基于微信小程序的精准健康管理平台的设计与实现

目的满足体检者个性化的健康管理服务需求,提高医护人员的工作效率。方法应用人工智能、移动互联网、物联网等新一代信息技术,基于健康体检数据、日常监测数据、区域全民健康信息化平台的健康数据,以软件工程理论和方法为指导,设计并实现一个基于微信小程序的精准健康管理平台。结果平台的应用为体检者提供了个性化的精准健康管理服务,提升了医院的健康管理服务水平和效率。结论在公众对优质健康管理服务需求增加但医疗资源紧缺的矛盾下,专业的医疗机构利用新一代信息技术提供个性化的精准健康管理服务,能以较小的成本创造出较大的社会效益。     

社区卫生服务+社工服务在居家养老中的应用

目的探讨社区卫生服务联合社工服务的个性化居家养老服务的应用效果。方法选择2016年3月-2017年2月接受为期至少6个月的社区卫生服务联合社工服务的居家养老者835例作为研究对象,在入组前及完成社区卫生服务联合社工服务的个性化居家养老6个月后对研究对象作全数的问卷调查,调查其健康知识知晓、满意度及不同群体人群对社区卫生服务的需求。并与社区卫生服务联合社工服务实施前相关健康知识知晓率、满意度等进行比较。结果个性化居家养老服务后健康知识知晓率、满意度均明显高于个性化居家养老服务前,差异有统计学意义(P0.05)。结论接受以社区卫生服务联合社工服务的居家养老模式能够提高参养老人对健康保健知识的掌握水平及满意度。     

个性化医疗服务类型及相关数据资源研究

个性化医疗可针对患者个体差异选择并提供最佳诊疗方案,能有效提升医疗服务质量,降低医疗费用。文章在介绍个性化医疗相关概念的基础上,分析了个性化医疗的服务类型及支撑个性化医疗的相关数据资源,如基因数据、电子病历、健康档案及健康监测信息等,并对实现信息资源整合,促进个性化医疗服务的开展,提出了相关对策和建议。     

健康物联网与健康云

文章介绍了健康物联网和健康云的基本概念、组成、功能和关键技术,并给出了健康服务的愿景。健康物联网和健康云将使未来的健康服务不再是被动地满足用户的需求,而是主动感知用户的健康状况,并及时进行智能决策,及时为用户提供个性化的贴身健康服务。     

苏州市部分社区开展健康管理情况分析

健康量化管理服务模式的过程是通过健康信息收集，早期发现健康危险因素；健康评估，提供个性化的健康危险因素评价；健康危险因素干预，通过规范化的服务和个体化的督导，使健康计划变成服务对象的实际行动。核心是“能量平衡、有效运动、量化管理”^[1]，应用能量监测仪和饮食运动管理软件技术，对参与者进行个性化健康指导。     

精神疾病患者回归社会的个性化教育对策——基于某县精神康复医院的调查

精神障碍患者回归社会,目前存在的问题主要有:服务能力不足,健康教育方法单一,教育前准备不充分,教育对象范围狭窄,教育效果较差。要改进、完善精神障碍患者回归社会的个性化教育对策,即强化服务能力建设,开展健康教育评估,制定个性化健康教育计划,更新健康教育形式,拓展健康教育范围。     

互联网+社区健康管理服务模式探讨

"互联网+"为创新社区健康管理服务提供了新的思路,针对目前社区健康管理存在的问题,提出利用移动互联网、物联网、智能传感技术、云计算技术、大数据技术等现代信息化技术手段,建立以社区健康服务团队为基础,以社区健康管理服务系统为依托,同时与区域人口健康信息平台网络化联接的互联网+社区健康管理服务模式,面向社区居民提供个性化、专业化的智慧健康管理服务。     

基于物联网的智慧型医院管理服务模式探析

随着移动互联的普及以及人们对健康的重视,个性化以及智能化的健康管理成为一种迫切的需求。大型医院作为健康服务机构的核心,必须与时俱进,利用物联网形成一种智慧型管理服务模式,在提供医疗资源支撑的同时,调动社会资源合作分工,共同完成健康管理服务,从而让百姓方便快捷地享受到智慧型管理服务带来的巨大收益。     

融合"健康管理"理念实施连贯性的体检护理服务

目的 为适应健康管理模式的要求,探讨连贯性的体检护理服务.方法 引入健康管理的理念,开展体检前、体检中、体检后的护理服务,整个体检护理服务的全过程以人文关怀为特色,突出个性化的护理,着重连贯性的护理服务.结果 健康管理服务更加到位,体检人员的满意度从95.7%提高到100.0%,提升了体检服务的品牌.结论 实施连贯性的体检护理服务,能有效地提高健康管理的品质.     

电子健康档案建设现状及开放便民应用技术路径研究

对全国电子健康档案建设应用情况进行梳理,分析了跨机构健康信息共享互认、居民个人健康信息整合服务、个性化和精准化健康服务等需求,提出了电子健康档案开放便民应用的设计思路、技术架构、主要功能、安全隐私保护和开放应用等内容,为各地推进电子健康档案规范化建设及开放便民应用提供参考。     

Between hype and hope: What is really at stake with personalized medicine?

Over the last decade, personalized medicine has become a buzz word, which covers a broad spectrum of meanings and generates many different opinions. The purpose of this article is to achieve a better understanding of the reasons why personalized medicine gives rise to such conflicting opinions. We show that a major issue of personalized medicine is the gap existing between its claims and its reality. We then present and analyze different possible reasons for this gap. We propose an hypothesis inspired by the Windelband’s distinction between nomothetic and idiographic methodology. We argue that the fuzzy situation of personalized medicine results from a mix between idiographic claims and nomothetic methodological procedures. Hence we suggest that the current quandary about personalized medicine cannot be solved without getting involved in a discussion about the complex epistemological and methodological status of medicine. To conclude, we show that the Gadamer’s view of medicine as a dialogical process can be fruitfully used and reveals that personalization is not a theoretical task, but a practical one, which takes place within the clinical encounter.     

The promise of personalized medicine: a conversation with Michael Svinte. Interview by Michael Millenson

In early 2004, IBM combined its Healthcare unit, which focused on the technology needs of providers, with its Life Sciences unit, which catered to research scientists. Out of that union was born an "emerging business opportunity" called information-based medicine, in which IBM has already invested tens of millions in the expectation of reaping billions of dollars in revenues. Michael Svinte describes his mission as providing the information technology infrastructure that will enable technologies such as proteomics and molecular imaging to progress from the bench to the bedside, thereby resulting in predictive and personalized health care.     

Linking pharmacogenetics-based diagnostics and drugs for personalized medicine

Progress toward personalized medicine in the five years following the sequencing of the human genome has been slower than many expected. We focus on two potential factors that might be important in explaining this disappointing progress: the limitations of genetic prediction and the lack of appropriate economic incentives. Clinical application of DNA-based and other biomarkers is likely to succeed only on a case-by-case basis, depending on such factors as information content of the biomarker, accuracy of current assessment methods, and effectiveness of available interventions. Both strong intellectual property and value-based, flexible pricing systems will be important in making personalized medicine a reality.     

Defining the balance of risk and benefit in the era of genomics and proteomics

The ability to measure the function of genes and proteins has spawned the construct of personalized medicine, in which patients' own risks and preferences are used to choose diagnostic and therapeutic strategies. The complexity of clinical data required to guide personalized medicine calls for improvements in our system of clinical research, including (1) overhauling it to produce networks that can do adequate-size pragmatic trials; (2) synchronization of regulatory and payment systems to encourage adequate studies; and (3) an investment in education of providers and patients to improve the understanding of the probabilistic predictions forming the basis of personalized medicine.     

Herausforderungen an die klinische Evaluation und Gesundheits?konomie auf dem Weg zur personalisierten Medizin

Healthcare systems across the globe are currently challenged by aging populations, increases in chronic diseases and the difficult task of managing a healthcare budget. In this health economic climate, personalized medicine promises not only an improvement in healthcare delivery but also the possibility of more cost-effective therapies. It is important to remember, however, that personalized medicine has the potential to both increase and decrease costs. Each targeted therapy must be evaluated individually. However, standard clinical trial design is not suitable for personalized therapies. Therefore, both scientists and regulatory authorities will need to accept innovative study designs in order to validate personalized therapies. Hence correct economic evaluations are difficult to carry out due to lack of clear clinical evidence, longitudinal accounting and experience with patient/clinician behavior in the context of personalized medicine. In terms of reimbursement, payers, pharmaceutical companies and companion diagnostic manufacturers will also need to explore creative risk-sharing concepts. Germany is no exception to the challenges that face personalized medicine and for personalized medicine to really become the future of medicine many health economic challenges first need to be overcome. The health economic implications of personalized medicine remain unclear but it is certain that the expansion of targeted therapies in current healthcare systems will create a host of challenges.     

Conceptual and Analytical Considerations toward the Use of Patient-Reported Outcomes in Personalized Medicine

Background

Patient-reported outcomes (PROs) can play an important role in personalized medicine. PROs can be viewed as an important fundamental tool to measure the extent of disease and the effect of treatment at the individual level, because they reflect the self-reported health state of the patient directly. However, their effective integration in personalized medicine requires addressing certain conceptual and methodological challenges, including instrument development and analytical issues.

Objectives

To evaluate methodological issues, such as multiple comparisons, missing data, and modeling approaches, associated with the analysis of data related to PRO and personalized medicine to further our understanding on the role of PRO data in personalized medicine.

Discussion

There is a growing recognition of the role of PROs in medical research, but their potential use in customizing healthcare is not widely appreciated. Emerging insights into the genetic basis of PROs could potentially lead to new pathways that may improve patient care. Knowledge of the biologic pathways through which the various genetic predispositions propel people toward negative or away from positive health experiences may ultimately transform healthcare. Understanding and addressing the conceptual and methodological issues in PROs and personalized medicine are expected to enhance the emerging area of personalized medicine and to improve patient care. This article addresses relevant concerns that need to be considered for effective integration of PROs in personalized medicine, with particular reference to conceptual and analytical issues that routinely arise with personalized medicine and PRO data. Some of these issues, including multiplicity problems, handling of missing values-and modeling approaches, are common to both areas. It is hoped that this article will help to stimulate further research to advance our understanding of the role of PRO data in personalized medicine.

Conclusion

A robust conceptual framework to incorporate PROs into personalized medicine can provide fertile opportunity to bring these two areas even closer and to enhance the way a specific treatment is attuned and delivered to address patient care and patient needs.Personalized medicine aims to assist healthcare providers to individualize a patient treatment based on the patient''s attributes, which may include biomarkers, genetics, demographic characteristics, and other covariates. Much progress has been made in recent years in the translational research areas of genomics, proteomics, and metabolomics, and several biomarkers have been identified for a number of important diseases, including atherosclerosis, cancer, and rheumatoid arthritis. Many of these biomarkers are now being studied in clinical trials to identify subgroups of patients who best benefit from a given therapy. However, despite the growing importance of patient-reported outcomes (PROs) in medical research, their role in customizing healthcare is not widely recognized. Information solicited directly from patients about their health status or health-related quality of life (QOL), disease burden, or other aspects of their disease or treatment should be an essential component of any treatment paradigm that relies on genetic and other patient-specific information to ensure optimal care delivery for the individual patient.Broadly defined, a PRO is any report on the status of a patient''s clinical condition that comes directly from the patient, without interpretation of the patient''s response by a clinician or by anyone else. “Patient-reported outcomes” is an umbrella term that includes a variety of subjective outcomes, such as pain, fatigue, depression, aspects of well-being (eg, physical, functional, psychological), treatment satisfaction, health-related QOL, and physical symptoms, such as nausea and vomiting. PROs are often relevant for studying different conditions—such as pain, erectile dysfunction, fatigue, migraine, anxiety, and depression—that cannot be assessed adequately without input from the patient on the impact of the disease or the treatment.To be useful to patients and to other decision makers (eg, physicians, regulatory agencies, reimbursement authorities) who are stakeholders in medical care, a PRO must undergo a validation process to confirm that it is reliably measuring what it is intended to measure. The focus of this article is on the analysis and reporting of PRO data derived from standardized PRO instruments for use mainly in clinical research, such as in clinical trials and in drug development.In recent years, there has been growing evidence for the impact of genetics on QOL and on PROs.1–7 Most notably, Raat and colleagues describe the value of a population-based prospective cohort study from fetal life and beyond in Rotterdam, the Netherlands, as a template that enables candidate gene study and genome-wide association study regarding the QOL of mothers and their young children.3 Although several articles refer to QOL when the focus is on groups of individuals, be they patients or not,1–3 overall considerations about QOL in the context of personalized medicine are equally applicable to the more general term “PRO” when referring to any health-related report coming directly from the patient. Rijsdijk and colleagues found that the overall heritability of psychosocial distress ranged from 20% to 44% in their study.4 In other studies, evidence of genetic influences has been reported for PROs.5,6 Although much research is still needed to determine the precise proportion of variability in PRO that is explained by genetic factors, considerable progress has been seen in some areas, such as in oncology, to quantify the association between polymorphisms and PROs.7Personalized medicine involves the customization of healthcare tailored to the individual patient by use of genetic and other information, including PROs such as symptoms, functional status, treatment satisfaction, and health-related QOL. Yet methodological advancements needed for PROs and genetics are lacking. Insights into the genetics of PROs will ultimately allow early identification of patients susceptible to PRO deficits, as well as to target care in advance. Therefore, by unraveling the genetic understandings of PROs (eg, what specific single-nucleotide polymorphisms, on which specific genes, are associated with pain), researchers will have a greater understanding of diagnosis and treatment management for an individual patient—an understanding that has the potential to lead to improved survival, PRO assessments, and health service delivery.

KEY POINTS

• ▸ “Patient-reported outcomes” (PROs) refers to any report on the status of a patient''s clinical condition that comes directly from the patient, without interpretation by a clinician or by anyone else.
• ▸ Personalized medicine aims to individualize a patient treatment based on the patient''s unique attributes.
• ▸ By identifying patients who are susceptible to certain poor aspects of patient-reported health status (eg, pain), healthcare stakeholders will be in a better position to target preventive strategies or provide specific interventions.
• ▸ PROs must undergo a validation process to be useful to patients and stakeholders in medical care.
• ▸ A major step in the incorporation of PROs in personalized medicine is the establishment and use of standardized instruments that have proven reliability and validity.
• ▸ The most important challenge in personalized medicine is to establish a statistical framework for data analysis that links outcomes to concepts of interest, and subsequently links those to specific aspects of patient-reported health status.
• ▸ Incorporating PROs into personalized medicine can provide information to enhance patient care.

Effective use of PRO data in the context of personalized medicine entails a careful evaluation of conceptual and methodological issues associated with PRO and with personalized medicine. Guidelines and best practices have been developed to strengthen the value of the data from those two fields.8–12 The issues surrounding PRO data, which are generally used to quantify PROs in a structured way, have been a particular focus of concerted research.8 Regulatory guidelines and other guidance documents have also been issued to address several central concerns.9,10Emerging insights into the genetic basis of PROs could potentially lead to new pathways to help to improve patient care. Knowledge of the biologic pathways through which the various genetic predispositions propel people toward negative, or away from positive, health experiences may ultimately transform healthcare. By identifying patients who are susceptible to certain poor aspects of patient-reported health status (eg, pain), healthcare stakeholders will be in a better position to target preventive strategies or provide specific interventions, such as pharmacologic treatment, psychological counseling, lifestyle and behavioral changes, or a combination thereof. The risk of not making PROs an integral component in the genetic profile may have, by not imposing an effective targeted early intervention, a profound and untoward impact wherein individuals experience substantially diminished well-being. Under such a circumstance, healthcare providers would miss the opportunity to effectively screen patients to discover who would likely experience PRO deficits associated with a disease or its treatment or both. Consequently, treatment decision-making and patient care would be compromised.Furthermore, genetic research shares some of the often-encountered issues that arise in PRO studies, including multiplicity of end points, missing data, reliability, and validity.11 For genetic research, the need for methodological standards as a resource for researchers has been the focus of a recent study.12The role of QOL in personalized medicine has also garnered increasing attention, in part as a result of the activities of organizations such as the GENEQOL Consortium, which aims to promote research on biologic mechanisms, potential genes, and genetic variants that may be involved in QOL.13 Advances in that area include summaries on the genetic background of common symptoms and overall well-being.13In this article we consider the role of PRO data in personalized medicine, with a particular reference to analytical issues that routinely arise with personalized medicine and PRO data, including multiplicity problems, missing values, and statistical models. Given the abundance of material relating to personalized medicine, the focus of this article is on the relationship between PRO data analysis and reporting and personalized medicine. Other important aspects of PROs, including data collection and its storage for ease of use in the clinical setting, as well as integration of such data with clinical guidelines of care, are beyond the scope of this article.     

浅议医院图书馆个性化信息服务的必要性及实施策略

医院图书馆在医院临床、科研和教学工作中发挥了重要作用,在高度信息化的网络时代,如何提高医院图书馆的利用效率值得深入研究。鉴于目前网络化时代各种信息资源铺天盖地,因此医院图书馆有义务对各项资源进行归纳整理,提供个性化信息服务。本文从个性化信息服务定义出发,深刻分析了其实行的必要性,并探讨了其实施的各种具体策略,以期能针对不同读者提供不同个性化信息服务,从而大大提高图书馆的使用效率,推动医院科研和临床医疗工作的进度和发展。     

Personalisierte Medizin und individuelle Gesundheitsversorgung

The individualization of medicine and healthcare appears to be following a general societal trend. The terms “personalized medicine” and “personal health” are used to describe this process. Here it must be emphasized that personalized medicine is not limited to pharmacogenomics, but that the spectrum of personalized medicine is much broader. Applications range from individualized diagnostics, patient-specific pharmacological therapy, therapy with individual prostheses and implants to therapy approaches using autologous cells, and from patient model-based therapy in the operating room, electronic patient records through to the individual care of patients in their home environment with the use of technical systems and services. Although in some areas practical solutions have already been found, most applications will not be fully developed for many years to come. Medical and information technology are essential to personalized medicine and personal health, each driving the other forward.     

Comparative effectiveness and personalized medicine: evolving together or apart?

Comparative effectiveness research and personalized medicine can at first appear to be at odds with each other. This research initially compares the overall benefits of one therapeutic approach with those of another for the majority of patients, while personalized medicine identifies the subsets of patients who could benefit based on personal characteristics such as genetics. But because comparative effectiveness research typically enrolls heterogeneous patient populations, it can uncover subpopulations that might benefit most from particular treatments. Thus, comparative effectiveness research can help discern the appropriate role of personalized medicine in improving health care outcomes and rationalizing costs.     

Challenges in the Development and Reimbursement of Personalized Medicine—Payer and Manufacturer Perspectives and Implications for Health Economics and Outcomes Research: A Report of the ISPOR Personalized Medicine Special Interest Group

BackgroundPersonalized medicine technologies can improve individual health by delivering the right dose of the right drug to the right patient at the right time but create challenges in deciding which technologies offer sufficient value to justify widespread diffusion. Personalized medicine technologies, however, do not neatly fit into existing health technology assessment and reimbursement processes.ObjectivesIn this article, the Personalized Medicine Special Interest Group of the International Society for Pharmacoeconomics and Outcomes Research evaluated key development and reimbursement considerations from the payer and manufacturer perspectives.MethodsFive key areas in which health economics and outcomes research best practices could be developed to improve value assessment, reimbursement, and patient access decisions for personalized medicine have been identified.ResultsThese areas are as follows: 1 research prioritization and early value assessment, 2 best practices for clinical evidence development, 3 best practices for health economic assessment, 4 addressing health technology assessment challenges, and 5 new incentive and reimbursement approaches for personalized medicine.ConclusionsKey gaps in health economics and outcomes research best practices, decision standards, and value assessment processes are also discussed, along with next steps for evolving health economics and outcomes research practices in personalized medicine.