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SunCloud Health Outcome Study Update – April 2019

April, 2019

Collecting data for us is about using it to improve our patient’s health outcomes.  It is also about wanting to measure our integrated model to a parallel or serial model, and then using that information to improve what we do and to share with patients and payers that can be used to make critical decisions.

The implementation of survey selection and data collection and maintenance was iterative. It evolved over time and required strong leadership, patience, and flexibility. This was rewarded when clinicians saw results of individual clients on user-friendly graphs. This sharing of results fostered celebration of success as well as curiosity about surprising results and subsequent sleuthing to best understand the health trajectories of patients and related treatment approaches.


Survey bundles with instruments that assess mental health, eating attitudes and behaviors, relationships, and social behavior, are loaded to tablets and administered weekly to patients in care. Our results discuss findings from one instrument that measures mental health, relationships, and social behavior.

Data were categorized as Time 1 (on or within two weeks of admit) and Time 2 (on or within two weeks of discharge, or the final-most survey at least four weeks after admission). The primary research question was whether client health improves from Time 1 to Time 2. The secondary research question was whether health changed differently as a function of sex, age, presenting diagnoses,or previous treatment level.


Age, Sex, Previous Level of Care were measured at intake. Previous level of care spanned none to inpatient.

Treatment Completion was indicated at discharge by WHO as either partial or full completion.

Outcome Questionnaire 45.2 (OQ45.2). The OQ45.2 is a 45-item instrument with three sub-scales, which are the focus of this study. All sub-scales have good validity, test-retest reliability (.78-.84), internal consistency (.74-.93)(REFERENCE THE ADMIN MANUAL), The Symptom Distress subscale

Disorder. Disorder was assessed by our intake director at admit. We broke them down in to the following buckets:  substance use, anorexia, bulimia, binge eating disorder, mood disorder (anxiety/depression), PTSD and other. . Over 90% of our patients are in treatment for two or more disorders.  Number of disorders was calculated by adding the number of individual disorders assessed to a client.

Open to View Table 1. OQ45.2 Subscale Average Scores by Time and Client Characteristics
Clinical Benchmark 36 15 12
Reliable Change Index 10 8 7
All Clients (N=183) 53.8 43.7 19.5 16.2 15.0 11.5
Standard Deviations 15.3 18.9 7.0 7.5 5.5 6.0
With Mood Disorder (n=145) 55.2 44.4 19.9 16.4 15.3 11.6
With Substance Disorder (n=98) 53.6 43.0 20.3 16.8 15.2 12.2
With Bulimia (n=14) 55.9 50.8 17.6 18.0 14.9 12.7
With Binge Eating (n=18) 54.8 46.1 21.8 19.2 16.8 13.8
With Anorexia (n=58) 55.9 44.1 19.4 15.5 15.2 11.5
With PTSD (n=87) 57.3 46.7 20.1 16.6 15.4 12.1
With Other Diagnosis (n=54) 57.7 47.2 21.6 17.9 15.8 12.0
Males (n=25) 45.7 35.2 17.2 14.7 14.2 11.7
Females (n=158) 55.0 45.0 19.9 16.4 14.9 11.5
Clients 25 and younger (n=71) 57.8 46.0 19.4 15.5 15.8 11.5
Clients 25-40 (n=66) 51.2 42.1 19.0 15.5 14.1 11.6
Clients 40 and older (n=46) 51.3 42.3 20.5 18.3 14.4 11.6
One Diagnosis (n=9) 50.9 38.1 16.2 12.1 14.1 10.9
Two Diagnoses (n=40) 45.1 35.9 16.8 14.1 13.6 10.2
Three Diagnoses (n=68) 54.9 44.3 20.3 16.6 15.2 11.6
Four Diagnoses (n=34) 60.0 49.7 20.7 17.2 16.0 12.2
Five Diagnoses (n=9) 65.3 52.1 24.9 21.3 17.8 16.6
From Residential (n=32) 58.8 54.1 21.6 19.8 15.6 13.3
From Inpatient (n=22) 50.9 38.0 19.1 14.8 14.5 10.9
From Another IOP/PHP (n=22) 55.8 41.7 18.6 14.0 16.0 10.6
From Referring OP (n=46) 51.2 42.7 18.6 15.3 14.2 11.3
From None (n=32) 54.2 39.9 20.2 16.4 15.8 11.5
From Unknown (n=23) 52.8 45.1 19.5 16.6 13.2 11.2
Partial Completion (n=77) 54.8 49.8 19.6 18.0 14.8 12.8
Full Completion (n=72) 53.5 35.8 19.1 13.9 15.1 10.2


Repeated measures Analysis of Variance was adopted to assess whether health scores changed from pre- to post-treatment. Changes on the Symptom Distress subscale were significant with a large effect size (F(182)=85.4, p<.001, η2=.32). Changes on the Interpersonal Relations subscale were also significant with large effect size (F(182)=59.8, p<.001, η2=.24), and changes on Social Role were significant with large effect size (F(182)=64.1, p<.001, η2=.26).

To explore whether client characteristics impacted change, we regressed difference scores from Time 2 to Time 1 on Symptom Distress onto age, sex, previous level of care, number of diagnoses, and treatment completion.

The overall model was significant (F(5,140)=7.1, p<.001; R2 = .20), accounting for 20% of the variability on Symptom distress change. Specifically, age and completion were significant predictors of change. Clients who fully completed treatment improved more than those who partially completed treatment. Similarly, we regressed change scores on Interpersonal Relations onto the predictor variables.

The overall model was not significant (F(5,150)=0.8, p<.76; R2 = .02). When we regressed change scores for Social Role onto all predictors, the overall model was significant (F(5,140)=3.02, p<.01; R2 = .10), accounting for 10% of the variability of Social Social Role change. Specifically, treatment completers experienced more profound change than those who partially completed treatment.

Summary. People change similarly, but significantly even if they have more complex (co occurring) problems, AND that completion of treatment is a key in optimizing outcomes.

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