studied the effectiveness of alcoholism treatment
within only one treatment center (e.g. [14]) or within the context of narrowly defined alcoholism
treatment regimes (e.g. [5]). Furthermore, alcoholism treatment has changed over time from a
higher reliance on inpatient care programs to a greater tendency to place patients in outpatient
treatment programs to contain rising costs [15,16].
This research describes a methodology to test statistically a number of different definitions
of an episode of treatment for alcoholism. The results show that 1. the definition of an episode is
insensitive to the number of months required for a clear zone of no encounters, with the ANOVA
residuals centered closest to 0 when the clear zone is 3 months, 2. convergent validity, while
similar for all definitions, is slightly better for definitions with 3-5 minimum OP encounters or 2-3
minimum IP encounters, 3. criterion validity of positive predictive value increases the most when
the minimum number of OP encounters increases from 2 to 3. Based on these results, the
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definition of an episode of treatment for our subsequent research on assessing the impact of
alcoholism treatment on medical care utilization was set to a minimum of 3 IP or OP encounters
with a clear zone of 3 months.
The episode of care methodology developed in this paper allows more general inferences
regarding health outcomes to be made to larger populations of patients than may be obtained by
following specific cohorts of patients over time. Furthermore, computer based automation of
episode construction, together with the relatively inexpensive cost of obtaining utilization records
means that episodes of care can be constructed for many patients over long periods of time. The
relative ease in which episodes of care can be created with different definitions enables researchers
to begin with many candidate episode definitions and select subsets of definitions based upon the
importance of the factors composing the episode definition. The ANOVA model used in this study
provided a mechanism to quantify the relative importance of each factor in the episode definition
and subsequently greatly reduced the set of episode definitions that needed to be further examined
by fixing the clear zone length to three months. Moreover, the mechanism to evaluate both the
convergent and criterion validity of each episode definition allowed for the selection of a specific
episode definitions which can then be used for further analysis.
For alcoholism research, the episode of care provides an ideal tool for studying treatment
outcomes across clinical setting, clinical management region, or comparing pre-/post-episode
behaviors. The alcoholism treatment episode provides the exact starting time, stopping time, and
measures the intensity of alcoholism treatment regardless of the actual treatment program. For
example, this methodology could enable a better estimation of the cost offset associated with
treating alcoholism. Previous investigations of the cost offset hypothesis have often focussed on
identifying health care savings in particular cohorts of patients [16,17] where inferences may not
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have wider applicability. Other cost offset studies have focussed on large cohorts of alcoholics, but
have not adequately described the period of time in which alcoholism treatment occurred. These
studies instead focussed on comparing costs before and after a single index case of alcoholism
treatment [18,19]. Use of the episode of care methodology in cost offset analyses could establish a
better criterion in which to compare pre-treatment with post-treatment health care costs across a
diverse patient population.
We chose to study only episodes consisting of all IP encounters (IP episodes) or OP
encounters (OP episodes) and did not consider episodes composed of both IP and OP encounters.
This enabled us to detect differences in both forms of treatment. Furthermore, construction of IP
and OP episodes of alcohol treatment separately could facilitate future comparisons between the
effectiveness of IP versus OP treatment, currently a research area of some debate [16,20].
However, the methodology reported here could easily be adapted to construct mixed episodes
containing both OP and IP encounters.
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5. Trent, L. K. Evaluation of a four- versus six-week length of stay in the Navy's alcohol treatment program. J. Stud. Alcohol. 1998;59(3): 270-279.
6. Holder, H. D. and Blose, J. O. The reduction of health care costs associated with alcoholism treatment: A 14-year longitudinal study. Journal of Studies on Alcohol. 1992;53 293-302.
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8. Mitchell, J. B. et al. Using medicare claims for outcomes research. Medical Care. 1994;32(7): JS38-JS51.
9. Schulman, K. A., Yabroff, K. R., Kong, J., Gold, K. F., Rubenstein, L. E., Epstein, A. J., Glick, H. A claims approach to defining an episode of care. Health Services Research. 1999;34(2): 603-621.
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11. Pendery, M. L., Maltzman, I. M., and West, L. J. Controlled drinking by alcoholics? New findings and a reevaluation of a major affirmative study. Science. 1982;217(4555): 169-175.
12. Walitzer, K. S., Dermen, K. H., and Conners, G. J. Strategies for preparing clients for treatment. A review. Behav. Modif. 1999; 23(1): 129-151.
13. Le, C. T. Applied Categorical Data Analysis. John Wiley and Sons, Inc. New York; 1998.
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14. Holder, H. D. The cost offsets of alcoholism treatment. Recent Developments in Alcoholism. 1998;14: 361-374.
15. Schuckit, M. A., 1998. Penny-wise, ton-foolish? The recent movement to abolish inpatient alcohol and drug treatment. J. Stud. Alcohol. 1998;59: 5-6.
16. Walsh, D. C. et al. A randomized trial of treatment options for alcohol-abusing workiers. NEJM. 1991;325(11) 775-782.
17. Weisner, C., Mertens, J., Parthasarathy, S., Moore, C., Hunkeler, E. M., Hu, T., and Selby, J. V. The outcome and cost of alcohol and drug treatment in an HMO: day hospital versus traditional outpatient regimes. Health Services Research. 2000;35(4): 791-812.
18. Goodman, A. C., Tilford, J. M., Hankin, J. R.,Holder, H. D., and Nishiura, E. Alcoholism treatment offseteffects: an insurance perspective. Medical Care Research and Review. 2000; 57(1) 51-75.
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20. Parthasarathy, S., Weisner, C., Hu, T., and Moore, C. 2001. Association of outpatient alcohol and drug treatment with health care utilization and cost: revisiting the offset hypothesis. J. Stud. Alcohol. 2001;62(1): 89-97.
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Table 1: Demographic characteristics of patients in alcoholism care database.
All Subset withbaseline data
n 88,188 8,080
age(mean±sd) 40.0±11.9 40.8±9.8sex(%)F 33.2 33.3M 66.8 66.7region(%)W 15.5 6.2S 18.3 7.6MW 32.3 38.2NE 33.9 48.0alcoholism encounters>1 IP (%)1 28.9 20.2>1 OP(%)2 75.5 76.81Percentage of patients with at least 1 inpatient alcohol encounter.2Percentage of patients with at least 1 outpatient alcohol encounter.
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Table 2: Sample of outpatient alcohol encounters for three patients from study month 49 (January, 1995) to study month 64 (April, 1996).
Outpatient Alcohol Encounters per Monthmonth 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64patient 1 0 3 0 0 1 2 0 0 0 0 0 0 0 0 0 0patient 2 0 0 0 0 3 15 14 12 2 0 0 0 0 0 0 0patient 3 0 0 1 2 4 2 0 0 0 0 0 0 5 2 0 0
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Table 3: Percentage of patients receiving at least one episode of IP or OP alcoholism treatment under different definitions. Clear zone length held fixed at three months.
Minimum number of IP encounters for IP episode
Minimum number of OP encounters for OP episode
2 3 4 5 62 68.49 60.90 56.75 53.71 51.443 67.37 59.69 55.49 52.42 50.114 65.73 57.90 53.61 50.56 48.095 63.75 55.72 51.31 48.05 45.626 62.13 53.92 49.41 46.09 43.59
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Figure 1: Outpatient encounter profile of nine randomly selected alcohol patients having at least one outpatient alcohol encounter.
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ce in
terv
als f
or th
e od
ds ra
tio a
t eac
h of
ht
e 25
epi
sode
def
initi
ons c
onsi
dere
d. C
lear
zon
e le
ngth
fixe
d at
thre
e m
onth
s.
Stromberg
Title:(S-PLUS Graphics)Creator:S-PLUSPreview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
25
Figu
re 4
: Po
sitiv
e (A
) and
neg
ativ
e (B
) pre
dict
ivity
for 2
5 m
inim
um e
piso
de
defin
ition
s.