The impact of radiation treatment planning technique on unplanned hospital admissions.
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ABSTRACT:
SUBMITTER: Chang S
PROVIDER: S-EPMC6200879 | biostudies-other | 2018 Oct-Dec
REPOSITORIES: biostudies-other
Publications
The impact of radiation treatment planning technique on unplanned hospital admissions.
Chang Sanders S Ru Meng M Moshier Erin L EL Mazumdar Madhu M Ricks Doran D Goldstein Nathan E NE Wisnivesky Juan P JP Dharmarajan Kavita V KV
Advances in radiation oncology 20180712 4
<h4>Purpose</h4>Treatment burdens and toxicities related to palliative radiation therapy (RT) may lead to unplanned hospital admissions (UHAs). The likelihood for these toxicities may be related to treatment technique. We compared rates of UHA between patients receiving nonconformal (2-dimensional) and conformal (3-dimensional or higher) radiation treatments to bone metastases involving the vertebral column.<h4>Methods and materials</h4>We retrospectively analyzed patients treated with RT for bo ...[more]
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Project description:PurposeBoth obesity and type 2 diabetes are associated with an increased risk of skin and soft tissue (SSTI), urinary tract, and lower respiratory tract infections but it is not clear whether the incidence of such infections is reduced after bariatric surgery.Materials and methodsIn people accepted onto our publicly funded bariatric program, we recorded unplanned admissions to public hospitals over a median follow-up of 4.5 years in those successfully undergoing surgery and in those who withdrew from the program. Rates of admission for the composite outcome (SSTI, urinary tract, or lower respiratory infection) were compared.ResultsOf 774 people accepted onto the program, 49% underwent surgery. Infections accounted for 27% of unplanned admissions in those not completing surgery and 13% of those who underwent surgery (p < 0.001). The rate of admission was 60% lower in people who underwent surgery than those who did not: 4.3 vs 12.2 per 100 patient-years (P < 0.002), a difference maintained across 8 years' follow-up. The impact of surgery was independent of enrolment age, BMI, or diabetes and smoking status. Of the three types of infection in the composite outcome, SSTI were the most prevalent and showed the greatest reduction (p < 0.0001). The median day stay for infection was 0.5 day less in those who underwent surgery (p < 0.01).ConclusionsHospitalization for these three infectious diseases in people undergoing bariatric surgery was lower than that in people enrolled in the bariatric program but not completing surgery. The effect was greatest for SSTI, and sustained to at least 8 years.
| S-EPMC9072262 | biostudies-literature
Project description:ObjectiveTo investigate the association between indicators of quality of diabetic management in English family practices and emergency hospital admissions for short-term complications of diabetes.Study settingA total of 8,223 English family practices from 2001/2002 to 2006/2007.Study designMultiple regression analyses of associations between admissions and proportions of practice diabetic patients with good (glycated hemoglobin [HbA1c] ?7.4 percent) and moderate (7.4 percent <HbA1c ?10 percent) glycemic control. Covariates included diabetes prevalence, baseline admission rates, socioeconomic, demographic, and geographic characteristics.DataPractice quality measures extracted from practice records linked with practice-level hospital admissions data and practice-level covariates data.Principal findingsPractices with 1 percent more patients with moderate rather than poor glycemic control on average had 1.9 percent (95 percent CI: 1.1-2.6 percent) lower rates of emergency admissions for acute hyperglycemic complications. Having more patients with good rather than moderate control was not associated with lower admissions. There was no association of moderate or good control with hypoglycemic admissions.ConclusionCross-sectionally, family practices with better quality of diabetes care had fewer emergency admissions for short-term complications of diabetes. Over time, after controlling for national trends in admissions, improvements in quality in a family practice were associated with a reduction in its admissions.
| S-EPMC3034260 | biostudies-literature
Project description:Universal health coverage (UHC) aims to improve child health through preventive primary care and vaccine coverage. Yet, in many developed countries with UHC, unplanned and ambulatory care sensitive (ACS) hospital admissions in childhood continue to rise. We investigated the relation between preventive primary care and risk of unplanned and ACS admission in children in a high-income country with UHC.We followed 319,780 children registered from birth with 363 English practices in Clinical Practice Research Datalink linked to Hospital Episodes Statistics, born between January 2000 and March 2013. We used Cox regression estimating adjusted hazard ratios (HR) to examine subsequent risk of unplanned and ACS hospital admissions in children who received preventive primary care (development checks and vaccinations), compared with those who did not.Overall, 98% of children had complete vaccinations and 87% had development checks. Unplanned admission rates were 259, 105 and 42 per 1000 child-years in infants (aged <?1 year), preschool (1-4 years) and primary school (5-9 years) children, respectively. Lack of preventive care was associated with more unplanned admissions. Infants with incomplete vaccination had increased risk for all unplanned admissions (HR 1.89, 1.79-2.00) and vaccine-preventable admissions (HR 4.41, 2.59-7.49). Infants lacking development checks had higher risk for unplanned admission (HR 4.63, 4.55-4.71). These associations persisted across childhood. Children who had higher consulting rates with primary care providers also had higher risk of unplanned admission (preschool children: HR 1.17, 1.17-1.17). One third of all unplanned admissions (62,154/183,530) were for ACS infectious illness. Children with chronic ACS conditions, asthma, diabetes or epilepsy had increased risk of unplanned admission (HR 1.90, 1.77-2.04, HR 11.43, 8.48-15.39, and HR 4.82, 3.93-5.91, respectively). These associations were modified in children who consulted more in primary care.A high uptake of preventive primary care from birth is associated with fewer unplanned and ACS admissions in children. However, the clustering of poor health, a lack of preventive care uptake, and social deprivation puts some children with comorbid conditions at very high risk of admission. Strengthening immunisation coverage and preventive primary care in countries with poor UHC could potentially significantly reduce the health burden from hospital admission in children.
| S-EPMC6139908 | biostudies-other
Project description:BackgroundTimely care by general practitioners in the community keeps children out of hospital and provides better continuity of care. Yet in the UK, access to primary care has diminished since 2004 when changes in general practitioners' contracts enabled them to 'opt out' of providing out-of-hours care and since then unplanned pediatric hospital admission rates have escalated, particularly through emergency departments. We hypothesised that any increase in isolated short stay admissions for childhood illness might reflect failure to manage these cases in the community over a 10 year period spanning these changes.Methods and findingsWe conducted a population based time trends study of major causes of hospital admission in children <10 years using the Hospital Episode Statistics database, which records all admissions to all NHS hospitals in England using ICD10 codes. Outcomes measures were total and isolated short stay unplanned hospital admissions (lasting less than 2 days without readmission within 28 days) from 1997 to 2006. Over the period annual unplanned admission rates in children aged <10 years rose by 22% (from 73.6/1000 to 89.5/1000 child years) with larger increases of 41% in isolated short stay admissions (from 42.7/1000 to 60.2/1000 child years). There was a smaller fall of 12% in admissions with length of stay of >2 days. By 2006, 67.3% of all unplanned admissions were isolated short stays <2 days. The increases in admission rates were greater for common non-infectious than infectious causes of admissions.ConclusionsShort stay unplanned hospital admission rates in young children in England have increased substantially in recent years and are not accounted for by reductions in length of in-hospital stay. The majority are isolated short stay admissions for minor illness episodes that could be better managed by primary care in the community and may be evidence of a failure of primary care services.
| S-EPMC2758998 | biostudies-literature
Project description:BackgroundEnhanced management of multimorbidity constitutes a major clinical challenge. Multimorbidity shows well-established causal relationships with the high use of health care resources and, specifically, with unplanned hospital admissions. Enhanced patient stratification is vital for achieving effectiveness through personalized postdischarge service selection.ObjectiveThe study has a 2-fold aim: (1) generation and assessment of predictive models of mortality and readmission at 90 days after discharge; and (2) characterization of patients' profiles for personalized service selection purposes.MethodsGradient boosting techniques were used to generate predictive models based on multisource data (registries, clinical/functional and social support) from 761 nonsurgical patients admitted in a tertiary hospital over 12 months (October 2017 to November 2018). K-means clustering was used to characterize patient profiles.ResultsPerformance (area under the receiver operating characteristic curve, sensitivity, and specificity) of the predictive models was 0.82, 0.78, and 0.70 and 0.72, 0.70, and 0.63 for mortality and readmissions, respectively. A total of 4 patients' profiles were identified. In brief, the reference patients (cluster 1; 281/761, 36.9%), 53.7% (151/281) men and mean age of 71 (SD 16) years, showed 3.6% (10/281) mortality and 15.7% (44/281) readmissions at 90 days following discharge. The unhealthy lifestyle habit profile (cluster 2; 179/761, 23.5%) predominantly comprised males (137/179, 76.5%) with similar age, mean 70 (SD 13) years, but showed slightly higher mortality (10/179, 5.6%) and markedly higher readmission rate (49/179, 27.4%). Patients in the frailty profile (cluster 3; 152/761, 19.9%) were older (mean 81 years, SD 13 years) and predominantly female (63/152, 41.4%, males). They showed medical complexity with a high level of social vulnerability and the highest mortality rate (23/152, 15.1%), but with a similar hospitalization rate (39/152, 25.7%) compared with cluster 2. Finally, the medical complexity profile (cluster 4; 149/761, 19.6%), mean age 83 (SD 9) years, 55.7% (83/149) males, showed the highest clinical complexity resulting in 12.8% (19/149) mortality and the highest readmission rate (56/149, 37.6%).ConclusionsThe results indicated the potential to predict mortality and morbidity-related adverse events leading to unplanned hospital readmissions. The resulting patient profiles fostered recommendations for personalized service selection with the capacity for value generation.
| S-EPMC9982720 | biostudies-literature
Project description:BackgroundTo investigate the feasibility of a knowledge-based automated intensity-modulated radiation therapy (IMRT) planning technique for locally advanced nasopharyngeal carcinoma (NPC) radiotherapy.MethodsOne hundred forty NPC patients treated with definitive radiation therapy with the step-and-shoot IMRT techniques were retrospectively selected and separated into a knowledge library (n = 115) and a test library (n = 25). For each patient in the knowledge library, the overlap volume histogram (OVH), target volume histogram (TVH) and dose objectives were extracted from the manually generated plan. 5-fold cross validation was performed to divide the patients in the knowledge library into 5 groups before validating one group by using the other 4 groups to train each neural network (NN) machine learning models. For patients in the test library, their OVH and TVH were then used by the trained models to predict a corresponding set of mean dose objectives, which were subsequently used to generate automated plans (APs) in Pinnacle planning system via an in-house developed automated scripting system. All APs were obtained after a single step of optimization. Manual plans (MPs) for the test patients were generated by an experienced medical physicist strictly following the established clinical protocols. The qualities of the APs and MPs were evaluated by an attending radiation oncologist. The dosimetric parameters for planning target volume (PTV) coverage and the organs-at-risk (OAR) sparing were also quantitatively measured and compared using Mann-Whitney U test and Bonferroni correction.ResultsAPs and MPs had the same rating for more than 80% of the patients (19 out of 25) in the test group. Both AP and MP achieved PTV coverage criteria for no less than 80% of the patients. For each OAR, the number of APs achieving its criterion was similar to that in the MPs. The AP approach improved planning efficiency by greatly reducing the planning duration to about 17% of the MP (9.85 ± 1.13 min vs. 57.10 ± 6.35 min).ConclusionA robust and effective knowledge-based IMRT treatment planning technique for locally advanced NPC is developed. Patient specific dose objectives can be predicted by trained NN models based on the individual's OVH and clinical TVH goals. The automated planning scripts can use these dose objectives to efficiently generate APs with largely shortened planning time. These APs had comparable dosimetric qualities when compared to our clinic's manual plans.
| S-EPMC7397573 | biostudies-literature
Project description:Backgroundthe socioeconomic distribution of unplanned hospital admissions in older adults is poorly understood. We compared associations of two life-course measures of socioeconomic status (SES) with unplanned hospital admissions while comprehensively accounting for health, and examined the role of social network in this association.Methodsin 2,862 community-dwelling adults aged 60+ in Sweden, we derived (i) an aggregate life-course SES measure grouping individuals into Low, Middle or High SES based on a summative score, and (ii) a latent class measure that additionally identified a Mixed SES group, characterised by financial difficulties in childhood and old age. The health assessment combined measures of morbidity and functioning. The social network measure included social connections and support components. Negative binomial models estimated the change in hospital admissions over 4 years in relation to SES. Stratification and statistical interaction assessed effect modification by social network.Resultsadjusting for health and social network, unplanned hospitalisation rates were higher for the latent Low SES and Mixed SES group (incidence rate ratio [IRR] = 1.38, 95% confidence interval [CI]: 1.12-1.69, P = 0.002; IRR = 2.06, 95% CI: 1.44-2.94, P < 0.001; respectively; ref: High SES). Mixed SES was at a substantially greater risk of unplanned hospital admissions among those with poor (and not rich) social network (IRR: 2.43, 95% CI: 1.44-4.07; ref: High SES), but the statistical interaction test was non-significant (P = 0.493).Conclusionsocioeconomic distributions of older adults' unplanned hospitalisations were largely driven by health, although considering SES dynamics across life can reveal at-risk sub-populations. Financially disadvantaged older adults might benefit from interventions aimed at improving their social network.
| S-EPMC10118263 | biostudies-literature
Project description:Backgroundhospitalisations are sentinel events for people with dementia. How patterns of unplanned hospital admissions change among people with dementia after diagnosis is relatively unknown.Objectiveto describe patterns of unplanned hospital admissions of people with dementia from diagnosis until death/study end.Methodsretrospective cohort study using mental healthcare provider data of people diagnosed with dementia in London, UK (1995-2017), linked to mortality and hospital data. The primary outcome was the rate of unplanned hospital admissions after diagnosis until death/study end. We calculated the cumulative incidence of unplanned hospital admissions. The rates of unplanned hospital admissions and the percentage of time spent as an inpatient were stratified by time from first dementia diagnosis.Resultsfor 19,221 people with dementia (61.4% female, mean age at diagnosis 81.0 years (standard deviation, SD 8.5)), the cumulative incidence of unplanned hospital admissions (n = 14,759) was 76.8% (95% CI 76.3%-77.3%). Individuals remained in the study for mean 3.0 (SD 2.6) years, and 12,667 (65.9%) died. Rates and lengths of unplanned hospital admissions remained relatively low and short in the months after the dementia diagnosis, increasing only as people approached the end of life. Percentage of time spent as an inpatient was <3% for people who were alive at the study end but was on average 19.6 and 13.3% for the decedents in the last 6 and 12 months of life, respectively.Conclusionsthe steep rise in hospitalisations before death highlights the need for improved community care and services for people with dementia who are approaching the end of life.
| S-EPMC9113942 | biostudies-literature
Project description:BackgroundIdentification of community-dwelling older adults at risk of unplanned hospitalizations is of importance to facilitate preventive interventions. Our objective was to review and appraise the methodological quality and predictive performance of prediction models for predicting unplanned hospitalizations in community-dwelling older adults.Methods and findingsWe searched MEDLINE, EMBASE and CINAHL from August 2013 to January 2021. Additionally, we checked references of the identified articles for the inclusion of relevant publications and added studies from two previous reviews that fulfilled the eligibility criteria. We included prospective and retrospective studies with any follow-up period that recruited adults aged 65 and over and developed a prediction model predicting unplanned hospitalizations. We included models with at least one (internal or external) validation cohort. The models had to be intended to be used in a primary care setting. Two authors independently assessed studies for inclusion and undertook data extraction following recommendations of the CHARMS checklist, while quality assessment was performed using the PROBAST tool. A total of 19 studies met the inclusion criteria. Prediction horizon ranged from 4.5 months to 4 years. Most frequently included variables were specific medical diagnoses (n = 11), previous hospital admission (n = 11), age (n = 11), and sex or gender (n = 8). Predictive performance in terms of area under the curve ranged from 0.61 to 0.78. Models developed to predict potentially preventable hospitalizations tended to have better predictive performance than models predicting hospitalizations in general. Overall, risk of bias was high, predominantly in the analysis domain.ConclusionsModels developed to predict preventable hospitalizations tended to have better predictive performance than models to predict all-cause hospitalizations. There is however substantial room for improvement on the reporting and analysis of studies. We recommend better adherence to the TRIPOD guidelines.
| S-EPMC9506609 | biostudies-literature
Project description:OBJECTIVES:The primary objective of the review was to describe change that occurs in skeletal muscle during periods of unplanned hospitalisation in adult patients. The secondary objective was to examine the relationship between both physical activity and inflammation with the change in skeletal muscle. A further objective was to investigate the effect of interventions on change in skeletal muscle during periods of unplanned hospitalisation. DESIGN:A systematic review and meta-analyses. Embase, MEDLINE, CINAHL, AMED, PEDro and the Cochrane Library were searched for studies that included any measures of skeletal muscle (excluding pulmonary function) at two time points during unplanned hospitalisation. Studies that were set in critical care, or included patients with acute or progressive neurological illness, were excluded. RESULTS:Our search returned 27,809 unique articles, of which 35 met the inclusion criteria. Meta-analyses of change between baseline and follow-up in random effects models suggested that grip strength had an average increase: standardised mean difference (SMD) = 0.10 (95% CI: 0.03; 0.16); knee extension strength had an average reduction: SMD = -0.24 (95% CI: -0.33; -0.14); and mid-arm muscle circumference had an average reduction: SMD = -0.17 (95% CI: -0.22; -0.11). Inflammation appeared to be associated with greater loss of muscle strength. There was inconclusive evidence that the level of physical activity affects change in skeletal muscle. In regard to the effect of interventions, only exercise interventions were consistently associated with improved skeletal muscle outcomes. CONCLUSIONS:Adult patients who undergo an unplanned hospital admission may experience a small reduction in knee extension strength and mid-arm muscle mass. Prospective research is needed to clarify the contribution of confounding factors underlying the observations made in this review, with particular attention to levels of physical activity, and possible contributions from environmental factors and processes of hospital care.
| S-EPMC6319740 | biostudies-literature