Evaluating the Accuracy of Existing EMR Data as Predictors of Follow-up Providers

In order to evaluate the accuracy of existing EMR data in predicting follow-up providers, a retrospective analysis was performed on six months of data for inpatient and ED encounters occurring at two hospitals, and on related outpatient data. Sensitivity and Positive Predictive Value (PPV) were calculated for each of eight predictors, to determine their effectiveness in predicting follow-up providers. Our findings indicate that access to longitudinal patient care records can improve prediction of which providers a patient is likely to see post-discharge compared to simply using Primary Care Provider data from admissions records. Of the predictors evaluated, a patient''s past appointment history was the best predictor of which providers they would see in the future (PPV = 48% following inpatient visits, 35% following emergency department visits). However, even the best performing predictors failed to predict more than half of the follow-up providers and might generate many “false” alerts.     

The impact of electronic medical records data sources on an adverse drug event quality measure

Objective

To examine the impact of billing and clinical data extracted from an electronic medical record system on the calculation of an adverse drug event (ADE) quality measure approved for use in The Joint Commission''s ORYX program, a mandatory national hospital quality reporting system.

Design

The Child Health Corporation of America''s “Use of Rescue Agents—ADE Trigger” quality measure uses medication billing data contained in the Pediatric Health Information Systems (PHIS) data warehouse to create The Joint Commission-approved quality measure. Using a similar query, we calculated the quality measure using PHIS plus four data sources extracted from our electronic medical record (EMR) system: medications charged, medication orders placed, medication orders with associated charges (orders charged), and medications administered.

Measurements

Inclusion and exclusion criteria were identical for all queries. Denominators and numerators were calculated using the five data sets. The reported quality measure is the ADE rate (numerator/denominator).

Results

Significant differences in denominators, numerators, and rates were calculated from different data sources within a single institution''s EMR. Differences were due to both common clinical practices that may be similar across institutions and unique workflow practices not likely to be present at any other institution. The magnitude of the differences would significantly alter the national comparative ranking of our institution compared to other PHIS institutions.

Conclusions

More detailed clinical information may result in quality measures that are not comparable across institutions due institution-specific workflow, differences that are exposed using EMR-derived data.     

Brief communication: Louisiana Clinical Data Research Network: establishing an infrastructure for efficient conduct of clinical research

The state of Louisiana, like the nation as a whole, is facing the salient challenge of improving population health and efficiency of healthcare delivery. Research to inform innovations in healthcare will best enhance this effort if it is timely, efficient, and patient-centered. The Louisiana Clinical Data Research Network (LACDRN) will increase the capacity to conduct robust comparative effectiveness research by building a health information technology infrastructure that provides access to comprehensive clinical data for more than 1 million patients statewide. To ensure that network-based research best serves its end-users, the project will actively engage patients and providers as key informants and decision-makers in the implementation of LACDRN. The network''s patient-centered research agenda will prioritize patients’ and clinicians’ needs and aim to support evidence-based decisions on the healthcare they receive and provide, to optimize patient outcomes and quality of life.     

The Business Value of Health Care Information Technology

The American health care system is one of the world''s largest and most complex industries. The Health Care Financing Administration reports that 1997 expenditures for health care exceeded one trillion dollars, or 13.5 percent of the gross domestic product. Despite these expenditures, over 16 percent of the U.S. population remains uninsured, and a large percentage of patients express dissatisfaction with the health care system. Managed care, effective in its ability to attenuate the rate of cost increase, is associated with a concomitant degree of administrative overhead that is often perceived by providers and patients alike as a major source of cost and inconvenience. Both providers and patients sense a great degree of inconvenience and an excessive amount of paperwork associated with both the process of seeking medical care and the subsequent process of paying for medical services.Traditionally, health practitioners have sought a return to traditional fee-for-service payment to mitigate the inconvenience associated with managed care. More populist proposals include universal health insurance or mandatory enrollment in health maintenance organizations. Advocates of managed care argue that the business methods required for effective trials of this approach are only beginning to be realized. By all accounts, information technology is a necessary part of these initiatives, but there is universal consensus that our current systems are inadequate to the task. (Oxford Health System''s difficulties in 1998, for example, have been attributed in part to inadequate deployment of information technology.) To this author, the model for the current generation of health care information systems is strikingly similar to that for the information systems employed by the Internal Revenue Service. In each case, the system allows for low-cost changes to administrative code brought about by legislation, but in both cases the “ripple effects” of additional complexity and administrative burden far exceed the cost of immediate change. To paraphrase a quotation attributed to Major Richard Dailey, made about his police force during the 1998 Chicago Democratic Convention, our information systems “are not here to create disorder; they are here to preserve disorder.”This case explores one alternative source for models in health care delivery. Through an examination of a typical patient experience, we explore Porter''s notion of the value chain and “just-in-time” logistics common to successful organizations like Wal-Mart and Amazon.com (see Suggested Readings). We close with a brief discussion of how these logistics and inventory systems apply to health care. Clearly, logistics are important in patient care, accounts receivable are a cause of severe working capital problems in health care, and the logistics of caring for patients are becoming more complex. But the concepts we discuss have an even greater importance: Effective management of these issues through information technology may restore our most precious commodity—time.     

Informatics,evidence-based care,and research; implications for national policy: a report of an American Medical Informatics Association health policy conference

There is an increased level of activity in the biomedical and health informatics world (e-prescribing, electronic health records, personal health records) that, in the near future, will yield a wealth of available data that we can exploit meaningfully to strengthen knowledge building and evidence creation, and ultimately improve clinical and preventive care. The American Medical Informatics Association (AMIA) 2008 Health Policy Conference was convened to focus and propel discussions about informatics-enabled evidence-based care, clinical research, and knowledge management. Conference participants explored the potential of informatics tools and technologies to improve the evidence base on which providers and patients can draw to diagnose and treat health problems. The paper presents a model of an evidence continuum that is dynamic, collaborative, and powered by health informatics technologies. The conference''s findings are described, and recommendations on terminology harmonization, facilitation of the evidence continuum in a “wired” world, development and dissemination of clinical practice guidelines and other knowledge support strategies, and the role of diverse stakeholders in the generation and adoption of evidence are presented.     

Computerized Alerts Improve Outpatient Laboratory Monitoring of Transplant Patients

Authors evaluated the impact of computerized alerts on the quality of outpatient laboratory monitoring for transplant patients. For 356 outpatient liver transplant patients managed at LDS Hospital, Salt Lake City, this observational study compared traditional laboratory result reporting, using faxes and printouts, to computerized alerts implemented in 2004. Study alerts within the electronic health record notified clinicians of new results and overdue new orders for creatinine tests and immunosuppression drug levels. After implementing alerts, completeness of reporting increased from 66 to >99 %, as did positive predictive value that a report included new information (from 46 to >99 %). Timeliness of reporting and clinicians'' responses improved after implementing alerts (p <0.001): median times for clinicians to receive and complete actions decreased to 9 hours from 33 hours using the prior traditional reporting system. Computerized alerts led to more efficient, complete, and timely management of laboratory information.     

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.     

Research and applications: Formative evaluation of the accuracy of a clinical decision support system for cervical cancer screening

Objectives

We previously developed and reported on a prototype clinical decision support system (CDSS) for cervical cancer screening. However, the system is complex as it is based on multiple guidelines and free-text processing. Therefore, the system is susceptible to failures. This report describes a formative evaluation of the system, which is a necessary step to ensure deployment readiness of the system.

Materials and methods

Care providers who are potential end-users of the CDSS were invited to provide their recommendations for a random set of patients that represented diverse decision scenarios. The recommendations of the care providers and those generated by the CDSS were compared. Mismatched recommendations were reviewed by two independent experts.

Results

A total of 25 users participated in this study and provided recommendations for 175 cases. The CDSS had an accuracy of 87% and 12 types of CDSS errors were identified, which were mainly due to deficiencies in the system''s guideline rules. When the deficiencies were rectified, the CDSS generated optimal recommendations for all failure cases, except one with incomplete documentation.

Discussion and conclusions

The crowd-sourcing approach for construction of the reference set, coupled with the expert review of mismatched recommendations, facilitated an effective evaluation and enhancement of the system, by identifying decision scenarios that were missed by the system''s developers. The described methodology will be useful for other researchers who seek rapidly to evaluate and enhance the deployment readiness of complex decision support systems.     

Supporting interoperability of genetic data with LOINC

Electronic reporting of genetic testing results is increasing, but they are often represented in diverse formats and naming conventions. Logical Observation Identifiers Names and Codes (LOINC) is a vocabulary standard that provides universal identifiers for laboratory tests and clinical observations. In genetics, LOINC provides codes to improve interoperability in the midst of reporting style transition, including codes for cytogenetic or mutation analysis tests, specific chromosomal alteration or mutation testing, and fully structured discrete genetic test reporting. LOINC terms follow the recommendations and nomenclature of other standards such as the Human Genome Organization Gene Nomenclature Committee’s terminology for gene names. In addition to the narrative text they report now, we recommend that laboratories always report as discrete variables chromosome analysis results, genetic variation(s) found, and genetic variation(s) tested for. By adopting and implementing data standards like LOINC, information systems can help care providers and researchers unlock the potential of genetic information for delivering more personalized care.     

Development of a HIPAA-compliant environment for translational research data and analytics

High-performance computing centers (HPC) traditionally have far less restrictive privacy management policies than those encountered in healthcare. We show how an HPC can be re-engineered to accommodate clinical data while retaining its utility in computationally intensive tasks such as data mining, machine learning, and statistics. We also discuss deploying protected virtual machines. A critical planning step was to engage the university''s information security operations and the information security and privacy office. Access to the environment requires a double authentication mechanism. The first level of authentication requires access to the university''s virtual private network and the second requires that the users be listed in the HPC network information service directory. The physical hardware resides in a data center with controlled room access. All employees of the HPC and its users take the university''s local Health Insurance Portability and Accountability Act training series. In the first 3 years, researcher count has increased from 6 to 58.     

医院临床信息互联互通标准化建设实践

以上海交通大学附属第六人民医院临床信息互联互通标准化建设为背景,介绍医院信息集成平台建设以及现有临床信息系统的改造升级方案,成功构建患者主索引为主线,以信息集成平台为基础,整合全院不同业务系统数据的临床数据中心,分析应用效果,对目前医院临床信息系统建设特别是临床信息共享互联互通具有借鉴作用。     

门诊临床路径信息系统设计

分析门诊临床路径信息系统建设需求,从思路、架构、关键技术等方面介绍系统设计,阐述具体功能实现,包括临床路径管理、门诊医生站、护理路径、患者路径、质控管理、系统管理等子系统,指出该系统的应用能够使患者享受更完善的门诊诊疗服务。     

Contextual Implementation Model: A Framework for Assisting Clinical Information System Implementations

Objective

This paper presents a multiple perspectives model of clinical information system implementation, the Contextual Implementation Model (CIM). Although other implementation models have been developed, few are grounded in data and others fail to take adequate account of the clinical environment and users’ requirements.

Design

The CIM arose from qualitative data collected from four clinical units in two large Australian teaching hospitals. The aim of the study was to explore physicians’ test management work practices associated with the compulsory use of a hospital-wide, mandatory computerized provider order entry (CPOE) system.¹ The dataset consisted of non-participatory observations of physicians using CPOE (n=55 sessions) and interviews with health professionals (n=28) about test management work practices. Data were analyzed by two researchers independently using an iterative grounded approach.

Results

A core underlying theme of ‘contextual differences’ emerged which explained physicians’ use of the CPOE system in the sites. The CIM focuses attention on diversity at three contextual levels: the organizational level; the clinical or departmental level, and the individual level. Within each of these levels there are dimensions for consideration (for example, organizational culture, leadership and diverse ways of working) which affect physicians’ attitudes to, and use of, CPOE.

Conclusion

The CIM provides a contextual differences perspective which can be used to facilitate the implementation of clinical information systems. Developing a clinical information system implementation model serves as a framework to guide future implementations to ensure their safe and efficient use and also improve the likelihood of uptake by physicians.     

Design and development of an international clinical data exchange system: the international layer function of the Dolphin Project

Objective

At present, most clinical data are exchanged between organizations within a regional system. However, people traveling abroad may need to visit a hospital, which would make international exchange of clinical data very useful.

Background

Since 2007, a collaborative effort to achieve clinical data sharing has been carried out at Zhejiang University in China and Kyoto University and Miyazaki University in Japan; each is running a regional clinical information center.

Methods

An international layer system named Global Dolphin was constructed with several key services, sharing patients'' health information between countries using a medical markup language (MML). The system was piloted with 39 test patients.

Results

The three regions above have records for 966 000 unique patients, which are available through Global Dolphin. Data exchanged successfully from Japan to China for the 39 study patients include 1001 MML files and 152 images. The MML files contained 197 free text-type paragraphs that needed human translation.

Discussion

The pilot test in Global Dolphin demonstrates that patient information can be shared across countries through international health data exchange. To achieve cross-border sharing of clinical data, some key issues had to be addressed: establishment of a super directory service across countries; data transformation; and unique one—language translation. Privacy protection was also taken into account. The system is now ready for live use.

Conclusion

The project demonstrates a means of achieving worldwide accessibility of medical data, by which the integrity and continuity of patients'' health information can be maintained.     

Care transitions as opportunities for clinicians to use data exchange services: how often do they occur?

Background

The electronic exchange of health information among healthcare providers has the potential to produce enormous clinical benefits and financial savings, although realizing that potential will be challenging. The American Recovery and Reinvestment Act of 2009 will reward providers for ‘meaningful use’ of electronic health records, including participation in clinical data exchange, but the best ways to do so remain uncertain.

Methods

We analyzed patient visits in one community in which a high proportion of providers were using an electronic health record and participating in data exchange. Using claims data from one large private payer for individuals under age 65 years, we computed the number of visits to a provider which involved transitions in care from other providers as a percentage of total visits. We calculated this ‘transition percentage’ for individual providers and medical groups.

Results

On average, excluding radiology and pathology, approximately 51% of visits involved care transitions between individual providers in the community and 36%–41% involved transitions between medical groups. There was substantial variation in transition percentage across medical specialties, within specialties and across medical groups. Specialists tended to have higher transition percentages and smaller ranges within specialty than primary care physicians, who ranged from 32% to 95% (including transitions involving radiology and pathology). The transition percentages of pediatric practices were similar to those of adult primary care, except that many transitions occurred among pediatric physicians within a single medical group.

Conclusions

Care transition patterns differed substantially by type of practice and should be considered in designing incentives to foster providers'' meaningful use of health data exchange services.     

Real-time Notification of Laboratory Data Requested by Users through Alphanumeric Pagers

The authors developed a novel feature in their clinical information systems, which allows clinicians to request notification about laboratory results. Clinicians who are expecting a particular laboratory result for a particular patient can request a report of the result via an alphanumeric pager as soon as the result is filed into the patient database. This feature has gained popularity and is heavily used in both inpatient and outpatient settings, at a rate of about 2,300 times per month. This event-monitor-based feature illustrates one way that information technology can be applied to improve communication in health care.Clinicians rely heavily on laboratory data to make medical decisions in various settings. However, the lag between the time when laboratory data become available and when clinicians review and act on them is considerable.¹ While certain clinical situations permit such delays, many do not. For example, a patient who has had gastrointestinal bleeding should have further units of blood cross-matched if it is clear the hematocrit has not responded to previous blood transfusions. The conscientious clinician who keeps checking the hospital laboratory information system for pending results can waste a lot of time doing so, and yet not checking may lead to unacceptable delays in patient care.Several groups, including ours, have developed applications that notify physicians when certain conditions apply.^1–10 For example, our group has developed an application that alerts physicians when life-threatening results are present, and that application has been shown to decrease the time it takes for a physician to act on such results.¹Previously described applications, however, were all designed to identify results that somehow are unusual or indicate gross deviation in a patient''s status from expected norms. In clinical practice, however, many results, including normal ones, may be important for decision making¹¹ and may warrant rapid notification of physicians. Furthermore, given the variety of user preferences¹² and the uniqueness of each clinical scenario, it may be difficult, at least with laboratory results in non-life-threatening cases, for an information system to predict whether a particular result merits urgent notification of a particular user.We designed an application—called “Result Notification via Alphanumeric Pagers,” or ReNAP—that allows clinicians to make this choice. Using this application, a clinician can indicate that he or she wants to be notified about a particular result for a particular patient, regardless of whether the result is abnormal. In this paper, we report the implementation methods, use statistics, and the results of a user satisfaction survey.     

A Gesture-based Tool for Sterile Browsing of Radiology Images

The use of doctor-computer interaction devices in the operation room (OR) requires new modalities that support medical imaging manipulation while allowing doctors'' hands to remain sterile, supporting their focus of attention, and providing fast response times. This paper presents “Gestix,” a vision-based hand gesture capture and recognition system that interprets in real-time the user''s gestures for navigation and manipulation of images in an electronic medical record (EMR) database. Navigation and other gestures are translated to commands based on their temporal trajectories, through video capture. “Gestix” was tested during a brain biopsy procedure. In the in vivo experiment, this interface prevented the surgeon''s focus shift and change of location while achieving a rapid intuitive reaction and easy interaction. Data from two usability tests provide insights and implications regarding human-computer interaction based on nonverbal conversational modalities.     

检验科信息系统建设对患者满意度的影响

目的 探讨检验科信息系统建设对门诊患者满意度的影响.方法 完善和优化检验科信息系统建设,系统投入使用后随机抽取门诊患者填写满意度调查问卷,采用Likert五级评定法计分,运用SPSS17.0软件对所获数据进行统计学描述及相关性检验.结果 检验方便性满意度与检验科信息系统建设前中后三个季度具有显著相关性,三个季度分别为（3.7±0.6）分,（4.3±0.8）分,（4.3±0.8）分.信息系统建设中期整体满意度均值最低,仅为（3.5±0.5）分.结论 我院通过检验科信息系统的建设,显著缩短了门诊病人就诊的时间,给病人复诊与疾病治疗带来了极大的方便,提高了门诊患者的满意度.     

全处方集中点评系统应用效果分析

对杭州市10家市属医院的门急诊处方和住院医嘱进行研究,抽取干预前、干预1年后和干预2年后的处方数据进行对比分析,深入探讨全处方集中点评系统对临床合理用药的促进效果。     

Understanding the acceptability of a computer decision support system in pediatric primary care

Objective

Individual users’ attitudes and opinions help predict successful adoption of health information technology (HIT) into practice; however, little is known about pediatric users’ acceptance of HIT for medical decision-making at the point of care.

Materials and methods

We wished to examine the attitudes and opinions of pediatric users’ toward the Child Health Improvement through Computer Automation (CHICA) system, a computer decision support system linked to an electronic health record in four community pediatric clinics. Surveys were administered in 2011 and 2012 to all users to measure CHICA''s acceptability and users’ satisfaction with it. Free text comments were analyzed for themes to understand areas of potential technical refinement.

Results

70 participants completed the survey in 2011 (100% response rate) and 64 of 66 (97% response rate) in 2012. Initially, satisfaction with CHICA was mixed. In general, users felt the system held promise; however various critiques reflected difficulties understanding integrated technical aspects of how CHICA worked, as well as concern with the format and wording on generated forms for families and users. In the subsequent year, users’ ratings reflected improved satisfaction and acceptance. Comments also reflected a deeper understanding of the system''s logic, often accompanied by suggestions on potential refinements to make CHICA more useful at the point of care.

Conclusions

Pediatric users appreciate the system''s automation and enhancements that allow relevant and meaningful clinical data to be accessible at point of care. Understanding users’ acceptability and satisfaction is critical for ongoing refinement of HIT to ensure successful adoption into practice.