Regenstrief Medical Record System (RMRS)

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The Regenstrief Medical Record System (RMRS) is a comprehensive electronic health record (EHR) used at the Indiana University Medical Center and the surrounding Indianapolis area [1]. The Regenstrief Medical Record System handles laboratory results, orders, medications, registration information, nursing assessments, EKGs and other clinical data.


History of RMRS

In 1972, Clement J. McDonald and Charles Clark began collecting data on 35 diabetes patients in Marion the County General Hospital. McDonald and Clark built a hard coded program to enter patient data, store it in a data struture, and print flowsheet reports. Difficulties arose because data was not always collected. Clinical personnel often did not mark patient replacement cards for manual data re-entry. Laboratory results from different departments were not shared. The hard coded data structure was also unsustainable, and soon replaced by a data base system.

Overview of RMRS

Organizational and geographic scope

The Regenstrief Medical Record System (RMRS) serves 1.3 million patients, records 200 million separate coded observations, 15 million prescriptions and 212,000 electrocardiographic (EKG) tracings. 1300 nurses, 1000 physicians, and 220 medical students access patient data over 628,000 times per month. The Wishard Health Services accesses the RMRS 10 million times per year. The RMRS is used by the Indiana University Medical Center, 40 local clinics, and 30 outreach clinics.

Mission statement

The RMRS hopes to lead in three areas:

  1. Physician leadership in the informatics effort. Physicians are intelligent, confident, energetic, and possess important clinical knowledge.
  2. Commitment to high quality health care that is driven by the best in the hospital
  3. Continuous quality improvement via user feedback [2]

Goals

The goals of the RMRS are to:

  1. Eliminate the logistic problems of a paper recording system. An electronic recording system makes clinical data immediately available to authorized users. There will no longer be lost or misplaced papers, or undecipherable notes.
  2. Reduce the manpower needed in clinical bookkeeping and managing patients. An electronic recording system automatically reminds patients of their laboratory results and diagnoses.
  3. Create informational 'gold' in the medical record. All the information would be accessible to clinical, epidemiological, outcomes and management research.

The Three-Legged Stool

The RMRS is built upon three crucial foundations- each of which may be considered a three-legged stool:[3]

Foundation I: Committed support of the leadership and close collaboration between-

  1. The Regenstrief Institute
  2. The Wishard Memorial Hospital
  3. The Indiana University School of Medicine, with it's faculty and the affiliated clinical practices

Foundation II: The tripartite a mission of an academic medical center-

  1. Teaching
  2. Research
  3. Public service

Foundation III:

  1. Careful analysis and improvement of processes
  2. Technical excellence
  3. Responsiveness to user need


Technology

The RMRS has served as the laboratory for many high quality studies of the application of clinical information systems to hearth care, including a landmark study of the impact of physician order entry within a hospital.


Hardware

The RMRS operates on Digital Equipment’s Alpha computers and a Novell-based PC network. The central system communicates via 10 megabit Ethernet links, 1.6 megabit T1 lines, or 56-Kb modems. The system’s software uses web browser technology that supports voice dictation and voice understanding features. Initial assessments of hospitalized patients are recorded on portable PCs that utilize Proxim’s spread spectrum technology.

Unique Patient Identification Numbers

A global patient number identifies patients. This allows the RMRS to identify patients, even when they go to a different doctor or hospital. However, one patient could be given more than one identifier; RMRS has a mechanism to combine the data from two different chart numbers into one, and for reversing when the combining was a mistake. [1] To account for variations in name, the identifying index uses a sophisticated matching algorithms to determine if registration records from different hospitals are from the same patient. If the registry records match, all medical records from all locations can be produced for one patient. This ‘cross enterprise’ access occurs at a very low level and allows most of the RMRS texts to function in this multiple enterprise environment with minimal modification.

Data Capture

RMRS data capture aims to be comprehensive and efficient. The RMRS faces a challenge to capture data from multiple systems, formats, types of data, and from a large number of people. Universal or standardized codes such as LOINC and SNOMED through HL7 interfaces have made it easier to capture clinical data.

Types of data captured

  • Registration information: demographics, insurance information
  • Scheduling and visit activity: site, charges and diagnoses
  • Outpatient prescription data: prescriptions filled at the Regenstrief pharmacy
  • Diagnostic test results: from clinical laboratory, pathology, radiology, diagnostic cardiology (e.g. EKGs)
  • Imaging studies, procedures and diagnoses
  • Vital signs: blood pressure, pulse, temperature, weight
  • Death certificates
  • Charges and billing

Table 1 shows a sample of the kinds of data captured by the RMRS at the Clarian/IU/Riley hospitals and Wishard hospitals. http://img16.imageshack.us/img16/3250/rmrs.png

Direct capture by electronic interface

Data capture can be made directly from instruments, such as a bedside measuring devices recording inpatient blood pressure, pulse and temperature, and EKG measurements and tracings. Data can also be collected by three patient registration systems, three laboratories, three pharmacies, two appointment scheduling, two dictation transcriptions, one radiology, one nurse telephone triage and five billing systems. The dictation systems produce an unstructured raw word processing file, which requires an algorithm to find key information, such as patient ID, date and report type. Manual effort must be expended as 1-5% of dictated reports have key data errors.

Clerk data entry

Specially trained personnel code and enter most diagnostic reports that are not coded by the source system, such as EEG, EMG, colonoscopy, radiology and endoscopy reports. The coders enter standardized phrases and abbreviations rather than numeric codes, that would add to the training. This allows the system can understand the diagnostic content for patient retrievals and reminders. The computer translates these standardized text phrases into internal codes for storage, and back into human readable language. The data entry clerks also enter the number values of predefined questions, such as blood pressure or finger stick glucose.

Physician entry

Originally, the RMRS did not require data entry for physician observations because physicians were reluctant to do so. The system developers first enlisted physicians for data entry with a physician orders system because orders are more easily structured for data input than observations.

Physicians began entry of outpatient test orders in 1984, and in 1990, this was extended to outpatient test orders. In 1994, the Institute extended RMRS to the Indiana Network for Patient Care (INPC) in order to link Indianapolis' five major hospital systems. The majority of all hospital discharge notes have been entered by physicians since 1997.

Rule-based reminders/Decision Support

In 1974, the RMRS is the first EHR to implement rule-based reminders to make physicians make better clinical decisions. Reminders can be generated by the system called CARE; a rule based system which can generate reminders or retrieve patient records base on pre-specified criteria. [2]

The Gopher workstation also allows the printing of personalized patient information handouts, permits doctors and nurses to communicate via confidential email and can even display satellite weather photos. . The system also allows for printing of hard copy inpatient paper reports, referred to as ‘scut’ cards, that fit neatly into a physician’s lab coat pocket in the form of a small booklet that provides a compact overview of the patient’s state. Physicians can also access past issues of leading medical journals and the American Hospital Formulary drug monographs to research specific topics or learn more about a certain medication. For clinical questions, they can consult the Journal of the American Medical Association, New England Journal of Medicine, Annals of Internal Medicine, the Yearbook of Medicine, NLM’s Medline, and full bibliographic references for any numbered citation on the user interface.

Search and retrieval capabilities— cross-patient reports

Cross-patient searches can be performed for IRB-approved research and quality management purposes. CARE language can be used to search the entire data base, a subset of the data base, or several institutions’ databases for patients whose EMR contains particular patterns of data. [4] Fast retrieval is a second way to search the data base. It uses direct indexes by clinical variable (e.g. glucose, chest X-ray) and by results within the medical record files to provide fast access to medical records based on the content of those records. Fast retrieval produces a list of patients who satisfy the search criteria. It can then retrieve specific data elements from each of those patient’s medical records. This functionality lends itself well to retrospective clinical research.

Future challenges

  • Complete capture of care provider notes
  • Dictation & Voice recognition (eg. Active X component that Dragon System's voice understanding)
  • Note capture system from Datamedic
  • Wireless provider carried devices
  • User identification (eg. Biometric identification)

References

  1. McDonald, C. J., Overhage, J. M., Tierney, W. M., Dexter, P. R., Martin, D. K., Suico, J. G., . . . Wodniak, C. (1999). The regenstrief medical record system: A quarter century experience. International Journal of Medical Informatics, 54(3), 225-253. http://www.sciencedirect.com/science/article/pii/S138650569900009X
  2. McDonald, C. J., Overhage, J. M., Tierney, W. M., Dexter, P. R., Martin, D. K., Suico, J. G., . . . Wodniak, C. (1999). The regenstrief medical record system: A quarter century experience. International Journal of Medical Informatics, 54(3), 225-253. http://www.sciencedirect.com/science/article/pii/S138650569900009X
  1. McDonald CJ. The Regenstrief Medical Record System: a quarter century experience. International Journal of Medical Informatics. 1999. 54(1999)225-53 [5]
  2. McDonald, C.J., Tierney, W.M., Overhage J.M., et al. (1997). The three-legged stool: Regenstrief institute for health care. In J.M. Teich (Ed.), The third annual Nicholas E. Davis award: Proceedings of the CPR recognition symposium: (pp. 131-158). Shaumburg, IL.
  3. McDonald CJ, Tierney WM, Overhage JM, Dexter PR. The Three Legged Stool: Regenstrief Institute for Health Care. Proc 3rd Annual N.E. Davis CPR Recognition Symp. 1997; 101-147
  4. Indiana School of Medicine
  5. RMRS Introduction
  6. Dexter PR, et al. A Computerized Reminder System to Increase The Use of Preventative Care for Hospitalized Patients. NEJM 2001; 345 (13):965-70.
  7. Friedlin J., et al. Details of a Successful Clinical Decision Support System. AMIA Annu Symp Proc 2007; 2007:254-258.
  8. Indiana Network for Patient Care
  9. Clement J McDonald, William M Tierney, J Marc Overhage, Paul Dexter, Blaine Takesure, Greg Abernathy. The Three-Legged Stool, in : Regenstrief Institute for Health Care