wic_kr_poster_final
TRANSCRIPT
0 5 10 15 20 25 30 35 40
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Number of Episodes
Number of Days
Pe
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FIGURE 1: DISTRIBUTION OF DAYS AND EPISODES IN HOSPITAL OVER 5 YEARS FOLLOWING INDEX
ADMISSION
# of Days # of episodes
65% of individuals did not have additional inpatient
episodes or days in hospital during the 5 years
following their index admission
DESIGN
Prospective cohort: Secondary analysis of population & clinical data.
• Linked Via Forward Sortation Area (FSA)
• Cohort: index admissions between 2006 and 2009.
• First psychiatric admission
• Follow-up: 5 years
• Total number of subsequent episodes since index
• Total number of subsequent days in hospital since index
SAMPLE (N=29,938)
Exclusion Criteria
• Forensic designation
• No Ontario FSA
• Individuals with lifetime exposure not captured by OMHRS
• Short stay episodes which occur prior to index admission
DATABASES
• RAI-Mental Health (RAI-MH) data from the Ontario Mental Health
Reporting System (OMHRS).
• Ontario Marginalization index (On-MARG)
• Developed by systematic review and factor analysis
• Derived from 2006 census, geographically focussed measure
• Describes four dimensions of geographic areas, including
residential instability
INDEPENDENT VARIABLES
Residential instability
• Consists of 9 dimensions, for example, proportion of population living
alone, and proportion of dwellings in an area that are not owned
• Reported as ordinal quintiles:
• 1= least unstable, 5=most unstable.
Diagnoses
• Primary diagnoses as determined by clinicians upon discharge
OUTCOME VARIABLES
• Number of days spent in hospital since index admission
• Number of episodes since index admission
NEIGHBOURHOOD LIVING ENVIRONMENT AND MENTAL HEALTH
SERVICE USE: USING INTERRAI TO IMPROVE RIGORKYLE ROGERS, M.SC CANDIDATE
CHRIS PERLMAN, PH.D
BACKGROUND
A review of mental health service use research has identified several
gaps in the literature:
1. Socio-environmental factors have received limited attention.
• This stands in contrast to the body of knowledge examining the
relationship between mental illness and socio-environmental factors.
2. Much of the research utilizes binary measures to capture service use
(e.g. Used in past 12 months, yes/no?)
Residential instability is one such socio-environmental factor that
describes the transience of the population living in an area.
• Aspects of residential instability been previously associated with
increased mental health service use.
Research that combines rich data from the RAI-MH with existing socio-
environmental data provides the opportunity to complement existing
research by:
1. Investigating the association between socio-environmental factors,
individual factors and inpatient service use.
2. Examining more nuanced measures of service use that go beyond
yes/no binary operationalizations
DISCUSSION• 65% of individuals who have an index admission between 2006 and
2009 did not have further contact with inpatient services for 5 years.
• There is an association between residential instability and the pattern
of service use, with a slight increasing trend in both number of
episodes and days in hospital as residential instability increases.
• Individuals with schizophrenia have extensive variation in their
patterns of service use at both episode and number of day levels.
• Individuals with dementia have some variation in their pattern of
service use in terms of days in hospital, but less in the number of
episodes.
• Individuals with concurrent mental illness have patterns of increased
number of visits to hospital, while number of days in hospital was not
shown to be statistically significant.
• There is a greater proportion of individuals with schizophrenia and
substance use in areas with the highest degree of residential
instability.
• There is a lower proportion of individuals with mood disorders and
dementia in areas with the highest degree of instability
ACKNOWLEDGEMENTS AND THANKS• interRAI and CIHI for providing access to OMHRS
• Sebastian Rios for providing feedback throughout the development of the
poster
• Jonathan Chen for his help developing the final dataset for analysis
IMPLICATIONS• Combining OMHRS data with the On-MARG allows researchers to develop
a nuanced consideration of inpatient mental health service that considers
both individual and socio-environmental factors.
• Further consideration of other individual and socio-environmental factors
available in the combined dataset may establish an understanding of
what drives inpatient service use.
• Multivariate multi-level modelling is needed to better understand the role
of residential instability in MHSU when compared against individual
aspects.
0% 20% 40% 60% 80% 100%
Quintile 1 (Lowest Instability)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (Highest instability)
FIGURE 2: DAYS IN HOSPITAL OVER 5 YEARS FOLLOWING INDEX ADMISSION BY RESIDENTIAL INSTABILITY QUINTILES
0 Days 1-14 Days 15-30 Days 31-90 Days 90+ Days
0% 20% 40% 60% 80% 100%
Quintile 1 (Lowest instability)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (Highest instability)
FIGURE 3: SUBSEQUENT EPISODES 5 YEARS FOLLOWING INDEX ADMISSION BY RESIDENTIAL INSTABILITY QUINTILES
0 episodes 1-2 episodes 3+ episodes
0% 20% 40% 60% 80% 100%
Concurrent Substance Abuse (27%)
Eating Disorders (1%)
Substance Use (17%)
Mood (45%)
Dementia (9%)
Schizophrenia (17%)
FIGURE 4: DAYS IN HOSPITAL OVER 5 YEARS FOLLOWING INDEX ADMISSION BY DIAGNOSIS
0 Days 1-14 Days 15-30 Days 31-90 Days 90+ Days
0% 20% 40% 60% 80% 100%
Concurrent Mental Illness (38%)
Concurrent Substance use (27%)
Substance Use ( 17%)
Dementia (9%)
Schizophrenia (17%)
FIGURE 5: SUBSEQUENT EPISODES 5 YEARS FOLLOWING INDEX ADMISSION BY DIAGNOSIS
No episodes 1-2 episodes 3+ episodes
…
…
*y axis percentile distribution jumps to accommodate extreme observations
36
5 d
ay
s
Greatest instability
associated with sum of
days greater than a
month
Greater instability
associated with
subsequent episodes
Schizophrenia has great
variation with days in
hospital following index
admission
Schizophrenia has
great variation in
subsequent episodes
Dementia does not
0% 20% 40% 60% 80% 100%
Concurrent Mental Illness (38%)
Concurrent Substance use (27%)
Eating Disorders (1%)
Substance use( 17%)
Mood (45%)
Anxiety (4%)
Dementia (10%)
Schizophrenia (17%)
FIGURE 6: PRIMARY DIAGNOSIS BY RESIDENTIAL INSTABILITY QUARTILES
Quintile 1 (Lowest instability) Quintile 2 Quintile 3 Quintile 4 Quintile 5 (Highest instability)
TABLE 1: NUMBER OF DAYS SPENT IN HOSPITAL BY
SUBSEQUENT DAYS
REFERENCESBabitsch B, Gohl D, Lengerke T von. Re-revisiting Andersen’s Behavioral Model of Health Services Use: a systematic
review of studies from 1998–2011. GMS Psycho-Social-Medicine. German Medical Science; 2012;9.
Twomey CD, Baldwin DS, Hopfe M, Cieza A. A systematic review of the predictors of health service utilisation by
adults with mental disorders in the UK. BMJ open. British Medical Journal Publishing Group; 2015;5(7):e007575.
Fleury M, Ngui AN, Bamvita J, Grenier G, Caron J. Predictors of healthcare service utilization for mental health
reasons. International journal of environmental research and public health 2014;11(10):10559-10586.