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Newman C, Mulrine S, Brittain K, Dawson P, Mason C, Spencer M, Sykes K, Young-Murphy L, Waring J, Scott J. Care Home Safety Incidents and Safeguarding Reports Relating to Hospital to Care Home Transitions: A Retrospective Content Analysis. J Patient Saf 2024; 20:478-489. [PMID: 39190398 DOI: 10.1097/pts.0000000000001267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/28/2024]
Abstract
OBJECTIVE The purpose of this study was to further the understanding of reported patient safety events at the interface between hospital and care home including what active failings and latent conditions were present and how reporting helped learning. METHODS Two care home organizations, one in the North East and one in the South West of England, participated in the study. Reports relating to a transition and where a patient safety event had occurred were sought during the COVID-19 (SARS-CoV-2) virus prepandemic and intrapandemic periods. All reports were screened for eligibility and analyzed using content analysis. RESULTS Seventeen South West England care homes and 15 North East England care homes sent 114 safety incident reports and after screening 91 were eligible for review. A hospital discharge transition (n = 78, 86%) was most common. Pressure damage (n = 29, 32%), medication errors (n = 26, 29%) and premature discharge (n = 21, 23%) contributed to 84% of the total reporting. Many 'active failings' (n = 340) were identified with fewer latent conditions (failings) (n = 14, 15%) being reported. No examples of individual learning were identified. Organization and systems learning were identified in 12 reports (n = 12, 13%). CONCLUSIONS The findings highlight potentially high levels of underreporting. The most common safety incidents reported were pressure damage, medication errors, and premature discharge. Many active failings causing numerous staff actions were identified emphasizing the cost to patients and services. Additionally, latent conditions (failings) were not emphasized; similarly, evidence of learning from safety incidents was not addressed.
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Affiliation(s)
- Craig Newman
- From the Northumbria University, Newcastle upon Tyne, United Kingdom
| | | | - Katie Brittain
- Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Pamela Dawson
- Plymouth Marjon University, Plymouth, United Kingdom
| | - Celia Mason
- From the Northumbria University, Newcastle upon Tyne, United Kingdom
| | - Michele Spencer
- North Tyneside Community and Health Care Forum, North Tyneside, United Kingdom
| | - Kate Sykes
- From the Northumbria University, Newcastle upon Tyne, United Kingdom
| | | | - Justin Waring
- University of Birmingham, Birmingham, United Kingdom
| | - Jason Scott
- From the Northumbria University, Newcastle upon Tyne, United Kingdom
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Fakeye O, Rana P, Han F, Henderson M, Stockwell I. Behavioral, Cognitive, and Functional Risk Factors for Repeat Hospital Episodes Among Medicare-Medicaid Dually Eligible Adults Receiving Long-Term Services and Supports. J Appl Gerontol 2024:7334648241286608. [PMID: 39325649 DOI: 10.1177/07334648241286608] [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: 09/28/2024] Open
Abstract
Repeat hospitalizations adversely impact the well-being of adults dually eligible for Medicare and Medicaid in the United States. This study aimed to identify behavioral, cognitive, and functional characteristics associated with the risk of a repeat hospital episode (HE) among the statewide population of dually eligible adults in Maryland receiving long-term services and supports prior to an HE between July 2018 and May 2020. The odds of experiencing a repeat HE within 30 days after an initial HE were positively associated with reporting difficulty with hearing (adjusted odds ratio, AOR: 1.10 [95% confidence interval: 1.02-1.19]), being easily distractible (AOR: 1.09 [1.00-1.18]), being self-injurious (AOR: 1.33 [1.09-1.63]), and exhibiting verbal abuse (AOR: 1.15 [1.02-1.30]). Conversely, displaying inappropriate public behavior (AOR: 0.62 [0.42-0.92]) and being dependent for eating (AOR: 0.91 [0.83-0.99]) or bathing (AOR: 0.79 [0.67-0.92]) were associated with reduced odds of a repeat HE. We also observed differences in the magnitude and direction of these associations among adults 65 years of age or older relative to younger counterparts.
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Affiliation(s)
| | - Prashant Rana
- University of Maryland Baltimore County, Baltimore, MD, USA
| | - Fei Han
- University of Maryland Baltimore County, Baltimore, MD, USA
| | | | - Ian Stockwell
- University of Maryland Baltimore County, Baltimore, MD, USA
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Bortolani A, Fantin F, Giani A, Zivelonghi A, Pernice B, Bortolazzi E, Urbani S, Zoico E, Micciolo R, Zamboni M. Predictors of hospital readmission rate in geriatric patients. Aging Clin Exp Res 2024; 36:22. [PMID: 38321332 PMCID: PMC10847193 DOI: 10.1007/s40520-023-02664-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 11/11/2023] [Indexed: 02/08/2024]
Abstract
BACKGROUND Hospital readmissions among older adults are associated with progressive functional worsening, increased institutionalization and mortality. AIM Identify the main predictors of readmission in older adults. METHODS We examined readmission predictors in 777 hospitalized subjects (mean age 84.40 ± 6.77 years) assessed with Comprehensive Geriatric Assessment (CGA), clinical, anthropometric and biochemical evaluations. Comorbidity burden was estimated by Charlson Comorbidity Index (CCI). Median follow-up was 365 days. RESULTS 358 patients (46.1%) had a second admission within 365 days of discharge. Estimated probability of having a second admission was 0.119 (95%C.I. 0.095-0.141), 0.158 (95%C.I. 0.131-0.183), and 0.496 (95%C.I. 0.458-0.532) at 21, 30 and 356 days, respectively. Main predictors of readmission at 1 year were length of stay (LOS) > 14 days (p < 0.001), albumin level < 30 g/l (p 0.018), values of glomerular filtration rate (eGFR) < 40 ml/min (p < 0.001), systolic blood pressure < 115 mmHg (p < 0.001), CCI ≥ 6 (p < 0.001), and cardiovascular diagnoses. When the joint effects of selected prognostic variables were accounted for, LOS > 14 days, worse renal function, systolic blood pressure < 115 mmHg, higher comorbidity burden remained independently associated with higher readmission risk. DISCUSSION Selected predictors are associated with higher readmission risk, and the relationship evolves with time. CONCLUSIONS This study highlights the importance of performing an accurate CGA, since defined domains and variables contained in the CGA (i.e., LOS, lower albumin and systolic blood pressure, poor renal function, and greater comorbidity burden), when combined altogether, may offer a valid tool to identify the most fragile patients with clinical and functional impairment enhancing their risk of unplanned early and late readmission.
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Affiliation(s)
- Arianna Bortolani
- Section of Geriatric Medicine, Department of Surgery, Dentistry, Pediatric and Gynecology, University of Verona, 37126, Verona, Italy.
| | - Francesco Fantin
- Section of Geriatric Medicine, Centre for Medical Sciences - CISMed, Department of Psychology and Cognitive Science, University of Trento, Rovereto (TN), Italy
| | - Anna Giani
- Section of Geriatric Medicine, Department of Surgery, Dentistry, Pediatric and Gynecology, University of Verona, 37126, Verona, Italy
| | - Alessandra Zivelonghi
- Section of Geriatric Medicine, Department of Surgery, Dentistry, Pediatric and Gynecology, University of Verona, 37126, Verona, Italy
| | - Bruno Pernice
- Section of Geriatric Medicine, Department of Surgery, Dentistry, Pediatric and Gynecology, University of Verona, 37126, Verona, Italy
| | - Elena Bortolazzi
- Section of Geriatric Medicine, Department of Surgery, Dentistry, Pediatric and Gynecology, University of Verona, 37126, Verona, Italy
| | - Silvia Urbani
- Section of Geriatric Medicine, Department of Surgery, Dentistry, Pediatric and Gynecology, University of Verona, 37126, Verona, Italy
| | - Elena Zoico
- Section of Geriatric Medicine, Department of Medicine, University of Verona, Verona, Italy
| | - Rocco Micciolo
- Centre for Medical Sciences, Department of Psychology and Cognitive Sciences, University of Trento, Trento, Italy
| | - Mauro Zamboni
- Section of Geriatric Medicine, Department of Surgery, Dentistry, Pediatric and Gynecology, University of Verona, 37126, Verona, Italy
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Amano S, Ohta R, Sano C. Relationship between Anemia and Readmission among Older Patients in Rural Community Hospitals: A Retrospective Cohort Study. J Clin Med 2024; 13:539. [PMID: 38256673 PMCID: PMC10816581 DOI: 10.3390/jcm13020539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/02/2024] [Accepted: 01/16/2024] [Indexed: 01/24/2024] Open
Abstract
Readmission rates among older adults are a growing concern, and the association of readmission with anemia and the potential benefits of a systematic assessment and intervention remain unclear. This study investigated the association between anemia and readmission within 28 and 90 days in an older population. Data from 1280 patients admitted to the Department of General Medicine of Unnan City Hospital between April 2020 and December 2021 were retrospectively analyzed. Variables such as anemia status, Charlson comorbidity index (CCI) score, Functional Independence Measure (FIM) score, and dependent status were evaluated. Multivariate logistic regression was used to determine the associations between 28-day and 90-day readmissions. The average age was 84.9 years, and the prevalence of anemia was 36.4%. The readmission rates within 28 and 90 days were 10.4% and 19.1%, respectively. Anemia was significantly associated with readmission in both periods (28-day adjusted odds ratio, 2.28; 90-day adjusted odds ratio, 1.65). CCI score, FIM score, and dependent status were also identified as significant factors. Anemia is significantly associated with short- and medium-term readmissions in older patients. Addressing anemia, along with other identified factors, may help reduce readmission rates.
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Affiliation(s)
- Shiho Amano
- Community Care, Unnan City Hospital, Daito-cho Iida, Unnan 699-1221, Japan;
- Department of Community Medicine Management, Faculty of Medicine, Shimane University, Enya-cho, Izumo 693-8501, Japan;
| | - Ryuichi Ohta
- Community Care, Unnan City Hospital, Daito-cho Iida, Unnan 699-1221, Japan;
| | - Chiaki Sano
- Department of Community Medicine Management, Faculty of Medicine, Shimane University, Enya-cho, Izumo 693-8501, Japan;
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Gao X, Alam S, Shi P, Dexter F, Kong N. Interpretable machine learning models for hospital readmission prediction: a two-step extracted regression tree approach. BMC Med Inform Decis Mak 2023; 23:104. [PMID: 37277767 DOI: 10.1186/s12911-023-02193-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 05/09/2023] [Indexed: 06/07/2023] Open
Abstract
BACKGROUND Advanced machine learning models have received wide attention in assisting medical decision making due to the greater accuracy they can achieve. However, their limited interpretability imposes barriers for practitioners to adopt them. Recent advancements in interpretable machine learning tools allow us to look inside the black box of advanced prediction methods to extract interpretable models while maintaining similar prediction accuracy, but few studies have investigated the specific hospital readmission prediction problem with this spirit. METHODS Our goal is to develop a machine-learning (ML) algorithm that can predict 30- and 90- day hospital readmissions as accurately as black box algorithms while providing medically interpretable insights into readmission risk factors. Leveraging a state-of-art interpretable ML model, we use a two-step Extracted Regression Tree approach to achieve this goal. In the first step, we train a black box prediction algorithm. In the second step, we extract a regression tree from the output of the black box algorithm that allows direct interpretation of medically relevant risk factors. We use data from a large teaching hospital in Asia to learn the ML model and verify our two-step approach. RESULTS The two-step method can obtain similar prediction performance as the best black box model, such as Neural Networks, measured by three metrics: accuracy, the Area Under the Curve (AUC) and the Area Under the Precision-Recall Curve (AUPRC), while maintaining interpretability. Further, to examine whether the prediction results match the known medical insights (i.e., the model is truly interpretable and produces reasonable results), we show that key readmission risk factors extracted by the two-step approach are consistent with those found in the medical literature. CONCLUSIONS The proposed two-step approach yields meaningful prediction results that are both accurate and interpretable. This study suggests a viable means to improve the trust of machine learning based models in clinical practice for predicting readmissions through the two-step approach.
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Affiliation(s)
- Xiaoquan Gao
- School of Industrial Engineering, Purdue University, West Lafayette, USA
| | - Sabriya Alam
- Department of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, USA
| | - Pengyi Shi
- Krannert School of Management, Purdue University, West Lafayette, USA.
| | | | - Nan Kong
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, USA
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Laura T, Melvin C, Yoong DY. Depressive symptoms and malnutrition are associated with other geriatric syndromes and increase risk for 30-Day readmission in hospitalized older adults: a prospective cohort study. BMC Geriatr 2022; 22:634. [PMID: 35918652 PMCID: PMC9344637 DOI: 10.1186/s12877-022-03343-6] [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: 12/18/2021] [Accepted: 07/27/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Readmission in older adults is typically complex with multiple contributing factors. We aim to examine how two prevalent and potentially modifiable geriatric conditions - depressive symptoms and malnutrition - relate to other geriatric syndromes and 30-day readmission in hospitalized older adults. METHODS Consecutive admissions of patients ≥ 65 years to a general medical department were recruited over 16 months. Patients were screened for depression, malnutrition, delirium, cognitive impairment, and frailty at admission. Medical records were reviewed for poor oral intake and functional decline during hospitalization. Unplanned readmission within 30-days of discharge was tracked through the hospital's electronic health records and follow-up telephone interviews. We use directed acyclic graphs (DAGs) to depict the relationship of depressive symptoms and malnutrition with geriatric syndromes that constitute covariates of interest and 30-day readmission outcome. Multiple logistic regression was performed for the independent associations of depressive symptoms and malnutrition with 30-day readmission, adjusting for variables based on DAG-identified minimal adjustment set. RESULTS We recruited 1619 consecutive admissions, with mean age 76.4 (7.9) years and 51.3% females. 30-day readmission occurred in 331 (22.0%) of 1,507 patients with follow-up data. Depressive symptoms, malnutrition, higher comorbidity burden, hospitalization in the one-year preceding index admission, frailty, delirium, as well as functional decline and poor oral intake during the index admission, were more commonly observed among patients who were readmitted within 30 days of discharge (P < 0.05). Patients with active depressive symptoms were significantly more likely to be frail (OR = 1.62, 95% CI 1.22-2.16), had poor oral intake (OR = 1.35, 95% CI 1.02-1.79) and functional decline during admission (OR = 1.58, 95% CI 1.11-2.23). Malnutrition at admission was significantly associated with frailty (OR = 1.53, 95% CI 1.07-2.19), delirium (OR = 2.33, 95% CI 1.60-3.39) cognitive impairment (OR = 1.88, 95% CI 1.39-2.54) and poor oral intake during hospitalization (OR = 2.70, 95% CI 2.01-3.64). In minimal adjustment set identified by DAG, depressive symptoms (OR = 1.38, 95% CI 1.02-1.86) remained significantly associated with 30-day readmission. The association of malnutrition with 30-day readmission was no longer statistically significant after adjusting for age, ethnicity and depressive symptoms in the minimal adjustment set (OR = 1.40, 95% CI 0.99-1.98). CONCLUSION The observed causal associations support screening and targeted interventions for depressive symptoms and malnutrition during admission and in the post-acute period.
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Affiliation(s)
- Tay Laura
- Department of General Medicine, Sengkang General Hospital, 110 Sengkang East Way, 544886, Singapore, Singapore. .,Geriatric Education and Research Institute, Singapore, Singapore.
| | - Chua Melvin
- Department of General Medicine, Sengkang General Hospital, 110 Sengkang East Way, 544886, Singapore, Singapore
| | - Ding Yew Yoong
- Geriatric Education and Research Institute, Singapore, Singapore.,Department of Geriatric Medicine, Tan Tock Seng Hospital, Singapore, Singapore
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Coatsworth-Puspoky R, Dahlke S, Duggleby W, Hunter KF. Older persons with multiple chronic conditions' experiences of unplanned readmission: An integrative review. Int J Older People Nurs 2022; 17:e12481. [PMID: 35621261 DOI: 10.1111/opn.12481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 03/01/2022] [Accepted: 04/26/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND As persons, 60 years of age and older live longer, they are more likely to develop one or more chronic conditions. Rising numbers of older persons with multiple chronic conditions (MCCs) will increase the need for home healthcare services and hospital services and unplanned readmissions will increase globally. AIM The aim of this integrative review was to explore the experiences of older persons with MCCs' unplanned readmission from home to hospital within 30 days of discharge using an integrative review. METHOD Whittemore and Knafl's method was followed to address the research aim. Four databases (Ovid MEDLINE, Scopus, CINAHL and Embase) were searched between 2005 and 2020, suitability for inclusion was assessed, and data were extracted and analysed using content analysis. RESULTS Thirteen articles (10 qualitative, one quantitative, and two mixed methods) were included in this review. Three themes emerged from the data that reflected older persons with MCCs' unplanned readmission experiences. These themes included (a) feelings of security, support and relief; (b) undesirable challenges at home (struggling to manage care and balancing support needs); and (c) unpleasant feelings and emotions (feelings of fear and mistrust, feelings of disappointment and loss, feelings of anxiousness and pressure). CONCLUSION Research about unplanned readmission to the hospital does not provide sufficient detail or understanding about older persons with MCCs' experiences or their psychosocial experiences. Addressing research gaps related to the psychosocial processes and factors associated with unplanned readmission is needed to expand the current understanding of the process and concept of unplanned readmission.
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Affiliation(s)
| | - Sherry Dahlke
- Faculty of Nursing, University of Alberta, Edmonton, Alberta, USA
| | - Wendy Duggleby
- Faculty of Nursing, University of Alberta, Edmonton, Alberta, USA
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El Abd A, Schwab C, Clementz A, Fernandez C, Hindlet P. Safety of Elderly Fallers: Identifying Associated Risk Factors for 30-Day Unplanned Readmissions Using a Clinical Data Warehouse. J Patient Saf 2022; 18:230-236. [PMID: 34419990 DOI: 10.1097/pts.0000000000000893] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Hospital readmissions are a major problem in the older people as they are frequent, costly, and life-threatening. Falls among older adults are the leading cause of injury, deaths, and emergency department visits for trauma. OBJECTIVE The main objective was to determine risk factors associated with a 30-day readmission after index hospital admission for fall-related injuries. METHODS A retrospective nested case-control study was conducted. Data from elderly patients initially hospitalized for fall-related injuries in 2019, in 11 of the Greater Paris University Hospitals and discharged home, were retrieved from the clinical data warehouse. Cases were admission of elderly patients who subsequently experienced a readmission within 30 days after discharge from the index admission. Controls were admission of elderly patients who were not readmitted to hospital. RESULTS Among 670 eligible index admissions, 127 (18.9%) were followed by readmission within 30 days after discharge. After multivariate analysis, men sex (odds ratio [OR] = 2.29, 95% confidence interval [CI] = 1.45-3.61), abnormal concentration of C-reactive protein, and anemia (OR = 2.22, 95% CI = 1.28-3.85; OR = 1.85, 95% CI = 1.11-3.11, respectively) were associated with a higher risk of readmission. Oppositely, having a traumatic injury at index admission decreased this risk (OR = 0.47, 95% CI = 0.28-0.81). CONCLUSIONS Reducing early unplanned readmission is crucial, especially in elderly patients susceptible to falls. Our results indicate that the probability of unplanned readmission is higher for patients with specific characteristics that should be taken into consideration in interventions designed to reduce this burden.
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Affiliation(s)
- Asmae El Abd
- From the GHU AP-HP.Sorbonne Université, Hôpital Saint Antoine, Service Pharmacie, Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris
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Zurek KI, Boswell CL, E. Miller N, L. Pecina J, D. Decker M, I. Wi C, Garrison GM. Association of Early and Late Hospital Readmissions with a Novel Housing-Based Socioeconomic Measure. Health Serv Res Manag Epidemiol 2022; 9:23333928221104644. [PMID: 35769114 PMCID: PMC9234927 DOI: 10.1177/23333928221104644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Background While socioeconomic status has been linked to hospital readmissions for several conditions, reliable measures of individual socioeconomic status are often not available. HOUSES, a new measure of individual socioeconomic status based upon objective public data about one's housing unit, is inversely associated with overall hospitalization rate but it has not been studied with respect to readmissions. Purpose To determine if patients in the lowest HOUSES quartile are more likely to be readmitted within 30 days (short-term) and 180 days (long-term). Methods A retrospective cohort study of 11 993 patients having 21 633 admissions was conducted using generalized linear mixed-effects models. Results HOUSES quartile did not show any significant association with early readmission. However, when compared to the lowest HOUSES quartile, the second quartile (OR = 0.90, 95%CI 0.83-0.98) and the third quartile (OR = 0.91, 95%CI 0.83-0.99) were associated with lower odds of late readmission while the highest quartile (OR = 0.91, 95%CI 0.82-1.01) was not statistically different. Conclusion HOUSES was associated with late readmission, but not early readmission. This may be because early readmissions are influenced by medical conditions and hospital care while late readmissions are influenced by ambulatory care and home-based factors. Since HOUSES relies on public county assessor data, it is generally available and may be used to focus interventions on those at highest risk for late readmission.
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Affiliation(s)
| | | | | | | | | | - Chung I. Wi
- Department of Pediatric and Adolescent Medicine, Precision
Population Science Lab, Mayo Clinic, Rochester, MN, USA
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Factors associated with early 14-day unplanned hospital readmission: a matched case-control study. BMC Health Serv Res 2021; 21:870. [PMID: 34433448 PMCID: PMC8390214 DOI: 10.1186/s12913-021-06902-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 08/17/2021] [Indexed: 11/17/2022] Open
Abstract
Background/Purpose Early unplanned hospital readmissions are burdensome health care events and indicate low care quality. Identifying at-risk patients enables timely intervention. This study identified predictors for 14-day unplanned readmission. Methods We conducted a retrospective, matched, case–control study between September 1, 2018, and August 31, 2019, in an 1193-bed university hospital. Adult patients aged ≥ 20 years and readmitted for the same or related diagnosis within 14 days of discharge after initial admission (index admission) were included as cases. Cases were 1:1 matched for the disease-related group at index admission, age, and discharge date to controls. Variables were extracted from the hospital’s electronic health records. Results In total, 300 cases and 300 controls were analyzed. Six factors were independently associated with unplanned readmission within 14 days: previous admissions within 6 months (OR = 3.09; 95 % CI = 1.79–5.34, p < 0.001), number of diagnoses in the past year (OR = 1.07; 95 % CI = 1.01–1.13, p = 0.019), Malnutrition Universal Screening Tool score (OR = 1.46; 95 % CI = 1.04–2.05, p = 0.03), systolic blood pressure (OR = 0.98; 95 % CI = 0.97–0.99, p = 0.01) and ear temperature within 24 h before discharge (OR = 2.49; 95 % CI = 1.34–4.64, p = 0.004), and discharge with a nasogastric tube (OR = 0.13; 95 % CI = 0.03–0.60, p = 0.009). Conclusions Factors presented at admission (frequent prior hospitalizations, multimorbidity, and malnutrition) along with factors presented at discharge (clinical instability and the absence of a nasogastric tube) were associated with increased risk of early 14-day unplanned readmission.
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Impact of COPD exacerbations leading to hospitalization on general and disease-specific quality of life. Respir Med 2021; 186:106526. [PMID: 34229290 DOI: 10.1016/j.rmed.2021.106526] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 06/22/2021] [Accepted: 06/27/2021] [Indexed: 01/01/2023]
Abstract
RATIONALE Acute exacerbations negatively impact quality of life in patients with chronic obstructive pulmonary disease (COPD), but the impact of hospitalized exacerbations on quality of life is not clear. We hypothesized that patients with hospitalized exacerbations would benefit from hospitalization and experience improvement in general and disease-specific quality of life (as measured by the St. George's respiratory questionnaire (SGRQ) and the medical outcomes study 36-item short form health survey (SF-36)) compared to those without exacerbations, or with non-hospitalized acute exacerbations. METHODS 1219 COPD patients enrolled in either the simvastatin for the prevention of exacerbations in moderate-to severe COPD Trial (STATCOPE) or azithromycin for prevention of exacerbations of COPD trial (MACRO) were analyzed. Demographic information, spirometry, and symptom scores were noted at baseline. Exacerbation events and changes in quality of life scores were assessed over a mean of 538 days of follow-up. RESULTS Of patients studied, 25.6% were hospitalized, 44.0% had at least one outpatient exacerbation, and 30.4% had no exacerbation. Baseline SGRQ and SF-36 scores were severely impaired in all groups studied. Over time, SF-36 scores did not change significantly between groups. SGRQ symptom domain scores improved in other groups but did not improve in those hospitalized for a COPD exacerbation. CONCLUSIONS At baseline, patients hospitalized for acute exacerbations of COPD had more impaired quality of life scores. Over time, SGRQ symptom domain scores improved in other groups but did not in those who were hospitalized. Other measurements of quality of life were not improved by hospitalization for COPD.
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Cho PG, Kim TH, Lee H, Ji GY, Park SH, Shin DA. Incidence, reasons, and risk factors for 30-day readmission after lumbar spine surgery for degenerative spinal disease. Sci Rep 2020; 10:12672. [PMID: 32728078 PMCID: PMC7391755 DOI: 10.1038/s41598-020-69732-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Accepted: 07/14/2020] [Indexed: 11/09/2022] Open
Abstract
This study investigated risk factors for 30-day readmission of discharged patients who had undergone lumbar spinal surgery. This retrospective, case–control study reviewed 3,933 patients discharged after elective spinal surgery for lumbar degenerative diseases from 2005 to 2012 at a university hospital. Of these patients, 102 were re-hospitalized within 30 days of discharge. Patient medical records were reviewed. The incidence of readmission within 30 days was 2.6%, and uncontrolled pain was the most common reason for readmission. In the univariate analysis, age, mental illness, the number of medical comorbidities, previous spinal surgery, fusion surgery, number of fusion levels, estimated blood loss, operation time, intensive care unit (ICU) admission, length of hospital stays, and total medical expenses were associated with a higher risk of readmission within 30 days. Multiple logistic regression analysis revealed that previous spinal surgery, operation time, ICU admission, length of hospital stays, and total medical expenses were independent risk factors for 30-day readmission. Independent risk factors for readmission were longer operation time, a previous spinal surgery, ICU admission, longer hospital stays, and higher medical expenses. Further studies controlling these risk factors could contribute to reducing readmission and thus improving the quality of care.
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Affiliation(s)
- Pyung Goo Cho
- Department of Neurosurgery, Ajou University College of Medicine, Suwon, Republic of Korea
| | - Tae Hyun Kim
- Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea
| | - Hana Lee
- Department of Neurosurgery, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea
| | - Gyu Yeul Ji
- Department of Neurosurgery, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea
| | - Sang Hyuk Park
- Department of Neurosurgery, Seoul Now Hospital, Seongnam, Republic of Korea
| | - Dong Ah Shin
- Department of Neurosurgery, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea.
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Abstract
Massachusetts has one of the highest rates of 30-day readmissions in the country. To identify patient-reported factors that may contribute to readmissions, we conducted semi-structured interviews with patients with unplanned readmissions within 30 days of inpatient discharge from the medicine services at an urban medical center between June and August 2016. Interviews with patients and/or proxies were conducted in English, Spanish, Mandarin, or Cantonese, then translated to English if necessary, transcribed verbatim, and deidentified. A team of four coders conducted the thematic analysis. Most patients did not identify factors associated with readmission beyond their underlying illness; however, a mismatch between the patient's clinical care needs and services available at postacute facilities, as well as poor communication between providers, facilities, and patients/proxies, were identified as contributing factors to readmissions. Non-English speaking patients and their families reported confusion with written discharge instructions, even if an interpreter provided verbal instructions. Patients will benefit from future interventions that aim to improve transfers to postacute care facilities, develop written materials in languages prevalent in the local population, and improve communication among providers, facilities, and patients and their families.
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Machine Learning Prediction of Postoperative Emergency Department Hospital Readmission. Anesthesiology 2020; 132:968-980. [DOI: 10.1097/aln.0000000000003140] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Abstract
Background
Although prediction of hospital readmissions has been studied in medical patients, it has received relatively little attention in surgical patient populations. Published predictors require information only available at the moment of discharge. The authors hypothesized that machine learning approaches can be leveraged to accurately predict readmissions in postoperative patients from the emergency department. Further, the authors hypothesize that these approaches can accurately predict the risk of readmission much sooner than hospital discharge.
Methods
Using a cohort of surgical patients at a tertiary care academic medical center, surgical, demographic, lab, medication, care team, and current procedural terminology data were extracted from the electronic health record. The primary outcome was whether there existed a future hospital readmission originating from the emergency department within 30 days of surgery. Secondarily, the time interval from surgery to the prediction was analyzed at 0, 12, 24, 36, 48, and 60 h. Different machine learning models for predicting the primary outcome were evaluated with respect to the area under the receiver-operator characteristic curve metric using different permutations of the available features.
Results
Surgical hospital admissions (N = 34,532) from April 2013 to December 2016 were included in the analysis. Surgical and demographic features led to moderate discrimination for prediction after discharge (area under the curve: 0.74 to 0.76), whereas medication, consulting team, and current procedural terminology features did not improve the discrimination. Lab features improved discrimination, with gradient-boosted trees attaining the best performance (area under the curve: 0.866, SD 0.006). This performance was sustained during temporal validation with 2017 to 2018 data (area under the curve: 0.85 to 0.88). Lastly, the discrimination of the predictions calculated 36 h after surgery (area under the curve: 0.88 to 0.89) nearly matched those from time of discharge.
Conclusions
A machine learning approach to predicting postoperative readmission can produce hospital-specific models for accurately predicting 30-day readmissions via the emergency department. Moreover, these predictions can be confidently calculated at 36 h after surgery without consideration of discharge-level data.
Editor’s Perspective
What We Already Know about This Topic
What This Article Tells Us That Is New
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Predictors of hospital readmission among older adults with cancer. J Geriatr Oncol 2020; 11:1108-1114. [PMID: 32222347 DOI: 10.1016/j.jgo.2020.03.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 01/01/2020] [Accepted: 03/19/2020] [Indexed: 02/08/2023]
Abstract
OBJECTIVE Older adults with cancer are at higher risk for costly and potentially dangerous hospital readmissions. Identifying risk factors for readmission in this population is important for future prevention of readmission. MATERIALS AND METHODS Hospital discharges among patients ≥ 65 years with solid tumors on non-surgical services from 2006-2011 were reviewed in this matched case-control study. We abstracted patient/cancer characteristics; functional status; fall risk; chemotherapy line; comorbidities; laboratory values; discharge parameters; and miscellaneous information (Do Not Resuscitate Order, pain scores) from medical records. Conditional logistic regression was used for univariate and multivariable analysis. RESULTS This analysis included 184 case-patients readmitted within 30 days after discharge from the index admission and 184 sex- and age-matched control-patients discharged from index admission within three months of the cases with no readmission. Cases and controls had no differences in terms of primary cancer type, treatment, and index admission reason. Cases were more likely to have abnormal hemoglobin, albumin, sodium, and SGOT on discharge. Compared to those with ≤1 abnormal laboratory test, patients with 2 or more abnormal test results were 3 times more likely to be readmitted within 30 days. CONCLUSION This study demonstrated that older adults with cancer who had at least 2 abnormal laboratory results (hemoglobin, albumin, sodium, and SGOT) at discharge were 3 times more likely to be readmitted within 30 days compared to those with ≤1 abnormal results. These laboratory values may be predictive of the risk of readmission, and should be monitored before discharge to potentially prevent readmission.
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Qi J, Liu C, Chen L, Chen J. Postoperative Serum Albumin Decrease Independently Predicts Delirium in the Elderly Subjects after Total Joint Arthroplasty. Curr Pharm Des 2020; 26:386-394. [PMID: 31880243 DOI: 10.2174/1381612826666191227153150] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 12/23/2019] [Indexed: 12/30/2022]
Abstract
Background:
Postoperative delirium (POD), a neurobehavioral syndrome induced by dysfunction of
neural activity, is a common and serious complication. This current study aimed to investigate independent predictors
for POD in elderly subjects after total joint arthroplasty (TJA).
Methods:
Eligible elderly patients (≥65 years) who underwent elective unilateral primary hip or knee arthroplasty
under epidural anesthesia from October 2016 to January 2019 were consecutively enrolled. POD was diagnosed
following the guidance of the 5th edition of Diagnostic and Statistical Manual of Mental Disorders, (DSM V,
2013). The relative change in serum Alb (ΔAlb) was defined as the absolute value of (preoperative Alb value–
nadir value within postoperative day 2)/preoperative Alb ×100%. The predictive value of ΔAlb for POD was
evaluated by receiver operating characteristic (ROC) curve analysis. Univariate and multivariate logistic regression
analyses were used for evaluating risk factors for POD.
Results:
A total of 328 patients were enrolled in the analysis, of which 68 (20.7%, 68/328) patients developed
POD within postoperative 7 days. ΔAlb was an effective predictor for POD with an area under the curve (AUC)
of 0.821, a sensitivity of 76.15% and a specificity of 70.59%, respectively (P<0.001). Univariate and multivariate
logistic regression analyses indicated that ΔAlb was the only independent risk factor for POD (OR: 2.43, 95%CI:
1.17–4.86, P=0.015).
Conclusions:
ΔAlb was an independent risk factor for POD in elderly subjects after TJA.
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Affiliation(s)
- Jianmin Qi
- Department of anesthesiology, HwaMei Hospital, University of Chinese Academy of Sciences, Beijing, China
| | - Cheng Liu
- Department of anesthesiology, HwaMei Hospital, University of Chinese Academy of Sciences, Beijing, China
| | - Li'an Chen
- Department of anesthesiology, HwaMei Hospital, University of Chinese Academy of Sciences, Beijing, China
| | - Junping Chen
- Department of anesthesiology, HwaMei Hospital, University of Chinese Academy of Sciences, Beijing, China
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Sumner K, Grandizio LC, Gehrman MD, Graham J, Klena JC. Incidence and Reason for Readmission and Unscheduled Health Care Contact After Distal Radius Fracture. Hand (N Y) 2020; 15:243-251. [PMID: 30052074 PMCID: PMC7076622 DOI: 10.1177/1558944718788687] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Understanding risk factors for readmission may help decrease the rate of these costly events. The purpose of this study is to define the incidence of 30-day readmission and unscheduled health care contact (UHC) after distal radius fracture (DRF). In addition, we aim to define risk factors for readmission and UHC. Methods: A retrospective review of patients who sustained a DRF at our trauma center was performed. We recorded baseline demographics, fracture characteristics, and treatment. Any UHC or readmission (including emergency department [ED] visits) was documented. Reasons for readmission and UHC were stratified by cause. We utilized a case-control design comparing patients readmitted within 30 days after DRF versus those who were not, as well as patients with and without UHC. Results: About 353 patients were identified. The 30-day incidence of readmission after DRF was 7% with 2% of patients readmitted for reasons related to their fracture. Twenty percent of patients had UHC within 30 days, most frequently due to pain. Patients with anxiety or depression and those with open fractures were more likely to be readmitted. Patients with UHC were younger, more likely to have depression or anxiety, and more likely to have undergone operative treatment. Conclusions: For patients sustaining DRF, we report a 30-day readmission rate of 7% with 20% of patients having UHC. Patients with depression or anxiety were more likely to be both readmitted and have UHC. Identifying risk factors for readmission during initial presentation may help reduce readmissions. Improving pain relief strategies early may aid in decreasing the burden of UHC.
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Affiliation(s)
- Kirsten Sumner
- Geisinger Medical Center, Danville, PA, USA,Kirsten Sumner, Department of Orthopaedic Surgery, 21-30, Geisinger Medical Center, 100 N Academy Avenue, Danville, PA 17822, USA.
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Beeler PE, Cheetham M, Held U, Battegay E. Depression is independently associated with increased length of stay and readmissions in multimorbid inpatients. Eur J Intern Med 2020; 73:59-66. [PMID: 31791574 DOI: 10.1016/j.ejim.2019.11.012] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 11/08/2019] [Accepted: 11/14/2019] [Indexed: 12/30/2022]
Abstract
BACKGROUND Little is known about the impact of depression across a broad range of multimorbid patients hospitalized for reasons other than depression. The objective of the study was to investigate in a large sample of multimorbid inpatients whether ancillary depression is associated with increased length of stay (LOS) and readmissions, two important clinical outcomes with implications for healthcare utilization and costs. METHODS We retrospectively analyzed a cohort of 253,009 multimorbid inpatients aged ≥18 at an academic medical center, 8/2009-8/2017. PRIMARY OUTCOME LOS. SECONDARY OUTCOMES LOS related to different main diagnoses, readmissions within 1, 3, 6, 12, and 24-months after discharge. RESULTS Multivariable linear regression showed 24% longer LOS in patients with ancillary depression (1.24; 95% confidence interval [CI]: 1.22, 1.25). Females stayed 22% longer (1.22; 95% CI: 1.20, 1.25), males 24% (1.24; 95% CI: 1.22, 1.27). We identified 16 main diagnosis clusters in which ancillary depression was associated with significant LOS increases, with associations being strongest for "Failure and rejection of transplanted organs and tissues", "Other noninfective gastroenteritis and colitis", and "Other soft tissue disorders, not elsewhere classified". Multivariable logistic and Poisson regression showed independent associations of ancillary depression with increased readmission odds and frequencies at 1, 3, 6, 12, and 24 months. CONCLUSIONS Ancillary depression was independently associated with increased LOS and more readmissions across a broad range of multimorbid inpatients.
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Affiliation(s)
- P E Beeler
- Department of Internal Medicine, University Hospital Zurich & University of Zurich, Zurich, Switzerland; University Research Priority Program "Dynamics of Healthy Aging", University Zurich, Zurich, Switzerland; Center of Competence Multimorbidity, University of Zurich, Zurich, Switzerland.
| | - M Cheetham
- Department of Internal Medicine, University Hospital Zurich & University of Zurich, Zurich, Switzerland; University Research Priority Program "Dynamics of Healthy Aging", University Zurich, Zurich, Switzerland.
| | - U Held
- Department of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Switzerland.
| | - E Battegay
- Department of Internal Medicine, University Hospital Zurich & University of Zurich, Zurich, Switzerland; University Research Priority Program "Dynamics of Healthy Aging", University Zurich, Zurich, Switzerland; Center of Competence Multimorbidity, University of Zurich, Zurich, Switzerland.
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Elbeddini A, Yang L, Aly A. A Case-Control Study: The Impact of Unintentional Discrepancies and Pharmacist Discharge Prescription Review on 30-Day Hospital Readmission. J Prim Care Community Health 2020; 11:2150132720932012. [PMID: 32486942 PMCID: PMC7270941 DOI: 10.1177/2150132720932012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Introduction: Medication discrepancies on hospital discharge are
common and occur despite the use of technology to generate electronically
created discharge (e-discharge) prescriptions, justifying pharmacist
involvement. No published studies have focused on medication discrepancies as a
risk factor for readmission. The aim was to explore the relationship between
medication discrepancies on discharge and readmission rates, and how both are
affected by pharmacist intervention. Objectives: The primary
objective was to establish the relationship between medication discrepancies on
the e-discharge prescription and hospital readmissions within 30 days of
discharge. Secondary objectives were to determine the 30-day readmission rate
with and without pharmacist involvement, and risk factors for 30-day
readmission. Methods: This was a matched case-control study where
cases and controls consisted of patients readmitted and not readmitted to
hospital within 30 days of discharge from the general medicine service,
respectively. Case patients were defined as patients who had been readmitted to
the hospital within 30 days of discharge from the general medicine unit. Control
patients were defined as patients who had not been readmitted to the hospital
within 30 days of discharge. Chi-square statistics was used to analyze the
association between the presence of medication discrepancy at discharge and
30-day readmission. Multivariate logistic regression was used to further analyze
the associations to determine which risk factors best relate to 30-day
readmission. Results: Between January 1, 2017 and December 31,
2017, a total of 401 e-discharge prescriptions were reviewed, and 194 cases were
readmitted within 30 days of discharge. Similar proportions of patients were
readmitted compared with not readmitted regardless of whether discrepancies were
identified on the e-discharge prescriptions, and there was no relationship
identified between medication discrepancies and readmission within 30 days (odds
ratio [OR] = 1.04; P = .854). The readmission rate with and
without pharmacist involvement was similar between the case group (50%) and
control group (48.0%). The proportion of discharge prescriptions with
discrepancies was 48.8% in the group that had pharmacist involvement and 47.0%
in the group that had no pharmacist involvement. Additionally, a LACE score of
12 or greater was identified as a statistically significant risk factor for
readmission (OR = 2.13; P < .001). Conclusions:
Pharmacist review of the e-discharge prescription did not affect the readmission
rate. A LACE score of 12 or greater was associated with a higher risk of
readmission. Future studies are needed to identify patient groups at high risk
of readmission and to determine pharmacist interventions that could reduce
readmission rates.
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Affiliation(s)
- Ali Elbeddini
- Winchester District Memorial Hospital (WDMH), Winchester, Ontario, Canada
| | - Lucy Yang
- Winchester District Memorial Hospital (WDMH), Winchester, Ontario, Canada
| | - Ahmed Aly
- Winchester District Memorial Hospital (WDMH), Winchester, Ontario, Canada
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Dharod A, Wells BJ, Lenoir K, Willeford WG, Milks MW, Atkinson HH. Holiday Discharges Are Associated with Higher 30-Day General Internal Medicine Hospital Readmissions at an Academic Medical Center. South Med J 2019; 112:338-343. [PMID: 31158889 DOI: 10.14423/smj.0000000000000989] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
OBJECTIVE Academic medical centers face unique challenges in educating physician trainees in effective discharge practices to prevent readmissions. Meanwhile, residents must handle high workloads coupled with frequent rotations to different services. This study aimed to determine whether daily service census, service turnover, time of discharge, and day of discharge increase the risk of 30-day readmission. METHODS All of the discharges from two academic general internal medicine teaching services between October 1, 2013 and September 30, 2014 were included in this observational data analysis. Variables were fit to a 30-day, all-cause readmission outcome using multiple logistic regression with inverse probability of treatment weighting and multiple imputations with chained equations. The following potential confounding variables were included in the model: health system utilization, demographics, laboratory values, and comorbidities. RESULTS Among 1935 total discharges, 258 patients (13.3%) were readmitted within 30 days of the index discharge. Turnover, service census, weekend discharge, and time of discharge were not significantly associated with the risk of readmission. Patients discharged during holiday periods had higher odds of readmission (odds ratio 2.56, 95% confidence interval 2.01-3.25), whereas patients discharged on an intern switch day had lower odds of readmission (odds ratio 0.33, 95% confidence interval 0.27-0.41). CONCLUSIONS Patients who are discharged during holiday periods are at a higher risk of readmission after adjusting for potential confounders. These results also suggest that discharge on an intern switch day had a protective effect on readmission. Further work is needed to examine whether these findings can be replicated, and, if confirmed, to determine to what extent these associations are causal.
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Affiliation(s)
- Ajay Dharod
- From the Department of Internal Medicine, Section on General Internal Medicine, the Department of Biostatistics and Data Science, and the Department of Internal Medicine, Internal Medicine Residency and Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, the Department of Internal Medicine, Section on Infectious Diseases, University of Alabama, Birmingham, and the Department of Internal Medicine, Division of Cardiovascular Medicine, Ohio State University College of Medicine, Columbus
| | - Brian J Wells
- From the Department of Internal Medicine, Section on General Internal Medicine, the Department of Biostatistics and Data Science, and the Department of Internal Medicine, Internal Medicine Residency and Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, the Department of Internal Medicine, Section on Infectious Diseases, University of Alabama, Birmingham, and the Department of Internal Medicine, Division of Cardiovascular Medicine, Ohio State University College of Medicine, Columbus
| | - Kristin Lenoir
- From the Department of Internal Medicine, Section on General Internal Medicine, the Department of Biostatistics and Data Science, and the Department of Internal Medicine, Internal Medicine Residency and Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, the Department of Internal Medicine, Section on Infectious Diseases, University of Alabama, Birmingham, and the Department of Internal Medicine, Division of Cardiovascular Medicine, Ohio State University College of Medicine, Columbus
| | - Wesley G Willeford
- From the Department of Internal Medicine, Section on General Internal Medicine, the Department of Biostatistics and Data Science, and the Department of Internal Medicine, Internal Medicine Residency and Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, the Department of Internal Medicine, Section on Infectious Diseases, University of Alabama, Birmingham, and the Department of Internal Medicine, Division of Cardiovascular Medicine, Ohio State University College of Medicine, Columbus
| | - Michael W Milks
- From the Department of Internal Medicine, Section on General Internal Medicine, the Department of Biostatistics and Data Science, and the Department of Internal Medicine, Internal Medicine Residency and Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, the Department of Internal Medicine, Section on Infectious Diseases, University of Alabama, Birmingham, and the Department of Internal Medicine, Division of Cardiovascular Medicine, Ohio State University College of Medicine, Columbus
| | - Hal H Atkinson
- From the Department of Internal Medicine, Section on General Internal Medicine, the Department of Biostatistics and Data Science, and the Department of Internal Medicine, Internal Medicine Residency and Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, the Department of Internal Medicine, Section on Infectious Diseases, University of Alabama, Birmingham, and the Department of Internal Medicine, Division of Cardiovascular Medicine, Ohio State University College of Medicine, Columbus
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Hemenway AN, Kandil MM, MacDowell M. The Association of Medication Knowledge and Adherence Scores With Hospital Readmission. Hosp Pharm 2019; 56:205-209. [PMID: 34381250 DOI: 10.1177/0018578719883808] [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: 11/17/2022]
Abstract
Introduction: Readmission scoring systems are used to predict 30-day hospital readmission. These prediction tools do not considerlack of patient medication knowledge or adherence which can worsen disease outcomes or increase risk of readmissions. Objective: To determine if medication knowledge and adherence, as assessed by validated questionnaires, are associated with an increased rate of 30-day readmission. Methods: Adult medical inpatients were randomly selected for a prospective, single center study that was conducted from January to August 2017. Patients were asked the 4-question Morisky Green Levine Scale (MGLS) and the 4-question Medication Knowledge Score (MKS). Validated readmission score; MKS; and MGLS, as well as baseline information and readmission status within 30 days after the index admission were recorded. Mean or median scores were compared for patients readmitted within 30 days with those not readmitted using descriptive and univariate inferential statistics. Results: Data from 119 patients showed a mean age of 63 years (SD = 16). There was no difference in baseline information: age, sex, or number of scheduled home medications between those readmitted within 30 days and those not readmitted. Patients readmitted within 30 days had a statistically higher readmission score compared to patients not readmitted (66.4 vs 57.1, P = .017). There was no difference in median MKS or mean MGLS between patients readmitted within 30 days and those not readmitted (MKS: 4.0 vs 3.0, P = .753; MGLS: 1 vs 1.3, P = .162). Conclusions: In this prospective study, neither the MKS nor the MGLS scores were associated with 30-day hospital readmission.
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Affiliation(s)
- Alice N Hemenway
- University of Illinois at Chicago - Rockford Health Sciences Campus, College of Pharmacy, Rockford, IL, USA
| | - Manar M Kandil
- University of Illinois at Chicago - Rockford Health Sciences Campus, College of Pharmacy, Rockford, IL, USA
| | - Martin MacDowell
- University of Illinois at Chicago, Colleges of Medicine and Pharmacy, Rockford, IL, USA
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Hamar GB, Coberley C, Pope JE, Cottrill A, Verrall S, Larkin S, Rula EY. Effect of post-hospital discharge telephonic intervention on hospital readmissions in a privately insured population in Australia. AUST HEALTH REV 2019; 42:241-247. [PMID: 28390471 DOI: 10.1071/ah16059] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Accepted: 02/02/2017] [Indexed: 11/23/2022]
Abstract
Objective The aim of the present study was to evaluate the effect of telephone support after hospital discharge to reduce early hospital readmission among members of the disease management program My Health Guardian (MHG) offered by the Hospitals Contribution Fund of Australia (HCF). Methods A quasi-experimental retrospective design compared 28-day readmissions of patients with chronic disease between two groups: (1) a treatment group, consisting of MHG program members who participated in a hospital discharge (HODI) call; and (2) a comparison group of non-participating MHG members. Study groups were matched for age, gender, length of stay, index admission diagnoses and prior MHG program exposure. Adjusted incidence rate ratios (IRR) and odds ratios (OR) were estimated using zero-inflated negative binomial and logistic regression models respectively. Results The treatment group exhibited a 29% lower incidence of 28-day readmissions than the comparison group (adjusted IRR 0.71; 95% confidence interval (CI) 0.59-0.86). The odds of treatment group members being readmitted at least once within 28 days of discharge were 25% lower than the odds for comparison members (adjusted OR 0.75; 95% CI 0.63-0.89). Reduction in readmission incidence was estimated to avoid A$713730 in cost. Conclusions The HODI program post-discharge telephonic support to patients recently discharged from a hospital effectively reduced the incidence and odds of hospital 28-day readmission in a diseased population. What is known about the topic? High readmission rates are a recognised problem in Australia and contribute to the over 600000 potentially preventable hospitalisations per year. What does this paper add? The present study is the first study of a scalable intervention delivered to an Australian population with a wide variety of conditions for the purpose of reducing readmissions. The intervention reduced 28-day readmission incidence by 29%. What are the implications for practitioners? The significant and sizable effect of the intervention support the delivery of telephonic support after hospital discharge as a scalable approach to reduce readmissions.
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Affiliation(s)
- G Brent Hamar
- Healthways Inc., 701 Cool Springs Boulevard, Franklin, TN 37067, USA
| | | | - James E Pope
- Healthways Inc., 701 Cool Springs Boulevard, Franklin, TN 37067, USA
| | - Andrew Cottrill
- Hospitals Contribution Fund of Australia (HCF), Level 6, 403 George Street, Sydney, NSW 2000, Australia.
| | - Scott Verrall
- Hospitals Contribution Fund of Australia (HCF), Level 6, 403 George Street, Sydney, NSW 2000, Australia.
| | - Shaun Larkin
- Hospitals Contribution Fund of Australia (HCF), Level 6, 403 George Street, Sydney, NSW 2000, Australia.
| | - Elizabeth Y Rula
- Tivity Health, 701 Cool Springs Boulevard, Franklin, TN 37067, USA. Email
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Rodriguez-Gutierrez R, Herrin J, Lipska KJ, Montori VM, Shah ND, McCoy RG. Racial and Ethnic Differences in 30-Day Hospital Readmissions Among US Adults With Diabetes. JAMA Netw Open 2019; 2:e1913249. [PMID: 31603490 PMCID: PMC6804020 DOI: 10.1001/jamanetworkopen.2019.13249] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
IMPORTANCE Differences in readmission rates among racial and ethnic minorities have been reported, but data among people with diabetes are lacking despite the high burden of diabetes and its complications in these populations. OBJECTIVES To examine racial/ethnic differences in all-cause readmission among US adults with diabetes and categorize patient- and system-level factors associated with these differences. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study includes 272 758 adult patients with diabetes, discharged alive from the hospital between January 1, 2009, and December 31, 2014, and stratified by race/ethnicity. An administrative claims data set of commercially insured and Medicare Advantage beneficiaries across the United States was used. Data analysis took place between October 2016 and February 2019. MAIN OUTCOMES AND MEASURES Unplanned all-cause readmission within 30 days of discharge and individual-, clinical-, economic-, index hospitalization-, and hospital-level risk factors for readmission. RESULTS A total of 467 324 index hospitalizations among 272 758 adults with diabetes (mean [SD] age, 67.7 [12.7]; 143 498 [52.6%] women) were examined. The rates of 30-day all-cause readmission were 10.2% (33 683 of 329 264) among white individuals, 12.2% (11 014 of 89 989) among black individuals, 10.9% (4151 of 38 137) among Hispanic individuals, and 9.9% (980 of 9934) among Asian individuals (P < .001). After adjustment for all factors, only black patients had a higher risk of readmission compared with white patients (odds ratio, 1.05; 95% CI, 1.02-1.08). This increased readmission risk among black patients was sequentially attenuated, but not entirely explained, by other demographic factors, comorbidities, income, reason for index hospitalization, or place of hospitalization. Compared with white patients, both black and Hispanic patients had the highest observed-to-expected (OE) readmission rate ratio when their income was low (annual household income <$40 000 among black patients: OE ratio, 1.11; 95% CI, 1.09-1.14; among Hispanic patients: OE ratio, 1.11; 95% CI, 1.07-1.16) and when they were hospitalized in nonprofit hospitals (black patients: OE ratio, 1.10; 95% CI, 1.08-1.12; among Hispanic patients: OE ratio, 1.08; 95% CI, 1.05-1.12), academic hospitals (black patients: OE ratio, 1.16; 95% CI, 1.13-1.20; Hispanic patients: OE ratio, 1.12; 95% CI, 1.06-1.19), or large hospitals (ie, with ≥400 beds; black patients: OE ratio, 1.11; 95% CI, 1.09-1.14; Hispanic patients: OE ratio, 1.09; 95% CI, 1.04-1.14). CONCLUSIONS AND RELEVANCE In this study, black patients with diabetes had a significantly higher risk of readmission than members of other racial/ethnic groups. This increased risk was most pronounced among lower-income patients hospitalized in nonprofit, academic, or large hospitals. These findings reinforce the importance of identifying and addressing the many reasons for persistent racial/ethnic differences in health care quality and outcomes.
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Affiliation(s)
- Rene Rodriguez-Gutierrez
- Division of Endocrinology, Hospital Universitario Dr José E. Gonzalez, Universidad Autónoma de Nuevo León, Monterrey, Nuevo León, Mexico
- Knowledge and Evaluation Research Unit in Endocrinology, Mayo Clinic, Rochester, Minnesota
- Plataforma INVEST Medicina Universidad Autónoma de Nuevo León–Knowledge and Evaluation Research Unit Mayo Clinic, Universidad Autónoma de Nuevo León, Monterrey, Nuevo León, Mexico
| | - Jeph Herrin
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Flying Buttress Associates, Charlottesville, Virginia
| | - Kasia J. Lipska
- Division of Endocrinology, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Victor M. Montori
- Knowledge and Evaluation Research Unit in Endocrinology, Mayo Clinic, Rochester, Minnesota
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Mayo Clinic, Rochester, Minnesota
| | - Nilay D. Shah
- Knowledge and Evaluation Research Unit in Endocrinology, Mayo Clinic, Rochester, Minnesota
- OptumLabs, Cambridge, Massachusetts
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota
| | - Rozalina G. McCoy
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota
- Division of Community Internal Medicine Department of Medicine, Mayo Clinic, Rochester, Minnesota
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Kirk J, Andersen O, Petersen J. Organizational transformation in health care: an activity theoretical analysis. J Health Organ Manag 2019; 33:547-562. [PMID: 31483210 PMCID: PMC7068732 DOI: 10.1108/jhom-10-2018-0284] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 01/23/2019] [Accepted: 02/18/2019] [Indexed: 11/17/2022]
Abstract
PURPOSE Older patients are at high risk of hospital readmission, which has led to an increasing number of screening and intervention programs. Knowledge on implementing screening tools for preventing readmissions in emergency department (ED), where the primary focus is often the present-day flow of patients, is scant. The purpose of this paper is to explore whether a new screening tool for predicting readmissions and functional decline in medical patients>65 years of age could be implemented and its influence on cross-continuum collaborations between the primary and secondary sectors. DESIGN/METHODOLOGY/APPROACH The study took place in an ED in Denmark, in collaboration with the surrounding municipalities. An evaluation workshop with nurses and leaders from the ED and the surrounding municipalities took place with the aim of investigating the organizational changes that occurred in daily practice after the implementation of the screening tool. The workshop was designed and analyzed using cultural historical activity theory (CHAT). FINDINGS The results showed that it was possible to develop collaboration between the two sectors during the test period. However, the screening tool created different transformations for the municipality employees and in the ED. The contradictions indicated that the screening tool did not mediate a general and sustained transformation in the cross-continuum collaboration. RESEARCH LIMITATIONS/IMPLICATIONS Screening tools are not objective, neutral or "acontexual" artifacts and must always be adapted to the local context and sectors. CHAT offers a perspective to understand the collective object when working with organizational transformations and implementation. PRACTICAL IMPLICATIONS The study have shown that screening tools are not objective, neutral or "acontexual" artifacts and must always be adapted to the local context. This is called adaption process. This adaption requires time and resources that should be taken into consideration from the beginning of introduction of new screens. ORIGINALITY/VALUE This paper contributes with knowledge about CHAT which offers a way to understand the leading collective object when working with organizational transformations and implementation. CHAT focuses not only on the structural changes but also on the cultural aspects of organizational changes, which is important if we want to reach a sustained change and implement the new screening tool in different sectors.
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Affiliation(s)
- Jeanette Kirk
- The Emergency Department, Clinical Research Centre, Amager and Hvidovre Hospital, University of Copenhagen , Hvidovre, Denmark
| | - Ove Andersen
- The Emergency Department, Clinical Research Centre, Amager and Hvidovre Hospital, University of Copenhagen , Hvidovre, Denmark
| | - Janne Petersen
- Department of Public Health, University of Copenhagen , Copehagen, Denmark
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90-day Readmission in Elective Primary Lumbar Spine Surgery in the Inpatient Setting: A Nationwide Readmissions Database Sample Analysis. Spine (Phila Pa 1976) 2019; 44:E857-E864. [PMID: 30817732 DOI: 10.1097/brs.0000000000002995] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
STUDY DESIGN Secondary analysis of a large administrative database. OBJECTIVE The objectives of this study are to: 1) identify the incidence and cause of 90-day readmissions following primary elective lumbar spine surgery, 2) offer insight into potential risk factors that contribute to these readmissions, and 3) quantify the cost associated with these readmissions. SUMMARY OF BACKGROUND DATA As bundled-payment models for the reimbursement of surgical services become more popular in spine, the focus is shifting toward long-term patient outcomes in the context of 90-day episodes of care. With limited data available on national 90-day readmission statistics available, we hope to provide evidence that will aid in the development of more cost-effective perioperative care models. METHODS Using ICD-9 coding, we identified all patients 18 years of age and older in the 2014 Nationwide Readmissions Database (NRD) who underwent an elective, inpatient, primary lumbar spine surgery. Using multivariate logistic regression, we identified independent predictors of 90-day readmission while controlling for a multitude of confounding variables and completed a comparative cost analysis. RESULTS We identified 169,788 patients who underwent a primary lumbar spine procedure. In total 4268 (2.5%) were readmitted within 90 days. There was no difference in comorbidity burden between cohorts (readmitted vs. not readmitted) as quantified by the Elixhauser Comorbidity index. Independent predictors of increased odds of 90-day readmission were: anemia, uncomplicated diabetes and diabetes with chronic complications, surgical wound disruption and acute myocardial infarction at the time of the index admission, self-pay status, and an anterior surgical approach. Implant complications were identified as the primary related cause of readmission. These readmissions were associated with a significant cost increase. CONCLUSION There are clearly identifiable risk factors that increase the odds of hospital readmission within 90 days of primary lumbar spine surgery. An overall 90-day readmission rate of 2.5%, while relatively low, carries significantly increased cost to both the patient and hospital. LEVEL OF EVIDENCE 3.
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Physical Therapist Determination of Discharge Disposition in the Acute Care Setting. JOURNAL OF ACUTE CARE PHYSICAL THERAPY 2019. [DOI: 10.1097/jat.0000000000000099] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Impact of Pharmacist-Driven Heart Failure in-Home Counseling on 30-Day Readmission Rates. Prof Case Manag 2019; 24:194-200. [PMID: 31145238 DOI: 10.1097/ncm.0000000000000332] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE/OBJECTIVE This study examines the impact of a pharmacist-driven intervention specific to heart failure patients with the goal of reducing readmission rates and improving quality of life in this population. FINDINGS/CONCLUSIONS A total of 21 patients were included in the study. Twelve patients were female and 9 were male. The mean age was 76 years with a range of 65-93 years. Two of the 21 patients were readmitted within 30 days. One of the 2 readmitted patients died soon after admission was in the final stages of his or her disease and passed away soon after; it is unlikely for a home visit to have altered their path. This study did not meet the goal sample size due to some unforeseen limitations. However, the limited data that were obtained suggest a strong basis for further research. IMPLICATIONS FOR CASE MANAGEMENT PRACTICE During a patient's transition in care from hospital to home, he or she is most vulnerable for complications and readmission. Intervention during this time will not only improve patient care and quality of life but also contribute to a notable cost savings for each prevented readmission. Pharmacist intervention, as part of the health care team, during this tenuous time has shown to make a valuable impact.
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Garrison GM, Keuseman RL, Boswell CL, Horn JL, Nielsen NT, Nielsen ML. Family Medicine Patients Have Shorter Length of Stay When Cared for on a Family Medicine Inpatient Service. J Prim Care Community Health 2019; 10:2150132719840517. [PMID: 31027438 PMCID: PMC6487748 DOI: 10.1177/2150132719840517] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Introduction: Hospitalists have been shown to have shorter lengths of stays than physicians with concurrent outpatient practices. However, hospitalists at academic medical centers may be less aware of local resources that can support the hospital to home transition for local primary care patients. We hypothesized that local family medicine patients admitted to a family medicine inpatient service have shorter length of stay than those admitted to general hospitalist services which also care for tertiary patients at an academic medical center. Methods: A retrospective cohort study was conducted at an academic medical center with a department of family medicine providing primary care to over 80 000 local patients. A total of 3100 consecutive family medicine patients admitted to either the family medicine inpatient service or a general medicine inpatient service over 3 years were studied. The primary outcome was length of stay, which was adjusted using multivariate linear regression for demographics, prior utilization, diagnosis, and disease severity. Results: Adjusted length of stay was 33% longer (95% CI 24%-44%) for local family medicine patients admitted to general medicine inpatient services as compared with the family medicine inpatient service. Readmission rates within 30 days were not different (19% vs 16%, P = .14). Conclusions: Local primary care patients were safely discharged from the hospital sooner on the family medicine inpatient service than on general medicine inpatient services. This is likely because the family physicians staffing their inpatient service are more familiar with outpatient resources that can be effectively marshaled to help local patients with the transition from hospital to home.
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Schwarz CM, Hoffmann M, Schwarz P, Kamolz LP, Brunner G, Sendlhofer G. A systematic literature review and narrative synthesis on the risks of medical discharge letters for patients' safety. BMC Health Serv Res 2019; 19:158. [PMID: 30866908 PMCID: PMC6417275 DOI: 10.1186/s12913-019-3989-1] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 03/06/2019] [Indexed: 11/30/2022] Open
Abstract
Background The medical discharge letter is an important communication tool between hospitals and other healthcare providers. Despite its high status, it often does not meet the desired requirements in everyday clinical practice. Occurring risks create barriers for patients and doctors. This present review summarizes risks of the medical discharge letter. Methods The research question was answered with a systematic literature research and results were summarized narratively. A literature search in the databases PubMed and Cochrane Library for Studies between January 2008 and May 2018 was performed. Two authors reviewed the full texts of potentially relevant studies to determine eligibility for inclusion. Literature on possible risks associated with the medical discharge letter was discussed. Results In total, 29 studies were included in this review. The major identified risk factors are the delayed sending of the discharge letter to doctors for further treatments, unintelligible (not patient-centered) medical discharge letters, low quality of the discharge letter, and lack of information as well as absence of training in writing medical discharge letters during medical education. Conclusions Multiple risks factors are associated with the medical discharge letter. There is a need for further research to improve the quality of the medical discharge letter to minimize risks and increase patients’ safety.
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Affiliation(s)
- Christine Maria Schwarz
- Research Unit for Safety in Health, c/o Division of Plastic, Aesthetic and Reconstructive Surgery, Department of Surgery, Medical University of Graz, Graz, Austria
| | - Magdalena Hoffmann
- Research Unit for Safety in Health, c/o Division of Plastic, Aesthetic and Reconstructive Surgery, Department of Surgery, Medical University of Graz, Graz, Austria. .,Executive Department for Quality and Risk Management, University Hospital Graz, Auenbruggerplatz 1/3, 8036, Graz, Austria.
| | - Petra Schwarz
- Carinthia University of Applied Science, Feldkirchen, Austria
| | - Lars-Peter Kamolz
- Research Unit for Safety in Health, c/o Division of Plastic, Aesthetic and Reconstructive Surgery, Department of Surgery, Medical University of Graz, Graz, Austria
| | - Gernot Brunner
- Research Unit for Safety in Health, c/o Division of Plastic, Aesthetic and Reconstructive Surgery, Department of Surgery, Medical University of Graz, Graz, Austria
| | - Gerald Sendlhofer
- Research Unit for Safety in Health, c/o Division of Plastic, Aesthetic and Reconstructive Surgery, Department of Surgery, Medical University of Graz, Graz, Austria.,Executive Department for Quality and Risk Management, University Hospital Graz, Auenbruggerplatz 1/3, 8036, Graz, Austria
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Self-Identified Social Determinants of Health during Transitions of Care in the Medically Underserved: a Narrative Review. J Gen Intern Med 2018; 33:1959-1967. [PMID: 30128789 PMCID: PMC6206338 DOI: 10.1007/s11606-018-4615-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 06/15/2018] [Accepted: 07/23/2018] [Indexed: 10/28/2022]
Abstract
BACKGROUND Medically underserved or low socioeconomic status (SES) patients face significant vulnerability and a high risk of adverse events following hospital discharge. The environmental, social, and economic factors, otherwise known as social determinants, that compound this risk have been ineffectually described in this population. As the underserved comprise 30% of patients discharged from the hospital, improving transitional care and preventing readmission in this group has profound quality of care and financial implications. METHOD EMBASE and MEDLINE searches were conducted to examine specific barriers to care transitions in underserved patients following an episode of acute care. Articles were reviewed for barriers and categorized within the context of five general themes. RESULTS This review yielded 17 peer-reviewed articles. Common factors affecting care transitions were cost of medications, access to care, housing instability, and transportation. When categorized within themes, social fragility and access failures, as well as therapeutic misalignment, disease behavior, and issues with accountability were noted. DISCUSSION Providers and health systems caring for medically underserved patients may benefit through dedicating increased resources and broadening collaboration with community partners in order to expand health care access and enhance coordination of social services within this population. Future studies are needed to identify potential interventions targeting underserved patients to improve their post-hospital care.
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Artetxe A, Beristain A, Graña M. Predictive models for hospital readmission risk: A systematic review of methods. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2018; 164:49-64. [PMID: 30195431 DOI: 10.1016/j.cmpb.2018.06.006] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Revised: 05/03/2018] [Accepted: 06/05/2018] [Indexed: 06/08/2023]
Abstract
OBJECTIVES Hospital readmission risk prediction facilitates the identification of patients potentially at high risk so that resources can be used more efficiently in terms of cost-benefit. In this context, several models for readmission risk prediction have been proposed in recent years. The goal of this review is to give an overview of prediction models for hospital readmission, describe the data analysis methods and algorithms used for building the models, and synthesize their results. METHODS Studies that reported the predictive performance of a model for hospital readmission risk were included. We defined the scope of the review and accordingly built a search query to select the candidate papers. This query string was used as input for the chosen search engines, namely PubMed and Google Scholar. For each study, we recorded the population, feature selection method, classification algorithm, sample size, readmission threshold, readmission rate and predictive performance of the model. RESULTS We identified 77 studies that met the inclusion criteria, out of 265 citations. In 68% of the studies (n = 52) logistic regression or other regression techniques were utilized as the main method. Ten (13%) studies used survival analysis for model construction, while 14 (18%) used machine learning techniques for classification, of which decision tree-based methods and SVM were the most utilized algorithms. Among these, only four studies reported the use of any class imbalance addressing technique, of which resampling is the most frequent (75%). The performance of the models varied significantly among studies, with Area Under the ROC Curve (AUC) values in the ranges between 0.54 and 0.92. CONCLUSION Logistic regression and survival analysis have been traditionally the most widely used techniques for model building. Nevertheless, machine learning techniques are becoming increasingly popular in recent years. Recent comparative studies suggest that machine learning techniques can improve prediction ability over traditional statistical approaches. Regardless, the lack of an appropriate benchmark dataset of hospital readmissions makes a comparison of models' performance across different studies difficult.
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Affiliation(s)
- Arkaitz Artetxe
- Vicomtech-IK4 Research Centre, Mikeletegi Pasealekua 57, 20009 San Sebastian, Spain.
| | - Andoni Beristain
- Vicomtech-IK4 Research Centre, Mikeletegi Pasealekua 57, 20009 San Sebastian, Spain
| | - Manuel Graña
- Computation Intelligence Group, Basque University (UPV/EHU) P. Manuel Lardizabal 1, 20018 San Sebastian, Spain
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Lamanna C. A Storytelling Approach: Insights from the Shambaa. THE JOURNAL OF MEDICAL HUMANITIES 2018; 39:377-389. [PMID: 29552699 DOI: 10.1007/s10912-018-9512-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Narrative medicine explores the stories that patients tell; this paper, conversely, looks at some of the stories that patients are told. The paper starts by examining the 'story' told by the Shambaa people of Tanzania to explain the bubonic plague and contrasts this with the stories told by Ghanaian communities to explain lymphatic filariasis. By harnessing insights from memory studies, these stories' memorability is claimed to be due to their use mnemonic devices woven into stories. The paper suggests that stories can be unpatronising, informative, and appropriate vehicles for communicating medical information to all age groups across all cultures.
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Alokozai A, Bernstein DN, Sheikholeslami N, Uhler L, Ring D, Kamal RN. Impact of Health Literacy on Time Spent Seeking Hand Care. Hand (N Y) 2018; 13:538-546. [PMID: 28513193 PMCID: PMC6109906 DOI: 10.1177/1558944717708027] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Patients with limited health literacy may have less knowledge and fewer resources for efficient access and navigation of the health care system. We tested the null hypothesis that there is no correlation between health literacy and total time spent seeking hand surgery care. METHODS New patients visiting a hand surgery clinic at a suburban academic medical center were asked to complete a questionnaire to determine demographics, total time spent seeking hand surgery care, and outcomes. A total of 112 patients were included in this study. RESULTS We found health literacy levels did not correlate with total time seeking hand surgery care or from booking an appointment to being evaluated in clinic. CONCLUSIONS In this suburban academic medical center, patients with low health literacy do not spend more time seeking hand surgery care and do have longer delays between seeking and receiving care. The finding that-at least in this setting-health literacy does not impact patient time seeking hand care suggests that resources to improve health disparities can be focused elsewhere in the care continuum.
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Affiliation(s)
| | | | | | | | | | - Robin N. Kamal
- Stanford University, Redwood City, CA,
USA,Robin N. Kamal, Department of Orthopaedic
Surgery, Stanford University, 450 Broadway Street, Pavilion C, 440, Redwood
City, CA 94063, USA.
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Hughes LD, Witham MD. Causes and correlates of 30 day and 180 day readmission following discharge from a Medicine for the Elderly Rehabilitation unit. BMC Geriatr 2018; 18:197. [PMID: 30153802 PMCID: PMC6114496 DOI: 10.1186/s12877-018-0883-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 08/15/2018] [Indexed: 12/16/2022] Open
Abstract
Background Recently hospitalized patients experience a period of generalized risk of adverse health events. This study examined reasons for, and predictors of, readmission to acute care facilities within 30 and 180 days of discharge from an inpatient rehabilitation unit for older people. Methods Routinely collected, linked clinical data on admissions to a single inpatient rehabilitation facility over a 13-year period were analysed. Data were available regarding demographics, comorbid disease, admission and discharge Barthel scores, length of hospital stay, and number of medications on discharge. Discharge diagnoses for the index admission and readmissions were available from hospital episode statistics. Univariate and multivariate Cox regression analyses were performed to identify baseline factors that predicted 30 and 180-day readmission. Results A total of 3984 patients were included in the analysis. The cohort had a mean age of 84.1 years (SD 7.4), and 39.7% were male. Overall, 5.6% (n = 222) and 23.2% (n = 926) of the patients were readmitted within 30 days and 180 days of discharge respectively. For patients readmitted to hospital, 26.6% and 21.1% of patients were readmitted with the same condition as their initial admission at 30 days and 180 respectively. For patients readmitted within 30 days, 13.5% (n = 30) were readmitted with the same condition with the most common diagnoses associated with readmission being chest infection, falls/immobility and stroke. For patients readmitted within 180 days, 12.4% (n = 115) of patients were readmitted with the same condition as the index condition with the most common diagnoses associated with readmission being falls/immobility, cancer and chest infections. In multivariable Cox regression analyses, older age, male sex, length of stay and heart failure predicted 30 or 180-day readmission. In addition, discharge from hospital to patients own home predicted 30-day readmission, whereas diagnoses of cancer, previous myocardial infarction or chronic obstructive pulmonary disease predicted 180-day readmission. Conclusion Most readmissions of older people after discharge from inpatient rehabilitation occurred for different reasons to the original hospital admission. Patterns of predictors for early and late readmission differed, suggesting the need for different mitigation strategies.
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Affiliation(s)
- Lloyd D Hughes
- GP Registrar, Primary Care Directorate, NHS Education for Scotland, Edinburgh, UK
| | - Miles D Witham
- Ageing and Health, University of Dundee, Ninewells Hospital, Dundee, UK.
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Jurado C, Calmels V, Lobinet E, Divol E, Hanaire H, Metsu D, Sallerin B. The Electronic Pharmaceutical Record: A new method for medication reconciliation. J Eval Clin Pract 2018; 24:681-687. [PMID: 29761596 DOI: 10.1111/jep.12942] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 04/15/2018] [Accepted: 04/16/2018] [Indexed: 01/17/2023]
Abstract
RATIONALE, AIM, AND OBJECTIVE There are several ways to establish an accurate medication list in the hospital admission medication reconciliation (MedRec). The challenge for MedRec lies in the availability, reliability, and completeness of the data used. In France, the Electronic Pharmaceutical Record (ePR) was developed to register each medication taken by ambulatory patients, primarily to make dispensation in community pharmacies safe. We evaluated the suitability of this tool in the MedRec when patients were admitted to the hospital. METHOD We conducted a 6-month pilot study of 249 MedRec files from a hospital diabetology department. The analysis was supplemented by the ePR for any patient for whom this information was recorded. The study evaluated the ePR as a new MedRec tool, as well as the clinical impact (CI) of the new data collected. RESULTS The ePR was contributory for 28% of the patients. Discrepancies were associated with polypharmacy, most of which had a CI = 1. Medication omission was the most frequently found discrepancy (72%), but self-medication (8%) and lack of medication adherence (9%) were also observed. CONCLUSION This tool provided added value for reconciliation, as it quickly identifies regular medications, adherence, and self-medication behaviour. The ePR is essential for conducting a thorough MedRec.
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Affiliation(s)
- Camille Jurado
- Department of Pharmacy, Hôpital Rangueil, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Violaine Calmels
- Department of Pharmacy, Hôpital Rangueil, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Emilie Lobinet
- Department of Endocrinology, Hôpital Larrey, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Elodie Divol
- Department of Pharmacy, Hôpital Rangueil, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Hélène Hanaire
- Department of Diabetology, Metabolic Diseases, and Nutrition, Hôpital Rangueil, Centre Hospitalier Universitaire de Toulouse, Toulouse, France.,Department of Medicine, University Toulouse III, Paul Sabatier, Toulouse, France
| | - David Metsu
- Department of Pharmacokinetics and Toxicology, Institut Fédératif de Biologie, Centre Hospitalier Universitaire de Toulouse, Toulouse, France.,INTHERES, INRA, ENVT, Université de Toulouse, France
| | - Brigitte Sallerin
- Department of Pharmacy, Hôpital Rangueil, Centre Hospitalier Universitaire de Toulouse, Toulouse, France.,I2MC, Team 6: Cardiac Remodeling and New Therapies, National Institute of Health and Medical, INSERM, Toulouse, France.,Department of Pharmacy, University Toulouse III, Paul Sabatier, Toulouse, France
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Abstract
Hospital readmissions are common and result in increased mortality and cost while reducing quality of life. Readmission rates have been subjected to increasing scrutiny in recent years as part of a larger effort to improve the quality and value of healthcare in the United States. Emerging evidence suggests that sepsis survivors are at high risk for hospital readmission and experience readmission rates comparable to survivors of congestive heart failure, acute myocardial infarction, pneumonia, and chronic obstructive pulmonary disease, diseases whose readmission rates determine reimbursement penalties from the federal government. In this article, we review the unique challenges that sepsis survivors face as well as the patient-level and hospital-level risk factors that are known to be associated with hospital readmission after sepsis survival. Additionally, we identify the causes and outcomes of readmissions in this population before concluding with a discussion of readmission prevention strategies and future directions.
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Émond M, Boucher V, Carmichael PH, Voyer P, Pelletier M, Gouin É, Daoust R, Berthelot S, Lamontagne ME, Morin M, Lemire S, Minh Vu TT, Nadeau A, Rheault M, Juneau L, Le Sage N, Lee J. Incidence of delirium in the Canadian emergency department and its consequences on hospital length of stay: a prospective observational multicentre cohort study. BMJ Open 2018; 8:e018190. [PMID: 29523559 PMCID: PMC5855334 DOI: 10.1136/bmjopen-2017-018190] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVE We aim to determine the incidence of delirium and describe its impacts on hospital length of stay (LOS) among non-delirious community-dwelling older adults with an 8-hour exposure to the emergency department (ED) environment. DESIGN This is a prospective observational multicentre cohort study (March-July 2015). Patients were assessed two times per day during their entire ED stay and up to 24 hours on hospital ward. SETTING The study took place in four Canadian EDs. PARTICIPANTS 338 included patients: (1) aged ≥65 years; (2) who had an ED stay ≥8 hours; (3) were admitted to hospital ward and (4) were independent/semi-independent. MAIN OUTCOMES AND MEASURES The primary outcomes of this study were incident delirium in the ED or within 24 hours of ward admission and ED and hospital LOS. Functional and cognitive status were assessed using validated Older Americans Resources and Services and the modified Telephone Interview for Cognitive Status tools. The Confusion Assessment Method was used to detect incident delirium. Univariate and multivariate analyses were conducted to evaluate outcomes. RESULTS Mean age was 76.8 (±8.1), 17.7% were aged >85 years old and 48.8% were men. The mean incidence of delirium was 12.1% (n=41). Median IQR ED LOS was 32.4 (24.5-47.9) hours and hospital LOS was 146.6 (75.2-267.8) hours. Adjusted mean hospital LOS was increased by 105.4 hours (4.4 days) (95% CI 25.1 to 162.0, P<0.001) for patients who developed an episode of delirium compared with non-delirious patient. CONCLUSIONS An incident delirium was observed in one of eight independent/semi-independent older adults after an 8-hour ED exposure. An episode of delirium increases hospital LOS by 4 days and therefore has important implications for patients and could contribute to ED overcrowding through a deleterious feedback loop.
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Affiliation(s)
- Marcel Émond
- Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec-Université Laval, Québec, Canada
- Département de médecine d’urgence, CHU de Québec-Université Laval, Québec, Canada
- Medicine, Université Laval, Québec, Canada
- Centre d’excellence sur le vieillissement de Québec, Québec, Canada
- Centre de recherche sur les soins et les services de première ligne de l’Université Laval, Québec, Canada
| | - Valérie Boucher
- Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec-Université Laval, Québec, Canada
- Medicine, Université Laval, Québec, Canada
- Centre d’excellence sur le vieillissement de Québec, Québec, Canada
- Centre interdisciplinaire de recherche en réadaptation et intégration sociale, Québec, Canada
| | | | - Philippe Voyer
- Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec-Université Laval, Québec, Canada
- Centre d’excellence sur le vieillissement de Québec, Québec, Canada
- Nursing, Université Laval, Québec, Canada
| | - Mathieu Pelletier
- Medicine, Université Laval, Québec, Canada
- Centre Intégré de Santé et de Services Sociaux de Lanaudière, Joliette, Canada
| | - Émilie Gouin
- Centre Hospitalier Régional de Trois-Rivières, Trois-Rivières, Canada
| | - Raoul Daoust
- Centre de recherche de l’Hôpital du Sacré-Cœur de Montréal, Montréal, Canada
- Medicine, Université de Montréal, Montréal, Canada
| | - Simon Berthelot
- Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec-Université Laval, Québec, Canada
- Département de médecine d’urgence, CHU de Québec-Université Laval, Québec, Canada
- Medicine, Université Laval, Québec, Canada
| | - Marie-Eve Lamontagne
- Medicine, Université Laval, Québec, Canada
- Centre interdisciplinaire de recherche en réadaptation et intégration sociale, Québec, Canada
| | - Michèle Morin
- Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec-Université Laval, Québec, Canada
- Medicine, Université Laval, Québec, Canada
| | - Stéphane Lemire
- Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec-Université Laval, Québec, Canada
- Medicine, Université Laval, Québec, Canada
- Centre d’excellence sur le vieillissement de Québec, Québec, Canada
| | - Thien Tuong Minh Vu
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montréal, Canada
- Centre hospitalier de l’Université de Montréal, Montréal, Canada
- Institut de gériatrie de l’Université de Montréal, Montréal, Canada
| | - Alexandra Nadeau
- Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec-Université Laval, Québec, Canada
- Medicine, Université Laval, Québec, Canada
- Centre d’excellence sur le vieillissement de Québec, Québec, Canada
- Centre interdisciplinaire de recherche en réadaptation et intégration sociale, Québec, Canada
| | | | - Lucille Juneau
- Centre Intégré Universitaire de Services Sociaux et de Santé de la Capitale-Nationale, Québec, Canada
| | - Natalie Le Sage
- Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec-Université Laval, Québec, Canada
- Département de médecine d’urgence, CHU de Québec-Université Laval, Québec, Canada
- Medicine, Université Laval, Québec, Canada
| | - Jacques Lee
- Department of Family and Community Medicine, University of Toronto, Toronto, Canada
- Sunnybrook Health Sciences Center, Toronto, Canada
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Harhay MN, Jia Y, Thiessen-Philbrook H, Besharatian B, Gumber R, Weng FL, Hall IE, Doshi M, Schroppel B, Parikh CR, Reese PP. The association of discharge decisions after deceased donor kidney transplantation with the risk of early readmission: Results from the deceased donor study. Clin Transplant 2018; 32:e13215. [PMID: 29393541 DOI: 10.1111/ctr.13215] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/20/2018] [Indexed: 01/12/2023]
Abstract
BACKGROUND Kidney transplant (KT) recipients experience high rates of early (≤30 days) hospital readmission (EHR) after KT, and existing studies provide limited data on modifiable discharge factors that may mitigate EHR risk. METHODS We performed a retrospective cohort study of 468 adult deceased donor KT recipients transplanted between 4/2010 and 11/2013 at 5 United States transplant centers. We fit multivariable mixed effects models to assess the association of two potentially modifiable discharge factors with the probability of EHR after KT: (i) weekend discharge and (ii) days to first scheduled follow-up. RESULTS Among 468 KT recipients, 38% (n = 178) experienced EHR after KT. In fully adjusted analyses, compared to weekday discharges, KT recipients discharged on the weekend had a 29% lower risk of EHR (adjusted odds ratio [aOR] 0.71, 95% confidence interval [CI] 0.41-0.94). Compared to follow-up within 2 days of discharge, KT recipients with follow-up within 3 to 6 days had a 28% higher probability of EHR (aOR 1.28, 95% CI 1.13-1.45). CONCLUSIONS These findings suggest that clinical decisions related to the timing of discharge and follow-up modify EHR risk after KT, independent of traditional risk factors.
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Affiliation(s)
- Meera Nair Harhay
- Division of Nephrology & Hypertension, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Yaqi Jia
- Yale University, New Haven, CT, USA
| | | | - Behdad Besharatian
- Division of Nephrology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ramnika Gumber
- Division of Nephrology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Francis L Weng
- Robert Wood Johnson Barnabas Health, Livingston, NJ, USA
| | | | - Mona Doshi
- Wayne State University, Detroit, MI, USA
| | | | | | - Peter P Reese
- Division of Nephrology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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Schwab C, Korb-Savoldelli V, Escudie JB, Fernandez C, Durieux P, Saint-Jean O, Sabatier B. Iatrogenic risk factors associated with hospital readmission of elderly patients: A matched case-control study using a clinical data warehouse. J Clin Pharm Ther 2018; 43:393-400. [PMID: 29446115 DOI: 10.1111/jcpt.12670] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Accepted: 01/09/2018] [Indexed: 12/29/2022]
Abstract
WHAT IS KNOWN Hospital readmission within 30 days of patient discharge has become a standard to judge the quality of hospitalizations. It is estimated that 14% of the elderly, people over 75 years old or those over 65 with comorbidities, are at risk of readmission, of which 23% are avoidable. It may be possible to identify elderly patients at risk of readmission and implement steps to reduce avoidable readmissions. OBJECTIVE The aim of this study was to identify iatrogenic risk factors for readmission. The secondary objective was to evaluate the rate of drug-related readmissions (DRRs) among all readmissions and compare it to the rate of readmissions for other reasons. METHODS We conducted a retrospective, matched, case-control study to identify non-demographic risk factors for avoidable readmission, specifically DRRs. The study included patients hospitalized between 1 September 2014 and 31 October 2015 in an 800-bed university hospital. We included patients aged 75 and over. Cases consisted of patients readmitted to the emergency department within 30 days of initial discharge. Controls did not return to the emergency department within 30 days. Cases and controls were matched on sex and age because they are known as readmissions risk factors. After comparison of the mean or percentage between cases and controls for each variable, we conducted a conditional logistic regression. RESULTS The risk factors identified were an emergency admission at the index hospitalization, returning home after discharge, a history of unplanned readmissions and prescription of nervous system drugs. Otherwise, 11.4% of the readmissions were DRRs, of which 30% were caused by an overdose of antihypertensive. The number of drugs at readmission was higher, and potentially inappropriate medications were more widely prescribed for DRRs than for readmissions for other reasons. WHAT IS NEW AND CONCLUSION In this matched case-control retrospective study, after controlling for gender and age, we identified the typical profile of elderly patients at risk of readmission. These patients had an unplanned admission at the index hospitalization and prescribed nervous system drugs at discharge from the index admission; they have a history of unplanned readmission within 30 days and return home after discharge.
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Affiliation(s)
- C Schwab
- INSERM UMR 1138, Equipe 22, Centre de Recherche des Cordeliers, Universités Paris, Paris, France.,Service Pharmacie, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - V Korb-Savoldelli
- Service Pharmacie, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.,Université Paris-Sud, Faculté de Pharmacie, Châtenay-Malabry, France
| | - J B Escudie
- INSERM UMR 1138, Equipe 22, Centre de Recherche des Cordeliers, Universités Paris, Paris, France.,Département de Santé Publique et Informatique Médicale, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - C Fernandez
- Université Paris-Sud, Faculté de Pharmacie, Châtenay-Malabry, France.,Service de Pharmacie, Hôpital Saint-Antoine, Assistance Publique - Hôpitaux de Paris, Paris, France.,Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis D'Epidémiologie et de Santé Publique, Paris, France
| | - P Durieux
- INSERM UMR 1138, Equipe 22, Centre de Recherche des Cordeliers, Universités Paris, Paris, France.,Département de Santé Publique et Informatique Médicale, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - O Saint-Jean
- Faculté de Médecine, Université Paris-Descartes, Paris, France.,Service de Gériatrie, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - B Sabatier
- INSERM UMR 1138, Equipe 22, Centre de Recherche des Cordeliers, Universités Paris, Paris, France.,Service Pharmacie, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
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Borkenhagen LS, McCoy RG, Havyer RD, Peterson SM, Naessens JM, Takahashi PY. Symptoms Reported by Frail Elderly Adults Independently Predict 30-Day Hospital Readmission or Emergency Department Care. J Am Geriatr Soc 2017; 66:321-326. [PMID: 29231962 DOI: 10.1111/jgs.15221] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
OBJECTIVES To assess the degree to which self-reported symptoms predict unplanned readmission or emergency department (ED) care within 30 days of high-risk, elderly adults enrolled in a posthospitalization care transition program (CTP). DESIGN Retrospective cohort study. SETTING Posthospitalization CTP at Mayo Clinic, Rochester, Minnesota, from January 1, 2013, through March 3, 2015. PARTICIPANTS Frail, elderly adults (N = 230; mean age 83.5 ± 8.3, 46.5% male). MEASUREMENTS Charlson Comorbidity Index (CCI) and self-reported symptoms, measured using the Edmonton Symptom Assessment System (ESAS), were ascertained upon CTP enrollment. RESULTS Mean CCI was 3.9 ± 2.3. Of 51 participants returning to the hospital within 30 days of discharge, 13 had ED visits, and 38 were readmitted. Age, sex, and CCI were not significantly different between returning and nonreturning participants, but returning participants were significantly more likely to report shortness of breath (P = .004), anxiety (P = .02), depression (P = .02), and drowsiness (P = .01). Overall ESAS score was also a significant predictor of hospital return (P = .01). CONCLUSION Four self-reported symptoms and overall ESAS score, but not CCI, ascertained after hospital discharge were strong predictors of hospital return within 30 days. Including symptoms in risk stratification of high-risk elderly adults may help target interventions and reduce readmissions.
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Affiliation(s)
- Lynn S Borkenhagen
- Division of Primary Care Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Rozalina G McCoy
- Division of Primary Care Internal Medicine, Mayo Clinic, Rochester, Minnesota.,Division of Health Care Policy & Research, Mayo Clinic, Rochester, Minnesota
| | - Rachel D Havyer
- Division of Primary Care Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Stephanie M Peterson
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - James M Naessens
- Division of Health Care Policy & Research, Mayo Clinic, Rochester, Minnesota
| | - Paul Y Takahashi
- Division of Primary Care Internal Medicine, Mayo Clinic, Rochester, Minnesota
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Labrada M, Mintzer MJ, Karanam C, Castellanos R, Cruz L, Hoang M, Wieger R, Aguilar E, Florez H, Ruiz JG. Dramatic Reduction in 30-Day Readmissions Through High-Risk Screening and Two-Phase Interdisciplinary Care. South Med J 2017; 110:757-760. [PMID: 29197308 DOI: 10.14423/smj.0000000000000745] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
OBJECTIVES Thirty-day readmissions are common, serious, and costly. Most important, often they are preventable. The purpose of this quality improvement study was to evaluate an interdisciplinary, two-phase intervention to reduce 30-day readmissions among high-risk medical patients. One or two high-risk patients were selected each weekday by a hospitalist using literature-based, locally tested criteria that included common medical illnesses, active psychiatric illness, and recent or recurrent hospital admissions. METHODS Patients admitted to 1 of 5 medical hospitalist teams were selected to receive the intervention; patients admitted to the 4 remaining teams were used for comparison. The two-phase care coordination intervention consisted of a daily interdisciplinary team meeting for the selected high-risk patients and postdischarge interventions that included outpatient care coordination until the patients' first follow-up appointment. The care plan addressed medical/geriatric assessment, social stability, medication reconciliation, nutritional needs, care coordination including future appointments/testing, and community services. Eighty-five patients in the intervention group were compared with 84 patients from the comparison group using propensity score matching. Patient characteristics were similar at baseline. RESULTS The intervention group demonstrated a reduction in 30-day readmissions by 52% (11 vs 23, P = 0.019). Length of stay was reduced: 5.5 days compared with 7.2 days (P = 0.258). CONCLUSIONS This intervention produced a significant reduction in 30-day readmissions for high-risk patients and a trend for shorter lengths of stay compared with similarly matched patients. Future research trials are needed to verify these results.
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Affiliation(s)
- Mabel Labrada
- From the Miami GRECC and MiamiVeterans Affairs Healthcare System, Miami, and the University of Miami Miller School of Medicine, Miami, Florida
| | - Michael J Mintzer
- From the Miami GRECC and MiamiVeterans Affairs Healthcare System, Miami, and the University of Miami Miller School of Medicine, Miami, Florida
| | - Chandana Karanam
- From the Miami GRECC and MiamiVeterans Affairs Healthcare System, Miami, and the University of Miami Miller School of Medicine, Miami, Florida
| | - Raquel Castellanos
- From the Miami GRECC and MiamiVeterans Affairs Healthcare System, Miami, and the University of Miami Miller School of Medicine, Miami, Florida
| | - Lorinda Cruz
- From the Miami GRECC and MiamiVeterans Affairs Healthcare System, Miami, and the University of Miami Miller School of Medicine, Miami, Florida
| | - Minh Hoang
- From the Miami GRECC and MiamiVeterans Affairs Healthcare System, Miami, and the University of Miami Miller School of Medicine, Miami, Florida
| | - Regina Wieger
- From the Miami GRECC and MiamiVeterans Affairs Healthcare System, Miami, and the University of Miami Miller School of Medicine, Miami, Florida
| | - Enrique Aguilar
- From the Miami GRECC and MiamiVeterans Affairs Healthcare System, Miami, and the University of Miami Miller School of Medicine, Miami, Florida
| | - Hermes Florez
- From the Miami GRECC and MiamiVeterans Affairs Healthcare System, Miami, and the University of Miami Miller School of Medicine, Miami, Florida
| | - Jorge G Ruiz
- From the Miami GRECC and MiamiVeterans Affairs Healthcare System, Miami, and the University of Miami Miller School of Medicine, Miami, Florida
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90-day Readmission After Lumbar Spinal Fusion Surgery in New York State Between 2005 and 2014: A 10-year Analysis of a Statewide Cohort. Spine (Phila Pa 1976) 2017; 42:1706-1716. [PMID: 28441307 DOI: 10.1097/brs.0000000000002208] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
UNLABELLED MINI: We assessed 90-day readmission and evaluated risk factors associated with readmission after lumbar spinal fusion surgery in New York State. The overall 90-day readmission rate was 24.8%. Age, sex, race, insurance, procedure, number of operated spinal levels, health service area, and comorbidities are major risk factors for 90-day readmission. STUDY DESIGN Retrospective cohort study. OBJECTIVE The aim of this study was to assess 90-day readmission and evaluate risk factors associated with readmission after lumbar fusion in New York State. SUMMARY OF BACKGROUND DATA Readmission is becoming an important metric for quality and efficiency of health care. Readmission and its predictors following spine surgery are overall poorly understood and limited evidence is available specifically in lumbar fusion. METHODS The New York Statewide Planning and Research Cooperative System (SPARCS) was utilized to capture patients undergoing lumbar fusion from 2005 to 2014. Temporal trend of 90-day readmission was assessed using Cochran-Armitage test. Logistic regression was used to examine predictors associated with 90-day readmission. RESULTS There were 86,869 patients included in this cohort study. The overall 90-day readmission rate was 24.8%. On a multivariable analysis model, age (odds ratio [OR] comparing ≥75 versus <35 years: 1.24, 95% confidence interval [CI]: 1.13-1.35), sex (OR female to male: 1.19, 95% CI: 1.15-1.23), race (OR African-American to white: 1.60, 95% CI: 1.52-1.69), insurance (OR Medicaid to Medicare: 1.42, 95% CI: 1.33-1.53), procedure (OR comparing thoracolumbar fusion, combined [International Classification of Disease, Ninth Revision, ICD-9: 81.04] to posterior lumbar interbody fusion/transforaminal lumbar spinal fusion [ICD-9: 81.08]: 2.10, 95% CI: 1.49-2.97), number of operated spinal levels (OR comparing four to eight vertebrae to two to three vertebrae: 2.39, 95% CI: 2.07-2.77), health service area ([HSA]; OR comparing Finger Lakes to New York-Pennsylvania border: 0.67, 95% CI: 0.61-0.73), and comorbidity, i.e., coronary artery disease (OR: 1.26, 95% CI: 1.19-1.33) were significantly associated with 90-day readmission. Directions of the odds ratios for these factors were consistent after stratification by procedure type. CONCLUSION Age, sex, race, insurance, procedure, number of operated spinal levels, HSA, and comorbidities are major risk factors for 90-day readmission. Our study allows risk calculation to determine high-risk patients before undergoing spinal fusion surgery to prevent early readmission, improve quality of care, and reduce health care expenditures. LEVEL OF EVIDENCE 3.
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Purtle SW, Horkan CM, Moromizato T, Gibbons FK, Christopher KB. Nucleated red blood cells, critical illness survivors and postdischarge outcomes: a cohort study. CRITICAL CARE : THE OFFICIAL JOURNAL OF THE CRITICAL CARE FORUM 2017. [PMID: 28633658 PMCID: PMC5479031 DOI: 10.1186/s13054-017-1724-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background Little is known about risk factors associated with out-of-hospital outcomes in survivors of critical illness. We hypothesized that the presence of nucleated red blood cells in patients who survived critical care would be associated with adverse outcomes following hospital discharge. Methods We performed a two-center observational cohort study of patients treated in medical and surgical intensive care units in Boston, Massachusetts. All data were obtained from the Research Patient Data Registry at Partners HealthCare. We studied 2878 patients, age ≥ 18 years, who received critical care between 2011 and 2015 and survived hospitalization. The exposure of interest was nucleated red blood cells occurring from 2 days prior to 7 days after critical care initiation. The primary outcome was mortality in the 90 days following hospital discharge. Secondary outcome was unplanned 30-day hospital readmission. Adjusted odds ratios were estimated by multivariable logistic regression models with inclusion of covariate terms thought to plausibly interact with both nucleated red blood cells and outcome. Adjustment included age, race (white versus nonwhite), gender, Deyo–Charlson Index, patient type (medical versus surgical), sepsis and acute organ failure. Results In patients who received critical care and survived hospitalization, the absolute risk of 90-day postdischarge mortality was 5.9%, 11.7%, 15.8% and 21.9% in patients with 0/μl, 1–100/μl, 101–200/μl and more than 200/μl nucleated red blood cells respectively. Nucleated red blood cells were a robust predictor of postdischarge mortality and remained so following multivariable adjustment. The fully adjusted odds of 90-day postdischarge mortality in patients with 1–100/μl, 101–200/μl and more than 200/μl nucleated red blood cells were 1.77 (95% CI, 1.23–2.54), 2.51 (95% CI, 1.36–4.62) and 3.72 (95% CI, 2.16–6.39) respectively, relative to patients without nucleated red blood cells. Further, the presence of nucleated red blood cells is a significant predictor of the odds of unplanned 30-day hospital readmission. Conclusion In critically ill patients who survive hospitalization, the presence of nucleated red blood cells is a robust predictor of postdischarge mortality and unplanned hospital readmission. Electronic supplementary material The online version of this article (doi:10.1186/s13054-017-1724-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Steven W Purtle
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado, Boulder, CO, USA
| | - Clare M Horkan
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Takuhiro Moromizato
- Renal and Rheumatology Division, Internal Medicine Department, Okinawa Southern Medical Center and Children's Hospital, Haebaru, Okinawa, Japan
| | - Fiona K Gibbons
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Kenneth B Christopher
- The Nathan E. Hellman Memorial Laboratory, Renal Division, Channing Division of Network Medicine, Brigham and Women's Hospital, MRB 418, 75 Francis Street, Boston, MA, 02115, USA.
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The Relationship Between Index Hospitalizations, Sepsis, and Death or Transition to Hospice Care During 30-Day Hospital Readmissions. Med Care 2017; 55:362-370. [PMID: 27820595 DOI: 10.1097/mlr.0000000000000669] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Hospital readmissions are common, expensive, and increasingly used as a metric for assessing quality of care. The relationship between index hospitalizations and specific outcomes among those readmitted remains largely unknown. OBJECTIVES Identify risk factors present during the index hospitalization associated with death or transition to hospice care during 30-day readmissions and examine the contribution of infection in readmissions resulting in death. RESEARCH DESIGN Retrospective cohort study. SUBJECTS A total of 17,716 30-day readmissions in an academic health system. MEASURES We used mixed-effects multivariable logistic regression models to identify risk factors associated with the primary outcome, in-hospital death, or transition to hospice during 30-day readmissions. RESULTS Of 17,716 30-day readmissions, 1144 readmissions resulted in death or transition to hospice care (6.5%). Risk factors identified included: age, burden, and type of comorbid conditions, recent hospitalizations, nonelective index admission type, outside hospital transfer, low discharge hemoglobin, low discharge sodium, high discharge red blood cell distribution width, and disposition to a setting other than home. Sepsis (OR=1.33; 95% CI, 1.02-1.72; P=0.03) and shock (OR=1.78; 95% CI, 1.22-2.58; P=0.002) during the index admission were associated with the primary outcome, and in-hospital mortality specifically. In patients who died, infection was the primary cause for readmission in 51.6% of readmissions after sepsis and 28.6% of readmissions after a nonsepsis hospitalization (P=0.009). CONCLUSIONS We identified factors, including sepsis and shock during the index hospitalization, associated with death or transition to hospice care during readmission. Infection was frequently implicated as the cause of a readmission that ended in death.
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Menendez ME, van Hoorn BT, Mackert M, Donovan EE, Chen NC, Ring D. Patients With Limited Health Literacy Ask Fewer Questions During Office Visits With Hand Surgeons. Clin Orthop Relat Res 2017; 475:1291-1297. [PMID: 27796802 PMCID: PMC5384911 DOI: 10.1007/s11999-016-5140-5] [Citation(s) in RCA: 90] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 10/21/2016] [Indexed: 02/06/2023]
Abstract
BACKGROUND In the midst of rapid expansion of medical knowledge and decision-support tools intended to benefit diverse patients, patients with limited health literacy (the ability to obtain, process, and understand information and services to make health decisions) will benefit from asking questions and engaging actively in their own care. But little is known regarding the relationship between health literacy and question-asking behavior during outpatient office visits. QUESTIONS/PURPOSES (1) Do patients with lower levels of health literacy ask fewer questions in general, and as stratified by types of questions? (2) What other patient characteristics are associated with the number of questions asked? (3) How often do surgeons prompt patients to ask questions during an office visit? METHODS We audio-recorded office visits of 84 patients visiting one of three orthopaedic hand surgeons for the first time. Patient questions were counted and coded using an adaptation of the Roter Interaction Analysis System in 11 categories: (1) therapeutic regimen; (2) medical condition; (3) lifestyle; (4) requests for services or medications; (5) psychosocial/feelings; (6) nonmedical/procedural; (7) asks for understanding; (8) asks for reassurance; (9) paraphrase/checks for understanding; (10) bid for repetition; and (11) personal remarks/social conversation. Directly after the visit, patients completed the Newest Vital Sign (NVS) health literacy test, a sociodemographic survey (including age, sex, race, work status, marital status, insurance status), and three Patient-Reported Outcomes Measurement Information System-based questionnaires: Upper-Extremity Function, Pain Interference, and Depression. The NVS scores were divided into limited (0-3) and adequate (4-6) health literacy as done by the tool's creators. We also assessed whether the surgeons prompted patients to ask questions during the encounter. RESULTS Patients with limited health literacy asked fewer questions than patients with adequate health literacy (5 ± 4 versus 9 ± 7; mean difference, -4; 95% CI, -7 to -1; p = 0.002). More specifically, patients with limited health literacy asked fewer questions regarding medical-care issues such as their therapeutic regimen (1 ± 2 versus 3 ± 4; mean difference, -2; 95% CI, -4 to -1]; p < 0.001) and condition (2 ± 2 versus 3 ± 3; mean difference, -1; 95% CI, -3 to 0; p = 0.022). Nonwhite patients asked fewer questions than did white patients (5 ± 4 versus 9 ± 7; mean difference, -4; 95% CI, -7 to 0; p = 0.032). No other patient characteristics were associated with the number of questions asked. Surgeons only occasionally (29%; 24/84) asked patients if they had questions during the encounter, but when they did, most patients (79%; 19/24) asked questions. CONCLUSIONS Limited health literacy is a barrier to effective patient engagement in hand surgery care. In the increasingly tangled health-information environment, it is important to actively involve patients with limited health literacy in the decision-making process by encouraging question-asking, particularly in practice settings where most decisions are preference-sensitive. Instead of assuming that patients understand what they are told, orthopaedic surgeons may take "universal precautions" by assuming that patients do not understand unless proved otherwise. LEVEL OF EVIDENCE Level II, therapeutic study.
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Affiliation(s)
- Mariano E. Menendez
- Department of Orthopaedic Surgery, Tufts Medical Center, Tufts University School of Medicine, 800 Washington Street, TMC Box #306, Boston, MA 02111 USA ,Department of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - Bastiaan T. van Hoorn
- Department of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - Michael Mackert
- Center for Health Communication, Moody College of Communication, The University of Texas at Austin, Austin, TX USA
| | - Erin E. Donovan
- Center for Health Communication, Moody College of Communication, The University of Texas at Austin, Austin, TX USA
| | - Neal C. Chen
- Department of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - David Ring
- Department of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA ,Department of Surgery and Perioperative Care, Dell Medical School at the University of Texas at Austin, Austin, TX USA
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Cheen MHH, Goon CP, Ong WC, Lim PS, Wan CN, Leong MY, Khee GY. Evaluation of a care transition program with pharmacist-provided home-based medication review for elderly Singaporeans at high risk of readmissions. Int J Qual Health Care 2017; 29:200-205. [PMID: 28453819 DOI: 10.1093/intqhc/mzw150] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 12/07/2016] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE This study aimed to determine whether pharmacist-provided home-based medication review (HBMR) can reduce readmissions in the elderly. DESIGN Retrospective cohort study. SETTING Patient's home. PARTICIPANTS Records of patients referred to a care transition program from March 2011 through March 2015 were reviewed. Patients aged 60 years and older taking more than 5 medications and had at least 2 unplanned admissions within 3 months preceding the first home visit were included. INTERVENTION Pharmacist-provided HBMR. MAIN OUTCOME MEASURES Primary outcome was readmission rate over 6 months after the first home visit. Secondary outcomes included emergency department (ED) visits, outpatient visits and mortality. Drug-related problems (DRPs) were reported for the HBMR group. Multivariate incidence rate ratios (IRR) and hazard ratio (HR) were calculated with adjustments for covariates. RESULTS The study included 499 patients (97 HBMR, 402 no HBMR). Pharmacist-provided HBMR reduced readmissions by 26% (IRR = 0.74, 95% CI: 0.59-0.92, P = 0.007), reduced ED visits by 20% (IRR = 0.80, 95% CI: 0.66-0.98, P = 0.030) and increased outpatient visits by 16% (IRR = 1.16, 95% CI: 0.95-1.41, P = 0.150). There were 8 and 44 deaths in the HBMR and no HBMR groups respectively (HR = 0.73, 95% CI: 0.29-1.81, P = 0.492). Pharmacists identified 464 DRPs, with 169 (36.4%) resolved within 1 month after the home visit. CONCLUSIONS The study suggests that pharmacist-provided HBMR is effective in reducing readmissions and ED visits in the elderly. More studies in the Asian population are needed to determine its long term benefits and patient's acceptability.
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Affiliation(s)
- McVin Hua Heng Cheen
- Department of Pharmacy, Singapore General Hospital, Singapore
- Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore
| | - Chong Ping Goon
- Department of Pharmacy, Singapore General Hospital, Singapore
| | - Wan Chee Ong
- Department of Pharmacy, Singapore General Hospital, Singapore
| | - Paik Shia Lim
- Department of Pharmacy, Singapore General Hospital, Singapore
| | - Choon Nam Wan
- Department of Pharmacy, Singapore General Hospital, Singapore
| | - Mei Yan Leong
- Agency for Integrated Care, Nursing Division, Singapore General Hospital, Singapore
| | - Giat Yeng Khee
- Department of Pharmacy, Singapore General Hospital, Singapore
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Deschepper M, Vermeir P, Vogelaers D, Devulder J, Eeckloo K. Is pain at discharge a risk factor for unplanned hospital readmission? Acta Clin Belg 2017; 72:95-102. [PMID: 28229625 DOI: 10.1080/17843286.2017.1293311] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
INTRODUCTION Unplanned readmissions are associated with a high cost to health insurances and the incidence of preventable readmissions could be considered as a quality indicator for the initial hospital admission. We aimed to assess the predictive value for unplanned readmission of higher pain scores at discharge of the initial admission as well as of other pain and demographic characteristics. The documentation of significant associations would provide further support for a structured pain management policy. METHODS A retrospective analysis of a large single university hospital data-set of 33.122 admissions within a 13-month period allowed for the assessment of the predictive relationship of pain toward unplanned readmission at 7 and at 30 days after discharge through logistic regression, and of other characteristics through linear regression. RESULTS Pain scores at discharge of the initial admission were not significantly different (p > 0.05) with or without unplanned readmission and hence have no predictive value on the individual patient level. The prediction of the number of patients for each group, for example the number of patients that will be readmitted (size of the group), shows significance for pain at the moment of discharge (p_initial = 0.000), pain medication (p = 0.0044), and age (p = 0.0017). Pathology (p = 0.6151) and gender (p = 0.7029) have no significant predictive value. CONCLUSION Pain as dichotomous variable upon discharge cannot be used as single risk predictor for unplanned readmission. However, the pain score at discharge in combination with the use of pain medication and age is a risk factor for the number of short-term unplanned readmissions.
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Affiliation(s)
- Mieke Deschepper
- Ghent University Hospital, (Strategic) Policy Cell, Ghent, Belgium
| | - Peter Vermeir
- Department of General Internal Medicine, Ghent University Hospital, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Internal Medicine, Ghent University, Ghent, Belgium
| | - Dirk Vogelaers
- Department of General Internal Medicine, Ghent University Hospital, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Internal Medicine, Ghent University, Ghent, Belgium
| | - Jacques Devulder
- Ghent University Hospital, Centre Multidisciplinary Pain, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Anaesthesiology and Perioperative Medicine, Ghent University, Ghent, Belgium
| | - Kristof Eeckloo
- Ghent University Hospital, (Strategic) Policy Cell, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Public Health, Ghent University, Ghent, Belgium
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Nazemi AK, Gowd AK, Carmouche JJ, Kates SL, Albert TJ, Behrend CJ. Prevention and Management of Postoperative Delirium in Elderly Patients Following Elective Spinal Surgery. Clin Spine Surg 2017; 30:112-119. [PMID: 28141603 DOI: 10.1097/bsd.0000000000000467] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
STUDY DESIGN This study is a systematic review. OBJECTIVE Propose an evidence-based algorithm for prevention, diagnosis, and management of postoperative delirium in geriatric patients undergoing elective spine surgery. SUMMARY OF BACKGROUND DATA Delirium is associated with longer stays after elective surgery, increased risk of readmission, and $6.9 billion annually in medical costs. Early diagnosis and treatment of delirium can reduce length of stay (LOS), in-hospital morbidity, and health care costs. After spinal surgery, postoperative delirium increases average LOS to >7 days and is diagnosed in 12.5%-24.3% of geriatric patients. Currently, studies for management of postoperative delirium after elective spinal procedures are not available. METHODS A literature review was performed for observational studies, randomized controlled trials, and systematic reviews between 1990 and 2015. RESULTS Risk factors for delirium after elective spinal surgery include age, functional impairment, preexisting dementia, general anesthesia, surgical duration >3 hours, intraoperative hypercapnia and hypotension, greater blood loss, low hematocrit and albumin, preoperative affective dysfunction, and postoperative sleep disorders. Postoperatively, decreasing the use of methylprednisolone and promoting movement with an appropriate orthosis can reduce delirium incidence (P=0.0091). Polypharmacy is an independent risk factor for delirium (P=0.01) and decreasing use of delirium-inducing medications may reduce incidence. The delirium observation screening scale diagnoses and monitors delirium and is rated by nurses as easier to use than the NEECHAM Confusion Scale (P<0.003). Haloperidol is used widely to treat postoperative delirium. Randomized controlled trials show that adding quetiapine results in delirium resolution an average of 3.5 days faster than haloperidol alone (P=0.001) and decreases agitation and LOS (P=0.02; P=0.05). CONCLUSIONS An evidence-based algorithm is proposed to prevent, diagnose, and manage postoperative delirium that can be used clinically for geriatric patients undergoing elective spine surgery. Prevention and diagnosis involve efforts from the anesthesiologist and postoperative clinical care team. Treatment may include a therapeutic regimen of low-dose neuroleptic medications as needed. LEVEL OF EVIDENCE Level II.
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Affiliation(s)
- Alireza K Nazemi
- *Virginia Tech Carilion School of Medicine †Carilion Clinic, Institute for Orthopaedics and Neurosciences, Roanoke ‡Department of Orthopaedic Surgery, Virginia Commonwealth University, Richmond, VA §Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, NY
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Navathe AS, Zhong F, Lei VJ, Chang FY, Sordo M, Topaz M, Navathe SB, Rocha RA, Zhou L. Hospital Readmission and Social Risk Factors Identified from Physician Notes. Health Serv Res 2017; 53:1110-1136. [PMID: 28295260 DOI: 10.1111/1475-6773.12670] [Citation(s) in RCA: 106] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE To evaluate the prevalence of seven social factors using physician notes as compared to claims and structured electronic health records (EHRs) data and the resulting association with 30-day readmissions. STUDY SETTING A multihospital academic health system in southeastern Massachusetts. STUDY DESIGN An observational study of 49,319 patients with cardiovascular disease admitted from January 1, 2011, to December 31, 2013, using multivariable logistic regression to adjust for patient characteristics. DATA COLLECTION/EXTRACTION METHODS All-payer claims, EHR data, and physician notes extracted from a centralized clinical registry. PRINCIPAL FINDINGS All seven social characteristics were identified at the highest rates in physician notes. For example, we identified 14,872 patient admissions with poor social support in physician notes, increasing the prevalence from 0.4 percent using ICD-9 codes and structured EHR data to 16.0 percent. Compared to an 18.6 percent baseline readmission rate, risk-adjusted analysis showed higher readmission risk for patients with housing instability (readmission rate 24.5 percent; p < .001), depression (20.6 percent; p < .001), drug abuse (20.2 percent; p = .01), and poor social support (20.0 percent; p = .01). CONCLUSIONS The seven social risk factors studied are substantially more prevalent than represented in administrative data. Automated methods for analyzing physician notes may enable better identification of patients with social needs.
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Affiliation(s)
- Amol S Navathe
- Division of Health Policy, University of Pennsylvania, Philadelphia, PA.,CMC Philadelphia VA Medical Center, Philadelphia, PA.,Leonard Davis Institute of Health Economics, The Wharton School, University of Pennsylvania, Philadelphia, PA.,Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Harvard Medical School, Boston, MA
| | - Feiran Zhong
- Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Harvard Medical School, Boston, MA
| | - Victor J Lei
- Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Harvard Medical School, Boston, MA
| | - Frank Y Chang
- Clinical Informatics, Partners eCare, Partners Healthcare Inc., Boston, MA
| | - Margarita Sordo
- Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Harvard Medical School, Boston, MA.,Clinical Informatics, Partners eCare, Partners Healthcare Inc., Boston, MA
| | - Maxim Topaz
- Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Harvard Medical School, Boston, MA
| | - Shamkant B Navathe
- School of Computer Science, College of Computing, Georgia Institute of Technology, Atlanta, GA
| | - Roberto A Rocha
- Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Harvard Medical School, Boston, MA.,Clinical Informatics, Partners eCare, Partners Healthcare Inc., Boston, MA
| | - Li Zhou
- Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Harvard Medical School, Boston, MA.,Clinical Informatics, Partners eCare, Partners Healthcare Inc., Boston, MA
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