Standardising policy and technology responses in the immediate aftermath of a pandemic: a comparative and conceptual framework.

BACKGROUND: The initial policy response to the COVID-19 pandemic has differed widely across countries. Such variability in government interventions has made it difficult for policymakers and health research systems to compare what has happened and the effectiveness of interventions across nations. Timely information and analysis are crucial to addressing the lag between the pandemic and government responses to implement targeted interventions to alleviate the impact of the pandemic. METHODS: To examine the effect government interventions and technological responses have on epidemiological and economic outcomes, this policy paper proposes a conceptual framework that provides a qualitative taxonomy of government policy directives implemented in the immediate aftermath of a pandemic announcement and before vaccines are implementable. This framework assigns a gradient indicating the intensity and extent of the policy measures and applies the gradient to four countries that share similar institutional features but different COVID-19 experiences: Italy, New Zealand, the United Kingdom and the United States of America. RESULTS: Using the categorisation framework allows qualitative information to be presented, and more specifically the gradient can show the dynamic impact of policy interventions on specific outcomes. We have observed that the policy categorisation described here can be used by decision-makers to examine the impacts of major viral outbreaks such as SARS-CoV-2 on health and economic outcomes over time. The framework allows for a visualisation of the frequency and comparison of dominant policies and provides a conceptual tool to assess how dominant interventions (and innovations) affect different sets of health and non-health related outcomes during the response phase to the pandemic. CONCLUSIONS: Policymakers and health researchers should converge toward an optimal set of policy interventions to minimize the costs of the pandemic (i.e., health and economic), and facilitate coordination across governance levels before effective vaccines are produced. The proposed framework provides a useful tool to direct health research system resources and build a policy benchmark for future viral outbreaks where vaccines are not readily available.

Comparing risk adjustment estimation methods under data availability constraints.

The Italian National Healthcare Service relies on per capita allocation for healthcare funds, despite having a highly detailed and wide range of data to potentially build a complex risk-adjustment formula. However, heterogeneity in data availability limits the development of a national model. This paper implements and ealuates machine learning (ML) and standard risk-adjustment models on different data scenarios that a Region or Country may face, to optimize information with the most predictive model. We show that ML achieves a small but generally statistically insignificant improvement of adjusted R2 and mean squared error with fine data granularity compared to linear regression, while in coarse granularity and poor range of variables scenario no differences were observed. The advantage of ML algorithms is greater in the coarse granularity and fair/rich range of variables set and limited with fine granularity scenarios. The inclusion of detailed morbidity- and pharmacy-based adjustors generally increases fit, although the trade-off of creating adverse economic incentives must be considered.

How do hospital-specialty characteristics influence health system responsiveness? An empirical evaluation of in-patient care in the Italian region of Emilia-Romagna.

Studies of health system responsiveness mostly focus on the demand side by investigating the association between sociodemographic characteristics of patients and their reported level of responsiveness. However, little is known about the influence of supply-side factors. This paper addresses that research gap by analysing the role of hospital-specialty characteristics in explaining variations in patients' evaluation of responsiveness from a sample of about 38,700 in-patients treated in public hospitals within the Italian Region of Emilia-Romagna. The analysis is carried out by adopting a 2-step procedure. First, we use patients' self-reported data to derive 5 measures of responsiveness at the hospital-specialty level. By estimating a generalised ordered probit model, we are able to correct for variations in individual reporting behaviour due to the health status of patients and their experience of being in pain. Second, we run cross-sectional regressions to investigate the association between patients' responsiveness and potential supply-side drivers, including waiting times, staff workload, the level of spending on non-clinical facilities, the level of spending on staff education and training, and the proportion of staff expenditure between nursing and administrative staff. Results suggest that responsiveness is to some extent influenced by the supply-side drivers considered.

Price Changes in Regulated Healthcare Markets: Do Public Hospitals Respond and How?

This paper examines the behaviour of public hospitals in response to the average payment incentives created by price changes for patients classified in different diagnosis-related groups (DRGs). Using panel data on public hospitals located within the Italian region of Emilia-Romagna, we test whether a 1-year increase in DRG prices induced public hospitals to increase their volume of activity and whether a potential response is associated with changes in waiting times and/or length of stay. We find that public hospitals reacted to the policy change by increasing the number of patients with surgical treatments. This effect was smaller in the 2 years after the policy change than in later years, and for providers with a lower excess capacity in the pre-policy period, whereas it did not vary significantly across hospitals according to their degree of financial and administrative autonomy. For patients with medical DRGs, instead, there appeared to be no effect on inpatient volumes. Our estimates also suggest that an increase in DRG prices had no impact on the proportion of patients waiting more than 6 months. Finally, we find no evidence of a significant effect on patients' average length of stay. Copyright © 2016 John Wiley & Sons, Ltd.

Supply-side solutions targeting demand-side characteristics: causal effects of a chronic disease management program on adherence and health outcomes.

We estimate the effects of a chronic disease management program (CDMP) which adapts various supply-side interventions to specific demand-side conditions (disease-staging) for patients with chronic kidney disease (CKD). Using a unique dataset on the entire population of the Emilia-Romagna region of Italy with hospital-diagnosed CKD, we estimate the causal effects of the CDMP on adherence indicators and health outcomes. As CKD is a progressive disease with clearly-defined disease stages and a treatment regimen that can be titrated by disease severity, we calculate dynamic, severity-specific, indicators of adherence as well as several long-term health outcomes. Our empirical work produces statistically significant and sizeable causal effects on many adherence and health outcome indicators across all CKD patients. More interestingly, we show that the CDMP produces larger effects on patients with early-stage CKD, which is at odds with some of the literature on CDMP that advocates intensifying interventions for high-cost (or late-stage) patients. Our results suggest that it may be more efficient to target early-stage patients to slow the deterioration of their health capital. The results contribute to a small, recent literature in health economics that focuses on the marginal effectiveness of CDMPs after controlling either for supply- or demand-side sources of heterogeneity.

Disease management in diabetes care: When involving GPs improves patient compliance and health outcomes.

Although the study of the association between interventions in primary care and health outcomes continues to produce mixed findings, programs designed to promote the greater compliance of General Practitioners and their diabetic patients with guidelines have been increasingly introduced worldwide, in an attempt to achieve better quality diabetes care through the enhanced standardisation of patient supervision. In this study, we use clinical data from the Diabetes Register of one large Local Health Authority (LHAs) in Italy's Emilia-Romagna Region for the period 2012-2015. Firstly, we investigate whether GPs' participation in the local Diabetes Management Program (DMP) leads to improved patient compliance with regional guidelines. Secondly, we test whether the monitoring activities prescribed for diabetics by the Regional diabetes guidelines have a positive impact on patients' health outcomes and increase appropriateness in health care utilization. Our results show that such a Program, which aims to increase GPs' involvement and cooperation in following the Regional guidelines, achieves its goal of improved patient compliance with the prescribed actions. In turn, through the implementation of the DMP and the greater involvement of physicians, Regional policies have succeeded in promoting better health outcomes and improved appropriateness of health care utilization.

Competitive Health Markets and Risk Equalisation in Australia: Lessons Learnt from Other Countries.

The aims of this paper are to evaluate the risk equalisation (RE) arrangement in Australia's private health insurance against practices in other countries with similar arrangements and to propose ways of improving the system to advance economic efficiency and solidarity. Possible regulatory responses to insurance market failures are reviewed based on standard economic arguments. We describe various regulatory strategies used elsewhere to identify essential system features against which the Australian system is compared. Our results reveal that RE is preferred over alternative regulatory strategies such as premium rate restrictions, premium compensation and claims equalisation. Compared with some countries' practices, the calculated risk factors in Australia should be enhanced with further demographic, social and economic factors and indicators of long-term health issues. Other coveted features include prospective calculation and annual clearing of equalisation payments. Australia currently operates with a crude mechanism for RE in which the scheme incentivises insurers to select on risk rather than focusing on efficiency and equity-promoting actions. System changes should be introduced in a stepwise manner; thus, we propose an incremental reform.

Decision Making and Priority Setting: The Evolving Path Towards Universal Health Coverage.

Health technology assessment (HTA) is widely viewed as an essential component in good universal health coverage (UHC) decision-making in any country. Various HTA tools and metrics have been developed and refined over the years, including systematic literature reviews (Cochrane), economic modelling, and cost-effectiveness ratios and acceptability curves. However, while the cost-effectiveness ratio is faithfully reported in most full economic evaluations, it is viewed by many as an insufficient basis for reimbursement decisions. Emotional debates about the reimbursement of cancer drugs, orphan drugs, and end-of-life treatments have revealed fundamental disagreements about what should and should not be considered in reimbursement decisions. Part of this disagreement seems related to the equity-efficiency tradeoff, which reflects fundamental differences in priorities. All in all, it is clear that countries aiming to improve UHC policies will have to go beyond the capacity building needed to utilize the available HTA toolbox. Multi-criteria decision analysis (MCDA) offers a more comprehensive tool for reimbursement decisions where different weights of different factors/attributes can give policymakers important insights to consider. Sooner or later, every country will have to develop their own way to carefully combine the results of those tools with their own priorities. In the end, all policymaking is based on a mix of facts and values.

Dealing with minor illnesses: The link between primary care characteristics and Walk-in Centres' attendances.

The reformulation of existing boundaries between primary and secondary care, in order to shift selected services traditionally provided by Emergency Departments (EDs) to community-based alternatives, has determined a variety of organisational solutions. One innovative change has been the introduction of fast-track systems for minor injuries or illnesses, whereby community care providers are involved in order to divert patients away from EDs. These facilities offer an open-access service for patients not requiring hospital treatments, and may be staffed by nurses and/or primary care general practitioners operating within, or alongside, the ED. To date little research has been undertaken on such experiences. To fill this gap, we analyse a Walk-in Centre (WiC) in the Italian city of Parma, consisting of a minor injury unit located alongside the teaching hospital's ED. We examine the link between the utilisation rates of the WiC and primary care characteristics, focusing on the main organisational features of the practices and estimating panel count data models for 2007-2010. Our main findings indicate that the extension of practice opening hours significantly lowers the number of attendances, after controlling for General Practitioner's and practice's characteristics.

Are bad health and pain making us grumpy? An empirical evaluation of reporting heterogeneity in rating health system responsiveness.

In recent years, the concept of responsiveness has been put forward as one desirable measure of the performance of health systems. Responsiveness can be defined as a system's ability to respond to the legitimate expectations of potential users regarding non-health enhancing aspects of care. However, since responsiveness is evaluated by patients on a categorical scale, their self-evaluation can be affected by the phenomenon of reporting heterogeneity. A few studies have investigated how standard socio-demographic characteristics influence the reporting style of patients with regard to responsiveness. However, we are not aware of studies that focus explicitly on the influence that both the patients' state of health and their experiencing of pain have on their reporting style on responsiveness. This paper tries to bridge this gap by using data regarding a sample of about 2500 patients hospitalized in four Local Health Authorities (LHA) in Italy's Emilia-Romagna region between 2010 and 2012. These patients have evaluated 27 different aspects of the quality of care, concerning five domains of responsiveness (communication, privacy, dignity, waiting times and quality of facilities). Data have been stratified into five sub-samples, according to these domains. We estimate a generalized ordered probit model, an extension of the standard ordered probit model which permits the reporting behaviour of respondents to be modelled as a function of certain respondents' characteristics, which in our analysis are represented by the variables "state of health" and "pain". Our results suggest that unhealthier patients and patients experiencing pain are more likely to report a lower level of responsiveness, all other things being equal.

GPs and hospital expenditures. Should we keep expenditure containment programs alive?

Pay-for-Performance programs offering additional payments to GPs can be used not only to improve the quality of care but also for cost containment purposes. In this paper, we analyse the impact of removing financial incentives in primary care that were aimed at containing hospital expenditure in the Italian region of Emilia-Romagna during the period 2002-2004. Our analysis draws on regional databanks linking GPs' characteristics to those of their patients (including all sources of public payments made to GPs), together with information on the utilisation of hospital services. The dataset includes 2,936,834 patients, 3229 GPs and 39 districts belonging to 11 Local Health Authorities. We employ a difference-in-difference specification to assess changes in expenditures for avoidable and total hospital admissions. We identify the treatment group with GPs operating in districts where the program is withdrawn during the observation period ("Leavers"). Their performance is compared to that of two separate control groups, namely: GPs working in districts that grant incentives for the entire period ("Stayers") and those working in districts that never introduced measures for the containment of hospitalisations ("Non Participants"). The comparison between treatment and control groups shows that removing incentives does not result in a worse performance by Leavers compared to both control groups. This supports the policy of removing incentives, as such entail extra payments to GPs which, however, do not seem capable of significantly influencing their behaviour in the desired way. Our findings complement previous evidence from the same institutional context showing that only those programs that aim to improve disease management for specific conditions - rather than to simply contain expenditure - have proven successful in reducing avoidable admissions for the target population.

Incentives in primary care and their impact on potentially avoidable hospital admissions.

Financial incentives in primary care have been introduced with the purpose of improving appropriateness of care and containing demand. We usually observe pay-for-performance programs, but alternatives, such as pay-for-participation in improvement activities and pay-for-compliance with clinical guidelines, have also been implemented. Here, we assess the influence of different programs that ensure extra payments to GPs for containing avoidable hospitalisations. Our dataset covers patients and GPs of the Italian region Emilia-Romagna for the year 2005. By separating pay-for-performance from pay-for-participation and pay-for-compliance programs, we estimate the impact of different financial incentives on the probability of avoidable hospitalisations. As dependent variable, we consider two different sets of conditions for which timely and effective primary care should be able to limit the need for hospital admission. The first is based on 27 medical diagnostic related groups that Emilia-Romagna identifies as at risk of inappropriateness in primary care, while the second refers to the internationally recognised ambulatory care-sensitive conditions. We show that pay-for-performance schemes may have a significant effect over aggregate indicators of appropriateness, while the effectiveness of pay-for-participation schemes is adequately captured only by taking into account subpopulations affected by specific diseases. Moreover, the same scheme produces different effects on the two sets of indicators used, with performance improvements limited to the target explicitly addressed by the Italian policy maker. This evidence is consistent with the idea that a "tunnel vision" effect may occur when public authorities monitor specific sets of objectives as proxies for more general improvements in the quality of health care delivered.