Time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates: A survival analysis using routinely collected electronic medical records.
<h4>Background</h4>Health systems are undergoing widespread adoption of the collaborative chronic care model (CCM). Care structured around the CCM may reduce costly psychiatric hospitalizations. Little is known, however, about the time course or heterogeneity of treatment effects (HTE) f...
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Public Library of Science (PLoS)
2021-01-01
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| author | Michael A Ruderman Bo Kim Kelly Stolzmann Samantha Connolly Christopher J Miller Mark S Bauer |
| author_facet | Michael A Ruderman Bo Kim Kelly Stolzmann Samantha Connolly Christopher J Miller Mark S Bauer |
| author_sort | Michael A Ruderman |
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| description | <h4>Background</h4>Health systems are undergoing widespread adoption of the collaborative chronic care model (CCM). Care structured around the CCM may reduce costly psychiatric hospitalizations. Little is known, however, about the time course or heterogeneity of treatment effects (HTE) for CCM on psychiatric hospitalization.<h4>Rationale</h4>Assessment of CCM implementation support on psychiatric hospitalization might be more efficient if the timing were informed by an expected time course. Further, understanding HTE could help determine who should be referred for intervention.<h4>Objectives</h4>(i) Estimate the trajectory of CCM effect on psychiatric hospitalization rates. (ii) Explore HTE for CCM across demographic and clinical characteristics.<h4>Methods</h4>Data from a stepped wedge CCM implementation trial were reanalyzed using 5 570 patients in CCM treatment and 46 443 patients receiving usual care. Time-to-event data was constructed from routine medical records. Effect trajectory of CCM on psychiatric hospitalization was simulated from an extended Cox model over one year of implementation support. Covariate risk contributions were estimated from subset stratified Cox models without using simulation. Ratios of hazard ratios (RHR) allowed comparison by trial arm for HTE analysis, also without simulation. No standard Cox proportional hazards models were used for either estimating the time-course or heterogeneity of treatment effect.<h4>Results</h4>The effect of CCM implementation support increased most rapidly immediately after implementation start and grew more gradually throughout the rest of the study. On the final study day, psychiatric hospitalization rates in the treatment arm were 17% to 49% times lower than controls, with adjustment for all model covariates (HR 0.66; 95% CI 0.51-0.83). Our analysis of HTE favored usual care for those with a history of prior psychiatric hospitalization (RHR 4.92; 95% CI 3.15-7.7) but favored CCM for those with depression (RHR 0.61; 95% CI: 0.41-0.91). Having a single medical diagnosis, compared to having none, favored CCM (RHR 0.52; 95% CI 0.31-0.86).<h4>Conclusion</h4>Reduction of psychiatric hospitalization is evident immediately after start of CCM implementation support, but assessments may be better timed once the effect size begins to stabilize, which may be as early as six months. HTE findings for CCM can guide future research on utility of CCM in specific populations. |
| format | Article |
| id | doaj-art-431df88c945a4e9f95992eee4f3b0868 |
| institution | DOAJ |
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| language | English |
| publishDate | 2021-01-01 |
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| spelling | doaj-art-431df88c945a4e9f95992eee4f3b08682025-08-20T02:55:20ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01163e024900710.1371/journal.pone.0249007Time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates: A survival analysis using routinely collected electronic medical records.Michael A RudermanBo KimKelly StolzmannSamantha ConnollyChristopher J MillerMark S Bauer<h4>Background</h4>Health systems are undergoing widespread adoption of the collaborative chronic care model (CCM). Care structured around the CCM may reduce costly psychiatric hospitalizations. Little is known, however, about the time course or heterogeneity of treatment effects (HTE) for CCM on psychiatric hospitalization.<h4>Rationale</h4>Assessment of CCM implementation support on psychiatric hospitalization might be more efficient if the timing were informed by an expected time course. Further, understanding HTE could help determine who should be referred for intervention.<h4>Objectives</h4>(i) Estimate the trajectory of CCM effect on psychiatric hospitalization rates. (ii) Explore HTE for CCM across demographic and clinical characteristics.<h4>Methods</h4>Data from a stepped wedge CCM implementation trial were reanalyzed using 5 570 patients in CCM treatment and 46 443 patients receiving usual care. Time-to-event data was constructed from routine medical records. Effect trajectory of CCM on psychiatric hospitalization was simulated from an extended Cox model over one year of implementation support. Covariate risk contributions were estimated from subset stratified Cox models without using simulation. Ratios of hazard ratios (RHR) allowed comparison by trial arm for HTE analysis, also without simulation. No standard Cox proportional hazards models were used for either estimating the time-course or heterogeneity of treatment effect.<h4>Results</h4>The effect of CCM implementation support increased most rapidly immediately after implementation start and grew more gradually throughout the rest of the study. On the final study day, psychiatric hospitalization rates in the treatment arm were 17% to 49% times lower than controls, with adjustment for all model covariates (HR 0.66; 95% CI 0.51-0.83). Our analysis of HTE favored usual care for those with a history of prior psychiatric hospitalization (RHR 4.92; 95% CI 3.15-7.7) but favored CCM for those with depression (RHR 0.61; 95% CI: 0.41-0.91). Having a single medical diagnosis, compared to having none, favored CCM (RHR 0.52; 95% CI 0.31-0.86).<h4>Conclusion</h4>Reduction of psychiatric hospitalization is evident immediately after start of CCM implementation support, but assessments may be better timed once the effect size begins to stabilize, which may be as early as six months. HTE findings for CCM can guide future research on utility of CCM in specific populations.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0249007&type=printable |
| spellingShingle | Michael A Ruderman Bo Kim Kelly Stolzmann Samantha Connolly Christopher J Miller Mark S Bauer Time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates: A survival analysis using routinely collected electronic medical records. PLoS ONE |
| title | Time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates: A survival analysis using routinely collected electronic medical records. |
| title_full | Time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates: A survival analysis using routinely collected electronic medical records. |
| title_fullStr | Time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates: A survival analysis using routinely collected electronic medical records. |
| title_full_unstemmed | Time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates: A survival analysis using routinely collected electronic medical records. |
| title_short | Time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates: A survival analysis using routinely collected electronic medical records. |
| title_sort | time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates a survival analysis using routinely collected electronic medical records |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0249007&type=printable |
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