Preferences for Monitoring Comprehensive Heart Failure Care: A Latent Class Analysis.

OBJECTIVE: To measure preference heterogeneity for monitoring systems among patients with a chronic heart failure. METHODS: A best-worst scaling experiment (BWS case 3) was conducted among patients with chronic heart failure to assess preferences for hypothetical monitoring care scenarios. These were characterized by the attributes mobility, risk of death, risk of hospitalization, type and frequency of monitoring, risk of medical device, and system-relevant complications. A latent class analysis (LCA) was used to analyze and interpret the data. In addition, a market simulator was used to examine which treatment configurations participants in the latent classes preferred. RESULTS: Data from 278 respondents were analyzed. The LCA identified four heterogeneous classes. For class 1, the most decisive factor was mobility with a longer distance covered being most important. Class 2 respondents directed their attention toward attribute "monitoring," with a preferred monitoring frequency of nine times per year. The attribute risk of hospitalization was most important for respondents of class 3, closely followed by risk of death. For class 4, however, risk of death was most important. A market simulation showed that, even with high frequency of monitoring, most classes preferred therapy with high improvement in mobility, mortality, and hospitalization. CONCLUSION: Using LCA, variations in preferences among different groups of patients with chronic heart failure were examined. This allows treatment alternatives to be adapted to individual needs of patients and patient groups. The findings of the study enhance clinical and allocative decision-making while elevating the quality of clinical data interpretation.

Which body functions and activities matter for stroke patients? Study protocol for best-Worst scalings to value core elements of the International Classification of Functioning, Disability and Health.

BACKGROUND: Stroke is a common, serious, and disabling healthcare problem with increasing incidence and prevalence. Following a stroke, identifying the factors associated with decisions about rehabilitation interventions is important to assess rehabilitation after stroke. The aim is to guide clinical staff to make patient-centered decisions. Fundamentally, decision makers cannot draw on evidence to consider the relevance of distinct functions and activities from the patient's perspective. Until now, outcomes of rehabilitation are generally categorized using the International Classification of Functioning, Disability and Health (ICF). This can be seen as a conceptual basis for the assessment of health and disability. Since the ICF does not distinguish importance between these aspects there is a need to value the most important clinical factors as well as related activities from a patients and public perspective to help guide therapists in effectively designing post-acute rehabilitation care for individuals following stroke. The research question is which ICF body functions and activities are of value to stroke patients? Which trade-offs are patients willing to make within the core elements? Health preference research (HPR) answers the need to develop additional preference weights for certain ICF dimensions. Patient preference information (PPI) values health conditions based on the ICF from a patient perspective. METHODS: In this study we conduct three best-worst scaling (BWS) experiments to value body function and activities from patients' and public perspective. Out of all ICF dimensions this research covers health conditions relevant to stroke patients in terms of body function, perception, and activities of daily living. Stroke patients as well as members of the general population will be recruited to participate in the online BWS surveys. Fractional, efficient designs are applied regarding the survey design. Conditional and multinominal logit analyses will be used as the main analysis method, with the best-worst count analysis as a secondary analysis. The survey is being piloted prior to commencing the process of data collection. Results are expected by the autumn of 2023. DISCUSSION: The research will add to the current literature on clinical decision-making in stroke rehabilitation and the value of certain body functions as well as related activities in neurorehabilitation. Moreover, the study will show whether body functions and activities that are currently equally weighted in international guidelines are also equally important from the point of view of those affected, or whether there are disconcordances in terms of differences between public judgements and patients' preferences.

Patient preferences in the treatment of hemophilia A: A latent class analysis.

OBJECTIVE: To examine subgroup-specific treatment preferences and characteristics of patients with hemophilia A. METHODS: Best-Worst Scaling (BWS) Case 3 (four attributes: application type; bleeding frequencies/year; inhibitor development risk; thromboembolic events of hemophilia A treatment risk) conducted via online survey. Respondents chose the best and the worst option of three treatment alternatives. Data were analyzed via latent class model (LCM), allowing capture of heterogeneity in the sample. Respondents were grouped into a predefined number of classes with distinct preferences. RESULTS: The final dataset contained 57 respondents. LCM analysis segmented the sample into two classes with heterogeneous preferences. Preferences within each were homogeneous. For class 1, the most decisive factor was bleeding frequency/year. Respondents seemed to focus mainly on this in their choice decisions. With some distance, inhibitor development was the second most important. The remaining attributes were of far less importance for respondents in this class. Respondents in class 2 based their choice decisions primarily on inhibitor development, also followed, by some distance, the second most important attribute bleeding frequency/year. There was statistical significance (P < 0.05) between the number of annual bleedings and the probability of class membership. CONCLUSIONS: The LCM analysis addresses heterogeneity in respondents' choice decisions, which helps to tailor treatment alternatives to individual needs. Study results support clinical and allocative decision-making and improve the quality of interpretation of clinical data.

Personalized diabetes management: what do patients with diabetes mellitus prefer? A discrete choice experiment.

BACKGROUND: There are unresolved procedural and medical problems in the care of diabetes, which cause high costs for health systems. These include the inadequate glycemic adjustment, care gaps, therapeutic inertia, and a lack of motivation. Personalized diabetes management can be seen as a kind of "standard process" that provides both physicians and patients with a framework. The aim of this empirical survey is the evaluation of patient preferences regarding personalized diabetes management. The purpose of this experiment is to demonstrate the properties of the programs that are relevant for the choice of insulin-based therapy regimens for patients with type II diabetes mellitus. METHODS: A discrete choice experiment (DCE) was applied to identify preferences for a personalized diabetes management in patients with type II diabetes mellitus. Six attributes were included. The DCE was conducted in June 2017 using a fractional factorial design, and the statistical data analysis used random effect logit models. RESULTS: N = 227 patients (66.1% male) were included. The preference analysis showed dominance for the attribute "occurrence of severe hypoglycemias per year" [level difference (LD) 2765]. Preference analysis also showed that participants weight the "risk of myocardial infarction (over 10 years)" (LD 1.854) highest among the side effects. Within the effectiveness criterion of "change in the long-term blood glucose level (HbA1c)" a change at an initial value of 9.5% (LD 1.146) is weighted slightly higher than changes at 7.5% (LD 1.141). Within the random parameter logit estimation, all coefficients proved to be significantly different from zero at the level p ≤ 0.01. The latent class analysis shows three heterogeneous classes, each showing clearly different weights of the therapeutic properties. This results in a clear three-folding: for 1/3 of the respondents the change of the long-term blood sugar (HbA1c value) is the top objective. Another third is solely interested in the short-term effectiveness of the therapy in the sense of the occurrence of severe hypoglycemias per year. The last third of the interviewees finally focuses on the follow-up regarding cardiovascular events. Overall, there were five structural and personality traits which have an influence on the respective probability of the class membership. DISCUSSION/CONCLUSION: This study identifies and weights the key decision-making criteria for optimal management of diabetes from the perspective of patients. It was shown that the effectiveness of a care program is the most important from the perspective of the patient and avoiding severe a hypoglycemia has the greatest influence on the choice. The risk of myocardial infarction as a follow-up disease and the long-term adjustment of the blood glucose follow the importance. In the analysis of possible subgroup differences by means of latent class analysis, it was found that three preference patterns exist within the sample. The generated preference data can be used for the design of personalized management approaches. It remains open to the extent to which expert opinions and patient preferences diverge.

Patient Preferences in the Treatment of Hemophilia A: A Best-Worst Scaling Case 3 Analysis.

OBJECTIVE: To assess patient preferences for benefits and risks in hemophilia A treatment. METHODS: A systematic literature search and pretest interviews were conducted to determine the most patient-relevant endpoints in terms of effects, risks, and administration of hemophilia A treatments. A Best-Worst Scaling (BWS; Case 3 or multiprofile case) approach was applied in a structured questionnaire. Patients were surveyed by interviewers in a computer-assisted personal interview. Treatments in the choice scenarios comprised bleeding frequency per year, application type, risk of thromboembolic event risk, and inhibitor development. Each respondent answered 13 choice tasks, including 1 dominant task, comparing 3 treatment profiles. Data were analyzed using a mixed logit model (random-parameters logit). RESULTS: Data from 57 patients were used. The attributes "bleeding frequency per year" and "inhibitor development" had the greatest impact on respondents' choice decisions. Patients disliked being at risk of inhibitor development more than being at risk of thromboembolic events. The type of application, whether intravenous or subcutaneous, was of less importance for patients. There was a significant preference variation for all attributes. CONCLUSIONS: Patients value low frequency of bleeding per year and low risk of development of inhibitors the most. An increase of risk and frequency would significantly decrease the impact on choice decisions. The type of application does not seem to influence the choice decision very much compared with the other attributes. Regarding preference heterogeneity, further analysis is needed to identify subgroups among patients and their characteristics. This may help to adapt individually patient-tailored treatment alternatives for hemophilia A patients.

Patient Preferences Concerning Alternative Treatments for Neuroendocrine Tumors: Results of the "PIANO-Study".

OBJECTIVES: Neuroendocrine tumors (NETs) are rare, slow-growing malignant tumors. So far, there are no data on patient preferences regarding its therapy. This empirical study aimed to elicit patient preferences in the drug treatment of NET. METHODS: Based on qualitative patient interviews and an analytic hierarchy process, six patient-relevant attributes were analyzed and weighted using a discrete-choice experiment. Patients were recruited with the help of a NET support group. An experimental 3*3 + 6*3 -MNL design was created using NGene. The design consisted of eighty-four choices, divided into seven blocks. Participants were randomly assigned to these blocks. The analysis included random parameter logit and latent class models. RESULTS: A total of 275 participants (51.6 percent female; mean age, 58.4 years) were included. The preference analysis within the random parameter logit model, taking into account the 95 percent confidence interval, showed predominance for the attribute "overall survival." The attributes "response to treatment" and "stabilization of tumor growth" followed. The side effects "nausea/vomiting" and "diarrhea" were considered of relatively equal importance. Latent class analysis of possible subgroup differences revealed three preference patterns. CONCLUSIONS: Preferences can influence therapeutic decisions. Preference analyses indicated that "overall survival" had the strongest influence, with participants clearly weighing outcome attributes higher than side effect attributes. In conclusion, mono-criterial decisions would not fully reflect patient perspectives.

Contract Design: Risk Management and Evaluation.

INTRODUCTION: Effective risk adjustment is an aspect that is more and more given weight on the background of competitive health insurance systems and vital healthcare systems. The risk structure of the providers plays a vital role in Pay for Performance. A prerequisite for optimal incentive-based service models is a (partial) dependence of the agent's returns on the provider's gain level. Integrated care systems as well as accountable care organisations (ACOs) in the US and similar concepts in other countries are advocated as an effective method of improving the performance of healthcare systems. These systems outline a payment and care delivery model that intends to tie provider reimbursements to predefined quality metrics. By this the total costs of care shall be reduced. METHODS: Little is known about the contractual design and the main challenges of delegating "accountability" to these new kinds of organisations and/or contracts. The costs of market utilisation are highly relevant for the conception of healthcare contracts; furthermore information asymmetries and contract-specific investments are an obstacle to the efficient operation of ACOs. A comprehensive literature review on methods of designing contracts in Integrated Care was conducted. The research question in this article focuses on how reimbursement strategies, evaluation of measures and methods of risk adjustment can best be integrated in healthcare contracting. RESULTS: Each integrated care contract includes challenges for both payers and providers without having sufficient empirical data on both sides. These challenges are clinical, administrative or financial nature. Risk adjusted contracts ensure that the reimbursement roughly matches the true costs resulting from the morbidity of a population. If reimbursement of care provider corresponds to the actual expenses for an individual/population the problem of risk selection is greatly reduced. The currently used methods of risk adjustment have widely differing model and forecast accuracy. For this reason, it is necessary to clearly regulate the method of risk adjustment in the integrated care contract. CONCLUSIONS AND DISCUSSION: The series of three articles on contract design has shown that coordination and motivation problems in designing healthcare contracts cannot be solved at no-costs. Moreover, it became clear, that complete contracts in healthcare are unrealistic and that contracts do always include certain uncertainties. These are based on the risk of random, and no contracting party can control these risks completely. It is also not possible to fully integrate these risks in the contract or to eliminate these risks by the parties.

Contract Design: The problem of information asymmetry.

INTRODUCTION: Integrated care systems are advocated as an effective method of improving the performance of healthcare systems. These systems outline a payment and care delivery model that intends to tie provider reimbursements to predefined quality metrics. Little is known about the contractual design and the main challenges of delegating "accountability" to these new kinds of organisations and/or contracts. The research question in this article focuses on how healthcare contracts can look like and which possible problems arise in designing such contracts. In this a special interest is placed on information asymmetries. METHODS: A comprehensive literature review on methods of designing contracts in Integrated Care was conducted. This article is the first in a row of three that all contribute to a specific issue in designing healthcare contracts. Starting with the organisation of contracts and information asymmetries, part 2 focusses on financial options and risks and part 3 finally concludes with the question of risk management and evaluation. RESULTS: Healthcare contracting between providers and payers will have a major impact on the overall design of future healthcare systems. If Integrated care systems or any other similar concept of care delivery are to be contracted directly by payers to manage the continuum of care the costs of market utilisation play an essential role. Transaction costs also arise in the course of the negotiation and implementation of contracts. These costs are the reason why it is generally not possible to conclude perfect (complete) contracts. Problems with asymmetric distribution of information can relate to the situation before a contract is concluded (adverse selection) and after conclusion of a contract (moral hazard). DISCUSSION AND CONCLUSIONS: Information asymmetries are seen as a major obstacle to the efficient operation of integrated care programmes. Coordination and motivation problems cannot be solved at no-costs. The presented problems in the design of selective individual contracts represent a necessary but not a sufficient condition for further government intervention. A state or political failures have to be assumed continuously.

Contract Design: Financial Options and Risk.

INTRODUCTION: Integrated care systems as well as accountable care organisations (ACOs) in the US and similar concepts in other countries are advocated as an effective method of improving the performance of healthcare systems. These systems outline a payment and care delivery model that intends to tie provider reimbursements to predefined quality metrics. By this the total costs of care shall be reduced. When designing healthcare options contractors are faced with a variety of financial options. The costs of market utilisation are highly relevant for the conception of healthcare contracts; furthermore contract-specific investments are an obstacle to the efficient operation of ACOs. METHODS: A comprehensive literature review on methods of designing contracts in Integrated Care was conducted. This article is the second in a row of three that are all published in this issue and contribute to a specific issue in designing healthcare contracts. The first dealt with the organisation of contracts and information asymmetries, while part 3 concludes with the question of risk management and evaluation. The specific research question of this second article focusses on the financial options and reimbursement schemes that are available to define healthcare contracts. RESULTS: A healthcare contract is a relational contract, which determines the level of reimbursement, the scope of services and the quality between service providers and payers, taking account of the risks relating to population and performance. A relational contract is an agreement based upon assumption of a longer timeframe. A major obstacle to the practical implementation of healthcare contracts is the prognosis of the inflows and outflows due to the actuarial risks of the insured population. Financing conditions and reimbursement arrangements that are based on a prospectively determined fixed price, have a significant drawback: it is very difficult to take the differences in health status and the utilisation of distinct insured clientele (panel) into account. DISCUSSION AND CONCLUSION: The first two articles of this series on contract design have shown that complete contracts in healthcare are unrealistic. Healthcare reimbursement contracts are incomplete contracts with a high degree of uncertainty. In incomplete contracts specific contractual regulations are not made for any eventuality. For this reason it is important that the parties agree on the prevention of endogenous risks (asymmetric information after the conclusion of the contract) and on the procedure in the case of unforeseen circumstances (the risks of random, parameter risk and change risks to the healthcare program).

Treatment Preferences in Germany Differ Among Apheresis Patients with Severe Hypercholesterolemia.

BACKGROUND: Severe hypercholesterolemia is a major risk factor of death in patients with coronary heart disease. New adjunctive drug therapies (proprotein convertase subtilisin/kexin type 9 [PCSK9] inhibitors) have gained approval in Europe and the USA. OBJECTIVE: In this empirical study, we documented preferences regarding adjuvant drug therapy in apheresis-treated patients with severe familial hypercholesterolemia. METHODS: We conducted a systematic literature search to identify patient-relevant outcomes in patients with severe hypercholesterolemia currently undergoing apheresis. Data were used to generate a semi-structured qualitative interview that enabled seven patient-relevant characteristics with three levels each to be identified. For the discrete choice experiment, an experimental design (7 × 3) was generated using NGene Software that consisted of 96 choices divided into eight blocks. The survey was conducted between November 2015 and April 2016 using computer-assisted personal interviews. RESULTS: The survey was completed by 348 patients (64.9% male). The random parameter logit estimation showed predominance for the attribute 'reduction of LDL-C (low-density lipoprotein cholesterol) level'. 'Risk of myopathy' and 'frequency of apheresis' dominated next. Within the random parameter logit estimation, all coefficients were significant (P ≤ 0.01). The latent class analysis identified three patient groups. The first group (126 patients) found 'reduction of LDL-C level in blood' to be most important. This group focused solely on this treatment outcome independently of apheresis frequency or additional injections. The second group (106 patients) focused on three attributes: 'frequency of apheresis', 'risk of myopathy', and 'reduction of LDL-C level in blood'. Respondents clearly considered a high frequency of apheresis to have a negative impact. The third group (116 patients) demonstrated the highest preference for apheresis. These patients have adjusted to apheresis for > 10 years. CONCLUSION: Regarding patient preference, clinical efficacy seems to dominate. Hence, 'reduction of LDC-C in blood' was ranked highest above patient-relevant modes of administration and adverse effects. In the patient groups identified, reduction of apheresis was important for only a subsegment (30%) of patients. Another 30% wanted effective LDL-C reduction by whatever means necessary. Most strikingly, another 30% preferred higher frequencies of apheresis.

[Benefit Assessment for Examination and Treatment Methods with Medical Devices of High Hisk: Trade-off between Patient Benefit, Evidence and Access]. / Nutzenbewertung für Untersuchungs- und Behandlungsmethoden mit Medizinprodukten hoher Klassen: Die Abwägung von Patientennutzen, Evidenz und Zugang.

The lately inured § 137 h SGB V aims to assess the benefit of new examination and treatment methods with medical devices of class IIb and III. In the future, the decision on the reimbursement eligibility will be marked by high requirements in terms of documentation of benefits and harm. The objective of benefit assessment is the operationalization of benefit to patients. A comparative determination of benefit enables rational decision by regulatory authorities. The process of benefit assessment should guarantee transparent decision-making, and the underlying medical and health economic fundamentals should be documented. In principle, benefit assessment can be divided into 3 phases: measuring causal effects of an intervention, assessment of the measured effects and decision on reimbursement based on the aggregation of an overall benefit. To address the peculiarities of medical devices in this process, adaptive study designs, MCDA and adaptive benefit assessment provide a sustainable concept for rapid access by patients to innovative treatments of high quality and safety.

Patient-Focused Benefit-Risk Analysis to Inform Regulatory Decisions: The European Union Perspective.

Regulatory decisions are often based on multiple clinical end points, but the perspectives used to judge the relative importance of those end points are predominantly those of expert decision makers rather than of the patient. However, there is a growing awareness that active patient and public participation can improve decision making, increase acceptance of decisions, and improve adherence to treatments. The assessment of risk versus benefit requires not only information on clinical outcomes but also value judgments about which outcomes are important and whether the potential benefits outweigh the harms. There are a number of mechanisms for capturing the input of patients, and regulatory bodies within the European Union are participating in several initiatives. These can include patients directly participating in the regulatory decision-making process or using information derived from patients in empirical studies as part of the evidence considered. One promising method that is being explored is the elicitation of "patient preferences." Preferences, in this context, refer to the individual's evaluation of health outcomes and can be understood as statements regarding the relative desirability of a range of treatment options, treatment characteristics, and health states. Several methods for preference measurement have been proposed, and pilot studies have been undertaken to use patient preference information in regulatory decision making. This article describes how preferences are currently being considered in the benefit-risk assessment context, and shows how different methods of preference elicitation are used to support decision making within the European context.

[Involving patients, the insured and the general public in healthcare decision making]. / Patienten- und Bürgerpartizipation in der Entscheidungsfindung im Gesundheitswesen insbesondere bei der Bewertung von Arzneimitteln.

No doubt, the public should be involved in healthcare decision making, especially when decision makers from politics and self-government agencies are faced with the difficult task of setting priorities. There is a general consensus on the need for a stronger patient centeredness, even in HTA processes, and internationally different ways of public participation are discussed and tested in decision making processes. This paper describes how the public can be involved in different decision situations, and it shows how preference measurement methods are currently being used in an international context to support decision making. It distinguishes between different levels of decision making on health technologies: approval, assessment, pricing, and finally utilization. The range of participation efforts extends from qualitative surveys of patients' needs (Citizen Councils of NICE in the UK) to science-based documentation of quantitative patient preferences, such as in the current pilot projects of the FDA in the US and the EMA at the European level. Possible approaches for the elicitation and documentation of preference structures and trade-offs in relation to alternate health technologies are decision aids, such as multi-criteria decision analysis (MCDA), that provide the necessary information for weighting and prioritizing decision criteria.

A Review on Methods of Risk Adjustment and their Use in Integrated Healthcare Systems.

INTRODUCTION: Effective risk adjustment is an aspect that is more and more given weight on the background of competitive health insurance systems and vital healthcare systems. The objective of this review was to obtain an overview of existing models of risk adjustment as well as on crucial weights in risk adjustment. Moreover, the predictive performance of selected methods in international healthcare systems should be analysed. THEORY AND METHODS: A comprehensive, systematic literature review on methods of risk adjustment was conducted in terms of an encompassing, interdisciplinary examination of the related disciplines. RESULTS: In general, several distinctions can be made: in terms of risk horizons, in terms of risk factors or in terms of the combination of indicators included. Within these, another differentiation by three levels seems reasonable: methods based on mortality risks, methods based on morbidity risks as well as those based on information on (self-reported) health status. CONCLUSIONS AND DISCUSSION: After the final examination of different methods of risk adjustment it was shown that the methodology used to adjust risks varies. The models differ greatly in terms of their included morbidity indicators. The findings of this review can be used in the evaluation of integrated healthcare delivery systems and can be integrated into quality- and patient-oriented reimbursement of care providers in the design of healthcare contracts.

Chronic pain patients' treatment preferences: a discrete-choice experiment.

OBJECTIVE: The objective of this study was to identify, document, and weight attributes of a pain medication that are relevant from the perspective of patients with chronic pain. Within the sub-population of patients suffering from "chronic neuropathic pain", three groups were analyzed in depth: patients with neuropathic back pain, patients with painful diabetic polyneuropathy, and patients suffering from pain due to post-herpetic neuralgia. The central question was: "On which features do patients base their assessment of pain medications and which features are most useful in the process of evaluating and selecting possible therapies?" METHODS: A detailed literature review, focus groups with patients, and face-to-face interviews with widely recognized experts for pain treatment were conducted to identify relevant treatment attributes of a pain medication. A pre-test was conducted to verify the structure of relevant and dominant attributes using factor analyses by evaluating the most frequently mentioned representatives of each factor. The Discrete-Choice Experiment (DCE) used a survey based on self-reported patient data including socio-demographics and specific parameters concerning pain treatment. Furthermore, the neuropathic pain component was determined in all patients based on their scoring in the painDETECT(®) questionnaire. For statistical data analysis of the DCE, a random effect logit model was used and coefficients were presented. RESULTS: A total of 1,324 German patients participated in the survey, of whom 44 % suffered from neuropathic back pain (including mixed pain syndrome), 10 % complained about diabetic polyneuropathy, and 4 % reported pain due to post-herpetic neuralgia. A total of 36 single quality aspects of pain treatment, detected in the qualitative survey, were grouped in 7 dimensions by factor analysis. These 7 dimensions were used as attributes for the DCE. The DCE model resulted in the following ranking of relevant attributes for treatment decision: "no character change", "less nausea and vomiting", "pain reduction" (coefficient: >0.9 for all attributes, "high impact"), "rapid effect", "low risk of addiction" (coefficient ~0.5, "middle impact"), "applicability with comorbidity" (coefficient ~0.3), and "improvement of quality of sleep" (coefficient ~0.25). All attributes were highly significant (p < 0.001). CONCLUSIONS: The results were intended to enable early selection of an individualized pain medication. The results of the study showed that DCE is an appropriate means for the identification of patient preferences when being treated with specific pain medications. Due to the fact that pain perception is subjective in nature, the identification of patients´ preferences will enable therapists to better develop and implement patient-oriented treatment of chronic pain. It is therefore essential to improve the therapists´ understanding of patient preferences in order to make decisions concerning pain treatment. DCE and direct assessment should become valid instruments to elicit treatment preferences in chronic pain.

Patient-centredness in integrated healthcare delivery systems - needs, expectations and priorities for organised healthcare systems.

INTRODUCTION: Patient-centred healthcare is becoming a more significant success factor in the design of integrated healthcare systems. The objective of this study is to structure a patient-relevant hierarchy of needs and expectations for the design of organised healthcare delivery systems. METHODS: A questionnaire with 84 items was conducted with N = 254 healthcare experts and N = 670 patients. Factor analyses were performed using SPSS©18. The number of factors retained was controlled by Kaiser's criterion, validation of screeplots and interpretability of the items. Cronbach's α was used to assess the internal consistency of the subscales. RESULTS: Exploratory factor analysis led to 24 factors in the expert sample and 20 in the patient sample. After analysing the screeplots, confirmatory factor analyses were computed for 7-factor solutions accounting for 42.963% of the total variance and Kaiser-Meyer-Olkin of 0.914 for the patients (experts: 38.427%, Kaiser-Meyer-Olkin = 0.797). Cronbach's α ranged between 0.899 and 0.756. Based on the analysis, coordinated care could be differentiated into seven dimensions: access, data and information, service and infrastructure, professional care, interpersonal care, individualised care, continuity and coordination. CONCLUSION AND DISCUSSION: The study provides insight into patient and experts expectations towards the organisation of integrated healthcare delivery systems. If providers and payers can take into account patient needs and expectations while implementing innovative healthcare delivery systems, greater acceptance and satisfaction will be achieved. In the best case, this will lead to better adherence resulting in better clinical outcomes.

Patient preferences versus physicians' judgement: does it make a difference in healthcare decision making?

Clinicians and public health experts make evidence-based decisions for individual patients, patient groups and even whole populations. In addition to the principles of internal and external validity (evidence), patient preferences must also influence decision making. Great Britain, Australia and Germany are currently discussing methods and procedures for valuing patient preferences in regulatory (authorization and pricing) and in health policy decision making. However, many questions remain on how to best balance patient and public preferences with physicians' judgement in healthcare and health policy decision making. For example, how to define evaluation criteria regarding the perceived value from a patient's perspective? How do physicians' fact-based opinions also reflect patients' preferences based on personal values? Can empirically grounded theories explain differences between patients and experts-and, if so, how? This article aims to identify and compare studies that used different preference elicitation methods and to highlight differences between patient and physician preferences. Therefore, studies comparing patient preferences and physician judgements were analysed in a review. This review shows a limited amount of literature analysing and comparing patient and physician preferences for healthcare interventions and outcomes. Moreover, it shows that methodology used to compare preferences is diverse. A total of 46 studies used the following methods-discrete-choice experiments, conjoint analyses, standard gamble, time trade-offs and paired comparisons-to compare patient preferences with doctor judgements. All studies were published between 1985 and 2011. Most studies reveal a disparity between the preferences of actual patients and those of physicians. For most conditions, physicians underestimated the impact of intervention characteristics on patients' decision making. Differentiated perceptions may reflect ineffective communication between the provider and the patient. This in turn may keep physicians from fully appreciating the impact of certain medical conditions on patient preferences. Because differences exist between physicians' judgement and patient preferences, it is important to incorporate the needs and wants of the patient into treatment decisions.