Complex Care Hospital Use and Postdischarge Coaching: A Randomized Controlled Trial

Coller, Ryan J.; Klitzner, Thomas S.; Lerner, Carlos F.; Nelson, Bergen B.; Thompson, Lindsey R.; Zhao, Qianqian; Saenz, Adrianna A.; Ia, Siem; Flores-Vazquez, Jessica; Chung, Paul J.

doi:10.1542/peds.2017-4278

Cited by 45 publications

(51 citation statements)

References 35 publications

(33 reference statements)

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“… 1 , 2 To address these issues and deliver higher value care, interdisciplinary complex care programs for CMC have been developed to provide high intensity care coordination. 2 - 4 Care coordination by complex care programs focused on frequent follow-up and outreach post-hospitalization and between clinic visits is mostly conducted via phone calls. 4 A limitation of phone-based care coordination between parents and providers is the lack of face-to-face interactions, thus limiting opportunities for evaluation of a child’s clinical status and relationship building between parent and provider.…”

Section: Introductionmentioning

confidence: 99%

“… 2 - 4 Care coordination by complex care programs focused on frequent follow-up and outreach post-hospitalization and between clinic visits is mostly conducted via phone calls. 4 A limitation of phone-based care coordination between parents and providers is the lack of face-to-face interactions, thus limiting opportunities for evaluation of a child’s clinical status and relationship building between parent and provider. Face-to-face, real-time care between providers and parents that brings the clinical expertise of complex care programs directly into CMC patients’ home is possible via an approach called telemedicine video visits (TMVV).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Telemedicine Video Visits for Children with Medical Complexity in a Structured Clinical Complex Care Program

Ross

Parnell

Spears

et al. 2020

Global Pediatric Health

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Telemedicine Video Visits for Children with Medical Complexity in a Structured Clinical Complex Care Program

Ross

Parnell

Spears

et al. 2020

Global Pediatric Health

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“…6,[11][12][13][14][15][16][17][18] Such a prediction model may help to identify CMC at highest risk for readmission in real time, aiding in the targeting of interventions and resources to reduce readmission rates and associated costs while improving patient and family quality of life and experiences. 17,19,20 This study therefore aimed to develop clinical prediction models for 30-day readmission among children with CCCs capable of use during admission for targeting of inpatient interventions, care coordination, or discharge planning, or for use at discharge for targeting outpatient services.…”

mentioning

confidence: 99%

Developing Prediction Models for 30-Day Unplanned Readmission Among Children With Medical Complexity

Leary

Price

Scott³

et al. 2019

Hospital Pediatrics

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A B S T R A C TOBJECTIVES: To target interventions to prevent readmission, we sought to develop clinical prediction models for 30-day readmission among children with complex chronic conditions (CCCs). METHODS:After extracting sociodemographic and clinical characteristics from electronic health records for children with CCCs admitted to an academic medical center, we constructed a multivariable logistic regression model to predict readmission from characteristics obtainable at admission and then a second model adding hospitalization and discharge variables to the first model. We assessed model performance using c-statistic and calibration curves and internal validation using bootstrapping. We then created readmission risk scoring systems from final model b-coefficients. RESULTS:Of the 2296 index admissions involving children with CCCs, 188 (8.2%) had unplanned 30-day readmissions. The model with admission characteristics included previous admissions, previous emergency department visits, number of CCC categories, and medical versus surgical admission (c-statistic 0.65). The model with hospitalization and discharge factors added discharge disposition, length of stay, and weekday discharge to the admission variables (c-statistic 0.67). Bootstrap samples had similar c-statistics, and slopes did not suggest significant overfitting for either model. Readmission risk was 3.6% to 4.9% in the lowest risk quartile versus 15.9% to 17.6% in the highest risk quartile (or 3.6-4.5 times higher) for both models. CONCLUSIONS:Clinical variables related to the degree of medical complexity and illness severity can stratify children with CCCs into groups with clinically meaningful differences in the risk of readmission. Future research will explore whether these models can be used to target interventions and resources aimed at decreasing readmissions.

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“…This notion is supported by prior work that demonstrated successful readmission reduction interventions for children with chronic conditions often rely on enhanced education or coaching. 25,26 We elected to present models both with and without LOS as a confounder because it is a potentially modifiable attribute of hospitalization. Change in medical complexity aspects were significantly associated with readmission in multivariable models without LOS.…”

Section: Discussionmentioning

confidence: 99%

Discharge Medical Complexity, Change in Medical Complexity and Pediatric 30‐day Readmission

Auger

Shah

Huang

et al. 2019

Journal of Hospital Medicine

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BACKGROUND: While medical complexity is associated with pediatric readmission risk, less is known about how increases in medical complexity during hospitalization affect readmission risk. METHODS: We conducted a five-year retrospective, case-control study of pediatric hospitalizations at a tertiary care children’s hospital. Cases with a 30-day unplanned readmission were matched to controls based on admission seasonality and distance from the hospital. Complexity variables included the number of medications prescribed at discharge, medical technology, and the need for home healthcare services. Change in medical complexity variables included new complex chronic conditions and new medical technology. We estimated odds of 30-day unplanned readmission using adjusted conditional logistic regression. RESULTS: Of 41,422 eligible index hospitalizations, we included 595 case and 595 control hospitalizations. Complexity: Polypharmacy after discharge was common. In adjusted analyses, being discharged with ≥2 medications was associated with higher odds of readmission compared with being discharged without medication; children with ≥5 discharge medications had a greater than four-fold higher odds of readmission. Children assisted by technology had higher odds of readmission compared with children without technology assistance. Change in complexity: New diagnosis of a complex chronic condition (Adjusted Odds Ratio (AOR) = 1.75; 1.11-2.75) and new technology (AOR = 1.84; 1.09-3.10) were associated with higher risk of readmission when adjusting for patient characteristics. However, these associations were not statistically significant when adjusting for length of stay. CONCLUSION: Polypharmacy and use of technology at discharge pose a substantial readmission risk for children. However, added technology and new complex chronic conditions do not increase risk when accounting for length of stay

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Complex Care Hospital Use and Postdischarge Coaching: A Randomized Controlled Trial

Cited by 45 publications

References 35 publications

Telemedicine Video Visits for Children with Medical Complexity in a Structured Clinical Complex Care Program

Telemedicine Video Visits for Children with Medical Complexity in a Structured Clinical Complex Care Program

Developing Prediction Models for 30-Day Unplanned Readmission Among Children With Medical Complexity

Discharge Medical Complexity, Change in Medical Complexity and Pediatric 30‐day Readmission

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