Systemic treatment of HCC in special populations.

Recent years have seen significant progress in the systemic treatment of hepatocellular carcinoma (HCC), including the advent of immunotherapy. While several large phase III trials have provided the evidence for a multi-line treatment paradigm, they have focused on a highly selected group of patients by excluding potentially confounding comorbidities. As a result, high quality evidence for the systemic treatment of HCC in patients with various comorbidities is missing. This review summarises current knowledge on the use of approved medicines in patients with HIV, autoimmune disease, cardiovascular disease, diabetes, fibrolamellar HCC, mixed HCC-cholangiocarcinoma, decompensated cirrhosis (Child-Pugh B and C), a significant bleeding history, vascular invasion or portal vein thrombosis, as well as the elderly, those on haemodialysis, and those after solid organ transplantation. The article highlights relevant knowledge gaps and current clinical challenges. To improve the safety and efficacy of HCC treatment in these subgroups, future trials should be designed to specifically include patients with comorbidities.

Multimorbidity networks of chronic obstructive pulmonary disease and heart failure in men and women: Evidence from the EpiChron Cohort.

Patients with heart failure (HF) and/or chronic obstructive pulmonary disease (COPD) constitute a complex population with different phenotypes based on pathophysiology, comorbidity, sex and age. We aimed to compare the multimorbidity patterns of HF and COPD in men and women using network analysis. Individuals aged 40 years or older on 2015 of the EpiChron Cohort (Aragon, Spain) were stratified by sex and as having COPD (n = 28,608), HF (n = 13,414), or COPD and HF (n = 3952). We constructed one network per group by obtaining age-adjusted phi correlations between comorbidities. For each sex, networks differed between the three study groups; between sexes, similarities were found for the two HF groups. We detected some specific diseases highly connected in all networks (e.g., cardio-metabolic, respiratory diseases, and chronic kidney failure), and some others that were group-specific that would require further study. We identified common clusters (i.e., cardio-metabolic, cardiovascular, cancer, and neuro-psychiatric) and others specific and clinically relevant in COPD patients (e.g., behavioral risk disorders were systematically associated with psychiatric diseases in women and cancer in men). Network analysis represents a powerful tool to analyze, visualize, and compare the multimorbidity patterns of COPD and HF, also facilitated by developing an ad hoc website.

Use of Latent Class Analysis and k-Means Clustering to Identify Complex Patient Profiles.

Importance: Medically complex patients are a heterogeneous group that contribute to a substantial proportion of health care costs. Coordinated efforts to improve care and reduce costs for this patient population have had limited success to date. Objective: To define distinct patient clinical profiles among the most medically complex patients through clinical interpretation of analytically derived patient clusters. Design, Setting, and Participants: This cohort study analyzed the most medically complex patients within Kaiser Permanente Northern California, a large integrated health care delivery system, based on comorbidity score, prior emergency department admissions, and predicted likelihood of hospitalization, from July 18, 2018, to July 15, 2019. From a starting point of over 5000 clinical variables, we used both clinical judgment and analytic methods to reduce to the 97 most informative covariates. Patients were then grouped using 2 methods (latent class analysis, generalized low-rank models, with k-means clustering). Results were interpreted by a panel of clinical stakeholders to define clinically meaningful patient profiles. Main Outcomes and Measures: Complex patient profiles, 1-year health care utilization, and mortality outcomes by profile. Results: The analysis included 104 869 individuals representing 3.3% of the adult population (mean [SD] age, 70.7 [14.5] years; 52.4% women; 39% non-White race/ethnicity). Latent class analysis resulted in a 7-class solution. Stakeholders defined the following complex patient profiles (prevalence): high acuity (9.4%), older patients with cardiovascular complications (15.9%), frail elderly (12.5%), pain management (12.3%), psychiatric illness (12.0%), cancer treatment (7.6%), and less engaged (27%). Patients in these groups had significantly different 1-year mortality rates (ranging from 3.0% for psychiatric illness profile to 23.4% for frail elderly profile; risk ratio, 7.9 [95% CI, 7.1-8.8], P < .001). Repeating the analysis using k-means clustering resulted in qualitatively similar groupings. Each clinical profile suggested a distinct collaborative care strategy to optimize management. Conclusions and Relevance: The findings suggest that highly medically complex patient populations may be categorized into distinct patient profiles that are amenable to varying strategies for resource allocation and coordinated care interventions.

Health literacy profiles of adults with multiple chronic diseases: A cross-sectional study using the Health Literacy Questionnaire.

Health literacy is multidimensional, comprising functional, communicative, and critical thinking dimensions. Understanding health literacy is crucial for clinicians to develop effective health education strategies. In this study, we examined the multiple dimensions of health literacy in Vietnamese adults with chronic comorbidities. A cross-sectional sample of 600 patients, aged ≥18 years with a diagnosis of at least two chronic diseases (cardiovascular conditions, chronic kidney disease, or diabetes), completed the Health Literacy Questionnaire, an instrument assessing nine distinct domains. Descriptive and parametric tests were performed to analyze the health literacy levels for various demographic characteristics. Generalized linear models using backward modelling explored factors associated with higher health literacy. The lowest scoring domains were "Healthcare provider support" and "Appraisal of health information." In multivariate models greater health literacy was associated with those <65 years, having a postsecondary degree or higher level of education, greater income, urban residence, being cared for by spouses/children, and having fewer comorbidities. To improve health literacy, clinicians in primary and acute healthcare settings should build supportive relationships with patients and assist them with understanding and appraising health information.

"They are interrelated, one feeds off the other": A taxonomy of perceived disease interactions derived from patients with multiple chronic conditions.

OBJECTIVE: To understand patients' experiences with condition interactions and develop a taxonomy to inform care for patients with multiple chronic conditions. METHODS: We conducted qualitative and quantitative analysis of free-text data from patient surveys in which respondents were asked to indicate their most bothersome chronic condition and describe how their other conditions affect their self-care for that condition. Using standard content analysis, we developed a taxonomy comprising how patients perceive interactions among their conditions, and examined cross-cutting themes that reflect qualities of these interactions. RESULTS: Among 383 eligible survey respondents, the mean (SD) number of chronic conditions was 4 (2); common conditions included hypertension (60%), chronic pain (49%), arthritis (41%), depression (32%), diabetes (29%), and post-traumatic stress disorder (26%). Patients' perceived condition interactions took four broad forms: 1) unidirectional interactions among conditions and/or treatments, 2) cyclical or multidimensional interactions, 3) uncertain or indistinct interactions, and 4) no perceived interaction. Cross-cutting themes included beliefs about causal relationships between conditions, identification of interactions as negative vs. positive, and interactions between physical and mental health. CONCLUSION: This study presents a novel taxonomy of condition interactions from the patient perspective. PRACTICE IMPLICATIONS: Understanding perceived condition interactions may support patient self-management and shared decision-making efforts.

Association Between Care Management and Outcomes Among Patients With Complex Needs in Medicare Accountable Care Organizations.

Importance: People with complex needs account for a disproportionate amount of Medicare spending, partially because of fragmented care delivered across multiple practitioners and settings. Accountable care organization (ACO) contracts give practitioners incentives to improve care coordination to the extent that coordination initiatives reduce total spending or improve quality. Objective: To assess the association between ACO-reported care management and coordination activities and quality, utilization, spending, and health care system interactions in older adults with complex needs. Design, Setting, and Participants: In this cross-sectional study, survey information on care management and coordination processes from 244 Medicare Shared Savings Program ACOs in the 2017-2018 National Survey of ACOs (of 351 Medicare ACO respondents; response rate, 69%) conducted from July 20, 2017, to February 15, 2018, was linked to 2016 Medicare administrative claims data. Medicare beneficiaries 66 years or older who were defined as having complex needs because of frailty or 2 or more chronic conditions associated with high costs and clinical need were included. Exposures: Beneficiary attribution to ACO reporting comprehensive (top tertile) care management and coordination activities. Main Outcomes and Measures: All-cause prevention quality indicator admissions, 30-day all-cause readmissions, acute care and critical access hospital admissions, evaluation and management visits in ambulatory settings, inpatient days, emergency department visits, total spending, post-acute care spending, health care contact days, and continuity of care (from Medicare claims). Results: Among 1 402 582 Medicare beneficiaries with complex conditions, the mean (SD) age was 78 (8.0) years and 55.1% were female. Compared with beneficiaries assigned to ACOs in the bottom tertile of care management and coordination activities, those assigned to ACOs in the top tertile had identical median prevention quality indicator admissions and 30-day all-cause readmissions (0 per beneficiary across all tertiles), hospitalization and emergency department visits (1.0 per beneficiary in bottom and top tertiles), evaluation and management visits in ambulatory settings (14.0 per beneficiary [interquartile range (IQR), 8.0-21.0] in both tertiles), longer median inpatient days (11.0 [IQR, 4.0-33.0] vs 10.0 [IQR, 4.0-32.0]), higher median annual spending ($14 350 [IQR, $4876-$36 119] vs $14 229 [IQR, $4805-$36 268]), lower median health care contact days (28.0 [IQR, 17.0-44.0] vs 29.0 [IQR, 18.0-45.0]), and lower continuity-of-care index (0.12 [IQR, 0.08-0.20] vs 0.13 [IQR, 0.08-0.21]). Accounting for within-patient correlation, quality, utilization, and spending outcomes among patients with complex needs attributed to ACOs were not statistically different comparing the top vs bottom tertile of care management and coordination activities. Conclusions and Relevance: The ACO self-reports of care management and coordination capacity were not associated with differences in spending or measured outcomes for patients with complex needs. Future efforts to care for patients with complex needs should assess whether strategies found to be effective in other settings are being used, and if so, why they fail to meet expectations.

Pediatric Complex Chronic Conditions: Does the Classification System Work for Infants?

BACKGROUND: One widely accepted approach to identify children with life-limiting health problems is the complex chronic conditions (CCCs) classification system. Although considered the "gold standard" for classifying children with serious illness, little is known about its performance, especially among infants. OBJECTIVE/HYPOTHESIS: This research examined the prevalence of CCCs and the infant characteristics related to a CCC classification. METHODS: Multivariate regression analysis was conducted with 2012 Kids' Inpatient Database, Healthcare Cost and Utilization Project data files, using a national sample of infant decedents less than 1 year. RESULTS: Our findings showed that 40% of the infants were classified with a CCC. African Americans were negatively associated with a CCC classification (adjusted odds ratio [aOR] = 0.63; 95% confidence interval [CI] = 0.543-0.731). When infants had other insurance coverage, they were less likely (aOR = 0.63; 95% CI = 0.537-0.748) to have a CCC classification. Infants who resided in nonurban areas (aOR = 1.21; 95% CI =1.034-1.415) and had comorbidities (aOR = 38.19; 95% CI = 33.12-44.04) had greater odds of having a CCC classification. CONCLUSIONS: The findings suggested that the infants are not commonly classified with a CCC and highlighted the significant variation in race with African American infants exhibiting different CCC classifications than Caucasian infants. Given the importance of reducing disparities in palliative care, critical attention to using CCC classifications in research is warranted.

[Multimorbidity and Disease Severity Measured by the Charlson Index in Portuguese Hospitalised Patients During the Year 2015: A Cross-Sectional Study]. / Multimorbilidade e Gravidade da Doença Medida pelo Índice de Charlson em Doentes Hospitalizados Durante o Ano de 2015: Estudo Transversal.

INTRODUCTION: The association between multimorbidity and disease severity is not well established. The objectives were to characterise multimorbidity and determine disease severity (trough Charlson), as well as to verify if there is an association between the number and type of disease and the Charlson index. MATERIAL AND METHODS: A cross-sectional study based on exported data from the Portuguese National Health Service hospitalisations database, during the year 2015. The study included 22 chronic health conditions: 15 predicted in the Charlson index and seven frequent conditions (hypertension, obesity, dyslipidaemia, osteoarthritis, osteoporosis, anxiety and depression). The analysis was performed through the generalised linear model, considering binary logistic regression. In the analysis, the IBM SPSS version 24.0 tool was used. RESULTS: The study analysed 800 376 hospitalisations, from which 42% correspond to males. The average age of the sample was 59.8 years, being higher in men (62.3 years). The mean number of problems per person was 1.6, greater in men (1.8). Disease severity was also higher in males. The worst prognosis was associated with six or more conditions per person. The largest predictor of disease severity was the number of problems, followed by dementia and diabetes. DISCUSSION: The results seem to confirm the gender difference regarding morbidity pattern. The number of conditions per person was the greatest predictor of disease severity, particularly the presence of six or more conditions per person. CONCLUSION: The major limitation was the use of the same medical conditions to measure multimorbidity and disease severity. Other studies and analysis models should explore the complexity of the multimorbidity phenomenon.

Introdução: A associação entre multimorbilidade e gravidade da doença não está bem estabelecida. Os objetivos foram caracterizar a multimorbilidade e determinar a gravidade da doença, bem como verificar se existe associação entre o número e natureza dos diagnósticos e o índice de Charlson. Material e Métodos: Estudo transversal realizado através de dados exportados da base de dados de internamentos, durante o ano de 2015. O estudo incluiu 22 doenças crónicas: 15 previstas no índice de Charlson e sete condições médicas frequentes (hipertensão, obesidade, dislipidemia, osteoartrose, osteoporose, ansiedade e depressão). A análise foi realizada através do modelo linear generalizado, regressão logística binária. Na análise, utilizou-se a ferramenta IBM SPSS versão 24.0. Resultados: Foram analisadas 800 376 hospitalizações, das quais 42% correspondem a homens. A idade média da amostra foi de 59,8 anos, sendo maior nos homens (62,3 anos). O número médio de problemas por pessoa foi de 1,6, sendo superior nos homens (1,8). A gravidade da doença também foi maior nos homens. O pior prognóstico esteve associado a seis ou mais condições por pessoa. O maior preditor de gravidade da doença foi o número de problemas, seguido da demência e diabetes. Discussão: Os resultados parecem confirmar a diferença entre sexos quanto ao padrão de morbilidade. O número de condições por pessoa foi o maior preditor de gravidade da doença, particularmente a presença de seis ou mais condições por pessoa. Conclusão: A principal limitação identificada foi o uso das mesmas condições médicas para medir a multimorbilidade e a gravidade da doença. Outros estudos e modelos de análise devem explorar a complexidade do fenómeno da multimorbilidade.

Valoración de la fragilidad: aspecto fundamental en el paciente crítico / Frailty: Critical term for critical care

No disponible

Patterns and temporal trends of comorbidity among adult patients with incident cardiovascular disease in the UK between 2000 and 2014: A population-based cohort study.

BACKGROUND: Multimorbidity in people with cardiovascular disease (CVD) is common, but large-scale contemporary reports of patterns and trends in patients with incident CVD are limited. We investigated the burden of comorbidities in patients with incident CVD, how it changed between 2000 and 2014, and how it varied by age, sex, and socioeconomic status (SES). METHODS AND FINDINGS: We used the UK Clinical Practice Research Datalink with linkage to Hospital Episode Statistics, a population-based dataset from 674 UK general practices covering approximately 7% of the current UK population. We estimated crude and age/sex-standardised (to the 2013 European Standard Population) prevalence and 95% confidence intervals for 56 major comorbidities in individuals with incident non-fatal CVD. We further assessed temporal trends and patterns by age, sex, and SES groups, between 2000 and 2014. Among a total of 4,198,039 people aged 16 to 113 years, 229,205 incident cases of non-fatal CVD, defined as first diagnosis of ischaemic heart disease, stroke, or transient ischaemic attack, were identified. Although the age/sex-standardised incidence of CVD decreased by 34% between 2000 to 2014, the proportion of CVD patients with higher numbers of comorbidities increased. The prevalence of having 5 or more comorbidities increased 4-fold, rising from 6.3% (95% CI 5.6%-17.0%) in 2000 to 24.3% (22.1%-34.8%) in 2014 in age/sex-standardised models. The most common comorbidities in age/sex-standardised models were hypertension (28.9% [95% CI 27.7%-31.4%]), depression (23.0% [21.3%-26.0%]), arthritis (20.9% [19.5%-23.5%]), asthma (17.7% [15.8%-20.8%]), and anxiety (15.0% [13.7%-17.6%]). Cardiometabolic conditions and arthritis were highly prevalent among patients aged over 40 years, and mental illnesses were highly prevalent in patients aged 30-59 years. The age-standardised prevalence of having 5 or more comorbidities was 19.1% (95% CI 17.2%-22.7%) in women and 12.5% (12.0%-13.9%) in men, and women had twice the age-standardised prevalence of depression (31.1% [28.3%-35.5%] versus 15.0% [14.3%-16.5%]) and anxiety (19.6% [17.6%-23.3%] versus 10.4% [9.8%-11.8%]). The prevalence of depression was 46% higher in the most deprived fifth of SES compared with the least deprived fifth (age/sex-standardised prevalence of 38.4% [31.2%-62.0%] versus 26.3% [23.1%-34.5%], respectively). This is a descriptive study of routine electronic health records in the UK, which might underestimate the true prevalence of diseases. CONCLUSIONS: The burden of multimorbidity and comorbidity in patients with incident non-fatal CVD increased between 2000 and 2014. On average, older patients, women, and socioeconomically deprived groups had higher numbers of comorbidities, but the type of comorbidities varied by age and sex. Cardiometabolic conditions contributed substantially to the burden, but 4 out of the 10 top comorbidities were non-cardiometabolic. The current single-disease paradigm in CVD management needs to broaden and incorporate the large and increasing burden of comorbidities.

Prevalence of Chronic Conditions and Multimorbidities in a Geographically Defined Geriatric Population With Diverse Races and Ethnicities.

OBJECTIVE: The objective of this study is to examine racial/ethnic differences in prevalence of chronic conditions and multimorbidities in the geriatric population of a state with diverse races/ethnicities. METHOD: Fifteen chronic conditions and their dyads and triads were investigated using Hawaii Medicare 2012 data. For each condition, a multivariable logistic regression model was used to investigate differences in race/ethnicity, adjusting for subject characteristics. RESULTS: Of the 84,212 beneficiaries, 27.8% were Whites, 54.6% Asians, and 5.2% Hispanics. Racial/ethnic disparities were prevalent for most conditions. Compared with Whites, Asians, Hispanics, and Others showed significantly higher prevalence rates in hypertension, hyperlipidemia, diabetes, and most dyads or triads of the chronic conditions. However, Whites had higher prevalence rates in arthritis and dementia. DISCUSSION: Race/ethnicity may need to be considered when making clinical decisions and developing health care programs to reduce health disparities and improve quality of life for older individuals with chronic conditions.

Defining Multiple Chronic Conditions for Quality Measurement.

BACKGROUND/OBJECTIVE: Patients with multiple chronic conditions (MCCs) are a critical but undefined group for quality measurement. We present a generally applicable systematic approach to defining an MCC cohort of Medicare fee-for-service beneficiaries that we developed for a national quality measure, risk-standardized rates of unplanned admissions for Accountable Care Organizations. RESEARCH DESIGN: To define the MCC cohort we: (1) identified potential chronic conditions; (2) set criteria for cohort conditions based on MCC framework and measure concept; (3) applied the criteria informed by empirical analysis, experts, and the public; (4) described "broader" and "narrower" cohorts; and (5) selected final cohort with stakeholder input. SUBJECTS: Subjects were patients with chronic conditions. Participants included 21.8 million Medicare fee-for-service beneficiaries in 2012 aged 65 years and above with ≥1 of 27 Medicare Chronic Condition Warehouse condition(s). RESULTS: In total, 10 chronic conditions were identified based on our criteria; 8 of these 10 were associated with notably increased admission risk when co-occurring. A broader cohort (2+ of the 8 conditions) included 4.9 million beneficiaries (23% of total cohort) with an admission rate of 70 per 100 person-years. It captured 53% of total admissions. The narrower cohort (3+ conditions) had 2.2 million beneficiaries (10%) with 100 admissions per 100 person-years and captured 32% of admissions. Most stakeholders viewed the broader cohort as best aligned with the measure concept. CONCLUSIONS: By systematically narrowing chronic conditions to those most relevant to the outcome and incorporating stakeholder input, we defined an MCC admission measure cohort supported by stakeholders. This approach can be used as a model for other MCC outcome measures.

Paciente preso: controversias en su abordaje como paciente pluripatológico y sistemas de clasificación según complejidad y severidad / No disponible

No disponible

El etiquetado de pacientes en atención primaria. El caso de la cronicidad / Labelling chronically ill patients in primary care

No disponible

The quest for sustained multiple morbidity reduction in very low-birth-weight infants: the Antifragility project.

OBJECTIVE: Can a comprehensive, explicitly directive evidence-based guideline for all therapies that might affect the major morbidities of very low-birth-weight (VLBW) infants help a neonatal intensive care unit (NICU) further improve generally favorable morbidity rates? Can Antifragility principles of provider adaptive growth from stressors, enhanced infant risk assessment and adherence to effective therapies minimize unproven treatments and reduce all morbidities? STUDY DESIGN: Prospectively planned observational trial in VLBW infants: control group born October 2011 to September 2013 and study group October 2013 to September 2015. Multi-disciplinary evidence-based review assigned all NICU treatments into one of four distinct categories: (1) always employ this therapy for VLBW infants, (2) never use this therapy, (3) employ this questionable therapy thoughtfully, only in certain circumstances and (4) this therapy has insufficient evidence of efficacy and safety. Extensive staff education emphasized evidence-based potentially better practice (PBP) selection with compliance checks, appreciation of intertwined co-morbidities and prioritizing infant risk reduction strategies. RESULTS: Control included 221 infants, mean (s.d.) age 29 (2.6) weeks, birth weight 1129 (257) g and Study included 197 infants, 29 (2.7) weeks, 1093 (292) g. One hundred and four distinct therapies were placed into categories 1 to 4, with 32 specific compliance checks. Overall mean compliance with the process checks during the second era was 70%, high: 100% (exclusive breast milk use), low: 24% (correct pulse oximetry alarm settings). Morbidity and mortality rates did not significantly change during the second era. CONCLUSIONS: In our NICU with favorable morbidity rates, an expanded effort using a comprehensive therapy guideline for VLBW infants did not further improve outcomes. We need deeper understanding of continuous quality improvement (CQI) fundamentals, therapy compliance, co-morbidity relationships and enhanced sensitivity of risk assessment. Our innovative Antifragility PBP guideline could be useful to other NICUs seeking improvement in VLBW infant morbidities, as we offer a reasoned and concise template of a broad array of therapies categorized efficiently for transparency and review, designed to enhance responsible CQI decision-making.

Apples and Oranges: Four Definitions of Multiple Chronic Conditions and their Relationship to 30-Day Hospital Readmission.

OBJECTIVES: To determine the extent of agreement between four commonly used definitions of multiple chronic conditions (MCCs) and compare each definition's ability to predict 30-day hospital readmissions. DESIGN: Retrospective cohort study. SETTING: National Medicare claims data. PARTICIPANTS: Random sample of Medicare beneficiaries discharged from the hospital from 2005 to 2009 (n = 710,609). MEASUREMENTS: Baseline chronic conditions were determined for each participant using four definitions of MCC. The primary outcome was all-cause 30-day hospital readmission. Agreement between MCC definitions was measured, and sensitivities and specificities for each definition's ability to identify patients experiencing a future readmission were calculated. Logistic regression was used to assess the ability of each MCC definition to predict 30-day hospital readmission. RESULTS: The sample prevalence of hospitalized Medicare beneficiaries with two or more chronic conditions ranged from 18.6% (Johns Hopkins Adjusted Clinical Groups (ACG) Case-Mix System software) to 92.9% (Medicare Chronic Condition Warehouse (CCW)). There was slight to moderate agreement (kappa = 0.03-0.44) between pair-wise combinations of MCC definitions. CCW-defined MCC was the most sensitive (sensitivity 95.4%, specificity 7.4%), and ACG-defined MCC was the most specific (sensitivity 32.7%, specificity 83.2%) predictor of being readmitted. In the fully adjusted model, the risk of readmission was higher for those with chronic condition Special Needs Plan (c-SNP)-defined MCCs (odds ratio (OR) = 1.50, 95% confidence interval (CI) = 1.47-1.52), Charlson Comorbidity Index-defined MCCs (OR = 1.45, 95% CI = 1.42-1.47), ACG-defined MCCs (OR = 1.22, 95% CI = 1.19-1.25), and CCW-defined MCCs (OR = 1.15, 95% CI = 1.11-1.19) than for those without MCCs. CONCLUSION: MCC definitions demonstrate poor agreement and should not be used interchangeably. The two definitions with the greatest agreement (CCI, c-SNP) were also the best predictors of 30-day hospital readmissions.

[Concordance between stratification systems and identification of patients with multiple chronic diseases in Primary Care]. / Concordancia entre sistemas de estratificación e identificación de pacientes crónicos complejos en Atención Primaria.

OBJECTIVE: To determine the prevalence of patients with multiple chronic diseases in Primary Care using the multiple morbidity criteria and Clinical Risk Groups, and the agreement in identifying high-risk patients that require case management with both methods. MATERIAL AND METHOD: A cross-sectional study was conducted on 240 patients, selected by random sampling of 16 care quotas from two Primary Health Care centres of a health area. Informed consent was obtained to access their electronic medical records for the study, and a record was made of age, sex, health status of Clinical Risk Groups, severity, multiple morbidity criteria, and Charlson index by physicians during clinical practice. Three patients were excluded due to incomplete data. RESULTS: The prevalence of patients with multiple chronic diseases following the criteria of the Ministry of Health among users was 4.11 (95% CI; 2.13-7.30). The frequency of patients with high risk Clinical Risk Groups (G3) in the chronicity strategy of Valencian Community was 7.59 (95% CI; 4.70-11.70), which includes patients with health status 6 and complexity level 5-6, and health status 7, 8, and 9. Agreement between the two classifications was low, with a kappa index 0.17 (95% CI; 0-0.5) CONCLUSIONS: The prevalence did not differ significantly from that expected, and the agreement between the two stratifications was very weak, not selecting the same patients for highly complex case management.

[Adjusted morbidity groups: A new multiple morbidity measurement of use in Primary Care]. / Los grupos de morbilidad ajustados: nuevo agrupador de morbilidad poblacional de utilidad en el ámbito de la atención primaria.

The Adjusted Morbidity Groups (GMA) is a new morbidity measurement developed and adapted to the Spanish healthcare System. It enables the population to be classified into 6 morbidity groups, and in turn divided into 5 levels of complexity, along with one healthy population group. Consequently, the population is divided into 31 mutually exclusive categories. The results of the stratification in Catalonia are presented. GMA is a method for grouping morbidity that is comparable to others in the field, but has been developed with data from the Spanish health system. It can be used to stratify the population and to identify target populations. It has good explanatory and predictive results in the use of health resources indicators. The Spanish Ministry of Health is promoting the introduction of the GMA into the National Health System.