Frailty Is Associated With Decreased Time Spent at Home After Critical Illness: A Population-Based Study

Cross-sectional and longitudinal associations among healthcare costs and deficit accumulation

BACKGROUND

Type 2 diabetes mellitus and overweight/obesity increase healthcare costs. Both are also associated with accelerated aging. However, the contributions of this accelerated aging to increased healthcare costs are unknown.

METHODS

We use data from a 8-year longitudinal cohort followed at 16 U.S. clinical research sites. Participants were adults aged 45-76 years with established type 2 diabetes and overweight or obesity who had enrolled in the Action for Health in Diabetes clinical trial. They were randomly (1:1) assigned to either an intensive lifestyle intervention focused on weight loss versus a comparator of diabetes support and education. A validated deficit accumulation frailty index (FI) was used to characterize biological aging. Discounted annual healthcare costs were estimated using national databases in 2012 dollars. Descriptive characteristics were collected by trained and certified staff.

RESULTS

Compared with participants in the lowest tertile (least frail) of baseline FI, those in the highest tertile (most frail) at Year 1 averaged $714 (42%) higher medication costs, $244 (22%) higher outpatient costs, and $800 (134%) higher hospitalization costs (p < 0.001). At Years 4 and 8, relatively greater increases in FI (third vs. first tertile) were associated with an approximate doubling of total healthcare costs (p < 0.001). Mean (95% confidence interval) relative annual savings in healthcare costs associated with randomization to the intensive lifestyle intervention were $437 ($195, $579) per year during Years 1-4 and $461 ($232, $690) per year during Years 1-8. These were attenuated and the 95% confidence interval no longer excluded $0 after adjustment for the annual FI differences from baseline.

CONCLUSIONS

Deficit accumulation frailty tracks well with healthcare costs among adults with type 2 diabetes and overweight or obesity. It may serve as a useful marker to project healthcare needs and as an intermediate outcome in clinical trials.

Identifying Predictors of Nursing Home Admission by Using Electronic Health Records and Administrative Data: Scoping Review

Background

Among older adults, nursing home admissions (NHAs) are considered a significant adverse outcome and have been extensively studied. Although the volume and significance of electronic data sources are expanding, it is unclear what predictors of NHA have been systematically identified in the literature via electronic health records (EHRs) and administrative data.

Objective

This study synthesizes findings of recent literature on identifying predictors of NHA that are collected from administrative data or EHRs.

Methods

The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines were used for study selection. The PubMed and CINAHL databases were used to retrieve the studies. Articles published between January 1, 2012, and March 31, 2023, were included.

Results

A total of 34 papers were selected for final inclusion in this review. In addition to NHA, all-cause mortality, hospitalization, and rehospitalization were frequently used as outcome measures. The most frequently used models for predicting NHAs were Cox proportional hazards models (studies: n=12, 35%), logistic regression models (studies: n=9, 26%), and a combination of both (studies: n=6, 18%). Several predictors were used in the NHA prediction models, which were further categorized into sociodemographic, caregiver support, health status, health use, and social service use factors. Only 5 (15%) studies used a validated frailty measure in their NHA prediction models.

Conclusions

NHA prediction tools based on EHRs or administrative data may assist clinicians, patients, and policy makers in making informed decisions and allocating public health resources. More research is needed to assess the value of various predictors and data sources in predicting NHAs and validating NHA prediction models externally.

Outcomes and cost analysis of patients with dementia in the intensive care unit: a population-based cohort study

BACKGROUND

Dementia is a neurological syndrome affecting the growing elderly population. While patients with dementia are known to require significant hospital resources, little is known regarding the outcomes and costs of patients admitted to the intensive care unit (ICU) with dementia.

METHODS

We conducted a population-based retrospective cohort study of patients with dementia admitted to the ICU in Ontario, Canada from 2016 to 2019. We described the characteristics and outcomes of these patients alongside those with dementia admitted to non-ICU hospital settings. The primary outcome was hospital mortality but we also assessed length of stay (LOS), discharge disposition, and costs.

RESULTS

Among 114,844 patients with dementia, 11,341 (9.9%) were admitted to the ICU. ICU patients were younger, more comorbid, and had less cognitive impairment (81.8 years, 22.8% had ≥ 3 comorbidities, 47.5% with moderate-severe dementia), compared to those in non-ICU settings (84.2 years, 15.0% had ≥ 3 comorbidities, 54.1% with moderate-severe dementia). Total mean LOS for patients in the ICU group was nearly 20 days, compared to nearly 14 days for the acute care group. Mortality in hospital was nearly three-fold greater in the ICU group compared to non-ICU group (22.2% vs. 8.8%). Total healthcare costs were increased for patients admitted to ICU vs. those in the non-ICU group ($67,201 vs. $54,080).

CONCLUSIONS

We find that patients with dementia admitted to the ICU have longer length of stay, higher in-hospital mortality, and higher total healthcare costs. As our study is primarily descriptive, future studies should investigate comprehensive goals of care planning, severity of illness, preventable costs, and optimizing quality of life in this high risk and vulnerable population.

Medication optimization according to the Fit fOR The Aged (FORTA) rules improves functional status in patients hospitalized for geriatric rehabilitation

INTRODUCTION

Functional status is one of the most important issues of geriatric care. Polypharmacy seems to be a modifiable factor associated with functional decline in older adults. However, the impact of pharmacotherapy optimization on the activities of daily living in patients undergoing geriatric rehabilitation has not been investigated prospectively so far.

METHODS

This post hoc analysis of a subsample of the VALFORTA study included individuals only undergoing geriatric rehabilitation with a length of in-hospital stay of at least 14 days. Medication was modified according to the FORTA rules in the intervention group while in the control group standard drug treatment was applied. Both groups received comprehensive geriatric treatment.

RESULTS

The intervention and control groups consisted of 96 and 93 individuals respectively. They did not differ according to basic data except for age and Charlson Comorbidity Index (CCI) on admission. On discharge, activities of daily living (Barthel index, BI) were improved in both groups. An increase of at least 20 points of the BI was observed in 40% of patients in the intervention group and in 12% of patients in the control group (p< 0.001). Logistic regression analysis with an increase of at least 20 BI-points was significantly and independently associated with patient group (2.358, p< 0.02), BI on admission (0.957, p< 0.001), and the CCI (0.793, p< 0.041).

CONCLUSION

This post hoc analysis of a subsample of older individuals hospitalized for geriatric rehabilitation demonstrates a significant additional improvement in activities of daily living by modification of medication according to FORTA.

REGISTRATION

DRKS-ID: DRKS00000531.

The Association of Frailty With Long-Term Outcomes in Patients With Acute Respiratory Failure Treated With Noninvasive Ventilation

The objective of this study was to investigate the prevalence and impact of frailty on mortality in patients with acute respiratory failure (ARF) treated with noninvasive ventilation (NIV). This was a single-center, prospective study of patients who developed ARF (irrespective of etiology) and were treated with NIV support. Frailty was assessed using the Clinical Frailty Scale (CFS). We modeled the relationship of CFS with one-year mortality using Cox proportional hazards regression, adjusting for other clinical and demographic characteristics. Of the 166 patients enrolled, 48% had moderate to severe frailty. These patients were more likely to be female (67% versus 33%) and on oxygen therapy at home (46% versus 28%). The median CFS score was 5 (interquartile range (IQR): 5-6). Moderate to severe frailty was associated with a 60% higher risk of one-year mortality (hazard ratio (HR): 1.63, 95% confidence interval (CI): 1.15-2.31). Frailty assessment may identify patients in need of ventilatory support who are at increased risk of mortality and may be an important factor to consider when discussing goals of care in this vulnerable population.

Association Between Frailty and Time Alive and At Home After Cancer Surgery Among Older Adults: A Population-Based Analysis

BACKGROUND

Although frailty is known to impact short-term postoperative outcomes, its long-term impact is unknown. This study examined the association between frailty and remaining alive and at home after cancer surgery among older adults.

METHODS

Adults aged ≥70 years undergoing cancer resection were included in this population-based retrospective cohort study using linked administrative datasets in Ontario, Canada. The probability of remaining alive and at home in the 5 years after cancer resection was evaluated using Kaplan-Meier methods. Extended Cox regression with time-varying effects examined the association between frailty and remaining alive and at home.

RESULTS

Of 82,037 patients, 6,443 (7.9%) had preoperative frailty. With median follow-up of 47 months (interquartile range, 23-81 months), patients with frailty had a significantly lower probability of remaining alive and at home 5 years after cancer surgery compared with those without frailty (39.1% [95% CI, 37.8%-40.4%] vs 62.5% [95% CI, 62.1%-63.9%]). After adjusting for age, sex, rural living, material deprivation, immigration status, cancer type, surgical procedure intensity, year of surgery, and receipt of perioperative therapy, frailty remained associated with increased hazards of not remaining alive and at home. This increase was highest 31 to 90 days after surgery (hazard ratio [HR], 2.00 [95% CI, 1.78-2.24]) and remained significantly elevated beyond 1 year after surgery (HR, 1.56 [95% CI, 1.48-1.64]). This pattern was observed across cancer sites, including those requiring low-intensity surgery (breast and melanoma).

CONCLUSIONS

Preoperative frailty was independently associated with a decreased probability of remaining alive and at home after cancer surgery among older adults. This relationship persisted over time for all cancer types beyond short-term mortality and the initial postoperative period. Frailty assessment may be useful for all candidates for cancer surgery, and these data can be used when counseling, selecting, and preparing patients for surgery.

Feasibility of Extracting Meaningful Patient Centered Outcomes From the Electronic Health Record Following Critical Illness in the Elderly

Background

Meaningful patient centered outcomes of critical illness such as functional status, cognition and mental health are studied using validated measurement tools that may often be impractical outside the research setting. The Electronic health record (EHR) contains a plethora of information pertaining to these domains. We sought to determine how feasible and reliable it is to assess meaningful patient centered outcomes from the EHR.

Methods

Two independent investigators reviewed EHR of a random sample of ICU patients looking at documented assessments of trajectory of functional status, cognition, and mental health. Cohen's kappa was used to measure agreement between 2 reviewers. Post ICU health in these domains 12 month after admission was compared to pre- ICU health in the 12 months prior to assess qualitatively whether a patient's condition was “better,” “unchanged” or “worse.” Days alive and out of hospital/health care facility was a secondary outcome.

Results

Thirty six of the 41 randomly selected patients (88%) survived critical illness. EHR contained sufficient information to determine the difference in health status before and after critical illness in most survivors (86%). Decline in functional status (36%), cognition (11%), and mental health (11%) following ICU admission was observed compared to premorbid baseline. Agreement between reviewers was excellent (kappa ranging from 0.966 to 1). Eighteen patients (44%) remained home after discharge from hospital and rehabilitation during the 12- month follow up.

Conclusion

We demonstrated the feasibility and reliability of assessing the trajectory of changes in functional status, cognition, and selected mental health outcomes from EHR of critically ill patients. If validated in a larger, representative sample, these outcomes could be used alongside survival in quality improvement studies and pragmatic clinical trials.

Characteristics and resource utilization of high-cost users in the intensive care unit: a population-based cohort study

Background

Healthcare expenditure within the intensive care unit (ICU) is costly. A cost reduction strategy may be to target patients accounting for a disproportionate amount of healthcare spending, or high-cost users. This study aims to describe high-cost users in the ICU, including health outcomes and cost patterns.

Methods

We conducted a population-based retrospective cohort study of patients with ICU admissions in Ontario from 2011 to 2018. Patients with total healthcare costs in the year following ICU admission (including the admission itself) in the upper 10th percentile were defined as high-cost users. We compared characteristics and outcomes including length of stay, mortality, disposition, and costs between groups.

Results

Among 370,061 patients included, 37,006 were high-cost users. High-cost users were 64.2 years old, 58.3% male, and had more comorbidities (41.2% had ≥3) when likened to non-high cost users (66.1 years old, 57.2% male, 27.9% had ≥3 comorbidities). ICU length of stay was four times greater for high-cost users compared to non-high cost users (22.4 days, 95% confidence interval [CI] 22.0–22.7 days vs. 5.56 days, 95% CI 5.54–5.57 days). High-cost users had lower in-hospital mortality (10.0% vs.14.2%), but increased dispositioning outside of home (77.4% vs. 42.2%) compared to non-high-cost users. Total healthcare costs were five-fold higher for high-cost users ($238,231, 95% CI $237,020–$239,442) compared to non-high-cost users ($45,155, 95% CI $45,046–$45,264). High-cost users accounted for 37.0% of total healthcare costs.

Conclusion

High-cost users have increased length of stay, lower in-hospital mortality, and higher total healthcare costs when compared to non-high-cost users. Further studies into cost patterns and predictors of high-cost users are necessary to identify methods of decreasing healthcare expenditure.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07318-y.

A Population-Based Analysis of Long-Term Outcomes Among Older Adults Requiring Unexpected Intensive Care Unit Admission After Cancer Surgery

BACKGROUND

High-intensity cancer surgery is increasingly common among older adults. However, these patients are at high-risk for unexpected intensive care unit (ICU) admissions after surgery. How these admissions impact older adults' long-term outcomes is unknown.

METHODS

We performed a population-based, cohort study of older adults (age ≥ 70 years) who underwent high-intensity cancer surgery from 2007 to 2017. Analyses were performed to examine time alive and at home following surgery, defined as time from surgery to nursing home admission or death. Patients were followed for up to 5 years. Extended Cox proportional hazards models examined the independent association between unexpected ICU admission (ICU admissions excluding routine postoperative monitoring) and remaining alive and at home. Subgroup analysis stratified patients by duration of mechanical ventilation (MV).

RESULTS

Of 47,367 identified older adults, 7372 (15.6%) had an unexpected ICU admission. Patients with an unexpected ICU admission had a significantly lower probability of being alive and at home at 5 years (26.2%; 95% confidence interval [CI] 25.1-27.2%) compared with those without an unexpected admission (56.8%; 95% CI 56.3-57.4%). After adjusting for baseline characteristics, unexpected ICU admission remained associated with less time alive and at home. The elevated risk of death or nursing home admission persisted for 5 years after surgery (years 2-5: hazard ratio [HR] 1.58, 95% CI 1.50-1.66). Duration of MV was inversely associated with time alive and at home.

CONCLUSIONS

Older adults with an unexpected ICU admission after high-intensity cancer surgery are at increased risk for death or admission to a nursing home for at least 5 years.

Baseline Frailty as a Predictor of Survival After Critical Care: A Retrospective Cohort Study of Older Adults Receiving Home Care in Ontario, Canada

BACKGROUND

The extent to which the degree of baseline frailty, as measured using standardized multidimensional health assessments before hospital admission, predicts survival among older adults after admission to an ICU, remains unclear.

RESEARCH QUESTION

Is baseline frailty an independent predictor of survival among older adults receiving care in an ICU?

STUDY DESIGN AND METHODS

Retrospective cohort study of community-dwelling older adults (age, ≥ 65 years) receiving public home services who were admitted to any ICU in Ontario, Canada, between April 1, 2009, and March 31, 2015. All individuals underwent an inter-Resident Assessment Instrument-Home Care (RAI-HC) assessment completed within 180 days of ICU admission. These assessments were linked to hospital discharge abstract records. Patients were categorized using frailty measures each calculated from the RAI-HC: a classification tree version of the Clinical Frailty Scale; the Frailty Index-Acute Care; and the Changes in Health, End-Stage Disease, Signs, and Symptoms Scale. One-year survival models were used to compare their performance. Patients were stratified based on the receipt of mechanical ventilation in the ICU.

RESULTS

Of 24,499 individuals admitted to an ICU within 180 days of a RAI-HC assessment, 26.4% (n = 6,467) received mechanical ventilation. Overall, 43.0% (95% CI, 42.4%-43.6%) survived 365 days after ICU admission. In general, among the overall cohort and both mechanical ventilation subgroups, mortality hazards increased with the severity of baseline frailty. Models predicting survival 30, 90, and 365 days after admission to an ICU that adjusted for one of the frailty measures were more discriminant than reference models that adjusted only for age, sex, major clinical category, and area income quintile.

INTERPRETATION

Severity of baseline frailty is associated independently with survival after ICU admission and should be considered when determining goals of care and treatment plans for people with critical illness.

Frailty and long-term outcomes following critical illness: A population-level cohort study

PURPOSE

To provide population-level estimates of the association of frailty with one-year outcomes after critical illness.

MATERIALS AND METHODS

Retrospective cohort study of patients who survived an ICU admission between April 2002 and March 2015. Pre-existing frailty was classified using the Johns Hopkins Adjusted Clinical Groups frailty indicator. Multivariable Cox regression and Fine and Gray models were used to examine the association between frailty and mortality and hospital readmission.

RESULTS

Of 534,991 patients, 19.3% had pre-existing frailty. Compared to non-frail survivors, at one-year frail patients had higher mortality (18.3% vs 9.5%, adjusted HR 1.17 95% CI: 1.15-1.19) and hospital readmission (44.4% vs 36.6%, adjusted HR 1.10 95% CI: 1.08-1.11) and a CAN$19,628 (95% CI: $19,279-$19,997) greater increase in healthcare costs compared to the year prior to hospitalization. The association between frailty and mortality was stronger among older individuals, but the risk of readmission among frail patients decreased with age.

CONCLUSION

Patients with pre-existing frailty who develop critical illness have higher rates of hospital readmission and death than patients without frailty, and age modifies these associations. These data highlight the importance of considering both frailty and age when seeking to identify at-risk patients who might benefit from closer follow-up after discharge.