Background: The creation of a computerized clinical database with the ability to collect prospective information from patients and with the possibility of rescue and crossing data enables scientific studies of higher quality and credibility in less time. Aim: To validate, in a single master protocol, the clinical data referring to Surgery of Digestive System in a multidisciplinary way, incorporating in the SINPE© platform, and to verify the incidence of digestive diseases based on the prospectively performed collections. Method: Organize in one software, in a standardized structure, all the pre-existing items in the SINPE© database; the theoretical basis was computerized through the MIGRASINPE© module creating a single multiprofessional master protocol for use as a whole. Results: The existing specific protocols were created and/or adapted - they correspond to the most prevalent digestive diseases - unifying them. The possibility of multiprofessional use was created by integrating all data collected from medicine, nursing, physiotherapy, nutrition and health management in a prospective way. The total was 4,281 collections, distributed as follows: extrahepatic biliary tract, n=1,786; esophagus, n=1015; anorectal, n=736; colon, n=550; small intestine, n=86; pancreas, n=71; stomach, n=23; liver, n=14. Conclusions: The validation of the unification and structuring in a single master protocol of the clinical data referring to the Surgery of the Digestive System in a multiprofessional and prospective way was possible and the epidemiological study carried out allowed to identify the most prevalent digestive diseases.

Population health management (PHM) is an important approach to promote wellness and deliver health care to targeted individuals who meet criteria for preventive measures or treatment. A critical component for any PHM program is a data analytics platform that can target those eligible individuals. Objective The aim of this study was to design and implement a scalable standards-based clinical decision support (CDS) approach to identify patient cohorts for PHM and maximize opportunities for multi-site dissemination. Materials and Methods An architecture was established to support bidirectional data exchanges between heterogeneous electronic health record (EHR) data sources, PHM systems, and CDS components. HL7 Fast Healthcare Interoperability Resources and CDS Hooks were used to facilitate interoperability and dissemination. The approach was validated by deploying the platform at multiple sites to identify patients who meet the criteria for genetic evaluation of familial cancer. Results The Genetic Cancer Risk Detector (GARDE) platform was created and is comprised of four components: (1) an open-source CDS Hooks server for computing patient eligibility for PHM cohorts, (2) an open-source Population Coordinator that processes GARDE requests and communicates results to a PHM system, (3) an EHR Patient Data Repository, and (4) EHR PHM Tools to manage patients and perform outreach functions. Site-specific deployments were performed on onsite virtual machines and cloud-based Amazon Web Services. Discussion GARDE’s component architecture establishes generalizable standards-based methods for computing PHM cohorts. Replicating deployments using one of the established deployment methods requires minimal local customization. Most of the deployment effort was related to obtaining site-specific information technology governance approvals.

Racial/ethnic minority, low socioeconomic status, and rural populations are disproportionately affected by COVID-19. Developing and evaluating interventions to address COVID-19 testing and vaccination among these populations are crucial to improving health inequities. The purpose of this paper is to describe the application of a rapid-cycle design and adaptation process from an ongoing trial to address COVID-19 among safety-net healthcare system patients. The rapid-cycle design and adaptation process included: (a) assessing context and determining relevant models/frameworks; (b) determining core and modifiable components of interventions; and (c) conducting iterative adaptations using Plan-Do-Study-Act (PDSA) cycles. PDSA cycles included: Plan. Gather information from potential adopters/implementers (e.g., Community Health Center [CHC] staff/patients) and design initial interventions; Do. Implement interventions in single CHC or patient cohort; Study. Examine process, outcome, and context data (e.g., infection rates); and, Act. If necessary, refine interventions based on process and outcome data, then disseminate interventions to other CHCs and patient cohorts. Seven CHC systems with 26 clinics participated in the trial. Rapid-cycle, PDSA-based adaptations were made to adapt to evolving COVID-19-related needs. Near real-time data used for adaptation included data on infection hot spots, CHC capacity, stakeholder priorities, local/national policies, and testing/vaccine availability. Adaptations included those to study design, intervention content, and intervention cohorts. Decision-making included multiple stakeholders (e.g., State Department of Health, Primary Care Association, CHCs, patients, researchers). Rapid-cycle designs may improve the relevance and timeliness of interventions for CHCs and other settings that provide care to populations experiencing health inequities, and for rapidly evolving healthcare challenges such as COVID-19.

This chapter introduces strategies to meet knowledge transfer needs. The clinical knowledge repository infrastructure and tools developed at Intermountain Healthcare are described. The knowledge repository (KR) is a database with services housing knowledge assets. The electronic tools are used to access and manipulate the assets. The tools include (1) the Knowledge Repository Online, used to load, view, and review knowledge assets stored in the KR, (2) the Knowledge Authoring Tool, used to compose knowledge assets using schema-based XML templates, (3) the viewer, used for easy and rapid access to a predetermined collection of knowledge assets, and (4) KR Reports, used to mine monitoring data about KR tool usage and the user experience. The process for knowledge asset development is described, and four project-specific case studies are presented describing asset development incorporating the infrastructure and tools. The value added by knowledge engineers to the knowledge transfer process is discussed.

Racional: A criação de um banco de dados clínicos informatizado com a capacidade de coletar informações dos pacientes de forma prospectiva e com possibilidade de resgate e cruzamento viabiliza estudos científicos de maior qualidade e credibilidade em menor tempo. Objetivos: Validar em único protocolo mestre os dados clínicos referentes à Cirurgia do Aparelho Digestivo de forma multiprofissional incorporando-o na plataforma SINPEâ, e verificar a incidência das doenças digestivas com base nas coletas prospectivamente realizadas. Método: Organizar no software em estrutura padronizada todos os itens pré-existentes no banco de dados do SINPEâ, informatizou-se a base teórica através do módulo MIGRASINPE© criando-se um único protocolo mestre multiprofissional para uso como um todo. Resultados: Foram criados e/ou adaptados os protocolos específicos existentes - que correspondem às doenças mais prevalentes que assolam este aparelho – unificando-os. Criou-se a possibilidade de uso multiprofissional integrando todos os dados coletados da Medicina, Enfermagem, Fisioterapia, Nutrição e Gestão em Saúde de maneira prospectiva. O total foi de 4.281 coletas assim distribuídas: vias biliares extra-hepáticas n=1.786; esôfago n=1015; anorretais n=736; cólon n=550; intestino delgado n=86; pâncreas n=71; estômago=23; fígado n=14.  Conclusões: A validação da unificação e estruturação em único protocolo mestre dos dados clínicos referentes à Cirurgia do Aparelho Digestivo de forma multiprofissional e prospectiva foi possível e o estudo epidemiológico realizado permitiu identificar as doenças mais prevalentes nesse aparelho em um hospital universitário terciário.