国内外电子健康档案建设概况

电子健康档案研究是当今国内外卫生信息化的热点。对国内外电子健康档案建设现状以及我国电子健康档案建设存在问题做了综述,主要从发展背景、政策法规、数据标准及系统架构方面进行比较,指出电子健康档案建设在总体设计、支持力度、利益协调、推广引导等方面存在的不足。     

我国电子健康档案建立与应用进展

电子健康档案的发展是全球数字化的必然趋势，介绍电子健康档案的建立与国家相关政策，阐述电子健康档案在德阳、上海、北京、广州、南昌等地的建设实践，对未来发展进行展望，为其他省市电子健康档案的建设提供有益参考。     

军队人员电子健康档案的总体框架设计与应用

军人电子健康档案是广大官兵享有均等化公共卫生服务的重要体现，详细介绍了军人电子健康档案的系统架构、技术标准、需求模型以及建设目标和主要功能，并总结了军区应用电子健康档案的初步成效，旨在为军队电子健康档案建设提供参考。     

国外电子健康档案发展现况及借鉴

电子健康档案是国内外卫生信息化研究的热点。本文探讨了电子健康档案的涵义与作用,分析国外电子健康档案的发展现状,以期为我国电子健康档案的建设提供借鉴。     

我国电子健康档案研究现状

通过对中文电子健康档案文献的梳理,发现我国当前研究热点集中于对电子健康档案的介绍、电子健康档案建设的工具、技术和方法以及电子健康档案的应用。未来的研究方向应该围绕电子健康档案面临的问题,将重心落到标准化、安全性、法律法规、人员培养等方面的细节研究上。     

电子健康档案云安全研究

近年来，云计算逐步进入了电子健康档案建设与共享的应用领域，为电子健康档案系统建设的标准化、智能化、高性价比及资源的可持续利用带来了契机。从信息技术能力、法律法规缺失、安全威胁以及隐私性等角度分析丫云环境电子健康档案的安全问题，提出通过电子健康云服务等级协议来保障服务效能，明确了关键指标，并探讨丁云环境的电子健康档案存储安全和终端安全。     

国外居民电子健康档案共享服务体系建设及启示

居民电子健康档案与区域卫生信息网络在全世界范围内正在成为医疗卫生信息化的前沿阵地。而区域卫生信息网络的核心是居民电子健康档案服务的共享。本文从组织机构、政策法规制定、数据共享标准和重视数据安全与隐私保护四方面介绍国外主要国家居民电子健康档案的共享服务体系建设,以期为我国共享服务体系建设提供借鉴。     

标准化健康档案应用调查方案论证暨工作研讨会在京召开

为了解掌握卫生部信息化试点地区居民电子健康档案标准化建设与应用情况，指导健康档案标准化应用和规范化建设，受卫生部卫生监督中心委托，卫生部统计信息中心组织开展了标；位化电子健康档案应用现状调查工作.     

国外电子健康档案发展概况及启示

以卫生信息化发展较好的国家英国、美国、加拿大为研究对象,以我国为参照对象,通过网络及文献调研,从法律法规、支撑技术及卫生信息标准等方面对各国电子健康档案建设概况进行综合分析,为我国电子健康档案建设提供参考和借鉴。     

从匠域匠疗协同的角度看电子健康档案的深度应用

2011年9月16日,卫生部召开会议,要求各省（区、市）电子健康档案建档率在年底前达到40％以上。作为“十二五”卫生信息化“3521”工程中两个基础数据库建设之一的电子健康档案,建设速度不断加快,建设数量不断攀升,建设质量不断提高、基于健康档案、整合公共卫生、医疗服务等业务的区域医疗卫生信息化平台已经成为我国卫生信息化建设的重要内容。     

英国电子健康档案建设与启示

阐述英国电子健康档案建设历程、系统构成及主要功能,分析存在的问题,包括资金短缺、进度滞后、存在安全隐患等,提出对我国的启示,即强化利用先进技术促进国民健康,加强项目资金规划、管理及国家统一指导,建立完备的法律法规。     

Understanding differences in electronic health record (EHR) use: linking individual physicians’ perceptions of uncertainty and EHR use patterns in ambulatory care

Objective

Electronic health records (EHR) hold great promise for managing patient information in ways that improve healthcare delivery. Physicians differ, however, in their use of this health information technology (IT), and these differences are not well understood. The authors study the differences in individual physicians'' EHR use patterns and identify perceptions of uncertainty as an important new variable in understanding EHR use.

Design

Qualitative study using semi-structured interviews and direct observation of physicians (n=28) working in a multispecialty outpatient care organization.

Measurements

We identified physicians'' perceptions of uncertainty as an important variable in understanding differences in EHR use patterns. Drawing on theories from the medical and organizational literatures, we identified three categories of perceptions of uncertainty: reduction, absorption, and hybrid. We used an existing model of EHR use to categorize physician EHR use patterns as high, medium, and low based on degree of feature use, level of EHR-enabled communication, and frequency that EHR use patterns change.

Results

Physicians'' perceptions of uncertainty were distinctly associated with their EHR use patterns. Uncertainty reductionists tended to exhibit high levels of EHR use, uncertainty absorbers tended to exhibit low levels of EHR use, and physicians demonstrating both perspectives of uncertainty (hybrids) tended to exhibit medium levels of EHR use.

Conclusions

We find evidence linking physicians'' perceptions of uncertainty with EHR use patterns. Study findings have implications for health IT research, practice, and policy, particularly in terms of impacting health IT design and implementation efforts in ways that consider differences in physicians'' perceptions of uncertainty.     

Use of a support vector machine for categorizing free-text notes: assessment of accuracy across two institutions

Background

Electronic health record (EHR) users must regularly review large amounts of data in order to make informed clinical decisions, and such review is time-consuming and often overwhelming. Technologies like automated summarization tools, EHR search engines and natural language processing have been shown to help clinicians manage this information.

Objective

To develop a support vector machine (SVM)-based system for identifying EHR progress notes pertaining to diabetes, and to validate it at two institutions.

Materials and methods

We retrieved 2000 EHR progress notes from patients with diabetes at the Brigham and Women''s Hospital (1000 for training and 1000 for testing) and another 1000 notes from the University of Texas Physicians (for validation). We manually annotated all notes and trained a SVM using a bag of words approach. We then used the SVM on the testing and validation sets and evaluated its performance with the area under the curve (AUC) and F statistics.

Results

The model accurately identified diabetes-related notes in both the Brigham and Women''s Hospital testing set (AUC=0.956, F=0.934) and the external University of Texas Faculty Physicians validation set (AUC=0.947, F=0.935).

Discussion

Overall, the model we developed was quite accurate. Furthermore, it generalized, without loss of accuracy, to another institution with a different EHR and a distinct patient and provider population.

Conclusions

It is possible to use a SVM-based classifier to identify EHR progress notes pertaining to diabetes, and the model generalizes well.     

Social networks and physician adoption of electronic health records: insights from an empirical study

Objective

To study how social interactions influence physician adoption of an electronic health records (EHR) system.

Design

A social network survey was used to delineate the structure of social interactions among 40 residents and 15 attending physicians in an ambulatory primary care practice. Social network analysis was then applied to relate the interaction structures to individual physicians'' utilization rates of an EHR system.

Measurements

The social network survey assessed three distinct types of interaction structures: professional network based on consultation on patient care-related matters; friendship network based on personal intimacy; and perceived influence network based on a person''s perception of how other people have affected her intention to adopt the EHR system. EHR utilization rates were measured as the proportion of patient visits in which sentinel use events consisting of patient data documentation or retrieval activities were recorded. The usage data were collected over a time period of 14 months from computer-recorded audit trail logs.

Results

Neither the professional nor the perceived influence network is correlated with EHR usage. The structure of the friendship network significantly influenced individual physicians'' adoption of the EHR system. Residents who occupied similar social positions in the friendship network shared similar EHR utilization rates (p<0.05). In other words, residents who had personal friends in common tended to develop comparable levels of EHR adoption. This effect is particularly prominent when the mutual personal friends of these ‘socially similar’ residents were attending physicians (p<0.001).

Conclusions

Social influence affecting physician adoption of EHR seems to be predominantly conveyed through interactions with personal friends rather than interactions in professional settings.Social influence pervades our lives. Watching a movie recommended by friends, reading a news article referred by colleagues, dressing up for a formal social event (assuming everybody else will do the same), and so on, are all examples of how other people''s opinions or behavior affect our everyday choices. Social influence theories therefore postulate that people are neither born with beliefs or behavior nor are beliefs or behavior developed in isolation. Their formation and evolution occur primarily through social interactions as people compare their own beliefs or behavior with those of others, in particular, similar others.¹Social influence plays the same role in the process of innovation diffusion. This is especially true when an innovation is complex entailing unknown costs or unknown consequences. For example, it has been shown that physicians who are ‘socially proximate’ in a social environment often use one another as information sources or behavior referents to manage the uncertainty of adopting new antibiotic drugs.² Does social influence exert a similar effect on physician adoption of complex technological innovations such as electronic health records (EHR)?Answering this question is very important in a healthcare policy climate in which strong emphasis has been placed on increased and improved use of health information technology, and EHR in particular. Furthermore, EHR is much more complex than other types of medical innovations. The adoption of EHR not only requires significant financial investments and learning effort, but also introduces radical change to every single aspect of clinical work. Understanding the social mechanisms underlying physician adoption of EHR is therefore critical to identifying effective strategies to accelerate EHR diffusion and to promote its meaningful use. Unfortunately, such an understanding has been largely missing,^{3 4} resulting in failed implementations⁵ and suboptimal or even adverse outcomes.^{6 7} Given this context, we designed and conducted a study to examine physician adoption of EHR through the lens of social influence.Social influence, often crystallized as opinion exchange and behavior ‘imitating’, is conveyed in physicians'' interpersonal social interactions. Social network analysis (SNA), which views the structure of social interactions as networks composed of nodes (physicians) interconnected by edges (social relations), is an ideal approach for delineating interaction patterns to study how social influence is transmitted among physicians and how it affects their contingent behavior such as EHR adoption. In particular, we designed and conducted a SNA study to assess the social structures among physicians in an ambulatory primary care practice and then relate these structures to individual physicians'' utilization rates of an EHR system.     

区域医疗信息共享中健康档案安全与隐私保护的领域分析

将当前区域医疗信息共享平台中健康档案的安全和隐私保护问题作为研究对象,采用面向特征的领域分析方法,分析了区域医疗信息共享中健康档案存在的安全隐患以及产生信息安全隐患的原因,研究了健康档案用户操作行为与安全隐患之间的关系,构建了关于区域医疗信息共享中健康档案安全与隐私保护的领域模型。     

Building longitudinal medication dose data using medication information extracted from clinical notes in electronic health records

ObjectiveTo develop an algorithm for building longitudinal medication dose datasets using information extracted from clinical notes in electronic health records (EHRs).Materials and MethodsWe developed an algorithm that converts medication information extracted using natural language processing (NLP) into a usable format and builds longitudinal medication dose datasets. We evaluated the algorithm on 2 medications extracted from clinical notes of Vanderbilt’s EHR and externally validated the algorithm using clinical notes from the MIMIC-III clinical care database.ResultsFor the evaluation using Vanderbilt’s EHR data, the performance of our algorithm was excellent; F1-measures were ≥0.98 for both dose intake and daily dose. For the external validation using MIMIC-III, the algorithm achieved F1-measures ≥0.85 for dose intake and ≥0.82 for daily dose.DiscussionOur algorithm addresses the challenge of building longitudinal medication dose data using information extracted from clinical notes. Overall performance was excellent, but the algorithm can perform poorly when incorrect information is extracted by NLP systems. Although it performed reasonably well when applied to the external data source, its performance was worse due to differences in the way the drug information was written. The algorithm is implemented in the R package, “EHR,” and the extracted data from Vanderbilt’s EHRs along with the gold standards are provided so that users can reproduce the results and help improve the algorithm.ConclusionOur algorithm for building longitudinal dose data provides a straightforward way to use EHR data for medication-based studies. The external validation results suggest its potential for applicability to other systems.     

Area-level factors associated with electronic health record adoption and meaningful use in the Regional Extension Center Program

Objective

To identify area-level correlates of electronic health record (EHR) adoption and meaningful use (MU) among primary care providers (PCPs) enrolled in the Regional Extension Center (REC) Program.

Materials and methods

County-level data on 2013 EHR adoption and MU among REC-enrolled PCPs were obtained from the Office of the National Coordinator for Health Information Technology and linked with other county-level data sources including the Area Resource File, American Community Survey, and Federal Communications Commission''s broadband availability database. Hierarchical models with random intercepts for RECs were employed to assess associations between a broad set of area-level factors and county-level rates of EHR adoption and MU.

Results

Among the 2715 counties examined, the average county-level EHR adoption and MU rates for REC-enrolled PCPs were 87.5% and 54.2%, respectively. Community health center presence and Medicaid enrollment concentration were positively associated with EHR adoption, while metropolitan status and Medicare Advantage enrollment concentration were positively associated with MU. Health professional shortage area status and minority concentration were negatively associated with EHR adoption and MU.

Discussion

Increased financial incentives in areas with greater concentrations of Medicaid and Medicare enrollees may be encouraging EHR adoption and MU among REC-enrolled PCPs. Disparities in EHR adoption and MU in some low-resource and underserved areas remain a concern.

Conclusions

Federal efforts to spur EHR adoption and MU have demonstrated some early success; however, some geographic variations in EHR diffusion indicate that greater attention needs to be paid to ensuring equitable uptake and use of EHRs throughout the US.     

Organization’s Quality Maturity as a Vehicle for EHR Success

In health care industry, EHR has been advocated to improve care quality. The journey toward the development and adaptation of EHR should be holistic and integrate all the EHR’s building blocks-health record management, business process improvement (BPI), collaboration and innovation, change management, user governance, etc.—that are intertwined together as like the links of a chain to improve quality of health care services. These cornerstones that shares common features with quality principles will pave the way for implementing EHR. To go along with quality features and take advantage of quality principles namely “quality maturity” builds a solid foundation for adaptation of EHR. Therefore, the recent theories of EHR success go far beyond technical rationales and focus on organizational and managerial factors in quality improvement. The milestone of quality concept in information system success is revealed in Delone and Mclean’s model which launches system quality, information quality, service quality, as distinct elements of the IS success. EHR is a means to an end -to improve quality within enterprises- based on quality approaches. In this regards, more research should be conducted to investigate the relationship between of organization’s quality maturity and EHR development success.     

Effects of electronic health record use on the exam room communication skills of resident physicians: a randomized within-subjects study

Background The effects of electronic health records (EHRs) on doctor–patient communication are unclear.Objective To evaluate the effects of EHR use compared with paper chart use, on novice physicians’ communication skills.Design Within-subjects randomized controlled trial using observed structured clinical examination methods to assess the impact of use of an EHR on communication.Setting A large academic internal medicine training program.Population First-year internal medicine residents.Intervention Residents interviewed, diagnosed, and initiated treatment of simulated patients using a paper chart or an EHR on a laptop computer. Video recordings of interviews were rated by three trained observers using the Four Habits scale.Results Thirty-two residents completed the study and had data available for review (61.5% of those enrolled in the residency program). In most skill areas in the Four Habits model, residents performed at least as well using the EHR and were statistically better in six of 23 skills areas (p<0.05). The overall average communication score was better when using an EHR: mean difference 0.254 (95% CI 0.05 to 0.45), p = 0.012, Cohen''s d of 0.47 (a moderate effect). Residents scoring poorly (>3 average score) with paper methods (n = 8) had clinically important improvement when using the EHR.Limitations This study was conducted in first-year residents in a training environment using simulated patients at a single institution.Conclusions Use of an EHR on a laptop computer appears to improve the ability of first-year residents to communicate with patients relative to using a paper chart.     

Electronic health records improve clinical note quality

Background and objective The clinical note documents the clinician''s information collection, problem assessment, clinical management, and its used for administrative purposes. Electronic health records (EHRs) are being implemented in clinical practices throughout the USA yet it is not known whether they improve the quality of clinical notes. The goal in this study was to determine if EHRs improve the quality of outpatient clinical notes.Materials and methods A five and a half year longitudinal retrospective multicenter quantitative study comparing the quality of handwritten and electronic outpatient clinical visit notes for 100 patients with type 2 diabetes at three time points: 6 months prior to the introduction of the EHR (before-EHR), 6 months after the introduction of the EHR (after-EHR), and 5 years after the introduction of the EHR (5-year-EHR). QNOTE, a validated quantitative instrument, was used to assess the quality of outpatient clinical notes. Its scores can range from a low of 0 to a high of 100. Sixteen primary care physicians with active practices used QNOTE to determine the quality of the 300 patient notes.Results The before-EHR, after-EHR, and 5-year-EHR grand mean scores (SD) were 52.0 (18.4), 61.2 (16.3), and 80.4 (8.9), respectively, and the change in scores for before-EHR to after-EHR and before-EHR to 5-year-EHR were 18% (p<0.0001) and 55% (p<0.0001), respectively. All the element and grand mean quality scores significantly improved over the 5-year time interval.Conclusions The EHR significantly improved the overall quality of the outpatient clinical note and the quality of all its elements, including the core and non-core elements. To our knowledge, this is the first study to demonstrate that the EHR significantly improves the quality of clinical notes.