Challenges and opportunities to developing a frailty index using electronic health record data

Hematological Malignancies in Older Patients: Focus on the Potential Role of a Geriatric Assessment Management

Geriatric assessment management is a multidimensional tool used to evaluate prognosis for clinical outcomes and targets for interventions in older adults with cancer receiving chemotherapy. In this review, we evaluated the possible application of geriatric assessment management (GAM) in hematological malignancies. In older patients with Diffuse Large B Cell Lymphoma, GAM might be helpful in both predicting planned hospital admissions and improving quality of life. In chronic myeloid leukemia, the Charlson Comorbidity Index demonstrates how comorbidities could affect treatment compliance and overall outcomes. In multiple myeloma, the application of different scores such as the International Myeloma Working Group Frailty Index and the Revised Myeloma Comorbidity Index can identify frail patients who need suitable interventions in treatment plan (reducing drug dose or changing treatment). Therefore, including GAM in the management plan of older patients with hematological malignancies may direct and optimize cancer care.

Big Data for Geriatric Oncology Research

Cancer is the second leading cause of death in North Carolina and approximately half of cancers are diagnosed in older adults (≥65 years). Cancer clinical trials in older adults are limited and there is a lack of evidence on optimal care strategies in this population. We highlight how big data can fill in gaps in geriatric oncology research.

Baseline correlates of frailty and its association with survival in United States veterans with acute myeloid leukemia

Frailty is an important construct to measure in acute myeloid leukemia (AML). We used the Veterans Affairs Frailty Index (VA-FI) - calculated using readily available data within the VA's electronic health records - to measure frailty in U.S. veterans with AML. Of the 1166 newly diagnosed and treated veterans with AML between 2012 and 2022, 722 (62%) veterans with AML were classified as frail (VA-FI > 0.2). At a median follow-up of 252.5 days, moderate-severely frail veterans had significantly worse survival than mildly frail, and non-frail veterans (median survival 179 vs. 306 vs. 417 days, p < .001). Increasing VA-FI severity was associated with higher mortality. A model with VA-FI in addition to the European LeukemiaNet (ELN) risk classification and other covariates statistically outperformed a model containing the ELN risk and other covariates alone (p < .001). These findings support the VA-FI as a tool to expand frailty measurement in research and clinical practice for informing prognosis in veterans with AML.

Automated Electronic Frailty Index-Identified Frailty Status and Associated Postsurgical Adverse Events

Importance

Electronic frailty index (eFI) is an automated electronic health record (EHR)-based tool that uses a combination of clinical encounters, diagnosis codes, laboratory workups, medications, and Medicare annual wellness visit data as markers of frailty status. The association of eFI with postanesthesia adverse outcomes has not been evaluated.

Objective

To examine the association of frailty, calculated as eFI at the time of the surgical procedure and categorized as fit, prefrail, or frail, with adverse events after elective noncardiac surgery.

Design, Setting, and Participants

This cohort study was conducted at a tertiary care academic medical center in Winston-Salem, North Carolina. The cohort included patients 55 years or older who underwent noncardiac surgery of at least 1 hour in duration between October 1, 2017, and June 30, 2021.

Exposure

Frailty calculated by the eFI tool. Preoperative eFI scores were calculated based on available data 1 day prior to the procedure and categorized as fit (eFI score: ≤0.10), prefrail (eFI score: >0.10 to ≤0.21), or frail (eFI score: >0.21).

Main Outcomes and Measures

The primary outcome was a composite of the following 8 adverse component events: 90-item Patient Safety Indicators (PSI 90) score, hospital-acquired conditions, in-hospital mortality, 30-day mortality, 30-day readmission, 30-day emergency department visit after surgery, transfer to a skilled nursing facility after surgery, or unexpected intensive care unit admission after surgery. Secondary outcomes were each of the component events of the composite.

Results

Of the 33 449 patients (median [IQR] age, 67 [61-74] years; 17 618 females [52.7%]) included, 11 563 (34.6%) were classified as fit, 15 928 (47.6%) as prefrail, and 5958 (17.8%) as frail. Using logistic regression models that were adjusted for age, sex, race and ethnicity, and comorbidity burden, patients with prefrail (odds ratio [OR], 1.24; 95% CI, 1.18-1.30; P < .001) and frail (OR, 1.71; 95% CI, 1.58-1.82; P < .001) statuses were more likely to experience postoperative adverse events compared with patients with a fit status. Subsequent adjustment for all other potential confounders or covariates did not alter this association. For every increase in eFI of 0.03 units, the odds of a composite of postoperative adverse events increased by 1.06 (95% CI, 1.03-1.13; P < .001).

Conclusions and Relevance

This cohort study found that frailty, as measured by an automatically calculated index integrated within the EHR, was associated with increased risk of adverse events after noncardiac surgery. Deployment of eFI tools may support screening and possible risk modification, especially in patients who undergo high-risk surgery.

Frailty and Inflammatory Bowel Disease: A Scoping Review of Current Evidence

Frailty is increasingly recognized as an important concept in patients with Inflammatory Bowel Disease (IBD). The aim of this scoping review is to summarize the current literature on frailty in IBD. We will discuss the definition of frailty, frailty assessment methods, the prevalence of frailty, risk factors for frailty and the prognostic value of frailty in IBD. A scoping literature search was performed using the PubMed database. Frailty prevalence varied from 6% to 53.9%, depending on the population and frailty assessment method. Frailty was associated with a range of adverse outcomes, including an increased risk for all-cause hospitalization and readmission, mortality in non-surgical setting, IBD-related hospitalization and readmission. Therefore, frailty assessment should become integrated as part of routine clinical care for older patients with IBD.

Associations among frailty and quality of life in older patients with cancer treated with chemotherapy

INTRODUCTION

Previous studies have suggested that frailty among older adults with cancer is associated with a variety of negative outcomes, including greater chemotherapy toxicity and worse survival. However, results often do not include patient-reported outcomes, such as quality of life (QOL). The objective of this study was to evaluate frailty prior to receipt of moderately- or highly-emetogenic chemotherapy and acute changes in QOL in patients at least 65 years of age. It was hypothesized that frail patients would report greater declines in QOL.

MATERIALS AND METHODS

Participants completed questionnaires before receiving their first infusion and again five days later. A 59-item deficit accumulation index score was created at baseline using a modified Rockwood frailty index. QOL was assessed using the Functional Assessment of Cancer Therapy-General (FACT-G). The relationship between baseline frailty and QOL was evaluated using a dichotomized deficit accumulation index (frail vs. robust) in repeated measures ANOVA.

RESULTS

Study participants (n = 151) had a mean age of 72 (SD = 4.5) and 62% were female. Nearly half (42%) were frail at baseline. Frail participants reported worse QOL at baseline compared to robust participants. Frail patients reported smaller declines in overall and physical (p < 0.0001) and emotional (p = 0.006) QOL from baseline to five days after receiving chemotherapy. At five days, frail participants reported better emotional and physical QOL compared to robust participants.

DISCUSSION

Contrary to expectations, frail patients reported smaller declines in QOL compared to robust patients using a deficit accumulation index. These results can be used to help educate frail patients on what to expect during treatment.

Identifying Frail Patients by Using Electronic Health Records in Primary Care: Current Status and Future Directions

With the rapidly aging population, frailty, characterized by an increased risk of adverse outcomes, has become a major public health problem globally. Several frailty guidelines or consensuses recommend screening for frailty, especially in primary care settings. However, most of the frailty assessment tools are based on questionnaires or physical examinations, adding to the clinical workload, which is the major obstacle to converting frailty research into clinical practice. Medical data naturally generated by routine clinical work containing frailty indicators are stored in electronic health records (EHRs) (also called electronic health record (EHR) data), which provide resources and possibilities for frailty assessment. We reviewed several frailty assessment tools based on primary care EHRs and summarized the features and novel usage of these tools, as well as challenges and trends. Further research is needed to develop and validate frailty assessment tools based on EHRs in primary care in other parts of the world.

Contemporary Analysis of Electronic Frailty Measurement in Older Adults with Multiple Myeloma Treated in the National US Veterans Affairs Healthcare System

Simple Summary

Geriatric and frailty assessment are recommended for all older adults with cancer undergoing systemic therapy, but assessments remain difficult to scale. The aim of this study was to use an electronic frailty index based on data from administrative claims and electronic health records—the Veterans Affairs Frailty Index (VA-FI-10)—to estimate frailty and its impact on older United States (US) military veterans treated for multiple myeloma (MM) throughout the national VA Healthcare System. We found frailty to be prevalent and strongly associated with mortality and hospitalizations—independently of age, race, and MM stage. We also showed that changing the way in which the VA-FI-10 is measured affects its classification of frailty for individual veterans but not its association with mortality. These findings support the VA-FI-10’s use in research investigating outcomes in frail veterans treated with contemporary MM therapies. We provide further insights into the VA-FI-10’s potential use in clinical practice.

Abstract

Electronic frailty indices based on data from administrative claims and electronic health records can be used to estimate frailty in large populations of older adults with cancer where direct frailty measures are lacking. The objective of this study was to use the electronic Veterans Affairs Frailty Index (VA-FI-10)—developed and validated to measure frailty in the national United States (US) VA Healthcare System—to estimate the prevalence and impact of frailty in older US veterans newly treated for multiple myeloma (MM) with contemporary therapies. We designed a retrospective cohort study of 4924 transplant-ineligible veterans aged ≥ 65 years initiating MM therapy within VA from 2004 to 2017. Initial MM therapy was measured using inpatient and outpatient treatment codes from pharmacy data in the VA Corporate Data Warehouse. In total, 3477 veterans (70.6%) were classified as frail (VA-FI-10 > 0.2), with 1510 (30.7%) mildly frail (VA-FI-10 > 0.2–0.3), 1105 (22.4%) moderately frail (VA-FI-10 > 0.3–0.4), and 862 (17.5%) severely frail (VA-FI-10 > 0.4). Survival and time to hospitalization decreased with increasing VA-FI-10 severity (log-rank p-value < 0.001); the VA-FI-10 predicted mortality and hospitalizations independently of age, sociodemographic variables, and measures of disease risk. Varying data sources and assessment periods reclassified frailty severity for a substantial portion of veterans but did not substantially affect VA-FI-10’s association with mortality. Our study supports use of the VA-FI-10 in future research involving older veterans with MM and provides insights into its potential use in identifying frailty in clinical practice.