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Masot O, Cox A, Mold F, Sund-Levander M, Tingström P, Boersema GC, Botigué T, Daltrey J, Hughes K, Mayhorn CB, Montgomery A, Mullan J, Carey N. Decision support-tools for early detection of infection in older people (aged> 65 years): a scoping review. BMC Geriatr 2022; 22:552. [PMID: 35778707 PMCID: PMC9247966 DOI: 10.1186/s12877-022-03218-w] [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: 05/23/2022] [Indexed: 11/21/2022] Open
Abstract
Background Infection is more frequent, and serious in people aged > 65 as they experience non-specific signs and symptoms delaying diagnosis and prompt treatment. Monitoring signs and symptoms using decision support tools (DST) is one approach that could help improve early detection ensuring timely treatment and effective care. Objective To identify and analyse decision support tools available to support detection of infection in older people (> 65 years). Methods A scoping review of the literature 2010–2021 following Arksey and O’Malley (2005) framework and PRISMA-ScR guidelines. A search of MEDLINE, Cochrane, EMBASE, PubMed, CINAHL, Scopus and PsycINFO using terms to identify decision support tools for detection of infection in people > 65 years was conducted, supplemented with manual searches. Results Seventeen papers, reporting varying stages of development of different DSTs were analysed. DSTs largely focussed on specific types of infection i.e. urine, respiratory, sepsis and were frequently hospital based (n = 9) for use by physicians. Four DSTs had been developed in nursing homes and one a care home, two of which explored detection of non- specific infection. Conclusions DSTs provide an opportunity to ensure a consistent approach to early detection of infection supporting prompt action and treatment, thus avoiding emergency hospital admissions. A lack of consideration regarding their implementation in practice means that any attempt to create an optimal validated and tested DST for infection detection will be impeded. This absence may ultimately affect the ability of the workforce to provide more effective and timely care, particularly during the current covid-19 pandemic. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-022-03218-w.
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Affiliation(s)
- Olga Masot
- Department of Nursing and Physiotherapy, University of Lleida, Lleida, Spain. .,Health Care Research Group (GRECS), [Lleida Institute for Biomedical Research Dr. Pifarré Foundation], IRBLleida, 25198, Lleida, Spain.
| | - Anna Cox
- School of Health Sciences, University of Surrey, Guildford, GU2 7YH, UK
| | - Freda Mold
- School of Health Sciences, University of Surrey, Guildford, GU2 7YH, UK
| | - Märtha Sund-Levander
- Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Pia Tingström
- Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | | | - Teresa Botigué
- Department of Nursing and Physiotherapy, University of Lleida, Lleida, Spain.,Health Care Research Group (GRECS), [Lleida Institute for Biomedical Research Dr. Pifarré Foundation], IRBLleida, 25198, Lleida, Spain
| | - Julie Daltrey
- School of Nursing, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Karen Hughes
- School of Health Sciences, University of Surrey, Guildford, GU2 7YH, UK
| | - Christopher B Mayhorn
- Department of Psychology, North Carolina State University, Raleigh, NC, 27695-7801, USA
| | - Amy Montgomery
- School of Nursing, University of Wollongong, Wollongong, NSW, 2522, Australia
| | - Judy Mullan
- School of Medicine, University of Wollongong, Wollongong, NSW, 2522, Australia
| | - Nicola Carey
- Department of Nursing and Midwifery, University of the Highlands and Islands, Inverness, IV2 3JH, UK
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Jones K, Mantey J, Washer L, Meddings J, Patel PK, Montoya A, Mills JP, Gibson K, Mody L. When planning meets reality: COVID-19 interpandemic survey of Michigan Nursing Homes. Am J Infect Control 2021; 49:1343-1349. [PMID: 33794312 PMCID: PMC8007185 DOI: 10.1016/j.ajic.2021.03.016] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 01/08/2023]
Abstract
BACKGROUND Nursing home (NH) populations have borne the brunt of morbidity and mortality of COVID-19. We surveyed Michigan NHs to evaluate preparedness, staffing, testing, and adaptations to these challenges. METHODS Interpandemic survey responses were collected May 1-12, 2020. We used Pearson's Chi-squared test, Fisher's exact test, and logistic regression to evaluate relationships. RESULTS Of 452 Michigan NHs contacted via e-mail, 145 (32.1%) opened the survey and of these, 143 (98.6%) responded. Sixty-eight percent of respondents indicated their response plan addressed most issues. NHs reported receiving rapidly changing guidance from many sources. Two-thirds reported shortages of personal protective equipment and other supplies. Half (50%) lacked sufficient testing resources with only 36% able to test residents and staff with suspected COVID-19. A majority (55%) experienced staffing shortages. Sixty-three percent experienced resignations, with front-line clinical staff more likely to resign, particularly in facilities caring for COVID-19 patients (P < .001). Facilities adapted quickly, creating COVID-19 units (78%) to care for patients on site. To reduce isolation, NHs facilitated communication via phone calls (98%), videoconferencing (96%), and window visits (81%). A majority continued to provide requisite therapies (90%). CONCLUSIONS NHs experienced shortages of resources, testing supplies, and staffing challenges. COVID-19 in the facility was a key predictor of staff resignations. Facilities relied on rapidly changing, often conflicting advice from multiple sources, suggesting high-yield areas of improvement.
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Affiliation(s)
- Karen Jones
- Department of Internal Medicine, Division of Geriatric and Palliative Medicine, University of Michigan Medical School, Ann Arbor, MI
| | - Julia Mantey
- Department of Internal Medicine, Division of Geriatric and Palliative Medicine, University of Michigan Medical School, Ann Arbor, MI
| | - Laraine Washer
- Department of Internal Medicine, Division of Infectious Diseases, University of Michigan Medical School, Ann Arbor, MI; Department of Infection Prevention and Epidemiology, Michigan Medicine, Ann Arbor, MI
| | - Jennifer Meddings
- Department of Internal Medicine, Division of Geriatric and Palliative Medicine, University of Michigan Medical School, Ann Arbor, MI; Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI; Department of Pediatrics and Communicable Diseases, University of Michigan Medical School, Ann Arbor, MI
| | - Payal K Patel
- Department of Internal Medicine, Division of Infectious Diseases, University of Michigan Medical School, Ann Arbor, MI; Division of Infectious Diseases, Department of Internal Medicine, Veterans Affairs, Ann Arbor Healthcare System, Ann Arbor, MI
| | - Ana Montoya
- Department of Internal Medicine, Division of Geriatric and Palliative Medicine, University of Michigan Medical School, Ann Arbor, MI
| | - John P Mills
- Department of Internal Medicine, Division of Infectious Diseases, University of Michigan Medical School, Ann Arbor, MI
| | - Kristen Gibson
- Department of Internal Medicine, Division of Geriatric and Palliative Medicine, University of Michigan Medical School, Ann Arbor, MI
| | - Lona Mody
- Department of Internal Medicine, Division of Geriatric and Palliative Medicine, University of Michigan Medical School, Ann Arbor, MI; Geriatrics Research Education and Clinical Center (GRECC), Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI.
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