Health Econ Research Articles

On absolute socioeconomic health inequality comparisons.

This paper introduces a new graphical tool: the mean deviation concentration curve. Using a unified approach, we derive the associated dominance conditions that identify robust rankings of absolute socioeconomic health inequality for all indices obeying Bleichrodt and van Doorslaer's (J Health Econ 25:945-957, 2006) principle of income-related health transfer. We also derive dominance conditions that are compatible with other transfer principles available in the literature. To make the identification of all robust orderings implementable using survey data, we discuss statistical inference for these dominance tests. To illustrate the empirical relevance of the proposed approach, we compare joint distributions of income and health-related behavior in the United States.

The EQ-5D-5L Predicts Treatment Outcomes and Provides Added Value to the R-IPSS in Patients with MDS, CMML or AML Treated within the Austrian Azacitidine Registry - a Prospective Cohort Study By the AGMT Study Group

The EQ-5D-5L Predicts Treatment Outcomes and Provides Added Value to the R-IPSS in Patients with MDS, CMML or AML Treated within the Austrian Azacitidine Registry - a Prospective Cohort Study By the AGMT Study Group

Preference measurement in health using experiments

This contribution has three objectives. First, it seeks to justify the use of the economic criterion, “Provision of health care in accordance with the preferences of current and potential patients” for guiding decisions concerning the adoption of costly innovation in health. Next, it proposes the measurement of these preferences in the guise of willingness to pay (WTP) values through Discrete Choice Experiments (DCEs). Third, it purports to examine two popular arguments against accepting lay persons´ preferences, viz. that they are unwilling or unable to express preferences with regard to health and health care, and that their preferences are unstable, depending on the current state of health. Both of these arguments are refuted by the findings of four DCEs designed to measure WTP for attributes of health insurance and of the treatment of diabetes, respectively [Zweifel in J Regul Econ 29(3): 319–332, 2006; MacNeil Vrooman and Zweifel in Eur J Health Econ 12(1): 87–95, 2011; Sennhauser and Zweifel in: Jakovlijevic M (ed.), Health Economics and Policy Challenges in Global Emerging Markets. NOVA Publishers, Hauppauge NY, 2016].

Long-Term Results and Cost-Effectiveness of the Flagida-Lite Regimen in Elderly Patients with Acute Myeloid Leukemia or High-Risk Myelodysplastic Syndrome

▪INTRODUCTIONAcute Myeloid Leukemia (AML) and high risk Myelodisplastic Syndrome (MDS) have a higher incidence in older patients. Due to their age, comorbidity and unfavorable biology of the disease, intensive chemotherapy offers poor results. Hypomethylating agents and other alternative regimens are being tested but the best strategy is currently not well defined.OBJECTIVEUpdating the FLAGIDA-lite intermediate intensity chemotherapy scheme results (Am J Hematol. 2012 Jan;87(1):42-4). Rate of overall response (OR), overall survival (OS) and treatment-related mortality (TRM) were evaluated. An estimated cost approach and a review of the 5-azacytidine cost estimation was made.PATIENTS AND METHODSSeventy patients older than 65 years with AML or high risk MDS treated with the FLAGIDA-lite regimen in three Spanish centers between 2006 and 2016 were analyzed. Median age was 76 years (IQL 73-81) and patients´ characteristics are shown in table 1 . The regimen consisted of: Fludarabine (40mg/m2 daily, days 1-5, P.O), Citarabine (20 mg/m2 daily, days 1-5, sub-Q) and Idarrubicin (15 mg/m2 daily, days 1-3, P.O until 2014, or IV 10 mg/m2 daily, days 1-3 when oral formulation disappeared). G-CSF (300 µg/24h sub-Q, days -1 to 5) was added except when leukocytosis was greater than 100,000/µl. Treatment administration and subsequent follow-up were performed under hospitalization, home care or ambulatory regimen. We calculated the regimen costs.RESULTSToxicity and Treatment Related MortalityA total of 117 chemotherapy cycles were administered (80 as induction and 37 as consolidation).Sixty-one (76.2%) induction and 34 (91.9%) consolidation cycles were administered under ambulatory or home care regimen; in 21 (34.4%) and 8 (21.6%) of them, respectively, hospital admission was necessary, mainly due to infectious complications.Thirteen (18.6%) patients died after induction, 10 due to treatment-related complications and 4 due to disease progression. Early mortality at 8 weeks was 20.9%. Treatment-related mortality was higher in patients older than 80 years (30 vs 10%), as shown in figure 1.Overall Response and Overall SurvivalSixty patients received one induction cycle and 10 received 2. OR rate was 64.9% (49.1% CR, 8.8% CRi; 7% PR) and 35.1% of patients were refractory. Median time to CR was 36 days (26-51). Twenty-six patients who had reached CR/CRi received consolidation with the same regimen (35 cycles) and 6 patients were submitted to a related allogeneic hematopoietic stem-cell transplantation.With a median follow-up of 23.8 months (9-105) in alive patients, estimated OS at 2 years was 22.6 (±5.4%) in the whole series and 41.1% (±9.4%) in patients who reached CR/CRi, as shown in figure 2. Median OS in patients who reached CR/CRi was significantly higher than in non-responder patients (17.4 vs 2.9 months, p< 0,001).Cost estimationThe cost of one cycle of FLAGIDA-lite, in Spain, is 1825.18 euros, as shown in table 2 . The median number of cycles administered in our study was 2, so the global cost of treatment drugs was 3650.36 euros. The estimated cost in Spain of another non-intensive regimen with not higher or similar efficacy (5-azacitidine) according to literature is 3028.14 euros each cycle and a total cost of 18,168.84 euros (median number of 6 cycles) . ( Health Econ Rev. 2013 Dec 5;3(1):28).CONCLUSIONFLAGIDA-lite is an effective alternative regimen in elderly patients with AML and high risk MDS, with low treatment-related mortality in patients younger than 80 years (10%) and with the possibility of an ambulatory management. This treatment offers an overall response rate around 65%, and an estimated overall survival at two years around 41% in responder patients. Its cost is markedly lower than the cost of 5-azacytidine. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Determinants of attitude and intention towards private health insurance: a comparison of insured and uninsured young adults in Australia

BackgroundSince the introduction in 1984 of Australia’s publicly-funded universal healthcare system, Medicare, healthcare financing has relied on a mix of public and private sources to meet the needs of the population (Sowa et al., Appl Health Econ Health Policy 15:31–41, 2018). However, in recent years, there has been a decline in the number of Australians choosing to purchase private health insurance (PHI), particularly within the young adult age group with the proportion of insurance customers aged 20 to 29 falling from 10.3 to 9.4% between 2012 and 2017 (Sivey, The Conversation, 2017). Young adults are critical to private health insurance funding models as their involvement offsets the drawdown by older adults (Dalzell and Borys, ABC News, 2019). While this issue is widely reported in the Australian media, few empirical studies have explored the factors that enable or constrain young adults’ enrolment in PHI.MethodsTo address the scarcity of research about the motivational factors behind young adult decision-making, this study conducted a survey of 594 Australian young adults aged between 18 and 30 years. Within this age group, the survey sought an equal split of participants who were members and non-members of PHI schemes.ConclusionThe findings identified perceived value and trust in insurers as additional motivational factors alongside traditional measures of recognition of the problem and involvement in the problem. Differences between the insured and uninsured groups were identified which help to shape a more holistic understanding of the key motivational factors and barriers in relation to Australian young adults’ enrolment in PHI.

Health State Utility Valuation in Patients with Triple-Class-Exposed Relapsed and Refractory Multiple Myeloma Treated with the Bcma-Directed CAR T Cell Therapy, Idecabtagene Vicleucel (ide-cel, bb2121): Results from the Karmma Trial

Health State Utility Valuation in Patients with Triple-Class-Exposed Relapsed and Refractory Multiple Myeloma Treated with the Bcma-Directed CAR T Cell Therapy, Idecabtagene Vicleucel (ide-cel, bb2121): Results from the Karmma Trial

Socioeconomic inequalities in child malnutrition in Egypt

In this paper, we study the evolution of socioeconomic inequalities in child malnutrition in Egypt between 2000 and 2014. Unlike most of the literature, we go beyond the usual dichotomous framework of stunting incidence and adopt a continuous indicator approach of child stunting. We use Wagstaff (J Health Econ 21:627-641, 2002) health achievement index to measure health shortfall as indicator of the social impact of child stunting. In order to analyze the determinants of stunting shortfall, we derive the expression of the recentered influence function of the health shortfall index. We also use this result in a recentered influence function regression framework and perform a Oxaca-Blinder type of decomposition of the change in stunting shortfall during that period. We find that stunting shortfall did not change significantly during that period. However, the Oxaca-Blinder decomposition indicates that the endowment effect would have decreased significantly stunting shortfall between 2000 and 2014. Unfortunately, the adverse economic conditions implied a structural effect in the opposite direction.

Probiotics: Promise, Evidence, and Hope

Probiotics: Promise, Evidence, and Hope

Novel Approaches to Value Assessment Within the Cost-Effectiveness Framework

Novel Approaches to Value Assessment Within the Cost-Effectiveness Framework

Clostridioides difficile Infection in Chronic Kidney Disease/End-Stage Renal Disease.

Clostridioides difficile infection (CDI) is a major health-care burden and increasingly seen in patients with chronic kidney disease (CKD) and end-stage renal disease (ESRD). Increased antibiotic use, alteration in host defenses, and gastric acid suppression are some of the etiologies for increased risk of CDI in these populations. Patients with CKD/ESRD have a higher risk of initial episode, recurrence, and development of severe CDI than those without CKD or ESRD. Diagnosis and management of CDI in patients with CKD/ESRD are similar to that in the general population. The mortality, length of stay, and health-care costs are higher in patients with CDI and CKD/ESRD. Antimicrobial stewardship with reduction in antibiotic use along with infection-control measures such as contact isolation and hand hygiene with soap and water is essential in the control and prevention of CDI in patients with CKD/ESRD.

Comparison of Equity Preferences for Life Expectancy Gains: A Discrete Choice Experiment Among the Japanese and Korean General Public

Setting priorities for limited public resources has become a topic of heated discussion the world over. Assigning different weights for the health gains of different population groups allows for equity considerations in cost-effectiveness analysis. However, only a few empirical works have elicited the preferences of the general public. To compare the equity preferemce assigned by Japanese and Koreans. We conducted a Web-based survey in March 2013, including a discrete choice experiment, to elicit the equity preferences of the general public for the life expectancy gains of different population groups. We selected attributes and designed the experiment following Norman etal.'s study (Norman R, Hall J, Street D, Viney R. Efficiency and equity: a stated preference approach. Health Econ 2013;22:568-81). Accordingly, we analyzed preference for sex, smoking status, lifestyle, caring status, income, and age. The Japanese assigned a higher preference for males (P < 0.001), nonsmokers (P < 0.001), those with lower income (P < 0.001), and carers (P < 0 .001), and they assigned a lower preference for those with a life expectancy of 60 years (P = 0.002) and 75-year-olds (P < 0.001). Koreans have the same patterns of preference for lower income (P < 0.001), caring (P < 0.001), and smoking status (P = 0.026). However, they prefer both sexes (P = 0.331) and different age groups equally. In both countries, respondents tend to prefer groups with characteristics similar to their own. People from the two Asian developed countries, with universal health insurance, show different equity preferences. These may reflect the variations in cultural background and coverage of health care services.

Introduction to the Special Issue: Contributions to the History of Health Economics

Nowadays, health economics is a thriving sub-discipline of economics. The field has its own specialised journals, conferences, research centres and academic programmes. Both policy makers and the medical sector make use of the results of applied health economics research. Insights from health economics are helpful to analyse the market for health care, to find cost-effective ways to eradicate diseases, to predict the effects of lowering the price of medication, etc. The origins of health econ...

Trends in available beds per death in England

British Journal of Healthcare ManagementVol. 24, No. 7 Money MattersTrends in available beds per death in EnglandRodney JonesRodney JonesSearch for more papers by this authorRodney JonesPublished Online:2 Jul 2018https://doi.org/10.12968/bjhc.2018.24.7.358AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References Beeknoo N, Jones R. A simple method to forecast next years bed requirements: a pragmatic alternative to queuing theory. British Journal of Medicine and Medical Research 2016; 18(4): 1-20. https://doi.org/https://doi.org/10.9734/BJMMR/2016/29518 Crossref, Google ScholarBone A, Gomes B, Etkind S, et al.. What is the impact of population ageing on the future provision of end-of-life care? Population-based projections of place of death. Palliative Med 2018; 32(2): 329-336. https://doi.org/httpa://doi.org/10.1177/0269216317734435. Crossref, Google ScholarDepartment of Health. The National Beds Inquiry, 2001. http://webarchive.nationalarchives.gov.uk/+/http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/AnnualReports/Browsable/DH_4989760 (accessed 25 June 2018) Google ScholarDepartment of Health. The Wanless report: Securing good health for the whole population, February 2004. http://webarchive.nationalarchives.gov.uk/+/ http://www.dh.gov.uk/en/Publichealth/Healthinequalities/Healthinequalitiesguidancepublications/DH_066213 (accessed 25 June 2018) Google ScholarEuropean Health Information Gateway. Bed occupancy rate (%), acute hospitals only. 2018. https://gateway.euro.who.int/en/indicators/hfa_542-6210-bed-occupancy-rate-acute-care-hospitals-only/ (accessed 25 June 2018) Google ScholarFransham M, Dorling D. Have mortality improvements stalled in England? BMJ 2017; 357: j1946. https://doi.org/https://doi.org/10.1136/bmj.j1946 Crossref, Google ScholarInstitute for Public Policy Research. The Lord Darzi review of Health and Care. Interim Report. April 2018; https://www.ippr.org/publications/darzi-review-interim-report (accessed 25 June 2018) Google ScholarJones R. Does hospital bed demand depend more on death than demography? BJHCM 2011a;17(5):190-197. https://doi.org/https://doi.org/10.12968/bjhc.2011.17.5.190 Google ScholarJones R. Bed days per death: a new performance measure. BJHCM 2011b;17(5): 212–213. https://doi.org/https://doi.org/10.12968/bjhc.2011.17.5.213 Google ScholarJones R. Demand for hospital beds in English Primary Care Organisations. BJHCM 2011c;17(8):360–367. https://doi.org/https://doi.org/10.12968/bjhc.2011.17.8.360 Google ScholarJones R. Deaths and the marginal changes in healthcare costs BJHCM 2016;22(10):503–509. https://doi.org/https://doi.org/10.12968/bjhc.2016.22.10.503 Google ScholarJones R. Deaths and acute hospital beds in the Sustainability and Transformation Plans. BJHCM 2017a; 23(10): 498–499. https://doi.org/https://doi.org/10.12968/bjhc.2017.23.10.498 Google ScholarJones R. Government data on death rates do not tell a full story. BJHCM 2017b;23(8): 572-573. https://doi.org/https://doi.org/10.12968/bjhc.2017.23.8.396 Google ScholarJones R. The link between seasonal death rates and workloads. BJHCM 2017c;23(9): 448–450. https://doi.org/https://doi.org/10.12968/bjhc.2017.23.9.448 Google ScholarJones R. Volatility in emergency admissions per death. BJHCM 2017d; 23(11): 554-556. https://doi.org/https://doi.org/10.12968/bjhc.2017.23.11.552 Google ScholarJones R. Periods of unexplained higher deaths and medical admissions have occurred previously – but were apparently ignored, misinterpreted or not investigated. Eur J Internal Medicine 2018a; 40: e18-e20. https://doi.org/https://doi.org/10.1016/j.ejim.2017.11.004 Crossref, Google ScholarJones R. Admissions for certain conditions show explosive growth in England following a sudden and unexpected increase in deaths. Eur J Internal Medicine 2018b/ https://doi.org/https://doi.org/10.1016/j.ejim.2018.03.005 Crossref, Google ScholarJones R. Do outbreaks of ‘Disease X’ regulate NHS beds and costs? BJHCM 2018c; 24(4): 204-205. https://doi.org/https://doi.org/10.12968/bjhc.2018.24.4.204 Google ScholarNHS England. Winter daily SITREP 2017-18 data. 2018b; https://www.england.nhs.uk/statistics/statistical-work-areas/winter-daily-sitreps/winter-daily-sitrep-2017-18-data/ (accessed 25 June 2018) Google ScholarOffice for National Statistics. Monthly figures on deaths registered by usual area of residence in England and Wales, 2018a; https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/monthlyfiguresondeathsregisteredbyareaofusualresidence (accessed 25 June 2018) Google ScholarOffice for National Statistics. Deaths by single year of age tables. 2018b; https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/ (accessed 25 June 2018) Google ScholarPayne G, Laporte A, Deber R, Coyte P. Counting backward to health care's future: Using time-to-death modelling to identify changes in end-of-life morbidity and the impact of aging on health care expenditures. Milbank Quarterly 2007; 85(2):213–257. Crossref, Google ScholarRoyal College of Surgeons. Over 62,000 fewer operations performed this winter, following necessary cancellations. 8 March 2018. https://www.rcseng.ac.uk/news-and-events/media-centre/press-releases/more-patients-wait-longer-for-elective-surgery/ (accessed 25 June 2018) Google ScholarStearns S, Norton E. Time to include time to death? The future of health care expenditure predictions. Health Econ 2004;13(4):315–327. Crossref, Google ScholarStenholm S, Kivimaki M, Jylha M et al.. Trajectories of self-rated health in the last 15 years of life by cause of death. Eur J Epidemiol 2016; 31(2):177-185. https://doi.org/https://doi.org/10.1007/s10654-015-0071-0 Crossref, Google ScholarThorne J, Turner E, Hounsome L et al.. Validating the use of Hospital Episode Statistics data and comparison of costing methodologies for economic evaluation: an end-of-life case study from the Cluster randomised trial of PSA testing for Prostate cancer (CAP). BMJ Open 2016; 6: e011603.https://doi.org/https://doi.org/10.1136/bmjopen-2016-011063. Google Scholar FiguresReferencesRelatedDetails 2 July 2018Volume 24Issue 7ISSN (print): 1358-0574ISSN (online): 1759-7382 Metrics History Published online 2 July 2018 Published in print 2 July 2018 Information© MA Healthcare LimitedPDF download

Gesundes Kinzigtal 4.0 - A new financial model and performance metrics for the delivery of population-based integrated care

Introduction: The integrated care approach of Gesundes Kinzigtal has been in operation for more than 10 years, currently covering a population of about 33,000 people. During this time, the approach resulted in this population being both healthier and less cost-intensive compared to the overall population of the federal state of Baden-Wurttemberg, where the Kinzigtal is located (Pimperl et al., 2016). Cost savings are shared between the Gesundes Kinzigtal management company and the health insurance. A revision of the integrated care contract between the management company and the health insurances introduces a new financial model that grants partial budgetary responsibility to the company and the affiliated general practitioners (GPs) and specialists. Practice change, theory, current status and timeline: The primary and secondary care budget for patients that are members of the integrated care contract is commonly paid to doctors via a doctors’ association (“KV”), but will be shifted to Gesundes Kinzigtal with doctors requesting reimbursement from the company. The new model consists of a simplified accounting procedure (a combination of capitation and sessional payment) and financial incentives for GPs and specialists. At the same time, reimbursement data are transferred electronically, by further integrating practise information systems with the electronic patient record and a specialised accounting database. These data (containing diagnosis and intervention codes) allow for closer monitoring of health spending, and can serve as a proxy for population health, effectively providing a short-term regional health system performance dashboard. The model is currently in its implementation and testing stage, with full operation expected to begin in January 2018. When viewed against the background of a concept of integrated care such as that presented by MacAdam (2008), on the basis of Leutz (1999), Banks (2004) and others, this new model can be seen to shift Gesundes Kinzigtal’s integrated care model from the coordination type towards the full integration type and from the organizational integration level towards system integration. Innovativeness, impacts, sustainability, and transferability: The new financial model constitutes an innovation at least within the German healthcare system, potentially circumventing benefit shifts currently existing between health insurances, doctors’ associations, and doctors. The mixed payment model is expected to both improve cost-effectiveness and patient satisfaction, if implemented right (Barham and Milliken, 2015; Wranik and Durier-Copp, 2009). The performance metrics in combination with the simplified accounting and the financial incentives allow for early detection of cost increases, analysis of their cause and implementation of targeted remedial action, with doctors and the management company acting together on the basis of mutual trust and transparency. The shared-revenue model of the integrated care contract serves as the basis for the new model’s sustainability plan. The model can be transferred in a German context without further changes to framework conditions, and potentially also to other Bismarck-type healthcare systems. Beyond that, the model promises relevant lessons in particular with a view to the performance dashboard and the IT integration.

Is technology still a major driver of health expenditure in the United States? Evidence from cointegration analysis with multiple structural breaks.

Using a longer span of available time series data and employing powerful unit root and cointegration tests that allow for multiple structural breaks, developed recently by Carrion-i-Silvestre et al. (Econ Theory 25:1754-1792, 2009), Perron and Yabu (J Bus Econ Stat 27:369-396, 2009), Kejriwal and Perron (J Econ 146(1):59-73, 2008; J Bus Econ Stat 28(4):503-522, 2010a; J Time Ser Anal 31:305-328, 2010b) and Maki (Econ Model 29:2011-2015, 2012), this paper empirically investigates, whether technology continues to be a major driver of real per capita health expenditure, along with some control variables such as per capita income and life expectancy, in the United States, during the period 1960-2012. Specifically, the paper applies the most recent cointegration tests under multiple structural breaks and extends the work of Okunade (J Health Econ 21(1):147-159, 2002) with the possibility whether a linear cointegration model with multiple structural breaks would provide a better economic model to quantify the impact of some major determinants of US real per capita health expenditure. This paper presents evidence to show that per capita real income, technology as indicated by four proxy measures and life expectancy at birth are some major drivers of real per capita health expenditure in the United States. Contrary to the available evidence in the literature, the finding of this paper is that the point aggregate income elasticity of health expenditure estimate is less than one, indicating that health care has evolved to become a necessity in the United States. Policy implications of the empirical findings are discussed in the paper.

Utilizing selection biomarkers in clinical trials: is this the future of drug development?

Biomarkers in MedicineVol. 10, No. 9 OpinionUtilizing selection biomarkers in clinical trials: is this the future of drug development?Adam CarrollAdam Carroll*Author for correspondence: E-mail Address: adam@amplion.com Amplion, Inc., 1011 SW Emkay Dr., Suite 208, Bend, OR 97702, USASearch for more papers by this authorPublished Online:22 Aug 2016https://doi.org/10.2217/bmm-2016-0174AboutSectionsView ArticleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInReddit View articleKeywords: biomarkersclinical trialscompanion diagnosticsdrug developmentlikelihood of approvalLOAoncologypatient selection biomarkersprecision medicinerare diseaseReferences1 Thomas DW, Burns J, Audette J, Carroll C, Dow-Hygelund C, Hay C. Clinical development success rates (2006–2015) (2016). www.bio.org.Google Scholar2 Press report: biomarkers triple clinical trial success rate according to largest study of its kind. Amplion (2016). www.prnewswire.com.Google Scholar3 Thomas D, Wessel C. Emerging therapeutic company investment and deal trends (2006–2016). Biotechnol. Innov. Organ. (2016). www.bio.org.Google Scholar4 DiMasi JA, Grabowski HG, Hansen RW. Innovation in the pharmaceutical industry: new estimates of R&D costs. J. Health Econ. 47, 20–33 (2016).Crossref, Medline, Google Scholar5 Hay M, Thomas DW, Craighead JL, Economides C, Rosenthal J. Clinical development success rates for investigational drugs. Nat. Biotechnol. 32, 40–51 (2014).Crossref, Medline, CAS, Google Scholar6 Pharmaceutical Research and Manufacturers of America. 2011 Annual report (2011). www.phrma.org.Google Scholar7 Cook D, Brown D, Alexander R et al. Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework. Nat. Rev. Drug Discov. 13, 419–431 (2014).Crossref, Medline, CAS, Google Scholar8 Global Genes. Rare diseases: facts and statistics: http://globalgenes.org/rare-diseases-facts-statistics.Google ScholarFiguresReferencesRelatedDetailsCited ByTherapeutic DNA Vaccines against HPV-Related Malignancies: Promising Leads from Clinical Trials25 January 2022 | Viruses, Vol. 14, No. 2Clinical pharmacogeneticsAccelerating the Development of Personalized Cancer Immunotherapy by Integrating Molecular Patients’ Profiles with Dynamic Mathematical Models6 August 2020 | Clinical Pharmacology & Therapeutics, Vol. 108, No. 3Review of biomarkers to assess the effects of switching from cigarettes to modified risk tobacco products9 January 2018 | Biomarkers, Vol. 23, No. 3 Vol. 10, No. 9 Follow us on social media for the latest updates Metrics Downloaded 119 times History Published online 22 August 2016 Published in print September 2016 Information© Future Medicine LtdKeywordsbiomarkersclinical trialscompanion diagnosticsdrug developmentlikelihood of approvalLOAoncologypatient selection biomarkersprecision medicinerare diseaseFinancial & competing interests disclosureA Carroll is an employee and shareholder of Amplion and therefore has a financial relationship with the organization. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.PDF download

Aligning incentives to fulfil the promise of personalised medicine

Aligning incentives to fulfil the promise of personalised medicine

Persistent and transient productive inefficiency: a maximum simulated likelihood approach

The productive efficiency of a firm can be seen as composed of two parts, one persistent and one transient. The received empirical literature on the measurement of productive efficiency has paid relatively little attention to the difference between these two components. Ahn and Sickles (Econ Rev 19(4):461–492, 2000) suggested some approaches that pointed in this direction. The possibility was also raised in Greene (Health Econ 13(10):959–980, 2004. doi: 10.1002/hec.938 ), who expressed some pessimism over the possibility of distinguishing the two empirically. Recently, Colombi (A skew normal stochastic frontier model for panel data, 2010) and Kumbhakar and Tsionas (J Appl Econ 29(1):110–132, 2012), in a milestone extension of the stochastic frontier methodology have proposed a tractable model based on panel data that promises to provide separate estimates of the two components of efficiency. The approach developed in the original presentation proved very cumbersome actually to implement in practice. Colombi (2010) notes that FIML estimation of the model is ‘complex and time consuming.’ In the sequence of papers, Colombi (2010), Colombi et al. (A stochastic frontier model with short-run and long-run inefficiency random effects, 2011, J Prod Anal, 2014), Kumbhakar et al. (J Prod Anal 41(2):321–337, 2012) and Kumbhakar and Tsionas (2012) have suggested other strategies, including a four step least squares method. The main point of this paper is that full maximum likelihood estimation of the model is neither complex nor time consuming. The extreme complexity of the log likelihood noted in Colombi (2010), Colombi et al. (2011, 2014) is reduced by using simulation and exploiting the Butler and Moffitt (Econometrica 50:761–764, 1982) formulation. In this paper, we develop a practical full information maximum simulated likelihood estimator for the model. The approach is very effective and strikingly simple to apply, and uses all of the sample distributional information to obtain the estimates. We also implement the panel data counterpart of the Jondrow et al. (J Econ 19(2–3):233–238, 1982) estimator for technical or cost inefficiency. The technique is applied in a study of the cost efficiency of Swiss railways.

Cost-effectiveness in goal-directed therapy: are the dollars spent worth the value?

HEALTHCARE FINANCING has become a fixed agenda of international discussions on health policy. An aging population coupled with an insatiable demand for new and costly medical technology pose an unpredictable challenge for future healthcare funding. 1 Jurd A: Expenditures on healthcare in the UK, 1997-2010. Office for National Statistics. 2012. Available at: www.ons.gov.uk/ons/dcp171766_264293.pdf. Google Scholar , 2 OECD: Health data 2013 (online) Health expenditures, OECD Publishing. Available at: http://www.compareyourcountry.org/health/health-spending-change?cr=oecd&lg=en. Accessed on May 10, 2014 Google Scholar , 3 Anderson G. Frogner B. Johns R. et al. Health care spending and use of information technology in OECD countries. Health Affairs. 2006; 25: 819-831 Google Scholar Under such economic pressure, policymakers are expected to deliver cost-containment solutions for efficient and sustainable healthcare provision. On first sight, this idea seems to conflict with the clinicians’ main concern of delivering comprehensive care to the patients, who then often dismiss the positive effect of careful resource allocation on long-term care provision and, consequently, on the overall good to society. 4 Higgins A. Harris A. Health economic methods: cost-minimization, cost-effectiveness, cost-utility, and cost-benefit evaluation. Crit Care Clin. 2012; 28: 11-24 Google Scholar Cost-effectiveness analysis combines both principles by pooling clinical and economic benefit before suggesting sustainable strategies of effective resource allocation. 5 Weinstein M. Siegel J. Gold M. Recommendations of the Panel on Cost-effectiveness in Health and Medicine. JAMA. 2006; 276: 3353-3358 Google Scholar , 6 Weinstein M. Foundations of cost-effectiveness analysis for health and medical practice. N Engl J Med. 1977; 296: 716-721 Google Scholar , 7 Murray C.J. Evans D.B. Acharya A. et al. Development of WHO guidelines on generalized cost-effectiveness analysis. Health Econ. 2000; 9: 235-251 Google Scholar In this paper, the authors review the available literature on cost-effectiveness analysis and goal-directed therapy (GDT).

Health burden and costs of obesity and overweight in Germany: an update.

In 2011, Konnopka et al. (Eur J Health Econ 12:345-352, 2011) published a top-down cost of illness study on the health burden, and direct and indirect costs of morbidity and mortality attributable to excess weight (BMI ≥25 kg/m(2)) in Germany in 2002. The objective of the current study was to update the 2002 estimates to the year 2008. To simplify comparisons, we closely followed the methods and assumptions of the original study, using 2008 data for most input parameters (e.g. prevalence, mortality, resource use, costs). Excess weight related deaths increased by 31% (from 36,653 to 47,964) and associated years of potential life lost (from 428,093 to 588,237) and quality adjusted life years lost (from 367,722 to 505,748) by about 37%, respectively. Excess weight caused €16,797 million in total costs in 2008 (+70%), of which €8,647 million were direct costs (corresponding to 3.27% of total German health care expenditures in 2008). About 73% (€12,235 million) of total excess weight related costs were attributable to obesity (BMI ≥30 kg/m(2)). The main drivers of direct costs were endocrinological (44%) and cardiovascular (38%) diseases. Indirect costs amounted to €8,150 million in 2008 (+62%), of which about two-thirds were indirect costs from unpaid work. The great majority of indirect costs were due to premature mortality (€5,669 million). The variation of input parameters (univariate sensitivity analyses) resulted in attributable costs between €8,978 million (-47% compared to base case) and €25,060 million (+49%). The marked increase in excess weight related costs can largely be explained by increases in the prevalence of overweight and obesity, and to a lesser extent from increases in resource consumption, as well as increases in (unit) costs and wages (comprising 5.5% inflation).