Time Pressures

Time is an important factor for current healthcare providers. Although clinicians perceive that EHRs, with or without personal health records (PHRs) components, consume more time than paper records they do offer some time-saving features.²³ Examples where EHR or PHR systems or other devices such as tablets in waiting rooms can save time and can enable patients to book their own appointments and provide data on current issues before clinic visits. The patients and caregivers can state the reason for the scheduled visit plus signs and symptoms, provide detailed lists of prescribed and over-the-counter medications, and update information on addresses and insurance coverage. The time that is available for the appointment can then be spent analyzing the data and formulating decisions and care plans. EHRs that integrate data from multiple caregivers and settings (e.g., primary care clinics, nursing homes, specialists, and hospitals) also save time during patient visits. Complete records can also alleviate the need for duplicate diagnostic or evaluation studies if all the patient data are successfully aggregated in a timely manner and available for all caregivers and all locations of care.

Computerized Physician (or Provider) Order Entry

Another informatics application designed to save time as well as improve information flow and reduce errors is computerized physician (or provider) order entry (CPOE) systems (also mentioned previously in the error section). Using a CPOE system, healthcare professionals place their orders for components such as medications, diagnostic tests, appointments with specialists or generalists, or discharge instructions online rather than verbally or on paper. These online orders are then quickly distributed without transcription and its inherent errors to those who can ensure that the tests are booked, carried out, and the results reported back to all who are involved. CPOE systems can not only speed care but also check and verify that the data are accurate, actions are appropriate, their booking is efficient, and communication is facilitated and recorded. A study by Wietholter et al. illustrates the time-saving potential made possible by CPOE systems. The study compared processing time for prescriptions (time from the initial order by the physician or nurse until it is prepared and delivered by the hospital pharmacists) with and without automated systems. Processing time for prescriptions showed a mean time of 115 minutes before automation compared with 3 minutes to process the same drug order after the introduction of CPOE for prescribing.²⁴

Workflow Applications

Workflow is vitally important for clinicians in all care settings and has often been overlooked or underappreciated by system developers. Workflow refers to the processes and their time sequencing when patients, healthcare professionals, and their system interact. Often, physicians have different ways of working than do nurses. New systems, either online or not, must respect and adapt to these differences. For example, in a teaching hospital, the physicians in charge “round” each morning, bringing along the care team of medical students, residents, and sometimes pharmacists, social workers, or librarians. They meet as a team with each patient assigned to their care, ascertain his or her progress and needs, and plan for next steps. Each patient is completed and orders are given to address all of the needs—a patient-centered workflow. Nurses in hospital units deal with patients differently. For example, one nurse provides all of the medications for patients several times per day. The nurse wants the information in an EHR to be focused only on the needed medications and presented in patient order—needed medications for the patient in room 1 bed 1, for the patient in room 1 bed 2, and so on. Those who schedule diagnostic testing or assign operating room time to physicians or teams need to see the clinical information in another format as do the administrative team who maintain supplies and equipment. Informatics professionals must ascertain the flow of people, tasks, and information: the workflow and how it differs for different groups of people before planning for new systems.

Zahra Niazkhani of the Institute of Health Policy and Management in the Netherlands provides a summary of what is known about the effects of CPOE on workflow.²⁵ Computerizing a system with existing poor workflow has been the downfall of many systems. Not recognizing and respecting the existing workflow as well as the culture of an organization has also proven costly and frustrating for system designers during implementation.

Computer Reminders

Manual or computerized reminder systems have been shown to be one of the most effective methods of improving clinical behavior, improving clinical practice or knowledge translation. Reminders originally were provided in the form of paper notes on paper charts for such things as missing childhood vaccinations, influenza shots, and mammographies. The next implementation came in the form of emails. These emails were often more general reminders such as notices of a new hand sanitizer solution system to be implemented into a hospital or to consider generic instead of brand name drugs. Paper and general email-based reminders are not as effective as those that are patient specific and delivered at the point-of-care from within an EHR. Shojania and colleagues produced a Cochrane Review of point- of-care reminders delivered by a computerized decision support system within an EHR. They reviewed 28 original studies that showed consistent increases in actions when the reminders were provided across a range of conditions, practitioners, and settings.²⁶

Reminder systems within EHRs are important in many applications. The 28 studies in the Shojania review described the settings and content areas of the 32 comparisons in these studies:

Of the 32 comparisons that provided analyzable results for improvements in process adherence, 21 reported outcomes involving prescribing practices, six specifically targeted adherence to recommended vaccinations, 13 reported outcomes related to test ordering, three captured documentation, and seven reported adherence to miscellaneous other processes (for example composite compliance with a guideline).

Reminder systems can work for patients also. For example, Puccio and colleagues studied whether reminders via cell phones would improve adherence (taking their medications) with HIV and AIDS medication in adolescents and young adults.²⁷

Producing New Knowledge from Data

Another opportunity for increasing efficiencies in healthcare is that data stored and generated by powerful integrated EHRs and PHRs, hospital information systems, and insurance collections can be mined via quantitative analytic techniques to extract information and produce new knowledge. This new knowledge can, and will, direct an increasing number of patient-specific decisions. Currently our limited data collection and analysis capabilities could create knowledge only on groups of people (i.e., populations) rather than individuals. These new data will likely have an impact on being able to predict prognosis for an individual (the likely path that a person’s disease or condition will take). This is very useful information for the patient, health professionals, and insurers. For example, data mining of information on 258 variables from 16,604 patients with heart-lung transplants showed associations between variables that could be used to predict survival in the patients where traditional statistical analyses of data sets with that many variables could not yield these results.²⁸

In addition to data mining and knowledge discovery, advances in bioinformatics can link a person’s health and family history data with his or her genomic data for decision-making. This information will allow for better targeting of treatments: some drugs work well for some people and not for others. Strong data collection and analyses will be able to sort this puzzle out. Thervet and colleagues provide a summary of the promise of tailoring drugs based on genomic data.²⁹

The production of new data is not really a classical knowledge translation task but it is one that will become more important over time as our data collection methods become stronger and more genomic data are available. Our systems will continue to play an increasing role in the application of new and proven knowledge to maintain optimal healthcare, especially in the production and integration of new patient-specific information.