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.

Multimorbidity and Hospital Admissions in High-Need, High-Cost Elderly Patients.

Objective: The aim was to clarify which pairs or clusters of diseases predict the hospital-related events and death in a population of patients with complex health care needs (PCHCN). Method: Subjects classified in 2012 as PCHCN in a local health unit by ACG® (Adjusted Clinical Groups) System were linked with hospital discharge records in 2013 to identify those who experienced any of a series of hospital admission events and death. Number of comorbidities, comorbidities dyads, and latent classes were used as exposure variable. Regression analyses were applied to examine the associations between dependent and exposure variables. Results: Besides the fact that larger number of chronic conditions is associated with higher odds of hospital admission or death, we showed that certain dyads and classes of diseases have a particularly strong association with these outcomes. Discussion: Unlike morbidity counts, analyzing morbidity clusters and dyads reveals which combinations of morbidities are associated with the highest hospitalization rates or death.

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.

Multimorbidity patterns in high-need, high-cost elderly patients.

INTRODUCTION: Patients with complex health care needs (PCHCN) are individuals who require numerous, costly care services and have been shown to place a heavy burden on health care resources. It has been argued that an important issue in providing value-based primary care concerns how to identify groups of patients with similar needs (who pose similar challenges) so that care teams and care delivery processes can be tailored to each patient subgroup. Our study aims to describe the most common chronic conditions and their combinations in a cohort of elderly PCHCN. METHODS: We focused on a cohort of PCHCN residing in an area served by a local public health unit (the "Azienda ULSS4-Veneto") and belonging to Resource Utilization Bands 4 and 5 according to the ACG System. For each patient we extracted Expanded Diagnosis Clusters, and combined them with information available from Rx-MGs diagnoses. For the present work we focused on 15 diseases/disorders, analyzing their combinations as dyads and triads. Latent class analysis was used to elucidate the patterns of the morbidities considered in the PCHCN. RESULTS: Five disease clusters were identified: one concerned metabolic-ischemic heart diseases; one was labelled as neurological and mental disorders; one mainly comprised cardiac diseases such as congestive heart failure and atrial fibrillation; one was largely associated with respiratory conditions; and one involved neoplasms. CONCLUSIONS: Our study showed specific common associations between certain chronic diseases, shedding light on the patterns of multimorbidity often seen in PCHCN. Studying these patterns in more depth may help to better organize the intervention needed to deal with these patients.

Out-of-hours primary care services: demands and patient referral patterns in a Veneto region (Italy) Local Health Authority.

PURPOSE: The aim of this study was to describe the characteristics of patients admitted to an out-of-hours (OOH) service and to analyze the related outputs. SETTING: A retrospective population-based cohort study was conducted by analyzing an electronic database recording 23,980 OOH service contacts in 2011 at a Local Health Authority in the Veneto Region (North-East Italy). METHOD: A multinomial logistic regression was used to compare the characteristics of contacts handled by the OOH physicians with cases referred to other services. RESULTS: OOH service contact rates were higher for the oldest and youngest age groups and for females rather than males. More than half of the contacts concerned patients who were seen by a OOH physician. More than one in three contacts related problems managed over the phone; only ≈10% of the patients were referred to other services. Many factors, including demographic variables, process-logistic variables and clinical characteristics of the contact, were associated with the decision to visit the patient's home (rather than provide telephone advice alone), or to refer patients to an ED or to a specialist. Our study demonstrated, even after adjusting, certain OOH physicians were more likely than their colleagues to refer a patient to an ED. CONCLUSION: Our study shows that OOH services meet composite and variously expressed demands. The determining factors associated with cases referred to other health care services should be considered when designing clinical pathways in order to ensure a continuity of care. The unwarranted variability in OOH physicians' performance needs to be addressed.

What determines frequent attendance at out-of-hours primary care services?

BACKGROUND: A detailed description of the characteristics of frequent attenders (FAs) at primary care services is needed to devise measures to contain the phenomenon. The aim of this population-registry-based research was to sketch an overall picture of the determinants of frequent attendance at out-of-hours (OOH) services, considering patients' clinical conditions and socio-demographic features, and whether the way patients' genaral practitioners (GPs) were organized influenced their likelihood of being FAs. METHODS: This study was a retrospective cohort study on electronic population-based records. The dataset included all OOH primary care service contacts from 1 January to 31 December 2011, linked with the mortality registry and with patients' exemption from health care charges. A FA was defined as a patient who contacted the service three or more times in 12 months. A logistic regression model was constructed to identify independent variables associated with this outcome. RESULTS: Multivariate analysis showed that not only frailty and clinical variables such as psychiatric disease are associated with FA status, but also socio-demographic variables such as sex, age and income level. Alongside other environmental factors, the GP's gender and mode of collaboration in the provision of health services were also associated with OOH FA. CONCLUSION: Our study demonstrates that the determinants of OOH FA include not only patients' clinical conditions, but also several socio-economic characteristics (including income level) and their GPs' organizational format.

[Risk factors for one year hospitalization and death of 615 home care patients with multidimensional assessment]. / Fattori di rischio per i'ospedalizzazione ed il decesso ad un anno in 615 pazienti assistiti in cure domiciliari sottoposti a valutazione multidimensionale.

INTRODUCTION: The District care activities are often presented as number of patients, interventions or home visits. A better description should render more visible the persons and their clinical problems whose outcomes should be monitored. AIM: To prospectically monitor the outcomes in a sample of home care patients followed for one year. METHODS: Six hundred sixty two home care patients of two Local Health Units of Veneto Region with at least two nurses visits per month had a multidimensional assessment and were followed for one year. RESULTS: At the end of follow-up 32% of patients had died, 3.9% had been admitted to a Nursing home; 41.9% had at least one hospital admission and for 49.7% the number of nursing visits was increased. Closeness to death and inadequate family support were independently associated to an increased risk of hospital admission, while patients with severe cognitive impairment tend to be admitted to hospital less frequently. Of the 216 bedridden patients those with inadequate family support are at higher risk for death and hospital admissions. CONCLUSIONS: Home care informative systems allow to assess and monitor the more severe patients thus producing information useful for the continuous improvement of caring processes.

[Diabetes prevalence estimated using a standard algorithm based on electronic health data in various areas of Italy]. / Stima della prevalenza di diabete basata su dati sanitari correnti mediante un algoritmo comune in differenti aree italiane.

AIMS: the goal of this study was to estimate the prevalence of diabetes through record linkage of various data sources in four Italian areas. SETTING: Aulss 12 Veneziana, Aulss 4 Alto vicentino, Torino, ASL10 of Firenze. PARTICIPANTS: all 2002 to 2004 residents in the four areas (n = 2,123,913 on 30th June 2003). MAIN OUTCOME: crude prevalence by age and gender and standardized prevalence by gender. METHODS: we used three different data sources. The first was the set of files of all persons discharged from hospitals with a primary or secondary diagnosis of diabetes (ICD-9-CM code 250*) in the year of interest or in the four previous years. The second data source was the set of files of all prescriptions of antidiabetic drugs (ATC code: A10A* and A10B*) prescribed in the year of interest; we considered as persons with diabetes only those who had at least two prescriptions of antidiabetic drugs at two different times. The third source was the set of files of all subjects who obtained exemption from payment of drugs or laboratory testing due to a diagnosis of diabetes mellitus in the year of interest or in the 3 previous years. All data sources were matched by a deterministic linkage procedure. We defined as "prevalent case" those persons who were present in at least one of the three data sources. We compared the estimated prevalence in the four different areas. RESULTS: in 2003, the prevalence of diabetes in the four areas ranged from 3.93% to 5.55% among men, and from 3.55% to 4.52% among women. After adjustment for age, differences among men were reduced and were no longer present among women. Prevalence is higher among the elderly and among men. CONCLUSIONS: using routinely collected data we were able to identify large cohorts of persons with known diabetes and to estimate the prevalence of the disease, which was shown to be highly homogeneous among participating centres, and similar to that reported in other studies conducted in Italy with more costly and time consuming methods.