scholarly journals Understanding the impact and causes of ‘failure to attend’ on continuity of care for patients with chronic conditions

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247914
Author(s):  
Amy-Louise Byrne ◽  
Adele Baldwin ◽  
Clare Harvey ◽  
Janie Brown ◽  
Eileen Willis ◽  
...  
Keyword(s):  
Chronic Conditions ◽  
Hospital Admissions ◽  
Hospital Setting ◽  
Public Hospitals ◽  
Multiple Chronic Conditions ◽  
Outpatient Services ◽  
Nurse Navigator ◽  
Hospital Utilisation ◽  
The Impact ◽  
Causes Of Failure

Aim To understand the impact and causes of ‘Failure to Attend’ (FTA) labelling, of patients with chronic conditions. Background Nurse navigators are registered nurses employed by public hospitals in Queensland, Australia, to coordinate the care of patients with multiple chronic conditions, who frequently miss hospital appointments. The role of the nurse navigator is to improve care management of these patients. Evidence for this is measured through improvement in patient self-management of their conditions, a reduction in preventable hospital admissions and compliance with attendance at outpatient clinics. Failure to attend (FTA) is one measure of hospital utilisation, identifying outpatient appointments that are cancelled or not attended. Method The cohort for this study was patients with multiple chronic conditions, and nurse navigators coordinating their care. Data describing the concept of FTA were thematically analysed twelve months into this three year evaluation. Results Although the patient is blamed for failing to attend appointments, the reasons appear to be a mixture of systems error/miscommunication between the patient and the health services or social reasons impacting on patient’s capacity to attend. Themes emerging from the data were: access barriers; failure to recognise personal stigma of FTA; and bridging the gap. Conclusion The nurse navigators demonstrate their pivotal role in engaging with outpatient services to reduce FTAs whilst helping patients to become confident in dealing with multiple appointments. There are many reasons why a patient is unable to attend a scheduled appointment. The phrase ‘Failure to Attend’ has distinctly negative connotations and can lead to a sense of blame and shame for those with complex chronic needs. We propose the use of the neutral phrase “appointment did not proceed” to replace FTA. Implications for Nursing management This article advocates for further consideration of collaborative models that engage the patient in their care journey and for consideration of the language used within the outpatient acute hospital setting, proposing the term ‘appointment did not proceed.’

scholarly journals The Importance of Studying Health Behavior in Older Adults

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 827-827
Author(s):  
Jaime Hughes ◽  
Susan Hughes ◽  
Mina Raj ◽  
Janet Bettger
Keyword(s):  
Social Support ◽  
Older Adults ◽  
Behavior Change ◽  
Chronic Conditions ◽  
Population Level ◽  
Multiple Chronic Conditions ◽  
Prior Work ◽  
Time Changes ◽  
The Impact ◽  
Over Time

Abstract Behavior change is an inherent aspect of routine geriatric care. However, most research and clinical programs emphasis how to initiate behavior change with less emphasis placed on skills and strategies to maintain behaviors over time, including after an intervention has concluded. This presentation will provide an introduction to the symposium, including a review of prior work and our rationale for studying the critical yet overlooked construct of maintenance in older adults. Several key considerations in our work include the impact of multiple chronic conditions, declines in cognitive and functional capacity over time, changes in environmental context and/or social support, and sustainability of community and population-level programs and services.

scholarly journals The impact of the environment on patient experiences of hospital admissions in palliative care

2015 ◽  
Vol 8 (4) ◽  
pp. 485-492 ◽  
Author(s):  
Jackie Robinson ◽  
Merryn Gott ◽  
Clare Gardiner ◽  
Christine Ingleton
Keyword(s):  
Palliative Care ◽  
Health Professionals ◽  
Hospital Admissions ◽  
Hospital Setting ◽  
Prognostic Indicators ◽  
Care Needs ◽  
Acute Hospitals ◽  
Almost All ◽  
The Impact ◽  
Palliative Care Needs

ObjectiveTo explore the impact of environment on experiences of hospitalisation from the perspective of patient's with palliative care needs.MethodsA qualitative study design using longitudinal semistructured, face-to-face interviews were used to elicit the views of patients with palliative care needs admitted to hospital in 1 large urban acute hospital in New Zealand. The sample comprised of 14 patients admitted to hospital between July 2013 and March 2014 who met one of the Gold Standard Framework Prognostic Indicators for palliative care need.ResultsAlmost all participants described a range of factors associated with the environment which impacted negatively on their experiences of hospitalisation. This included challenges with the physical surroundings, the impact on social relationships with other patients, families and health professionals and the influence of the cultural milieu of the hospital setting.ConclusionsEmulating the ‘ideal’ environment for palliative care such as that provided in a hospice setting is an unrealistic goal for acute hospitals. Paying attention to the things that can be changed, such as enabling family to stay and improving the flexibility of the physical environment while improving the social interplay between patients and health professionals, may be a more realistic approach than replicating the hospice environment in order to reduce the burden of hospitalisations for patients with palliative care needs.

An evaluation of opioid use during acute hospital admissions

2022 ◽  
Vol 4 (1) ◽  
pp. 24-31
Author(s):  
Alison Blackburn
Keyword(s):  
Acute Pain ◽  
Hospital Admissions ◽  
Hospital Setting ◽  
Acute Hospital ◽  
Opioid Use ◽  
Opioid Medication ◽  
Age Range ◽  
The Impact ◽  
Acute Hospital Setting

Long-term opioid use can begin with the treatment of acute pain. However, there is little evidence concerning the impact that better opioid awareness in the acute phase may have on reducing the use of opioids in the long term. This project explored which opioids are routinely prescribed within an acute hospital setting and how these opioids were used over the course of the hospital stay. Codeine and morphine remain the most commonly prescribed opioids. Opioids were prescribed and given to people across the age range, from 16 to 98 years. The project found that 19% of patients were admitted with a pre-existing opioid. Up to 66% of patients were discharged with opioid medication, with almost 20% leaving with more than one opioid. Regular opioid use routinely exposes patients to long-term opioid use and those patients initiated onto opioid medication during admission should have the benefit of planned de-escalation before discharge.

scholarly journals Addressing Implementation Challenges to Digital Care Delivery for Adults With Multiple Chronic Conditions: Stakeholder Feedback in a Randomized Controlled Trial (Preprint)

2020 ◽  
Author(s):  
Kelly Williams ◽  
Sarah Markwardt ◽  
Shannon M Kearney ◽  
Jordan F Karp ◽  
Kevin L Kraemer ◽  
...  
Keyword(s):  
Chronic Conditions ◽  
Care Delivery ◽  
Text Message ◽  
Chronically Ill ◽  
High Tech ◽  
Multiple Chronic Conditions ◽  
Broadband Internet ◽  
Implementation Challenges ◽  
Before And After ◽  
The Impact

BACKGROUND Digital tools accessed via smartphones can promote chronic condition management, reduce disparities in health care and hospital readmissions, and improve quality of life. However, whether digital care strategies can be implemented successfully on a large scale with traditionally underserved populations remains uncertain. OBJECTIVE As part of a randomized trial comparing care delivery strategies for Medicaid and Medicare-Medicaid beneficiaries with multiple chronic conditions, our stakeholders identified implementation challenges, and we developed stakeholder-driven adaptions to improve a digitally delivered care management strategy (high-tech care). METHODS We used 4 mechanisms (study support log, Patient Partners Work Group log, case interview log, and implementation meeting minutes) to capture stakeholder feedback about technology-related challenges and solutions from 9 patient partners, 129 participants, and 32 care managers and used these data to develop and implement solutions. To assess the impact, we analyzed high-tech care exit surveys and intervention engagement outcomes (video visits and condition-specific text message check-ins sent at varying intervals) before and after each solution was implemented. RESULTS Challenges centered around 2 themes: difficulty using both smartphones and high-tech care components and difficulty using high-tech care components due to connectivity issues. To respond to the first theme’s challenges, we devised 3 solutions: tech visits (eg, in-person technology support visits), tech packet (eg, participant-facing technology user guide), and tailored condition-specific text message check-ins. During the first 20 months of implementation, 73 participants received at least one tech visit. We observed a 15% increase in video call completion for participants with data before and after the tech visit (n=25) and a 7% increase in check-in completion for participants with data before and after the tech visit (n=59). Of the 379 participants given a tech packet, 179 completed care during this timeframe and were eligible for an exit survey. Of the survey respondents, 76% (73/96) found the tech packet helpful and 64% (62/96) actively used it during care. To support condition-specific text message check-in completion, we allowed for adaption of day and/or time of the text message with 31 participants changing the time they received check-ins and change in standard biometric settings with 13 physicians requesting personalized settings for participants. To respond to the second theme’s challenges, tech visits or phone calls were made to demonstrate how to use a smartphone to connect or disconnect from the internet, to schedule video calls, or for condition-specific text message check-ins in a location with broadband/internet. CONCLUSIONS Having structured stakeholder feedback mechanisms is key to identify challenges and solutions to digital care engagement. Creating flexible and scalable solutions to technology-related challenges will increase equity in accessing digital care and support more effective engagement of chronically ill populations in the use of these digital care tools. CLINICALTRIAL ClinicalTrials.gov NCT03451630; https://clinicaltrials.gov/ct2/show/NCT03451630.

scholarly journals Effect of Seasonal Variation on Clinical Outcome in Patients with Chronic Conditions: Analysis of the Commonwealth Scientific and Industrial Research Organization (CSIRO) National Telehealth Trial (Preprint)

2017 ◽  
Author(s):  
Ahmadreza Argha ◽  
Andrey Savkin ◽  
Siaw-Teng Liaw ◽  
Branko George Celler
Keyword(s):  
Seasonal Variation ◽  
Length Of Stay ◽  
Clinical Outcome ◽  
Seasonal Variations ◽  
Chronic Conditions ◽  
Hospital Admissions ◽  
Australian Capital Territory ◽  
Home Telemonitoring ◽  
The Impact ◽  
At Home

BACKGROUND Seasonal variation has an impact on the hospitalization rate of patients with a range of cardiovascular diseases, including myocardial infarction and angina. This paper presents findings on the influence of seasonal variation on the results of a recently completed national trial of home telemonitoring of patients with chronic conditions, carried out at five locations along the east coast of Australia. OBJECTIVE The aim is to evaluate the effect of the seasonal timing of hospital admission and length of stay on clinical outcome of a home telemonitoring trial involving patients (age: mean 72.2, SD 9.4 years) with chronic conditions (chronic obstructive pulmonary disease coronary artery disease, hypertensive diseases, congestive heart failure, diabetes, or asthma) and to explore methods of minimizing the influence of seasonal variations in the analysis of the effect of at-home telemonitoring on the number of hospital admissions and length of stay (LOS). METHODS Patients were selected from a hospital list of eligible patients living with a range of chronic conditions. Each test patient was case matched with at least one control patient. A total of 114 test patients and 173 control patients were available in this trial. However, of the 287 patients, we only considered patients who had one or more admissions in the years from 2010 to 2012. Three different groups were analyzed separately because of substantially different climates: (1) Queensland, (2) Australian Capital Territory and Victoria, and (3) Tasmania. Time series data were analyzed using linear regression for a period of 3 years before the intervention to obtain an average seasonal variation pattern. A novel method that can reduce the impact of seasonal variation on the rate of hospitalization and LOS was used in the analysis of the outcome variables of the at-home telemonitoring trial. RESULTS Test patients were monitored for a mean 481 (SD 77) days with 87% (53/61) of patients monitored for more than 12 months. Trends in seasonal variations were obtained from 3 years’ of hospitalization data before intervention for the Queensland, Tasmania, and Australian Capital Territory and Victoria subgroups, respectively. The maximum deviation from baseline trends for LOS was 101.7% (SD 42.2%), 60.6% (SD 36.4%), and 158.3% (SD 68.1%). However, by synchronizing outcomes to the start date of intervention, the impact of seasonal variations was minimized to a maximum of 9.5% (SD 7.7%), thus improving the accuracy of the clinical outcomes reported. CONCLUSIONS Seasonal variations have a significant effect on the rate of hospital admission and LOS in patients with chronic conditions. However, the impact of seasonal variation on clinical outcomes (rate of admissions, number of hospital admissions, and LOS) of at-home telemonitoring can be attenuated by synchronizing the analysis of outcomes to the commencement dates for the telemonitoring of vital signs. CLINICALTRIAL Australian New Zealand Clinical Trial Registry ACTRN12613000635763; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364030&isReview=true (Archived by WebCite at http://www.webcitation.org/ 6xLPv9QDb)

Healthcare inequalities in emergency visits and hospitalisation at the end of life: a study of 395 019 public hospital records

2021 ◽  
pp. bmjspcare-2020-002800
Author(s):  
Roger Yat-Nork Chung ◽  
Derek Chun Kiu Lai ◽  
Alvin Yik-Kiu Hui ◽  
Patsy Yuen-Kwan Chau ◽  
Eliza Lai-Yi Wong ◽  
...  
Keyword(s):  
Hong Kong ◽  
End Of Life ◽  
Hospital Admissions ◽  
Secondary Data ◽  
Public Hospitals ◽  
Emergency Visits ◽  
Elderly Home ◽  
Care Services ◽  
Lower Socioeconomic ◽  
Hospital Utilisation

ObjectivesTo investigate whether there were any socioeconomic disparities in utilisation of hospital care services during end of life in Hong Kong.MethodsSecondary data analyses were conducted using frequency of the accident and emergency (A&E) department visits and hospital admissions during the last year of life in all public hospitals from 2004 to 2014 in Hong Kong. A total of 1 237 044 A&E records from 357 853 patients, and 1 878 982 admission records from 375 506 patients were identified for analyses. In total, 395 019 unique deceased patients were identified from both datasets.ResultsRegression analyses showed that comprehensive social security assistance (CSSA) recipients used A&E services 1.29 times more than the non-recipients. Being either a CSSA recipient or an elderly home resident was more likely to be admitted to hospitals and stayed longer. Elderly home residents tended to stay longer than those from the community in the earlier months during the last year of life regardless of CSSA status; however, non-elderly home residents surpassed the residents in the duration of stay at hospitals towards the later months of the last year of life. There were also significant differences in hospital utilisation across various districts of residence.ConclusionsPeople of lower socioeconomic position tend to have higher emergency visits and hospitalisation during their last year of life in Hong Kong, implying the presence of health inequality during end of life. However, due to Hong Kong’s largely pro-rich primary care system, the predominantly public A&E and inpatient services may inadvertently act as a mitigator of such health inequalities.

scholarly journals Managing chronic conditions care across primary care and hospital systems: lessons from an Australian Hospital Avoidance Risk Program using the Flinders Chronic Condition Management Program

2018 ◽  
Vol 42 (5) ◽  
pp. 542 ◽  
Author(s):  
Sharon Lawn ◽  
Sara Zabeen ◽  
David Smith ◽  
Ellen Wilson ◽  
Cathie Miller ◽  
...  
Keyword(s):  
Emergency Department ◽  
Heart Disease ◽  
Length Of Stay ◽  
Chronic Conditions ◽  
Chronic Condition ◽  
Hospital Admissions ◽  
Self Management ◽  
Psychosocial Needs ◽  
Post Discharge ◽  
The Impact

Objective The study aimed to determine the impact of the Flinders Chronic Condition Management Program for chronic condition self-management care planning and how to improve its use with Bendigo Health’s Hospital Admission Risk Program (HARP). Methods A retrospective analysis of hospital admission data collected by Bendigo Health from July 2012 to September 2013 was undertaken. Length of stay during admission and total contacts post-discharge by hospital staff for 253 patients with 644 admissions were considered as outcome variables. For statistical modelling we used the generalised linear model. Results The combination of the HARP and Flinders Program was able to achieve significant reductions in hospital admissions and non-significant reduction in emergency department presentations and length of stay. The generalised linear model predicted that vulnerable patient groups such as those with heart disease (P = 0.037) and complex needs (P < 0.001) received more post-discharge contacts by HARP staff than those suffering from diabetes, renal conditions and psychosocial needs when they lived alone. Similarly, respiratory (P < 0.001), heart disease (P = 0.015) and complex needs (P = 0.050) patients had more contacts, with an increased number of episodes than those suffering from diabetes, renal conditions and psychosocial needs. Conclusion The Flinders Program appeared to have significant positive impacts on HARP patients that could be more effective if high-risk groups, such as respiratory patients with no carers and respiratory and heart disease patients aged 0–65, had received more targeted care. What is known about the topic? Chronic conditions are common causes of premature death and disability in Australia. Besides mental and physical impacts at the individual level, chronic conditions are strongly linked to high costs and health service utilisation. Hospital avoidance programs such as HARP can better manage chronic conditions through a greater focus on coordination and integration of care across primary care and hospital systems. In support of HARP, self-management interventions such as the Flinders Program aim to help individuals better manage their medical treatment and cope with the impact of the condition on their physical and mental wellbeing and thus reduce health services utilisation. What does this paper add? This paper sheds light on which patients might be more or less likely to benefit from the combination of the HARP and Flinders Program, with regard to their impact on reductions in hospital admissions, emergency department presentations and length of stay. This study also sheds light on how the Flinders Program could be better targeted towards and implemented among high-need and high-cost patients to lessen chronic disease burden on Australia’s health system. What are the implications for practitioners? Programs targeting vulnerable populations and applying evidence-based chronic condition management and self-management support achieve significant reductions in potentially avoidable hospitalisation and emergency department presentation rates, though sex, type of chronic condition and living situation appear to matter. Benefits might also accrue from the combination of contextual factors (such as the Flinders Program, supportive service management, clinical champions in the team) that work synergistically.

scholarly journals Comparison of EHR-based diagnosis documentation locations to a gold standard for risk stratification in patients with multiple chronic conditions

2017 ◽  
Vol 08 (03) ◽  
pp. 794-809 ◽  
Author(s):  
Shelby Martin ◽  
Jesse Wagner ◽  
Nicoleta Lupulescu-Mann ◽  
Katrina Ramsey ◽  
Aaron Cohen ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Gold Standard ◽  
Chronic Conditions ◽  
Chart Review ◽  
Risk Scores ◽  
Multiple Chronic Conditions ◽  
Validity Testing ◽  
Combining Data ◽  
Diagnostic Statistics ◽  
The Impact

SummaryObjective: To measure variation among four different Electronic Health Record (EHR) system documentation locations versus ‘gold standard’ manual chart review for risk stratification in patients with multiple chronic illnesses.Methods: Adults seen in primary care with EHR evidence of at least one of 13 conditions were included. EHRs were manually reviewed to determine presence of active diagnoses, and risk scores were calculated using three different methodologies and five EHR documentation locations. Claims data were used to assess cost and utilization for the following year. Descriptive and diagnostic statistics were calculated for each EHR location. Criterion validity testing compared the gold standard verified diagnoses versus other EHR locations and risk scores in predicting future cost and utilization.Results: Nine hundred patients had 2,179 probable diagnoses. About 70% of the diagnoses from the EHR were verified by gold standard. For a subset of patients having baseline and prediction year data (n=750), modeling showed that the gold standard was the best predictor of outcomes on average for a subset of patients that had these data. However, combining all data sources together had nearly equivalent performance for prediction as the gold standard.Conclusions: EHR data locations were inaccurate 30% of the time, leading to improvement in overall modeling from a gold standard from chart review for individual diagnoses. However, the impact on identification of the highest risk patients was minor, and combining data from different EHR locations was equivalent to gold standard performance.Martin S, Wagner J, Lupulescu-Mann N et al. Comparison of EHR-based diagnosis documentation locations to a gold standard for risk stratification in patients with multiple chronic conditions . Appl Clin Inform 2017; 8: 794–809 https://doi.org/10.4338/ACI-2016-12-RA-0210

scholarly journals Changes in Eating Habits and Sedentary Behavior During the COVID-19 Pandemic in Adolescents With Chronic Conditions

2021 ◽  
Vol 9 ◽  
Author(s):  
Bruna Caruso Mazzolani ◽  
Fabiana Infante Smaira ◽  
Camilla Astley ◽  
Amanda Yuri Iraha ◽  
Ana Jessica Pinto ◽  
...  
Keyword(s):  
Sedentary Behavior ◽  
Screen Time ◽  
Chronic Conditions ◽  
Eating Habits ◽  
Multiple Chronic Conditions ◽  
Tertiary Referral ◽  
Tertiary Referral Hospital ◽  
School Closures ◽  
Specific Care ◽  
The Impact

Introduction: Among healthy adolescents, school closures and home confinement were shown to increase unhealthier eating habits and sedentary behavior. It remains unknown to which extent the pandemic has impacted the lifestyle of adolescents with chronic conditions. Thus, the aim of this study is to report on the impact of the COVID-19 outbreak on eating habits and sedentary behavior among adolescents with multiple chronic conditions (n = 347) from a tertiary, referral hospital vs. healthy peers.Methods: This observational study was conducted in São Paulo (Brazil) between July and October 2020, period in which a set of social distancing measures to contain the pandemic.Results: The main findings of this study were that adolescents with chronic conditions and health peers showed important changes in eating habits (e.g., more often cooking and eating in front of television than before quarantine). Also, 86.8% of adolescents with chronic conditions and 91.6% of healthy adolescents reported increasing screen time during pandemic. No major differences were observed between patients and controls.Conclusions: Adolescents with chronic conditions and healthy peers exposed to pandemic showed substantial changes in lifestyle, stressing the need for specific care to mitigate poor eating habits and excessive sedentary behavior for patients and healthy adolescents.

scholarly journals Clustering and Healthcare Costs With Multiple Chronic Conditions in a US Cross-Sectional Study

2020 ◽  
Author(s):  
cother hajat ◽  
yakir siegal ◽  
amalia adler-waxman
Keyword(s):  
Mental Health ◽  
Chronic Conditions ◽  
Healthcare Costs ◽  
Multiple Chronic Conditions ◽  
Cross Sectional ◽  
The Us ◽  
Health Related ◽  
Insured Patients ◽  
The Impact ◽  
Hiv Aids

Objective To investigate healthcare costs and contributors to costs for multiple chronic conditions (MCCs), common clusters of conditions and their impact on cost and utilisation. Methods This was a cross-sectional analysis of US financial claims data representative of the US population, including Medicare, Medicaid and Commercial insurance claims in 2015. Outcome measures included healthcare costs and contributors; ranking of clusters of conditions according to frequency, strength of association and unsupervised (k-means) analysis; the impact of clustering on costs and contributors to costs. Results Of 1,878,951 patients, 931,045(49.6%) had MCCs, 56.5% weighted to the US population. Mean age was 53.0 years(SD16.7); 393,121(42.20%) were male. Mean annual healthcare spending was $12,601, ranging from $4,385 (2 conditions) to $33,874 (11 conditions), with spending increasing by 22-fold for inpatient services, 6-fold for outpatient services, 4.5-fold for generic drugs and 4.2-fold for branded drugs. Cluster ranking using the 3 methodologies yielded similar results: highest ranked clusters included metabolic syndrome(12.2% of US insured patients), age related diseases(7.7%), renal failure(5.6%), respiratory disorders(4.5%), cardiovascular disease(CVD)(4.3%), cancers(4.1-4.3%), mental health-related clusters(1.0-1.5%) and HIV/AIDS(0.2%). Highest spending was in HIV/AIDS clusters ($48,293), mental health-related clusters ($38,952-$40,637), renal disease ($38,551) and CVD ($37,155); with 89.9% of spending on outpatient and inpatient care combined, and 10.1% on medication. Conclusion and Relevance Over 57% of insured patients in the US may have MCCs. MCC Clustering is frequent and is associated with healthcare utilisation. The findings favour health system redesign towards a multiple condition approach for clusters of chronic conditions, alongside other cost-containment measures for MCCs.

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