Proposals for enhanced health risk assessment and stratification in an integrated care scenario

Strengthening primary health care in Europe with digital solutions

This article provides an in-depth analysis of digital transformation in European primary healthcare (PHC). It assesses the impact of digital technology on healthcare delivery and management, highlighting variations in digital maturity across Europe. It emphasizes the significance of digital tools, especially during the COVID-19 pandemic, in enhancing accessibility and efficiency in healthcare. It discusses the integration of telehealth, remote monitoring, and e-health solutions, showcasing their role in patient empowerment and proactive care. Examples are included from various countries, such as Greece's ePrescription system, Lithuania's adoption of remote consultations, Spain's use of risk stratification solutions, and the Netherlands' advanced use of telemonitoring solutions, to illustrate the diverse implementation of digital solutions in PHC. The article offers insights into the challenges and opportunities of embedding digital technologies into a multidisciplinary healthcare framework, pointing towards future directions for PHC in Europe.

The value of admission avoidance: cost-consequence analysis of one-year activity in a consolidated service

BACKGROUND

Many advantages of hospital at home (HaH), as a modality of acute care, have been highlighted, but controversies exist regarding the cost-benefit trade-offs. The objective is to assess health outcomes and analytical costs of hospital avoidance (HaH-HA) in a consolidated service with over ten years of delivery of HaH in Barcelona (Spain).

METHODS

A retrospective cost-consequence analysis of all first episodes of HaH-HA, directly admitted from the emergency room (ER) in 2017-2018, was carried out with a health system perspective. HaH-HA was compared with a propensity-score-matched group of contemporary patients admitted to conventional hospitalization (Controls). Mortality, re-admissions, ER visits, and direct healthcare costs were evaluated.

RESULTS

HaH-HA and Controls (n = 441 each) were comparable in terms of age (73 [SD16] vs. 74 [SD16]), gender (male, 57% vs. 59%), multimorbidity, healthcare expenditure during the previous year, case mix index of the acute episode, and main diagnosis at discharge. HaH-HA presented lower mortality during the episode (0 vs. 19 (4.3%); p < 0.001). At 30 days post-discharge, HaH-HA and Controls showed similar re-admission rates; however, ER visits were lower in HaH-HA than in Controls (28 (6.3%) vs. 34 (8.1%); p = 0.044). Average costs per patient during the episode were lower in the HaH-HA group (€ 1,078) than in Controls (€ 2,171). Likewise, healthcare costs within the 30 days post-discharge were also lower in HaH-Ha than in Controls (p < 0.001).

CONCLUSIONS

The study showed higher performance and cost reductions of HaH-HA in a real-world setting. The identification of sources of savings facilitates scaling of hospital avoidance.

REGISTRATION

ClinicalTrials.gov (26/04/2017; NCT03130283).

Incidence and Determinants of COVID-19 in Patients Seeking Treatment for Substance Use Disorder: A Patient-Based Linkage Study

INTRODUCTION

People with substance use disorder (SUD) may be at increased risk of COVID-19 infection. However, there is little evidence regarding the incidence of and determinants associated with infection in this group. The aims of the study were to determine the cumulative incidence of COVID-19 among people who sought treatment for heroin, cocaine, cannabis, and alcohol use disorder in Catalonia; to identify sociodemographic, substance, and clinical determinants associated with COVID-19 infection among SUD patients; and to compare the cumulative incidence of COVID-19 infection in the population with SUD with that of the general population.

METHODS

A patient-based retrospective observational study was conducted. The study population comprised people who sought treatment for heroin, cocaine, cannabis, or alcohol use disorder in Catalonia in 2018 and 2019. We analysed cumulative incidence of COVID-19 (confirmed by PCR test) from 25 February to 31 December 2020. Additionally, we used a log-link binomial generalized linear model for COVID-19 infection, using the substance as the exposition, adjusting for sociodemographic and clinical variables.

RESULTS

Of the 23,092 individuals who sought treatment for SUD, 38.15% were considered suspected cases of COVID-19, and 2.60% (95% CI = 2.41-2.82) were confirmed positive for COVID-19 by PCR test during the study period. Those who sought treatment for alcohol use (cumulative incidence of COVID-19 of 3% [95% CI = 2.70-3.34]) had a higher risk ratio than, those who sought treatment for heroin use (cumulative incidence of 1.94% [95% CI = 1.47-2.56]). Being born outside of Spain, living in an institutionalized residence, having HIV, and being in a high morbidity group were associated with higher risk of COVID-19 infection. Meanwhile, the cumulative incidence of COVID-19 in the general population, according to public COVID-19 test data, was 3.86% (95% CI = 3.85-3.87).

CONCLUSION

This study did not find higher cumulative incidence of COVID-19 infection among people with SUD in Catalonia in 2020, despite the clinical vulnerability of this population and their social disadvantage. However, differences were seen in the cumulative incidence of COVID-19 according to the substance for which treatment was sought. For example, those with alcohol dependence had a higher rate than those dependent on heroin. Further studies are needed to determine the factors contributing to these differences.

A Practice-Proven Adaptive Case Management Approach for Innovative Health Care Services (Health Circuit): Cluster Randomized Clinical Pilot and Descriptive Observational Study

BACKGROUND

Digital health tools may facilitate the continuity of care. Enhancement of digital aid is imperative to prevent information gaps or redundancies, as well as to facilitate support of flexible care plans.

OBJECTIVE

The study presents Health Circuit, an adaptive case management approach that empowers health care professionals and patients to implement personalized evidence-based interventions, thanks to dynamic communication channels and patient-centered service workflows; analyze the health care impact; and determine its usability and acceptability among health care professionals and patients.

METHODS

From September 2019 to March 2020, the health impact, usability (measured with the system usability scale; SUS), and acceptability (measured with the net promoter score; NPS) of an initial prototype of Health Circuit were tested in a cluster randomized clinical pilot (n=100) in patients with high risk for hospitalization (study 1). From July 2020 to July 2021, a premarket pilot study of usability (with the SUS) and acceptability (with the NPS) was conducted among 104 high-risk patients undergoing prehabilitation before major surgery (study 2).

RESULTS

In study 1, Health Circuit resulted in a reduction of emergency room visits (4/7, 13% vs 7/16, 44%), enhanced patients' empowerment (P<.001) and showed good acceptability and usability scores (NPS: 31; SUS: 54/100). In study 2, the NPS was 40 and the SUS was 85/100. The acceptance rate was also high (mean score of 8.4/10).

CONCLUSIONS

Health Circuit showed potential for health care value generation and good acceptability and usability despite being a prototype system, prompting the need for testing a completed system in real-world scenarios.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04056663; https://clinicaltrials.gov/ct2/show/NCT04056663.

Prevention of Unplanned Hospital Admissions in Multimorbid Patients Using Computational Modeling: Observational Retrospective Cohort Study

BACKGROUND

Enhanced management of multimorbidity constitutes a major clinical challenge. Multimorbidity shows well-established causal relationships with the high use of health care resources and, specifically, with unplanned hospital admissions. Enhanced patient stratification is vital for achieving effectiveness through personalized postdischarge service selection.

OBJECTIVE

The study has a 2-fold aim: (1) generation and assessment of predictive models of mortality and readmission at 90 days after discharge; and (2) characterization of patients' profiles for personalized service selection purposes.

METHODS

Gradient boosting techniques were used to generate predictive models based on multisource data (registries, clinical/functional and social support) from 761 nonsurgical patients admitted in a tertiary hospital over 12 months (October 2017 to November 2018). K-means clustering was used to characterize patient profiles.

RESULTS

Performance (area under the receiver operating characteristic curve, sensitivity, and specificity) of the predictive models was 0.82, 0.78, and 0.70 and 0.72, 0.70, and 0.63 for mortality and readmissions, respectively. A total of 4 patients' profiles were identified. In brief, the reference patients (cluster 1; 281/761, 36.9%), 53.7% (151/281) men and mean age of 71 (SD 16) years, showed 3.6% (10/281) mortality and 15.7% (44/281) readmissions at 90 days following discharge. The unhealthy lifestyle habit profile (cluster 2; 179/761, 23.5%) predominantly comprised males (137/179, 76.5%) with similar age, mean 70 (SD 13) years, but showed slightly higher mortality (10/179, 5.6%) and markedly higher readmission rate (49/179, 27.4%). Patients in the frailty profile (cluster 3; 152/761, 19.9%) were older (mean 81 years, SD 13 years) and predominantly female (63/152, 41.4%, males). They showed medical complexity with a high level of social vulnerability and the highest mortality rate (23/152, 15.1%), but with a similar hospitalization rate (39/152, 25.7%) compared with cluster 2. Finally, the medical complexity profile (cluster 4; 149/761, 19.6%), mean age 83 (SD 9) years, 55.7% (83/149) males, showed the highest clinical complexity resulting in 12.8% (19/149) mortality and the highest readmission rate (56/149, 37.6%).

CONCLUSIONS

The results indicated the potential to predict mortality and morbidity-related adverse events leading to unplanned hospital readmissions. The resulting patient profiles fostered recommendations for personalized service selection with the capacity for value generation.

Development and validation of a population-based risk stratification model for severe COVID-19 in the general population

The shortage of recently approved vaccines against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has highlighted the need for evidence-based tools to prioritize healthcare resources for people at higher risk of severe coronavirus disease (COVID-19). Although age has been identified as the most important risk factor (particularly for mortality), the contribution of underlying comorbidities is often assessed using a pre-defined list of chronic conditions. Furthermore, the count of individual risk factors has limited applicability to population-based “stratify-and-shield” strategies. We aimed to develop and validate a COVID-19 risk stratification system that allows allocating individuals of the general population into four mutually-exclusive risk categories based on multivariate models for severe COVID-19, a composite of hospital admission, transfer to intensive care unit (ICU), and mortality among the general population. The model was developed using clinical, hospital, and epidemiological data from all individuals among the entire population of Catalonia (North-East Spain; 7.5 million people) who experienced a COVID-19 event (i.e., hospitalization, ICU admission, or death due to COVID-19) between March 1 and September 15, 2020, and validated using an independent dataset of 218,329 individuals with COVID-19 confirmed by reverse transcription—polymerase chain reaction (RT-PCR), who were infected after developing the model. No exclusion criteria were defined. The final model included age, sex, a summary measure of the comorbidity burden, the socioeconomic status, and the presence of specific diagnoses potentially associated with severe COVID-19. The validation showed high discrimination capacity, with an area under the curve of the receiving operating characteristics of 0.85 (95% CI 0.85–0.85) for hospital admissions, 0.86 (0.86–0.97) for ICU transfers, and 0.96 (0.96–0.96) for deaths. Our results provide clinicians and policymakers with an evidence-based tool for prioritizing COVID-19 healthcare resources in other population groups aside from those with higher exposure to SARS-CoV-2 and frontline workers.

Use of hospital care services by chronic patients according to their characteristics and risk levels by adjusted morbidity groups

Background

In-hospital care of chronic patients is based on their characteristics and risk levels. Adjusted morbidity groups (AMG) is a population stratification tool which is currently being used in Primary Care but not in Hospitals. The objectives of this study were to describe the use of hospital services by chronic patients according to their risk levels assigned by AMG and to analyze influencing variables.

Material and methods

In this cross-sectional study, patients aged ≥18 years from a healthcare service area classified as chronically ill by the AMG classification system who used their referral hospital services from June 2015 to June 2016 were included. Predisposing and needs factors were collected. Univariate, bivariate and multiple linear regressions were performed.

Results

Of the 9,443 chronic patients identified (52.1% of the population in the selected area), 4,143 (43.9%) used hospital care services. Their mean age was 62.1 years (standard deviation (SD) = 18.4); 61.8% were female; 9% were high risk; 30% were medium risk, and 61% were low risk. The mean number of hospital service contacts was 5.0 (SD = 6.2), with 3.8 (SD = 4.3) visits to outpatient clinic, 0.7 (SD = 1.2) visits to emergency departments, 0.3 (SD = 2.8) visits to day hospital, and 0.2 (SD = 0.5) hospitalizations. The factors associated with greater service use were predisposing factors such as age (coefficient B (CB) = 0.03; 95% confidence interval (CI) = 0.01–0.05) and Spanish origin (CB = 3.9; 95% CI = 3.2–4.6). Among the needs factors were palliative care (CB = 4.8; 95% CI = 2.8–6.7), primary caregiver status (CB = 2.3; 95% CI = 0.7–3.9), a high risk level (CB = 2.9; 95% CI = 2.1–3.6), multimorbidity (CB = 0.8, 95% CI = 0.4–1.3), chronic obstructive pulmonary disease (COPD) (CB = 1.5, 95% CI = 0.8–2.3), depression (CB = 0.8, 95% CI = 0.3–1.3), active cancer (CB = 4.4, 95% CI = 3.7–5.1), and polymedication (CB = 1.1, 95% CI = 0.5–1.7).

Conclusions

The use of hospital services by chronic patients was high and increased with the risk level assigned by the AMG. The most frequent type of contact was outpatient consultation. Use was increased with predisposing factors such as age and geographic origin and by needs factors such as multimorbidity, risk level and severe diseases requiring follow-up, home care, and palliative care.

Evolving mortality and clinical outcomes of hospitalized subjects during successive COVID-19 waves in Catalonia, Spain

Background

The changes in shield strategies, treatments, emergence variants, and healthcare pathways might shift the profile and outcome of patients hospitalized with COVID-19 in successive waves of the outbreak.

Methods

We retrospectively analysed the characteristics and in-hospital outcomes of all patients admitted with COVID-19 in eight university hospitals of Catalonia (North-East Spain) between Feb 28, 2020 and Feb 28, 2021. Using a 7-joinpoint regression analysis, we split admissions into four waves. The main hospital outcomes included 30-day mortality and admission to intensive care unit (ICU).

Findings

The analysis included 17,027 subjects admitted during the first wave (6800; 39.9%), summer wave (1807; 10.6%), second wave (3804; 22.3%), and third wave (4616; 27.1%). The highest 30-day mortality rate was reported during the first wave (17%) and decreased afterwards, remaining stable at 13% in the second and third waves (overall 30% reduction); the lowest mortality was reported during the summer wave (8%, 50% reduction). ICU admission became progressively more frequent during successive waves. In Cox regression analysis, the main factors contributing to differences in 30-day mortality were the epidemic wave, followed by gender, age, diabetes, chronic kidney disease, and neoplasms.

Interpretation

Although in-hospital COVID-19 mortality remains high, it decreased substantially after the first wave and is highly dependent of patient's characteristics and ICU availability. Highest mortality reductions occurred during a wave characterized by younger individuals, an increasingly frequent scenario as vaccination campaigns progress.

Funding

This work did not receive specific funding.

The impact of an easy access drug supply management policy law on the consumption and abuse of opioids in Catalonia: A population-based study

BACKGROUND

Over the last two decades, the rise in opioid prescription has worsened health outcomes worldwide, increasing both levels of abuse and mortality rates. In order to reduce the scale of this public health problem, new policies have been implemented in many countries. In 2012, Spain adopted new legislation on opioid prescription (the ROE law), which meant that practitioners no longer needed to obtain extra authorisation in order to prescribe strong opioids. The objective of the paper is to assess the impact of this law on opioid use and abuse in Catalonia, Spain.

METHODS

We established two measures of the use of strong and weak opioids: DDDs, and abuse. We used benzodiazepines and antidepressants as controls, and adjusted for age, sex, drug co-payment level, death or near death, cancer diagnosis, morbidity group, and type of prescription. The data were obtained from administrative and dispensing drug databases in a population of 7.5 million inhabitants. We estimated two-way fixed effects using difference in difference models.

RESULTS

The ROE law impacted reducing the monthly use of strong opioids by 0.903 DDDs, representing a 3.15% decrease in the mean monthly use of strong opioids. However, abuse rose 1.86 times compared with the average pre-ROE value, which represents an increase of 11,190 months of opioid abuse (i.e., an 11.33% of all monthly opioids use).

CONCLUSION

The abolition of the duplicate prescription programme for strong opioids led to a reduction in the average monthly use of strong opioids, but an increase in abuse.

Adjusted Morbidity Groups and Intracerebral Haemorrhage: A Retrospective Primary Care Cohort Study

Background: Intracerebral haemorrhage rates are increasing among highly complex, elderly patients. The main objective of this study was to identify modifiable risk factors of intracerebral haemorrhage. Methods: Multicentre, retrospective, community-based cohort study was conducted, including patients in the Adjusted Morbidity Group 4 with no history of intracerebral haemorrhage. Cases were obtained from electronic clinical records of the Catalan Institute of Health and were followed up for five years. The primary outcome was the occurrence of intracerebral haemorrhage during the study period. Demographic, clinical and pharmacological variables were included. Logistic regression analyses were carried out to detect prognostic variables for intracerebral haemorrhage. Results: 4686 subjects were included; 170 (3.6%) suffered an intracerebral haemorrhage (85.8/10,000 person–year [95% CI 85.4 to 86.2]). The HAS-BLED score for intracerebral haemorrhage risk detection obtained the best AUC (0.7) when used in the highest complexity level (cut-off point ≥3). Associated independent risk factors were age ≥80 years, high complexity and use of antiplatelet agents. Conclusions: The Adjusted Morbidity Group 4 is associated with a high risk of intracerebral haemorrhage, particularly for highly complex patients and the use of antiplatelet agents. The risk of bleeding in these patients must be closely monitored.

Do hospitals have a higher mortality rate on weekend admissions? An observational study to analyse weekend effect on urgent admissions to hospitals in Catalonia

BACKGROUND

'Weekend effect' is a term used to describe the increased mortality associated with weekend emergency admissions to hospital, in contrast with admission on weekdays. The objective of the present study is to determine whether the weekend effect is present in hospitals in Catalonia.

METHODS

We analysed all urgent admissions in Catalonia in 2018, for a group of pathologies. Two groups were defined (those admitted on a weekday and those admitted on a weekend). We obtained mortality at 3, 7, 15 and 30 days, and applied a proportions test to both groups. Additionally, we used Cox's regression for mortality at 30 days, using the admission on a weekend as the exposition, adjusting by socioeconomic and clinical variables. We used the hospital discharge database and the Central Registry of the Insured Population.

RESULTS

72 427 admissions for the selected pathologies during 2018 were found. No statistically significant differences in mortality at 30 days (p=0.524) or at 15 days (p=0.119) according to the day of admission were observed. However, significant differences were found in mortality at 7 days (p=0.025) and at 3 days (p=0.002). The hazard rate associated with the weekend was 1.13 (95% CI: 1.04 to 1.23). By contrast, the adjusted HR of the weekend interaction with time was 0.99 (95% CI: 0.99 to 1.00).

CONCLUSIONS

There is a weekend effect, but it is not constant in time. This could suggest the existence of dysfunctions in the quality of care during the weekend.

Performance of quantitative measures of multimorbidity: a population-based retrospective analysis

BACKGROUND

Multimorbidity measures are useful for resource planning, patient selection and prioritization, and factor adjustment in clinical practice, research, and benchmarking. We aimed to compare the explanatory performance of the adjusted morbidity group (GMA) index in predicting relevant healthcare outcomes with that of other quantitative measures of multimorbidity.

METHODS

The performance of multimorbidity measures was retrospectively assessed on anonymized records of the entire adult population of Catalonia (North-East Spain). Five quantitative measures of multimorbidity were added to a baseline model based on age, gender, and socioeconomic status: the Charlson index score, the count of chronic diseases according to three different proposals (i.e., the QOF, HCUP, and Karolinska institute), and the multimorbidity index score of the GMA tool. Outcomes included all-cause death, total and non-scheduled hospitalization, primary care and ER visits, medication use, admission to a skilled nursing facility for intermediate care, and high expenditure (time frame 2017). The analysis was performed on 10 subpopulations: all adults (i.e., aged > 17 years), people aged > 64 years, people aged > 64 years and institutionalized in a nursing home for long-term care, and people with specific diagnoses (e.g., ischemic heart disease, cirrhosis, dementia, diabetes mellitus, heart failure, chronic kidney disease, and chronic obstructive pulmonary disease). The explanatory performance was assessed using the area under the receiving operating curves (AUC-ROC) (main analysis) and three additional statistics (secondary analysis).

RESULTS

The adult population included 6,224,316 individuals. The addition of any of the multimorbidity measures to the baseline model increased the explanatory performance for all outcomes and subpopulations. All measurements performed better in the general adult population. The GMA index had higher performance and consistency across subpopulations than the rest of multimorbidity measures. The Charlson index stood out on explaining mortality, whereas measures based on exhaustive definitions of chronic diagnostic (e.g., HCUP and GMA) performed better than those using predefined lists of diagnostics (e.g., QOF or the Karolinska proposal).

CONCLUSIONS

The addition of multimorbidity measures to models for explaining healthcare outcomes increase the performance. The GMA index has high performance in explaining relevant healthcare outcomes and may be useful for clinical practice, resource planning, and public health research.

Characteristics and Service Utilization by Complex Chronic and Advanced Chronic Patients in Catalonia: A Retrospective Seven-Year Cohort-Based Study of an Implemented Chronic Care Program

The Chronic Care Program introduced in Catalonia in 2011 focuses on improving the identification and management of complex chronic (CCPs) and advanced chronic patients (ACPs) by implementing an individualized care model. Its first stage is their identification based on chronicity, difficult clinical management (i.e., complexity), and, in ACPs, limited life prognosis. Subsequent stages are individual evaluation and implementation of a shared personalized care plan. This retrospective study, including all CCPs and ACPs identified in Catalonia between 2013 and 2019, was aimed at describing the characteristics and healthcare service utilization among these patients. Data were obtained from an administrative database and included sociodemographic, clinical, and service utilization variables and morbidity-associated risk according to the Adjusted Morbidity Groups (GMA) stratification. During the study period, CCPs’ and ACPs’ prevalence increased and was higher in lower-income populations; most cases were women. CCPs and ACPs had all comorbidities at higher frequencies, higher utilization of healthcare services, and were more frequently at high risk (63% and 71%, respectively) than age-, sex-, and income level-adjusted non-CCP (23%) and non-ACP populations (30%). These results show effective identification of the program’s target population and demonstrate that CCPs and ACPs have a higher burden of multimorbidity and healthcare needs.

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.

Guided Internet-Based Cognitive Behavioral Therapy for Depression: Implementation Cost-Effectiveness Study

Background

Major depressive disorder is a chronic condition; its prevalence is expected to grow with the aging trend of high-income countries. Internet-based cognitive-behavioral therapy has proven efficacy in treating major depressive disorder.

Objective

The objective of this study was to assess the cost-effectiveness of implementing a community internet-based cognitive behavioral therapy intervention (Super@, the Spanish program for the MasterMind project) for treating major depressive disorder.

Methods

The cost-effectiveness of the Super@ program was assessed with the Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing tool, using a 3-state Markov model. Data from the cost and effectiveness of the intervention were prospectively collected from the implementation of the program by a health care provider in Badalona, Spain; the corresponding data for usual care were gathered from the literature. The health states, transition probabilities, and utilities were computed using Patient Health Questionnaire–9 scores.

Results

The analysis was performed using data from 229 participants using the Super@ program. Results showed that the intervention was more costly than usual care; the discounted (3%) and nondiscounted incremental cost-effectiveness ratios were €29,367 and €26,484 per quality-adjusted life-year, respectively (approximately US $35,299 and $31,833, respectively). The intervention was cost-effective based on the €30,000 willingness-to-pay threshold typically applied in Spain (equivalent to approximately $36,060). According to the deterministic sensitivity analyses, the potential reduction of costs associated with intervention scale-up would reduce the incremental cost-effectiveness ratio of the intervention, although it remained more costly than usual care. A discount in the incremental effects up to 5% exceeded the willingness-to-pay threshold of €30,000.

Conclusions

The Super@ program, an internet-based cognitive behavioral therapy intervention for treating major depressive disorder, cost more than treatment as usual. Nevertheless, its implementation in Spain would be cost-effective from health care and societal perspectives, given the willingness-to-pay threshold of €30,000 compared with treatment as usual.

Use of healthcare resources and drug expenditure before and after treatment of chronic hepatitis C with direct antiviral agents

The aim of this study was to analyse the impact of treating chronic hepatitis C (CHC) with direct-acting agents (DAA) on the use of healthcare resources. We included all patients treated with DAA for CHC from January 2015 to December 2017 in Catalonia whose medical records from 12 months before to 24 months after treatment were available. Data were obtained from the Catalan Health Surveillance System. A total of 12,199 patients in Catalonia were treated with DAA for CHC. Of these, 11.3% had no-minimal fibrosis (F0-F1), 24.0% had moderate fibrosis (F2), 50.3% had significant fibrosis or cirrhosis (F3-F4), and 14.4% had decompensated cirrhosis. Use of healthcare resources decreased from the pre-treatment period to the post-treatment period for the following: hospital admissions due to complications of cirrhosis, from 0.19 to 0.12 per month per 100 patients (RR 0.57; 95% CI 0.47-0.68); length of hospital stay, from 12.9 to 12.2 days (RR 0.93; 95% CI 0.91-0.94); outpatient visits, from 65.0 to 49.2 (RR 0.75; 95% CI 0.74-0.75); and number of medication containers per patient per month, from 13.9 to 12.5 (RR 0.837; 95% CI 0.835-0.838). However, the number of invoices for antineoplastic treatment increased after DAA treatment, especially for patients with high morbidity or advanced fibrosis stage. In conclusion, a decrease in health resource use was seen in CHC patients treated with DAA, as measured by length of hospital stay, number of admissions due to cirrhosis complications, outpatient visits and overall drug invoicing. However, use of antineoplastic drugs increased significantly, especially in patients with cirrhosis and high morbidity.

Clustering Complex Chronic Patients: A Cross-Sectional Community Study From the General Practitioner's Perspective

Objective:

Characterize subgroups of Complex Chronic Patients (CCPs) with cluster analysis from the general practitioner’s perspective.

Study design:

Cross-sectional population-based study.

Setting:

Three Primary Care urban centres for a reference population of 43,647 inhabitants over 14 years old in Sabadell, Catalonia, Spain.

Methods:

Complexity is defined by the independent clinical judgment of general practitioners with the aid of complexity domains (both clinical and social). We used a Two-Step Cluster method to identify relevant subgroups of CCPs.

Results:

Three relevant subgroups were identified. The first one was mainly managed by primary care professionals, and 63% of its CCPs belonged to the high-risk stratum of the Adjusted Morbidity Groups (GMA). The second subgroup included younger patients than the other two clusters, and showed the highest ratios of social deprivation and severe mental disease; 48% of its CCPs belonged to the high-risk stratum of the GMA. A third cluster included patients who belonged to the high-risk stratum of the GMA. Their age was similar to that of the patients in the first cluster, but they showed the highest values in the following areas: (i) risk of admission; (ii) proportion of advanced chronic disease and limited-life prognosis; (iii) functional loss and (iv) geriatric syndromes, along with special uncertainty in decision-making and clinical management.

Conclusions:

Characterization of CCPs shows clearly distinct profiles of needs, which provides an improved epidemiological picture by identifying clusters of patients who are likely to benefit from targeted interventions.

How the Integration of Telehealth and Coordinated Care Approaches Impact Health Care Service Organization Structure and Ethos: Mixed Methods Study

Background

Coordinated care and telehealth services have the potential to deliver quality care to chronically ill patients. They can both reduce the economic burden of chronic care and maximize the delivery of clinical services. Such services require new behaviors, routines, and ways of working to improve health outcomes, administrative efficiency, cost-effectiveness, and user (patient and health professional) experience.

Objective

The aim of this study was to assess how health care organization setup influences the perceptions and experience of service managers and frontline staff during the development and deployment of integrated care with and without telehealth.

Methods

As part of a multinational project exploring the use of coordinated care and telehealth, questionnaires were sent to service managers and frontline practitioners. These questionnaires gathered quantitative and qualitative data related to organizational issues in the implementation of coordinated care and telehealth. Three analytical stages were followed: (1) preliminary analysis for a direct comparison of the responses of service managers and frontline staff to a range of organizational issues, (2) secondary analysis to establish statistically significant relationships between baseline and follow-up questionnaires, and (3) thematic analysis of free-text responses of service managers and frontline staff.

Results

Both frontline practitioners and managers highlighted that training, tailored to the needs of different professional groups and staff grades, was a crucial element in the successful implementation of new services. Frontline staff were markedly less positive than managers in their views regarding the responsiveness of their organization and the pace of change.

Conclusions

The data provide evidence that the setup of health care services is positively associated with outcomes in several areas, particularly tailored staff training, rewards for good service, staff satisfaction, and patient involvement.

Health Outcomes from Home Hospitalization: Multisource Predictive Modeling

BACKGROUND

Home hospitalization is widely accepted as a cost-effective alternative to conventional hospitalization for selected patients. A recent analysis of the home hospitalization and early discharge (HH/ED) program at Hospital Clínic de Barcelona over a 10-year period demonstrated high levels of acceptance by patients and professionals, as well as health value-based generation at the provider and health-system levels. However, health risk assessment was identified as an unmet need with the potential to enhance clinical decision making.

OBJECTIVE

The objective of this study is to generate and assess predictive models of mortality and in-hospital admission at entry and at HH/ED discharge.

METHODS

Predictive modeling of mortality and in-hospital admission was done in 2 different scenarios: at entry into the HH/ED program and at discharge, from January 2009 to December 2015. Multisource predictive variables, including standard clinical data, patients' functional features, and population health risk assessment, were considered.

RESULTS

We studied 1925 HH/ED patients by applying a random forest classifier, as it showed the best performance. Average results of the area under the receiver operating characteristic curve (AUROC; sensitivity/specificity) for the prediction of mortality were 0.88 (0.81/0.76) and 0.89 (0.81/0.81) at entry and at home hospitalization discharge, respectively; the AUROC (sensitivity/specificity) values for in-hospital admission were 0.71 (0.67/0.64) and 0.70 (0.71/0.61) at entry and at home hospitalization discharge, respectively.

CONCLUSIONS

The results showed potential for feeding clinical decision support systems aimed at supporting health professionals for inclusion of candidates into the HH/ED program, and have the capacity to guide transitions toward community-based care at HH discharge.

BeyondSilos, a Telehealth-Enhanced Integrated Care Model in the Domiciliary Setting for Older Patients: Observational Prospective Cohort Study for Effectiveness and Cost-Effectiveness Assessments

BACKGROUND

Information and communication technology may provide domiciliary care programs with continuity of care. However, evidence about the effectiveness and cost-effectiveness of information and communication technology in the context of integrated care models is relatively scarce.

OBJECTIVE

The objective of our study was to provide evidence on the clinical effectiveness and cost-effectiveness of the BeyondSilos project for patients enrolled in the Badalona city pilot site in Spain.

METHODS

A quasi-experimental study was used to assess the cost-effectiveness of information and communication technology-enhanced integration of health and social care, including the third sector (intervention), compared to basic health and social care coordination (comparator). The study was conducted in Badalona between 2015 and 2016. Participants were followed for 8 months.

RESULTS

The study included 198 patients: 98 in the intervention group and 100 in the comparator group. The mean Barthel index remained unchanged in the intervention group (mean change 0.14, 95% CI -4.51 to 4.78; P=.95) but decreased in the comparator group (mean change -3.23, 95% CI -5.34 to -1.11; P=.003). Instrumental Activities of Daily Living significantly decreased in both groups: mean changes of -0.23 (95% CI -0.44 to -0.02; P=.03) and -0.33 (95% CI -0.46 to -0.20; P<.001) in the intervention and comparator groups, respectively. No differences were found in the Geriatric Depression Scale (intervention: mean change 0.28, 95% CI -0.44 to 1.01, P=.44; comparator: mean change -0.29, 95% CI -0.59 to 0.01, P=.06). The intervention showed cost-effectiveness (incremental cost-effectiveness ratio €6505.52, approximately US $7582).

CONCLUSIONS

The information and communication technology-enhanced integrated domiciliary care program was cost-effective. The beneficial effects of this approach strongly rely upon the commitment of the professional staff involved.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03111004; http://clinicaltrials.gov/ct2/show/ NCT03111004.

Emergency admission risk stratification tools in UK primary care: a cross-sectional survey of availability and use

Background

Stratifying patient populations by risk of adverse events was believed to support preventive care for those identified, but recent evidence does not support this. Emergency admission risk stratification (EARS) tools have been widely promoted in UK policy and GP contracts.

Aim

To describe availability and use of EARS tools across the UK, and identify factors perceived to influence implementation.

Design and setting

Cross-sectional survey in UK.

Method

Online survey of 235 organisations responsible for UK primary care: 209 clinical commissioning groups (CCGs) in England; 14 health boards in Scotland; seven health boards in Wales; and five local commissioning groups (LCGs) in Northern Ireland. Analysis results are presented using descriptive statistics for closed questions and by theme for open questions.

Results

Responses were analysed from 171 (72.8%) organisations, of which 148 (86.5%) reported that risk tools were available in their areas. Organisations identified 39 different EARS tools in use. Promotion by NHS commissioners, involvement of clinical leaders, and engagement of practice managers were identified as the most important factors in encouraging use of tools by general practices. High staff workloads and information governance were identified as important barriers. Tools were most frequently used to identify individual patients, but also for service planning. Nearly 40% of areas using EARS tools reported introducing or realigning services as a result, but relatively few reported use for service evaluation.

Conclusion

EARS tools are widely available across the UK, although there is variation by region. There remains a need to align policy and practice with research evidence.

Tailoring integrated care services for high-risk patients with multiple chronic conditions: a risk stratification approach using cluster analysis

Background

The purpose of this study was to produce a risk stratification within a population of high-risk patients with multiple chronic conditions who are currently treated under a case management program and to explore the existence of different risk subgroups. Different care strategies were then suggested for healthcare reform according to the characteristics of each subgroup.

Methods

All high-risk multimorbid patients from a case management program in the Navarra region of Spain were included in the study (n = 885). A 1-year mortality risk score was estimated for each patient by logistic regression. The population was then divided into subgroups according to the patients’ estimated risk scores. We used cluster analysis to produce the stratification with Ward’s linkage hierarchical algorithm. The characteristics of the resulting subgroups were analyzed, and post hoc pairwise tests were performed.

Results

Three distinct risk strata were found, containing 45, 38 and 17% of patients. Age increased from cluster to cluster, and functional status, clinical severity, nursing needs and nutritional values deteriorated. Patients in cluster 1 had lower renal deterioration values, and patients in cluster 3 had higher rates of pressure skin ulcers, higher rates of cerebrovascular disease and dementia, and lower prevalence rates of chronic obstructive pulmonary disease.

Conclusions

This study demonstrates the existence of distinct subgroups within a population of high-risk patients with multiple chronic conditions. Current case management integrated care programs use a uniform treatment strategy for patients who have diverse needs. Alternative treatment strategies should be considered to fit the needs of each patient subgroup.

Comorbidity patterns and socioeconomic inequalities in children under 15 with medical complexity: a population-based study

Background

Children with medical complexity (CMC) denotes the profile of a child with diverse acute and chronic conditions, making intensive use of the healthcare services and with special health and social needs. Previous studies show that CMC are also affected by the socioeconomic position (SEP) of their family. The aim of this study is to describe the pathologic patterns of CMC and their socioeconomic inequalities in order to better manage their needs, plan healthcare services accordingly, and improve the care models in place.

Methods

Cross-sectional study with latent class analysis (LCA) of the CMC population under the age of 15 in Catalonia in 2016, using administrative data. LCA was used to define multimorbidity classes based on the presence/absence of 57 conditions. All individuals were assigned to a best-fit class. Each comorbidity class was described and its association with SEP tested. The Adjusted Morbidity Groups classification system (Catalan acronym GMA) was used to identify the CMC. The main outcome measures were SEP, GMA score, sex, and age distribution, in both populations (CMC and non-CMC) and in each of the classes identified.

Results

71% of the CMC population had at least one parent with no employment or an annual income of less than €18,000. Four comorbidity classes were identified in the CMC: oncology (36.0%), neurodevelopment (13.7%), congenital and perinatal (19.8%), and respiratory (30.5%). SEP associations were: oncology OR 1.9 in boys and 2.0 in girls; neurodevelopment OR 2.3 in boys and 1.8 in girls; congenital and perinatal OR 1.7 in boys and 2.1 in girls; and respiratory OR 2.0 in boys and 2.0 in girls.

Conclusions

Our findings show the existence of four different patterns of comorbidities in CMC and a significantly high proportion of lower SEP children in all classes. These results could benefit CMC management by creating more efficient multidisciplinary medical teams according to each comorbidity class and a holistic perspective taking into account its socioeconomic vulnerability.

Multisystem chronic illness prognostication in non-oncologic integrated care

OBJECTIVES

To develop a mortality-predictive model for correct identification of patients with non-cancer multiple chronic conditions who would benefit from palliative care, recognise predictive indicators of death and provide with tools for individual risk score calculation.

DESIGN

Retrospective observational study with multivariate logistic regression models.

PARTICIPANTS

All patients with high-risk multiple chronic conditions incorporated into an integrated care strategy that fulfil two conditions: (1) they belong to the top 5% of the programme's risk pyramid according to the adjusted morbidity groups stratification tool and (2) they suffer simultaneously at least three selected chronic non-cancer pathologies (n=591).

MAIN OUTCOME MEASURE

1 year mortality since patient inclusion in the programme.

RESULTS

Among study participants, 201 (34%) died within the 1 year follow-up. Variables found to be independently associated to 1 year mortality were the Barthel Scale (p<0.001), creatinine value (p=0.032), existence of pressure ulcers (p=0.029) and patient global status (p<0.001). The area under the curve (AUC) for our model was 0.751, which was validated using bootstrapping (AUC=0.751) and k-fold cross-validation (10 folds; AUC=0.744). The Hosmer-Lemeshow test (p=0.761) showed good calibration.

CONCLUSIONS

This study develops and validates a mortality prediction model that will guide transitions of care to non-cancer palliative care services. The model determines prognostic indicators of death and provides tools for the estimation of individual death risk scores for each patient. We present a nomogram, a graphical risk calculation instrument, that favours a practical and easy use of the model within clinical practices.

What lies beneath: a retrospective, population-based cohort study investigating clinical and resource-use characteristics of institutionalized older people in Catalonia

Background

Planning population care in a specific health care setting requires deep knowledge of the clinical characteristics of the target care recipients, which tend to be country specific. Our area virtually lacks any descriptive, far-reaching publications about institutionalized older people (IOP). We aimed to investigate the demographic and clinical characteristics of institutionalized older people (IOP) ≥65 years old and compare them with those of the rest of the population of the same age.

Methods

Retrospective analysis (total cohort approach) of clinical and resource-use characteristics of IOP and non-IOP older than 65 years in Catalonia (North-East Spain). Variables analysed included age and sex, diagnoses, morbidity burden—using Adjusted Morbidity Groups (GMA, Grupos de Morbilidad Ajustada)—, mortality, use of resources, and medications taken. All data were obtained from the administrative database of the local healthcare system.

Results

This study included 93,038, 78,458, 68,545 and 67,456 IOP from 2011, 2013, 2015 and 2017, respectively. In this interval, an increase in median age (83 vs. 87 years), in women (68.64% vs. 72.11%) and in annual mortality (11.74% vs. 20.46%) was observed. Compared with non-IOP (p < 0.001 in all comparisons), IOP showed a higher annual mortality (20.46% vs. 3.13%), a larger number of chronic diseases (specially dementia: 46.47% vs. 4.58%), higher multimorbidity (15.2% vs. 4.2% with GMA of maximum complexity), and annual admissions to acute care (47.6% vs. 27.7%) and skilled nursing facilities (27.8% vs. 7.4%), mean length of hospital stay (10.0 vs. 7.2 days) and mean of medications taken (11.7 vs. 8.0).

Conclusions

There is a growing gap between the clinical and demographic characteristics of age-matched IOP and non-IOP, which overlaps with a higher mortality rate of IOP. The profile of resources utilization of IOP compared with non-IOP strongly suggests a deficiency of preventive actions and stresses the need to rethink the care model for IOP from a social and health care perspective.

Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population

Background

Multimorbidity is highly relevant for both service commissioning and clinical decision-making. Optimization of variables assessing multimorbidity in order to enhance chronic care management is an unmet need. To this end, we have explored the contribution of multimorbidity to predict use of healthcare resources at community level by comparing the predictive power of four different multimorbidity measures.

Methods

A population health study including all citizens ≥18 years (n = 6,102,595) living in Catalonia (ES) on 31 December 2014 was done using registry data. Primary care service utilization during 2015 was evaluated through four outcome variables: A) Frequent attendants, B) Home care users, C) Social worker users, and, D) Polypharmacy. Prediction of the four outcome variables (A to D) was carried out with and without multimorbidity assessment. We compared the contributions to model fitting of the following multimorbidity measures: i) Charlson index; ii) Number of chronic diseases; iii) Clinical Risk Groups (CRG); and iv) Adjusted Morbidity Groups (GMA).

Results

The discrimination of the models (AUC) increased by including multimorbidity as covariate into the models, namely: A) Frequent attendants (0.771 vs 0.853), B) Home care users (0.862 vs 0.890), C) Social worker users (0.809 vs 0.872), and, D) Polypharmacy (0.835 vs 0.912). GMA showed the highest predictive power for all outcomes except for polypharmacy where it was slightly below than CRG.

Conclusions

We confirmed that multimorbidity assessment enhanced prediction of use of healthcare resources at community level. The Catalan population-based risk assessment tool based on GMA presented the best combination of predictive power and applicability.

Outcomes and cost of lung cancer patients treated surgically or medically in Catalunya: cost-benefit implications for lung cancer screening programs

Lung cancer screening programs with computed tomography of the chest reduce mortality by more than 20%. Yet, they have not been implemented widely because of logistic and cost implications. Here, we sought to: (1) use real-life data to compare the outcomes and cost of lung cancer patients with treated medically or surgically in our region and (2) from this data, estimate the cost-benefit ratio of a lung cancer screening program (CRIBAR) soon to be deployed in our region (Catalunya, Spain). We accessed the Catalan Health Surveillance System (CHSS) and analysed data of all patients with a first diagnosis of lung cancer between 1 January 2014 and 31 December 2016. Analysis was carried forward until 30 months (t = 30) after lung cancer diagnosis. Main results showed that: (1) surgically treated lung cancer patients have better survival and return earlier to regular home activities, use less healthcare related resources and cost less tax-payer money and (2) depending on incidence of lung cancer identified and treated in the program (1-2%), the return on investment for CRIBAR is expected to break even at 3-6 years, respectively, after its launch. Surgical treatment of lung cancer is cheaper and offers better outcomes. CRIBAR is estimated to be cost-effective soon after launch.

Digital Health Transformation of Integrated Care in Europe: Overarching Analysis of 17 Integrated Care Programs

Background

Digital health tools comprise a wide range of technologies to support health processes. The potential of these technologies to effectively support health care transformation is widely accepted. However, wide scale implementation is uneven among countries and regions. Identification of common factors facilitating and hampering the implementation process may be useful for future policy recommendations.

Objective

The aim of this study was to analyze the implementation of digital health tools to support health care and social care services, as well as to facilitate the longitudinal assessment of these services, in 17 selected integrated chronic care (ICC) programs from 8 European countries.

Methods

A program analysis based on thick descriptions—including document examinations and semistructured interviews with relevant stakeholders—of ICC programs in Austria, Croatia, Germany, Hungary, the Netherlands, Norway, Spain, and the United Kingdom was performed. A total of 233 stakeholders (ie, professionals, providers, patients, carers, and policymakers) were interviewed from November 2014 to September 2016. The overarching analysis focused on the use of digital health tools and program assessment strategies.

Results

Supporting digital health tools are implemented in all countries, but different levels of maturity were observed among the programs. Only few ICC programs have well-established strategies for a comprehensive longitudinal assessment. There is a strong relationship between maturity of digital health and proper evaluation strategies of integrated care.

Conclusions

Notwithstanding the heterogeneity of the results across countries, most programs aim to evolve toward a digital transformation of integrated care, including implementation of comprehensive assessment strategies. It is widely accepted that the evolution of digital health tools alongside clear policies toward their adoption will facilitate regional uptake and scale-up of services with embedded digital health tools.

Evaluation of bottom-up interventions targeting community-dwelling frail older people in Belgium: methodological challenges and lessons for future comparative effectiveness studies

Background

Optimizing the organization of care for community-dwelling frail older people is an important issue in many Western countries. In Belgium, a series of complex, innovative, bottom-up interventions was recently designed and implemented to help frail older people live at home longer. As the effectiveness of these interventions may vary between different population groups according to their long-term care needs, they must be evaluated by comparison with a control group that has similar needs.

Methods

The goal was to identify target groups for these interventions and to establish control groups with similar needs and to explore, per group, the extent to which the utilization of long-term care is matched to needs. We merged two databases: a clinical prospective database and the routine administrative database for healthcare reimbursements. Through Principal Component Analysis followed by Clustering, the intervention group was first stratified into disability profiles. Per profile, comparable control groups for clinical variables were established, based on propensity scores. Using chi-squared tests and logistic regression analysis, long-term care utilization at baseline was then compared per profile and group studied.

Results

Stratification highlighted five disability profiles: people with low-level limitations; people with limitations in instrumental activities of daily life and low-level of cognitive impairment; people with functional limitations; people with functional and cognitive impairments; and people with functional, cognitive, and behavioral problems. These profiles made it possible to identify long-term care needs. For instance, at baseline, those who needed more assistance with hygiene tasks also received more personal nursing care (P < 0.05). However, there were some important discrepancies between the need for long-term care and its utilization: while 21% of patients who were totally dependent for hygiene tasks received no personal nursing care, personal nursing care was received by 33% of patients who could perform hygiene tasks.

Conclusions

The disability profiles provide information on long-term care needs but not on the extent to which those needs are met. To assess the effectiveness of interventions, controls at baseline should have similar disability profiles and comparable long-term care utilization. To allow for large comparative effectiveness studies, these dimensions should ideally be available in routine databases.

Electronic supplementary material

The online version of this article (10.1186/s12913-019-4240-9) contains supplementary material, which is available to authorized users.

Evaluation of integrated care services in Catalonia: population-based and service-based real-life deployment protocols

BACKGROUND

Comprehensive assessment of integrated care deployment constitutes a major challenge to ensure quality, sustainability and transferability of both healthcare policies and services in the transition toward a coordinated service delivery scenario. To this end, the manuscript articulates four different protocols aiming at assessing large-scale implementation of integrated care, which are being developed within the umbrella of the regional project Nextcare (2016-2019), undertaken to foster innovation in technologically-supported services for chronic multimorbid patients in Catalonia (ES) (7.5 M inhabitants). Whereas one of the assessment protocols is designed to evaluate population-based deployment of care coordination at regional level during the period 2011-2017, the other three are service-based protocols addressing: i) Home hospitalization; ii) Prehabilitation for major surgery; and, iii) Community-based interventions for frail elderly chronic patients. All three services have demonstrated efficacy and potential for health value generation. They reflect different implementation maturity levels. While full coverage of the entire urban health district of Barcelona-Esquerra (520 k inhabitants) is the main aim of home hospitalization, demonstration of sustainability at Hospital Clinic of Barcelona constitutes the core goal of the prehabilitation service. Likewise, full coverage of integrated care services addressed to frail chronic patients is aimed at the city of Badalona (216 k inhabitants).

METHODS

The population-based analysis, as well as the three service-based protocols, follow observational and experimental study designs using a non-randomized intervention group (integrated care) compared with a control group (usual care) with a propensity score matching method. Evaluation of cost-effectiveness of the interventions using a Quadruple aim approach is a central outcome in all protocols. Moreover, multi-criteria decision analysis is explored as an innovative method for health delivery assessment. The following additional dimensions will also be addressed: i) Determinants of sustainability and scalability of the services; ii) Assessment of the technological support; iii) Enhanced health risk assessment; and, iv) Factors modulating service transferability.

DISCUSSION

The current study offers a unique opportunity to undertake a comprehensive assessment of integrated care fostering deployment of services at regional level. The study outcomes will contribute refining service workflows, improving health risk assessment and generating recommendations for service selection.

TRIALS REGISTRATION

NCT03130283 (date released 04/06/2018), NCT03768050 (date released 12/05/2018), NCT03767387 (date released 12/05/2018).

Paradigm changes for diagnosis: using big data for prediction

Due to profound changes occurring in biomedical knowledge and in health systems worldwide, an entirely new health and social care scenario is emerging. Moreover, the enormous technological potential developed over the last years is increasingly influencing life sciences and driving changes toward personalized medicine and value-based healthcare. However, the current slow progression of adoption, limiting the generation of healthcare efficiencies through technological innovation, can be realistically overcome by fostering convergence between a systems medicine approach and the principles governing Integrated Care. Implicit with this strategy is the multidisciplinary active collaboration of all stakeholders involved in the change, namely: citizens, professionals with different profiles, academia, policy makers, industry and payers. The article describes the key building blocks of an open and collaborative hub currently being developed in Catalonia (Spain) aiming at generation, deployment and evaluation of a personalized medicine program addressing highly prevalent chronic conditions that often show co-occurrence, namely: cardiovascular disorders, chronic obstructive pulmonary disease, type 2 diabetes mellitus; metabolic syndrome and associated mental disturbances (anxiety-depression and altered behavioral patterns leading to unhealthy life styles).

Protocol for regional implementation of collaborative self-management services to promote physical activity

BACKGROUND

Chronic diseases are generating a major health and societal burden worldwide. Healthy lifestyles, including physical activity (PA), have proven efficacy in the prevention and treatment of many chronic conditions. But, so far, national PA surveillance systems, as well as strategies for promotion of PA, have shown low impact. We hypothesize that personalized modular PA services, aligned with healthcare, addressing the needs of a broad spectrum of individual profiles may show cost-effectiveness and sustainability.

METHODS

The current manuscript describes the protocol for regional implementation of collaborative self-management services to promote PA in Catalonia (7.5 M habitants) during the period 2017-2019. The protocols of three implementation studies encompassing a broad spectrum of individual needs are reported. They have a quasi-experimental design. That is, a non-randomized intervention group is compared to a control group (usual care) using propensity score methods wherein age, gender and population-based health risk assessment are main matching variables. The principal innovations of the PA program are: i) Implementation of well-structured modular interventions promoting PA; ii) Information and communication technologies (ICT) to facilitate patient accessibility, support collaborative management of individual care plans and reduce costs; and iii) Assessment strategies based on the Triple Aim approach during and beyond the program deployment.

DISCUSSION

The manuscript reports a precise roadmap for large scale deployment of community-based ICT-supported integrated care services to promote healthy lifestyles with high potential for comparability and transferability to other sites.

TRIAL REGISTRATION

This study protocol has been registered at ClinicalTrials.org ( NCT02976064 ). Registered November 24th, 2016.

Risk and temporal order of disease diagnosis of comorbidities in patients with COPD: a population health perspective

Introduction

Comorbidities in patients with chronic obstructive pulmonary disease (COPD) generate a major burden on healthcare. Identification of cost-effective strategies aiming at preventing and enhancing management of comorbid conditions in patients with COPD requires deeper knowledge on epidemiological patterns and on shared biological pathways explaining co-occurrence of diseases.

Methods

The study assesses the co-occurrence of several chronic conditions in patients with COPD using two different datasets: Catalan Healthcare Surveillance System (CHSS) (ES, 1.4 million registries) and Medicare (USA, 13 million registries). Temporal order of disease diagnosis was analysed in the CHSS dataset.

Results

The results demonstrate higher prevalence of most of the diseases, as comorbid conditions, in elderly (>65) patients with COPD compared with non-COPD subjects, an effect observed in both CHSS and Medicare datasets. Analysis of temporal order of disease diagnosis showed that comorbid conditions in elderly patients with COPD tend to appear after the diagnosis of the obstructive disease, rather than before it.

Conclusion

The results provide a population health perspective of the comorbidity challenge in patients with COPD, indicating the increased risk of developing comorbid conditions in these patients. The research reinforces the need for novel approaches in the prevention and management of comorbidities in patients with COPD to effectively reduce the overall burden of the disease on these patients.

FINGER (Forming and Identifying New Groups of Expected Risks): developing and validating a new predictive model to identify patients with high healthcare cost and at risk of admission

OBJECTIVE

Predictive statistical models used in population stratification programmes are complex and usually difficult to interpret for primary care professionals. We designed FINGER (Forming and Identifying New Groups of Expected Risks), a new model based on clinical criteria, easy to understand and implement by physicians. Our aim was to assess the ability of FINGER to predict costs and correctly identify patients with high resource use in the following year.

DESIGN

Cross-sectional study with a 2-year follow-up.

SETTING

The Basque National Health System.

PARTICIPANTS

All the residents in the Basque Country (Spain) ≥14 years of age covered by the public healthcare service (n=1 946 884).

METHODS

We developed an algorithm classifying diagnoses of long-term health problems into 27 chronic disease groups. The database was randomly divided into two data sets. With the calibration sample, we calculated a score for each chronic disease group and other variables (age, sex, inpatient admissions, emergency department visits and chronic dialysis). Each individual obtained a FINGER score for the year by summing their characteristics' scores. With the validation sample, we constructed regression models with the FINGER score for the first 12 months as the only explanatory variable.

RESULTS

The annual FINGER scores obtained by patients ranged from 0 to 57 points, with a mean of 2.06. The coefficient of determination for healthcare costs was 0.188 and the area under the receiver operating characteristic curve was 0.838 for identifying patients with high costs (>95th percentile); 0.875 for extremely high costs (>99th percentile); 0.802 for unscheduled admissions; 0.861 for prolonged hospitalisation (>15 days); and 0.896 for death.

CONCLUSION

FINGER presents a predictive power for high risks fairly close to other classification systems. Its simple and transparent architecture allows for immediate calculation by clinicians. Being easy to interpret, it might be considered for implementation in regions involved in population stratification programmes.

Complex Care Needs in Multiple Chronic Conditions: Population Prevalence and Characterization in Primary Care. A Study Protocol

Background:

Chronicity, and particularly complex care needs for people with chronic diseases is one of the main challenges of health systems.

Objective:

To determine the population prevalence of people with chronic diseases and complex care needs and to characterize these needs considering features of health and social complexity in Primary Care.

Design:

Cross-sectional population-based study.

Scope:

Patients who have one or more chronic health conditions from three Primary Care urban centres of a reference population of 43.647 inhabitants older than 14 years old.

Methodology:

Data will be obtained from the review of electronical medical records. Complexity will be defined by: 1) the independent clinical judgment of primary care physicians and nurses and 2) the aid of three complexity domains (clinical and social). Patients with advanced chronic disease and limited life prognosis will be also described.

Conclusions:

This research protocol intends to describe and analyse complex care needs from a primary care professional perspective in order to improve knowledge of complexity beyond multimorbidity and previous consumption of health resources. Knowing about health and social complexity with a more robust empirical basis could help for a better integration of social and health policies and a more proactive and differentiated care approach in this most vulnerable population.

Implementation of Home Hospitalization and Early Discharge as an Integrated Care Service: A Ten Years Pragmatic Assessment

Home Hospitalization has proven efficacy, but its effectiveness and potential as an Integrated Care Service in a real world setting deserves to be explored.

OBJECTIVE

To evaluate implementation and 10 years follow-up of Home Hospitalization and Early Discharge as an Integrated Care Service in an urban healthcare district in Barcelona.

METHODS

Prospective study with pragmatic assessment. Patients: Surgical and medical acute and exacerbated chronic patients requiring admission into a highly specialized hospital, from 2006 to 2015. Intervention: Home-based individualized care plan, administered as a hospital-based outreach service, aiming at substituting hospitalization and implementing a transitional care strategy for optimal discharge. Main measurements: Emergency Department, readmissions and mortality. Patients' and professionals' perspectives, technologies and costs were evaluated.

RESULTS

4,165 admissions (71 ± 15 yrs; Charlson Index 4 ± 3). In-hospital stay was 1 (0-3) days and the length of home-based stay was 6 (5-7) days. The 30-day readmission rate was 11% and mortality was 2%. Patients, careers and health professionals expressed high levels of satisfaction (98%). At the start, the service was reimbursed at a flat rate of 918€ per patient discharged, significantly lower than conventional hospitalization (2,879€) but still allowing the hospital to keep a balanced budget. At present, there is no difference in the payment schemes for both types of services.

CONCLUSIONS

The service freed an average of 6 in-hospital days per patient. The program showed health value generation, as well as potential for synergies with community-based Integrated Care Services.

Population-based analysis of patients with COPD in Catalonia: a cohort study with implications for clinical management

BACKGROUND

Clinical management of patients with chronic obstructive pulmonary disease (COPD) shows potential for improvement provided that patients' heterogeneities are better understood. The study addresses the impact of comorbidities and its role in health risk assessment.

OBJECTIVE

To explore the potential of health registry information to enhance clinical risk assessment and stratification.

DESIGN

Fixed cohort study including all registered patients with COPD in Catalonia (Spain) (7.5 million citizens) at 31 December 2014 with 1-year (2015) follow-up.

METHODS

A total of 264 830 patients with COPD diagnosis, based on the International Classification of Diseases (Ninth Revision) coding, were assessed. Performance of multiple logistic regression models for the six main dependent variables of the study: mortality, hospitalisations (patients with one or more admissions; all cases and COPD-related), multiple hospitalisations (patients with at least two admissions; all causes and COPD-related) and users with high healthcare costs. Neither clinical nor forced spirometry data were available.

RESULTS

Multimorbidity, assessed with the adjusted morbidity grouper, was the covariate with the highest impact in the predictive models, which in turn showed high performance measured by the C-statistics: (1) mortality (0.83), (2 and 3) hospitalisations (all causes: 0.77; COPD-related: 0.81), (4 and 5) multiple hospitalisations (all causes: 0.80; COPD-related: 0.87) and (6) users with high healthcare costs (0.76). Fifteen per cent of individuals with highest healthcare costs to year ratio represented 59% of the overall costs of patients with COPD.

CONCLUSIONS

The results stress the impact of assessing multimorbidity with the adjusted morbidity grouper on considered health indicators, which has implications for enhanced COPD staging and clinical management.

TRIAL REGISTRATION NUMBER

NCT02956395.

Economic burden of cirrhosis in Catalonia: a population-based analysis

BACKGROUND

Cirrhosis is a chronic disease with high morbidity and mortality. Few studies have evaluated healthcare resource use in patients with cirrhosis.

OBJECTIVE

We aimed to describe the point prevalence of cirrhosis on 31 December 2012 and the population-level distribution of healthcare resource use and expenditures in a non-selected population of patients with cirrhosis, stratified by whether their disease was compensated or decompensated, and by comorbidity burden.

METHODS

This population study included all known patients aged >18 years with cirrhosis (according to International Classification of Diseases, ninth revision) in Catalonia, Spain, on 31 December 2012. We evaluated healthcare resource use and expenditure during 2013, taking into account the presence of decompensation before or during 2012.

RESULTS

We documented 34 740 patients diagnosed with cirrhosis (58.7% men; mean age 61.8±14 years), yielding a point prevalence of 460 per 100 000 inhabitants on 31 December 2012. Annual mortality was 9.1%. During 2013, healthcare expenditures on patients with cirrhosis totalled €142.1 million (€4234 per patient), representing 1.8% of the total 2013 healthcare budget of Catalonia. Hospitalisation costs accounted for 35.1% of the total expenditure and outpatient care accounted for 22.4%. MultivariateMultivariate logistic regression identified morbidity burden, HIV infection, hospitalisation and emergency room visits during 2012 as independent predictors of expenditure above the 85th centile (area under the receiver operating curve, 0.88 (95% CI 0.883 to 0.893, P<0.001)).

CONCLUSIONS

Cirrhosis accounts for a high proportion of healthcare resource usage and expenditures; hospitalisation accounted for the highest expenditures.

Key aspects related to implementation of risk stratification in health care systems-the ASSEHS study

BACKGROUND

The lack of proven efficacy of new healthcare interventions represents a problem for health systems globally. It is partly related to suboptimal implementation processes, leading to poor adoption of new interventions. Activation of Stratification Strategies and Results of the interventions on frail patients of Healthcare Services (ASSEHS) EU project (N° 2013 12 04) aims to study current existing health Risk Stratification (RS) strategies and tools on frail elderly patients. This paper aims at identifying variables that make the implementation of population RS tools feasible in different healthcare services.

METHODS

Two different methods have been used to identify the key elements in stratification implementation; i) a Scoping Review, in order to search and gather scientific evidence and ii) Semi-structured interviews with six key experts that had been actively involved in the design and/or implementation of RS strategies. It aims to focus the implementation construct on real-life contextual understandings, multi-level perspectives, and cultural influences.

RESULTS

A Feasibility Framework has been drawn. Two dimensions impact the feasibility of RS: (i) Planning, deployment and change management and (ii) Care intervention. The former comprises communication, training and mutual learning, multidisciplinarity of the team, clinicians' engagement, operational plan and ICT display and functionalities. The latter includes case finding and selection of the target population, pathway definition and quality improvement process.

CONCLUSIONS

The Feasibility Framework provides a list of key elements that should be considered for an effective implementation of population risk stratification interventions. It helps to identify, plan and consider relevant elements to ensure a proper RS implementation.

Securing the Continuity of Medical Competence in Times of Demographic Change: A Proposal

BACKGROUND

University hospitals make up the backbone of medical and economic services of hospitals in Germany: they qualify specialist physicians, ensure medical research, and provide highly specialized maximum medical care, which other hospitals cannot undertake. In addition to this assignment, medical research and academic teaching must be managed despite a growing shortage of specialist physicians. By the year 2020, the need for the replacement of retired physicians and increased demand will total 30,000 positions. The situation will become more difficult because, on the whole, patients are becoming older and sicker and because specialist physicians are able to find more attractive working conditions in smaller hospitals, abroad, or outside of curative medicine.

OBJECTIVE

In order to retain sufficient qualified employees, major improvements in quality are required in terms of working and training conditions. For this purpose, a sustainable innovation process is necessary, which incorporates solutions from outside of the health care sector in order to be able to learn from experiences and mistakes from other industries. The FacharztPlus project aims to find suitable measures in order to retain specialist physicians for more years after the completion of 5 years of professional training. This should determine the suitability of additional qualifications alongside the professional career and an expertise-related work organization oriented to different stages of life.

METHODS

Structured interviews, surveys, and repertory grids are used as preparation for cross-industry expert panels to create future work scenarios for university hospitals. Industries involved are harbor logistics (container terminal), airports, and digitized industrial production ("industry 4.0") because these industries are also facing a shortage of qualified staff and have to respond to rapidly changing demands. Based on the experts' scenarios, consensus groups will be established in each university hospital trying to reach consensus about the implementation of relevant factors in order to improve employee retention.

RESULTS

We expect these consensus groups to develop and introduce measures for more structured training procedures, individual and team incentives, organizational guidelines for better recruiting and retention in hospitals, models of flexible and attractive working conditions including shift work and vacation planning, and use of new learning tools (eg, tablet PCs and mobile phones).

CONCLUSIONS

All measures are implemented in the Department of Anaesthesiology, Intensive Care, Emergency Care and Pain Medicine at the University Hospital Muenster (UKM) with approximately 150 physicians and in the further 44 departments of the UKM and 22 teaching hospitals, which all together employ more than 5000 physicians. The measures will also be implemented at the university hospitals in Aachen, Rostock, and Greifswald. All decisions and measures will be discussed with representatives from hospital management and professional associations. Results will be presented at conferences and published in journals.

Enhancing risk stratification for use in integrated care: a cluster analysis of high-risk patients in a retrospective cohort study

OBJECTIVE

To show how segmentation can enhance risk stratification tools for integrated care, by providing insight into different care usage patterns within the high-risk population.

DESIGN

A retrospective cohort study. A risk score was calculated for each person using a logistic regression, which was then used to select the top 5% high-risk individuals. This population was segmented based on the usage of different care settings using a k-means cluster analysis. Data from 2008 to 2011 were used to create the risk score and segments, while 2012 data were used to understand the predictive abilities of the models.

SETTING AND PARTICIPANTS

Data were collected from administrative data sets covering primary and secondary care for a random sample of 300 000 English patients.

MAIN MEASURES

The high-risk population was segmented based on their usage of 4 different care settings: emergency acute care, elective acute care, outpatient care and GP care.

RESULTS

While the risk strata predicted care usage at a high level, within the high-risk population, usage varied significantly. 4 different groups of high-risk patients could be identified. These 4 segments had distinct usage patterns across care settings, reflecting different levels and types of care needs. The 2008-2011 usage patterns of the 4 segments were consistent with the 2012 patterns.

DISCUSSION

Cluster analyses revealed that the high-risk population is not homogeneous, as there exist 4 groups of patients with different needs across the care continuum. Since the patterns were predictive of future care use, they can be used to develop integrated care programmes tailored to these different groups.

CONCLUSIONS

Usage-based segmentation augments risk stratification by identifying patient groups with different care needs, around which integrated care programmes can be designed.