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Technology, Computing, and Simulation: Review Article

A Narrative Review of Meaningful Use and Anesthesia Information Management Systems

Gálvez, Jorge A. MD*; Rothman, Brian S. MD; Doyle, Christine A. MD; Morgan, Sherry PhD, MLS, RN*; Simpao, Allan F. MD*; Rehman, Mohamed A. MD*

Author Information
doi: 10.1213/ANE.0000000000000881


Anesthesiologists worldwide have been using electronic systems, known as anesthesia information management systems (AIMS), for >30 years as a means to document the physiology and interventions for patients under their care.1 Various systems have been developed to assist in all phases of care, including preoperative evaluation, intraoperative delivery of care, and postoperative care for patients receiving anesthesia care. Widespread adoption of AIMS remains slow throughout the United States.

The Institute of Medicine report in 2000, “To Err Is Human: Building a Safer Health System,” highlighted the magnitude of medical errors that contribute to patient harm and was a call to action for quality improvement efforts at a national level.2 In 2009, the US government set the stage for the adoption of electronic health records (EHRs) under the provisions of the Health Information Technology for Economic and Clinical Health (HITECH) Act. Subsequently, the Department of Health and Human Services (HHS) set forth 2 regulations to promote the adoption of EHR technology in the United States: the first was a notice of proposed rules for eligible providers (EPs), eligible hospitals (EHs), and critical access hospitals (CAHs) to qualify for additional Medicare or Medicaid payments (incentive payments) for the implementation and demonstration of Meaningful Use (MU) of EHR technology; the second was a set of standards and certification criteria for EHR implementation. EPs, EHs, and CAHs were required to use only certified technologya in a meaningful way to be considered eligible for incentive payments.3 The goal of this legislation was to achieve universal access to EHR technology by 2014. After 2015, payment adjustments (a reduction increasing by 1% per year to a maximum of 5%) would be made to Medicare reimbursements for EPs, EHs, and CAHs who do not meet MU reporting guidelines.

The purpose of this article is to describe the MU program as it applies to anesthesiologists in the United States and to explore whether anesthesiologists are able to effectively participate in the MU program as conceived and implemented (see Section I). The secondary purpose is to perform a narrative review of functionality of operating room (OR) EHR technology, including AIMS platforms that would satisfy core MU objectives—objectives that may or may not be currently addressed by the MU program (see Section II).

The Anesthesia Patient Safety Foundation, an international leader in patient safety initiatives, “endorses and advocates the use of automated record keeping in the perioperative period and the subsequent retrieval and analysis of the data to improve patient safety.”4 Despite this initiative, the proportion of practicing anesthesiologists that uses AIMS remains low. A survey in 2011 reported that 24% of US anesthesiologists were using AIMS and 13% were planning to install AIMS in their institution.1 Furthermore, specialty physicians were found to be less likely to have implemented an EHR in their practice in comparison with a reference group of family medicine and general practitioners in 2013.5 Jha et al.6 reported that only 11.9% of US hospitals had either a basic or a comprehensive EHR in use based on a survey of 4493 hospitals (3101 responses) conducted by the American Hospital Association in 2010. The rate of EHR adoption increased in 2012, however, as reported by Grinspan et al.,5 with a 40% annual increase across all specialties. Despite the potential benefits of EHRs and their endorsement by professional societies, many practices remain reluctant to adopt electronic anesthesia records.


The federal guidelines for reporting and compliance with MU stage 1, stage 2 were reviewed. Stage 3 guidelines were not reviewed, because they had not been finalized at the time of this narrative review. The process for certification of EHR technology via the Office of the National Coordinator for Health Information Technology (ONC) was reviewed.

Literature Review Protocol

We took a broad approach to searching the biomedical literature in PubMed by including both MeSH terms (Official Terms—Medical Subject Headings—for PubMed/MEDLINE) and keywords—words used by authors in the titles and abstracts of article citations that may or may not be identical to official MeSH terms. Using keywords along with MeSH terms enabled us to capture articles that are not yet, or may never be, indexed using only official MeSH terms. For example, newly added citations that are “in process,” or citations in journals that are out of scope of the MEDLINE core of PubMed, might not have been found if we searched only using the official MeSH terms.7

There are 3 concepts constituting the goal of this article, which is to describe the MU program relative to anesthesiologists, with a specific focus on whether it is possible to meet the EP reporting criteria of MU using AIMS in various contexts. The 3 concepts comprising this goal are information systems, anesthesia, and management.

Using the PubMed database, we grouped MeSH with keywords that represent the information systems and anesthesia concepts separately, connecting the synonymous/related terms for each concept with the Boolean Connector “OR” to create sets of citations for each. We searched only 1 keyword, “management,” for the third concept to ensure that it would be present in all citations retrieved. We filtered the results to reflect the time period from January 1, 2000, to October 6, 2014. A detailed description of the search strategy is included in Appendix 1: PubMed Search Strategy from January 1, 2000, to October 6, 2014. Search results were limited to human subjects and the English language (Supplemental Digital Content 1,

Study Selection Criteria

Inclusion criteria were as follows: published, peer-reviewed primary manuscript or review articles involving AIMS functionality for (1) preoperative, (2) intraoperative, (3) postoperative care, or (4) OR management. Studies evaluating AIMS functionality were included: risk score development or validation, clinical decision support applications, and integration of AIMS in regional or national database designed to track outcomes and adverse events. The narrative review includes documentation of study time period, single or multi-institution, and number of patients when applicable (see Appendix 2 for additional information on cited articles, Supplemental Digital Content 2,

Exclusion criteria were as follows: non-English manuscript, provider survey of adoption or implementation of AIMS, manuscripts focusing on non-AIMS processes, and OR staffing models.

A single reviewer evaluated titles and abstracts from the retrieved articles to determine potential applicability to the inclusion criteria. The same reviewer evaluated the full texts of studies that appeared to be related to AIMS in the context of the stated hypotheses. Final inclusion determinations were made using the full text of each study.


Certification of EHR Technology

The ONC developed a process for certification of EHR technology to ensure that EPs, EHs, and CAHs would be able to report on MU criteria with the certified EHR technology (CEHRT). The process was necessary to ensure that the capital investment required to install an EHR or upgrade to a new EHR system would result in satisfying MU requirements. The first set of criteria for certification of EHR technology was published in 2011 and was revised in 2014.b The technology is evaluated by one of the ONC-Authorized Certification Bodies that awarded either partial or complete certification status.c,3 The EHR technology certified by the 2011 criteria may still be used through 2013. However, in 2014, providers were required to either upgrade or adopt their EHR technology to meet the 2014 definitions.3 Significantly, the 2014 final rule from the ONC allows providers the option to use only the EHR technology they need to achieve the MU goals they seek to meet.8

Although only temporary certifications are issued currently, a process for permanent certification is under development. In addition, either partial or comprehensive status is awarded to vendor products. A partial certification status indicates compliance with some, but not all, of the criteria set forth by the ONC. This is common among products that provide a narrow set of services, such as some AIMS software. The ONC maintains the list of CEHRT, and both the 2011 and 2014 versions are available for review at

A complete HITECH-certified EHR delivers 100% of the MU criteria on a successful implementation and appropriate use by EPs. Modular HITECH-certified programs require that EPs have access to other HITECH-certified applications that fulfill the remainder of the MU requirements for reporting.e

The web site of ONC allows EPs to search for and select their EHR products to determine whether 100% of the MU criteria can be met with their specific combination of CEHRT products. When an EHR combination satisfies 100% of the MU criteria, the EPs Centers for Medicare and Medicaid Services (CMS) EHR certification identifier (ID) can be generated for use to complete the attestation process.f It is important to note that although a combination of modules will result in 100% of MU criteria to be met, HITECH certification does not include certification that modules will be interoperable with each other. If interoperability cannot be achieved between modules, MU measures may not be achieved.g There are no clear advantages between modular or comprehensive EHR solutions, as each has its advantages and disadvantages (Table 1).

Table 1
Table 1:
Comprehensive Versus Modular EHR Configurations

A standalone AIMS may be used to satisfy MU criteria as long as the program is HITECH certified as a complete EHR. More commonly, AIMS satisfy some criteria and are therefore modular EHRs that contribute to the EPs or EHs reporting criteria. A search for anesthesia documentation systems that are HITECH certified revealed that most systems hold modular product classifications; however, there is ≥1 complete anesthesia EHR.g

Regional Extension Centers

In an effort to facilitate adoption in smaller practice settings, the HHS set up Regional Extension Centers.h These centers were distributed throughout the nation to provide customized assistance for EHR technology implementation. The infrastructure was specifically tailored to provide support for small-practice primary care physicians and small hospitals.

Meaningful Use

Beyond implementing CEHRT, EPs, EHs, and CAHs are expected to demonstrate MU of the EHR. MU is divided into 3 stages, with each stage increasing reporting requirements for attestation. At the time of this writing, stage 1 and stage 2 final rules are published and the stage 3 final rules are still under consideration. Each MU stage has different requirements for the time period for which reporting is required. Additional information about the timeframe for reporting at each stage is available via the CMS web site.i

The original timeline required implementation of CEHRT and compliance with each stage of MU requirements for 2 years before advancing to the next stage. An exception to this was stage 2, where the deadline for compliance was postponed to 2014. At the time of this writing, stage 3 MU attestation has been postponed to 2017.j It is not clear at this time whether the deadline to begin reporting will be extended. EPs must fully satisfy requirements for the duration of the reporting period of each stage before continuing to the next.

Are Anesthesiologists and Anesthesiologist Assistants Considered EPs?

Anesthesiologists are considered EPs and may submit for incentive compensation under the CMS MU rules. However, the CMS final rule for stage 2 designated an automatic hardship exemption from financial penalties for anesthesiologists.k Physicians must file an application for a hardship exemption for each fiscal year (beginning in July 1) on the year before they would be subject to payment adjustments.l For example, an anesthesiologist facing payment adjustments in 2016 should apply for hardship exemption by July 1, 2015. Note that the hardship exemption is currently limited to 5 years.m Specific compliance requirements for incentives differ under the CMS programs.

Provider eligibility criteria are available for the CMS programs (Table 2).m It is possible to be considered individually for EPs (each provider in a practice), as a group (the entire practice), or as EHs at the hospital level.3 Medicare guidelines for MU define EPs as doctors of medicine or osteopathy and specifically do not recognize certified registered nurse anesthetists or anesthesia assistants as EPs. Medicaid guidelines for MU define EPs as physicians (primarily doctors of medicine, doctors of osteopathy), nurse practitioners, certified nurse midwife, dentist, and physician assistant furnishing services in a federally qualified health center or rural health clinic that is led by a physician assistant.n

Table 2
Table 2:
Eligible Professional Criteria Available from the CMSa

Minimal EP requirements differ between Medicare and Medicaid guidelines. For Medicaid, eligibility criteria specify that 30% of services be provided to Medicaid patients in an outpatient setting. This requirement is reduced to 20% in pediatric settings. Most ambulatory surgical procedures satisfy these criteria. Medicare eligibility is based on a provider’s allowed charges and is subject to an annual cap. Providers who provide services primarily to inpatients, such as in the intensive care unit or the cardiac OR are not individually eligible under the MU criteria.

Table 3
Table 3:
MU Attestation for Providers Practicing at Multiple Locations

Anesthesiologists often provide care at multiple locations. Incentives are paid on a provider basis, not on a location basis, and thus an EP can only receive 1 incentive payment per year, regardless of the number of locations worked. If the attester has patient encounters at locations with different addresses, they are considered to be practicing in multiple locations. The multiple locations designation applies even if the EP works at >1 location for the same organization.o Multiple location EPs have increased attestation documentation requirements and separately consider eligibility criterion and MU measures when reporting multiple locations (Table 3).o

50% Eligibility and Adjustment Exceptions

Participation eligibility for EHR incentives requires that a location be equipped with CEHRT. CEHRT equipped is defined as a location where, at the beginning of the reporting period, an EP has access to CEHRT that is permanently installed, remotely accessed, or brought to the location by the EP and all functionalities required for an EP to meet MU requirements are accessible to the EP, even if the location hosts only some aspects of CEHRT.o

Furthermore, the EHR at the equipped location must be used in >50% of outpatient encounters (Places of Service [POS] that are not POS 21 or POS 23).o A patient encounter is where medical treatment and/or evaluation and management services are provided, excluding patient encounters in a hospital inpatient department or a hospital emergency department.o

The 50% criterion can be for 1 location or for a combination of practices, but eligibility is independent of EP employment status, and employment transitions do not negate patient encounters. Any previous employment site with patient encounters during the reporting period is considered a separate, reported location that must be included in attestation reports.

Attestation requires that the EHR certification IDs, which the ONC assigns to certified EHR systems, be provided for all systems at all locations used to demonstrate MU at the time of attestation. The ID is generated after the systems used are added to the EPs cart from the Certified Health IT Product list on the ONC web site. This service also is used to determine that the combination of the systems selected meet all MU requirements.o

If >50% of patient encounters do not occur at 1 location, then the multiple location eligibility criteria percentage is calculated by dividing the number of outpatient encounters at all locations using fully implemented CEHRT by the total number of all patient encounters across all locations, regardless of whether CEHRT was used.

Locum tenems providers do not need to include encounters that are billed under the National Provider Identifier of another EP. Although the locum tenens MU data inclusion is optional, the inclusion/exclusion decision must be applied consistently across all encounters and measures for the reporting period.o

Payment adjustment exceptions are available for EPs who do not have CEHRT accessible for >50% of their encounters. The exception is applied for annually and granted on a case-by-case basis. Supporting documentation must include proof that the applying EP has no facility ownership or purchasing authority to buy a CEHRT.o Anesthesiologists are presently granted an automatic hardship exemption from the penalties.


Attestation requires that measured data be reported from all locations with CEHRT (Table 3). The attestation reports must be generated with CEHRT software and cannot be a customized report. Simply adding all the locations’ reported numerators and denominators for each of the core measures and the same menu and clinical quality measures (CQMs) will determine the EPs final percentage for each measure.p If the menu and CQMs are different between locations, the percentage at the location that has the largest number of encounters for each measurement must be used for attestation.o

When data for MU measurements cannot be obtained from a location, the encounter should be added to the denominator, but not to the numerator.o The denominator also must include patient encounters at CEHRT-equipped locations that occurred but were not entered into the EHR.o Both of these instances will decrease the percentage reported and could lead to an MU percentage below the incentive threshold.o

For encounters at locations that do not have CEHRT where data are entered for these patients in a CEHRT at another location, the encounters may be included in both the numerators and denominators. The requirements to do so are that the EP has already reached 50% eligibility and if the data are entered at an encounter after the non-CEHRT encounter. For the eligibility criterion, the non-CEHRT encounter cannot be applied.o

The reporting requirements for EPs and EHs may not be the same. Beginning in 2014, all providers are required to demonstrate MU attestation for a 3-month reporting period. EPs may use any 90 consecutive days, whereas EHs must use a calendar quarter. The definition of the reporting periods may be subject to change and should be reviewed regularly on the CMS web site.q



EPs may qualify for up to $44,000 of Medicare incentives over 5 years if their MU attestation started in 2012. Beginning in 2015, Medicare EPs who do not successfully demonstrate MU will be subject to a payment adjustment (reduction). The adjustment begins at 1% the first year and increases each year that an EP does not demonstrate MU, up to a maximum of 5%, depending on the percentage of EPs who meet MU by 2018. Significantly, those claiming MU under Medicare must demonstrate MU every year without interruption or both past and future incentives will be at risk.


EPs may qualify for up to $63,750 of Medicaid incentives over 5 years if attestation to MU starts by 2016. There are no reimbursement adjustments associated with the Medicaid MU program at this time. Also, those claiming MU under Medicaid may have gaps in MU without placing past or future incentives at risk. Only the incentive for the year in question would be lost.

Hardship Exceptions

The CMS provides hardship exemptions where EPs, EHs, and CAHs can avoid penalties from failure to adopt and comply with MU regulations under Medicare guidelines. The exemptions apply to the penalties but not to the incentives. EPs, EHs, and CAHs who apply for incentives under MU automatically override any hardship exemption they had applied for previously. EPs can apply for exemptions in the following categories: infrastructure, new EPs, unforeseen circumstances, patient interaction, or practice at multiple locations. Under the infrastructure exemption, an EP or EH may claim a hardship exemption if the local Internet connectivity is inadequate, such as lack of broadband access. New EPs or EHs might not have the resources available to meet MU criteria when they begin to practice. The unforeseen circumstances exemption applies to situations such as a natural disaster that prevents access to resources required for MU reporting. Last, EPs who have limited interaction with patients (e.g., consultants) or practice at locations where they do not have control over the adoption of EHR also may claim a hardship exemption. The exemption application for the upcoming fiscal year (beginning in July 1) must be filed each year by July 1 and will not be issued for >5 years.

There is additional information specific to EPs, EHs, and specialists regarding the hardship exemptions.r,s,t The CMS is expected to provide additional details about hardship exemptions before the Medicare reimbursement adjustments become effective in 2015. The American Society of Anesthesiologists continues to work with CMS to advocate for MU criteria regulations to consider the specific requirements of practicing anesthesiologists. A direct result of the advocacy is an automatic exemption for anesthesiologists from the payment penalties that begin in 2015. Although participating in the MU incentive program waives any exemption, anesthesiologists are still eligible to receive the incentive compensation for MU attestation. Additional information about the advocacy efforts from the American Society of Anesthesiologists may be found at

Stage 1—Starting 2011–2012—Data Capture and Sharing

The stage 1 criteria consist of 24 core objectives for EPs (23 core objectives for EHs) and 10 menu items. EPs must complete 15 core objectives, 5 menu objectives, and 6 CQMs. The CQMs must include 3 core measures or alternate core measures as well as an additional 3 measures, which can be chosen from the 38 additional measures list. EHs and CAHs must complete 14 core objectives, 5 menu objectives, and 15 CQMs. A complete list of objectives and requirements for reporting is available from the CMS.i

CMS provides specifications on how to calculate the numerator and denominator for reporting each objective. Reports on CQMs must be generated with built-in features of certified EHR software.v EPs, EHs, and CAHs must submit reports on these items for 90 days in the form of an attestation for the first year. Full-year reporting to demonstrate MU is required in all subsequent years except for 2014 when only 90 days are required. The individual and institution must continue to satisfy MU requirements for the entire 2 years and then must progress to stage 2.

Some objectives may not be applicable to every provider or practice. Measures with a denominator of 0 may qualify for exclusion in the event that an EP, EH, or CAH does not have any patients who are appropriate or if the function demonstrating that measure is not performed. For example, if an EP does not perform immunizations, he or she is not required to satisfy an MU requirement that states a percentage of patients must receive immunizations.

Stage 2—Starting 2014—Advanced Clinical Processes

The final rule on stage 2 was published on September 2012. According to the regulation, all providers must achieve MU under stage 1 for 2 reporting years before advancing to stage 2. Thus, fiscal year 2014 will be the first year that stage 2 regulations will apply to those EPs, EHs, and CAHs that began reporting stage 1 in fiscal year 2012.

The criteria set forth under stage 2 requires that EPs meet 17 core objectives and 3 menu objectives from a list of 6 objectives or a total of 20 objectives. EHs are required to meet 16 core objectives and 3 menu objectives from list of 6 or a total of 19 objectives. The list of objectives developed from existing stage 1 objectives, although some objectives were either eliminated or combined to allow for new objectives. In addition, the menu objectives in stage 1 are now core objectives in stage 2. Within each objective, the requirement thresholds for compliance are greater in stage 2. CMS provides a detailed report for the changes in measure requirements for EPs and for EHs and CAHs.w,x

Clinical Quality Measures

The requirements for reporting on CQMs also increase with stage 2. Beginning in fiscal year 2014, all EPs, EHs, and CAHs are required to report CQMs the same way, regardless of their actual MU stage. Similar to core and menu objectives, there are 2 categories for CQMs: 1 for EPs and the other for EHs and CAHs. EP reporting requirements are 9 of 64 measures, whereas EH reporting requirements are 16 of 29 measures. In addition, providers must select 3 of the 6 key health care policy domains recommended by the HHS National Quality Strategy: (1) Patient and Family Engagement, (2) Patient Safety, (3) Care Coordination, (4) Population and Public Health, (5) Efficient Use of Healthcare Resources, or (6) Clinical Processes/Effectiveness. The complete list of CQMs is available from CMS.y All EPs, EHs, and CAHs are required to comply with reporting for stage 2 for 2 years and must then progress to stage 3.

Stage 3—Starting 2017—Improved Outcomes

The criteria for stage 3 have not been finalized. It is expected that this stage will focus on improving interconnectivity of health information through Health Information Exchanges between hospitals and expanded reporting to national tracking agencies such as the Anesthesia Quality Institute. The goal of the interconnectivity is to support improved safety and efficiency, with the expectation that improved outcomes will result due to the use of certified EHRs. The aggregated data collected to date also will be used to develop clinical decision support applications for national high-priority conditions that are currently being defined.

In addition, the interconnectivity in stage 3 moves beyond providers and hospitals and now specifically requires patient-centric solutions. Thresholds for patient access to self-management tools, previously a stage 2 menu objective, are expected to increase and to become core objectives. Stage 3 also will focus on electronic communications between patients and providers. Ultimately, the expectation of stage 3 is that exchange and accessibility of data between providers, hospitals, and patients will begin to improve the population’s health overall.


Narrative Review of AIMS Capabilities

Figure 1
Figure 1:
Unique records identified in PubMed (n = 1951) for screening. After title and abstract review, 284 manuscripts were determined to be eligible for full-text review. A total of 98 manuscripts were included in the review.
Figure 2
Figure 2:
Histogram of anesthesia information management systems publications from systematic review by publication year (x-axis).

The literature search returned a total of 1951 unique references,z of which 1584 were excluded after we screened the titles and abstracts. We reviewed 284 full-text articles, of which 98 met criteria for inclusion in the review (Fig. 1). The full references and a brief description of the manuscripts included (n = 98) can be found in Appendix 2 (Supplemental Digital Content 2, Most of the studies (67.3%) were published after 2007.9–80 The earliest studies were published in 2000. The increase in recent publications focused on AIMS between 2007 and 2014 and may reflect an increased adoption of health information technology in general (Fig. 2).

Automated Documentation of Physiologic Monitors

The anesthesia record documents the physiologic status of a patient during the delivery of an anesthetic for a diagnostic/therapeutic procedure. Core requirements for an anesthesia record include permanence, legibility, and authentication of provider authoring the record.60,61 The Anesthesia Patient Safety Foundation endorses the use of technology that enables the automatic recording of physiologic measurements during anesthetic delivery.4 AIMS can be configured to automatically capture data from physiologic monitors and have been shown to improve the quality of data captured in the anesthesia record.37,49,56,61,62,81 Enabling the provider to focus on patient care, rather than completing the anesthetic record by hand during the anesthetic course, is one benefit of such systems. Other AIMS benefits include automated record keeping, improving completion of preoperative anesthesia evaluation, increased anesthesia record accessibility, and reporting discrete data to local and national reporting agencies.12,21,25,31,39,45,61,62 Physiologic data captured with AIMS can be applied for secondary use, such as describing the hemodynamic profile of hypnotic drugs used for induction of general anesthesia.82 In a similar study, Hartmann et al.83 describe the hemodynamic response after administration of spinal anesthesia with data derived from automated hemodynamic recordings.

However, AIMS documentation also can be prone to errors, such as incomplete data entry and data artifacts.37,49 Therefore, it is critical that the user interface be configured in a way that facilitates data entry at the point of care without compromising other functions. Some have argued that vigilance may be compromised when using an electronic anesthesia record. Davis et al.56 studied this phenomenon by assessing anesthesiologists’ recall of important events during a case when using AIMS-versus-paper anesthesia records. The study was conducted in 2 institutions and found no difference between the ability of 2 groups to recall important data.

AIMS products are fairly specialized in their function. Nevertheless, there are vendors that integrate AIMS with the hospital-wide EHRs and others that provide products with partial certifications that have specific functions for anesthesiologists. Although meeting MU requirements may be a primary concern for some, important features and considerations provided by AIMS beyond the scope of the certification process must be considered. It is worth noting that many features that are desirable in AIMS may not fit into the MU criteria. For example, a system that provides reliable documentation and improves workflow may be a great asset for improving OR efficiency and safety, but these features would not contribute to the MU attestation.

Clinical Decision Support

Features that include preoperative evaluation integration with the anesthesia record, documentation, and clinical decision support applications during the course of an anesthetic, OR resource management, postoperative and recovery phase, and transfer of care (Table 4) are useful and likely crucial, value-added benefits. For example, an AIMS that integrates with the hospital medication administration record (MAR) database can provide a record of medications administered in the OR that is visible to the entire hospital. During surgery, medication administration reminders have been shown to improve adherence to timely administration of prophylactic antibiotics, β-blockers, and adherence to postoperative nausea and vomiting prevention guidelines in various settings.9,22,24,36,43,53,55,84–86 Furthermore, integration of the AIMS medication record with the hospital MAR can improve transfer of care and timing of postoperative medications such as antibiotics. Postoperative antibiotic dosing can be coordinated by clear identification of the last charted dose of antibiotics in the AIMS record and also can be incorporated into the hospital MAR. Additional features of interest include importing data regarding allergies, active medications, problem lists, and laboratory information into the preoperative evaluation record to assist in data collection.

Table 4
Table 4:
Anesthesia Information Management Systems Features

Intraoperative documentation, whether paper based or electronic, carries the risk of data entry errors. AIMS depend on the user interface to facilitate accurate and thorough data entry while caring for a patient. AIMS offer several advantages over paper records, such as improving completeness of anesthesia record and automatic data capture from the anesthesia machine and physiologic monitors.62,64 Processes that rely on manual data entry are always subject to errors, such as omission or incorrectly documented values, regardless of the use of paper-based or AIMS-based records.20,62,87 Several authors have shown that providing electronic reminders during the course of a procedure improves the rate of completion of key elements essential to achieve compliance benchmarks.10,11,23,44,63,69–71 Improving compliance with documentation, such as the guidelines from the Surgical Care Improvement Project, through electronic reminders embedded in AIMS has demonstrated measurable decreases in complications such as surgical site infections.44 Point-of-care alerts for gaps in hemodynamic monitoring intervals also have been shown to decrease the frequency of prolonged gaps in blood pressure documentation during the course of anesthesia care.50 Dexter et al.17 performed a prospective simulation study to determine whether OR managers (anesthesiology, nursing, and support staff) performed better or worse with a system that displayed recommended actions for daily OR management. Individuals made better quality decisions when given access to the command display system that provided recommended course of action and appropriately ignored recommendations that would compromise patient safety.17

There is ongoing development to refine clinical decision support applications to improve the delivery of anesthesia care in various institutions. Blum et al.65 described a system that displays best practice guidelines for ventilation management in patients at risk for acute lung injury. The clinical decision support system provided recommendations to decrease tidal volume to 6 mL/kg and demonstrated a clinically significant reduction in mean tidal volume between the study arms. Nair et al.43,53,63,66 describe the Smart Anesthesia Manager system, which integrates data from AIMS to provide clinical decision support applications, such as point-of-care reminders for antibiotic, and β-blocker administration. The Smart Anesthesia Manager system also has been configured to provide real-time alerts during management of hypotension and hypertension, which demonstrated reduction of the number of episodes of hypotension by displaying an alert when low blood pressure measurements coincided with MAC >1.25 of volatile drugs.66 Clinical decision support applications also can be applied to the preoperative planning process, such as by determining the probability of transfusion associated with specific procedure groups.67,68

OR Management

Patient flow through the perioperative environment involves complex processes requiring coordination among multidisciplinary care teams and transitions between the preoperative holding area, the OR, and the postoperative care area. Stakeholders include surgeons, anesthesiologists, and nursing and support personnel who require access to varied information to perform tasks. Tracking patient status and progress through the perioperative area can be achieved with electronic status boards.16,17,20,27,32,88,89 The electronic status boards can be configured to receive real-time event updates to reflect preoperative readiness and intraoperative events as well as postoperative status.32,69 These boards can be further configured to capture data from each OR and from locations throughout a hospital that involve the delivery of anesthesia, sedation services, or nursing care. These updates can provide actionable information to individuals beyond the point of care.16,20,27,32,89

Anesthesia staff assignments for educational programs also can benefit from systems with electronic procedure tracking. Wanderer et al.79 describe the implementation of a system that compares a resident’s case log to the list of required case numbers from the Accreditation Council for Graduate Medical Education (ACGME). The system allows teams that assign anesthesia cases to consider a resident’s experience and case requirements, whereas residents and residency programs can also keep track of educational activity. Simpao et al.42 describe a system that automates the data entry process for anesthesia resident case logs in the ACGME case log system. The automated system relies on text-parsing procedure descriptions and achieved 97% accuracy for the corresponding ACGME category. Furthermore, they demonstrated that more than half of residents underreport or overreport their case documentation by ≥5%.

Electronic status boards can be a vehicle to disseminate accurate, real-time information about patient and OR status, which can facilitate coordination of resources in the OR.88,89 OR management teams can analyze OR performance and resource utilization, which can assist in planning and daily management.70,90 Ideally, the software used to manage the OR schedule and daily operations integrates with the data from the AIMS records, the hospital’s EHR, and other information management systems that incorporate nursing documentation and the OR schedule.60,71,82 Previous work has attempted to develop algorithms to assist in OR management tasks, such as transferring cases from one room to another to minimize delays and personnel utilization.17,33,59,89,90

Designing daily OR block schedules for individual surgeons and services can be optimized to enhance productivity and minimize underused OR time and patient waiting times.41,59,70,72,91 Applying OR management software to improve decision making related to personnel, and resource assignment to optimize flow and productivity, has shown promise in retrospective and simulation studies.17,33 Dexter et al.17 demonstrated that in a simulated OR schedule, nurses and anesthesiologists made better decisions when given access to a command display with recommendations. When the recommendations compromised patient safety, the teams appropriately ignored them. Doebbeling et al.59 describe the role of leadership in investing and enabling the application of analytical and support applications to optimize both patient and staffing schedules to improve OR efficiency. Broka et al.91 conducted a retrospective evaluation of case duration and applied the information prospectively to adjust the surgical block schedule, leading to a reduction in number of procedures exceeding the allotted block time as well as the surgical waiting list during the study period. Elective block time may be affected by external factors, such as hospital capacity. Dexter and Lubarsky92 analyzed length-of-stay data for surgical and nonsurgical patients and found that the average length of stay for surgical patients is shorter and should be considered when deciding to cancel elective procedures on the grounds of hospital capacity.

Developing efficient models for OR block time relies on data analytics and intimate knowledge of the unique institutional dynamics in the perioperative environment.59 Surgical procedures may be scheduled for a specific amount of time based on a surgeon’s estimates, averages of actual case duration for a particular surgeon, or a combination of techniques. Yet patient factors, such as coexisting disease and unique characteristics, may present unforeseen challenges that contribute to longer or shorter than anticipated procedure times and contribute to gaps in the OR schedule. Surgical block times and resource allocation can be optimized with OR utilization data from daily operations.59,70,72,91 In addition to optimizing block schedules and resources, schedule optimization also can improve patient waiting times and the number of patients in the holding area by minimizing delays and providing clear expectations for fasting time and waiting-room time.41 Patients also can be risk stratified to optimize ambulatory procedures and those requiring overnight admission.73 Agnoletti et al.70 describe their experience incorporating data analysis techniques, which allowed the restructuring of the OR schedule to minimize unscheduled procedures and overtime staff without affecting total surgical case volume.

Electronic status boards can be designed to display the surgery time in several formats. A particular problem revolves around displaying information for procedures that are taking longer than anticipated, such as displaying the time remaining for a procedure that was scheduled to end at 4:00 PM at 4:30 PM. Sorge93 described an unsuccessful attempt to predict actual surgical time with an OR management system that relied solely on historical case duration. Electronic status boards may be configured to display the expected procedure end time, which does not convey actionable information to individuals outside the OR, as a procedure may be finished ahead of schedule or last longer than planned.74 Tiwari et al.74 describe a system that displays the expected remaining time for a surgical procedure rather than the expected time of completion.74 The system relies on status updates, such as indicating when the surgeons begin to close the incision. This study describes one of the challenges of electronic status boards: variations in presentation of information related to case duration.

Dexter et al.34 developed and validated a statistical model that calculated and updated the surgical time remaining based on historical case duration and an estimate from the anesthesiologist. Eijkemans et al.40 developed a statistical model that also incorporates surgeon’s estimate for case duration. Although the surgeon’s estimate had a substantial contribution to the prediction, applying the model would reduce shorter-than-predicted and longer-than-predicted procedures, respectively. Several groups have been able to demonstrate improved OR use after implementing electronic displays to monitor patient flow through the OR.34,40,89

Tracking patients through the perioperative process continues to benefit from ongoing development in OR management systems.69 Status boards have been applied for uses beyond the immediate needs of running an OR. Sullivan32 describe the development of a preoperative tracking system that allows the perioperative team to monitor patients’ readiness for the OR days before their scheduled procedure. Dexter et al.16 and Smallman and Dexter41 describe systems implemented to optimize individual preoperative fasting time instructions based on predictors of procedure duration for the preceding surgical procedures in a specific OR. Similarly, the transition from the OR to the recovery area can be a source of delays, particularly if nursing staff is not sufficient to manage the expected patient volume. Status boards can alert the recovery room of an imminent arrival. Dexter18 and Driscoll et al.20 describe methodologies to systematically evaluate the cause of delays related to transporting patients to the recovery area. Ehrenfeld et al.80 describe the initial implementation of an alert system to assist the postanesthesia care unit (PACU) in assigning beds to patients from ORs that would result in reduction of OR delays from unavailable PACU beds. Although the system was functional, it had no effect on reducing OR delays due to unavailable PACU beds.

Several groups have attempted, with varied success, to develop predictive systems to improve the accuracy of the OR schedule.34,41,74,93 Although status boards alone have not been shown to improve OR efficiency, the ability to track real-time use of the ORs and patient flow is valuable for disseminating information in the OR complex, assisting daily schedule management including staffing assignments, as well as for strategic planning at the institutional level.70,72,94 An additional benefit of OR-management systems used for schedule monitoring and evaluation of operational data is that they can provide critical insight for strategic OR-management decisions.27,33,59,70,72,91 Ultimately, the strength of any information management system depends on all of the processes that govern data entry in the institution.

Population Health—National Repositories

Anesthesiologists serve as patient safety advocates by participating in national data repositories used to establish benchmarks for outcomes such as the frequency of adverse events.28,75–78,95–107 These efforts have relied traditionally on voluntary reporting, a method that can often fail to reliably capture adverse events.51,96–98 Benson et al.98 compared the incidence of adverse events between manual reporting and automatic detection and demonstrated a greater rate of detection with automated systems. Techniques that either automate event reporting or incorporate reporting into the clinical workflow have been shown to increase the rate of reported events.46,51,96–98,108 Incident reporting systems are critical in detecting rare complications and can set the foundation for hypothesis generation and quality improvement initiatives.77

In the United States, MU stage 3 will focus on automating the process for delivering adverse event reports for the purpose of conducting population-level studies. Indeed, several agencies are collecting anesthesia-related, population-level data from hospitals throughout the country, including the Anesthesia Quality Institute, the Multicenter Perioperative Outcomes Group, Wake Up Safe, and the Pediatric Regional Anesthesia Network.57,58,75–77

Meanwhile, automated AIMS incident reporting systems have been implemented in other countries, including the Australian Incident Monitoring database, the German quality project, and the United Kingdom National Reporting and Learning systems.12,13,25,39,45,99–104 These systems allow for automatic AIMS data capture, which is then compiled at the national level to evaluate adverse event rates (e.g., medication errors), perform root cause analysis, and study the incidence of morbidity and mortality studies.78,105–107


The federal incentive program for implementation and MU of the EHR technology provides opportunities for EPs and EHs to receive federal incentive payments if they are able to demonstrate compliance with MU eligibility criteria. Anesthesiologists are currently allowed automatic exemption from participation in the program but may choose to enroll in MU eligibility and collect federal incentive payments. The criteria for provider and hospital eligibility are different under Medicare and Medicaid rules, although an individual or institution may receive incentive compensation from only one of the programs.

Anesthesiologists may be eligible to participate in the MU program and to receive incentives under certain scenarios as specified by the Medicare and Medicaid guidelines. Before enrolling in the MU program, anesthesiologists should consult with institutional MU experts as well as their local regional health information organization to verify eligibility and ability to meet reporting requirements. It may be difficult to comply with all of the reporting measures if anesthesiologists only have access to the data in a standalone AIMS platform, or for anesthesiologists practicing in several hospitals, particularly if the hospitals do not share EHR systems. Much of the data required for MU attestation can be obtained from certified EHR software.

CMS is continually defining MU criteria, which is currently divided into 3 stages. The criteria for the first 2 stages have been fully defined, although modifications to the criteria within these stages do occur as needed. The third stage is still under development. In general, EPs and EHs begin attestation in MU stage 1 and demonstrate compliance during a 2-year reporting period before advancing to stage 2 and 2 years after stage 2 before advancing to stage 3. Initially, providers will receive incentive compensation for participating in MU attestation. Providers who are eligible but do not participate in MU will be subject to reimbursement reductions of 1% of their annual Medicaid reimbursement. The reduction will increase each year by 1%, potentially to a maximum of 5%, unless a hardship exemption is granted.

CMS and the ONC continue to provide guidance for achieving MU attestation through regional extension centers for EHR systems that meet partial or full HITECH certification criteria. HITECH certification ensures the technology will deliver required functionality for MU, yet the requirements are incomplete with respect to important features needed to improve patient safety and practice efficiency during anesthetic care. The benefit of widespread EHR adoption and use, including AIMS, is to improve the quality of individual care through automated documentation of physiologic monitoring, optimizing quality and performance with clinical decision support applications for the patient and OR as a whole, and, ultimately, by contributing to population health tracking to guide quality improvement efforts.


Name: Jorge A. Gálvez, MD.

Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.

Attestation: Jorge A. Gálvez approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

Name Brian S. Rothman, MD.

Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.

Attestation: Brian S. Rothman approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

Name: Christine A. Doyle, MD.

Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.

Attestation: Christine A. Doyle approved the final manuscript.

Conflicts of Interest: Christine A. Doyle is a member of the Anesthesia Advisory Board for Surgical Information Systems and is paid for travel to those meetings.

Name: Sherry Morgan, PhD, MLS, RN.

Contribution: This author helped write the manuscript.

Attestation: Sherry Morgan approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

Name: Allan F. Simpao, MD.

Contribution: This author helped write the manuscript.

Attestation: Alan F. Simpao approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

Name: Mohamed A. Rehman, MD.

Contribution: This author helped write the manuscript.

Attestation: Mohamed A. Rehman approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

This manuscript was handled by: Maxime Cannesson, MD.


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