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This paper describes the first year of a national programme supporting implementation of one of the key policy initiatives forming part of the programme of health reform in England, practice‐based commissioning (PBC). The paper presents an audit of service redesign initiatives based on the first six months' work of 27 sites in the first wave of the programme, and discusses the early practical learning about the implementation of PBC by both participants and stakeholders. The role of the programme in facilitating two‐way links between policy development and practical implementation is highlighted, and the development of the programme, and other parallel learning routes, to meet the emerging needs of particular groups in relation to practice‐based commissioning is described.

The purpose of this research paper is to explore the determinants of patients' service choices between telephone consultation and text consultation in online health communities (OHCs).

This study utilized an empirical model based on the elaboration likelihood model and examined the effect of information, regarding service quality (the central route) and service price (the peripheral route), using online health consultation data from one of the largest OHCs in China.

The logistic regression results indicated that both physician- and patient-generated information can influence the patients' service choices; service price signals will lead patients to cheaper options. However, individual motivations, disease risk and consulting experience change a patients' information processing regarding central and peripheral cues.

Previous researchers have investigated the mechanism of patient behavior in OHCs; however, the researchers have not focused on the patients' choices regarding the multiple health services provided in OHCs. The findings of this study have theoretical and practical implications for future researchers, OHC designers and physicians.

The impact of image is widely investigated in various research fields. However, its effect in online health communities is rarely studied. In this research, the authors develop a theoretical model to assess the impact of physicians' image on patients' choices in online health communities.

The authors developed a web crawler based on R language program to collect more than 40,000 physicians' images and other related information from their homepages in Haodf.com–a leading online health community in China. The features of physicians' images are computed by Face++ Application Programming Interface (API) through the following variables: beauty, smile and skin status.

The empirical results derive the following findings: (1) physician's beauty or physical attractiveness has no significant effect on patients’ choice; (2) Smile has a positive effect on patients’ choices; (3) Physician's skin status also positively affects patients' choices; (4) Physician's professional capital strengthens the effect of beauty, smile and skin status on patients' choices; (5) Beauty and skin status are the substitutes for each other, and smile and skin status are the substitutes for each other too.

Also, this study provides implications for both physicians and online health community platform managers.

This study provides new evidence in understanding the impact of physician's online image and contributes to the literature on signaling theory, impression management theory and patients' choices.

Despite the prevalent use of professional status and service feedback in online healthcare markets, the potential interaction relationship between two types of information is still unknown. This study used the signaling theory to examine the substitute relationship between professional status and service feedback in patients' doctor choice, as well as the moderating effect of illness severity.

To test the paper's hypotheses, we constructed a panel data model using 418 doctors' data collected over a period of six months from an online healthcare market in China. Then, according to the results of the Hausman test, we estimated a fixed-effects model of patients' choice in online healthcare markets.

The empirical results showed that the effect of a doctor's professional status and service feedback on a patient's doctor choice was substitutable. Moreover, patients' illness severity played a moderating role, in that the influence of professional status on a patient with high-severity illness was higher than that on a patient with low-severity illness, whereas the influence of service feedback on a patient with low-severity illness was higher than that of a patient with high-severity illness. In addition, we found that illness severity negatively moderated the substitute relationship between professional status and service feedback on a patient's choice.

These findings not only contribute to signaling theory and research on online healthcare markets, but also help us understand the importance of professional status and service feedback on a patient's choice when seeking a doctor online.

The purpose of this paper is to explore the influence of a physician’s prosocial behavior on a patient's choices in the online health community (OHC) context. Moreover, the authors explore how such effects differ across different online word-of-mouth (WOM) and professional titles.

Guided by the motivation, opportunity and ability (MOA) framework, this paper develops hypotheses and an econometric model. Then this paper used spline regression to test hypotheses on 6,204 physicians at The Good Doctor (www.Haodf.com), which is one of the largest Chinese OHCs. The authors conducted the propensity score matching and difference-in-difference method (PSM-DID) to address the concern about the bias caused by possible endogeneity concerns.

The authors’ results show that a physician’s prosocial behavior improves a patient's choice only when the strength of a physician’s prosocial behavior is below the tipping point. In addition, the influence of a physician’s prosocial behavior is heterogeneous for physicians with different online WOM and professional titles. For physicians with higher online WOM, the effect of a physician's prosocial behaviors on a patient's choice is positive, while for physicians with lower online WOM, a physician’s prosocial behavior has no impact on a patient’s choice. For physicians with higher professional titles, the quantity of a physician’s prosocial behavior has a positive impact on a patient’s choice, while for physicians with lower professional titles the quality of a physician’s prosocial behavior has a positive impact on a patient’s choice.

This study contributes new knowledge and provides new perspectives to study a patient's choice by addressing the importance of physician's prosocial behavior. With the effort of explicitly explaining the complex mechanisms, this study encourages physicians' engagement in a physician’s prosocial behavior and gives some implications on how to perform the behaviors strategically.

The idea that patients should be informed about the benefits and risks of treatment options and involved in decisions about their care is, to many people, appealing and sensible. However, it has important implications. This paper briefly considers two motivations for involving patients in clinical decisions and explores some of the issues raised by these. It then makes some practical suggestions for those wanting to provide information to support patient involvement. The paper emphasizes that although the provision of more good‐quality information to patients is widely accepted to be a priority, it is not always a straightforward matter and warrants critical consideration. Substantial resources may be needed if it is to be done well.

Consumer confusion is an emerging phenomenon of interest that significantly drives choice behaviour. Considering the dearth of scholarly focus on confusion faced by consumers in a healthcare setting, this paper aims to conceptualize and validate a patient confusion model consisting of its drivers and outcomes.

Drawing upon adaptive decision-making framework and consumer confusion literature, patient confusion model has been developed. Empirical data of 310 patients from three private sector hospitals in India was collected through pen and paper survey administration. The hypothesized patient confusion model was tested using partial least squares structural equation modelling (PLS-SEM) to derive confirmatory results.

The results confirm the role of decision-making variables such as information overload, information similarity, information ambiguity, information asymmetry, patient involvement and physician-patient communication in the occurrence of patient confusion. A significant impact of confusion on switching intention was also confirmed, providing insights for healthcare managers.

The effect of confusion on switching intention of consumers found through the present study holds significant implications from a healthcare management standpoint. Dissemination of credible information, improved communication between doctors and patients and creation of organized channels of health information provision also represent some of the notable implications for healthcare managers to mitigate patient confusion.

This study presents an empirically validated model of patient confusion creating a research agenda for theory development in this emerging area. Consumer confusion represents a core consumer behaviour problem that is of utmost significance in the healthcare sector. This paper is one of the first and early attempts to address this research problem.

In healthcare, there is limited knowledge of and experience with patient choice management. The purpose of this paper is to focus on patient choice, apply and test demand-supply-based operating (DSO) logic integrated with clinical setting in clarifying choice contexts, investigate patient’s choice-making at different contexts and suggest context-based choice architectures to manage and develop patient choice.

Prenatal screening and testing in the Helsinki and Uusimaa Hospital District (HUS), Finland, was taken as an example. Choice points were contextualized by using the DSO framework. Women’s reflections, behaviors and experience at different choice contexts were studied by interviewing women participating in prenatal screening and testing. Semi-structured interview data were processed by thematic analysis.

By applying DSO logic, four choice contexts (prevention, cure, electives and continuous care) were relevant in the prenatal screening and testing episode. Women had different choice-making in prevention and cure mode contexts regarding choice activeness, information needs, social influence, preferences, emotion status and choice-making difficulty. Default choice was widely accepted by women in prevention mode and individual counseling can help women make informed choice in cure mode.

The authors apply the DSO model to contextualize the patient choice in one care episode and compare patient choice-making at different contexts. The authors also suggest the possible context-based choice architectures to manage and promote patient choice