Implantable cardioverter-defibrillators and cardiac resynchronization therapy-defibrillators (ICD/CRT-Ds) are evidence-based preventative treatments for many patients with heart failure (HF), yet large numbers of eligible patients remain untreated. It is uncertain if localities with more frequent ICD/CRT-D use have had better rates of HF survival.
To determine if US Hospital Referral Regions (HRRs) with larger increases in the rate of ICD/CRT-D utilization during 2002 to 2007 also had commensurate increases in HF survival.
Medicare beneficiaries age 66 to 80 nonelectively hospitalized for HF from 2002 to 2007.
Each HRR's annual ICD/CRT-D rate was estimated from the cohort's Medicare procedure claims. Survival duration was determined from Medicare mortality records. HRR-year-level panel regression models were estimated to assess whether an HRR's ICD/CRT-D rate predicted HF survival, adjusting for baseline differences in survival across HRRs and secular trends.
A total of 883,002 HF patients were propensity-score matched within HRR across 2002 to 2007. Across HRRs, growth in ICD/CRT-D use among such patients varied from 1 to 12 percentage points. Regression models indicated that a 1 percentage point increase in an HRR's ICD/CRT-D utilization among hospitalized HF patients was associated with an increase in 1-year survival of 0.12% [95% confidence interval (CI), 0.03%-0.21%, P=0.009] and with a 0.26% increase in HF survival at 2 years (95% CI, 0.14%-0.37%, P<0.001).
Localities with greater increases in ICD/CRT-D utilization from 2002 to 2007 also had greater improvements in HF survival. Areas with persistently low ICD/CRT-D use may be good targets for programs designed to increase the evidence-based use of defibrillators.
"However, it is noteworthy that these two studies led to similar conclusions with regard to ICD costs and benefits. More recently, another report derived from Medicare data showed how geographical areas in which the prophylactic use of ICDs increased over time showed greater improvements in survival, stressing the need for programs designed to increase the evidence-based use of ICDs . "
[Show abstract][Hide abstract] ABSTRACT: Background
A plethora of clinical studies have assessed the benefits of implantable cardioverter defibrillators (ICDs) and supported their use in clinical practice. However, evidence on the safety and efficacy of ICDs appears insufficient to support expansion of their use in clinical practice, and more information on their impact in real life settings is warranted. This paper aims to investigate the impact of ICDs using a large administrative dataset reflecting actual clinical practice.
Data were obtained from the hospital discharge database of the Friuli Venezia Giulia region in Italy containing patient-level information on 169,488 cases. Data on mortality outside hospital were obtained from regional sources. Exact matching method was used to estimate the outcomes associated with ICDs: mortality, length of stay, re-hospitalization and regional expenditure. The method was applied in two steps. First, patients with ICDs were matched with those without using the following: age class (by 5 years), gender, year of admission, type of admission (day hospital vs. ordinary) and primary diagnosis. In the second step, matching included also Charlson Comorbidities Index. Exact matching average treatment effect on the treated (ATT) was used as a main measure of impact.
Compared with matched controls, treatment with ICDs was associated with lower mortality (absolute risk reduction 10.6% at 1 year and 8.3% at 2 and 8.4% at 3 years, p < 0.001 and hazard ratio 0.80, p < 0.001), greater regional expenditure at index hospitalization (ATT: €9459.64, p < 0.001) and during follow up (ATT: €1707.29, p < 0.001) and higher re-hospitalization rate (ATT: 0.53, p < 0.001). No significant difference was found for length of stay (9.07 vs. 8.86 days). The results were maintained after more restrictive matching was applied.
Assessing the impact of innovative, expensive medical technologies on the basis of real world data is warranted, especially when there are barriers to implementation. Hospital administrative datasets can be of great value when a technology such as the ICD is implemented in a relatively small sample of patients, to allow use of exact matching techniques.
BMC Health Services Research 03/2013; 13(1):100. DOI:10.1186/1472-6963-13-100 · 1.71 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: BACKGROUND: While understanding geography's role in healthcare has been an area of research for over 40 years, the application of geography-based analyses to prescription medication use is limited. The body of literature was reviewed to assess the current state of such studies to demonstrate the scale and scope of projects in order to highlight potential research opportunities. OBJECTIVE: To review systematically how researchers have applied geography-based analyses to medication use data. METHODS: Empiric, English language research articles were identified through PubMed and bibliographies. Original research articles were independently reviewed as to the medications or classes studied, data sources, measures of medication exposure, geographic units of analysis, geospatial measures, and statistical approaches. RESULTS: From 145 publications matching key search terms, forty publications met the inclusion criteria. Cardiovascular and psychotropic classes accounted for the largest proportion of studies. Prescription drug claims were the primary source, and medication exposure was frequently captured as period prevalence. Medication exposure was documented across a variety of geopolitical units such as countries, provinces, regions, states, and postal codes. Most results were descriptive and formal statistical modeling capitalizing on geospatial techniques was rare. CONCLUSION: Despite the extensive research on small area variation analysis in healthcare, there are a limited number of studies that have examined geographic variation in medication use. Clearly, there is opportunity to collaborate with geographers and GIS professionals to harness the power of GIS technologies and to strengthen future medication studies by applying more robust geospatial statistical methods.
Research in Social and Administrative Pharmacy 01/2013; 9(6). DOI:10.1016/j.sapharm.2012.11.006 · 2.35 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background: Consensus guidelines define indications for cardiac resynchronization therapy (CRT), but the variability in implant rates in ‘real world’ clinical practice, as well as the relationship with the epidemiology of heart failure are not defined. Methods and results: In Emilia-Romagna, an Italian region with around 4.4 million inhabitants, a registry was instituted to collect data on implanted devices for CRT, with (CRT-D) or without defibrillation (CRT-P) capabilities. Data from all consecutive patients resident in this region who underwent a first implant of a CRT device in years 2006–2010 were collected and standardized (considering each of the nine provinces of the region). The number of CRT implants increased progressively, with a 71% increase in 2010 compared to 2006. Between 84 and 90% of implants were with CRT-D devices. The variability in standardized implant rates among the provinces was substantial and the ratio between the provinces with the highest and the lowest implant rates was always greater than 2. Considering prevalent cases of heart failure in the period 2006–2010, the proportion of patients implanted with CRT per year ranged between 0.23 and 0.30%. Conclusions: The application in ‘real world’ clinical practice of CRT in heart failure is quite heterogeneous, with substantial variability even among areas belonging to the same region, with the need to make the access to this treatment more equitable. Despite the increased use of CRT, its overall rate of adoption is low, if a population of prevalent heart failure patients is selected on the basis of administrative data on hospitalizations.
Journal of Cardiovascular Medicine 02/2014; 15(2):147-154. DOI:10.2459/JCM.0b013e3283638d90 · 1.51 Impact Factor
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