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A state transition framework for patient-level modeling of engagement and retention in HIV care using longitudinal cohort data.
Lee, Hana; Hogan, Joseph W; Genberg, Becky L; Wu, Xiaotian K; Musick, Beverly S; Mwangi, Ann; Braitstein, Paula.
Afiliación
  • Lee H; Department of Biostatistics, Brown University, 121 S. Main Street, Providence, 02912, RI, USA.
  • Hogan JW; Department of Biostatistics, Brown University, 121 S. Main Street, Providence, 02912, RI, USA.
  • Genberg BL; Academic Model Providing Access to Healthcare (AMPATH), Eldoret, Kenya.
  • Wu XK; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Maryland, U.S.A.
  • Musick BS; Department of Biostatistics, Brown University, 121 S. Main Street, Providence, 02912, RI, USA.
  • Mwangi A; Division of Biostatistics, School of Medicine, Indiana University, Indiana, USA.
  • Braitstein P; Academic Model Providing Access to Healthcare (AMPATH), Eldoret, Kenya.
Stat Med ; 37(2): 302-319, 2018 Jan 30.
Article en En | MEDLINE | ID: mdl-29164648
ABSTRACT
The human immunodeficiency virus (HIV) care cascade is a conceptual model used to outline the benchmarks that reflects effectiveness of HIV care in the whole HIV care continuum. The models can be used to identify barriers contributing to poor outcomes along each benchmark in the cascade such as disengagement from care or death. Recently, the HIV care cascade has been widely applied to monitor progress towards HIV prevention and care goals in an attempt to develop strategies to improve health outcomes along the care continuum. Yet, there are challenges in quantifying successes and gaps in HIV care using the cascade models that are partly due to the lack of analytic approaches. The availability of large cohort data presents an opportunity to develop a coherent statistical framework for analysis of the HIV care cascade. Motivated by data from the Academic Model Providing Access to Healthcare, which has provided HIV care to nearly 200,000 individuals in Western Kenya since 2001, we developed a state transition framework that can characterize patient-level movements through the multiple stages of the HIV care cascade. We describe how to transform large observational data into an analyzable format. We then illustrate the state transition framework via multistate modeling to quantify dynamics in retention aspects of care. The proposed modeling approach identifies the transition probabilities of moving through each stage in the care cascade. In addition, this approach allows regression-based estimation to characterize effects of (time-varying) predictors of within and between state transitions such as retention, disengagement, re-entry into care, transfer-out, and mortality. Copyright © 2017 John Wiley & Sons, Ltd.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Infecciones por VIH / Continuidad de la Atención al Paciente Tipo de estudio: Diagnostic_studies / Etiology_studies / Health_economic_evaluation / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged País/Región como asunto: Africa Idioma: En Revista: Stat Med Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Infecciones por VIH / Continuidad de la Atención al Paciente Tipo de estudio: Diagnostic_studies / Etiology_studies / Health_economic_evaluation / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged País/Región como asunto: Africa Idioma: En Revista: Stat Med Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos