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McKibbon KA, Lokker C, Handler SM, et al. Enabling Medication Management Through Health Information Technology. Rockville (MD): Agency for Healthcare Research and Quality (US); 2011 Apr. (Evidence Reports/Technology Assessments, No. 201.)

  • This publication is provided for historical reference only and the information may be out of date.

This publication is provided for historical reference only and the information may be out of date.

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Enabling Medication Management Through Health Information Technology.

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Scope and Purpose of the Systematic Review

The Agency for Healthcare Research and Quality (AHRQ) has considerable interest in health information technology (health IT). They have contracted several reports that are published or will soon be published. These evidence summaries on health information technology (IT) are related to costs and benefits;2 barriers and drivers of health IT for the elderly, chronically ill and underserved;3 the impact of consumer informatics applications;4 and telemedicine.5 Currently AHRQ has also contracted for the use of health IT in decisionmaking,6 in patient centered care7 and decision support for health care decisionmaking.8 These latter reports will be available early 2011. AHRQ asked the McMaster University Evidence-based Practice Center to generate an evidence report outlining the impact of health IT on the medication management process. Medication management is a major component of the health care system. Currently, approximately 10 percent of the health care budget in the United States is spent on prescription medications.22

To structure this evidence report we use the framework of medication management as presented by Bell and colleagues.1 They model the medication management continuum into the five phases of this evidence report; Figure 1 is a pictorial representation of the medication management phases.1

Figure 1 is a pictoral diagram used with permission from Bell et al. (2004) {5889}, depicting a functional model of the medication management process. It includes the phases of medication management and the participants involved and is used as the basis for categorization of studies in the current review. The phases are prescribe, transmit (called order communication in our report), dispense, administer and monitor. We refer to the transmission of the order/prescription as “order communication” in order to take into account the bi-directional communication between prescriber and pharmacy staff. Bell’s model shown here depicts a linear progression from (left to right) of 5 phases. Each phase had inputs that include people, technologies, and information flows. 1. The first phase on the far left, Prescribe, has 9 incoming arrows. Along the top, from left to right are Drug Information, Patient History, Formularies. To the left of the Prescribe box is: Rx need assessments, Patient Preferences and an elongated arrow which is feed back from the fifth phase of medication management along the bottom of the illustration back to the Prescribe box. Along the bottom of the Prescribe box are three incoming arrows: clinician, (showing a silhoutte of a person), e-Rx showing a hand held electronic device; and Medical records, illustrated by a folder. From the far-right hand side of the Prescribe box an arrow, entitled, Completed Rx is extended to the Right. This indicates that once completed the prescription is communicated electronically or in paper format to the transmit/order communication phase. 2. Inputs for the order communication phase include pharmacy options, patient, staff and clinicians, ePrescribing systems, and the telephone. Once the order communication phase is complete the medication is delivered or moved to the dispensing phase. 3. Inputs for the dispensing phase are drug information, patient history, formularies, the pharmacist, the pharmacy system, staff of clinician and office dispensary. Once complete the medication is moved to the administering phase. 4. Inputs for administering are the patient, patient educational information and the nurse or clinician who are administering the medication. 5. Once completed the next phase is monitoring where the effects of the medication are assessed to determine if changes need to be made to the prescription. Monitoring inputs are drug information, patient history, clinician, patient, and staff. We also added education and medication reconciliation as additional aspects to medication management to our review. Education involves providing information to either providers or patients to improve medication management knowledge. Reconciliation refers to generating a comprehensive and concurrent list of medications taken by patients using information from a number of sources. Used with permission BMJ Publishing Group. Bell DS, Cretin S, Marken RS, Landman AB. A conceptual framework for evaluating outpatient electronic prescribing systems based on their functional capabilities. J Am Med Inform Assoc 2004; 11(1):60–70.

Figure 1

A functional model of the medication management continuum created by Bell et al. Includes the major activities involved in medication management and forming the basis of our medication management phases. We refer to the transmission of the order/prescription (more...)

The first phase of the continuum is prescribing medications by clinicians who have assessed the patients’ conditions and needs. The second phase is to transmit the prescription to the pharmacists who work with the prescriber to clarify and verify the order (referred to as ‘order communication’ in this report to capture the complexity of the communication that occurs between prescriber and pharmacy). The next step is dispensing the medication in its required form and dose, followed by administering the medications to the patient. Monitoring is the final phase where ongoing oversight occurs to address the changing medication needs and situation of the individual. Reconciliation of the medications taken by individuals and postprofessional education or training related to medication management IT (MMIT) are additional aspects (as opposed to phases) of the medication management cycle covered by this report. Reconciliation is a process whereby a patient has their medication lists verified for completeness and accuracy when the patient moves from hospital to home or to a nursing home, or is involved with multiple care providers. Reconciliation can improve care by using health IT to ensure accuracy of medication lists, identification of gaps and conflicts in prescription, and provide timely and efficient transfer of patients and their medication data. Education is also important in MMIT systems for both improving knowledge and skills of patients and care providers and to enable timely implementation and optimal use of MMIT systems. Therefore, AHRQ requested inclusion of both reconciliation and education in this report in addition to the five medication management phases.

This report includes clinicians, patients, informal caregivers, and administrators. All care settings are also covered: home, community, primary care and specialty clinics, all levels of hospitals, long-term care facilities, and pharmacies of all types. This report does not focus on the health insurance or pharmacy industries.

Health IT holds great potential to improve the quality of health care and reduce potential and real errors while at the same time providing cost effective care. The coverage of this report is broad, reflecting the scope and breadth of health IT and the processes of medication management. This report centers on health IT applications that focus on medication management such as e-Prescribing applications, computerized provider order entry (CPOE), bar-coded medication administration (BCMA), pharmacy-based health IT, electronic medication administration record systems (eMAR), and other MMIT tools. Smaller health IT applications such as hand-held devices that provide calculations for dosing, as well as MMIT applications integrated with other health IT systems, such as electronic health or medical records systems (EHRs and EMRs), health information systems, hospital information systems, and personal health records (PHRs), and others as identified, are included. For inclusion, the MMIT had to be integrated into the health care system electronically and process patient-specific information that then provided direction for that patient’s care. This integration requirement meant that stand-alone devices such as smart infusion pumps and glucose monitors were not included unless they were integrated with other health IT. This requirement allowed the report to concentrate on MMIT systems and separate out these medical devices with some computing capabilities.

Because health IT is a new discipline that crosses many domains, definitions are not always standard. Therefore we have defined terms related to health IT and other issues in this report in a glossary, labeled as Appendix F.

Key Questions (KQs)

KQ1. Effectiveness. Within and across the phases of the medication management continuum (prescribing, order communication, dispensing, administering, and monitoring, plus reconciliation and education aspects) what evidence exists that health IT applications are effective in improving:

  1. Health care process changes (e.g., adherence to guidelines, changes in prescribing behavior, changes in patient monitoring activities, errors, efficiency),
  2. Other intermediate outcomes (e.g., use, measures correlated with use, satisfaction with system, usability, knowledge, skills, and attitudes),
  3. Costs and economic outcomes,
  4. Clinical outcomes for patients (e.g., physiological measures, adverse drug events, length of stay, mortality, quality of life, other patient events),
  5. Population level outcomes, and
  6. Composite outcomes.
  7. To what extent does the impact of health IT on improvement of the health care process, other outcomes, costs and economics, and clinical outcomes vary depending on the type of medication (e.g., controlled or noncontrolled substance) or the form of the medication (e.g., oral, injection, intravenous)?

KQ2. Gaps in Knowledge or Evidence. What knowledge or evidence deficits exist regarding needed information to support estimates of cost, benefit, impact, and net value with regard to enabling health IT applications in terms of prescribing, order transmission, dispensing, administering and monitoring, and adherence? Discuss gaps in research, including specific areas that should be addressed, and suggest possible public and private organizational types to perform the research, analysis, or both.

KQ3. Value Proposition. What critical information regarding the impact of health IT applications implemented to support the phases of medication management is needed to give clinicians (e.g., physicians, nurses, psychologists, dentists, and pharmacists), health care facility administrators, patients, and their families a clear understanding of the value proposition particular to them?

KQ4. System Characteristics. What evidence supports or refutes the impact of any of: open source, home grown, proprietary, local configuration ability, system configuration ability, conformity with U.S. Federal or other interoperability standards, conformity with other standards from other jurisdictions, being Certification Commission for Healthcare Information Technology (CCHIT) certified, system architecture, or feature set on the decision to purchase, implement, or use health IT in medication management systems?

KQ5. Sustainability. What factors influence sustainability (use and periodic updates) of health IT applications that support a phase of medication management continuum: prescribing, order communication, dispensing, administering and monitoring, plus reconciliation and education?

  1. To what extent does the evidence demonstrate that health care settings (e.g., inpatient, ambulatory, long-term care) influence implementation, use, and effectiveness of such health IT applications?
  2. What is the impact (e.g., challenges, merits, costs, and benefits) of having electronic access to patients’ computerized medication records (current and past), EHRs and PHRs, formulary information (inpatient and outpatient issues), billing information, laboratory records, and other electronic patient data in the quality and safety of care provided by health IT applications that support at least one phase of the continuum of medication management (i.e., prescribing and ordering, transmission and verification, dispensing, administering and monitoring and adherence)?

KQ6. Two-way EDI for Order Communication. It has been recognized that implementation and use of a complete, two-way electronic data interchange (EDI) (e-prescribing with e-transmission) between the prescribers’ electronic medical records (EMRs), including CPOE and other health IT within EMR, and other similar systems or stand-alone e-prescribing systems, retail, and mail-order pharmacy prescribing systems have been limited. In many instances, health IT systems that facilitate prescribing are used at the point-of-care and are combined with nonelectronic modalities for transmission of prescriptions, such as paper, facsimile, voice, and telephone. On the pharmacy side, prescriptions being received may not automatically populate the pharmacy prescribing system, instead appearing in the fax printer or in a different computer program than the one the pharmacist regularly uses to fill prescriptions, requiring the pharmacist to manually retype the prescription information into the pharmacy’s electronic system. This e-Prescribing with e-transmission also includes order clarification with electronic communication between the prescribers and pharmacists.

  1. What evidences exists demonstrating the barriers and drivers of implementation of complete EDI that can support the prescription, transmittal, receipt, and order clarification process of e-Prescriptions?
  2. How do barriers, facilitators, and economic incentives vary across pharmacists, physicians, and other relevant stakeholders with respect to adoption and use of complete EDI (e-Prescribing/ordering with e-Transmission)?

KQ7. RCTS of CDSS. What evidence exists regarding the extent of integration of electronic clinical decision support systems (CDSS) in a health IT system for the prescribing, dispensing, and administering of medications? To what extent does the use of the CDSS for prescribing/ordering, order communication, and dispensing of medications impact the various outcomes of interest, including health care process, intermediate, costs and economics, and clinical endpoints? CDSSs are broadly defined to include medical and pharmacy systems, reminders, and monitoring.


Medication management is a complex and expensive process with high potential for both benefit and harm. Ninety percent of American seniors and 58 percent of nonelderly adults rely on medications daily. The average cost of prescription drugs per clinic visit in the United States in 1996 was $79. By 2006, this had doubled to $161. Nationally, all prescription drugs costs are projected to be $246.3 billion for 2010. Substantial increases in medication costs are expected until at least 2019 based on the aging population23 and increased demand for medications (72 percent increase from 1997–2007).24 The introduction of newer, high cost, nongeneric, and specialty drugs also adds to the projected increases. The amount of new more complex medications also places a substantial cognitive burden on health professionals who prescribe and oversee these medications. Genomics research and its role in medication choices for individualized health care are also going to become more important in the next decades. Health IT can play a strong information support role to help deal with this increased cognitive load and provide efficiencies for provision of prescription medications, control, and recording of use.

In addition to increasing costs, medications can cause substantial health problems. Incorrect choice of medications and over or under use leads to less than optimal care. The U.S. Institute of Medicine (IOM)25 report on medication errors estimates that errors occur in all levels and locations of care. Estimates for hospitalized patients show 1.5 to 10 errors per 100 opportunities for errors for prescribing and 2.4 to 11 errors per 100 opportunities per dose for dispensing. This translates to approximately one error per patient per hospital day. Error rates in long-term care prescribing are calculated to be from 6 to 20 errors per 100 opportunities per dose. Ambulatory care studies show that up to 21 percent of prescriptions have errors.

Pediatric patients present special challenges in that doses must often be adjusted for body weight and age. As an example, one study showed that errors in acetaminophen use in the emergency department for children were 22 per 100 doses ordered.26 Elderly patients also have special prescribing and drug monitoring needs based on issues related to aging, multiple conditions, the need for several medications, and often, decreased kidney function.

Pharmacist errors in order communication and dispensing also occur. Cheung and colleagues27 reviewed the literature of dispensing errors and found that overall errors occurred in the range of 0.2 to 0.8 percent, although the number varied depending on how the errors were detected and reported. The task of medication administering by nurses, other health care providers, as well as patients and families, have also been shown to have associated errors. Many of the errors in medication management described above are preventable. The IOM report shows that preventable errors often constitute 20 to 50 percent of all errors. In addition to mortality, errors and inappropriate use are costly, often cause a huge drain on health care resources, and contribute to substantial morbidity and challenges to well-being.

Historically, the first MMIT application was published in 1979 as a decision support system to help in prescribing appropriate antibiotics.28 The first RCT was done 5 years later.29 Health IT has tremendous potential to improve care associated with medication management. For example, the Center for Information Technology Leadership (CITL), in their Value of Computerized Provider Order Entry in Ambulatory Care30 report that potential savings from implementation of CPOE in ambulatory care prescribing and its ability to detect errors would provide savings in the U.S. of $28 billion annually. Other MMIT applications are projected to have similar cost savings and improved care. However, the promises of health IT have not always been obtained after installation. For example, Mollen and colleagues31 reviewed CDSSs for prescribing and found 37 reports that successfully showed changed health care provider behavior. Only five of these studies noted improvements in patient outcomes. Similarly, Eslami and colleagues32 reviewed studies of CPOE applications in outpatient medication ordering. Of 67 studies, only 21 dealt with safety. Most of the evidence they identified used observational study methods. They showed that although CPOE and other information systems are often costly, some evidence supports medication safety benefits. However, they also note that some studies have data that support increased error rates and adverse drug events (ADEs) with CPOE implementation. Kaushal and colleagues33 show that e-Prescribing with CDSS reduced errors from 52.5 to 6.6 per 100 prescriptions in ambulatory care. Paoletti and colleagues34 reduced errors from 2.9 percent to 1.6 percent in a U.S. general hospital with the implementation of BCMA and eMAR.

Many groups have studied various components of the medication management process and the effects of multiple health IT systems and programs across settings and populations. However, the body of evidence that evaluates the actual, and not projected, effect of a broad range of MMIT applications and the medication management process is not available in one document or Web site. This evidence report is designed to be that summary.


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