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Brady N, Liang Y, Seidl KL, Marcozzi D, Stryckman B, Gingold DB. Association of Timely Outpatient Follow-Up and Readmission Risk in a Mobile Integrated Health Program. Popul Health Manag 2024; 27:249-256. [PMID: 38682441 DOI: 10.1089/pop.2024.0020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/01/2024] Open
Abstract
The objective was to identify medical conditions associated with 30-day readmission, determine patient characteristics for which outpatient follow-up is most associated with reduced readmission, and evaluate how readmission risk changes with time to outpatient follow-up within a mobile integrated health-community paramedicine (MIH-CP) program. This retrospective observational study used data from 1,118 adult patient enrollments in a MIH-CP program operating in Baltimore, Maryland, from May 14, 2018, to December 21, 2021. Bivariate analysis identified chronic disease exacerbations associated with higher 30-day readmission risk. Kaplan-Meier curves and Cox proportional hazard regressions were used to measure how hazard of readmission changes with outpatient follow-up and how that association may vary with other factors. Receiver operating characteristic analysis was used to evaluate how well time to follow-up could predict 30-day readmission. Timely outpatient follow-up was associated with a significant reduction in hazard of readmission for patients aged 50 and younger and for patients with fewer than 5 social determinants of health needs identified. No significant association between readmission and specific chronic disease exacerbations was observed. An optimal follow-up time frame to reduce readmissions could not be identified. Timely outpatient follow-up may be effective for reducing readmissions in younger patients and patients who are less socially complex. Programs and policies aiming to reduce 30-day readmissions may have more success by expanding efforts to include these patients.
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Affiliation(s)
- Nicholas Brady
- University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Yuanyuan Liang
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Kristin L Seidl
- Department of Quality and Safety, University of Maryland Medical Center, Baltimore, USA
- Department of Organizational Systems and Adult Health, University of Maryland School of Nursing, Baltimore, Maryland, USA
| | - David Marcozzi
- Departments of Emergency Medicine and Epidemiology, , University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Benoit Stryckman
- Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Daniel B Gingold
- Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
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Fassas E, Fischer K, Schenkel S, David Gatz J, Gingold DB. Public Health Interventions in the Emergency Department: A Framework for Evaluation. West J Emerg Med 2024; 25:415-422. [PMID: 38801049 PMCID: PMC11112666 DOI: 10.5811/westjem.18316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 12/14/2023] [Accepted: 12/15/2023] [Indexed: 05/29/2024] Open
Abstract
Emergency departments (ED) in the United States serve a dual role in public health: a portal of entry to the health system and a safety net for the community at large. Public health officials often target the ED for public health interventions due to the perception that it is uniquely able to reach underserved populations. However, under time and resource constraints, emergency physicians and public health officials must make calculated decisions in choosing which interventions in their local context could provide maximal impact to achieve public health benefit. We identify how decisions regarding public health interventions are affected by considerations of cost, time, and available personnel, and further consider the role of local community needs, health department goals, and political environment. We describe a sample of ED-based public health interventions and demonstrate how to use a proposed framework to assess interventions. We posit a series of questions and variables to consider: local disease prevalence; ability of the ED to perform the intervention; relative efficacy of the ED vs community partnerships as the primary intervention location; and expected outcomes. In using this framework, clinicians should be empowered to improve the public health in their communities.
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Affiliation(s)
| | - Kyle Fischer
- University of Maryland School of Medicine, Baltimore, Maryland
| | | | - John David Gatz
- University of Maryland School of Medicine, Baltimore, Maryland
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Mather H, Kleijwegt H, Bollens-Lund E, Liu B, Garrido MM, Kelley AS, Leff B, Ritchie CS, Ornstein KA. The heterogeneity of the homebound: A latent class analysis of a national sample of homebound older adults. J Am Geriatr Soc 2023; 71:2163-2171. [PMID: 36876755 DOI: 10.1111/jgs.18295] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/25/2023] [Accepted: 01/27/2023] [Indexed: 03/07/2023]
Abstract
BACKGROUND Homebound status is a final common pathway for people with a variety of diseases and conditions. There are 7 million homebound older adults in the United States. Despite concerns regarding their high healthcare costs and utilization and limited access to care, the unique subsets within the homebound population are understudied. Better understanding of distinct homebound groups may enable more targeted and tailored approaches to care delivery. Therefore, in a nationally representative sample of homebound older adults we used latent class analysis (LCA) to examine distinct homebound subgroups based on clinical and sociodemographic characteristics. MATERIALS AND METHODS Using data from the National Health and Aging Trends Study (NHATS) 2011-2019, we identified 901 newly homebound persons (defined as never/rarely leaving home or leaving home only with assistance and/or difficulty). Sociodemographic, caregiving context, health and function, and geographic covariates were derived from NHATS via self-report. LCA was used to identify the existence of distinct subgroups within the homebound population. Indices of model fit were compared for models testing 1-5 latent classes. Association between latent class membership and 1 year mortality was examined using a logistic regression. RESULTS We identified four classes of homebound individuals differentiated by their health, function, sociodemographic characteristics, and caregiving context: (i) Resource constrained (n = 264); (ii) Multimorbid/high symptom burden (n = 216); (iii) Dementia/functionally impaired (n = 307); (iv) Older/assisted living (n = 114). One year mortality was highest among the older/assisted living subgroup (32.4%) and lowest among the resource constrained (8.2%). CONCLUSIONS This study identifies subgroups of homebound older adults characterized by distinct sociodemographic and clinical characteristics. These findings will support policymakers, payers, and providers in targeting and tailoring care to the needs of this growing population.
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Affiliation(s)
- Harriet Mather
- Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Hannah Kleijwegt
- Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Evan Bollens-Lund
- Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bian Liu
- Department of Population Health Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Melissa M Garrido
- Partnered Evidence-based Policy Resource Center, Boston VA Healthcare System, Boston, Massachusetts, USA
- Department of Health Law, Policy & Management, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Amy S Kelley
- Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bruce Leff
- Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Center for Transformative Geriatrics Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Community and Public Health, Johns Hopkins School of Nursing, Baltimore, Maryland, USA
| | - Christine S Ritchie
- Division of Palliative Care and Geriatric Medicine, Mongan Institute Center for Aging and Serious Illness, Massachusetts General Hospital, Boston, Massachusetts, USA
- Center for Palliative Care, Harvard Medical School, Boston, Massachusetts, USA
| | - Katherine A Ornstein
- Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Community and Public Health, Johns Hopkins School of Nursing, Baltimore, Maryland, USA
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Wang M, Long F, Liu D, Zhuo Y, Tian L, Liang H. Application of WeChat-Utilized Mobile Health in Transitional Care Among Patients Undergoing Hepatectomy: A Pilot Study. Clin Nurs Res 2023; 32:298-305. [PMID: 36514816 DOI: 10.1177/10547738221143664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
This study aimed to investigate whether mobile health (mHealth)-based transitional care, which utilized WeChat, could benefit patients undergoing hepatectomy. From January 2019 to December 2020, 807 patients who underwent hepatectomy in a tertiary care hospital were included in the study. Patients were divided into a transitional care group (TC group) (n = 238) and a control group (n = 569) based on whether they participated in mHealth-based transitional care, which utilized the WeChat application. Depending on the type of variables, t-tests, χ2 tests, and other statistical methods were used to compare differences between groups. Propensity score matching analysis was conducted for factors that differed in basic characteristics. After 1:1 matching, 238 patients were included in each group. Less readmission within 90 days of discharge, better quality of life, and higher satisfaction were found in the TC group both before and after matching (p < .05). This study showed the potential of applying mHealth-based transitional care among post-hepatectomy patients.
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Affiliation(s)
- Meng Wang
- Department of Traditional Chinese Medicine, General Hospital of Western Theater Command (Chengdu Military General Hospital), China
| | - Fei Long
- Department of General Surgery, General Hospital of Western Theater Command (Chengdu Military General Hospital), China
| | - Defang Liu
- Department of Traditional Chinese Medicine, General Hospital of Western Theater Command (Chengdu Military General Hospital), China
| | - Yue Zhuo
- Department of Traditional Chinese Medicine, General Hospital of Western Theater Command (Chengdu Military General Hospital), China
| | - Lijuan Tian
- Department of Traditional Chinese Medicine, General Hospital of Western Theater Command (Chengdu Military General Hospital), China
| | - Hongyin Liang
- Department of General Surgery, General Hospital of Western Theater Command (Chengdu Military General Hospital), China
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Naimi S, Stryckman B, Liang Y, Seidl K, Harris E, Landi C, Thomas J, Marcozzi D, Gingold DB. Evaluating Social Determinants of Health in a Mobile Integrated Healthcare-Community Paramedicine Program. J Community Health 2023; 48:79-88. [PMID: 36269531 DOI: 10.1007/s10900-022-01148-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/05/2022] [Indexed: 11/26/2022]
Abstract
In 2018, the University of Maryland Medical Center and the Baltimore City Fire Department implemented a community paramedicine program to help medically or socially complex patients transition from hospital to home and avoid hospital utilization. This study describes how patients' social determinants of health (SDoH) needs were identified, and measures the association between needs and hospital utilization. SDoH needs were categorized into ten domains. Multinomial logistic regression was used to measure association between identified SDoH domains and predicted risk of readmission. Poisson regression was used to measure association between SDoH domains and actual 30-day hospital utilization. The most frequently identified SDoH needs were in the Coordination of Healthcare (37.7%), Durable Medical Equipment (18.8%), and Medication (16.3%) domains. Compared with low-risk patients, patients with an intermediate risk of readmission were more likely to have needs within the Coordination of Healthcare (RRR [95% CI] 1.12 [1.01, 1.24], p = 0.032) and Durable Medical Equipment (RRR = 1.13 [1.00, 1.27], p = 0.046) domains. Patients with the highest risk for readmission were more likely to have needs in the Utilities domain (RRR = 1.76 [0.97, 3.19], p = 0.063). Miscellaneous domain needs, such as requiring a social security card, were associated with increased 30-day hospital utilization (IRR = 1.23 [0.96, 1.57], p = 0.095). SDoH needs within the Coordination of Healthcare, Durable Medical Equipment, and Utilities domains were associated with higher predicted 30-day readmission, while identification documentation and social services needs were associated with actual readmission. These results suggest where to allocate resources to effectively diminish hospital utilization.
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Affiliation(s)
- Sean Naimi
- University of Maryland School of Medicine, 620 W Lexington St, Baltimore, MD, 21201, USA.
| | - Benoit Stryckman
- Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Yuanyuan Liang
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Kristin Seidl
- Department of Quality and Safety, University of Maryland Medical Center, Baltimore, USA
- Department of Organizational Systems and Adult Health, University of Maryland School of Nursing, Baltimore, MD, 21201, USA
| | - Erinn Harris
- Baltimore City Fire Department, Baltimore, MD, 21201, USA
| | - Colleen Landi
- Mobile Integrated Health Community Paramedicine, University of Maryland Medical Center, Baltimore, MD, 21201, USA
| | - Jessica Thomas
- Baltimore City Fire Department, Baltimore, MD, 21201, USA
| | - David Marcozzi
- Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Daniel B Gingold
- Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
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Sokan O, Stryckman B, Liang Y, Osotimehin S, Gingold DB, Blakeslee WW, Moore MJ, Banas CA, Landi CT, Rodriguez M. Impact of a mobile integrated healthcare and community paramedicine program on improving medication adherence in patients with heart failure and chronic obstructive pulmonary disease after hospital discharge: A pilot study. EXPLORATORY RESEARCH IN CLINICAL AND SOCIAL PHARMACY 2022; 8:100201. [DOI: 10.1016/j.rcsop.2022.100201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 11/02/2022] [Accepted: 11/10/2022] [Indexed: 11/14/2022] Open
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Shannon B, Eaton G, Lanos C, Leyenaar M, Nolan M, Bowles K, Williams B, O'Meara P, Wingrove G, Heffern JD, Batt A. The development of community paramedicine; a restricted review. HEALTH & SOCIAL CARE IN THE COMMUNITY 2022; 30:e3547-e3561. [PMID: 36065522 PMCID: PMC10087318 DOI: 10.1111/hsc.13985] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 06/01/2022] [Accepted: 08/13/2022] [Indexed: 05/22/2023]
Abstract
Community paramedic roles are expanding internationally, and no review of the literature could be found to guide services in the formation of community paramedicine programmes. For this reason, the aim of this restricted review was to explore and better understand the successes and learnings of community paramedic programmes across five domains being; education requirements, models of delivery, clinical governance and supervision, scope of roles and outcomes. This restricted review was conducted by searching four databases (CENTRAL, ERIC, EMBASE, MEDLINE and Google Scholar) as well as grey literature search from 2001 until 28/12/2021. After screening, 98 articles were included in the narrative synthesis. Most studies were from the USA (n = 37), followed by Canada (n = 29). Most studies reported on outcomes of community paramedicine programmes (n = 50), followed by models of delivery (n = 28). The findings of this review demonstrate a lack of research and understanding in the areas of education and scope of the role for community paramedics. The findings highlight a need to develop common approaches to education and scope of role while maintaining flexibility in addressing community needs. There was an observable lack of standardisation in the implementation of governance and supervision models, which may prevent community paramedicine from realising its full potential. The outcome measures reported show that there is evidence to support the implementation of community paramedicine into healthcare system design. Community paramedicine programmes result in a net reduction in acute healthcare utilisation, appear to be economically viable and result in positive patient outcomes with high patient satisfaction with care. There is a developing pool of evidence to many aspects of community paramedicine programmes. However, at this time, gaps in the literature prevent a definitive recommendation on the impact of community paramedicine programmes on healthcare system functionality.
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Affiliation(s)
- Brendan Shannon
- Department of ParamedicineMonash UniversityFrankstonVictoriaAustralia
| | - Georgette Eaton
- Nuffield Department of Primary Care Health SciencesUniversity of OxfordOxfordUK
| | | | - Matthew Leyenaar
- Department of Health and Wellness, Emergency Health ServicesGovernment of Prince Edward IslandPrince Edward IslandCanada
| | - Mike Nolan
- County of Renfrew Paramedic ServicePembrokeCanada
| | - Kelly‐Ann Bowles
- Department of ParamedicineMonash UniversityFrankstonVictoriaAustralia
| | - Brett Williams
- Department of ParamedicineMonash UniversityFrankstonVictoriaAustralia
| | - Peter O'Meara
- Department of ParamedicineMonash UniversityFrankstonVictoriaAustralia
| | - Gary Wingrove
- International Roundtable on Community ParamedicineDuluthMNUSA
| | - JD Heffern
- Indigenous Services Canada, Government of CanadaOttawaOntarioCanada
| | - Alan Batt
- Department of ParamedicineMonash UniversityFrankstonVictoriaAustralia
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Gingold DB, Liang Y, Stryckman B, Marcozzi D. The effect of a mobile integrated health program on health care cost and utilization. Health Serv Res 2021; 56:1146-1155. [PMID: 34402056 DOI: 10.1111/1475-6773.13773] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 07/14/2021] [Accepted: 07/19/2021] [Indexed: 11/28/2022] Open
Abstract
OBJECTIVE To measure the effect of a mobile integrated health community paramedicine (MIH-CP) transitional care program on hospital utilization, emergency department visits, and charges. DATA SOURCES Retrospective secondary data from the electronic health record and regional health information exchange were used to analyze patients discharged from a large academic medical center and an affiliated community hospital in Baltimore, Maryland, May 2018-October 2019. STUDY DESIGN We performed an observational study comparing patients enrolled in an MIH-CP program to propensity-matched controls. Propensity scores were calculated using measures of demographics, clinical characteristics, social determinants of health, and prior health care utilization. The primary outcome is inpatient readmission within 30 days of discharge. Secondary outcomes include excess days in acute care 30 days after discharge and emergency department visits, observation hospitalizations, and total health care charges within 30 and 60 days of discharge. DATA COLLECTION Included patients were over 18 years old, discharged to home from internal/family medicine services, and live in eligible ZIP codes. The intervention group was enrolled in the MIH-CP program; controls met inclusion criteria but were not enrolled during the study period. PRINCIPAL FINDINGS The adjusted model showed no difference in 30-day inpatient readmission between 464 enrolled patients and propensity-matched controls (adjusted incidence rate ratio = 1.19, 95% confidence interval [CI] [0.89, 1.60]). There was a higher rate of observation hospitalizations within 30 days of index discharge for MIH-CP patients (adjusted incidence rate ratio = 1.78, 95% CI = [1.01, 3.14]). This difference did not persist at 60 days, and there were no differences in other secondary outcomes. CONCLUSIONS We found no significant difference in short-term health care utilization or charges between patients enrolled in an MIH-CP transitional care program and propensity-matched controls. This highlights the importance of well-controlled, robust evaluations of effectiveness in novel care-delivery systems.
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Affiliation(s)
- Daniel B Gingold
- Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Yuanyuan Liang
- Department of Epidemiology and Public Health, Division of Biostatistics and Bioinformatics, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Benoit Stryckman
- Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - David Marcozzi
- Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
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