Defining ICD-10 surrogate variables to estimate the modified frailty index: a Delphi-based approach.
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ABSTRACT: Background
There are currently no validated globally and freely available tools to estimate the modified frailty index (mFI). The widely available and non-proprietary International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) coding could be used as a surrogate for the mFI. We aimed to establish an appropriate set of the ICD-10 codes for comorbidities to be used to estimate the eleven-variable mFI.Methods
A three-stage, web-based, Delphi consensus-building process among a panel of intensivists and geriatricians using iterative rounds of an online survey, was conducted between March and July 2021. The consensus was set a priori at 75% overall agreement. Additionally, we assessed if survey responses differed between intensivists and geriatricians. Finally, we ascertained the level of agreement.Results
A total of 21 clinicians participated in all 3 Delphi surveys. Most (86%, 18/21) had more than 5-years' experience as specialists. The agreement proportionately increased with every Delphi survey. After the third survey, the panel had reached 75% consensus in 87.5% (112/128) of ICD-10 codes. The initially included 128 ICD-10 variables were narrowed down to 54 at the end of the 3 surveys. The inter-rater agreements between intensivists and geriatricians were moderate for surveys 1 and 3 (κ = 0.728, κ = 0.780) respectively, and strong for survey 2 (κ = 0.811).Conclusions
This quantitative Delphi survey of a panel of experienced intensivists and geriatricians achieved consensus for appropriate ICD-10 codes to estimate the mFI. Future studies should focus on validating the mFI estimated from these ICD-10 codes.Trial registration
Not applicable.
SUBMITTER: Subramaniam A
PROVIDER: S-EPMC9107186 | biostudies-literature | 2022 May
REPOSITORIES: biostudies-literature
Publications
Defining ICD-10 surrogate variables to estimate the modified frailty index: a Delphi-based approach.
Subramaniam Ashwin A Ueno Ryo R Tiruvoipati Ravindranath R Darvall Jai J Srikanth Velandai V Bailey Michael M Pilcher David D Bellomo Rinaldo R
BMC geriatrics 20220513 1
<h4>Background</h4>There are currently no validated globally and freely available tools to estimate the modified frailty index (mFI). The widely available and non-proprietary International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) coding could be used as a surrogate for the mFI. We aimed to establish an appropriate set of the ICD-10 codes for comorbidities to be used to estimate the eleven-variable mFI.<h4>Methods</h4>A three-stage, web-based, De ...[more]
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Project description:Background: Substantial declines in genital warts (GW) have been observed in countries with quadrivalent HPV vaccination programmes, with Australia showing the highest reductions due to early commencement and high vaccination coverage. There is a real potential to achieve GW elimination; however, no GW elimination definition exists. Taking Australia as a case study, we aimed to reach expert consensus on a proposed GW elimination definition using a modified Delphi process. Method: We used modelling and epidemiological data to estimate the expected number of new GW cases, from pre-vaccination (baseline) in 2006 to the year 2060 in Australian heterosexuals, men who have sex with men (MSM), and newly arrived international travellers and migrants. We used these data and the literature, to develop a questionnaire containing ten elimination-related items, each with 9-point Likert scales (1-strongly disagree; 9-strongly agree). The survey was completed by 18 experts who participated in a full day face-to-face modified Delphi study, in which individuals and then small groups discussed and scored each item. The process was repeated online for items where consensus (≥70% agreement) was not initially achieved. Median and coefficient of variation (COV) were used to describe the central tendency and variability of responses, respectively. Findings: There was a 95% participation rate in the face-to-face session, and 84% response rate in the final online round. The median item score ranged between 7.0 and 9.0 and the COV was ≤0.30 on all items. Consensus was reached that at ≥80% HPV vaccination coverage, GW will be eliminated as a public health problem in Australia by 2060. During this time period there will be a 95% reduction in population-level incidence compared with baseline, equivalent to <1 GW case per 10,000 population. The reductions will occur most rapidly in Australian heterosexuals, with 73%, 90% and 97% relative reductions by years 2021, 2030 and 2060, respectively. The proportion of new GW cases attributable to importation will increase from 3.6% in 2006 to ~49% in 2060. Interpretation: Our results indicate that the vaccination programme will minimise new GW cases in the Australian population, but importation of cases will continue. This is the first study to define GW elimination at a national level. The framework developed could be used to define GW elimination in other countries, with thresholds particularly valuable for vaccination programme impact evaluation. Funding: LK supported through an Australian Government Research Training Programme Scholarship; unconditional funding from Seqirus to support the Delphi Workshop.
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Project description:BackgroundDespite significant interest in assessing activity patterns in different populations, there has been no consensus concerning the definition and operationalisation of this term. This has limited the comparability, interpretability, and synthesis of study findings to date. The aim of this study was to establish a consensus regarding the way in which activity patterns and activity pattern components are defined and reported.MethodsThe activity patterns literature was searched to identify experts to be invited to participate and to develop a proposed definition of activity patterns and activity pattern components. A three-round modified Delphi survey was conducted online (November 2021 to May 2022). In Round 1, participants were asked to rate their agreement with a proposed activity patterns definition, which also included six activity pattern components (e.g., activity intensity, activity bout, transitions), six examples of activity patterns (e.g., frequency of postural transitions in discrete time periods) and eight items for reporting activity patterns in future research (n = 21 items). Open-ended questions enabled participants to provide further comments and suggestions for additional items. Consensus was defined a priori as ≥ 80% participants rating their agreement with an item. In Round 2, participants were asked to rate their agreement with 25 items (13 original items, eight amended, and four new). In Round 3, participants rated their agreement with 10 items (five original items, four amended, and one new).ResultsTwenty experts in activity patterns research participated in Round 1, with response rates of 80% and 60% in Rounds 2 and 3, respectively. The proposed activity pattern definition, all activity pattern components definitions, four of the six activity pattern examples, and 10 items in the activity patterns reporting framework achieved consensus. The removal of one activity component item between Rounds 1 and 2 achieved consensus.ConclusionThis modified Delphi study achieved consensus for defining and reporting activity patterns for the first time. This consensus definition enables standardisation of activity patterns terminology, which is important given the significant interest in quantifying how individuals accumulate their physical activity and sedentary behaviour across the lifespan to inform the development of future public health guidelines and interventions efforts.
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Project description:BackgroundThe conventional count-based physical frailty phenotype (PFP) dichotomizes its criterion predictors-an approach that creates information loss and depends on the availability of population-derived cut-points. This study proposes an alternative approach to computing the PFP by developing and validating a model that uses PFP components to predict the frailty index (FI) in community-dwelling older adults, without the need for predictor dichotomization.MethodsA sample of 998 community-dwelling older adults (mean [SD], 68 [7] years) participated in this prospective cohort study. Participants completed a multi-domain geriatric screen and a physical fitness assessment from which the count-based PFP and the 36-item FI were computed. One-year prospective falls and hospitalization rates were also measured. Bayesian beta regression analysis, allowing for nonlinear effects of the non-dichotomized PFP criterion predictors, was used to develop a model for FI ("model-based PFP"). Approximate leave-one-out (LOO) cross-validation was used to examine model overfitting.ResultsThe model-based PFP showed good calibration with the FI, and it had better out-of-sample predictive performance than the count-based PFP (LOO-R2, 0.35 vs 0.22). In clinical terms, the improvement in prediction (i) translated to improved classification agreement with the FI (Cohen's kw, 0.47 vs 0.36) and (ii) resulted primarily in a 23% (95%CI, 18-28%) net increase in FI-defined "prefrail/frail" participants correctly classified. The model-based PFP showed stronger prognostic performance for predicting falls and hospitalization than did the count-based PFP.ConclusionThe developed model-based PFP predicted FI and clinical outcomes more strongly than did the count-based PFP in community-dwelling older adults. By not requiring predictor cut-points, the model-based PFP potentially facilitates usage and feasibility. Future validation studies should aim to obtain clear evidence on the benefits of this approach.
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Project description:BackgroundThe original Charlson Comorbidity Index (CCI) encompassed 19 categories of medical conditions that were identifiable in medical records. Subsequent publications provided scoring algorithms based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. The recent adoption of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes in the United States created a need for a new scoring scheme. In addition, a review of existing claims-based scoring systems suggested 3 areas for improvement: the lack of explicit identification of secondary diabetes, the lack of differentiation between HIV infection and AIDS, and insufficient guidance on scoring hierarchy. In addition, addressing the third need raised the issue of disease severity in renal disease.ObjectivesThis initiative aimed to create an expanded and refined ICD-9 scoring system for CCI, addressing the classification of issues noted above, create a corresponding ICD-10 system, assess the comparability of ICD-9- and ICD-10-based scores, and validate the new scoring scheme.MethodsWe created ICD-9 and ICD-10 code tables for 19 CCI medical conditions. The new scoring scheme was labeled CDMF CCI and was tested using claims-based data for individuals aged ≥65 years who participated in a Humana Medicare Advantage plan during at least 1 of 3 consecutive 12-month periods. Two 12-month periods were during the ICD-9 era and the third 12-month period was during the ICD-10 era. Because many individuals were counted in more than one 12-month period, we described the study population as comprising 3 panels. We used regression models to analyze the association between the CCI score and same-year inpatient admissions and near-term (90-day) mortality. Additional testing was done by comparing the mean CCI score or disease prevalence in the 3 subpopulations of people with HIV/AIDS, renal disease, or diabetes. Finally, we calculated area under the receiver operating characteristics (AUC-ROC) curve values by applying the Deyo system and our ICD-9 and ICD-10 scoring systems.ResultsThe CDMF ICD-9 and ICD-10 scoring scheme yielded comparable scores across the 3 panels, and inpatient admissions and mortality rates consistently increased in each panel as the CCI score increased. Comparisons of the performance of the Deyo system and our proposed CDMF ICD-9 system in the 3 key subpopulations showed that the CDMF ICD-9 system produced a lower CCI score in the presence of HIV infection without AIDS, achieved similar detection ability of diabetes, and allowed good differentiation between mild-to-moderate and severe renal disease. AUC-ROC values were similar between the CDMF ICD-9 coding system and the Deyo system.ConclusionOur results support the implementation of the CDMF CCI scoring instrument to triage individual patients for disease- and care-management programs. In addition, the CDMF scheme allows for a more precise understanding of chronic disease at a population level, thus allowing health systems and plans to design services and benefits to meet multifactorial clinical needs. Preliminary validation sets the stage for further testing using long-term follow-up data and for the adaptation of this coding scheme to a chart review instrument.
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Project description:The Clinical Frailty Scale (CFS) is the most used frailty measure in intensive care unit (ICU) patients. Recently, the modified frailty index (mFI), derived from 11 comorbidities has also been used. It is unclear to what degree the mFI is a true measure of frailty rather than comorbidity. Furthermore, the mFI cannot be freely obtained outside of specific proprietary databases.ObjectiveTo compare the performance of CFS and a recently developed International Classification of Diseases-10 (ICD-10) mFI (ICD-10mFI) as frailty-based predictors of long-term survival for up to 1 year.DesignA retrospective multicentric observational study.Setting and participantsAll adult (≥16 yr) critically ill patients with documented CFS scores admitted to sixteen Australian ICUs in the state of Victoria between April 1, 2017 to June 30, 2018 were included. We used probabilistic methods to match de-identified ICU admission episodes listed in the Australia and New Zealand Intensive Care Society Adult Patient Database with the Victorian Admission Episode Dataset and the Victorian Death Index via the Victorian Data Linkage Centre.Main outcomes and measuresThe primary outcome was the longest available survival following ICU admission. We compared CFS and ICD-10mFI as primary outcome predictors, after adjusting for key confounders.ResultsThe CFS and ICD-10mFI were compared in 7,001 ICU patients. The proportion of patients categorized as frail was greater with the CFS than with the ICD-10mFI (18.9% [n = 1,323] vs. 8.8% [n = 616]; p < 0.001). The median (IQR) follow-up time was 165 (82-276) days. The CFS predicted long-term survival up to 6 months after adjusting for confounders (hazard ratio [HR] = 1.26, 95% CI, 1.21-1.31), whereas ICD-10mFI did not (HR = 1.04, 95% CI, 0.98-1.10). The ICD-10mFI weakly correlated with the CFS (Spearman's rho = 0.22) but had a poor agreement (kappa = 0.06). The ICD-10mFI more strongly correlated with the Charlson comorbidity index (Spearman's rho 0.30) than CFS (Spearman's rho = 0.25) (p < 0.001).ConclusionsCFS, but not ICD-10mFI, predicted long-term survival in ICU patients. ICD-10mFI correlated with co-morbidities more than CFS. These findings suggest that CFS and ICD-10mFI are not equivalent.RelevanceCFS and ICD-10mFI are not equivalent in screening for frailty in critically ill patients and therefore ICD-10mFI in its current form should not be used.
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Project description:Community firearm violence (CFV), including fatal and non-fatal shootings that result from interpersonal violence, disproportionately harms people from marginalized racial groups. News reporting on CFV can further exacerbate these harms. However, examining the effects of harmful news reporting on CFV on individuals, communities, and society is hindered by the lack of a consensus definition of harmful reporting on CFV. In this study, we aimed to define harmful reporting on CFV. We used a modified, three-round Delphi process to achieve consensus among diverse stakeholders. Round 1 sought to assess consensus on 12 potentially harmful news content elements for three levels of harm (individual, community, and society). Round 2 invited panelists to rate the severity of each news content element at each level of harm. Round 3 asked panelists to agree or disagree with the panel's median severity rating of each element at each level of harm. Twenty-one panelists were recruited from three expertise groups (lived experience of CFV, journalism practice, scholarship) and all panelists completed all three rounds. In Round 1, no negative consensus was achieved for any of the proposed news content elements. In Round 2, panelists assigned moderate to severe harm ratings for all but two news content elements, and median harm ratings for each element varied across the different levels of harm. In Round 3, panelists reported high levels of agreement for each harm rating at each level. This modified Delphi process yielded a definition of the 12 elements that comprise harmful news reporting on CFV and severity ratings of harm caused by each element at each level according to expert consensus. Future work will use these results to evaluate and intervene on harmful reporting on CFV. Reducing harm from reporting on CFV can help address this health disparity and support evidence-based approaches to this urgent public health issue.
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Project description:Rationale: Diagnosis of chronic obstructive pulmonary disease (COPD) relies on abnormal spirometry. However, spirometry may underestimate the effects of smoking, missing smokers with respiratory disease who have minimal or no airflow obstruction. Objectives: To develop a multidimensional definition of a lung-related "resilient smoker" that is useful in research studies and then identify a resilient smoker subgroup in the SPIROMICS (SubPopulations and InteRmediate Outcome Measures In COPD Study) cohort using this definition. Methods: We performed a three-round modified Delphi survey among a panel of COPD experts to identify and reach a consensus on clinical and radiographic domains to be included in a lung-related resilient smoker definition. Consensus on domains of resilience was defined as ⩾80% of experts voting "agree" or "strongly agree" on a 5-point Likert scale. The Delphi-derived definition of resilience was applied to SPIROMICS to identify resilient smokers, whom we then characterized using known biomarkers of COPD. Results: Consensus was achieved on 6 of 12 diagnostic items, which include cough and sputum production, dyspnea, radiographic measures of emphysema and small airways disease, exacerbations, and decline in forced expiratory volume in 1 second. Although 892 SPIROMICS participants were classified as smokers with preserved lung function by spirometry, only 149 participants (16.7%) qualified as resilient smokers by our definition. Blood biomarker expression of CRP (C-reactive protein) and sTNFRSF1A (soluble tumor necrosis receptor factor1A) was lower in resilient than nonresilient smokers (P = 0.02 and P = 0.03). Conclusions: A Delphi-derived consensus definition of resilient smoker identified 83.3% of smokers with preserved spirometry as "nonresilient" based on the presence of adverse effects of smoking on the lung. Resilient smokers were biologically distinct from nonresilient smokers based on CRP measurements. Clinical trial registered with ClinicalTrials.gov (NCT01969344).
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Project description:The newly characterized modified frailty index (mFI) is a robust predictor of postoperative outcomes for surgical patients. The present study investigates the optimal cutoff for mFI specifically in older gastrointestinal (GI) cancer patients undergoing surgery. All patients more than 60 years old who underwent surgery for a GI malignancy (esophagus, stomach, colon, rectum, pancreas, liver, and bile duct) were identified in the 2005 to 2012 National Surgical Quality Improvement Program, Participant Use Data File (NSQIP PUF). Patients undergoing emergency procedures, of American Society of Anesthesiologists (ASA) five status, or diagnosed with preoperative sepsis were excluded. Logistic regression modeling and 10-fold cross validation were used to identify an optimal mFI cutoff. A total of 41,455 patients (mean age 72, 47.4% female) met the eligibility criteria. Among them, 19.0 per cent (n = 7891) developed a major postoperative complication and 2.8 per cent (n = 1150) died within 30 days. A random sampling by a cancer site was performed to create 90 per cent training and 10 per cent test sample datasets. Using 10-fold cross validation, logistical regression models evaluated the association between mFI and endpoints of 30-day mortality and major morbidity at various cutoffs. Optimal cutoffs for 30-day mortality and major morbidity were mFI ≥ 0.1 and ≥0.2, respectively. After adjusting for age, sex, ASA, albumin ≥3g/dl, and body mass index ≥ 30 kg/m2, mFI ≥ 0.1 was associated with increased mortality (odds ratio (OR) 1.49, 1.30-1.71 95% confidence interval (CI), P < 0.001) and mFI ≥ 0.2 was associated with increased morbidity (OR 1.52, 1.39-1.65 95% CI, P < 0.001). For older GI cancer patients, a very low mFI was a predictor of poor postoperative outcomes with an optimal cutoff of two or more mFI characteristics.
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