Comparison of count-based multimorbidity measures in predicting emergency admission and functional decline in older community-dwelling adults: a prospective cohort study

A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data

BACKGROUND

Multimorbidity is a significant public health concern, characterized by the coexistence and interaction of multiple preexisting medical conditions. This complex condition has been associated with an increased risk of COVID-19. Individuals with multimorbidity who contract COVID-19 often face a significant reduction in life expectancy. The postpandemic period has also highlighted an increase in frailty, emphasizing the importance of integrating existing multimorbidity details into epidemiological risk assessments. Managing clinical data that include medical histories presents significant challenges, particularly due to the sparsity of data arising from the rarity of multimorbidity conditions. Also, the complex enumeration of combinatorial multimorbidity features introduces challenges associated with combinatorial explosions.

OBJECTIVE

This study aims to assess the severity of COVID-19 in individuals with multiple medical conditions, considering their demographic characteristics such as age and sex. We propose an evolutionary machine learning model designed to handle sparsity, analyzing preexisting multimorbidity profiles of patients hospitalized with COVID-19 based on their medical history. Our objective is to identify the optimal set of multimorbidity feature combinations strongly associated with COVID-19 severity. We also apply the Apriori algorithm to these evolutionarily derived predictive feature combinations to identify those with high support.

METHODS

We used data from 3 administrative sources in Piedmont, Italy, involving 12,793 individuals aged 45-74 years who tested positive for COVID-19 between February and May 2020. From their 5-year pre-COVID-19 medical histories, we extracted multimorbidity features, including drug prescriptions, disease diagnoses, sex, and age. Focusing on COVID-19 hospitalization, we segmented the data into 4 cohorts based on age and sex. Addressing data imbalance through random resampling, we compared various machine learning algorithms to identify the optimal classification model for our evolutionary approach. Using 5-fold cross-validation, we evaluated each model's performance. Our evolutionary algorithm, utilizing a deep learning classifier, generated prediction-based fitness scores to pinpoint multimorbidity combinations associated with COVID-19 hospitalization risk. Eventually, the Apriori algorithm was applied to identify frequent combinations with high support.

RESULTS

We identified multimorbidity predictors associated with COVID-19 hospitalization, indicating more severe COVID-19 outcomes. Frequently occurring morbidity features in the final evolved combinations were age>53, R03BA (glucocorticoid inhalants), and N03AX (other antiepileptics) in cohort 1; A10BA (biguanide or metformin) and N02BE (anilides) in cohort 2; N02AX (other opioids) and M04AA (preparations inhibiting uric acid production) in cohort 3; and G04CA (Alpha-adrenoreceptor antagonists) in cohort 4.

CONCLUSIONS

When combined with other multimorbidity features, even less prevalent medical conditions show associations with the outcome. This study provides insights beyond COVID-19, demonstrating how repurposed administrative data can be adapted and contribute to enhanced risk assessment for vulnerable populations.

An exploratory randomised trial investigating feasibility, potential impact and cost effectiveness of link workers for people living with multimorbidity attending general practices in deprived urban communities

BACKGROUND

Social prescribing link workers are non-health or social care professionals who connect people with psychosocial needs to non-clinical community supports. They are being implemented widely, but there is limited evidence for appropriate target populations or cost effectiveness. This study aimed to explore the feasibility, potential impact on health outcomes and cost effectiveness of practice-based link workers for people with multimorbidity living in deprived urban communities.

METHODS

A pragmatic exploratory randomised trial with wait-list usual care control and blinding at analysis was conducted during the COVID 19 pandemic (July 2020 to January 2021). Participants had two or more ongoing health conditions, attended a general practitioner (GP) serving a deprived urban community who felt they may benefit from a one-month practice-based social prescribing link worker intervention.. Feasibility measures were recruitment and retention of participants, practices and link workers, and completion of outcome data. Primary outcomes at one month were health-related quality of life (EQ-5D-5L) and mental health (HADS). Potential cost effectiveness from the health service perspective was evaluated using quality adjusted life years (QALYs), based on conversion of the EQ-5D-5L and ICECAP-A capability index to utility scoring.

RESULTS

From a target of 600, 251 patients were recruited across 13 general practices. Randomisation to intervention (n = 123) and control (n = 117) was after baseline data collection. Participant retention at one month was 80%. All practices and link workers (n = 10) were retained for the trial period. Data completion for primary outcomes was 75%. There were no significant differences identified using mixed effects regression analysis in EQ-5D-5L (MD 0.01, 95% CI -0.07 to 0.09) or HADS (MD 0.05, 95% CI -0.63 to 0.73), and no cost effectiveness advantages. A sensitivity analysis that considered link workers operating at full capacity in a non-pandemic setting, indicated the probability of effectiveness at the €45,000 ICER threshold value for Ireland was 0.787 using the ICECAP-A capability index.

CONCLUSIONS

While the trial under-recruited participants mainly due to COVID-19 restrictions, it demonstrates that robust evaluations and cost utility analyses are possible. Further evaluations are required to establish cost effectiveness and should consider using the ICE-CAP-A wellbeing measure for cost utility analysis.

REGISTRATION

This trial is registered on ISRCTN.

TITLE

Use of link workers to provide social prescribing and health and social care coordination for people with complex multimorbidity in socially deprived areas.

TRIAL ID

ISRCTN10287737. Date registered 10/12/2019. Link: https://www.isrctn.com/ISRCTN10287737.

Promising algorithms to perilous applications: a systematic review of risk stratification tools for predicting healthcare utilisation

OBJECTIVES

Risk stratification tools that predict healthcare utilisation are extensively integrated into primary care systems worldwide, forming a key component of anticipatory care pathways, where high-risk individuals are targeted by preventative interventions. Existing work broadly focuses on comparing model performance in retrospective cohorts with little attention paid to efficacy in reducing morbidity when deployed in different global contexts. We review the evidence supporting the use of such tools in real-world settings, from retrospective dataset performance to pathway evaluation.

METHODS

A systematic search was undertaken to identify studies reporting the development, validation and deployment of models that predict healthcare utilisation in unselected primary care cohorts, comparable to their current real-world application.

RESULTS

Among 3897 articles screened, 51 studies were identified evaluating 28 risk prediction models. Half underwent external validation yet only two were validated internationally. No association between validation context and model discrimination was observed. The majority of real-world evaluation studies reported no change, or indeed significant increases, in healthcare utilisation within targeted groups, with only one-third of reports demonstrating some benefit.

DISCUSSION

While model discrimination appears satisfactorily robust to application context there is little evidence to suggest that accurate identification of high-risk individuals can be reliably translated to improvements in service delivery or morbidity.

CONCLUSIONS

The evidence does not support further integration of care pathways with costly population-level interventions based on risk prediction in unselected primary care cohorts. There is an urgent need to independently appraise the safety, efficacy and cost-effectiveness of risk prediction systems that are already widely deployed within primary care.

Comparing a new multimorbidity index with other multimorbidity measures for predicting disability trajectories

BACKGROUND

The optimal multimorbidity measures for predicting disability trajectories are not universally agreed upon. We developed a multimorbidity index among middle-aged and older community-dwelling Chinese adults and compare its predictive ability of disability trajectories with other multimorbidity measures.

METHODS

This study included 17,649 participants aged ≥50 years from the China Health and Retirement Longitudinal Survey 2011-2018. Two disability trajectory groups were estimated using the total disability score differences calculated between each follow-up visit and baseline. A weighted index was constructed using logistic regression models for disability trajectories based on the training set (70 %). The index and the condition count were used, along with the pattern identified by the latent class analysis to measure multimorbidity at baseline. Logistic regression models were used in the training set to examine associations between each multimorbidity measure and disability trajectories. C-statistics, integrated discrimination improvements, and net reclassification indices were applied to compare the performance of different multimorbidity measures in predicting disability trajectories in the testing set (30 %).

RESULTS

In the newly developed multimorbidity index, the weights of the chronic conditions varied from 1.04 to 2.55. The multimorbidity index had a higher predictive performance than the condition count. The condition count performed better than the multimorbidity pattern in predicting disability trajectories.

LIMITATION

Self-reported chronic conditions.

CONCLUSIONS

The multimorbidity index may be considered an ideal measurement in predicting disability trajectories among middle-aged and older community-dwelling Chinese adults. The condition count is also suggested due to its simplicity and superior predictive performance.

Impact of nurse-led interprofessional work in older patients with heart failure and multimorbidity: A retrospective cohort study

Background

The number of patients with multimorbidity has increased due to the aging of the global population. Although the World Health Organization has indicated that multimorbidity will be a major medical problem in the future, the appropriate interventions for patients with multimorbidity are currently unknown. This study aimed to investigate whether nurse-led interprofessional work is associated with improved prognosis in heart failure patients with multimorbidity aged ≥65 years who were admitted in an acute care hospital.

Methods

Patients who were admitted to the cardiovascular medicine ward of an acute care hospital in Osaka, Japan, and underwent nurse-led interprofessional work from April 1, 2017 to March 31, 2020, and from April 1, 2014 to March 31, 2016, were included in this retrospective cohort study. The patients were matched by age, sex, and New York Heart Association classification. The nurse-led interprofessional work was based on a three-step model that incorporates recommendations from international guidelines for multimorbidity. The primary outcome was all-cause mortality.

Results

The mean age of the participants was 80 years, and 62 % were men. The nurse-led interprofessional work group showed a significant difference in all-cause mortality compared with the usual care group (hazard ratio, 0.45; 95 % confidence interval [CI], 0.29-0.69; P < 0.001). Compared with the usual care group, the nurse-led interprofessional work group exhibited a 7 % difference in mortality rate at 1-year post-discharge (P < 0.001).

Conclusions

Nurse-led interprofessional work may reduce the all-cause mortality in older patients with heart failure and multimorbidity.

Functional limitation in the older Brazilian adults: Association with multimorbidity and socioeconomic conditions

The aim of this study was to assess the association between multimorbidity and the presence of functional limitation in basic (BADL) and instrumental activities of daily living (IADL) among Brazilian older adults and to verify whether this association is moderated by socioeconomic conditions. Cross-sectional study with data from the Brazilian National Health Survey (PNS) (2019) for the Brazilian population aged 60 years and over. The dependent variables were functional limitation, based on self-reported difficulty in performing one or more activities of daily living, including six BADL (feeding, bathing, using the toilet, dressing, crossing a room on the same floor and getting out of bed) and four IADL (shopping, managing money, taking medication and using transportation). The independent variables were multimorbidity (presence of two or more self-reported chronic diseases) and socioeconomic measures (per capita household income, asset score, and education level). The association between multimorbidity and outcomes was assessed using adjusted logistic regression models. The moderating effect of socioeconomic conditions on the association between multimorbidity and functional limitations was assessed by including an interaction term. The final sample consisted of 22,725 individuals. The prevalence of functional limitation was 8.5% (95%CI: 7.9-9.2) and 18.6% (95%CI: 17.8-19.5) in BADL and IADL, respectively. Multimorbidity was associated with BADL [OR: 2.30 (95%CI: 1.93-2.74)] and IADL [OR: 2.26 (95%CI: 1.98-2.57)]. The odds of functional limitation were higher among individuals with lower levels of education and income, but there was no interaction between multimorbidity and socioeconomic position measures. Multimorbidity was associated with functional limitation (BADL and IADL) and socioeconomic conditions, and this association was constant across socioeconomic position levels.

Simple approaches to characterising multiple long-term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants

BACKGROUND

Numerous approaches are used to characterise multiple long-term conditions (MLTC), including counts and indices. Few studies have compared approaches within the same dataset. We aimed to characterise MLTC using simple approaches, and compare their prevalence estimates of MLTC and associations with emergency hospital admission in the UK Biobank.

METHODS

We used baseline data from 495,465 participants (age 38-73 years) to characterise MLTC using four approaches: Charlson index (CI), Byles index (BI), count of 43 conditions (CC) and count of body systems affected (BC). We defined MLTC as more than two conditions using CI, BI and CC, and more than two body systems using BC. We categorised scores (incorporating weightings for the indices) from each approach as 0, 1, 2 and 3+. We used linked hospital episode statistics and performed survival analyses to test associations with an endpoint of emergency hospital admission or death over 5 years.

RESULTS

The prevalence of MLTC was 44% (BC), 33% (CC), 6% (BI) and 2% (CI). Higher scores using all approaches were associated with greater outcome rates independent of sex and age group. For example, using CC, compared with score 0, score 2 had 1.95 (95% CI: 1.91, 1.99) and a score of 3+ had 3.12 (95% CI: 3.06, 3.18) times greater outcome rates. The discriminant value of all approaches was modest (C-statistics 0.60-0.63).

CONCLUSIONS

The counts classified a greater proportion as having MLTC than the indices, highlighting that prevalence estimates of MLTC vary depending on the approach. All approaches had strong statistical associations with emergency hospital admission but a modest ability to identify individuals at risk.

A systematic review of risk stratification tools internationally used in primary care settings

BACKGROUND AND AIMS

In our current healthcare situation, burden on healthcare services is increasing, with higher costs and increased utilization. Structured population health management has been developed as an approach to balance quality with increasing costs. This approach identifies sub-populations with comparable health risks, to tailor interventions for those that will benefit the most. Worldwide, the use of routine healthcare data extracted from electronic health registries for risk stratification approaches is increasing. Different risk stratification tools are used on different levels of the healthcare continuum. In this systematic literature review, we aimed to explore which tools are used in primary healthcare settings and assess their performance.

METHODS

We performed a systematic literature review of studies applying risk stratification tools with health outcomes in primary care populations. Studies in Organisation for Economic Co-operation and Development countries published in English-language journals were included. Search engines were utilized with keywords, for example, "primary care," "risk stratification," and "model." Risk stratification tools were compared based on different measures: area under the curve (AUC) and C-statistics for dichotomous outcomes and R 2 for continuous outcomes.

RESULTS

The search provided 4718 articles. Specific election criteria such as primary care populations, generic health utilization outcomes, and routinely collected data sources identified 61 articles, reporting on 31 different models. The three most frequently applied models were the Adjusted Clinical Groups (ACG, n = 23), the Charlson Comorbidity Index (CCI, n = 19), and the Hierarchical Condition Categories (HCC, n = 7). Most AUC and C-statistic values were above 0.7, with ACG showing slightly improved scores compared with the CCI and HCC (typically between 0.6 and 0.7).

CONCLUSION

Based on statistical performance, the validity of the ACG was the highest, followed by the CCI and the HCC. The ACG also appeared to be the most flexible, with the use of different international coding systems and measuring a wider variety of health outcomes.

An analysis of frailty and multimorbidity in 20,566 UK Biobank participants with type 2 diabetes

Background

Frailty and multimorbidity are common in type 2 diabetes (T2D), including people <65 years. Guidelines recommend adjustment of treatment targets in people with frailty or multimorbidity. It is unclear how recommendations to adjust treatment targets in people with frailty or multimorbidity should be applied to different ages. We assess implications of frailty/multimorbidity in middle/older-aged people with T2D.

Methods

We analysed UK Biobank participants (n = 20,566) with T2D aged 40–72 years comparing two frailty measures (Fried frailty phenotype and Rockwood frailty index) and two multimorbidity measures (Charlson Comorbidity index and count of long-term conditions (LTCs)). Outcomes were mortality, Major Adverse Cardiovascular Event (MACE), hospitalization with hypoglycaemia or fall/fracture.

Results

Here we show  that choice of measure influences the population identified: 42% of participants are frail or multimorbid by at least one measure; 2.2% by all four measures. Each measure is associated with mortality, MACE, hypoglycaemia, and fall or fracture. The absolute 5-year mortality risk is higher in older versus younger participants with a given level of frailty (e.g. 1.9%, and 9.9% in men aged 45 and 65, respectively, using frailty phenotype) or multimorbidity (e.g. 1.3%, and 7.8% in men with 4 LTCs aged 45 and 65, respectively). Using frailty phenotype, the relationship between higher HbA1c and mortality is stronger in frail compared with pre-frail or robust participants.

Conclusions

Assessment of frailty/multimorbidity should be embedded within routine management of middle-aged and older people with T2D. Method of identification as well as features such as age impact baseline risk and should influence clinical decisions (e.g. glycaemic control).

Defining Multimorbidity and Its Impact in Older United States Veterans Newly Treated for Multiple Myeloma

BACKGROUND

Traditional count-based measures of comorbidity are unlikely to capture the complexity of multiple chronic conditions (multimorbidity) in older adults with cancer. We aimed to define patterns of multimorbidity and their impact in older United States veterans with multiple myeloma (MM).

METHODS

We measured 66 chronic conditions in 5076 veterans aged 65 years and older newly treated for MM in the national Veterans Affairs health-care system from 2004 to 2017. Latent class analysis was used to identify patterns of multimorbidity among these conditions. These patterns were then assessed for their association with overall survival, our primary outcome. Secondary outcomes included emergency department visits and hospitalizations.

RESULTS

Five patterns of multimorbidity emerged from the latent class analysis, and survival varied across these patterns (log-rank 2-sided P < .001). Older veterans with cardiovascular and metabolic disease (30.9%, hazard ratio [HR] = 1.33, 95% confidence interval [CI] = 1.21 to 1.45), psychiatric and substance use disorders (9.7%, HR = 1.58, 95% CI = 1.39 to 1.79), chronic lung disease (15.9%, HR = 1.69, 95% CI = 1.53 to 1.87), and multisystem impairment (13.8%, HR = 2.25, 95% CI = 2.03 to 2.50) had higher mortality compared with veterans with minimal comorbidity (29.7%, reference). Associations with mortality were maintained after adjustment for sociodemographic variables, measures of disease risk, and the count-based Charlson Comorbidity Index. Multimorbidity patterns were also associated with emergency department visits and hospitalizations.

CONCLUSIONS

Our findings demonstrate the need to move beyond count-based measures of comorbidity and consider cancer in the context of multiple chronic conditions.

Longitudinal Follow-Up Studies on the Bidirectional Association between ADL/IADL Disability and Multimorbidity: Results from Two National Sample Cohorts of Middle-Aged and Elderly Adults

BACKGROUND AND OBJECTIVES

Few studies have investigated the bidirectional relationship between disability and multimorbidity, which are common conditions among the older population. Based on the data from the China Health and Retirement Longitudinal Study (CHARLS) and the Survey of Health, Ageing and Retirement in Europe (SHARE), we aimed to investigate the bidirectional relationship between disability and multimorbidity.

METHODS

The activities of daily living (ADLs) and the instrumental activities of daily living (IADLs) scales were used to measure disability. In stage I, we used multinomial logistic regression to assess the longitudinal association between ADL/IADL disability and follow-up multimorbidity. In stage II, binary logistic regression was used to evaluate the multimorbidity effect on future disability.

RESULTS

Compared with those free of disability, people with disability possessed ascending risks for developing an increasing number of diseases. For ADL disability, the odds ratio (OR) (95% confidence interval [CI]) values of developing ≥4 diseases were 4.10 (2.58, 6.51) and 6.59 (4.54, 9.56) in CHARLS and SHARE; for IADL disability, the OR (95% CI) values were 2.55 (1.69, 3.84) and 4.85 (3.51, 6.70) in CHARLS and SHARE. Meanwhile, the number of diseases at baseline was associated, in a dose-response manner, with future disability. Compared with those without chronic diseases, participants carrying ≥4 diseases had OR (95% CI) values of 4.82 (3.73, 6.21)/4.66 (3.65, 5.95) in CHARLS and 3.19 (2.59, 3.94)/3.28 (2.71, 3.98) in SHARE for developing ADL/IADL disability.

CONCLUSION

The consistent findings across 2 national longitudinal studies supported a strong bidirectional association between disability and multimorbidity among middle-aged and elderly adults. Thus, tailored interventions should be taken to prevent the mutual development of disability and multimorbidity.

Primary care-based link workers providing social prescribing to improve health and social care outcomes for people with multimorbidity in socially deprived areas (the LinkMM trial): Pilot study for a pragmatic randomised controlled trial

Introduction

Individuals with multimorbidity in deprived areas experience worse health outcomes and fragmented care. Research suggests that primary care-based link workers providing social prescribing have potential to improve health and well-being. This paper reports the results of a pilot study conducted in preparation for a randomised controlled trial (RCT) that aims to test the effectiveness of primary care-based link workers providing social prescribing in improving health outcomes for people with multimorbidity who attend general practices in deprived areas in Ireland.

Methods

An uncontrolled pilot study of an intervention based on the Glasgow Deep End links worker programme, in a single general practice, tested the feasibility and acceptability of planned processes for a RCT. Outcomes were recruitment and retention rates and acceptability of the trial processes and intervention to patients, general practitioners (GPs) and the link worker. Structured interviews were conducted with six patients, the link worker and two GPs within the practice and analysed using descriptive qualitative analysis. Feedback from a Public Patient Involvement group and an Implementation Advisory Group of key stakeholders was incorporated into the evaluation process.

Results

Twelve out of 14 patients completed the intervention. Selection and recruitment processes were lengthier than expected. GPs recommended including psychosocial need in the selection process. Interviewed patients, the GPs and the link worker were positive about the intervention.

Conclusion

A range of adaptations were identified for the main trial, mainly considering psychosocial need in the selection process to reflect normal referral pathways. This has resulted in a pragmatic RCT design.

Systematic review on the instruments used for measuring the association of the level of multimorbidity and clinically important outcomes

OBJECTIVES

There are multiple instruments for measuring multimorbidity. The main objective of this systematic review was to provide a list of instruments that are suitable for use in studies aiming to measure the association of a specific outcome with different levels of multimorbidity as the main independent variable in community-dwelling individuals. The secondary objective was to provide details of the requirements, strengths and limitations of these instruments, and the chosen outcomes.

METHODS

We conducted the review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO registration number: CRD42018105297). We searched MEDLINE, Embase and CINAHL electronic databases published in English and manually searched the Journal of Comorbidity between 1 January 2010 and 23 October 2020 inclusive. Studies also had to select adult patients from primary care or general population and had at least one specified outcome variable. Two authors screened the titles, abstracts and full texts independently. Disagreements were resolved with a third author. The modified Newcastle-Ottawa Scale was used for quality assessment.

RESULTS

Ninety-six studies were identified, with 69 of them rated to have a low risk of bias. In total, 33 unique instruments were described. Disease Count and weighted indices like Charlson Comorbidity Index were commonly used. Other approaches included pharmaceutical-based instruments. Disease Count was the common instrument used for measuring all three essential core outcomes of multimorbidity research: mortality, mental health and quality of life. There was a rise in the development of novel weighted indices by using prognostic models. The data obtained for measuring multimorbidity were from sources including medical records, patient self-reports and large administrative databases.

CONCLUSIONS

We listed the details of 33 instruments for measuring the level of multimorbidity as a resource for investigators interested in the measurement of multimorbidity for its association with or prediction of a specific outcome.

Link workers providing social prescribing and health and social care coordination for people with multimorbidity in socially deprived areas (the LinkMM trial): protocol for a pragmatic randomised controlled trial

INTRODUCTION

Link workers are non-health or social care professionals based in primary care who support people to develop and achieve a personalised set of health and social goals by engaging with community resources. Link workers have been piloted in areas of deprivation, but there remains insufficient evidence to support their effectiveness. Multimorbidity is increasing in prevalence, but there are limited evidence-based interventions. This paper presents the protocol for a randomised controlled trial (RCT) that will test the effectiveness of link workers based in general practices in deprived areas in improving health outcomes for people with multimorbidity.

METHODS AND ANALYSIS

The protocol presents the proposed pragmatic RCT, involving 10 general practitioner (GP) practices and 600 patients. Eligible participants will be community dwelling adults with multimorbidity (≥two chronic conditions) identified as being suitable for referral to a practice-based link worker. Following baseline data collection, the patients will be randomised into intervention group that will meet the link worker over a1-month period, or a 'wait list' control that will receive usual GP care. Primary outcomes are health-related quality of life as assessed by EQ-5D-5L and mental health assessed by Hospital Anxiety and Depression Scale. Secondary outcomes are based on the core outcome set for multimorbidity. Data will be collected at baseline and on intervention completion at 1 month using questionnaires self-completed by participants and GP records. Parallel process and economic analyses will be conducted to explore participants' experiences and examine cost-effectiveness of the link worker intervention.

ETHICS AND DISSEMINATION

Ethical approval has been granted by the Irish College of General Practitioners Ethics Committee. The findings will be published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

ISRCTN10287737;Pre-results.

Effect of medicines management versus standard care on readmissions in multimorbid patients: a randomised controlled trial

OBJECTIVE

To investigate the effect of pharmacist-led medicines management in multimorbid, hospitalised patients on long-term hospital readmissions and survival.

DESIGN

Parallel-group, randomised controlled trial.

SETTING

Recruitment from an internal medicine hospital ward in Oslo, Norway. Patients were enrolled consecutively from August 2014 to the predetermined target number of 400 patients. The last participant was enrolled March 2016. Follow-up until 31 December 2017, that is, 21-40 months.

PARTICIPANTS

Acutely admitted multimorbid patients ≥18 years, using minimum four regular drugs from minimum two therapeutic classes. 399 patients were randomly assigned, 1:1, to the intervention or control group. After excluding 11 patients dying in-hospital and 2 erroneously included, the primary analysis comprised 386 patients (193 in each group) with median age 79 years (range 23-96) and number of diseases 7 (range 2-17).

INTERVENTION

Intervention patients received pharmacist-led medicines management comprising medicines reconciliation at admission, repeated medicines reviews throughout the stay and medicines reconciliation and tailored information at discharge, according to the integrated medicines management model. Control patients received standard care.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary endpoint was difference in time to readmission or death within 12 months. Overall survival was a priori the clinically most important secondary endpoint.

RESULTS

Pharmacist-led medicines management had no significant effect on the primary endpoint time to readmission or death within 12 months (median 116 vs 184 days, HR 0.82, 95% CI 0.64 to 1.04, p=0.106). A statistically significantly increased overall survival was observed during 21-40 months follow-up (HR 0.66, 95% CI 0.48 to 0.90, p=0.008).

CONCLUSIONS

Pharmacist-led medicines management had no statistically significant effect on time until readmission or death. A statistically significant increased overall survival was seen. Further studies should be conducted to investigate the effect of such an intervention on a larger scale.

TRIAL REGISTRATION NUMBER

NCT02336113.

Patterns of emergency admissions for ambulatory care sensitive conditions: a spatial cross-sectional analysis of observational data

OBJECTIVES

To examine the spatial and temporal patterns of English general practices' emergency admissions for Ambulatory Care Sensitive Conditions (ACSCs).

DESIGN

Observational study of practice level annual hospital emergency admissions data for ACSCs for all English practices from 2004-2017.

PARTICIPANTS

All patients with an emergency admission to a National Health Service hospital in England who were registered with an English general practice.

MAIN OUTCOME MEASURE

Practice level age and gender indirectly standardised ratios (ISARs) for emergency admissions for ACSC.

RESULTS

In 2017, 41.8% of the total variation in ISARs across practices was between the 207 Clinical Commissioning Groups (CCGs) (the administrative unit for general practices) and 58.2% was across practices within CCGs. ACSC ISARs increased by 4.7% between 2004 and 2017, while those for conditions incentivised by the Quality and Outcomes Framework (QOF) fell by 20%. Practice ISARs are persistent: practices with high rates in 2004 also had high rates in 2017. Standardising by deprivation as well as age and gender reduced the coefficient of variation of practice ISARs in 2017 by 22%.

CONCLUSIONS

There is persistent spatial pattern of emergency admissions for ACSC across England both within and across CCGs. We illustrate the reduction in ACSCs emergency admissions across the study period for conditions incentivised by the QOF but find that this was not accompanied by a reduction in variation in these admissions across practices. The observed spatial pattern persists when admission rates are standardised by deprivation. The persistence of spatial clusters of high emergency admissions for ACSCs within and across CCG boundaries suggests that policies to reduce potentially unwarranted variation should be targeted at practice level.

Functional Limitations Mediate the Relationship Between Pain and Depressive Symptoms in Former NFL Athletes

The objective of this study was to analyze data from the National Football League Player Care Foundation Study of Retired NFL Players to understand potential risks for depressive symptoms in former athletes by investigating the relationship between pain and depressive symptoms in a multivariate context, while simultaneously exploring the potential connection with functional limitations. Descriptive statistics were used to describe the study sample and to conduct bivariate comparisons by race and age cohort. Linear regression models were conducted in the subsample of respondents reporting on depressive symptoms using the PHQ-9. Models examine the relationship of bodily pain, injury as a reason for retirement or not re-signing with a team, length of NFL career, sociodemographic characteristics, chronic conditions, and functional limitations to depression. Interaction terms tested whether race and age moderated the effect of bodily pain and functional limitations on depressive symptoms. Bivariate associations revealed no significant differences between younger and older former players in indicators of pain and only slightly higher functional limitations among younger former players. In the multivariate models, pain was significantly associated with depressive symptoms (β = 0.36; p < .01), net of a range of relevant controls. Adding an index of functional limitations reduced this association by nearly half (β = 0.20; p < .01) and functional limitations was significantly associated with depressive symptoms (β = 0.40; p < .01). No statistically significant interactions were found. Overall, bodily pain was strongly associated with depressive symptoms. After accounting for the effects of functional limitations, this association was notably reduced. These results may be useful in identifying aging-related physical declines in relatively younger adult men who may be at the greatest risk for depression. They highlight how physical functionality and activity may mitigate the risk of depression, even in the presence of significant bodily pain.

Sociodemographic and lifestyle predictors of incident hospital admissions with multimorbidity in a general population, 1999-2019: the EPIC-Norfolk cohort

BACKGROUND

The ageing population and prevalence of long-term disorders with multimorbidity are a major health challenge worldwide. The associations between comorbid conditions and mortality risk are well established; however, few prospective community-based studies have reported on prior risk factors for incident hospital admissions with multimorbidity. We aimed to explore the independent associations for a range of demographic, lifestyle and physiological determinants and the likelihood of subsequent hospital incident multimorbidity.

METHODS

We examined incident hospital admissions with multimorbidity in 25 014 men and women aged 40-79 in a British prospective population-based study recruited in 1993-1997 and followed up until 2019. The determinants of incident multimorbidity, defined as Charlson Comorbidity Index ≥3, were investigated using multivariable logistic regression models for the 10-year period 1999-2009 and repeated with independent measurements in a second 10-year period 2009-2019.

RESULTS

Between 1999 and 2009, 18 179 participants (73% of the population) had a hospital admission. Baseline 5-year and 10-year incident multimorbidities were observed in 6% and 12% of participants, respectively. Age per 10-year increase (OR 2.19, 95% CI 2.06 to 2.33) and male sex (OR 1.32, 95% CI 1.19 to 1.47) predicted incident multimorbidity over 10 years. In the subset free of the most serious diseases at baseline, current smoking (OR 1.86, 95% CI 1.60 to 2.15), body mass index >30 kg/m² (OR 1.48, 95% CI 1.30 to 1.70) and physical inactivity (OR 1.16, 95% CI 1.04 to 1.29) were positively associated and plasma vitamin C (a biomarker of plant food intake) per SD increase (OR 0.86, 95% CI 0.81 to 0.91) inversely associated with incident 10-year multimorbidity after multivariable adjustment for age, sex, social class, education, alcohol consumption, systolic blood pressure and cholesterol. Results were similar when re-examined for a further time period in 2009-2019.

CONCLUSION

Age, male sex and potentially modifiable lifestyle behaviours including smoking, body mass index, physical inactivity and low fruit and vegetable intake were associated with increased risk of future incident hospital admissions with multimorbidity.

Agreement between self-reported morbidity and pharmacy claims data for prescribed medications in an older community based population

Background

Studies have indicated variability around prevalence estimates of multimorbidity due to poor consensus regarding its definition and measurement. Medication-based measures of morbidity may be valuable resources in the primary-care setting where access to medical data can be limited. We compare the agreement between patient self-reported and medication-based morbidity; and examine potential patient-level predictors of discordance between these two measures of morbidity in an older (≥ 50 years) community-based population.

Methods

A retrospective cohort study was performed using national pharmacy claims data linked to The Irish LongituDinal study on Ageing (TILDA). Morbidity was measured by patient self-report (TILDA) and two medication-based measures, the Rx-Risk (< 65 years) and Rx-Risk-V (≥65 years), which classify drug claims into chronic disease classes. The kappa statistic measured agreement between self-reported and medication-based morbidity at the individual patient-level. Multivariate logistic regression was used to examine patient-level characteristics associated with discordance between measures of morbidity.

Results

Two thousand nine hundred twenty-five patients were included (< 65 years: N = 1095, 37.44%; and ≥ 65 years: N = 1830 62.56%). Hypertension and high cholesterol were the most prevalent self-reported morbidities in both age cohorts. Agreement was good or very good (κ = 0.61–0.81) for diabetes, osteoporosis and glaucoma; and moderate for high cholesterol, asthma, Parkinson’s and angina (κ = 0.44–0.56). All other conditions had fair or poor agreement. Age, gender, marital status, education, poor-delayed recall, depression and polypharmacy were significantly associated with discordance between morbidity measures.

Conclusions

Most conditions achieved only moderate or fair agreement between self-reported and medication-based morbidity. In order to improve the accuracy in prevalence estimates of multimorbidity, multiple measures of multimorbidity may be necessary. Future research should update the current Rx-Risk algorithms in-line with current treatment guidelines, and re-assess the feasibility of using these indices alone, or in combination with other methods, to yield more accurate estimates of multimorbidity.

Comorbidity phenotypes and risk of mortality in patients with ischaemic heart disease in the UK

Objectives

The objective of this study is to use latent class analysis of up to 20 comorbidities in patients with a diagnosis of ischaemic heart disease (IHD) to identify clusters of comorbidities and to examine the associations between these clusters and mortality.

Methods

Longitudinal analysis of electronic health records in the health improvement network (THIN), a UK primary care database including 92 186 men and women aged ≥18 years with IHD and a median of 2 (IQR 1–3) comorbidities.

Results

Latent class analysis revealed five clusters with half categorised as a low-burden comorbidity group. After a median follow-up of 3.2 (IQR 1.4–5.8) years, 17 645 patients died. Compared with the low-burden comorbidity group, two groups of patients with a high-burden of comorbidities had the highest adjusted HR for mortality: those with vascular and musculoskeletal conditions, HR 2.38 (95% CI 2.28 to 2.49) and those with respiratory and musculoskeletal conditions, HR 2.62 (95% CI 2.45 to 2.79). Hazards of mortality in two other groups of patients characterised by cardiometabolic and mental health comorbidities were also higher than the low-burden comorbidity group; HR 1.46 (95% CI 1.39 to 1.52) and 1.55 (95% CI 1.46 to 1.64), respectively.

Conclusions

This analysis has identified five distinct comorbidity clusters in patients with IHD that were differentially associated with risk of mortality. These analyses should be replicated in other large datasets, and this may help shape the development of future interventions or health services that take into account the impact of these comorbidity clusters.

Measuring multimorbidity beyond counting diseases: systematic review of community and population studies and guide to index choice

OBJECTIVES

To identify and summarise existing indices for measuring multimorbidity beyond disease counts, to establish which indices include mental health comorbidities or outcomes, and to develop recommendations based on applicability, performance, and usage.

DESIGN

Systematic review.

DATA SOURCES

Seven medical research databases (Medline, Web of Science Core Collection, Cochrane Library, Embase, PsycINFO, Scopus, and CINAHL Plus) from inception to October 2018 and bibliographies and citations of relevant papers. Searches were limited to English language publications.

ELIGIBILITY CRITERIA FOR STUDY SELECTION

Original articles describing a new multimorbidity index including more information than disease counts and not focusing on comorbidity associated with one specific disease. Studies were of adults based in the community or at population level.

RESULTS

Among 7128 search results, 5560 unique titles were identified. After screening against eligibility criteria the review finally included 35 papers. As index components, 25 indices used conditions (weighted or in combination with other parameters), five used diagnostic categories, four used drug use, and one used physiological measures. Predicted outcomes included mortality (18 indices), healthcare use or costs (13), hospital admission (13), and health related quality of life (7). 29 indices considered some aspect of mental health, with most including it as a comorbidity. 12 indices are recommended for use.

CONCLUSIONS

35 multimorbidity indices are available, with differing components and outcomes. Researchers and clinicians should examine existing indices for suitability before creating new ones.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017074211.

Multimorbidity of chronic non-communicable diseases in low- and middle-income countries: A scoping review

BACKGROUND

Multimorbidity is rising in low- and middle-income countries (LMICs). However, the evidence on its epidemiology from LMICs settings is limited and the available literature has not been synthesized as yet.

OBJECTIVES

To review the available evidence on the epidemiology of multimorbidity in LMICs.

METHODS

PubMed, Scopus, PsycINFO and Grey literature databases were searched. We followed the PRISMA-ScR reporting guideline.

RESULTS

Of 33, 110 articles retrieved, 76 studies were eligible for the epidemiology of multimorbidity. Of these 76 studies, 66 (86.8%) were individual country studies. Fifty-two (78.8%) of which were confined to only six middle-income countries: Brazil, China, South Africa, India, Mexico and Iran. The majority (n = 68, 89.5%) of the studies were crosssectional in nature. The sample size varied from 103 to 242, 952. The largest proportion (n = 33, 43.4%) of the studies enrolled adults. Marked variations existed in defining and measuring multimorbidity. The prevalence of multimorbidity in LMICs ranged from 3.2% to 90.5%.

CONCLUSION AND RECOMMENDATIONS

Studies on the epidemiology of multimorbidity in LMICs are limited and the available ones are concentrated in few countries. Despite variations in measurement and definition, studies consistently reported high prevalence of multimorbidity. Further research is urgently required to better understand the epidemiology of multimorbidity and define the best possible interventions to improve outcomes of patients with multimorbidity in LMICs.

Multimorbidity predicts functional decline in community-dwelling older adults: Prospective cohort study

OBJECTIVE

To determine if multimorbidity is associated with functional status, and to assess if multimorbidity predicts declining functional status over a 5-year time frame, after accounting for baseline functional status and other potential confounding factors.

DESIGN

Analysis of an existing population-based cohort study.

SETTING

Manitoba.

PARTICIPANTS

Community-dwelling adults aged 65 and older.

MAIN OUTCOME MEASURES

Age, sex, education, and the Mini-Mental State Examination (MMSE) and Center for Epidemiological Studies Depression Scale (CES-D) scores were recorded for each patient. Multimorbidity was measured using a simple tally of self-reported diseases. Function was measured using the Older Americans Resources and Services scale in 1991 to 1992 and again 5 years later. Good or excellent level of function was compared with level of disability (mild or moderate or higher). Cross-sectional and prospective analyses were conducted.

RESULTS

In a cross-sectional analysis, multimorbidity predicted disability. The unadjusted odds ratio (OR) (95% CI) for disability was 1.45 (1.39 to 1.52) for each additional chronic illness. In models adjusting for age, sex, education, and MMSE and CES-D scores, the adjusted OR (95% CI) was 1.35 (1.29 to 1.42) for each additional chronic illness. Multimorbidity also predicted disability 5 years later. The unadjusted OR (95% CI) was 1.31 (1.24 to 1.38). In models adjusting for age, sex, education, and MMSE and CES-D scores in addition to baseline functional status, the adjusted OR (95% CI) was 1.15 (1.09 to 1.24).

CONCLUSION

Multimorbidity predicts disability in cross-sectional and prospective analyses.

Measuring multimorbidity in hospitalised patients using linked hospital episode data: comparison of two measures

Introduction

Multimorbidity is a complex and growing health challenge. There is no accepted “gold standard” multimorbidity measure for hospital resource planning, and few studies have compared measures in hospitalised patients.

Aim

To evaluate operationalisation of two multimorbidity measures in routine hospital episode data in NHS Grampian, Scotland.

Methods

Linked hospital episode data (Scottish Morbidity Record (SMR)) for the years 2009-2016 were used. Adults admitted to hospital as a general/acute inpatient during 2014 were included. Conditions (ICD-10) were identified from general/acute (SMR01) and psychiatric (SMR04) admissions during the five years prior to first admission in 2014. Two count-based multimorbidity measures were used (Charlson Comorbidity Index and Tonelli et al.), and multimorbidity was defined as ≥2 conditions. Kappa statistics assessed agreement. The association between multimorbidity and length of stay, readmission and mortality was assessed using logistic and negative binomial regression as appropriate.

Results

In 41,545 adults (median age 62 years, 52.6% female), multimorbidity prevalence was 15.1% (95% CI 14.8%, 15.5%) using Charlson and 27.4% (27.0%, 27.8%) using Tonelli – agreement 85.1% (Kappa 0.57). Multimorbidity prevalence, using both measures, increased with age. Multimorbidity was higher in males (16.5%) than females (13.9%) using the Charlson measure, but similar across genders when measured with Tonelli. After adjusting for covariates, multimorbidity remained associated with longer length of stay (Charlson IRR 1.1 (1.0, 1.2); Tonelli IRR 1.1 (1.0, 1.2)) and readmission (Charlson OR 2.1 (1.9, 2.2); Tonelli OR 2.1 (2.0, 2.2)). Multimorbidity had a stronger association with mortality when measured using Charlson (OR 2.7 (2.5, 2.9)), than using Tonelli (OR 1.8 (1.7, 2.0)).

Conclusions

Multimorbidity measures operationalised in hospital episode data identified those at risk of poor outcomes and such operationalised tools will be useful for future multimorbidity research and use in secondary care data systems. Multimorbidity measures are not interchangeable, and the choice of measure should depend on the purpose.

Highlights

Predicting poorer health outcomes in older community-dwelling patients with multimorbidity: prospective cohort study assessing the accuracy of different multimorbidity definitions

PURPOSE

Multimorbidity is commonly defined and measured using condition counts. The UK National Institute for Health Care Excellence Guidelines for Multimorbidity suggest that a medication-orientated approach could be used to identify those in need of a multimorbidity approach to management.

OBJECTIVES

To compare the accuracy of medication-based and diagnosis-based multimorbidity measures at higher cut-points to identify older community-dwelling patients who are at risk of poorer health outcomes.

DESIGN

A secondary analysis of a prospective cohort study with a 2-year follow-up (2010-2012).

SETTING

15 general practices in Ireland.

PARTICIPANTS

904 older community-dwelling patients.

EXPOSURE

Baseline multimorbidity measurements based on both medication classes count (MCC) and chronic disease count (CDC).

OUTCOMES

Mortality, self-reported health related quality of life, mental health and physical functioning at follow-up.

ANALYSIS

Sensitivity, specificity, positive predictive values (PPV) and negative predictive values (NPV) adjusting for clustering by practice for each outcome using both definitions.

RESULTS

Of the 904 baseline participants, 53 died during follow-up and 673 patients completed the follow-up questionnaire. At baseline, 223 patients had 3 or more chronic conditions and 89 patients were prescribed 10 or more medication classes. Sensitivity was low for both MCC and CDC measures for all outcomes. For specificity, MCC was better for all outcomes with estimates varying from 88.8% (95% CI 85.2% to 91.6%) for physical functioning to 90.9% (95% CI 86.2% to 94.1%) for self-reported health-related quality of life. There were no differences between MCC and CDC in terms of PPV and NPV for any outcomes.

CONCLUSIONS

Neither measure demonstrated high sensitivity. However, MCC using a definition of 10 or more regular medication classes to define multimorbidity had higher specificity for predicting poorer health outcomes. While having limitations, this definition could be used for proactive identification of patients who may benefit from targeted clinical care.

Identifying Older Patients at High Risk for Emergency Department Visits and Hospitalization

Hospitalizations are costly, potentially hazardous for older patients, and sometimes preventable. With Medicare's implementation of hospital penalties for 30-day readmissions on certain index conditions, health care organizations have prioritized addressing those issues that lead to avoidable hospitalizations. Little is known about the utility and feasibility of using standardized tools to identify adults at risk for hospitalizations in primary care. In this study, the goal was to determine, from a sample of 60 adults aged 65 and older, whether the Probability of Repeat Admission (PRA), the Vulnerable Elders Survey (VES-13), or a provider estimate of likelihood of hospitalization could identify patients at high risk for emergency department (ED) visits or hospitalization at 6 and 12 months, while being feasible to administer in a primary care setting. PRA, VES-13, and provider estimate were administered in an outpatient practice. Number of ED visits and hospitalizations at 6 and 12 months were assessed through follow-up phone calls and chart review. PRA and provider estimate were not significant predictors of hospitalizations at 6 months (PRA odds ratio [OR] 1.95; P = 0.39; physician estimate OR 4.33, P = 0.08), but were at 12 months (PRA OR 6.00; P < 0.001; physician estimate OR 2.3; P < 0.05). Additionally, a hospitalization during the prior year was not a significant predictor of hospitalization at 6 months (OR 2.97; P = 0.15) but was at 12 months (OR 3.89, P < 0.05). No tool was a significant predictor of ED visits at either time. PRA and the physician estimate were easy to administer and feasible to implement in a primary care setting.

Multimorbidity patterns and 5-year overall mortality: Results from a claims data-based observational study

Background:

Multimorbidity is prevalent and related to adverse outcomes. The effect on mortality is disputed, possibly because studies show differences in the diseases which operationalize multimorbidity. The aim of this study is to analyze the effects of three multimorbidity patterns (representing subgroups of diseases) on mortality.

Methods:

We conducted a longitudinal observational study based on insurance claims data of ambulatory care from 2005 to 2009. Analyses are based on 46 chronic conditions with a prevalence ≥1%. We included 52,217 females and 71,007 males aged 65+ and insured by the Gmünder ErsatzKasse throughout 2004. Our outcome was 5-year overall mortality documented as exact time of death. We calculated hazard ratios by Cox regression analyses with time-dependent covariates. Three statistical models were analyzed: (a) the individual diseases, (b) the number of diseases in multimorbidity patterns, and (c) a count of all diseases, all calculated separately for genders and adjusted for age.

Results:

During the study period, 12,473 males (17.6%) and 7,457 females (14.3%) died. The general effect of multimorbidity on mortality was small (females: 1.02, 1.01–1.02; males: 1.04, 1.03–1.04). The number of neuropsychiatric disorders was related to higher mortality (1.33, 1.30–1.36; 1.46, 1.43–1.50). Cardiovascular and metabolic disorders had inconsistent effects (0.99, 0.97–1.01; 1.08, 1.07–1.09). Psychiatric, psychosomatic, and pain-related disorders were related to higher life expectancy (0.87, 0.86–0.89; 0.88, 0.87–0.90).

Conclusions:

Chronic diseases have heterogeneous effects on mortality and generalized measures of multimorbidity reflect and even out the effects of the single diseases. In multimorbidity studies, a careful selection of diseases is therefore important.

Numeracy and Understanding of Quantitative Aspects of Predictive Models: A Pilot Study

BACKGROUND

The assessment of user preferences for performance characteristics of patient-oriented clinical prediction models is lacking. It is unknown if complex statistical aspects of prediction models are readily understandable by a general audience.

OBJECTIVE

A pilot study was conducted among nonclinical audiences to determine the feasibility of interpreting statistical concepts that describe the performance of prediction models.

METHODS

We conducted a cross-sectional electronic survey using the Amazon Mechanical Turk platform. The survey instrument included educational modules about predictive models, sensitivity, specificity, and confidence intervals (CIs). Follow-up questions tested participants' abilities to interpret these characteristics with both verbatim and gist knowledge. Objective and subjective numeracy were assessed using previously validated instruments. We also tested understanding of these concepts when embedded in a sample discrete choice experiment task to establish feasibility for future elicitation of preferences using a discrete choice experiment design. Multivariable linear regression was used to identify factors associated with correct interpretation of statistical concepts.

RESULTS

Among 534 respondents who answered all nine questions, the mean correct responses was 95.9% (95% CI, 93.8-97.4) for sensitivity, 93.1% (95% CI, 90.5-95.0) for specificity, and 86.6% (95% CI, 83.3-89.3) for CIs. Verbatim interpretation was high for all concepts, but significantly higher than gist only for CIs (p < 0.001). Scores on each discrete choice experiment tasks were slightly lower in each category. Both objective and subjective numeracy were positively associated with an increased proportion of correct responses (p < 0.001).

CONCLUSION

These results suggest that a nonclinical audience can interpret quantitative performance measures of predictive models with very high accuracy. Future development of patient-facing clinical prediction models can feasibly incorporate patient preferences for model features into their development.

Functional decline and associated factors in patients with multimorbidity at 8 months of follow-up in primary care: the functionality in pluripathological patients (FUNCIPLUR) longitudinal descriptive study

OBJECTIVE

To analyse short-term functional decline and associated factors in over 65-year-olds with multimorbidity.

DESIGN AND SETTING

Prospective multicentre study conducted in three primary care centres, over an 8-month period. During this period, we also analysed admissions to two referral hospitals.

PARTICIPANTS

Of the 241 patients ≥65 years included randomly in the study, 155 were already part of a multimorbidity programme (stratified by 'Adjusted Clinical Groups') and 86 were newly included (patients who met Ollero's criteria and with ≥1 hospital admission the previous year). Patients who were institutionalised, unable to complete follow-up or receiving dialysis were excluded.

OUTCOMES AND VARIABLES

The primary outcome was the decrease in functional status category (Barthel Index or Lawton Scale). Other variables considered were sociodemographic characteristics, comorbidity, medications, number of admissions and functional status on discharge.

RESULTS

Patients had a median age of 82 years (P₇₅ 86) and of five selected chronic conditions (IQR 4-6), and took 11 (IQR 9-14) regular medications; 46.9% were women; 38.2% had impaired function at baseline.Overall, 200 persons completed the follow-up; 10.4% (n=25) of the initial sample died within the 8 months. In 20.5% (95% CI 15.5% to 26.6%) of them we recorded a decrease in functionality, associated with older age (OR 1.1, 95% CI 1.0 to 1.2) and with having ≥1 admission during the follow-up (OR 3.6, 95% CI 1.6 to 7.7). There were 133 hospital admissions in total during the follow-up considering all the patients included, and a functional decline was observed in 35.5% (95% CI 25.7% to 46.7%) of the 76 discharges in which functional status was assessed.

CONCLUSIONS

A fifth of patients showed functional decline or loss of independence in just 8 months. These findings are important as functional decline and the increasing care needs are potentially predictable and modifiable. Age and hospitalisation were closely associated with this decline.

Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493 737 UK Biobank participants

BACKGROUND

Frailty is associated with older age and multimorbidity (two or more long-term conditions); however, little is known about its prevalence or effects on mortality in younger populations. This paper aims to examine the association between frailty, multimorbidity, specific long-term conditions, and mortality in a middle-aged and older aged population.

METHODS

Data were sourced from the UK Biobank. Frailty phenotype was based on five criteria (weight loss, exhaustion, grip strength, low physical activity, slow walking pace). Participants were deemed frail if they met at least three criteria, pre-frail if they fulfilled one or two criteria, and not frail if no criteria were met. Sociodemographic characteristics and long-term conditions were examined. The outcome was all-cause mortality, which was measured at a median of 7 years follow-up. Multinomial logistic regression compared sociodemographic characteristics and long-term conditions of frail or pre-frail participants with non-frail participants. Cox proportional hazards models examined associations between frailty or pre-frailty and mortality. Results were stratified by age group (37-45, 45-55, 55-65, 65-73 years) and sex, and were adjusted for multimorbidity count, socioeconomic status, body-mass index, smoking status, and alcohol use.

FINDINGS

493 737 participants aged 37-73 years were included in the study, of whom 16 538 (3%) were considered frail, 185 360 (38%) pre-frail, and 291 839 (59%) not frail. Frailty was significantly associated with multimorbidity (prevalence 18% [4435/25 338] in those with four or more long-term conditions; odds ratio [OR] 27·1, 95% CI 25·3-29·1) socioeconomic deprivation, smoking, obesity, and infrequent alcohol consumption. The top five long-term conditions associated with frailty were multiple sclerosis (OR 15·3; 99·75% CI 12·8-18·2); chronic fatigue syndrome (12·9; 11·1-15·0); chronic obstructive pulmonary disease (5·6; 5·2-6·1); connective tissue disease (5·4; 5·0-5·8); and diabetes (5·0; 4·7-5·2). Pre-frailty and frailty were significantly associated with mortality for all age strata in men and women (except in women aged 37-45 years) after adjustment for confounders.

INTERPRETATION

Efforts to identify, manage, and prevent frailty should include middle-aged individuals with multimorbidity, in whom frailty is significantly associated with mortality, even after adjustment for number of long-term conditions, sociodemographics, and lifestyle. Research, clinical guidelines, and health-care services must shift focus from single conditions to the requirements of increasingly complex patient populations.

FUNDING

CSO Catalyst Grant and National Health Service Research for Scotland Career Research Fellowship.

Patterns of Health Care Utilization for Noncommunicable Diseases in a Transitional European Country: Results From the National Health Survey

This study aimed to assess possible differences in health services utilization among people living with noncommunicable diseases (NCDs) in the Republic of Srpska (RS), Bosnia and Herzegovina, with special reference to NCD multimorbidity. In addition, the relationship between self-perceived health and health care utilization was assessed. Data were retrieved from the 2010 National Health Survey. A cross-sectional study design was used. A total of 4,673 persons aged 18 years and older were identified in the households, of which 4,128 were interviewed. Logistic regression analyses were used to estimate the effects of NCDs on health care utilization in RS. Respondents with NCD multimorbidity more frequently visited family physicians (odds ratio [OR], 2.74; 95% confidence interval [CI], 2.34 - 3.19), dentists (OR, 1.57; CI, 1.28 - 1.92), private doctors (OR, 2.14; CI, 1.74 - 2.64), and urgent care departments (OR, 2.30; CI, 1.75 - 3.03) than their counterparts without NCDs. They also had more hospital admissions (OR, 2.03; CI, 1.56 - 2.64). This is the first study to address the relationship between health care utilization and NCDs in the population of RS. Further research is needed to explore how best to organize health care to meet the needs of people in RS with NCDs, especially with NCD multimorbidity.

Symptoms Reported by Frail Elderly Adults Independently Predict 30-Day Hospital Readmission or Emergency Department Care

OBJECTIVES

To assess the degree to which self-reported symptoms predict unplanned readmission or emergency department (ED) care within 30 days of high-risk, elderly adults enrolled in a posthospitalization care transition program (CTP).

DESIGN

Retrospective cohort study.

SETTING

Posthospitalization CTP at Mayo Clinic, Rochester, Minnesota, from January 1, 2013, through March 3, 2015.

PARTICIPANTS

Frail, elderly adults (N = 230; mean age 83.5 ± 8.3, 46.5% male).

MEASUREMENTS

Charlson Comorbidity Index (CCI) and self-reported symptoms, measured using the Edmonton Symptom Assessment System (ESAS), were ascertained upon CTP enrollment.

RESULTS

Mean CCI was 3.9 ± 2.3. Of 51 participants returning to the hospital within 30 days of discharge, 13 had ED visits, and 38 were readmitted. Age, sex, and CCI were not significantly different between returning and nonreturning participants, but returning participants were significantly more likely to report shortness of breath (P = .004), anxiety (P = .02), depression (P = .02), and drowsiness (P = .01). Overall ESAS score was also a significant predictor of hospital return (P = .01).

CONCLUSION

Four self-reported symptoms and overall ESAS score, but not CCI, ascertained after hospital discharge were strong predictors of hospital return within 30 days. Including symptoms in risk stratification of high-risk elderly adults may help target interventions and reduce readmissions.