Cost-Sharing as a Financing Mechanism in the Greek Primary Health Care: An Assessment from the Managers’ Perspective

Cost-sharing was recently introduced in the Greek Primary Health Care, as a supplementary mechanism to finance spiraling health expenditure and to make patients cost-conscious. A specific questionnaire was distributed to the 188 managers of the health centres in Greece (response rate 93 per cent). The research was conducted from June 2011 to May 2012. Statistical analysis was performed using the Pearson x2 test, the Kolmogorov-Smirnov test, the t-test and the Mann-Whitney test at p<0.05 level of significance. 73 per cent of the managers stated that the introduction of the cost-sharing had a positive impact on patients‟ compliance and 66.3 per cent that the financing mechanism has contributed to cost consciousness from both the patients and personnel. The revenues from medical fees do not cover the running costs of health centres (81.5 per cent) and they do not promote a more effective delivery of services (80 per cent). 61 per cent of managers characterise cost-sharing as a positive step and 80 per cent support the economic autonomy of health centres. Managers stated that cost-sharing has a positive impact on patients‟ cost-consciousness and in the financing of the primary health care in Greece, but this policy option alone doesn‟t assure the financial and administrative viability of the health centres

Citizens’ Preferences on Health Care Expenditure Allocation: Evidence from Greece

Priority setting and resource allocation across various health care functions is a critical issue in health policy and strategic decision making. As health resources are limited while there are so many health challenges to resolve, consumers and payers have to make difficult decisions about expenditure allocation. Our research focus on the (dis)agreement between citizens’ preferences and actual public health expenditure across broad health care functions, on whether this (dis)agreement is persistent, on whether various demographic factors amplify this (dis)agreement and to derive useful implications for public health policies. Using survey data of 3,029 citizens in Greece for the year 2012 and employing logit estimation techniques, we analyzed the effect of demographic and other factors in shaping citizens’ (dis)agreement with public health expenditure allocation. Our results demonstrate the important role of income, family members and residence in shaping citizens’ preferences regarding health expenditure priorities in almost all health care functions, while other demographic factors such as job, age, gender and marital status do partly associate and play a significant role

Citizens’ Preferences on Health Care Expenditure Allocation: Evidence from Greece

Priority setting and resource allocation across various health care functions is a critical issue in health policy and strategic decision making. As health resources are limited while there are so many health challenges to resolve, consumers and payers have to make difficult decisions about expenditure allocation. Our research focus on the (dis)agreement between citizens’ preferences and actual public health expenditure across broad health care functions, on whether this (dis)agreement is persistent, on whether various demographic factors amplify this (dis)agreement and to derive useful implications for public health policies. Using survey data of 3,029 citizens in Greece for the year 2012 and employing logit estimation techniques, we analyzed the effect of demographic and other factors in shaping citizens’ (dis)agreement with public health expenditure allocation. Our results demonstrate the important role of income, family members and residence in shaping citizens’ preferences regarding health expenditure priorities in almost all health care functions, while other demographic factors such as job, age, gender and marital status do partly associate and play a significant role

On the decision rules of cost-effective treatment for patients with diabetic foot syndrome

John E Goulionis1, Athanassios Vozikis2, VK Benos1, D Nikolakis11Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece; 2Department of Economic Science, University of Piraeus, Piraeus, GreeceObjective: To assess the cost-effectiveness of two treatments (medical treatment and &amp;shy;amputation) in patients with diabetic foot syndrome, one of the most disabling diabetic complications. Diabetes mellitus is a massive health care problem worldwide with a current prevalence of 150 millions diabetic cases, estimated to increase to 300 million cases in 2025.Methods: Integrating medical knowledge and advances into the clinical setting is often difficult due to the complexity of the algorithms and protocols. Clinical decision support systems assist the clinician in applying new information to patient care through the analysis of patient-specific clinical variables. We require strategic decision support to analyze the cost-effectiveness of these programs compared to the status quo. We provide a simple partially observable Markov model to investigate that issue, and we propose an heuristic algorithm to find the best policy of intervention.Results: This study assesses the potential cost-effectiveness of two alternative treatment interventions in patients with diabetic foot syndrome. The implementation of the heuristic algorithm solution will assist doctors in clinical decision making, and health care organizations in evaluating medication choices for effective treatment. Finally, our study reveals that treatment programs are highly cost-effective for patients at high risk of diabetic foot ulcers and lower extremity amputations.Keywords: partially observable Markov decision model, diabetic foot syndrome, cost-&amp;shy;effectiveness metho

AI and Big Data: A New Paradigm for Decision Making in Healthcare

The latest developments in artificial intelligence (AI) - a general-purpose technology impacting many industries - have been based on advancements in machine learning, which is recast as a quality-adjusted decline in forecasting ratio. The influence of Policy on AI and big data has impacted two key magnitudes which are known as diffusion and consequences. And these must be focused primarily on the context of AI and big data. First, in addition to the policies on subsidies and intellectual property (IP) that will affect the propagation of AI in ways close to their effect on other technologies, three policy categories - privacy, exchange, and liability - may have a specific impact on the diffusion of AI. The first step in the prohibition process is to identify the shortcomings of current hospital procedures, why we need acute care AI, and eventually how the direction of patient decision-making will shift with the introduction of AI-based research. The second step is to establish a plan to shift the direction of medical education in order to enable physicians to retain control of AI. Medical research would need to rely less on threshold decision-making and more on the prediction, interpretation, and pathophysiological context of contextual time cycles. This should be an early part of a medical student's education, and this is what their hospital aid (AI) ought to do. Effective contact between human and artificial intelligence includes a shared pattern of focused knowledge base. Human-to-human contact protection in hospitals should lead this professional transformation process

Strategies to prioritize prevention in the Greek primary healthcare system

The present study presents financial incentives for General Practitioners(GPs) to engage in specific preventive care services and describes new roles for nurses to provide recommendations regarding brief nutrition counseling. To calculate the total number of personnel required to provide nutrition counseling, we considered 4 elements: (1) published and estimated time required to deliver nutrition counseling (2) the number of the maximum patients seen per day (3) the annual workload of the provider and (4) the number of people requiring those services. We annualize the frequency of performing specific preventive care services by GPs based on the official recommendations by the American Cancer Society. One exclusive nurse could provide a plan of care, designed to help almost 20.000 individuals either maintain the assessed status or attain a healthier status. Screening tests for cervical, colon and breast cancer should be performed by GPs to at least 3.537.810 individuals of the total Greek population for the year 2018

Demand for primary healthcare services in Greece based on general practice prescribing model.

Analyze the demand for general practitioners and estimate trends in the demand for health care services, mostly based on demographic and epidemiological development. We sought to project the cost and volume of prescribing in primary care. We used the data from the National Organization for the Provision of Primary Healthcare Services (EOPYY) to design a model based on the number of prescriptions issued to a patient visit. The prescriptions are grouped by patients' age, sex, place of residence and their diagnostic evaluation. We selected eleven conditions, which are identified by the codes from the International Classification of Diseases. The forecasting model is based on the negative binomial regression. Projections are made for drug expenditure based on data taken from the World Bank and analysis of current utilization trends. We project an increase in drug expenditure in 2021, although it is expected population decline. Older adults use more health services than younger people. It is noted that female have higher medical care service utilization than male. Greeks living in rural areas have less healthcare utilization rates than their urban counterparts

Strategies to prioritize prevention in the Greek primary healthcare system

The present study presents financial incentives for General Practitioners(GPs) to engage in specific preventive care services and describes new roles for nurses to provide recommendations regarding brief nutrition counseling. To calculate the total number of personnel required to provide nutrition counseling, we considered 4 elements: (1) published and estimated time required to deliver nutrition counseling (2) the number of the maximum patients seen per day (3) the annual workload of the provider and (4) the number of people requiring those services. We annualize the frequency of performing specific preventive care services by GPs based on the official recommendations by the American Cancer Society. One exclusive nurse could provide a plan of care, designed to help almost 20.000 individuals either maintain the assessed status or attain a healthier status. Screening tests for cervical, colon and breast cancer should be performed by GPs to at least 3.537.810 individuals of the total Greek population for the year 2018

Demand for primary healthcare services in Greece based on general practice prescribing model.

Analyze the demand for general practitioners and estimate trends in the demand for health care services, mostly based on demographic and epidemiological development. We sought to project the cost and volume of prescribing in primary care. We used the data from the National Organization for the Provision of Primary Healthcare Services (EOPYY) to design a model based on the number of prescriptions issued to a patient visit. The prescriptions are grouped by patients' age, sex, place of residence and their diagnostic evaluation. We selected eleven conditions, which are identified by the codes from the International Classification of Diseases. The forecasting model is based on the negative binomial regression. Projections are made for drug expenditure based on data taken from the World Bank and analysis of current utilization trends. We project an increase in drug expenditure in 2021, although it is expected population decline. Older adults use more health services than younger people. It is noted that female have higher medical care service utilization than male. Greeks living in rural areas have less healthcare utilization rates than their urban counterparts