C Quercioli

Importance of sociodemographic and morbidity aspects in measuring health-related quality of life: performances of three tools

BackgroundSince health-related quality of life (HRQL) measures are numerous, comparisons have been suggested.AimTo compare three HRQL measures: SF6D, HUI3 and EQ5D.MethodsThree questionnaires (SF36, HUI3, EQ5D) were administered to 1,011 patients attending 16 general practices in two Italian cities. Information about patients’ gender, age, education, marital status, smoking, body mass index (BMI) and chronic diseases (hypertension, diabetes, cardiovascular and musculoskeletal diseases) were also collected. Questionnaires scores were calculated using the appropriate algorithms; in particular SF6D scores were obtained from SF36 items. Agreement and correlation between questionnaires scores were investigated using Bland and Altman method and Spearman coefficient. The influence of socio-demographic and morbidity indicators on scores was analysed using the nonparametric quantile regression.ResultsThe Spearman coefficient was about 0.6 for all questionnaires. The 95% limits of agreement of the scores were approximately from −0.5 to 0.3 except for SF6D and EQ5D when they were from −0.4 to 0.2. The measures were influenced by socio-demographic and clinical variables in a similar way, especially SF6D (the index obtained from SF36) and EQ5D, which appeared to be influenced by the same pattern of factors, including gender, chronic diseases, smoking and BMI.ConclusionsOverall, the agreement between questionnaires scores was quite low, whilst the correlation level was good. Questionnaire scores were influenced by socio-demographic and clinical variables in a similar way, especially SF6D and EQ5D. Therefore, the descriptive capacity of SF6D and EQ5D was found to be similar.

The effect of healthcare delivery privatisation on avoidable mortality: longitudinal cross-regional results from Italy, 1993–2003

Background During the 1990s, Italy privatised a significant portion of its healthcare delivery. The authors compared the effectiveness of private and public sector healthcare delivery in reducing avoidable mortality (deaths that should not occur in the presence of effective medical care). Methods The authors calculated the average rate of change in age-standardised avoidable mortality rates in 19 of Italys regions from 1993 to 2003. Multivariate regression models were used to analyse the relationship between rates of change in avoidable mortality and levels of spending on public versus private healthcare delivery, controlling for potential demographic and economic confounders. Results Greater spending on public delivery of health services corresponded to faster reductions in avoidable mortality rates. Each €100 additional public spending per capita on NHS delivery was independently associated with a 1.47% reduction in the rate of avoidable mortality (p=0.003). In contrast, spending on private sector services had no statistically significant effect on avoidable mortality rates (p=0.557). A higher percentage of spending on private sector delivery was associated with higher rates of avoidable mortality (p=0.002). The authors found that neither public nor private sector delivery spending was significantly associated with non-avoidable mortality rates, plausibly because non-avoidable mortality is insensitive to healthcare services. Conclusion Public spending was significantly associated with reductions in avoidable mortality rates over time, while greater private sector spending was not at the regional level in Italy.

Patient mobility for cardiac problems: a risk-adjusted analysis in Italy

Background The Italian National Health System was revised in the last 20 years, introducing new elements such as efficacy, efficiency and competitiveness. Devolution to regional authorities has created a quasi-market system where patients can choose the hospital in which to be treated. Patient mobility therefore becomes an indicator of perceived hospital quality and of financial flows between the regions of Italy. Previous studies analyzed patient mobility in general or by specific disease/diagnosis-related groups but there is a lack of research on the influence of severity of patient condition. The aim of the study was to describe patient mobility, crude and stratified by disease severity, in cardiac surgery units of three health areas (HAs) in Tuscany (Italy). Methods In this retrospective observational study, data was gathered from hospital discharge records obtained from the Tuscan Regional Health Agency, Italy. The three HAs (HA1, HA2, HA3) recorded 25,017 planned hospitalizations in cardiac surgery units in the period 2001–2007. Patients were stratified in four All Patient Refined Diagnosis Related Group (APR-DRG) severity levels. Gandy’s nomogram was used to describe how HAs met health care demand and their capacity to attract patients. Cuzick’s test was used to identify significant differences in time trends. Results Raw data showed that the HAs met their own local health care demand. Stratifying by APR-DRG severity, it emerged that capacity to meet local demand remained unchanged for zero-to-minor severity levels, but one HA was less able to meet demand for moderate severity levels or to attract patients from other HAs and Regions of Italy. In fact, HA3 showed a decrease in admissions of local residents. Conclusions The study highlights important differences between the three HAs that were only revealed by severity stratification: unlike HA3, HA1 and HA2 seemed able to deal with local demand, even after severity stratification. Planners and researchers can benefit from risk stratification data, which provides more elements for correct comparisons and interventions. In the context of patient mobility, the present study is a step in that direction.BackgroundThe Italian National Health System was revised in the last 20 years, introducing new elements such as efficacy, efficiency and competitiveness. Devolution to regional authorities has created a quasi-market system where patients can choose the hospital in which to be treated. Patient mobility therefore becomes an indicator of perceived hospital quality and of financial flows between the regions of Italy. Previous studies analyzed patient mobility in general or by specific disease/diagnosis-related groups but there is a lack of research on the influence of severity of patient condition. The aim of the study was to describe patient mobility, crude and stratified by disease severity, in cardiac surgery units of three health areas (HAs) in Tuscany (Italy).MethodsIn this retrospective observational study, data was gathered from hospital discharge records obtained from the Tuscan Regional Health Agency, Italy. The three HAs (HA1, HA2, HA3) recorded 25,017 planned hospitalizations in cardiac surgery units in the period 2001–2007. Patients were stratified in four All Patient Refined Diagnosis Related Group (APR-DRG) severity levels. Gandy’s nomogram was used to describe how HAs met health care demand and their capacity to attract patients. Cuzick’s test was used to identify significant differences in time trends.ResultsRaw data showed that the HAs met their own local health care demand. Stratifying by APR-DRG severity, it emerged that capacity to meet local demand remained unchanged for zero-to-minor severity levels, but one HA was less able to meet demand for moderate severity levels or to attract patients from other HAs and Regions of Italy. In fact, HA3 showed a decrease in admissions of local residents.ConclusionsThe study highlights important differences between the three HAs that were only revealed by severity stratification: unlike HA3, HA1 and HA2 seemed able to deal with local demand, even after severity stratification. Planners and researchers can benefit from risk stratification data, which provides more elements for correct comparisons and interventions. In the context of patient mobility, the present study is a step in that direction.

Is It Possible to Evaluate Addiction From Clinical Records? Testing a Retrospective Addiction Severity Evaluation Measure

Aim. To compare an addiction severity score estimated from clinical records to addiction severity index (ASI) scores. Methods. During April–May 2004, 31 patients treated in a therapeutic community in the Piedmont region (Italy) were interviewed using the ASI questionnaire and their clinical records were used to obtain severity scores in seven areas: physical health, occupational functioning, alcohol use, drug use, legal problems, family/social relationships, psychological health. Correlation, agreement, and discriminatory capacity of the clinical records score in correctly classifying persons with low or high severity were investigated using Spearman, Kappa coefficient, and receiver operating characteristics curves. Conclusions. Clinical records score showed good correlation, agreement, and discriminatory accuracy with respect to ASI scores, especially in the drug use and legal problems areas. Further research is suggested to study the use of the score in other settings.

Reported experience of patients with single or multiple chronic diseases: empirical evidence from Italy

BackgroundMore and more countries have been implementing chronic care programs, such as the Chronic Care Model (CCM) to manage non-acute conditions of diseases in a more effective and less expensive way. Often, these programs aim to provide care for single conditions instead of the sum of diseases. This paper analyzes the satisfaction and better management of single and multiple chronic patients with the core elements of chronic care programs in Siena, Italy. In addition, the paper also considers whether the CCM introduced in Siena has any influence on satisfaction and better self-management.MethodsSurvey data from patients with single chronic (N = 500) and multiple chronic diseases (N = 454), assisted by the Local Health Authority in Siena (Tuscany, Italy), were considered for the analysis. Variables on education, monitoring system, proactivity, relational continuity, model of care (CCM versus no CCM) and patient demographics were used to detect which strategies are associated with a higher patient-reported ability to better self-manage the disease and overall patient satisfaction. Logistic and ordinary logistic models were executed on data related to patients with both single and multiple chronic diseases.ResultsThe results showed that monitoring was the sole strategy associated with overall satisfaction and better self-management for both single and multiple chronic patients. Relational continuity also showed a significant positive association with better self-management perception for both patient groups, but had a positive association with patient satisfaction only for single chronic patients. Enrolment in the CCM was not associated with both overall satisfaction and better management for the two patient groups.ConclusionsStrategies that are significantly associated with satisfaction and perception of better disease self-management were the same for both single and multiple chronic patients. The delivery of care based on the Siena CCM does not seem to make a difference in the perception of better self-management and overall satisfaction for all the patients. Other concurrent strategies implemented by the regional government in Tuscany on primary care monitoring and health promotion could partially explain why CCM does not have a significant influence.

La valutazione dello stato di salute percepita: strumenti psicometrici ed econometrici

Introduzione : per la messa a punto di modelli decisionali in Sanita Pubblica appare sempre piu indispensabile collegare i tradizionali riscontri “oggettivi” (spesso insufficientemente sensibili perche molto dipendenti dal versante dell’offerta) della statistica sanitaria, alle attese/percezioni soggettive degli utenti ed alla valutazione del bene salute. Perseguendo la nostra ricerca dell’ “anello mancante” tra Epidemiologia, Sociologia ed Economia, abbiamo voluto saggiare le correlazioni tra uno strumento tipicamente psicometrico ed uno econometrico di valutazione soggettiva dello stato di salute. Obiettivo : confrontare profili e valori di salute ottenuti con uno strumento psicometrico (SF36) ed uno econometrico (Health Utility Index-HUI). Materiali e metodi: SF36 descrive lo stato di salute attraverso 8 scale: Salute Generale, Attivita Fisica, Ruolo Fisico, Ruolo Emotivo, Attivita Sociali, Dolore Fisico, Vitalita e Salute Mentale. L’HUI produce sia un profilo di salute con 8 scale (Vista, Udito, Parola, Cognitivita, Deambulazione, Uso delle mani, Emotivita e Dolore), sia uno score riassuntivo del livello di salute. I questionari SF36 e HUI sono stati somministrati a 98 studenti dell’Universita di Siena. I punteggi delle otto scale dei due questionari e lo score sono stati confrontanti mediante il Coefficiente di Spearman. Risultati : i punteggi raggiunti nelle 8 scale dell’HUI rientrano nel 95% dei casi nella fascia piu alta (0,9-1), mentre quelli dell’SF36 rientrano nella fascia 90-100 solo per il 36%. Piu discriminante sembra essere lo score (solo il 44% dei valori compresi nella fascia 0,9-1). La correlazione piu forte e quella tra scala Salute Generale e score (r=0,458). La scala Attivita Fisica e correlata con Deambulazione (r=0,382) e Dolore (0,312); Ruolo Fisico con Cognitivita (r=0,425), Deambulazione (r=0,332), Dolore (r=0,383) e score (r= 0,347); Ruolo Emotivo con Cognitivita (r=0,398); Attivita Sociali con Cognitivita (r=0,324); Vitalita con Cognitivita (r=0,382), Emotivita (r=0,432) e score (r=0,438); Salute Mentale con Cognitivita (r=0,426) e score (r=0,383). Conclusioni : l’HUI appare, alle risultanze preliminari, meno discriminante rispetto all’ SF36. Le scale dell’Area Fisica dei due strumenti sembrano correlare, cosi come quelle dell’Area Emotiva. La scala “Salute Generale” e correlata con lo score.

Profili di salute soggettivi e oggettivi: una combinazione vincente

Introduzione : nella valutazione prospettica dell’impegno assistenziale richiesto o retrospettiva del risultato di salute ottenuto, entrambi collegabili a meccanismi retributivi, diventa sempre piu importante usare sintetici descrittori di severita/complessita/outcome. In quest’ottica abbiamo studiato con strumenti oggettivi (Charlson Index Score-CSI) e soggettivi (SF36) lo stato di salute di pazienti non ospedalizzati. Obiettivo: confrontare e correlare i livelli di salute registrati con i due strumenti. Materiali e Metodi : il CSI e un indice che considera numero e severita delle copatologie. Il questionario SF36 studia lo stato di salute percepito attraverso 8 domini. Sono stati studiati 137 pazienti di un Medico di Medicina Generale, che ha fornito eta, sesso, livello di istruzione e stato civile dei pazienti. E stato creato un modello di regressione in cui il punteggio del CSI costituiva la variabile dipendente e le quattro scale dell’SF36 che sono risultate correlate con il CSI le variabili indipendenti. Risultati: e stata identificata correlazione tra i punteggi del CSI e le scale Salute Generale (SG) (Coefficiente di Spearman 0,38 p‹0,001), Attivita Fisica (AF) (C.S. 0,35 p‹0,001), Ruolo Fisico (RF) (C.S. 0,37 p‹0,001), Ruolo Emotivo (RE) (C.S. 0,25 p=0,003). Aggiustando il CSI e le suddette 4 scale dell’SF 36 per “sesso”, “livello di istruzione” e “stato civile”, si e trovato che: (i) “stato civile” influenza l’associazione tra RF e CSI (crude O.R. 1,71, p‹0,001; O.R. coniugati 1,47 p= 0,025; O.R. non coniugati 3,05 p‹ 0,001) e SG e CSI (crude O.R. 1,76 p‹0,001; O.R. stato civile 1,61 p=0,006); (ii) “livello di istruzione” influenza l’associazione tra AF e CSI (crude O.R. 1,88 p‹0,001; O.R. livello di istruzione 1,76 p=0,001) e SG e CSI (crude O.R. 1,76 p‹0,001; O.R. elevata istruzione 1,22 p=0,33; O.R. scarsa istruzione 2,69 p‹0,001). Conclusioni : la correlazione tra i punteggi del CSI e le scale dell’SF36 (in particolare quelle relative all’area fisica) consente di ipotizzare un utilizzo integrato dei due strumenti e conferma l’affidabilita delle percezioni dei pazienti nell’ ”oggettivare” la propria salute.