The solution to the first problem, that of merging data from many sources into one EMR, lies in standards which the informatics community began to develop in the mid 80s.
18 Standards provide the bridges to the many islands of electronic patient data so that the data can inexpensively be combined into an electronic medical record.
The standards needed to transport patient data from one system to another inexpensively are in place. With these standards we can solve many of the problems and create a first-stage medical record system from the extensive medical data that already exist in systems such as laboratory, pharmacy, dictation, scheduling, EKG cart, and case abstract systems.
Standard mechanisms for communicating over networks in a secure fashion exist, as do standards for delivering structured medical record content like patient registry records, orders, test results, and standard identifiers for coding many (but not yet all) of the concepts we want to report in the fields of such structured records.
The communication standards of choice are the internet standards including the base internet protocol for sending packets of information, the Secure Sockets Layer for encrypting transmitted information, Certificates for verifying the identity of the communicant, and EDI over the Internet for secure MIME e-mail, to name just a few. The Internet protocols are the communications standards of choice for a private
Intranet as well as for the public
Internet. I believe that available or announced security tools are more than adequate for the threat over the public Internet. Those who do not believe can limit or avoid access to the public Internet until they can reach the necessary level of confidence. Anyone who would like to explore these Internet standards can download them from the Internet at no cost. (See
http://www.internic.net/std/std-index.txtfor formal standards, and
http://www.ietf.org/lid-abstracts.htmlfor draft standards.)
HL7
19 is the message standard of choice for communicating clinical information such as diagnostic results, notes, referrals, scheduling information, nursing notes, problems, clinical trials data, master file records, and more. It is used by more than 2,000 hospitals, by the US Centers for Disease Control and Prevention (CDC) for immunization, communicable disease and emergency visit information, as well as by most large referral laboratories. It is also widely used in Canada, Australia, New Zealand, Japan, and in many countries in Europe. Its nearly 2,000 members include 90% of the health system vendors, as well as major pharmaceutical and computer manufacturers. HL7/ASTM provides the structure (like a set of database records) for interchanging patient information between source systems like laboratory, dictation and pharmacy systems data repositories such as cancer registries, performance databases and medical record systems. HL7 provides all of its minutes, proposals and its draft standards on the internet at no cost. (See
http://www.mcis.duke.edu/standards/HL7/h17.htm.)
The message standards do not specify the choice of codes for many fields. They do provide a mechanism for identifying the code system for every transmitted code. This pleuralistic strategy was the only alternative in the past because universal code systems did not exist for important topics such as laboratory tests and clinical measurements; so institutions used their own local codes. Fortunately, universal code systems are now available for subject matter such as units of measure (ISO+
21), laboratory observations (LOINC
22), common clinical measurements (LOINC), drug entities (NDC
23), device classifications (UMDNS
24), organism names, topology, symptoms and pathology (SNOMED,
25 IUPAC
26), and outcomes variables (HOI
27). Even better, most are available without cost. So, for at least some source systems, we have all of the pieces needed for creating EMRs inexpensively from multiple independent sources, inside and outside of a health care organization.
I mention LOINC because it fills in an important gap (and it has occupied much of my recent life). At least four large commercial laboratory vendors (Corning MetPath, LabCorp, ARUP, and Life Chem) representing more than 20% of the nation's laboratory testing, and other care institutions (Intermountain Health Care, Indiana University Hospitals, University of Colorado, and the Veterans Hospitals) are actively converting to the LOINC laboratory test code standards mentioned above. The Province of Ontario, Canada, is using LOINC for a province-wide system, NLM incorporated it into the UMLS,
28 and ICD10-PCS has also incorporated it.
Readers should lobby their organizations, information system vendors, and external diagnostic study suppliers to use these communication, messaging and code systems standards. Information about all of them can be obtained from the following web site.
The sooner everyone adopts them, the faster and easier it will be to build first-stage EMRs.
The problem of linking to sources outside of one's organization is a little more difficult because of the differences in patient, provider, and place of service identifiers from institution to institution. However, these problems can be overcome in a local institutional cooperative by using linking algorithms with nearness metrics for identifiers such as patient name,
29 and by making local choices of standards (e.g., state license number for provider identifier). P.L. 104-191 (formerly the Kassebaum-Kennedy bill) requires a national patient and provider identifier, so it is likely that such identifiers will be available in the United States soon.
The data from large ancillary services (e.g., laboratory and pharmacy) and dictated notes (discharge, visit notes, diagnostic reports) make a very good starting EMR. First-stage EMRs can also provide reminders and retrievals to support a quality-assurance mechanism, and they can provide some management and research capability. However, these benefits are all constrained by the scope of the data available within the EMR. For example, a hospital would rarely have full information about pediatric immunization records, so it could not generate accurate reminders or quality assurance reports about pediatric immunizations without additional investment in interview and data entry time to capture and enter this information.
The benefits are also constrained by the degree to which information is stored as free text rather than as structured and coded results. For example, if blood pressures levels are buried in the free-text narrative of a visit note, the computer will not be able to find and interpret them for reminders or quality-assurance activity. Those planning the creation of an EMR should take the time to inventory their planned data sources against the data needs of particular management, or reminder projects, to see if the EMR will be able to perform those particular functions, and if not, consider investing in manual data collection to achieve their important goals.