Data collection for care pathways in the Cleveland Clinic Health System.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 115-115
Author(s):  
Katherine Glass ◽  
Chad W Cummings ◽  
Marc A. Shapiro ◽  
Dennis Urbanek ◽  
Brian James Bolwell
Keyword(s):  
Pilot Study ◽  
Data Collection ◽  
Health System ◽  
Real Time ◽  
Care Pathway ◽  
Care Pathways ◽  
Integration Of Care ◽  
Chemotherapeutic Regimen ◽  
Tumor Registry ◽  
Oncology Care

115 Background: Care pathways are established methods of reducing healthcare costs and disparities in oncology care. To demonstrate their impact, health systems must measure and report data on care pathway adherence and outcomes in near real-time. Automating data abstraction across a health system for oncology is difficult due to the amount and detail of data required. Manual abstraction of data is considered slow and costly. Many consider Electronic Medical Record (EMR) integration of care pathways essential in order to successfully implement and assess. Methods: 7 medical oncology care pathways and 45 medical oncologists across the health system were selected for a pilot study to assess the feasibility of implementing care pathways throughout the enterprise. The pilot study also allowed for testing of data collection capabilities. Patients eligible for the care pathways were prospectively identified by manual review of physician calendars. A small number of data points were manually abstracted from the patient EMR at the time of identification. Endpoints of interest, such as hospitalization rates, chemotherapy administered, time to treatment, and costs of care were reconciled through pre-existing databases within pharmacy, research, and finance. Tumor registry data identified a retrospective cohort. Results: Over 1,000 patients were prospectively identified for the care pathway pilot between 1/1/2014 and 12/31/2014. The tumor registry identified 700 additional retrospective patients. The rapid analyses possible as a result of these efforts demonstrated physician adherence, improved patient outcomes, and significant cost savings. In one example, a care pathway for metastatic non-small cell lung cancer reduced charges by more than $98,000/patient by recommending patients receive one standardized chemotherapeutic regimen. Conclusions: Timely data collection for oncology care pathways is feasible and cost effective without EMR integration. Manual identification of patients combined with pre-existing data sources allowed for near-real time analysis of care pathways and provided valuable information about care pathway impact. Institutions can implement and assess care pathways with resources already available to them.

scholarly journals Public health and multiple sclerosis in Italy

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
D Bezzini ◽  
M A Battaglia ◽  
M Ponzio ◽  
T Manacorda ◽  
P Zaratin ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Health System ◽  
National Health ◽  
Care Pathway ◽  
Clinical Care ◽  
National Health System ◽  
Interdisciplinary Management ◽  
Care Pathways ◽  
Health And Social Care ◽  
Diagnosis Therapy

Abstract Background Multiple Sclerosis (MS) is a complex and progressive disease of the central nervous system. In Italy, prevalence of MS ranges from 198 (continental Regions) to 370 (Sardinia) per 100,000. Despite a National Health System, differences among Regions cause inequalities in access to and quality of care, also involving chronic diseases and disabilities, including MS. Methods Interviews and focus groups involving persons with MS, caregivers, institutions, patients association and other stakeholders were conducted in 2019, to evaluate MS policy landscape, existing services, guidelines and care pathways regarding diagnosis, therapy, follow up, strenghts and weaknesses. Results 600 MS specialized neurologists and 350 MS nurses operate in 240 MS Centers located in hospital neurology departments providing clinical care, disease modifying drugs (DMDs), interdisciplinary care. 13 Regions on 20 approved a PDTA (Diagnosis, Therapy, Care Pathway), other are due by 2020. A reference national PDTA has been already discussed by Regional Health Authorities Conference and Ministry of Health. Regional multistakeholder observatories will be organized. A national MS registry started in 2017, at present involving over 140 Centers and including data of 50% (60.000 patients) of estimated prevalence. Discussion MS specialized centers are recognized as the key component of MS care in Italy and the main refererral for 80% of patients, also taking in account that over 60% of patients receive a DMD. Access to rehabilitation is lacking and hospital, community and primary care linkage is needed, also considering transition from early stages to severe disability. Access to psycological support is variable and cost containment strategies restrict drug access and symptomatic care in some areas along with lacking of interdisciplinary management. It is mandatory to integrate health and social care pathways accordingly with the National Plan for Chronicity in which MS has to be included. Key messages MS specialized centers are the backbone care network in Italy. Integrated care pathways (PDTA) stated as National Health System rules define the right for the patients to receive the proper care.

scholarly journals Digitization of Measurement Based Care Pathways in Mental Health through REDCap and Electronic Health Record Integration (Preprint)

2020 ◽  
Author(s):  
Steve Hawley ◽  
David Rotenberg ◽  
Joanna Yu ◽  
Nikola Bogetic ◽  
Natalia Potapova ◽  
...  
Keyword(s):  
Mental Health ◽  
Data Collection ◽  
Data Quality ◽  
Real Time ◽  
Fold Increase ◽  
Self Report ◽  
Care Pathways ◽  
Health Record ◽  
Measurement Based Care ◽  
Clinician Attitudes

BACKGROUND The delivery of standardized self-report assessments is essential for measurement-based care (MBC) in mental health. Paper-based methods of MBC data collection may result in transcription errors, missing data, and other data quality issues when entered into the patient electronic health record (EHR). OBJECTIVE To address these issues, a dedicated instance of REDCap, a free, widely used electronic data capture platform, was established to enable the deployment of digitized self-assessments in clinical care pathways to inform clinical decision making. METHODS REDCap was integrated with the primary clinical information system to facilitate real-time transfer of discrete data and descriptive reports from REDCap into the EHR. Both technical and administrative components were required for complete implementation. A technology acceptance survey was also administered to capture physician and clinician attitudes towards the new system. RESULTS Integration of REDCap with the EHR transitioned clinical workflows from paper-based to electronic data collection. This resulted in significant time-savings, improved data quality and valuable real-time information delivery. Digitization of self-report assessments at each appointment contributed to clinic-wide implementation of the Major Depressive Disorder Integrated Care Pathway (MDD-ICP). This digital transformation facilitated a 4-fold increase in physician adoption of this ICP workflow and a 3-fold increase in patient enrollment resulting in an overall significant increase in MDD-ICP capacity. Physician and Clinician attitudes were overall positive with almost all respondents agreeing that the system was useful to their work. CONCLUSIONS REDCap provided an intuitive patient interface for collection of self-report measures, real-time access to results to inform clinical decisions, and an extensible backend for systems integration. The approach scaled effectively and expanded to high-impact clinics throughout the hospital, allowing for broad deployment of complex workflows and standardized assessments leading to accumulation of harmonized data across clinics and care pathways. REDCap is a flexible tool that can be effectively leveraged to facilitate automatic transfer of self-report data to the EHR. However, thoughtful governance is required to complement the technical implementation to ensure that data standardization, data quality, patient safety, and privacy are maintained.

Real-time extraction of breast cancer treatment process and outcome measures from an EPIC electronic health record (EHR).

2013 ◽  
Vol 31 (31_suppl) ◽  
pp. 1-1 ◽  
Author(s):  
Julie Lawrence Kuznetsov ◽  
Kathryn Bailey ◽  
Pacharintra K. Bombach ◽  
Stacey Carmichael ◽  
Xuemei Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Real Time ◽  
Care Pathway ◽  
Registry Data ◽  
Fiscal Year ◽  
Tumor Registry ◽  
Time To Treatment ◽  
Process Improvements ◽  
Informatics Infrastructure ◽  
Cohort Identification

1 Background: In 2011, Stanford Cancer Institute (SCI) clinical leadership began process improvements to enhance patient satisfaction and quality of care. To measure impacts, unnecessary care variation, and outcomes, we recently developed an informatics infrastructure utilizing data from our EHR (epic modules: BEACON, Cadence, OpTime). We report successful initial efforts including real-time cohort identification (comparing with “gold standard” registry data), and improvements in time to treatment. Methods: A cohort of 1,692 patients was defined by 3 criteria: newly evaluated at SCI, AND received treatment [surgery, chemotherapy (chemo), or radiation (XRT)] at SCI, AND had a breast cancer related ICD-9 code. We analyzed data by fiscal year (FY), starting September, 2010 to FY13 year-to-date. “Time to treatment (Rx)” was measured as the interval between first EHR time stamp for SCI patient contact and Rx date. We used discrete data from the BEACON staging module to create sub-cohorts by stage, and used BEACON protocols to identify chemo regimens. Our cohorts were compared with SCI tumor registry data, and presented in a dynamic Qlikview dashboard. Results: 98% of the EHR-defined cohort matched a similarly defined tumor registry cohort. We detected the effect of process improvements (including scheduling a visit on first contact, coordinating among surgical specialties, outside records available pre-visit, etc.), which resulted in an accelerated time to Rx (Table). Discrete BEACON stage is available for 7% of these 1692 patients. The methodology is scalable and has been successfully replicated in GI and thoracic cohorts. Conclusions: Our work demonstrates utility of EHR data to track process improvements. Uniform use of the BEACON staging module will facilitate variation analysis across cancer types and stages, and allow us to explore variation within modalities (chemo, surgery, XRT). We will analyze associated costs and intermediate clinical outcomes (e.g., unplanned emergency visits and hospitalizations) to inform care pathway choice. [Table: see text]

Enhancing Clinical Supervision Using High-Definition Real-Time Digital Recording, Annotation, and Bluetooth Technology

2019 ◽  
Vol 4 (2) ◽  
pp. 356-362
Author(s):  
Jennifer W. Means ◽  
Casey McCaffrey
Keyword(s):  
Graduate Students ◽  
Data Collection ◽  
Real Time ◽  
Clinical Supervision ◽  
Video Recording ◽  
Advanced Technology ◽  
High Definition ◽  
Recording Technology ◽  
Self Confidence ◽  
Additional Data Collection

Purpose The use of real-time recording technology for clinical instruction allows student clinicians to more easily collect data, self-reflect, and move toward independence as supervisors continue to provide continuation of supportive methods. This article discusses how the use of high-definition real-time recording, Bluetooth technology, and embedded annotation may enhance the supervisory process. It also reports results of graduate students' perception of the benefits and satisfaction with the types of technology used. Method Survey data were collected from graduate students about their use and perceived benefits of advanced technology to support supervision during their 1st clinical experience. Results Survey results indicate that students found the use of their video recordings useful for self-evaluation, data collection, and therapy preparation. The students also perceived an increase in self-confidence through the use of the Bluetooth headsets as their supervisors could provide guidance and encouragement without interrupting the flow of their therapy sessions by entering the room to redirect them. Conclusions The use of video recording technology can provide opportunities for students to review: videos of prospective clients they will be treating, their treatment videos for self-assessment purposes, and for additional data collection. Bluetooth technology provides immediate communication between the clinical educator and the student. Students reported that the result of that communication can improve their self-confidence, perceived performance, and subsequent shift toward independence.

Patient Flow or the Patient’s Journey? Exploring Health Care Providers’ Experiences and Understandings of Implementing a Care Pathway to Improve the Quality of Transitional Care for Older People

2021 ◽  
pp. 104973232110038
Author(s):  
Cecilie Fromholt Olsen ◽  
Astrid Bergland ◽  
Jonas Debesay ◽  
Asta Bye ◽  
Anne Gudrun Langaas
Keyword(s):  
Health Care ◽  
Older People ◽  
Health Care Providers ◽  
Transitional Care ◽  
Care Pathway ◽  
Patient Flow ◽  
Care Pathways ◽  
Care Providers ◽  
Patient Centered ◽  
Care For Older People

Internationally, the implementation of care pathways is a common strategy for making transitional care for older people more effective and patient-centered. Previous research highlights inherent tensions in care pathways, particularly in relation to their patient-centered aspects, which may cause dilemmas for health care providers. Health care providers’ understandings and experiences of this, however, remain unclear. Our aim was to explore health care providers’ experiences and understandings of implementing a care pathway to improve transitional care for older people. We conducted semistructured interviews with 20 health care providers and three key persons, along with participant observations of 22 meetings, in a Norwegian quality improvement collaborative. Through a thematic analysis, we identified an understanding of the care pathway as both patient flow and the patient’s journey and a dilemma between the two, and we discuss how the negotiation of conflicting institutional logics is a central part of care pathway implementation.

scholarly journals Improving mobility and participation of older people with vertigo, dizziness and balance disorders in primary care using a care pathway: feasibility study and process evaluation

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Eva Seckler ◽  
Verena Regauer ◽  
Melanie Krüger ◽  
Anna Gabriel ◽  
Joachim Hermsdörfer ◽  
...  
Keyword(s):  
Primary Care ◽  
Data Collection ◽  
Older People ◽  
Process Evaluation ◽  
Feasibility Study ◽  
Health Professionals ◽  
Implementation Strategy ◽  
Care Pathway ◽  
Main Trial ◽  
Telephone Helpline

Abstract Background Community-dwelling older people are frequently affected by vertigo, dizziness and balance disorders (VDB). We previously developed a care pathway (CPW) to improve their mobility and participation by offering standardized approaches for general practitioners (GPs) and physical therapists (PTs). We aimed to assess the feasibility of the intervention, its implementation strategy and the study procedures in preparation for the subsequent main trial. Methods This 12-week prospective cohort feasibility study was accompanied by a process evaluation designed according to the UK Medical Research Council’s Guidance for developing and evaluating complex interventions. Patients with VDB (≥65 years), GPs and PTs in primary care were included. The intervention consisted of a diagnostic screening checklist for GPs and a guide for PTs. The implementation strategy included specific educational trainings and a telephone helpline. Data for mixed-method process evaluation were collected via standardized questionnaires, field notes and qualitative interviews. Quantitative data were analysed using descriptive statistics, qualitative data using content analysis. Results A total of five GP practices (seven single GPs), 10 PT practices and 22 patients were included in the study. The recruitment of GPs and patients was challenging (response rates: GP practices: 28%, PT practices: 39%). Ninety-one percent of the patients and all health professionals completed the study. The health professionals responded well to the educational trainings; the utilization of the telephone helpline was low (one call each from GPs and PTs). Familiarisation with the routine of application of the intervention and positive attitudes were emphasized as facilitators of the implementation of the intervention, whereas a lack of time was mentioned as a barrier. Despite difficulties in the GPs’ adherence to the intervention protocol, the GPs, PTs and patients saw benefit in the intervention. The patients’ treatment adherence to physical therapy was good. There were minor issues in data collection, but no unintended consequences. Conclusion Although the process evaluation provided good support for the feasibility of study procedures, the intervention and its implementation strategy, we identified a need for improvement in recruitment of participants, the GP intervention part and the data collection procedures. The findings will inform the main trial to test the interventions effectiveness in a cluster RCT. Trial registration Projektdatenbank Versorgungsforschung Deutschland (German registry Health Services Research) VfD_MobilE-PHY_17_003910, date of registration: 30.11.2017; Deutsches Register Klinischer Studien (German Clinical Trials Register) DRKS00022918, date of registration: 03.09.2020 (retrospectively registered).

scholarly journals Piloting the Play Cycle Observation Method in ‘real time’: Recording children’s Play Cycles in pre-school provision

2020 ◽  
pp. 1476718X2096985
Author(s):  
Pete King ◽  
LaDonna Atkins ◽  
Brandon Burr
Keyword(s):  
Pilot Study ◽  
Real Time ◽  
School Setting ◽  
Early Years ◽  
Good Reliability ◽  
Rater Reliability ◽  
Children's Play ◽  
Observational Tool ◽  
Observation Method ◽  
And Training

The Play Cycle Observation Method (PCOM) is an observational tool developed to focus on the process of play and has shown good reliability when watching videos of children playing. This study piloted use of the PCOM in ‘real time’ in a pre-school setting where 3-year-old children play. The results from two independent observers not familiar with the concept of the Play Cycle or the PCOM found good inter-rater reliability using Cohen Kappa (k) when observing play cues to form play cycles, as well as observing play cues within established play cycles. In addition, the recording of the nature of the play cues and play returns, the play frame and how the play cycle finishes (annihilation) were shown to be consistent between the two inter-rater observers. The results of this pilot study indicate the PCOM can be used as an observational tool to record the process of play by both students and practitioners working in a range of contexts including playwork, childcare, early years and statutory education. The PCOM can also be used as a teaching and training aid for trainers and lecturers.

scholarly journals DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Suppawong Tuarob ◽  
Poom Wettayakorn ◽  
Ponpat Phetchai ◽  
Siripong Traivijitkhun ◽  
Sunghoon Lim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Data Collection ◽  
Stock Market ◽  
Real Time ◽  
Stock Prices ◽  
Contextual Information ◽  
Online News ◽  
Stock Prediction ◽  
Stock Market Prediction

AbstractThe explosion of online information with the recent advent of digital technology in information processing, information storing, information sharing, natural language processing, and text mining techniques has enabled stock investors to uncover market movement and volatility from heterogeneous content. For example, a typical stock market investor reads the news, explores market sentiment, and analyzes technical details in order to make a sound decision prior to purchasing or selling a particular company’s stock. However, capturing a dynamic stock market trend is challenging owing to high fluctuation and the non-stationary nature of the stock market. Although existing studies have attempted to enhance stock prediction, few have provided a complete decision-support system for investors to retrieve real-time data from multiple sources and extract insightful information for sound decision-making. To address the above challenge, we propose a unified solution for data collection, analysis, and visualization in real-time stock market prediction to retrieve and process relevant financial data from news articles, social media, and company technical information. We aim to provide not only useful information for stock investors but also meaningful visualization that enables investors to effectively interpret storyline events affecting stock prices. Specifically, we utilize an ensemble stacking of diversified machine-learning-based estimators and innovative contextual feature engineering to predict the next day’s stock prices. Experiment results show that our proposed stock forecasting method outperforms a traditional baseline with an average mean absolute percentage error of 0.93. Our findings confirm that leveraging an ensemble scheme of machine learning methods with contextual information improves stock prediction performance. Finally, our study could be further extended to a wide variety of innovative financial applications that seek to incorporate external insight from contextual information such as large-scale online news articles and social media data.

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