The California collaborative network to promote data driven care and improve outcomes in early psychosis (EPI-CAL) project: rationale, background, design and methodology
Abstract Background A prolonged first episode of psychosis (FEP) without adequate treatment is a predictor of poor clinical, functional, and health outcomes and significant economic burden. Team-based “coordinated specialty care” (CSC) for early psychosis (EP) has established effectiveness in promot...
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2024-11-01
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| Online Access: | https://doi.org/10.1186/s12888-024-06245-6 |
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| author | Valerie L. Tryon Kathleen E. Nye Mark Savill Rachel Loewy Madison J. Miles Laura M. Tully Andrew J. Padovani Daniel J. Tancredi Joy Melnikow Sabrina Ereshefsky Nitasha Sharma Amanda P. McNamara Merissa Kado-Walton Christopher Komei Hakusui Chelyah Miller Khanh Linh H. Nguyen Maliha Safdar Viviana E. Padilla Leigh Smith Adam B. Wilcox Lindsay M. Banks Stephania L. Hayes Katherine M. Pierce Karina Muro Daniel I. Shapiro Khalima A. Bolden-Thompson Renata M. Botello Rebecca E. Grattan Yi Zhang Bonita Hotz Lisa Dixon Cameron S. Carter Tara A. Niendam |
| author_facet | Valerie L. Tryon Kathleen E. Nye Mark Savill Rachel Loewy Madison J. Miles Laura M. Tully Andrew J. Padovani Daniel J. Tancredi Joy Melnikow Sabrina Ereshefsky Nitasha Sharma Amanda P. McNamara Merissa Kado-Walton Christopher Komei Hakusui Chelyah Miller Khanh Linh H. Nguyen Maliha Safdar Viviana E. Padilla Leigh Smith Adam B. Wilcox Lindsay M. Banks Stephania L. Hayes Katherine M. Pierce Karina Muro Daniel I. Shapiro Khalima A. Bolden-Thompson Renata M. Botello Rebecca E. Grattan Yi Zhang Bonita Hotz Lisa Dixon Cameron S. Carter Tara A. Niendam |
| author_sort | Valerie L. Tryon |
| collection | DOAJ |
| description | Abstract Background A prolonged first episode of psychosis (FEP) without adequate treatment is a predictor of poor clinical, functional, and health outcomes and significant economic burden. Team-based “coordinated specialty care” (CSC) for early psychosis (EP) has established effectiveness in promoting clinical and functional recovery. However, California’s CSC program implementation has been unsystematic and could benefit from standardizing its processes and data collection infrastructure. To address this, we established a consortium of EP clinics across the state via a Learning Health Care Network (LHCN) framework to develop the Early Psychosis Intervention Network of California (EPI-CAL). EPI-CAL’s LHCN developed a core battery of evidence-based measures for service users and family members and linked them together using a unique data collection and visualization application, Beehive. Methods and objectives EPI-CAL’s LHCN collects, visualizes, and aggregates data at the individual and clinic level for EP programs across California via Beehive. Beehive was designed to: (1) collect outcomes data from service users receiving care at EP programs and their support persons, (2) provide the data to providers on a secure web-based dashboard to support measurement-based care, and (3) allow data to be used for program or research analysis. We will (1) determine the feasibility of implementing an LHCN across a diverse, decentralized network of early psychosis programs, (2) determine if the implementation of an LHCN increases the delivery of measurement-based care, and (3) determine if the implementation of measurement-based care is associated with significant improvements in key service user outcomes. EPI-CAL’s network will contribute data to the Early Psychosis Intervention Network (EPINET) program. Discussion The current study aims to establish an LHCN of EP clinics in California that implements harmonized data collection using Beehive and assesses the feasibility of establishing such a network. Our goal is for this harmonized data collection approach to be used to inform decisions and develop learning opportunities for service users, staff, and administrators, and to improve outcomes for service users and their supporters in CSC care. Further, the data will enable programs and research teams to examine what elements of care lead to program success and improved treatment outcomes for service users. Clinical trials registration www.ClinicalTrials.gov , identifier NCT04007510; registered 07/05/2019. |
| format | Article |
| id | doaj-art-d7f15c89fcd44a7490af47c25fbde0e4 |
| institution | Kabale University |
| issn | 1471-244X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Psychiatry |
| spelling | doaj-art-d7f15c89fcd44a7490af47c25fbde0e42024-11-17T12:40:25ZengBMCBMC Psychiatry1471-244X2024-11-0124111610.1186/s12888-024-06245-6The California collaborative network to promote data driven care and improve outcomes in early psychosis (EPI-CAL) project: rationale, background, design and methodologyValerie L. Tryon0Kathleen E. Nye1Mark Savill2Rachel Loewy3Madison J. Miles4Laura M. Tully5Andrew J. Padovani6Daniel J. Tancredi7Joy Melnikow8Sabrina Ereshefsky9Nitasha Sharma10Amanda P. McNamara11Merissa Kado-Walton12Christopher Komei Hakusui13Chelyah Miller14Khanh Linh H. Nguyen15Maliha Safdar16Viviana E. Padilla17Leigh Smith18Adam B. Wilcox19Lindsay M. Banks20Stephania L. Hayes21Katherine M. Pierce22Karina Muro23Daniel I. Shapiro24Khalima A. Bolden-Thompson25Renata M. Botello26Rebecca E. Grattan27Yi Zhang28Bonita Hotz29Lisa Dixon30Cameron S. Carter31Tara A. Niendam32University of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of CaliforniaUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of CaliforniaUniversity of CaliforniaUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of CaliforniaUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterWashington University in St. LouisUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterNew York State Psychiatric InstituteUniversity of California Davis Medical CenterUniversity of California Davis Medical CenterAbstract Background A prolonged first episode of psychosis (FEP) without adequate treatment is a predictor of poor clinical, functional, and health outcomes and significant economic burden. Team-based “coordinated specialty care” (CSC) for early psychosis (EP) has established effectiveness in promoting clinical and functional recovery. However, California’s CSC program implementation has been unsystematic and could benefit from standardizing its processes and data collection infrastructure. To address this, we established a consortium of EP clinics across the state via a Learning Health Care Network (LHCN) framework to develop the Early Psychosis Intervention Network of California (EPI-CAL). EPI-CAL’s LHCN developed a core battery of evidence-based measures for service users and family members and linked them together using a unique data collection and visualization application, Beehive. Methods and objectives EPI-CAL’s LHCN collects, visualizes, and aggregates data at the individual and clinic level for EP programs across California via Beehive. Beehive was designed to: (1) collect outcomes data from service users receiving care at EP programs and their support persons, (2) provide the data to providers on a secure web-based dashboard to support measurement-based care, and (3) allow data to be used for program or research analysis. We will (1) determine the feasibility of implementing an LHCN across a diverse, decentralized network of early psychosis programs, (2) determine if the implementation of an LHCN increases the delivery of measurement-based care, and (3) determine if the implementation of measurement-based care is associated with significant improvements in key service user outcomes. EPI-CAL’s network will contribute data to the Early Psychosis Intervention Network (EPINET) program. Discussion The current study aims to establish an LHCN of EP clinics in California that implements harmonized data collection using Beehive and assesses the feasibility of establishing such a network. Our goal is for this harmonized data collection approach to be used to inform decisions and develop learning opportunities for service users, staff, and administrators, and to improve outcomes for service users and their supporters in CSC care. Further, the data will enable programs and research teams to examine what elements of care lead to program success and improved treatment outcomes for service users. Clinical trials registration www.ClinicalTrials.gov , identifier NCT04007510; registered 07/05/2019.https://doi.org/10.1186/s12888-024-06245-6Early psychosisCoordinated specialty careLearning health care networkEPINET |
| spellingShingle | Valerie L. Tryon Kathleen E. Nye Mark Savill Rachel Loewy Madison J. Miles Laura M. Tully Andrew J. Padovani Daniel J. Tancredi Joy Melnikow Sabrina Ereshefsky Nitasha Sharma Amanda P. McNamara Merissa Kado-Walton Christopher Komei Hakusui Chelyah Miller Khanh Linh H. Nguyen Maliha Safdar Viviana E. Padilla Leigh Smith Adam B. Wilcox Lindsay M. Banks Stephania L. Hayes Katherine M. Pierce Karina Muro Daniel I. Shapiro Khalima A. Bolden-Thompson Renata M. Botello Rebecca E. Grattan Yi Zhang Bonita Hotz Lisa Dixon Cameron S. Carter Tara A. Niendam The California collaborative network to promote data driven care and improve outcomes in early psychosis (EPI-CAL) project: rationale, background, design and methodology BMC Psychiatry Early psychosis Coordinated specialty care Learning health care network EPINET |
| title | The California collaborative network to promote data driven care and improve outcomes in early psychosis (EPI-CAL) project: rationale, background, design and methodology |
| title_full | The California collaborative network to promote data driven care and improve outcomes in early psychosis (EPI-CAL) project: rationale, background, design and methodology |
| title_fullStr | The California collaborative network to promote data driven care and improve outcomes in early psychosis (EPI-CAL) project: rationale, background, design and methodology |
| title_full_unstemmed | The California collaborative network to promote data driven care and improve outcomes in early psychosis (EPI-CAL) project: rationale, background, design and methodology |
| title_short | The California collaborative network to promote data driven care and improve outcomes in early psychosis (EPI-CAL) project: rationale, background, design and methodology |
| title_sort | california collaborative network to promote data driven care and improve outcomes in early psychosis epi cal project rationale background design and methodology |
| topic | Early psychosis Coordinated specialty care Learning health care network EPINET |
| url | https://doi.org/10.1186/s12888-024-06245-6 |
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