A case-mix classification system for explaining healthcare costs using administrative data in Italy

Pricing of hospital services: evidence from a thematic review

The management implications of pricing healthcare services, especially hospitals, have received insufficient scholarly attention. Additionally, disciplinary overlaps have led to scattered academic efforts in this domain. This study performs a thematic synthesis of the literature and applies retrospective analysis to hospital service pricing articles to address these issues. The study's inputs were sourced from well-known online repositories, using a structured search string and PRISMA flow chart to select the pertinent documents. Our thematic analysis of pricing literature encompasses: (a) comprehension of hospital service pricing nature; (b) pricing objectives, strategies and practices differentiation; (c) presentation of factors impacting hospital service pricing. We observe that hospital pricing is an intricate and unclear matter. The terms 'pricing strategies' and 'pricing practices' are often used interchangeably in academic literature. Hospital service pricing is influenced by costs, demand and supply factors, market structure, pricing regulation and third-party reimbursements. The study's findings provide policy implications for service pricing in hospitals, in addition to suggesting avenues for future research on hospital pricing.

Projecting cancer prevalence by phase of care: a methodological approach for health service planning

Background

In most developed countries, the number of cancer survivors is expected to increase in the coming decades because of rising incidence and survival rates and an aging population. These patients are heterogeneous in terms of health service demands: from recently diagnosed patients requiring first-course therapy to patients with extensive care needs and severe disabilities to long-term survivors who only need minimal care. Therefore, in terms of providing healthcare planners and policymakers with useful indicators for addressing policies according to health service demands, it is worth supplying updated measures of prevalence for groups of patients based on the level of care they require. The aim of this paper is to illustrate a new method for estimating short-term projections of cancer prevalence by phase of care that applies to areas covered by cancer registration.

Methods

The proposed method combines linear regression models to project limited duration prevalence derived from cancer registry data and a session of the freely available software COMPREV to estimate the projected complete prevalence into three distinct clinically relevant phases of care: initial, continuing, and final. The method is illustrated and validated using data from the Veneto region in Italy for breast, colorectal, and lung cancers.

Results

Prevalence is expected to increase in 2015-2026 for all considered cancer sites and sexes, with average annual variations spanning from 2.6% for women with lung cancer to 0.5% for men with colorectal cancer. The only exception is lung cancer prevalence in men, which shows an average annual decrease of 1.9%. The majority of patients are in the continuing phase of care, followed by the initial and final phases, except for lung cancer, where the final phase of care prevails over the initial one.

Discussion

The paper proposes a method for estimating (short-term) future cancer healthcare needs that is based on user-friendly and freely available software and linear regression models. Validation results confirm the applicability of our method to the most frequent cancer types, provided that cancer registry data with at least 15 years of registration are available. Evidence from this method is addressed to policymakers for planning future cancer care, thus improving the cancer survivorship experience for patients and caregivers.

Using the Johns Hopkins ACG Case-Mix System for population segmentation in a hospital-based adult patient population in Singapore

OBJECTIVE

Population health management involves risk characterisation and patient segmentation. Almost all population segmentation tools require comprehensive health information spanning the full care continuum. We assessed the utility of applying the ACG System as a population risk segmentation tool using only hospital data.

DESIGN

Retrospective cohort study.

SETTING

Tertiary hospital in central Singapore.

PARTICIPANTS

100 000 randomly selected adult patients from 1 January to 31 December 2017.

INTERVENTION

Hospital encounters, diagnoses codes and medications prescribed to the participants were used as input data to the ACG System.

PRIMARY AND SECONDARY OUTCOME MEASURES

Hospital costs, admission episodes and mortality of these patients in the subsequent year (2018) were used to assess the utility of ACG System outputs such as resource utilisation bands (RUBs) in stratifying patients and identifying high hospital care users.

RESULTS

Patients placed in higher RUBs had higher prospective (2018) healthcare costs, and were more likely to have healthcare costs in the top five percentile, to have three or more hospital admissions, and to die in the subsequent year. A combination of RUBs and ACG System generated rank probability of high healthcare costs, age and gender that had good discriminatory ability for all three outcomes, with area under the receiver-operator characteristic curve (AUC) values of 0.827, 0.889 and 0.876, respectively. Application of machine learning methods improved AUCs marginally by about 0.02 in predicting the top five percentile of healthcare costs and death in the subsequent year.

CONCLUSION

A population stratification and risk prediction tool can be used to appropriately segment populations in a hospital patient population even with incomplete clinical data.

Measuring the geographic disparity of comorbidity in commercially insured individuals compared to the distribution of physicians in South Africa

Background

Measuring and addressing the disparity between access to healthcare resources and underlying health needs of populations is a prominent focus in health policy development. More recently, the fair distribution of healthcare resources among population subgroups have become an important indication of health inequities. Single disease outcomes are commonly used for healthcare resource allocations; however, leveraging population-level comorbidity measures for health disparity research has been limited. This study compares the geographical distribution of comorbidity and associated healthcare utilization among commercially insured individuals in South Africa (SA) relative to the distribution of physicians.

Methods

A retrospective, cross-sectional analysis was performed comparing the geographical distribution of comorbidity and physicians for 2.6 million commercially insured individuals over 2016–2017, stratified by geographical districts and population groups in SA. We applied the Johns Hopkins ACG® System across the claims data of a large health plan administrator to measure a comorbidity risk score for each individual. By aggregating individual scores, we determined the average healthcare resource need of individuals per district, known as the comorbidity index (CMI), to describe the disease burden per district. Linear regression models were constructed to test the relationship between CMI, age, gender, population group, and population density against physician density.

Results

Our results showed a tendency for physicians to practice in geographic areas with more insurance enrollees and not necessarily where disease burden may be highest. This was confirmed by a negative relationship between physician density and CMI for the overall population and for three of the four major population groups. Among the population groups, the Black African population had, on average, access to fewer physicians per capita than other population groups, before and after adjusting for confounding factors.

Conclusion

CMI is a novel measure for healthcare disparities research that considers both acute and chronic conditions contributing to current and future healthcare costs. Our study linked and compared the population-level geographical distribution of CMI to the distribution of physicians using routinely collected data. Our results could provide vital information towards the more equitable distribution of healthcare providers across population groups in SA, and to meet the healthcare needs of disadvantaged communities.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-022-01899-1.

Congestive heart failure and comorbidity as determinants of colorectal cancer perioperative outcomes

There has been an increase in surgical interventions in frailer elderly with concomitant chronic diseases. The purpose of this paper was to evaluate the impact of aging and comorbidities on outcomes in patients who underwent surgery for the treatment of colorectal cancer (CRC) in Veneto Region (Northeastern Italy). This is a retrospective cohort study in patients ≥ 40 years who underwent elective or urgent CRC surgical resection between January 2013 and December 2015. Independent variables included: age, sex, and comorbidities. We analyzed variables associated with the surgical procedure, such as stoma creation, hospitalization during the year before the index surgery, the surgical approach used, the American Society of Anesthesiologists (ASA) score, and the Charlson Comorbidity Index score. Eight thousand four hundred and forty-seven patients with CRC underwent surgical resection. Patient age affected both pre- and post-resection LOS as well as the overall survival (OS); however, it did not affect the 30-day readmission and reoperation rates. Multivariate analysis showed that age represented a risk factor for longer preoperative and postoperative LOS as well as for 30-day and 365-day mortality, but it was not associated with an increased risk of 30-day reoperation and 30-day readmission. Chronic Heart Failure increased the 30-day mortality risk by four times, the preoperative LOS by 51%, and the postoperative LOS by 33%. Chronic renal failure was associated with a 74% higher 30-day readmission rate. Advanced age and comorbidities require a careful preoperative evaluation and appropriate perioperative management to improve surgical outcomes in older patients undergoing elective or urgent CRC resection.

Impact of vaccination on the spread of SARS-CoV-2 infection in north-east Italy nursing homes. A propensity score and risk analysis

Background

In the Veneto Region, 421,000 coronavirus 2019 disease (COVID-19) cases and 11,000 deaths have been reported since 21 February 2020. The pandemic spread particularly in nursing homes (NH).

Objective

This study estimated the impact of SARS-CoV-2 infection among NH residents, focusing on the risk of hospitalisation and death due to COVID-19 compared with the general older population. It also provided evidence of risk changes over time.

Methods

Older people, resident in Veneto, were enrolled from the regional registry of the population. We collected also information about demographic characteristics, chronic diseases, COVID-19 positivity, NH institutionalization, hospitalisation and date of death. Patients were assigned to NH or non-NH residents groups through a propensity score 1:1 matching. The follow-up period was defined as 21 February 2020 – 3 May 2021 and then divided into three waves. Risk ratios (RRs) and 95% confidence interval were estimated by using Poisson models with robust estimation of variance.

Results

NH residents showed a higher risk of COVID-19 infection (RR = 6.28; 6.03–6.54), hospitalisation for COVID-19 (RR = 2.20; 2.05–2.36) and death with COVID-19 (RR = 6.07; 5.58–6.61).

Conclusion

NH residents shared common spaces with other patients and healthcare professionals and were more exposed to infections. Nonetheless, in Italy from late December 2020 to May 2021, 95% of NH residents and their healthcare professionals received at least one vaccine dose and RRs for all outcomes decreased in NH.

Prevalence, determinants, and outcomes of SARS-COV-2 infection among cancer patients. A population-based study in northern Italy

BACKGROUND

It is well established that cancer patients infected with SARS-CoV-2 are at particularly elevated risk of adverse outcomes, but the comparison of SARS-CoV-2 infection risk between cancer patients and cancer-free individuals has been poorly investigated on a population-basis.

METHODS

A population-based study was thus conducted in Friuli Venezia Giulia region, northeastern Italy, to estimate prevalence and determinants of SARS-CoV-2 infection among cancer patients, as compared to cancer-free individuals, and to evaluate adverse outcomes of SARS-CoV-2 infection. The study included 263,042 individuals tested for SARS-CoV-2 in February-December 2020 with cancer history retrieved through the regional cancer registry. Odds ratios (ORs) of SARS-CoV-2 positivity, with corresponding 95% confidence intervals (CIs), were calculated using multivariable logistic regression models, adjusted for sex and age. Hazard ratios (HRs) adjusted for sex and age for intensive care unit (ICU) admission and all-cause death were estimated using Cox models.

RESULTS

Among 26,394 cancer patients tested for SARS-CoV-2, the prevalence of infection was 11.7% versus 16.2% among 236,648 cancer-free individuals, with a corresponding OR = 0.59 (95% CI: 0.57-0.62). The prevalence was much higher (29% in both groups) during the second pandemic wave (October-December 2020). Among cancer patients, age ≥80 years and cancer diagnosis ≥13 months before SARS-CoV-2 testing were the major risk factors of infection. Among 3098 infected cancer patients, the fatality rate was 17.4% versus 15.8% among 23,296 negative ones (HR = 1.63, 95% CI: 1.49-1.78), and versus 5.0% among 38,268 infected cancer-free individuals (HR = 1.23, 95% CI: 1.12-1.36). No significant differences emerged when considering ICU admission risk.

CONCLUSION

Albeit cancer patients reported reduced SARS-CoV-2 infection risk, those infected showed higher mortality than uninfected ones and infected cancer-free population. Study findings claim for continuing to protect cancer patients from SARS-CoV-2, without reducing the level of oncologic care.

Type 1 diabetes prevalence and incidence rates in the pediatric population of Veneto Region (Italy) in 2015-2020

The prevalence of Type 1 Diabetes (T1D) in the Veneto Region (Italy) in the 2015-2020 years was 152.5/100,000 subjects and the incidence 19.7/100,000 person-years. Accordingly, Veneto Region can be defined as a high-risk area for pediatric T1D.

SARS-CoV-2 and COVID-19 in diabetes mellitus. Population-based study on ascertained infections, hospital admissions and mortality in an Italian region with ∼5 million inhabitants and ∼250,000 diabetic people

BACKGROUND AND AIMS

Diabetes conveys an increased risk of infectious diseases and related mortality. We investigated risk of ascertained SARS-CoV-2 infection in diabetes subjects from the Veneto Region, Northeastern Italy, as well as the risk of being admitted to hospital or intensive care unit (ICU), or mortality for COVID-19.

METHODS AND RESULTS

Diabetic subjects were identified by linkage of multiple health archives. The rest of the population served as reference. Information on ascertained infection by SARS-CoV-2, admission to hospital, admission to ICU and mortality in the period from February 21 to July 31, 2020 were retrieved from the regional registry of COVID-19. Subjects with ascertained diabetes were 269,830 (55.2% men; median age 72 years). Reference subjects were 4,681,239 (men 48.6%, median age 46 years). Ratios of age- and gender-standardized rates (RR) [95% CI] for ascertained infection, admission to hospital, admission to ICU and disease-related death in diabetic subjects were 1.31 [1.19-1.45], 2.11 [1.83-2.44], 2.45 [1.96-3.07], 1.87 [1.68-2.09], all p < 0.001. The highest RR of ascertained infection was observed in diabetic men aged 20-39 years: 1.90 [1.04-3.21]. The highest RR of ICU admission and death were observed in diabetic men aged 40-59 years: 3.47 [2.00-5.70] and 5.54 [2.23-12.1], respectively.

CONCLUSIONS

These data, observed in a large population of ∼5 million people of whom ∼250,000 with diabetes, show that diabetes not only conveys a poorer outcome in COVID-19 but also confers an increased risk of ascertained infection from SARS-CoV-2. Men of young or mature age have the highest relative risks.

Health care service use and costs for a cohort of high-needs elderly diabetic patients

AIMS

To describe the impact of diabetes comorbidities on the health care services use and costs of a cohort of elderly patients with diabetes and high health care needs (HHCN), based on real-world data.

METHODS

We focused on a cohort of diabetic patients with HHCN belonging to Resource Utilization Bands 4 and 5 according to the Adjusted Clinical Group (ACG) system. Their comorbidities were assessed using the clinical diagnoses that the ACG system assigns to single patients by combining different information flows. Regression models were applied to analyze the associations between comorbidities and health care service use or costs, adjusting for age and sex.

RESULTS

Our analyses showed that all health care service usage measures (e.g. access to emergency care; number of outpatient visits) and the total annual costs and pharmacy costs are associated significantly with comorbidity class. Instead, no differences in hospitalization rates by comorbidity class were revealed.

CONCLUSION

The association between a larger number of comorbidities and higher total health care service usage and costs was seen mainly for primary care services. This underscores the need to strengthen primary care for today's aging and multimorbid population.

The Economic Impact of Rectal Cancer: A Population-Based Study in Italy

Costs of cancer care are increasing worldwide, and sustainability of cancer burden is critical. In this study, the economic impact of rectal cancer on the Italian healthcare system, measured as public healthcare expenditure related to investigation and treatment of rectal cancer patients is estimated. A cross-sectional cohort of 9358 rectal cancer patients is linked, on an individual basis, to claims associated to rectal cancer diagnosis and treatments. Costs refer mainly to years 2010–2011 and are estimated by phase of care, as healthcare needs vary along the care pathway: diagnostic procedures are mainly provided in the first year, surveillance procedures are addressed to chronically ill patients, and end-of-life procedures are given in the terminal status. Clinical approaches and corresponding costs are specific by cancer type and vary by phase of care, stage at diagnosis, and age. Surgery is undertaken by the great majority of patients. Thus, hospitalization is the main cost driver. The evidence produced can be used to improve planning and allocation of healthcare resources. In particular, early diagnosis of rectal cancer is a gain in healthcare budget. Policies raising spreading of and adherence to screening plans, above all when addressed to people living in Southern Italy, should be strongly encouraged.

The Barthel index as an indicator of hospital outcomes: A retrospective cross-sectional study with healthcare data from older people

AIMS

The assessment of functional status is a more appropriate measure in the older people than traditional healthcare outcomes. The present study aimed to analyse the association between functional status assessed using the Barthel Index and length of stay, in-hospital mortality, discharge destination, and Diagnosis-Related Groups-based cost.

DESIGN

This study was a retrospective study that used administrative data from patients older than 65 discharged from the University Hospital of Padua (Italy) in 2016.

METHODS

A logistic regression model for categorical variables (length of stay, in-hospital mortality, and discharge destination) and a generalized linear model with gamma distributions and log links for continuous variables (cost of hospitalization) were used to evaluate associations with the Barthel Index.

RESULTS

A total of 13,484 admissions were included in the analysis. In-hospital mortality, safe discharge, and length of stay were higher in patients with severe dependence than in patients with mild/no dependence with a 12-fold increased risk of death (OR = 12.81; 95% CI 9.22-18.14), a 4 times greater likelihood of safe discharge (OR = 4.64; 95% CI 3.96-5.45), and a 2-fold increase in length of stay (OR = 2.56; 95% CI 2.34-2.81). On the other hand, no significant association was found between the cost of hospitalization and the Barthel Index.

CONCLUSIONS

Barthel Index was strongly associated with in-hospital mortality, discharge destination, and length of stay. The costs of hospitalization, however, were not related to patients' functional impairment.

IMPACT

The study considers functional status as an indicator of hospital outcomes. Better comprehension of the relationship between functional status and healthcare outcomes may help with early and adequate healthcare planning and resource management.

Assessing the geographical distribution of comorbidity among commercially insured individuals in South Africa

BACKGROUND

Comorbidities are strong predictors of current and future healthcare needs and costs; however, comorbidities are not evenly distributed geographically. A growing need has emerged for comorbidity surveillance that can inform decision-making. Comorbidity-derived risk scores are increasingly being used as valuable measures of individual health to describe and explain disease burden in populations.

METHODS

This study assessed the geographical distribution of comorbidity and its associated financial implications among commercially insured individuals in South Africa (SA). A retrospective, cross-sectional analysis was performed comparing the geographical distribution of comorbidities for 2.6 million commercially insured individuals over 2016-2017, stratified by geographical districts in SA. We applied the Johns Hopkins ACG® System across the insurance claims data of a large health plan administrator in SA to measure comorbidity as a risk score for each individual. We aggregated individual risk scores to determine the average risk score per district, also known as the comorbidity index (CMI), to describe the overall disease burden of each district.

RESULTS

We observed consistently high CMI scores in districts of the Free State and KwaZulu-Natal provinces for all population groups before and after age adjustment. Some areas exhibited almost 30% higher healthcare utilization after age adjustment. Districts in the Northern Cape and Limpopo provinces had the lowest CMI scores with 40% lower than expected healthcare utilization in some areas after age adjustment.

CONCLUSIONS

Our results show underlying disparities in CMI at national, provincial, and district levels. Use of geo-level CMI scores, along with other social data affecting health outcomes, can enable public health departments to improve the management of disease burdens locally and nationally. Our results could also improve the identification of underserved individuals, hence bridging the gap between public health and population health management efforts.

Integrating E-Prescribing and Pharmacy Claims Data for Predictive Modeling: Comparing Costs and Utilization of Health Plan Members Who Fill Their Initial Medications with Those Who Do Not

BACKGROUND

Nonfilling of prescribed medications is a worldwide problem of serious concern. Studies of health care costs and utilization associated with medication nonadherence frequently rely on claims data and usually focus on patients with specific conditions. Past studies also have little agreement on whether higher medication costs associated with higher adherence can reduce downstream health care consumption.

OBJECTIVES

To (a) compare the characteristics between people with and without complete medication initiations from a general population and (b) quantify the effect of medication initiation on health care utilization and expenditures with propensity score weighting.

METHODS

We conducted a retrospective cohort study using 2012 and 2013 electronic health records (EHR) and insurance claims data from an integrated health care delivery network. We included 43,097 eligible primary care patients in the study. Annual medication fill rates of initial prescriptions in 2012 were defined as the number of filled prescriptions from claims divided by the number of e-prescriptions from EHRs, while excluding all refills. A claim was considered filled if (a) EHR and claims records were from the same drug class; (b) claims occurred between the date of a current EHR order and that of the next EHR order of the same class; and (c) the maximum fill rate was 100%. The 6 annual outcomes included total costs, medical costs, pharmacy costs, being a high-cost "outlier" (in top 5%), having 1 or more hospitalizations, and having 1 or more emergency department (ED) visits. Individuals were classified as either having completed all medication initiations (100% annual filling rate for initiations) or not. We used propensity score weighting to control for baseline differences between complete and incomplete initial fillers. We adopted linear and logistic regressions to model costs and binary utilization indicators for the same year (concurrently) and next year (prospectively).

RESULTS

Approximately 42% of the study sample had complete medication initiations (100% filling rate), while the remaining 58% had incomplete initiations. Individuals who fully filled initial prescriptions had lower comorbidity burden and consumed fewer health care resources. After applying propensity score weighting and controlling for variables such as the number of prescription orders, patients with complete medication initiations had lower overall and medical costs, concurrently and prospectively (e.g., $751 and $252 less for annual total costs). Complete medication initiation fillers were also less likely to have concurrent health care utilization (OR = 0.78, 95% CI = 0.68-0.90 for hospitalization; OR = 0.77, 95% CI = 0.72-0.82 for ED admissions) but no difference in prospective utilization other than for ED visits (OR = 0.93, 95% CI = 0.87-0.99).

CONCLUSIONS

Identifying the subpopulation of patients with incomplete medication initiations (i.e., filling less than 100% of initial prescriptions) is a pragmatic approach for population health management programs to align resources and potentially contain cost and utilization.

DISCLOSURES

No outside funding supported this study. This study applied the Adjusted Clinical Group (ACG) case-mix/risk adjustment methodology, developed at Johns Hopkins Bloomberg School of Public Health. Although ACGs are an important aspect of this study, the goal of the study was not to directly assess or evaluate the methodology. The Johns Hopkins University receives royalties for nonacademic use of software based on the ACG methodology. Chang, Kharrazi, and Weiner receive a portion of their salary support from this revenue. Chang is also a part-time consultant for Monument Analytics, a health care consultancy whose clients include the life sciences industry, as well as plaintiffs in opioid litigation. Alexander is past Chair of FDA's Peripheral and Central Nervous System Advisory Committee; has served as a paid advisor to IQVIA; is a co-founding Principal and equity holder in Monument Analytics; and is a member of OptumRx's National P&T Committee. These arrangements have been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies. The other authors have nothing to disclose.

Impact of Area Deprivation Index on the Performance of Claims-Based Risk-Adjustment Models in Predicting Health Care Costs and Utilization

Traditionally, risk-adjustment models do not address the characteristics of minority populations, such as race or socioeconomic status. This study aimed to evaluate the added value of place-based social determinants on risk-adjustment models in explaining health care costs and utilization. Statewide commercial claims from the Maryland Medical Care Database were used, including 1,150,984 Maryland residents aged 18 to 63 with ≥6 months enrollment in 2013 and 2014. Area Deprivation Index (ADI) was assigned to individuals through zip code. The authors examined the addition of ADI to predictive models of concurrent and prospective costs and utilization; linear regression was adopted for costs and logistic regression for utilization markers. Performance measures included R² for costs (total, pharmacy, and medical costs) and the area under the curve (AUC) for utilization (being top 5% top users, having any hospitalization, having any emergency room [ER] visit, having any avoidable ER visit, and having any readmission). All performance measures were derived from the bootstrapping analysis with 200 iterations. Study subjects were ∼48% male with a mean age of ∼41 years. Adding ADI to the demographics or claims-based models generally did not improve performance except in predicting the probability of having any ER or any avoidable ER visit; for example, AUC of avoidable ER visits increased significantly from .610 to .613 when using ADI rank deciles in claims-based models. Future research should focus on patients with a higher need for social services, assess more granular place-based determinants (eg, Census block group), and evaluate the added value of individual social variables.

Patterns of care and cost profiles of women with breast cancer in Italy: EPICOST study based on real world data

OBJECTIVES

To estimate total direct health care costs associated to diagnosis and treatment of women with breast cancer in Italy, and to investigate their distribution by service type according to the disease pathway and patient characteristics.

METHODS

Data on patients provided by population-based Cancer Registries are linked at individual level with data on health-care services and corresponding claims from administrative databases. A combination of cross-sectional approach and a threephase of care decomposition model with initial, continuing and final phases-of-care defined according to time occurred since diagnosis and disease outcome is adopted. Direct estimation of cancer-related costs is obtained.

RESULTS

Study cohort included 49,272 patients, 15.2% were in the initial phase absorbing 42% of resources, 79.7% in the continuing phase absorbing 44% of resources and 5.1% in the final phase absorbing 14% of resources. Hospitalization was the most important cost driver, accounting for over 55% of the total costs.

CONCLUSIONS

This paper represents the first attempt in Italy to estimate the economic burden of cancer at population level taking into account the entire disease pathway and using multiple current health care databases. The evidence produced by the study can be used to better plan resources allocation. The model proposed is replicable to countries with individual health care information on services and claims.

Overall mortality and causes of death in newly admitted nursing home residents

BACKGROUND

In spite of a rapidly ageing population, there is a lack of population-based data on mortality among nursing home residents in Southern Europe.

AIMS

To assess mortality rates, their determinants, and causes of death in newly admitted nursing home residents in the Veneto region (northeastern Italy).

METHODS

19,392 subjects aged ≥ 65 years admitted to regional nursing homes during 2015-2017 were recruited in a cohort mortality study based on linked health records. Risk factors for mortality were investigated by Cox regression. The distribution of causes of death was retrieved from death certificates.

RESULTS

Mortality peaked in the first 4 months after admission; thereafter the monthly mortality rate fluctuated around 3% in males and 2% in females. Overall mortality was 23% at 6 months and 34% at 1 year. In addition to age, gender, and dependency, main risk factors for mortality were recent hospitalization (first 4 months after entry into the facility), and the burden of comorbidities (subsequent follow-up period). The most represented causes of mortality were similar in the first and in the subsequent period after admission: cardio-cerebrovascular diseases, neurodegenerative diseases, respiratory diseases, and infections.

DISCUSSION

The first months after admission represent a period at high risk of mortality, especially for patients with a recent hospitalization. Causes reported in death certificates suggest mainly an acute deterioration of pre-existing chronic conditions.

CONCLUSION

Health care plans should be personalized for newly admitted vulnerable patients. Palliative care needs should be recognized and addressed for high-risk non-cancer patients.

Direct cost of Parkinson's disease in a health system with high judicialization: evidence from Colombia

Objective: To estimate all-claims-all-conditions expenditures paid for by health plans for patients suffering from Parkinson´s disease (PD). Methods: Using administrative claims data from two health maintenance organizations for 2014 and 2015 in Colombia, we identified 2,917 patients with PD by applying an algorithm that uses International Statistical Classification of Diseases and Related Health Problems and Anatomical Therapeutic Chemical Classification System codes. Descriptive statistics were applied to compute unadjusted all-cause median costs. A generalized linear model was used to estimate adjusted and attributable direct costs of advanced PD. Results: Approximately 30% of the all-cause direct costs were associated with technologies not included in universal health coverage benefit packages. In 2015, the annual median interquartile range per patient all-cause direct costs to insurers was USD1,576 (605-3,617). About 16% of patients had advanced PD. Regression analysis estimated that additional costs attributable to advanced PD was USD3,416 (p = 0.000). Multimorbidity was highly prevalent, and 96% of PD patients had at least one other chronic condition. Conclusions: In the context of high judicialization, patients suffering from PD must increasingly use the judicial system to access treatment. To promote more equitable and efficient access benefit packages, developing countries must consider more thoroughly the needs of these patients.

Prevalence of chronic liver disease among young/middle-aged adults in Northern Italy: role of hepatitis B and hepatitis C virus infection by age, sex, ethnicity

Background

Sparse population-based data are available on the prevalence and etiology of chronic liver disease (CLD) in Italy. The study aims to assess the role of hepatitis B virus (HBV) and hepatitis C virus (HCV) infection in CLD according to age, gender and ethnicity.

Methods

Clinically diagnosed CLD in the general population aged 20–59 years in the Veneto Region (North-Eastern Italy) were identified through the Adjusted Clinical Groups System, by record linkage of the archive of subjects enrolled in the Regional Health System with Hospital Discharge Records, Emergency Room visits, Chronic disease registry for copayment exemptions, and the Home care database. Age-standardized prevalence rates (PR) were computed in Italians and immigrants, based on country of citizenship.

Results

Overall 22,934 subjects affected by CLD in 2016 were retrieved, 21% related to HBV and 43% to HCV infection. The prevalence of HCV-related CLD was higher in males, peaking at 50–54 years (males = 11/1000; females = 4/1000). The PR of HBV-related CLD was almost negligible in the Italian population (1/1000), and higher among immigrants, especially from East Asia (males = 17/1000; females = 11/1000) and Sub-Saharan Africa (males = 13/1000; females = 10/1000).

Conclusion

Specific population sub-groups identified by age, gender, and ethnicity, were demonstrated to be at increased risk, and these trends are in line with global epidemiological patterns of viral hepatitis.

Impactibility Model for Population Health Management in High-Cost Elderly Heart Failure Patients: A Capture Method Using the ACG System

The aim of the present study is to use the ACG (Adjusted Clinical Groups) System to create an impactibility model by identifying homogeneous clinical subgroups of patients with high risk of an adverse health outcome in a population of heart failure patients with complex health care needs (PCHCN). This method will allow policy makers to target and prioritize services for the highest risk PCHCN in the context of limited health care resources, by identifying relatively homogeneous groups of patients with similar comorbidities. Subjects classified in 2012 as PCHCN in a local health unit by the ACG System were linked with hospital discharge records in 2013. The authors applied the Apriori algorithm to identify the most common sets of the most predictive diseases for the following outcomes of interest: at least 1 admission and at least 1 preventable admission in the year. Predictive performance for the former outcome was compared between the impactability model with the available ACG's individual risk score. The Apriori algorithm also was applied to predict the latter outcome as an example of an event that a policy maker would be able to prevent. Evidence showed no statistically significant difference between the 2 methods. The present model also displayed evidence of good calibration. The Apriori algorithm was applied as an impactibility model, built based on the ACG System, that allowed the authors to obtain an "ACG-based group risk score" and use it to identify clinically homogeneous subgroups of PCHCN. This will help policy makers develop "tool kits" for homogeneous groups of patients that improve health outcomes.

Effectiveness of a community care management program for multimorbid elderly patients with heart failure in the Veneto Region

BACKGROUND

The rapidly growing population of elderly subjects with multimorbidity is at risk of receiving fragmented and uncoordinated care, and have frequent hospitalizations and emergency room (ER) visits.

AIMS

The study aims to describe the impact of a care management program (CMP) developed in the Veneto region (Northeastern Italy) for patients affected by chronic heart failure (CHF) and multimorbidity.

METHODS

The CMP was provided to 330 patients > 65 years suffering from CHF and multimorbidity. They were compared to a propensity score matched reference group who received usual care. The intervention was provided by care manager nurses and General Practitioners working in the community. The quality of care from the patients' perspective was assessed by means of the Patient Assessment of Chronic Illness Care (PACIC). The effectiveness of the CMP has been evaluated comparing time changes in hospital admissions in the medical area and ER visits between the intervention and the reference group.

RESULTS

The median PACIC overall score was 4 out of 5. The intervention group showed a reduction over time by 39% in hospitalization rates and by 33% in ER visits. The recourse to hospital care and ER did not change in the reference group.

DISCUSSION

The current results indicate that a CMP can reduce Emergency Room visits and hospital admissions for elderly patients with CHF and multimorbidity.

CONCLUSIONS

The CMP by emphasizing prevention, self-management, continuity and coordination of care, is beneficial among older community-dwelling multimorbid persons as compared to usual care.

Changing the Approach to Anticoagulant Therapy in Older Patients with Multimorbidity Using a Precision Medicine Approach

The ageing of the world population has resulted in an increase in the number of older patients with multimorbid conditions receiving multiple therapies. This emerging clinical scenario poses new challenges, which are mostly related to the increased incidence of adverse effects. This translates into poor clinical care, reduced cost-effectiveness of drug therapies, and social isolation of multimorbid patients due to reduced autonomy. A strategy to address these emerging challenges could involve the personalization of therapies based on the clinical, molecular, and genetic characterization of multimorbid patients. Anticoagulation therapy is a feasible model to implement personalized medicine since it generally involves older multimorbid patients receiving multiple drugs. In this study, in patients with atrial fibrillation, the use of the new generation of anticoagulation therapy, i.e., direct oral anti-coagulants (DOACs), is based on a preliminary assessment of the molecular targets of DOACS and any possible drug⁻drug interactions. Then, the genetic polymorphism of enzymes metabolizing DOACs is studied. After DOAC prescription, its circulating levels are measured. Clinical data are being collected to assess whether this personalized approach improves the safety and efficacy profiles of anticoagulation therapy using DOACs, thereby reducing the costs of healthcare for ageing multimorbid patients.