Frequency of use
Among the 4% of doctors with a fully functional electronic-records system, 97% reported using all the functions at least some of the time. Among the 13% of doctors with a basic system, more than 99% reported using all the functions at least some of the time.
A large majority of physicians reported being satisfied with their electronic-records systems over- all (93% for fully functional systems and 88% for basic systems, P = 0.20) and with the ease of use of the system when providing care to patients (88% and 81%, respectively; P = 0.11). Physicians with fully functional electronic-records systems were significantly more likely to be satisfied with the reliability of their system than were those with basic systems (90% and 79%, respectively; P = 0.01). Here again, results were adjusted for the characteristics of physicians and their practices.
Five High 5s priority risk areas:
- Managing concentrated injectable medicines (concentrated injectables).
- Assuring medication accuracy at transitions of care (medication reconciliation).
- Performance of the correct procedure at the correct body sites (correct site surgery).
- Communication during patient care handovers.
- Improved hand hygiene to prevent health care- associated infections
Standardization is the process of developing, agreeing upon and implementing uniform technical specifications, criteria, methods, processes, designs or practices that can increase compatibility, interoperability, safety, repeatability and quality. Process standardization is the specification and communication of a process at a level of detail sufficient to permit consistent and verifiable implementation by different users at different times and in different settings. Standardization reduces variation: ‘The tendency for a process to fail is also diminished in relation to the consistency with which it is carried out; that is, the degree to which it is standardized’.
Benefits of standardization in health care:
- Standardization provides policy and decision-makers and health care workers a means for comparing out- comes resulting from standardized process implementation within or among health care organizations;
- Standardization better enables investigators to compare data and to interpret the relevance and efficacy of an intervention;
- Through standardization health care workers are able to relate to one another in meaningful ways (including the standardization of terms used);
- As more hospitals begin to use the same standard protocols with the same data fields, the ability to analyze risk will be enhanced;
- Standardization of architectural design of hospital surgical suites, patient care units (specifically, patient rooms, treatment rooms, etc.) and other care settings reduces health care worker cognitive dissonance and thus the risk of human error.
- Standardization of technology and devices (e.g. IV pumps, hip prostheses) increases the likelihood of user familiarity with available technology and devices and thereby reduces the risk of human error.
- Building on the same solid foundation, rather than struggling to grasp the range of safety concepts that might otherwise arise in an unstructured environment;
- Standardization will allow health care workers to learn from each other’s experiences (i.e. new ideas on how to address problems—what has worked, what has not worked and why).
- Standardization will be incorporated into the architectural design of hospital facilities, including its technology and equipment to provide the highest level of safety.
- Health care workers who become proficient in applying the elements of an SOP will be constantly building on the same solid foundation, rather than struggling to grasp the range of safety concepts that might other- wise exist in an unstructured environment.
- Standardization will allow health care workers to learn more easily from each other’s experiences, i.e. new ideas on how to address problems—what has worked, what has not worked and why.
The medication use process is an ideal model for demonstrating this new approach to measurement; medications are the most common intervention in health care and virtually all studies of safety of care have identiWed the medication use process as one of the greatest risk to patients. Unfortunately these same studies reveal an enormous under-detection bias for both medication errors and adverse drug events. This very same bias has driven many hospitals to measure what is easiest to collect, i.e. voluntarily reported medication errors. Indeed recent studies have reported improved medication safety based solely on reductions in voluntary reported medication errors, a very problematic conclusion. Ultimately, creating a safe medication system will require the use of surveillance approaches to detect ADEs (the account- ability focus), the use of both surveillance and voluntary reporting to track medication errors (the learning focus), and a real-time system to allow for rapid detection and prevention of these problems (the intervention focus). This approach is impracticable in a paper-based system of
care, but quite feasible in an electronic world. Electronic measurement should be utilized to the maximum extent possible because it is a much more cost-effective and compre- hensive view of both problems and progress. This is not to say that voluntary reporting and chart review are ever totally replaced, but rather complemented and supplemented by electronic analysis. In fact, many situations picked up in auto- mated surveillance must be considered potential ADEs until they have been investigated, documented, and analyzed, often involving chart review. How best to leverage electronic data as part of the hospital’s
patient safety program should be reconsidered each time the scope of the data available for screening is enhanced. When new error situations are uncovered via voluntary reporting, electronic analysis can be useful in checking for other unreported occurrences and similar clinical situations. These systems can help with investigation, detection, identification, mitigation, and amelioration of medication-related problems.
Inneficient navigation in electronic health records has been shown to increase users’ cognitive load, which may increase potential for errors, reduce efficiency, and increase fatigue.
The human-computer interaction literature defines usability as the degree of effectiveness, efficiency, and satisfaction with which users of a system can realize their intended task. Research has highlighted a lack of adherence to user- centered design practices by commercial EHR vendors. Government and industry have formally recognized this challenge by publishing criteria for EHR certification and standard guidelines for the conduct of usability evaluations.
Navigation is a particularly important contributor to the usability of an EHR because information in an individual patient record tends to be scattered across multiple screens and sections, forcing the clinician-user to navigate repeatedly through the digital space to create an adequate mental model of the patient’s condition.[Top]
The difficulties in evaluation fall into three areas: defining appropriate measures of benefit, disentangling the effects of the system from other factors, and bias.
When defining appropriate measures, it is unrealistic to expect a clinical data system to improve patient outcomes directly (in the manner of a drug) because it is merely improving data management. Therefore, some investigators have settled for measuring clinical attitudes to such systems, or the accuracy and completeness of data. Others concentrate on clinical functions such as usage rates or time to enter data. To measure the effects of systems, the methods include surveys of system users and patients and “work sampling” to evaluate changes in work patterns. Measurement of direct effects on data management is more difficult. One suggestion is to adopt Shannon’s definition of information as the absence of uncertainty, and assess physicians’ uncertainty by asking them to make predictions whose accuracy is measured subsequently.  Most interesting of all, however, are those few assessments of the impact of systems on clinical processes known to improve outcomes (eg, screening rates for hypertension) or on clinical outcomes themselves.
Whichever measure is adopted, the reasons for any observed effects can be hard to disentangle, For example, installation of a hospital?wide clinical data system is a major project requiring teamwork, consultation, training, and even re?engineering of working relationships. Any changes observed may be due to these components rather than to the information system itself.
Finally, there is bias. For example, if patients are randomized to use of a clinical data system in a trial, staff may learn better data organisation from the system which may spill over to control cases (“contamination”). This can be partly overcome by randomizing staff to use the system, but this disrupts teamwork and can alienate control staff. It is better to randomize teams or departments, but the sample must be large enough to compensate for random variations. Thus, many studies so far have been before/after designs, though in a handful staff or teams have been randomized.
Characteristics of data systems:
- completeness of data
- availability of data
- use of clinicians’ time
- Effects on clinical process and outcomes
The characteristics above fit the risk factors of Standardization in patient safety: the WHO High 5s project academic paper.
Biomedical informatics (BMI) is the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving, and decision making, driven by efforts to improve human health.
- Scope and breadth of discipline: BMI investigates and supports reasoning, modeling, simulation, experimentation, and translation across the spectrum from molecules to individuals and to populations, from biological to social systems, bridging basic and clinical research and practice and the healthcare enterprise.
- Theory and methodology: BMI develops, studies, and applies theories, methods, and processes for the generation, storage, retrieval, use, management, and sharing of biomed- ical data, information, and knowledge.
- Technological approach: BMI builds on and contributes to computer, telecommunication, and information sciences and technologies, emphasizing their application in biomedicine.
- Human and social context: BMI, recognizing that people are the ultimate users of biomedical information, draws upon the social and behavioral sciences to inform the design and evaluation of technical solutions, policies, and the evolution of economic, ethical, social, educational, and organizational systems.
Clinical informatics covers the practice of informatics in healthcare through medical, nursing, dental, and other forms of informatics that are applied to patients or to healthy individuals. The figure bellow, illustrates how basic research in informatics applied to biomedicine is the natural purview of BMI, since it provides the methods, techniques, processes, and theories that are used across all the sub-specialty areas.