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Guo L, Reddy KP, Van Iseghem T, Pierce WN. Enhancing data practices for Whole Health: Strategies for a transformative future. Learn Health Syst 2024; 8:e10426. [PMID: 38883871 PMCID: PMC11176597 DOI: 10.1002/lrh2.10426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 03/22/2024] [Accepted: 04/16/2024] [Indexed: 06/18/2024] Open
Abstract
We explored the challenges and solutions for managing data within the Whole Health System (WHS), which operates as a Learning Health System and a patient-centered healthcare approach that combines conventional and complementary approaches. Addressing these challenges is critical for enhancing patient care and improving outcomes within WHS. The proposed solutions include prioritizing interoperability for seamless data exchange, incorporating patient-centered comparative clinical effectiveness research and real-world data to personalize treatment plans and validate integrative approaches, and leveraging advanced data analytics tools to incorporate patient-reported outcomes, objective metrics, robust data platforms. Implementing these measures will enable WHS to fulfill its mission as a holistic and patient-centered healthcare model, promoting greater collaboration among providers, boosting the well-being of patients and providers, and improving patient outcomes.
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Affiliation(s)
- Lei Guo
- Whole Health VA St. Louis Health Care System St. Louis Missouri USA
- School of Interdisciplinary Health Professions Northern Illinois University DeKalb Illinois USA
| | - Kavitha P Reddy
- Whole Health VA St. Louis Health Care System St. Louis Missouri USA
- Department of Veterans Affairs VHA Office of Patient-Centered Care and Cultural Transformation Washington D.C. USA
- School of Medicine Washington University in St. Louis St. Louis Missouri USA
| | - Theresa Van Iseghem
- Whole Health VA St. Louis Health Care System St. Louis Missouri USA
- School of Medicine Saint Louis University St. Louis Missouri USA
| | - Whitney N Pierce
- Whole Health VA St. Louis Health Care System St. Louis Missouri USA
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Baum L, Johns M, Poikela M, Möller R, Ananthasubramaniam B, Prasser F. Data integration and analysis for circadian medicine. Acta Physiol (Oxf) 2023; 237:e13951. [PMID: 36790321 DOI: 10.1111/apha.13951] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 02/04/2023] [Accepted: 02/12/2023] [Indexed: 02/16/2023]
Abstract
Data integration, data sharing, and standardized analyses are important enablers for data-driven medical research. Circadian medicine is an emerging field with a particularly high need for coordinated and systematic collaboration between researchers from different disciplines. Datasets in circadian medicine are multimodal, ranging from molecular circadian profiles and clinical parameters to physiological measurements and data obtained from (wearable) sensors or reported by patients. Uniquely, data spanning both the time dimension and the spatial dimension (across tissues) are needed to obtain a holistic view of the circadian system. The study of human rhythms in the context of circadian medicine has to confront the heterogeneity of clock properties within and across subjects and our inability to repeatedly obtain relevant biosamples from one subject. This requires informatics solutions for integrating and visualizing relevant data types at various temporal resolutions ranging from milliseconds and seconds to minutes and several hours. Associated challenges range from a lack of standards that can be used to represent all required data in a common interoperable form, to challenges related to data storage, to the need to perform transformations for integrated visualizations, and to privacy issues. The downstream analysis of circadian rhythms requires specialized approaches for the identification, characterization, and discrimination of rhythms. We conclude that circadian medicine research provides an ideal environment for developing innovative methods to address challenges related to the collection, integration, visualization, and analysis of multimodal multidimensional biomedical data.
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Affiliation(s)
- Lena Baum
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Marco Johns
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Maija Poikela
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ralf Möller
- Institute of Information Systems, University of Lübeck, Lübeck, Germany
| | | | - Fabian Prasser
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
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Snyder Valier AR, Huxel Bliven KC, Lam KC, Valovich McLeod TC. Patient-reported outcome measures as an outcome variable in sports medicine research. Front Sports Act Living 2022; 4:1006905. [PMID: 36406772 PMCID: PMC9666499 DOI: 10.3389/fspor.2022.1006905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 09/26/2022] [Indexed: 11/23/2022] Open
Abstract
Injury prevention and rehabilitation research often address variables that would be considered clinician-oriented outcomes, such as strength, range of motion, laxity, and return-to-sport. While clinician-oriented variables are helpful in describing the physiological recovery from injury, they neglect the patient perspective and aspects of patient-centered care. Variables that capture patient perspective are essential when considering the impact of injury and recovery on the lives of patients. The inclusion of patient-reported outcome measures (PROMs) as dependent variables in sports medicine research, including injury prevention and rehabilitation research, provides a unique perspective regarding the patient's perception of their health status, the effectiveness of treatments, and other information that the patient deems important to their care. Over the last 20 years, there has been a significant increase in the use of PROMs in sports medicine research. The growing body of work gives opportunity to reflect on what has been done and to provide some ideas of how to strengthen the evidence moving forward. This mini-review will discuss ideas for the inclusion of PROMs in sports medicine research, with a focus on critical factors, gaps, and future directions in this area of research. Important elements of research with PROMs, including instrument selection, administration, and interpretation, will be discussed and areas for improvement, consideration, and standardization will be provided.
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Affiliation(s)
- Alison R. Snyder Valier
- Department of Athletic Training, Arizona School of Health Sciences, A.T. Still University, Mesa, AZ, United States,School of Osteopathic Medicine in Arizona, A.T. Still University, Mesa, AZ, United States
| | - Kellie C. Huxel Bliven
- Department of Interdisciplinary Health Sciences, Arizona School of Health Sciences, A.T. Still University, Mesa, AZ, United States
| | - Kenneth C. Lam
- Department of Interdisciplinary Health Sciences, Arizona School of Health Sciences, A.T. Still University, Mesa, AZ, United States
| | - Tamara C. Valovich McLeod
- Department of Athletic Training, Arizona School of Health Sciences, A.T. Still University, Mesa, AZ, United States,School of Osteopathic Medicine in Arizona, A.T. Still University, Mesa, AZ, United States,*Correspondence: Tamara C. Valovich McLeod
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Delitto A, Patterson CG, Stevans JM, Freburger JK, Khoja SS, Schneider MJ, Greco CM, Freel JA, Sowa GA, Wasan AD, Brennan GP, Hunter SJ, Minick KI, Wegener ST, Ephraim PL, Beneciuk JM, George SZ, Saper RB. Stratified care to prevent chronic low back pain in high-risk patients: The TARGET trial. A multi-site pragmatic cluster randomized trial. EClinicalMedicine 2021; 34:100795. [PMID: 33870150 PMCID: PMC8040279 DOI: 10.1016/j.eclinm.2021.100795] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 02/22/2021] [Accepted: 02/24/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Many patients with acute low back pain (LBP) first seek care from primary care physicians. Evidence is lacking for interventions to prevent transition to chronic LBP in this setting. We aimed to test if implementation of a risk-stratified approach to care would result in lower rates of chronic LBP and improved self-reported disability. METHODS We conducted a pragmatic, cluster randomized trial using 77 primary care clinics in four health care systems across the United States. Practices were randomly assigned to a stratified approach to care (intervention) or usual care (control). Using the STarTBack screening tool, adults with acute LBP were screened low, medium, and high-risk. Patients screened as high-risk were eligible. The intervention included electronic best practice alerts triggering referrals for psychologically informed physical therapy (PIPT). PIPT education was targeted to community clinics geographically close to intervention primary care clinics. Primary outcomes were transition to chronic LBP and self-reported disability at six months. Trial Registry: ClinicalTrials.gov NCT02647658. FINDINGS Between May 2016 and June 2018, 1207 patients from 38 intervention and 1093 from 37 control practices were followed. In the intervention arm, around 50% of patients were referred for physical therapy (36% for PIPT) compared to 30% in the control. At 6 months, 47% of patients reported transition to chronic LBP in the intervention arm (38 practices, n = 658) versus 51% of patients in the control arm (35 practices, n = 635; OR=0.83 95% CI 0.64, 1.09; p = 0.18). No differences in disability were detected (difference -2·1, 95% CI -4.9-0.6; p = 0.12). Opioids and imaging were prescribed in 22%-25% and 23%-26% of initial visits, for intervention and control, respectively. Twelve-month LBP utilization was similar in the two groups. INTERPRETATION There were no differences detected in transition to chronic LBP among patients presenting with acute LBP using a stratified approach to care. Opioid and imaging prescribing rates were non-concordant with clinical guidelines. FUNDING Patient-Centered Outcomes Research Institute (PCORI) contract # PCS-1402-10867.
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Affiliation(s)
- Anthony Delitto
- School of Health and Rehabilitation Sciences, University of Pittsburgh, 4029 Forbes Tower, Pittsburgh, PA 15260 USA
- Corresponding author.
| | - Charity G. Patterson
- School of Health and Rehabilitation Sciences, University of Pittsburgh, 100 Technology Drive, Pittsburgh, PA 15219 USA
| | - Joel M. Stevans
- School of Health and Rehabilitation Sciences, University of Pittsburgh, 100 Technology Drive, Pittsburgh, PA 15219 USA
| | - Janet K. Freburger
- School of Health and Rehabilitation Sciences, University of Pittsburgh, 100 Technology Drive, Pittsburgh, PA 15219 USA
| | - Samannaaz S. Khoja
- School of Health and Rehabilitation Sciences, University of Pittsburgh, 100 Technology Drive, Pittsburgh, PA 15219 USA
| | - Michael J. Schneider
- School of Health and Rehabilitation Sciences, University of Pittsburgh, 100 Technology Drive, Pittsburgh, PA 15219 USA
| | - Carol M. Greco
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA 15213, USA
| | - Jennifer A. Freel
- Physician Network and Quality, St. Clair Hospital, 1000 Bower Hill Road, Pittsburgh, PA 15243 USA
| | - Gwendolyn A. Sowa
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, 3471 Fifth Avenue, Suite 1103, Pittsburgh, PA 15213, USA
| | - Ajay D. Wasan
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh School of Medicine, 3550 Terrace Street, Pittsburgh, PA 15261, USA
| | - Gerard P. Brennan
- 5848 South 300 East, Intermountain Healthcare Rehabilitation Services, Murray, Utah, 84107 USA
| | - Stephen J. Hunter
- 5848 South 300 East, Intermountain Healthcare Rehabilitation Services, Murray, Utah, 84107 USA
| | - Kate I. Minick
- 5848 South 300 East, Intermountain Healthcare Rehabilitation Services, Murray, Utah, 84107 USA
| | - Stephen T. Wegener
- 600 N. Wolfe Street, Johns Hopkins University School of Medicine, Baltimore, Maryland, 21287 USA
| | - Patti L. Ephraim
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 2024 E Monument Street, Baltimore, MD 21287, USA
| | - Jason M. Beneciuk
- Department of Physical Therapy, Box 100154, University of Florida College of Public Health and Health Professions, Gainesville, Florida, 32610 USA
| | - Steven Z. George
- Duke Clinical Research Institute and Department of Orthopaedic Surgery, 200 Morris Street, Duke University, Durham, North Carolina, 27701 USA
| | - Robert B. Saper
- Department of Family Medicine, Boston Medical Center, 1 Boston Medical Center Place, Dowling 5 South, Boston, MA 02118 USA
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