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Essays in Applied Health Economics

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Essays in Applied Health Economics UNIVERSITA' DEGLI STUDI DI ROMA \TOR VERGATA" FACOLTA' DI ECONOMIA Dottorato di ricerca in Econometria ed Economia Empirica XX ciclo Essays in Applied Health Economics Claudio Rossetti Docente guida: prof. Franco Peracchi Coordinatore: prof. Franco Peracchi Abstract Chapter 1 focuses on the issue of reporting bias in self-rated health. This chapter shows that gender and regional di®erences in self-rated health in Europe are only partly explained by di®erences in the prevalence of the various chronic conditions. However, a non-negligible part of these di®erences is due to other causes, which may include di®erences in reporting own health. The tool of \anchoring vignettes" is employed to understand whether and how women and men living in di®erent regions di®erently report levels in a number of health components or domains. The analysis is based on Release 2 of the ¯rst (2004) wave of the Survey of Health, Ageing and Retirement in Europe (SHARE). This survey is ideal for the purpose because it contains information on subjective measures of health (such as self-rated health) and more objective measures (such as hospitalization and interviewer-measured grip strength), as well as detailed information on chronic health conditions. Release 2 of the data also includes the use of vignettes in self-administered questionnaires given to a randomly selected subsample of respondents. Vignettes are found to help identifying gender and regional di®erences in response scales. After correcting for these di®erences, both gender and regional variation in reported health is substantially reduced, although not entirely eliminated. The results suggest that di®erences in response styles should be taken into account when using self-assessment of health in socio-economic studies. Failing to do so may lead to misleading conclusions. Focusing on a speci¯c chronic condition, hypertension, Chapter 2 studies the relationship between medical com- pliance and health outcomes (hospitalization and mortality rates) using a large panel of patients residing in a local health authority in Italy. These data allow to follow individual patients through all their accesses to public health care services until they either die or leave the local health authority. The results show that health outcomes clearly improve when patients become more compliant to drug therapy. At the same time, it is possible to infer valuable information on the role that drug co-payment can have on compliance, and as a consequence on health outcomes, by exploiting the presence of two natural experiments during the period of analysis. The results show that drug co-payment has a strong e®ect on compliance, and that this e®ect is immediate. Chapter 3 improves the analysis of the relationship between health and medical care provided in Chapter 2. In fact, looking at the raw correlation between medical care and health cannot be expected to give the right answer, because of simultaneity through the unobservable components of deterioration. In this chapter, it is used a dataset where very detailed information about medical drug use, hospitalization, and mortality, is collected over time for a sample of individuals su®ering from hypertension, a chronic asymptomatic pathology a®ecting a large share of the adult population. All those variables are expected to be strongly dependent on each other. For analysing the amount of information embedded in such variables, a dynamic factor model is proposed, where medical treatments and mortality may all in principle be driven by latent individual stock of health. Dynamics is introduced by including the e®ects of lagged treatment on latent health. The model is estimated by Maximum Simulated Likelihood (MSL). In line with ¯ndings provided so far in the literature, the results indicate that better health is associated to lower medical treatments. In addition, lagged medical drug use is found to have positive e®ects on current health. This is consistent with the fact that not taking the medication today may result in poorer health tomorrow. Nonetheless, taking more pills than needed cannot improve health. These ¯ndings have important policy implications. In fact, the results suggest that policies aimed at improving awareness of hypertensive diseases and the importance of the treatment of high blood pressure may help reduce cardiovascular risks, and consequent hospitalization and mortality. This is expected to have positive implications both for the large share of adult population su®ering from hypertension and for the National Health Systems themselves. Keywords: Self-rated health, health domains, anchoring vignettes, reporting bias, health policy reforms, co- payment, dynamic panel data models, factor models, simulated likelihood, latent variable models JEL codes: C35, C81, I12, J14, D12, C33 Abstract Il Capitolo 1 focalizza l'attenzione sui problemi di \reporting bias" legati all'indicatore di salute auto-riportato. Questo capitolo mostra che in Europa di®erenze di genere e di®erenze regionali possono solo parzialmente essere spiegate dalle di®erenze nella prevalenza delle varie condizioni croniche. Eppure, una parte non trascurabile di queste di®erenze `edovuta ad altre cause, che possono includere di®erenze nel modo in cui lo stato di salute viene riportato. Lo strumento delle \anchoring vignettes" `eutilizzato per comprendere se e come le donne e gli uomini che vivono in diverse regioni d'Europa riportano di®erentemente il livello di salute relativo a vari \domini". L'analisi `ebasata sulla seconda Release della prima (2004) wave della Survey of Health, Ageing and Retirement in Europe (SHARE). Questa indagine `eideale per lo scopo in quanto contiene informazioni circa misure soggettive dello stato di salute e misure pi`u oggettive (come ospedalizzazione e \grip strength"), come anche informazioni dettagliate circa condizioni croniche. La seconda Release dei dati contiene anche l'uso di \vignettes" in questionari assegnati ad un campione casuale di rispondenti. Le \vignettes" risultano essere utili per identi¯care di®erenze regionali e di genere nelle \response scales". Dopo aver corretto queste di®erenze, le variazioni regionali e di genere nelle stato di salute riportato risultano entrambe ridotte, seppure non del tutto eliminate. I risultati suggeriscono che le di®erenze nelle \response styles" devono essere prese in considerazione quando si utilizza lo salute auto-riportato in studi socio-economici. Non tenerne conto pu`ocondurre a risultati fuorvianti. Focalizzando l'attenzione su una speci¯ca condizione cronica, l'ipertensione, il Capitolo 2 studia la relazione tra compliance medica e outcome sanitari (ospedalizzazione e mortalit`a)utilizzando un panel di pazienti che risiedono in un’Autorit`aSanitaria Locale italiana. Questi dati consentono di seguire i pazienti attraverso tutti i loro accessi ai servizi sanitari pubblici. I risultati mostrano che gli outcome sanitari migliorano decisamente quando i pazienti sono pi`u\compliant" alla terapia. Inoltre, `epossibile inferire importanti informazioni circa il ruolo che il co-payment ha sulla compliance, e di conseguenza sugli outcome sanitari, esplorando due esperimenti naturali veri¯catisi durante il periodo qui analizzato. I risultati mostrano che il co-payment ha forti e®etti sulla compliance, e che questi e®etti sono immediati. Il Capitolo 3 estende l'analisi della relazione tra salute e trattamento sanitario fornita nel Capitolo 2. Infatti, considerando la semplice correlazione tra salute e trattamento sanitario non necessariamente fornisce la risposta adeguata, a causa della simultaneit`anelle componenti inosservate del deterioramento della salute. In questo capitolo, si utilizza un dataset in cui informazioni molto dettagliate circa il consumo farmaceutico, l'ospedalizzazione e la mortalit`asono collezionate nel tempo per un campione di individui a®etti da ipertensione. L'ipertensione `euna condizione cronica e asintomatica di cui so®re una larga parte della popolazione adulta. Tutte queste variabili sono fortemente dipendenti l'una dall'altra. Per analizzare l'informazione contenuta in tali variabili, viene proposto l'impiego di un modello a fattori dinamico, in cui il trattamento medico e la mortalit`asiano in principio tutti guidati dallo stato di salute latente. La dinamica viene introdotta nel modello includendo l'e®etto del trattamento medico passato sullo stato di salute corrente. Il modello `estimato tramite Massima Verosimiglianza Simulata. Coerentemente con i risultati presenti ¯nora in letteratura, i risultati indicano che una migliore condizione di salute `eassociata con un minore trattamento medico. Inoltre, il consumo farmaceutico nel periodo precedente ha e®etti positivi sullo stato di salute corrente. Questo `econsistente con il fatto che non seguire la terapia medica oggi pu`orisultare in una peggiore condizione di salute domani. Nonostante questo, assumere pi`upastiglie di quanto necessario non migliora ulteriormente la stato di salute. Questi risultati hanno importanti implicazioni in termini di policy. Infatti, i risultati suggeriscono che politiche mirate ad aumentare la consapevolezza delle malattie legate all'ipertensione e l'importanza della cura dell'alta pressione possono aiutare non poco a ridurre i rischi cardiovascolari, e la conseguente ospedalizzazione e mortalit`a. Ci si attende che questo abbia implicazioni positive sia per la larga parte di popolazione adulta a®etta da ipertensione sia per gli stessi Servizi Sanitari Nazionali. Contents 1 Chapter 1 Gender and regional di®erences in self-rated health in Europe 6 1.1 Introduction . 7 1.2 Data and descriptive statistics . 9 1.2.1 Data . 9 1.2.2 Variables . 10 1.2.3 Descriptive statistics and preliminary evidence . 11 1.3 SRH and chronic conditions . 12 1.3.1 Model speci¯cation and estimation . 12 1.3.2 Pooled data . 13 1.3.3 Gender di®erences . 14 1.3.4 Regional di®erences . 14 1.4 Anchoring vignettes . 15 1.4.1 A simple example . 16 1.4.2 Health on six domains and vignettes . 16 1.4.3 The statistical model . 17 1.4.4 Model estimation . 18 1.4.5 Decomposition of gender and regional di®erences . 20 1.5 Conclusions . 21 2 Chapter 2 Medical drug compliance, co-payment and health outcomes 40 2.1 Introduction .
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