Effects of chlorhexidine gluconate oral care on hospital mortality : a hospital-wide, observational cohort study

Chlorhexidine oral care is widely used in critically and non-critically ill hospitalized patients to maintain oral health. We investigated the effect of chlorhexidine oral care on mortality in a general hospitalized population. In this single-center, retrospective, hospital-wide, observational cohort study we included adult hospitalized patients (2012-2014). Mortality associated with chlorhexidine oral care was assessed by logistic regression analysis. A threshold cumulative dose of 300 mg served as a dichotomic proxy for chlorhexidine exposure. We adjusted for demographics, diagnostic category, and risk of mortality expressed in four categories (minor, moderate, major, and extreme). The study cohort included 82,274 patients of which 11,133 (14%) received chlorhexidine oral care. Low-level exposure to chlorhexidine oral care (ae 300 mg) was associated with increased risk of death [odds ratio (OR) 2.61; 95% confidence interval (CI) 2.32-2.92]. This association was stronger among patients with a lower risk of death: OR 5.50 (95% CI 4.51-6.71) with minor/moderate risk, OR 2.33 (95% CI 1.96-2.78) with a major risk, and a not significant OR 1.13 (95% CI 0.90-1.41) with an extreme risk of mortality. Similar observations were made for high-level exposure (> 300 mg). No harmful effect was observed in ventilated and non-ventilated ICU patients. Increased risk of death was observed in patients who did not receive mechanical ventilation and were not admitted to ICUs. The adjusted number of patients needed to be exposed to result in one additional fatality case was 47.1 (95% CI 45.2-49.1). These data argue against the indiscriminate widespread use of chlorhexidine oral care in hospitalized patients, in the absence of proven benefit in specific populations

Patient empowerment in Flemish hospital wards : a cross-sectional study

Objective: Measuring empowerment of patients on Flemish hospital wards by the short form of the Patient Activation Measure (PAM-13) and exploring the association between patient empowerment and patient-centred care, health literacy, patient- and context-related characteristics. Methods: Secondary analysis of data collected in nine regional hospitals and one university hospital in Flanders between February and June 2016. Patients needed to be admitted for a least 1 day, aged 18 years or over, and mentally competent with adequate ability to speak and read the Dutch language. Independent t-tests, one-way ANOVA and multivariable regression analysis were performed. Results: Mean empowerment was 58. Of the 670 patients, 22.7% tended to be unprepared to play an active role in their health care, 22.2% were struggling to manage own health, 39.4% reported to take action to maintain and improve own health, and 15.7% reported having confidence to perform adequate behaviours in most circumstances. Multivariable analysis showed that patients living together with family, a partner or a friend (p = 0.018), with higher health literacy (p < 0.001), and with higher perceptions of individuality in patients' care (p < 0.001) had higher empowerment scores. Conclusion: The multivariable analysis found three variables associated with patient empowerment and provided empirical evidence for the interrelatedness between patient-centred care and patient empowerment. Future research should use a clear framework to make sure that all relevant determinants of patient empowerment are included. Interventions to improve patient empowerment should incorporate patient characteristics and elements of both health literacy and patient-centred care

The patient perspective in health care networks

Background: Health care organization is entering a new age. Focus is increasingly shifting from individual health care institutions to interorganizational collaboration and health care networks. Much hope is set on such networks which have been argued to improve economic efficiency and quality of care. However, this does not automatically mean they are always ethically justified. A relevant question that remains is what ethical obligations or duties one can ascribe to these networks especially because networks involve many risks. Due to their often amorphous and complex structure, collective responsibility and accountability may increase while individual responsibility goes down. Main body: We argue that a business ethics approach to ethical obligations for health care networks, is problematic and we propose to opt for a patient perspective. Using the classic four principles of biomedical ethics (justice, nonmaleficence, beneficence and autonomy) it is possible to identify specific ethical duties. Based on the principle of justice, health care networks have an ethical duty to provide just and fair access for all patients and to be transparent to patients about how access is regulated. The principle of nonmaleficence implies an obligation to guarantee patient safety, whereas the principle of beneficence implies an obligation for health care networks to guarantee continuity of care in all its dimensions. Finally, the principle of autonomy is translated into a specific obligation to promote and respect patient choice. Networks that fail to meet any of these conditions are suspect and cannot be justified ethically. Conclusions: Faced with daunting challenges, the health care system is changing rapidly. Currently many hopes ride on integrated care and broad health care networks. Such networks are the topic of empirical debate, but more attention should be given to the ethical aspects. Health care networks raise new and pressing ethical issues and we are in need of a framework for assessing how and when such networks are justified

Organizing health care networks : balancing markets, government and civil society

Much is changing in health care organization today. A perspective or paradigm that is gaining ever increasing momentum is that of translational, extramural and integrated care. Current research suggests many potential benefits for integrated care and health care networks but the ethical issues are less frequently emphasized. Showing that integrated care can be beneficial, does not mean it is automatically 'ethically' justified. We will argue for three ethical requirements such health care networks should meet. Subsequently we will look at the mechanisms driving the formation of networks and examine how these can cause networks to meet or fail to meet these ethical requirements or obligations. The three mechanisms we will examine are government, civil society and market mechanisms, which, we argue, should be balanced properly. Each mechanism is able to provide a relevant ethical perspective to health care networks. However, when the balance is skewed towards a single mechanism, health care networks might fail to promote one or more of the ethical requirements

Challenges in turning a great idea into great health policy : the case of integrated care

BackgroundIn the organization of health care and health care systems, there is an increasing trend towards integrated care. Policy-makers from different countries are creating policies intended to promote cooperation and collaboration between health care providers, while facilitating the integration of different health care services. Hopes are high, as such collaboration and integration of care are believed to save resources and improve quality. However, policy-makers are likely to encounter various challenges and limitations when attempting to turn these great ideas into effective policies. In this paper, we look into these challenges.Main bodyWe argue that the organization of health care and integrated care is of public concern, and should thus be of crucial interest to policy-makers. We highlight three challenges or limitations likely to be encountered by policy-makers in integrated care. These are: (1) conceptual challenges; (2) empirical/methodological challenges; and (3) resource challenges. We will argue that it is still unclear what integrated care means and how we should measure it. 'Integrated care' is a single label that can refer to a great number of different processes. It can describe the integration of care for individual patients, the integration of services aimed at particular patient groups or particular conditions, or it can refer to institution-wide collaborations between different health care providers. We subsequently argue that health reform inevitably possesses a political context that should be taken into account. We also show how evidence supporting integrated care may not guarantee success in every context. Finally, we will discuss how promoting collaboration and integration might actually demand more resources. In the final section, we look at three different paradigmatic examples of integrated care policy: Norway, the UK's NHS, and Belgium.ConclusionsThere seems widespread agreement that collaboration and integration are the way forward for health care and health care systems. Nevertheless, we argue that policy-makers should remain careful; they should carefully consider what they hope to achieve, the amount of resources they are willing to invest, and how they will evaluate the success of their policy

The influence of nurses' demographics on patient participation in hospitals : a cross-sectional study

Background: Patient participation is an important issue in contemporary healthcare as it improves quality of care and enhances positive health outcomes. The participation of patients is mainly initiated by the nurses' willingness to share their power and responsibility, but knowledge on nurses' demographic characteristics influencing this behavior is nonexistent. This knowledge is essential to understand and improve patient participation. Aim: To determine if nurses' demographic characteristics influence their willingness to engage in patient participation. Methods: A cross-sectional multicenter study in 22 general and three university hospitals with 997 nurses was performed. The Patient Participation Culture Tool for healthcare workers, which measures patient participation behavior, was used. Multilevel analysis, taking into account the difference in wards and hospitals, was used to identify the influence of demographic characteristics. Results: A position as supervisor (range: p < .001-.028) and a higher level of education (range: p = <.001-.012) show significant higher scores. Younger nurses seem to be more reluctant in accepting a collaborative patient role (p = .002) and coping with more active patient behavior (p < .001). This new role was less accepted by nurses on geriatric wards (p = .013), who also showed less sharing of information with their patients (p < .001). Linking Evidence to Action: Age and level of education influence nurses' willingness to share power and responsibility with their patients, perhaps indicating that patient participation behavior is an advanced nursing skill and multifaceted interventions, are needed for optimal implementation. Moreover, supervising nurses have different perceptions on patient participation and possibly regard patient participation as an easier task than their team members. This could lead to misunderstandings about the expectations toward patient participation in daily practice, leading to struggles with their nursing staff. Both findings implicate that implementing patient participation on a wide scale is more difficult than expected, which is conflicting with the widespread societal demand for more participation

Using structured pathology data to predict hospital-wide mortality at admission

Early prediction of in-hospital mortality can improve patient outcome. Current prediction models for in-hospital mortality focus mainly on specific pathologies. Structured pathology data is hospital-wide readily available and is primarily used for e.g. financing purposes. We aim to build a predictive model at admission using the International Classification of Diseases (ICD) codes as predictors and investigate the effect of the self-evident DNR ("Do Not Resuscitate") diagnosis codes and palliative care codes. We compare the models using ICD-10-CM codes with Risk of Mortality (RoM) and Charlson Comorbidity Index (CCI) as predictors using the Random Forests modeling approach. We use the Present on Admission flag to distinguish which diagnoses are present on admission. The study is performed in a single center (Ghent University Hospital) with the inclusion of 36 368 patients, all discharged in 2017. Our model at admission using ICD-10-CM codes (AUCROC = 0.9477) outperforms the model using RoM (AUCROC = 0.8797 and CCI (AUCROC = 0.7435). We confirmed that DNR and palliative care codes have a strong impact on the model resulting in a decrease of 7% for the ICD model (AUCROC = 0.8791) at admission. We therefore conclude that a model with a sufficient predictive performance can be derived from structured pathology data, and if real-time available, can serve as a prerequisite to develop a practical clinical decision support system for physicians