Claims-based Frailty Indices: A Systematic Review

Adaptation of the Risk Analysis Index for Frailty Assessment Using Diagnostic Codes

Importance

Frailty is associated with adverse outcomes after even minor physiologic stressors. The validated Risk Analysis Index (RAI) quantifies frailty; however, existing methods limit application to in-person interview (clinical RAI) and quality improvement datasets (administrative RAI).

Objective

To expand the utility of the RAI utility to available International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) administrative data, using the National Inpatient Sample (NIS).

Design, Setting, and Participants

RAI parameters were systematically adapted to ICD-10-CM codes (RAI-ICD) and were derived (NIS 2019) and validated (NIS 2020). The primary analysis included survey-weighed discharge data among adults undergoing major surgical procedures. Additional external validation occurred by including all operative and nonoperative hospitalizations in the NIS (2020) and in a multihospital health care system (UPMC, 2021-2022). Data analysis was conducted from January to May 2023.

Exposures

RAI parameters and in-hospital mortality.

Main Outcomes and Measures

The association of RAI parameters with in-hospital mortality was calculated and weighted using logistic regression, generating an integerized RAI-ICD score. After initial validation, thresholds defining categories of frailty were selected by a full complement of test statistics. Rates of elective admission, length of stay, hospital charges, and in-hospital mortality were compared across frailty categories. C statistics estimated model discrimination.

Results

RAI-ICD parameters were weighted in the 9 548 206 patients who were hospitalized (mean [SE] age, 55.4 (0.1) years; 3 742 330 male [weighted percentage, 39.2%] and 5 804 431 female [weighted percentage, 60.8%]), modeling in-hospital mortality (2.1%; 95% CI, 2.1%-2.2%) with excellent derivation discrimination (C statistic, 0.810; 95% CI, 0.808-0.813). The 11 RAI-ICD parameters were adapted to 323 ICD-10-CM codes. The operative validation population of 8 113 950 patients (mean [SE] age, 54.4 (0.1) years; 3 148 273 male [weighted percentage, 38.8%] and 4 965 737 female [weighted percentage, 61.2%]; in-hospital mortality, 2.5% [95% CI, 2.4%-2.5%]) mirrored the derivation population. In validation, the weighted and integerized RAI-ICD yielded good to excellent discrimination in the NIS operative sample (C statistic, 0.784; 95% CI, 0.782-0.786), NIS operative and nonoperative sample (C statistic, 0.778; 95% CI, 0.777-0.779), and the UPMC operative and nonoperative sample (C statistic, 0.860; 95% CI, 0.857-0.862). Thresholds defining robust (RAI-ICD <27), normal (RAI-ICD, 27-35), frail (RAI-ICD, 36-45), and very frail (RAI-ICD >45) strata of frailty maximized precision (F1 = 0.33) and sensitivity and specificity (Matthews correlation coefficient = 0.26). Adverse outcomes increased with increasing frailty.

Conclusion and Relevance

In this cohort study of hospitalized adults, the RAI-ICD was rigorously adapted, derived, and validated. These findings suggest that the RAI-ICD can extend the quantification of frailty to inpatient adult ICD-10-CM-coded patient care datasets.

Longitudinal Patterns of Multimorbidity in Gulf War Era Veterans With and Without Gulf War Illness

Objectives: To examine whether severe Gulf War illness (SGWI) case status was associated with longitudinal multimorbidity patterns. Methods: Participants were users of the Veteran Health Administration Health Care System drawn from the Gulf War Era Cohort and Biorepository (n = 840). Longitudinal measures of multimorbidity were constructed using (1) electronic health records (Charlson Comorbidity Index; Elixhauser; and Veterans Affairs Frailty Index) from 10/1/1999 to 6/30/2023 and (2) self-reported medical conditions (Deficit Accumulation Index) since the war until the survey date. Accelerated failure time models examined SGWI case status as a predictor of time until threshold level of multimorbidity was reached, adjusted for age and sociodemographic and military characteristics. Results: Models, adjusted for covariates, revealed that (1) relative to the SWGI- group, the SGWI+ group was associated with an accelerated time for reaching each threshold and (2) the relationship between SGWI and each threshold was not moderated by age. Discussion: Findings suggest that veterans with SGWI experienced accelerated aging.

Comparative Performance of Three Claims-Based Frailty Measures Among Medicare Beneficiaries

Frailty is an important predictor of mortality, health care costs and utilization, and health outcomes. Validated measures of frailty are not consistently collected during clinical encounters, making comparisons across populations challenging. However, several claims-based algorithms have been developed to predict frailty and related concepts. This study compares performance of three such algorithms among Medicare beneficiaries. Claims data from 12-month continuous enrollment periods were selected during 2014-2016. Frailty scores, calculated using previously developed algorithms from Faurot, Kim, and RAND, were added to baseline regression models to predict claims-based outcomes measured in the following year. Root mean square error and area under the receiver operating characteristic curve were calculated for each model and outcome combination and tested in subpopulations of interest. Overall, Kim models performed best across most outcomes, metrics, and subpopulations. Kim frailty scores may be used by health systems and researchers for risk adjustment or targeting interventions.

Around the EQUATOR with Clin-STAR: Prediction modeling opportunities and challenges in aging research

The 2015 Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Statement was published to improve reporting transparency for prediction modeling studies. The objective of this review is to highlight methodologic challenges that aging-focused researchers will encounter when designing and reporting studies involving prediction models for older adults and provide guidance for addressing these challenges. In following the 22-item TRIPOD checklist, researchers must consider the representativeness of cohorts used (e.g., whether older adults with frailty, cognitive impairment, and social isolation were included), strategies for incorporating common geriatric predictors (e.g., age, comorbidities, functional status, and frailty), methods for handling missing data and competing risk of death, and assessment of model performance heterogeneity across important subgroups (e.g., age, sex, race, and ethnicity). We provide guidance to help aging-focused researchers develop, validate, and report models that can inform and improve patient care, which we label "TRIPOD-65."

Validated frailty measures using electronic primary care records: a review of diagnostic test accuracy

INTRODUCTION

Identification of people who have or are at risk of frailty enables targeted interventions, and the use of tools that screen for frailty using electronic records (which we term as validated electronic frailty measures (VEFMs)) within primary care is incentivised by NHS England. We carried out a systematic review to establish the sensitivity and specificity of available primary care VEFMs when compared to a reference standard in-person assessment.

METHODS

Medline, Pubmed, CENTRAL, CINHAL and Embase searches identified studies comparing a primary care VEFM with in-person assessment. Studies were quality assessed using Quality Assessment of Diagnostic Accuracy Studies revised tool. Sensitivity and specificity values were extracted or were calculated and pooled using StatsDirect.

RESULTS

There were 2,245 titles screened, with 10 studies included. These described three different index tests: electronic frailty index (eFI), claims-based frailty index (cFI) and polypharmacy. Frailty Phenotype was the reference standard in each study. One study of 60 patients examined the eFI, reporting a sensitivity of 0.84 (95% CI = 0.55, 0.98) and a specificity of 0.78 (0.64, 0.89). Two studies of 7,679 patients examined cFI, with a pooled sensitivity of 0.48 (95% CI = 0.23, 0.74) and a specificity of 0.80 (0.53, 0.98). Seven studies of 34,328 patients examined a polypharmacy as a screening tool (defined as more than or equal to five medications) with a pooled sensitivity of 0.61 (95% CI = 0.50, 0.72) and a specificity of 0.66 (0.58, 0.73).

CONCLUSIONS

eFI is the best-performing VEFM; however, based on our analysis of an average UK GP practice, it would return a high number of false-positive results. In conclusion, existing electronic frailty tools may not be appropriate for primary care-based population screening.

Do Home- and Community-Based Services Delay Frailty Onset in Older Adults With Low Care Needs?

OBJECTIVES

To assess whether using adult day services or personal assistance services can delay the onset of frailty among older adults with low care needs during a 5-year follow-up study.

DESIGN

This prospective cohort study was conducted using long-term care and health insurance claims data.

SETTING AND PARTICIPANTS

This was a population-based study of 3 municipalities in Osaka, Japan. Initially, 655 nonfrail or prefrail individuals were included from a cohort of 790 population-based adults aged ≥65 years, who were newly certified as being on a support level of the long-term care insurance program from September 2012 to March 2013.

METHODS

Using long-term care and health insurance claims data from the Southern Osaka Health and Aging Study, conducted between April 2012 and March 2017, monthly usage of adult day and personal assistance services was measured. Data were analyzed from December 2021 to January 2022.

RESULTS

Of the 655 individuals (median age at baseline: 79 years), 436 (66.6%) were female, 388 (59.2%) were nonfrail, and 267 (40.8%) were prefrail, according to the Veterans Affairs Frailty Index. During the 5-year follow-up period, 222 individuals (33.9%) experienced the onset of frailty. The time-dependent Cox regression models showed that using adult day services lowered the risk of frailty when compared with not using such services [hazard ratio (HR) 0.60, 95% CI 0.42-0.86; P = .006], although personal assistance services usage was not associated with the onset of frailty (HR 0.70, 95% CI 0.48-1.03, P = .07).

CONCLUSIONS AND IMPLICATIONS

Using adult day services lowered the risk of frailty in older adults with low care needs over the 5-year follow-up period. The findings support the value of providing adult day services to prevent frailty for those in need of long-term care.

Impact of Frailty on Clinical Outcomes in Patients With Atrial Fibrillation Who Underwent Cardiac Ablation Using a Nationwide Database

This study aimed to assess the association between frailty and clinical outcomes in patients with atrial fibrillation (AF) who undergo catheter ablation. We conducted a retrospective cohort study using the National Inpatient Sample database from 2017 to 2019. Adult patients hospitalized with a primary diagnosis of AF who underwent catheter ablation were included. Frailty was assessed using the Hospital Frailty Risk Score. The primary outcome was the presence of any complication (vascular, cardiac, respiratory, neurologic, or infectious), and secondary outcomes were in-hospital mortality, length of hospital stay, and hospital charges. A total of 21,075 weighted hospitalizations were included, and 14% were classified as intermediate or great risk of frailty. Patients with intermediate (adjusted relative risk 2.86, 95% confidence interval 2.24 to 3.67) and great (adjusted relative risk 6.68, 95% confidence interval 3.77 to 11.84) risk of frailty were associated with a greater risk of any complication than that of the group at less risk. The in-hospital mortality rate was significantly higher among patients at intermediate risk than among those at less risk of frailty (2.6% vs 0.1%, p <0.001). Patients with great and intermediate risk had significantly longer hospital stays than did the group with less risk (median 14 vs 5 vs 2 days, p <0.001), in addition to greater total charges (median $189,072 vs $161,598 vs $130,672, p <0.001), respectively. In conclusion, frailty was associated with a greater risk of poor short-term outcomes in patients with AF who underwent catheter ablation. The Hospital Frailty Risk Score is a useful tool for identifying patients at increased risk of adverse events and could aid in preoperative optimization and postoperative management.

Value-Based Payment for Clinicians Treating Cardiovascular Disease: A Policy Statement From the American Heart Association

Clinician payment is transitioning from fee-for-service to value-based payment, with reimbursement tied to health care quality and cost. However, the overarching goals of value-based payment-to improve health care quality, lower costs, or both-have been largely unmet. This policy statement reviews the current state of value-based payment and provides recommended best practices for future design and implementation. The policy statement is divided into sections that detail different aspects of value-based payment: (1) key program design features (patient population, quality measurement, cost measurement, and risk adjustment), (2) the role of equity during design and evaluation, (3) adjustment of payment, and (4) program implementation and evaluation. Each section introduces the topic, describes important considerations, and lists examples from existing programs. Each section includes recommended best practices for future program design. The policy statement highlights 4 key themes for successful value-based payment. First, programs should carefully weigh the incentives between lowering cost and improving quality of care and ensure that there is adequate focus on quality of care. Second, the expansion of value-based payment should be a tool for improving equity, which is central to quality of care and should be a focal point of program design and evaluation. Third, value-based payment should continue to move away from fee for service toward more flexible funding that allows clinicians to focus resources on the interventions that best help patients. Last, successful programs should find ways to channel clinicians' intrinsic motivation to improve their performance and the care for their patients. These principles should guide the future development of clinician value-based payment models.

Association Between Claims-Defined Frailty and Outcomes Following 30 Versus 12 Months of Dual Antiplatelet Therapy After Percutaneous Coronary Intervention: Findings From the EXTEND-DAPT Study

Background Frailty is rarely assessed in clinical trials of patients who receive dual antiplatelet therapy (DAPT) after percutaneous coronary intervention. This study investigated whether frailty defined using claims data is associated with outcomes following percutaneous coronary intervention, and if there is a differential association in patients receiving standard versus extended duration DAPT. Methods and Results Patients ≥65 years of age in the DAPT (Dual Antiplatelet Therapy) Study, a randomized trial comparing 30 versus 12 months of DAPT following percutaneous coronary intervention, had data linked to Medicare claims (n=1326), and a previously validated claims-based index was used to define frailty. Net adverse clinical events, a composite of all-cause mortality, myocardial infarction, stroke, and major bleeding, were compared between frail and nonfrail patients. Patients defined as frail using claims data (12.0% of the cohort) had higher incidence of net adverse clinical events (23.1%) compared with nonfrail patients (10.7%; P<0.001) at 18-month follow-up and increased risk after multivariable adjustment (adjusted hazard ratio [HR], 2.24 [95% CI, 1.38-3.63]). There were no differences in effects of extended duration DAPT on net adverse clinical events for frail (HR, 1.42 [95% CI, 0.73-2.75]) and nonfrail patients (HR, 1.18 [95% CI, 0.83-1.68]; interaction P=0.61), although analyses were underpowered. Bleeding was highest among frail patients who received extended duration DAPT. Conclusions Among older patients in the DAPT Study, claims-defined frailty was associated with higher net adverse clinical events. Effects of extended duration DAPT were not different for frail patients, although comparisons were underpowered. Further investigation of how frailty influences ischemic and bleeding risks with DAPT are warranted. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT00977938.

Incremental Health Care Costs of Self-Reported Functional Impairments and Phenotypic Frailty in Community-Dwelling Older Adults : A Prospective Cohort Study

BACKGROUND

Health care systems need better strategies to identify older adults at risk for costly care to select target populations for interventions to reduce health care burden.

OBJECTIVE

To determine whether self-reported functional impairments and phenotypic frailty are associated with incremental health care costs after accounting for claims-based predictors.

DESIGN

Prospective cohort study.

SETTING

Index examinations (2002 to 2011) of 4 prospective cohort studies linked with Medicare claims.

PARTICIPANTS

8165 community-dwelling fee-for-service beneficiaries (4318 women, 3847 men).

MEASUREMENTS

Weighted (Centers for Medicare & Medicaid Services Hierarchical Condition Category index) and unweighted (count of conditions) multimorbidity and frailty indicators derived from claims. Self-reported functional impairments (difficulty performing 4 activities of daily living) and frailty phenotype (operationalized using 5 components) derived from cohort data. Health care costs ascertained for 36 months after index examinations.

RESULTS

Average annualized costs (2020 U.S. dollars) were $13 906 among women and $14 598 among men. After accounting for claims-based indicators, average incremental costs of functional impairments versus no impairment in women (men) were $3328 ($2354) for 1 impairment increasing to $7330 ($11 760) for 4 impairments; average incremental costs of phenotypic frailty versus robust in women (men) were $8532 ($6172). Mean predicted costs adjusted for claims-based indicators in women (men) varied by both functional impairments and the frailty phenotype ranging from $8124 ($11 831) among robust persons without impairments to $18 792 ($24 713) among frail persons with 4 impairments. Compared with the model with claims-derived indicators alone, this model resulted in more accurate cost prediction for persons with multiple impairments or phenotypic frailty.

LIMITATION

Cost data limited to participants enrolled in the Medicare fee-for-service program.

CONCLUSION

Self-reported functional impairments and phenotypic frailty are associated with higher subsequent health care expenditures in community-dwelling beneficiaries after accounting for several claims-based indicators of costs.

PRIMARY FUNDING SOURCE

National Institutes of Health.

Interaction effects of multimorbidity and frailty on adverse health outcomes in elderly hospitalised patients

We quantified the interaction of multimorbidity and frailty and their impact on adverse health outcomes in the hospital setting. Using aretrospective cohort study of persons aged ≥ 75 years, admitted to hospital during 2010–2012 in New South Wales, Australia, and linked with mortality data, we constructed multimorbidity, frailty risk and outcomes: prolonged length of stay (LOS), 30-day mortality and 30-day unplanned readmissions. Relative risks (RR) of outcomes were obtained using Poisson models with random intercept for hospital. Among 257,535 elderly inpatients, 33.6% had multimorbidity and elevated frailty risk, 14.7% had multimorbidity only, 19.9% had elevated frailty risk only and 31.8% had neither. Additive interactions were present for all outcomes, with a further multiplicative interaction for mortality and LOS. Mortality risk was 4.2 (95% CI 4.1–4.4), prolonged LOS 3.3 (95% CI 3.3–3.4) and readmission 1.8 (95% CI 1.7–1.9) times higher in patients with both factors present compared with patients with neither. In conclusion, multimorbidity and frailty coexist in older hospitalized patients and interact to increase the risk of adverse outcomes beyond the sum of their individual effects. Their joint effect should be considered in health outcomes research and when administering hospital resources.

Three-Year Impact Of Stratification In The Medicare Hospital Readmissions Reduction Program

The Medicare Hospital Readmissions Reduction Program (HRRP) financially penalizes hospitals with high readmission rates. In fiscal year 2019 the program was changed to account for the association between social risk and high readmission rates. The new approach stratifies hospitals into five groups by hospitals' proportion of patients dually enrolled in Medicare and Medicaid, and it evaluates performance within each stratum instead of within the national cohort. Its impact on hospitals caring for vulnerable populations has not been studied. We calculated the change in average annual penalty percentage, before and after stratification, for safety-net hospitals, rural hospitals, and hospitals caring for a high share of Black and Hispanic or Latino patients. We found that stratification by proportion of dual enrollees was associated with a decrease in penalties by -0.09 percentage points at hospitals with the highest proportion of dual enrollees, -0.08 percentage points at rural hospitals, and -0.06 percentage points at hospitals with a large share of Black and Hispanic or Latino patients. Fully adjusted analyses suggest that these patterns were driven by penalty reductions at rural hospitals and hospitals disproportionately serving Black and Hispanic or Latino patients. Given the allocation of fewer penalties to these hospitals, we conclude that the stratification mandate was a modest step toward equity within the HRRP.

Development and validation of a knowledge-based score to predict Fried's frailty phenotype across multiple settings using one-year hospital discharge data: The electronic frailty score

BACKGROUND

Most claims-based frailty instruments have been designed for group stratification of older populations according to the risk of adverse health outcomes and not frailty itself. We aimed to develop and validate a tool based on one-year hospital discharge data for stratification on Fried's frailty phenotype (FP).

METHODS

We used a three-stage development/validation approach. First, we created a clinical knowledge-driven electronic frailty score (eFS) calculated as the number of deficient organs/systems among 18 critical ones identified from the International Statistical Classification of Diseases and Related Problems, 10th Revision (ICD-10) diagnoses coded in the year before FP assessment. Second, for eFS development and internal validation, we linked individual records from the Lc65+ cohort database to inpatient discharge data from Lausanne University Hospital (CHUV) for the period 2004-2015. The development/internal validation sample included community-dwelling, non-institutionalised residents of Lausanne (Switzerland) recruited in the Lc65+ cohort in three waves (2004, 2009, and 2014), aged 65-70 years at enrolment, and hospitalised at the CHUV at least once in the year preceding the FP assessment. Using this sample, we selected the best performing model for predicting the dichotomised FP, with the eFS or ICD-10-based variables as predictors. Third, we conducted an external validation using 2016 Swiss nationwide hospital discharge data and compared the performance of the eFS model in predicting 13 adverse outcomes to three models relying on well-designed and validated claims-based scores (Claims-based Frailty Index, Hospital Frailty Risk Score, Dr Foster Global Frailty Score).

FINDINGS

In the development/internal validation sample (n = 469), 14·3% of participants (n = 67) were frail. Among 34 models tested, the best-subsets logistic regression model with four predictors (age and sex at FP assessment, time since last hospital discharge, eFS) performed best in predicting the dichotomised FP (area under the curve=0·71; F1 score=0·39) and one-year adverse health outcomes. On the external validation sample (n = 54,815; 153 acute care hospitals), the eFS model demonstrated a similar performance to the three other claims-based scoring models. According to the eFS model, the external validation sample showed an estimated prevalence of 56·8% (n = 31,135) of frail older inpatients at admission.

INTERPRETATION

The eFS model is an inexpensive, transportable and valid tool allowing reliable group stratification and individual prioritisation for comprehensive frailty assessment and may be applied to both hospitalised and community-dwelling older adults.

FUNDING

The study received no external funding.

BBCIC Research Network Analysis of First-Cycle Prophylactic G-CSF Use in Patients Treated With High-Neutropenia Risk Chemotherapy

BACKGROUND

Chemotherapy-induced febrile neutropenia (FN) is prevented or minimized with granulocyte colony-stimulating factors (G-CSFs). Several G-CSF biosimilars are approved in the United States. The Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) is a nonprofit initiative whose objective is to provide scientific evidence on real-world use and comparative safety and effectiveness of biologics and biosimilars using the BBCIC distributed research network (DRN).

PATIENTS AND METHODS

We describe real-world G-CSF use in patients with breast or lung cancer receiving first-cycle chemotherapy associated with high FN risk. We assessed hospitalizations for FN, availability of absolute neutrophil counts, and G-CSF-induced adverse events to inform future observational comparative effectiveness studies of G-CSF reference products and their biosimilars. A descriptive analysis of 5 participating national health insurance plans was conducted within the BBCIC DRN.

RESULTS

A total of 57,725 patients who received at least one G-CSF dose were included. Most (92.5%) patients received pegfilgrastim. FN hospitalization rates were evaluated by narrow (<0.5%), intermediate (1.91%), and broad (2.99%) definitions. Anaphylaxis and hyperleukocytosis were identified in 1.15% and 2.28% of patients, respectively. This analysis provides real-world evidence extracted from a large, readily available database of diverse patients, characterizing G-CSF reference product use to inform the feasibility of future observational comparative safety and effectiveness analyses of G-CSF biosimilars. We showed that the rates of FN and adverse events in our research network are consistent with those reported by previous small studies.

CONCLUSIONS

Readily available BBCIC DRN data can be used to assess G-CSF use with the incidence of FN hospitalizations. Insufficient laboratory result data were available to report absolute neutrophil counts; however, other safety data are available for assessment that provide valuable baseline data regarding the effectiveness and safety of G-CSFs in preparation for comparative effectiveness studies of reference G-CSFs and their biosimilars.

Hospital Readmission Outcomes by Frailty Risk in Adults in Behavioral Health Acute Care

The purpose of the current retrospective study was to determine whether frailty is predictive of 30-day readmission in adults aged ≥50 years who were admitted with a psychiatric diagnosis to a behavioral health hospital from 2013 to 2017. A total of 1,063 patients were included. A 26-item frailty risk score (FRS-26-ICD) was constructed from electronic health record (EHR) data. There were 114 readmissions. Cox regression modeling for demographic characteristics, emergent admission, comorbidity, and FRS-26-ICD determined prediction of time to readmission was modest (incremental area under the receiver operating characteristic curve = 0.671). The FRS-26-ICD was a significant predictor of readmission alone and in models with demographics and emergent admission; however, only the Elixhauser Comorbidity Index was significantly related to hazard of readmission adjusting for other factors (adjusted hazard ratio = 1.26, 95% confidence interval [1.17, 1.37]; p < 0.001), whereas FRS-26-ICD became non-significant. Frailty is a relevant syndrome in behavioral health that should be further studied in risk prediction and incorporated into care planning to prevent hospital readmissions. [Journal of Psychosocial Nursing and Mental Health Services, xx(x), xx-xx.].