Summary
Objectives
Describe the state of Electronic Health Records (EHRs) in 1992 and their evolution by 2015 and where EHRs are expected to be in 25 years. Further to discuss the expectations for EHRs in 1992 and explore which of them were realized and what events accelerated or disrupted/derailed how EHRs evolved.
Methods
Literature search based on “Electronic Health Record”, “Medical Record”, and “Medical Chart” using Medline, Google, Wikipedia Medical, and Cochrane Libraries resulted in an initial review of 2,356 abstracts and other information in papers and books. Additional papers and books were identified through the review of references cited in the initial review.
Results
By 1992, hardware had become more affordable, powerful, and compact and the use of personal computers, local area networks, and the Internet provided faster and easier access to medical information. EHRs were initially developed and used at academic medical facilities but since most have been replaced by large vendor EHRs. While EHR use has increased and clinicians are being prepared to practice in an EHR-mediated world, technical issues have been overshadowed by procedural, professional, social, political, and especially ethical issues as well as the need for compliance with standards and information security. There have been enormous advancements that have taken place, but many of the early expectations for EHRs have not been realized and current EHRs still do not meet the needs of today’s rapidly changing healthcare environment.
Conclusion
The current use of EHRs initiated by new technology would have been hard to foresee. Current and new EHR technology will help to provide international standards for interoperable applications that use health, social, economic, behavioral, and environmental data to communicate, interpret, and act intelligently upon complex healthcare information to foster precision medicine and a learning health system.
Keywords: Electronic Health Record, medical record, medical chart
Introduction
Translation of ancient Egyptian hieroglyphic inscriptions and papyri from 1,600-3,000 BC indicate the use of medical records. However, paper medical records were not steadily used until 1900-1920. Medical record, medical chart, and health record are different terms used to describe the documentation of a patient’s medical history and care. In recent years, the term health record has received prominence based on the fact that a patient’s medical information should include health and lifestyle information beyond just episodic medical encounters. Traditionally, health records were written on paper, maintained in folders divided into sections based on the type of note, and only one copy was available. New computer technology developed in the 1960s and 1970s laid the foundation for the development of the Electronic Heath Record (EHR). The use of EHRs has not only made patients’ medical information easier to read and available from almost any location in the world, but also changed the format of health records, and thus changed health care.
Thousands of published studies report on EHRs increasing use, clinical decision support’s (CDS) ability to improve or not improve the healthcare process or clinical outcomes, evaluation methods, implementation/adoption, clinical trial patient identification, numerous new applications, and unintended consequences. Information on specific studies is beyond the scope of this paper and not included. For the 25th anniversary of the Yearbook of the International Medical Informatics Association (IMIA), this paper focuses on the overall state and use of EHRs in 1992 and how they have evolved by 2015. This paper also discusses the expectations for EHRs in 1992 and which of these were realized, what events accelerated or disrupted/derailed EHR evolution. Finally, we will discuss the expected state of EHRs in the 25 years.
State of EHRs in 1992
Initially, EHRs were developed and used at a number of academic inpatient and outpatient medical facilities [1-10], but none contained all the information in the paper chart and most EHRs today are still a hybrid collection of computerized and paper data [11, 12] (Table 1). Some EHRs developed between 1971 and 1992 were developed with hierarchical or relational databases, around or added to hospital billing and scheduling systems while others such as COSTAR, PROMIS, TMR, and HELP were developed as clinical systems to help improve medical care and for use in medical research [3, 13-15]. While some EHRs were developed on minicomputers, most were initially developed on large mainframe computers and in either case had limited storage, which required the use of removable disk packs and/or tape for extra data storage, nightly downtimes for database back-up, and dedicated/wired terminals. Only a few early EHRs allowed physician entry of orders, prescriptions, and notes and data entry was through keyboards focused mostly on laboratory and medication review [16]. While usually hospital-based, many of the early EHRs had features and functionalities that are still used and important today.
Table 1.
Capabilities and use of EHRs in 1992 and 2015
EHRs in1992 | State of the Art |
---|---|
Mostly developed and used at academic centers Hybrid of paper and electronic data Hierarchical and relational databases Based around billing and scheduling systems, some clinical systems Large mainframe and minicomputers with limited data storage Personal computers with graphics used as monitors Data entry through keyboards and mouse Used in inpatient & outpatient facilities Local area networks & Internet, web-based Admitting, pharmacy, laboratory, microbiology, surgery, radiology, respiratory therapy, infectious diseases, radiology, nurse charting, physician notes/orders/consults, patient measurements, patient care procedures, electrocardiogram, echocardiography Image scanning Paper printouts Clinical Decision Support Computerized Provider Order Entry Drug references, clinical manuals, textbooks of medicine, literature searching Physician documentation & electronic signatures Health Level Seven/IEEE P1157 Universal Medical Language System Medical device interfaces Picture Archiving and Communication Systems (PACS) Wide area networks Ethical issues: data ownership, data liability, informed consent, security and privacy |
|
EHRs in 2015 | Differences |
EHRs used in primary care exam rooms and by insurance companies, nursing homes, hospice, homeless population, departments of corrections Mostly vendor EHRs Personal Health Records interfaced to EHRs Intra-facility data sharing with standards more common Data mapping to SMOMED & LOINC Digital pathology, mental health, external labs, e-prescribing, order-sets, family history, genetics, biobanks, biosurveillance, public health Increased Clinical Decision Support Natural Language Processing Big Data Mobil devices Open-source EHRs Digital identities Enterprise Data Warehouses; birth to death data Increased EHR education Infobuttons Cloud computing Alerts via email, pagers/cell phones Copy and paste; note bloat Unintentional consequences Interfaces to medical libraries Medical scribes Technical issues overshadowed by procedural, professional, political, social and especially ethical issues and the need for compliance with standards and information security Significant increase in EHR related publications |
As inadequacies of the paper record became increasingly more apparent in 1992 [17], the Institute of Medicine advocated a shift from a paper-based to an electronic medical record [12]. However, the widespread use of EHRs was delayed by high costs, data entry errors, poor initial physicians’ acceptance, and lack of any real incentive. The goal of replacing the entire paper chart with an electronic record was considered problematic due to the large initial costs resulting in the view that only key data should be computerized. As a result, the EHR would complement and not replace the paper record [18]. Others also felt the costs to implement EHRs for general practices would outweigh any gains in efficiency, which also could be achieved through better use of paper records [19].
In the late 1980’s and early 1990’s, hardware became more affordable, powerful, and compact and the use of personal computers, local area networks, and the Internet provided faster and easier access to medical information and initiated the use of web-based EHRs [20]. The personal computer provided a mouse interface which made use easier with pull-down menus, pop-up lists, buttons, multi-page forms, and scrolling fields. Other features included help screens, control functions, audit trails, and export of data to statistical packages for analyses. An initial obstacle for EHR ease of use was the need for portable computers [21] and soon computers were being classified as laptop, palmtop, notebook, and pen-based [22].
EHR Use in 1992
Early use of EHRs also included data interchange for claims processing [23] and image scanning as a method for document capture [24]. Each of these efforts saved time by eliminating filing and retrieval of charts, photocopying, and chart location control [25]. More clinical use began when the physician workstation became the term used for personal computers integrated with EHRs that allowed access to physician notes, orders, consults, laboratory results, radiological studies, direct patient measurements, nursing assessments and notes, and patient care procedures. Workstations interfaced with tools such as drug references, clinical manuals, textbooks of medicine, literature search engines, CDS, and electronic communication [26, 27]. Data also could be represented in a variety of graphical formats which especially facilitated the management of critically ill patients. While not widespread, new applications and functionalities were being developed and used. For example, physicians began to use electronic documentation but many did not believe that computerization saved time, although they appreciated its value for administrative functions and for producing printouts [28]. Networks of microcomputer workstations were used to write all inpatient orders linked to an EHR. While this significantly lowered patient charges and hospital costs, the systems required more physician time than did the paper charts [29]. Likewise, initial attempts at nurse charting failed because they required time-consuming manual data entry. Automated management of patient records became available through the development of patient data management systems which could be connected to bedside monitoring devices to record and interpret patient data in the EHR [30]. Some specific areas such as admitting, pharmacy, laboratory, surgery, radiology, respiratory therapy, and infectious diseases were either interfaced with or completely developed within EHRs [31]. However, laws still required hospitals and practitioners to be accountable for the accuracy and completeness of medical records and thus all documents had to be reviewed and signed. While regulatory and accrediting agencies restricted the auto-authentication of medical records, electronic signatures could and were being used within EHRs [32].
Soon, the use of EHRs produced massive amounts of health care data which were found to be valuable for epidemiologic review. However, secondary use of EHR data soon elucidated issues with the quality of these data for research and evaluation. Use of data for purposes other than those for which the data was collected showed that poor quality data often led to significant misinformation and potential patient harm [33].
Clinical Decision Support
It was recognized that medical information in EHRs could be used for CDS which generated a new major domain of medical informatics. Knowledge bases began to be designed as separate databases and used within EHRs. Some academic EHRs included knowledge bases to feed CDS functions while few of the commercial systems did by 1992 [12, 34, 35]. Early CDS included drug-allergy, drug-drug, and abnormal laboratory test results while other areas were being covered as well [36, 37]. As an effort to influence physician decisions, CDS was built within Physician Order Entry (POE) [38] and required physicians to respond to computer-generated reminders to improve their compliance with preventive care protocols [39]. The benefit of sharing Medical Logic Modules (MLMs) was being tried in order to reduce efforts by avoiding that each group replicates what others had developed and evaluated. The Arden syntax [40] was an initial effort to show that CDS rules could be shared between different hospital EHRs with different databases and data dictionaries. Thus, in order to use data for CDS, numerous efforts to code data were emphasized and the use of “free-text” data was avoided whenever possible.
The Need for Standards
The increase of third party applications being used within EHRs required additional and specific interfaces to be developed. It soon became obvious that standards were needed. By 1992, Health Level Seven (HL7) [41] and IEEE P1157 [42] were being used as the main interface standards by homegrown EHRs and vendors to interface with other systems. The advantage of this approach was to reduce the ambiguity in data element definitions. As a number of EHRs and other applications began to be interfaced, the HL7 standard was refined and expanded into additional domains and became the most practical solution to aggregate ancillary systems like laboratory, microbiology, electrocardiogram, echocardiography, and other results into a central EHR [43]. The need for a consistent message format or syntax was recognized as only part of the problem. The need to use standardized dictionary codes (semantics) was spear headed by the National Library of Medicine and the development of the Universal Medical Language System (UMLS) reminding us today that computer systems come and go, but data last forever [44].
Data from medical devices such as ventilators, bedside monitors, and infusion pumps are critical for patient care. Manual entry of sporadic medical device data did not meet the needs of clinicians. The IEEE P1073 Medical Information Bus (MIB) standard developed to facilitate the interfacing with any type of medical device was only used by a small number of facilities due to the limited participation by medical device vendors [45]. However, Picture Archiving and Communication Systems (PACS) were being successfully used and found to improve the access, storage, and transfer of digital images [46].
Data Exchange and Networks
Data ownership and privacy became common issues whenever data storage and data exchange through computer networks were planned [19]. Despite these challenges, a number of community health information networks were in the developmental stages or at varying degrees of operability [47], and Singapore developed a national computer network for the medical and health community [48]. However, the technology raised several important ethical problems including data control and patient dignity along with other important ethical matters requiring solutions including data ownership, data liability, informed consent to use and retrieve, security, and access [49]. Other extensive views of EHR capabilities, functionalities, and use in 1992 can be found in The Computer-Based Patient Record: An Essential Technology for Health Care, Revised Edition [12] and in the paper by Reed Gardner on the past and future of clinical information systems in this anniversary edition of the Yearbook [50].
EHR Use and Evolution by 2015
Large health care organizations and government agencies are recognizing the value of information in EHRs to determine optimal patterns of care [51]. However, growing issues facing healthcare coverage, privacy, and especially the security of EHRs remain crucial obstacles for their acceptance. Patients, providers, and healthcare facilities continue to demand assurance that these records are securely protected [52, 53]. Thus, as EHR use has increased over time, technical issues continued to be overshadowed by procedural, professional, social, political, and especially ethical issues and the need for compliance with standards and information security [54].
A 2004 random sample of healthcare facilities from across the U.S. found that 13% of respondents had an EHR system fully implemented while 10% did not have or did not plan to have an EHR system. The majority of respondents (62%) used a vendor EHR system and most were not aware or slightly aware of the ASTM E1384 standards for the minimum data elements that should be included in all EHR systems [55]. Some healthcare facilities used a single EHR for nearly all care they provided while others used EHRs from more than one vendor or a homegrown EHR [56].
The number of academic institution developed EHRs in use have declined and been replaced by large vendor EHRs since 1992 [57]. However, the number of EHR-related articles published by academic institutions has significantly increased. From 1991-2005, most articles were published in English and were from North America, followed by the UK, Switzerland, the Netherlands, and Norway [58]. Since 2005, EHR innovation and development and published articles have steadily increased from most European countries, Australia, and Asia, including the establishment of an IMIA journal solely dedicated to applied clinical informatics [59, 60].
Most EHRs are now web/client-server-based, use relational databases, data access and entry screens are navigated using mouselike scrolling and pointer devices. In the U.S., the increase in EHR adoption was stimulated by the 2009 stimulus plan’s Meaningful Use initiative. Electronically sharing medical information from one facility to another has become more frequent and many medical organizations have implemented EHRs and health information exchange (HIE) networks [61]. The Veterans Administration in the U.S. Health Exchange has advanced HIE interoperability standards and patient consent policies [62]. In an effort to reach the same goal, the Canada Health Infoway initiative helped develop interoperable EHRs nationwide [63]. Australia launched a personally controlled EHR designed around the needs of consumers [64]. Estonia implemented a nationwide electronic health record system which gives full access to its citizens [65]. EHRs are implemented and used in ambulatory care in sub-Saharan Africa [66]; and Hong Kong’s web-based electronic patient record system allows integrated, real time patient-based information to be shared in clinics, and private and public hospitals [67]. To exchange a common set of data elements, a common terminology such as SNOMED and LOINC, common data structures, and a common transport standard, the HL7 Clinical Document Architecture (CDA) and The American Society for Testing and Materials (ASTM International) Continuity of Care Record (CCR) are being used [68]. Today, the ASTM CCR is usually viewed within an HL7 message. Remote follow-up of implanted medical devices can be made through data exchanged via an HL7/XML communication protocol to a patient’s clinical information stored in the local EHR [69, 70].
New Functionality and Use
EHR records are now being created, used, edited, and viewed by multiple independent entities including primary care physicians, hospitals, insurance companies, and patients. EHRs are increasingly being used in primary-care exam rooms to document and access patients’ records along with online medical information and decision-making tools, and prescribe medications. They have changed the dynamics of the patient-clinician interaction through clinician-patient email, virtual consults, and telemedicine [71-75].
Additional parts of the paper chart continue to be incorporated into the EHR since 1992. Digital pathology includes the information technology that allows for the management of data and images [76, 77]. Likewise, results from laboratories that are external to the health care enterprise are being integrated into the EHR [78]. Providers are now using order sets, voice recognition, barcodes, and documentation templates to directly enter information into the EHR and decision support rules along with computerized provider order entry (CPOE) are used daily [79, 81]. Mobile devices with high-resolution cameras are also used by clinicians to capture images from the bedside and insert them into the EHR [82]. Medication ordering is now coupled with CDS and includes e-prescribing interfaces to local pharmacies [83]. The inclusion of mental and behavioral health data in the EHR has significantly improved the quality of medical care and increased the use of medical services among patients [84, 85]. However, there is mounting pressure to decrease or remove the need for a patient’s consent to access their medical information. Mental health information is sensitive and potentially damaging if privacy is breached and can result in patients being reluctant to seek treatment if they cannot be assured of confidentiality [86]. Access to behavioral health data becomes even more complicated due to variations in states, countries, and international laws.
While more information is being stored in EHRs and shared with multiple facilities, EHRs are now also being used in nursing homes. This additional environment has been a challenge due to the multiplicity of different providers in a home, the physical structure of the facilities, multiple facility organizations, and high costs of implementation and maintenance. However, EHRs in nursing homes have improved communication between providers, consultants, hospital, and nursing home staff [87], and nursing homes are increasingly introducing EHRs into nursing practice [88]. Also, EHRs are being used by home health or hospice care [89], organizations that provide care to the homeless population [90], and departments of corrections [91].
The increased demand by patients to access their healthcare data has led to more personal use of the EHR [92]. Personal Health Records (PHRs) are now interfaced with applications within EHRs and are used by most large facilities and vendors [93]. Many patients are taking a more active role in managing their medical data which is essential for patient-centered care [94]. Patient-centered-care allows patients to add personal stories of key life events both medical and non-medical that enable clinicians to better understand what matters and is important to patients, and what are their personal health goals and care preferences [95, 96]. Recent reports have highlighted the need for efforts to better understand the collection and use of this information in the EHR [97] and there is a lack of consensus on how PHR success will be determined [98, 99]. There are no comprehensive laws or procedures regarding patients’ access rights to EHRs [100]. Another problem may be that the use of PHRs may be challenging for some older adults or those of lower socioeconomic status and with low health literacy [101].
Family health histories are also being entered into EHRs. They are used to assess disease risk and offer insight into the interplay between inherited and social factors relevant to patient care [102]. Additionally, the human genome has now been decoded and whole-exome and whole-genome sequencing results are now being stored in the EHR [103, 104]. DNA results can be provided to the practitioner, used for CDS, and collected data in the EHR serve as a source of phenotypic information for analytic purposes [105]. Together, these data sources make the EHR the paramount source of phenotypic information and genomic research [106]. However, there remain challenges in extracting phenotypic data that sometimes need to be inferred from multiple sources. But, recent work has made progress in translating “omic” data into patient care and CDS using pharmacogenomics data [107, 108]. Biobanks are now linked to personal and family health information in EHRs to accurately identify subjects with specific diseases and phenotypes and to identify genotype-phenotype associations [109].
In addition to patient and family health benefits, public health has found increased value in EHRs. Biosurveillance systems are linked to EHRs to detect events of public health significance [110]. Adapting EHR systems to serve public health needs provides the possibility of enormous advances in public health practice and policy [111]. Distributed networks for public health surveillance allow public health to initiate custom queries against participating EHRs while the data remain behind each practice’s firewall [112].
CDS applications continue to be promoted as one of the key features of EHRs. Diagnostic decision support systems were some of the earliest examples of medical informatics innovations. Computer-based diagnostic systems are available commercially and studies have shown that these computer programs have strengths and limitations [113, 114]. In addition, a comprehensive taxonomy of front-end CDS tools has been developed and validated. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of CDS content [115].
Modern patient care depends on a number of different medical devices in order to monitor a patient’s vital signs, infuse medications, and maintain life support. Data from medical devices such as ventilators, infusion pumps, bedside and portable monitors, and others are interfaced to EHRs through custom interface applications [116, 117]. Not only is this data valuable for a patient’s EHR, but it is essential for CDS applications to help prevent patient harm. Integrated Development Environments are now used along with new programming languages to facilitate and accelerate the development of CDS and other applications. A comprehensive discussion of current CDS capabilities can be found in Greenes’s “Clinical Decision Support” [118].
The increased amount of patient information stored in the EHR continues to include a large variety of free-text documents. This spawned the need for the use of Natural Language Processing (NLP) to read and code free-text data which has become common within most EHRs [119-121]. NLP and inference rules have acceptable performance for understanding and finding previously hidden information in dictated documents and especially for adding problems to the problem list [122].
The growing amount and availability of EHR data also present new opportunities for discovering new knowledge about diseases. In the past decade, there has been an increase in big- data and text mining focused on the identification of disease associations [123]. Big-data offers the promise of large-scale EHR data analysis of outcomes, patterns, temporal trends, and correlations. Many think the evolution of Big Data analytics will use EHR data and move us from description and reporting diseases to forecasting, predictive modeling, and decision optimization [124].
However, EHRs are often considered as incomplete. In 2011, fewer than 5% of anesthesia departments used an EMR that was anesthesia specific [125, 126], primary care functions frequently remained unsupported [127], and pediatricians reported the absence of pediatric data and functions in EHRs [128-130]. Not all available patient information is entered due to physicians’ and other providers’ complaints about increased workload and the inflexibility of EHRs and CPOE [131]. These complaints spawned the use of medical scribes, who are trained medical information managers specialized in charting physician encounters in real-time and assisting in the navigation of the EHR [132]. Implementation also continues to be limited in rural areas due to financial barriers [133]. Open source technology is becoming a solution to overcome the problems of high-cost and inflexibility associated with the proprietary EHRs. Open source EHRs are being used in a number of countries across the world and mainly in Sub-Saharan Africa and South America [134-137]. While open source EHRs may have limited capabilities currently, they offer a better option than paper and continue to improve their capabilities, functionalities, and user acceptance [138].
Still, healthcare providers are under increasing pressure to enable widespread access to their EHRs for the patients they serve. The meaningful use incentive program in the U.S. has been a significant driver encouraging this access. Elsewhere, the cloud has become extremely efficient and successful at establishing digital identities for individuals and making EHRs interoperable across heterogeneous systems. As the healthcare industry contemplates providing patients more access to their EHRs, the solution could leverage existing cloud technology [139, 140].
EHR data generated in the care of patients are also widely used to support clinical research and quality improvement [141]. The enormous amount of data being collected by EHRs has generated additional value when integrated and stored in enterprise data warehouses (EDWs). The EDW allows all data from organizations with numerous inpatient and outpatient facilities to be integrated and analyzed [142]. These data are not only an essential tool for management and strategic decision making, but also for enhanced data exploration, cohort identification, population management, and patient specific CDS. Patient data that was previously stored on removable disk packs or tape are now stored online; birth to death.
Implementation and Value
As stated, this paper focuses on the overall state and use of EHRs in 1992 and their evolution as of 2015. Some of the functionality and use described resulted in common use and opened new domains for most EHRs that have become standard while others may have only been reported in a single paper and later found to have little value or were never implemented outside the original facility. Perceived value and use are often dependent on the workflow of a medical specialty or facility. Thus, published work describing EHR capabilities was included, although it was beyond the scope of this paper, to comment directly on value or sustainability for each case. Further, an unsuccessful initial development may be used to identify new and useful functionality for future improvement.
Addressing Hurdles to Optimal Use of the EHR
Some healthcare professionals continue to develop workarounds and rely on paper alternatives rather than using EHRs [143]. Understanding of the reasons why EHR functionalities vary and why there is a need for workarounds remains important to facilitate user-centered design and create needed education for EHR use [144, 145]. There also continues to be discussion on the right balance between information overload and the right-and helpful-information [146] including the need for restrictions on the use of copy and paste to limit the growing challenge of ‘note bloat’ [147]. Moreover, many studies have demonstrated unintended negative consequences of the use of EHRs on the quality of care [148-151]. Research on the application of human factors to the design and development of EHRs has been used to improve their use and prevent unintentional consequences [152]. A centralized, nonpartisan board with an appropriate legal and regulatory infrastructure to ensure the safety of EHRs has been proposed to facilitate the identification of EHR-related adverse events and errors and potentially create a safer and more effective health care delivery system [153].
With the advanced capabilities of EHRs, the enormous amount of information that may not always be easy to locate and the potential of unintended consequences, education and training have become major issues. Clinicians are now being prepared to practice in an EHR-mediated world including electronic medical education [154-156]. Some medical schools are including lectures on EHR use. Educational systems have been integrated into the EHR [157]. Students of health professions and practicing professionals can access and interact with a set of representative solutions using an interdisciplinary EHR educational portal [158]. Likewise, medical simulation centers have been integrated into EHRs which provide realistic environments for usability testing, training, and evaluation of human-computer interactions [159]. A major role of simulation training is also to test the efficacy and safety of EHR-user interfaces, identify implementation gaps, and improve their safety [160-162].
Many medical school curricula have also added content on information retrieval [163]. Linking the EHR to the digital library and thus allowing the automatic integration of clinical data with relevant knowledge-based information to support informed decisions has been an important informatics goal [164]. Online information resources are now linked to EHRs and the role of medical librarians has changed to support this effort [165]. Infobuttons are forms of CDS and education tools that use information about the clinical context (institution, user, patient) in which an information need arises to provide direct access to relevant information from knowledge resources that accept context parameters from an EHR. Using the knowledge base of resources and information needs, these tools generate a set of links that direct the user to relevant information [166]. Infobuttons are standards-based, open source Web services that disseminate specific information in multiple EHR systems anticipating clinicians’ questions and providing automated links to relevant information in knowledge resources [167]. Additional history and information of EHR capabilities and functionality can be found in the chapter “Electronic Health Record Systems” in “Biomedical Informatics: Computer Applications in Health Care and Biomedicine” [168].
Discussion
Expectations for and Realization of EHRs in 1992
The changes in the use and handling of EHR information initiated by new technology, especially the microcomputer and internet would have been hard to predict prior to 1992. New technologies and events have had and will continue to have a profound effect on the development and use of future EHRs (Table 2). Even prior to the 1990s, it was expected that EHRs would become technically and economically feasible on a broad scale [169] and their data would be transmitted across high speed digital networks in response to user and patient needs [170]. Those are common daily occurrences in many places around the world and modern medical care is dependent on this ability. The Institute of Medicine’s 1991 recommendations stated that by the year 2000, each physician’s office should use an EHR in order to improve patient care and its provided rules and regulations focused on patient privacy and confidentially have only been partially realized as of 2015 [12]. Likewise, while EHR data in form of text, images, and voice are available instantaneously via the internet from virtually anywhere in the world, providers still do not have all the patient information they need [171, 172]. However, it is hard to downplay the enormous advancements that have taken place. Meaningful Use in the U.S. has had a positive influence on the implementation of EHRs in more hospitals and primary care physician offices [173]. While, some feel EHR adoption is outpacing published evidence of improvement in patient care, there is a growing body of descriptive literature regarding incentives, benefits, risks, costs of adoption, and utilization.
Table 2.
Expectations and realization of EHRs in 1992
Expectation | Realized |
---|---|
EHRs would become technically and economically feasible on a broad scale | yes |
Data transmitted across high speed digital networks | yes |
Each physician use an EHR | partially |
Rules and regulations for patient privacy and confidentially | partially |
Standards for EHR data including secondary uses for population data, communications, decision support, terminology and especially data exchange | partially |
Reduction in administrative costs of the healthcare | yes |
Voice recognition | yes |
Improved and extended use of image acquisition devices, | yes |
Expanded use in the ambulatory setting | yes |
Eliminate data duplication | no |
Simplify quality assurance, ease collection, generate reports, treatment plans, and medication orders | yes |
Computer diagnosis | partially |
Save clinician time | no |
Life-long EHRs | yes |
Improve patient care | yes |
Require change in medical practice | yes |
Pluggable medical logic modules | partially |
Completely interoperable Medical Logic Modules (CDS) | partially |
The expectation to have standards for EHR data including secondary uses for population data, communications, decision support, terminology, and data exchange has seen constant advances and progress, but still requires further work especially as new technology and innovation continue and the need for open services has become paramount [42, 44, 174, 175]. However, the number of organizations and vendors implementing HL7 has increased and the standard has continued to be refined and expanded along with new domain-specific areas [41].
Likewise, the expected reduction in administrative costs of the healthcare system through claims processing of EHR data utilizing data exchange standards has been realized [23]. At the same time, the IEEE P1073 MIB standard that had promised to facilitate the exchange of data between EHRs and medical devices was not supported by the medical device vendors and is currently not used [45].
The expectations for voice recognition have been realized and voice recognition has been accepted as a common method for dictated data entry into EHRs [176]. The improved and extended use of PACS image acquisition devices and medical image processing and management has had a positive impact on patient care [46]. The EHR was initially expected to provide the ability for computer diagnosis. While some definite advances have been made, computer diagnosis failed to reach the initial expectations of 1992.
The expectation to have EHRs used in the ambulatory setting has been realized and EHRs have been interfaced to or combined with hospital EHRs [177]. The use of EHRs in the ambulatory setting has been associated with increased adherence to recommended care [178]. This has been accomplished in part by the expected use of portable computing devices that can access patient information and allow patient information to be charted in the busy medical office [21, 22].
The expectation that EHRs would only complement and not replace the traditional office record, unfortunately, continues to be reality in many facilities around the world [18]. However, the expectation had implied that the EHR could be implemented in a modular step-by-step fashion rather than all at once with its high associated costs.
It had been expected that EHRs would eliminate data duplication [179] and save time by automatically issuing routine reports, improve clinical practice, simplify quality assurance, ease data collection, generate reports, treatment plans, and medication orders without removing records from circulation [180]. While we see some of these expectations realized today, we still suffer from data duplication and many clinicians do not believe EHRs are saving time.
Finally, we expected that health care reform and the changing healthcare environment would require medical data to be in electronic form that could be accessed by providers, hospitals, government organizations, and private health care management. Thus, the “successful” medical practitioners in the future would need to change the way in which they provide care and would be those whose practices have “life-long” EHRs that allow comprehensive medical record keeping, inclusive of patient charting, billing, coding, scheduling, and data reporting to third parties [181-183]. We have seen that the healthcare reform and the changing environment worldwide have definitely accelerated the implementation and use of EHRs. However, how we measure success was not defined back in 1992. A number of events and technologies helped to accelerate the development of EHRs. Unfortunately, there also has been a number that disrupted or derailed that effort (Table 3).
Table 3.
Events and technologies that helped to accelerate and disrupt or derailed planned development of EHRs
Accelerate | Disrupt or Derailed |
---|---|
Personal computers | Data quality issues |
Internet-cloud | Lack of certain standards |
Email, pagers/cell phones | Poor user design |
Local and wide area networks | Alert fatigue |
Client-server technology | IEEE P1073 Medical Information Bus (MIB) standard not used by medical device vendors |
Natural Language Processing | Lack of vendor Interoperability (APIs) |
Human genome | Social and political factors |
Interface standards | Lack of data security technology |
Email, pagers and smart phones | Innovation barriers |
Open-source | Financial/business goals trump medical needs: Billing vs patient care |
Wifi | Clinician’s inability to completely describe the clinical story of the patient within EHRs |
Picture Archiving & Communication Systems | Clinician need to fit medicine into a limited array of codes |
Personal Health Records | Lack of understanding of how to store and report genetic information |
Family history information | Limited use of open-source EHRs |
SNOMED-LOINC | Inflexible, proprietary, nonintuitive, expensive, difficult to maintain and rarely interoperable EHRs |
Unified Medical Language System | Unintended consequences |
BAR codes | Differences in semantics and data dictionaries |
Meaningful Use in the U.S. | Lack of clinician input and testing in application design and development. |
Improved relational databases | Billing and regulatory compliance driving clinical documentation |
Reduced cost of data storage and hardware | |
Integrated Development Environments | |
Increased number of EMR vendors |
Where Are EHRs Expected to Be in the Next 25 years?
Current EHRs do not meet the needs of today’s distributed systems and of the rapidly changing healthcare environment [184, 185]. The ability of applications to communicate, interpret, and act intelligently upon complex healthcare information has assumed paramount importance [186]. The future lies in the development of flexible component-based architectures that can operate seamlessly within the workflow of a healthcare environment (Table 4). Much of EHR adoption continues in an environment shaped by paper chart thinking, which continues to limit successs [187]. Further research is needed to understand human-technology integration factors that may be causing clinicians to continue to rely on paper alternatives to the EHR [143]. More research is needed to determine how to integrate the EHR into patient encounters more effectively [188] and provide clinicians with a greater control of the EHR resulting in greater flexibility to fit to their needs and preferences [189]. Many physicians are optimistic about the future benefits of EHRs, but are frustrated with the non-intuitive and multi-click interfaces and cumbersome data searches of existing EHRs [190].
Table 4.
Design and capabilities of EHRs in the next 25 years
Flexible component-based architectures Not shaped by paper-chart thinking Based on human-technology integration factors Clinicians will have greater control of the EHR customization resulting in greater fit to their needs and preferences Intuitive graphical user interfaces Totally electronic and clinician approved Based on internationally accepted standards Built in Health Information Exchange capabilities with pluggable application programming interfaces and open services. Pluggable, interchangeable and API based patient specific clinical decision support modules not dependent on EHR versions and updates. Built-in infrastructure to monitor and learn from adverse events and errors and potential adverse events and error. Complete access and use via mobile devices Extensive use of voice recognition Improved data entry applications Improved recognition and reduction of alert fatigue Improved computer diagnosis No data duplication across all continuity of care Measured reductions in clinician time World-wide access with secure information across all platforms Imbedded natural language processing Imbedded foreign language translation with preservation of clinical meaning. Birth to death data storage coupled with enterprise data warehouses Complete genetic data storage with result interpretation Ability to synthesize fragments of evidence documented in the entire record to understand the etiology of a disease and its clinical manifestation in individual patients. Big data storage and analysis needed for precision medicine and forecasting, predictive modeling, and decision optimization. Major contributor for a learning health system Increased patient access and control Interfaces for biosensors for improved patient monitoring Extended capability for population health Increased use for medical research and education Increased use of cloud technology Increased use, storage and access of social, economic, behavioral and environmental data Designed by clinicians and developed by those with medical knowledge (Medical Informaticists) Longitudinal based record; birth to death. Not encounter/billing based Domain knowledge to identify relevant parts of the record to display Increased development and use of “infobutton” like technology |
While the goal of creating integrated EHRs is within our reach, its success will depend chiefly on the creation and especially adoption of standards by all international parties [191]. HIE which will enable data integration, semantic interoperability, and CDS across multiple EHRs has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems [192, 193]. The opportunity for enabling such scalable CDS will require vendor-supported, web-based CDS development platforms along with vendor-supported application programming interfaces (APIs) allowing the use of innovative, pluggable, interchangeable, and API-based CDS applications. This will probably require initially using custom EHR APIs and then moving towards standardized EHR APIs which are already starting to be supported by major commercial EHR vendors [194]. Web applications that run on the Substitutable Medical Apps, Reusable Technologies (SMART) platform are starting to be used. The SMART platform is an example of an emerging framework that enables EHR systems to behave as “iPhone like platforms” by exhibiting an API for easy addition and deletion of third party applications [195].
Genetic testing has had limited impact on routine clinical care. Widespread adoption of future EHRs will provide the needed methods of disseminating genetic testing into diverse care settings [196]. However, the successful integration of genomic data will require significant redesign of existing EHRs. The future EHRs will be able to manage the size and complexity of genetic test results, use standards for combining clinical and genetic data, and eliminate the current limitations in the capacity to store and analyze genetic data. Related challenges of the uncertainty in the interpretation of results and privacy concerns specific to genetic testing will be resolved and EHRs will provide the genetic, environmental, and lifestyle data needed for precision medicine and the improvement of patient care [197].
The capabilities of NLP will continue to advance and its use will be needed to code the increasing dictated free-text produced by the concomitant advances and use of voice recognition. Data storage capabilities to handle the massive amount of patient information will increase as storage capacities will increase and the related costs decrease. Transforming clinical data into knowledge to improve patient care has been the goal of biomedical informatics professionals [198]. With the increase in the amount of electronic healthcare data, the potential for knowledge discovery will be substantial if data are managed in innovative and effective ways [199]. Some data sets will be so large or complex that traditional data processing applications will be inadequate. This will require the creation of new big data applications especially for data sharing. Analyses of this “big data” will provide the next step to transform healthcare data into actionable knowledge.
Displaying large amounts of irrelevant patient information can lead to information overload and user error. Next-generation interfaces for EHRs will use CDS to synthesize fragments of evidence documented throughout the entire record to understand the etiology of a disease and of its clinical manifestation in individual patients. Context-based EHRs will employ biomedical ontologies and disease models as sources of domain knowledge to identify relevant parts of the record to display [200]. Usability, the ultimate goal of recording and managing patient data, will require improved technical considerations in addition to appropriate methodologies for medical data management [201]. Since EHRs will continue to have the potential to increase medical errors, built-in EHR applications that detect physician-level usage of EHR features, and clinical simulations will be needed to analyze human-computer interaction in real healthcare settings [162, 202]. As EHRs continue to change and improve, engineering and reengineering will still be needed in order to increase their beneficial potential while at the same time improve their safety.
The fundamental role and purpose of the EHR in the future will be a data repository based on international standard APIs for the retrieval and storage of data. It will be coupled with facility and vendor provided, and user selected applications for data review and entry and especially CDS. In addition to health data, social, economic, behavioral, and environmental data will play a vital role in providing and especially improving healthcare. The applications will be interchangeable, not dependent on EHR versions and updates, and will facilitate innovation like the current Smart Phone applications [203].
EHR safety concerns involving both unsafe technology and unsafe use will persist in the future. Mounting pressure will require EHR implementations to build a robust infrastructure to monitor and learn from adverse events, errors, and potential adverse events and errors [204]. These errors will be electronically and securely reported to a centralized, nonpartisan body (like a patient safety organization) whose purpose will be to find ways for future prevention rather than punishment [153].
Tourism as well as international business travel creates health risks for individuals and populations [205]. International HIE standards like those proposed by the International Medical Informatics Association will provide travelers with their complete personal medical information interfaced with their primary EHR [206]. This information will be available on mobile phones and other future mobile devices. Applications will allow that information to be securely uploaded to any standards-based EHR using state of the art cloud-like technologies to provide current medical care. New information, including patient entered, will be stored in the primary EHR [207, 208]. This will be coupled with tele-health which will allow the patients’ primary care physicians to directly see and communicate with other healthcare providers in urban as well as rural areas worldwide through computerized language translation and the preservation of clinical meaning [209]. Thus, it will be necessary to develop specifications for privacy and trust agreements between international partners [210, 211].
Use of mobile devices with high-resolution cameras by clinicians to capture images from the bedside and incorporate them into the EHR will increase. However, secure and efficient ways to manage and share digital images are lacking to date. Future clinical image applications should more closely link clinical images and documentation and should consider enabling secure transmission over public WiFi or cellular networks. The capability to share data and harness their potential to generate knowledge rapidly and inform decisions will have transformative effects improving health. The infrastructure to achieve this goal at scale --marrying technology, process, and policy-- is commonly referred to as the Learning Health System [212]. We have been extremely fortunate to have the foresight and perseverance of a number of early biomedical informatics pioneers. While, we hope for a totally electronic and clinician accepted EHR within the next 25 years, we’ll have to wait and see. However, based on the current growth in education and training of numerous talented and innovative people, the future looks bright.
Acknowledgments
I’d like to thank Kyle V. Johnson, Stephen Howe, James F. Lloyd and Jacob S. Tripp for input on classifying events that have either accelerated or disrupted/derailed EHR development.
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