Evaluation of Automated Hospital Data Management Systems

The clinical laboratory (LAB) was an early adopter of computer technology, beginning with the chemistry and hematology laboratories, which had similar information processing requirements. LAB systems in the early 1960s were primarily offl ine, batch-oriented systems that used punched cards for data transfer to the hospital mainframe. The advent of minicomputers in the 1970s caused a rapid surge in the development of LAB systems that supported online processing of data from automated laboratory instruments. In the 1980s, LAB systems increasingly employed minicomputers to integrate data into a common database and satisfy functional requirements, including programs for quality control, reference values, trend analyses, graphical presentation, online test interpretations, and clinical guidelines. By 1987 about 20 % of US hospitals had computer links between their LAB systems and their hospital information systems and affi liated outpatient information systems. In the 1990s, LAB systems began using client-server architecture with networked workstations, and most hospitals had a variety of specialized clinical support information systems interconnected to form a medical information system with a distributed database of clinical data that constituted the electronic patient record. By the 2000s, several hundred different clinical tests were routinely available (there had been only a few dozen in the 1950s). The need for more sophisticated and powerful LAB systems has largely been met by commercially available standalone laboratory information systems (LIS); however, there is now increasing pressure to replace these products with the lab-system functionality of the enterprise-wide integrated electronic health record system, for which there is little reported experience.

Section: Discussionmentioning

confidence: 99%

Clinical Laboratory (LAB) Information Systems

Collen¹,

Miller

2015

“…Few hospitals in this survey had level-5 hospital applications (with two-way data transmission and clinical functions), which included test results reporting, medical chart reports, personnel history, and utilization review. Young [ 137 ] concluded that smaller HISs with minicomputers fell short of the more sophisticated HISs in larger hospitals with mainframe computers supporting a variety of patient care applications.…”

Section: Commercial Vendors' Mhismentioning

confidence: 99%

“…At the end of the 1970s, Young [ 137 ] and associates at the University of Southern California also conducted a survey of minicomputer-based HISs in medium-sized hospitals with 100-300 beds. They identifi ed 75 different applications that they grouped into fi ve levels or steps of diffi culty in a modular implementation of an HIS.…”

Section: Commercial Vendors' Mhismentioning

confidence: 99%

Multi-Hospital Information Systems (MHISs)

Collen¹,

Detmer

2015

Changing economics gave rise to the development of Multi-Hospital Information Systems (MHISs) serving systems of three or more hospitals and their associated services. Functional and technical capabilities, including translational databases, were developed to support the exchange and integration of multiple forms of information within and among facilities. Early examples in the private sector included MHISs at The Sisters of the Third Order of St. Francis (1960s) and Intermountain Health Care (1970s), and in mental health hospitals (1960s-1970s). In the federal sector, the U.S. Public Health Service and Indian Health Services began to develop MHISs in the 1970s. Efforts to use automation to support services started in the 1960s at the Department of Defense, which used a top down approach, and Veterans Administration, which worked bottom up; the complicated histories of these developments spanned decades. Also in the MHIS marketplace were com-

“…The major vendors of radiology systems were Siemens and General Electric; and the major vendors of pharmacy systems were Becton Dickenson, International Business Machines, and Shared Medical Systems [ 22 ]. A second survey, conducted by Young and associates [ 34 ] at the University of Southern California, identifi ed minicomputer-based information systems in medium-sized hospitals with 100-300 beds. They found that less than one-fourth of the hospitals had clinical laboratory applications that included the preparation of laboratory work sheets and schedules; very few had applications with two-way data transmission and laboratory test results reporting.…”

Section: Evolution Of Electronic Health Records Clinical Support Sysmentioning

confidence: 99%

Medical Informatics: Past and Future

Collen¹,

Greenes

2015

Led in its earliest decades by a few pioneers and supported by a small number of professional organizations and universities, medical informatics was funded primarily by federal grants and contracts until 1980, when industry began to enter the marketplace. Despite technology advances, diffusion across health care was slow, and computers were used predominately for business functions. In the 1980s specialized subsystems were developed for the clinical laboratory, radiology, and pharmacy, but by 1989 only a few medical information systems were operational, most of them in academic health centers that had received federal funding. In the 1990s, distributed information systems allowed physicians to enter orders and retrieve test results using clinical workstations; and hospital networks integrated data from all the distributed clinical specialty databases in an electronic patient record. By the end of 1990s, systems were up and running in the Department of Defense and Veterans Administration. In the 2000s, more clinicians in the United States were using electronic health records, due in part to steps taken to adjust the computer to its professional users. Diffusion was further advanced in 2010, when direct federal funding was extended to health care providers using systems that met "Meaningful Use" requirements in caring for Medicare and Medicaid patients. Advances expected in the next decade include precision medicine and patient genotyping; telehealth care; cloud computing; support for elder care with multiple chronic diseases and polypharmacy; advanced clinical decision support; patient data security; big data analytics, improved population health, public health, and disaster management; and interoperability and integration of care across venues.