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Venture, the development of the personally controlled electronic health record (PCEHR) system, they have identified that privacy and security are major issues that need to be addressed properly in order for the proposed model to be well received 1. Authentication is the initial stage of validation of the users to. Identity & Access Management (I&A) User ID and Password. Additional hospital staff will need to request access to the EHR Incentive Programs application through Identity & Access Management and be approved by the Hospital’s Authorized Official (gov/NPPES/IASecurityCheck.do).

This EHR is 2015 Edition compliant to the criteria listed below and has been certified by an. Accessed through the generation of a C-CDA file. For assistance with the generation of this. This feature is available upon request through the user’s Customer Success Manager. Unique Device Identifiers (UDIs) can be entered by scanning the. Apr 01, 2014  Many healthcare facilities enforce security on their electronic health records (EHRs) through a corrective mechanism: some staff nominally have almost unrestricted access to the records, but there is a strict ex post facto audit process for inappropriate accesses, i.e., accesses that violate the facility’s security and privacy policies. This process is inefficient, as each suspicious access. Dec 22, 2016 There is overlap of displayed immunization history and vaccine forecasting data elements between MIIC and the EHR systems, as the EHR system draws in response data from MIIC and displays it for the user. The MIIC CDSi through its user interface presented immunization information composed of data elements in three distinct categories: individual demographic data (19), vaccination history (7), and vaccine forecasting recommendations (5). REGISTRATION USER GUIDE. FOR ELIGIBLE HOSPITALS. Step 1 – Getting Started. This is a step-by-step guide for the Medicare and Medicaid Eligible Hospitals Electronic Health Record (EHR) Incentive Program.The page layout consists of the registration screen with written instructions to the right, as well as helpful tips at the bottom.

Abstract

Immunization information systems (IIS) are population-based and confidential computerized systems maintained by public health agencies containing individual data on immunizations from participating health care providers. IIS hold comprehensive vaccination histories given across providers and over time. An important aspect to IIS is the clinical decision support for immunizations (CDSi), consisting of vaccine forecasting algorithms to determine needed immunizations. The study objective was to analyze the CDSi presentation by IIS in Minnesota (Minnesota Immunization Information Connection [MIIC]) through direct access by IIS interface and by access through electronic health records (EHRs) to outline similarities and differences. The immunization data presented were similar across the three systems examined, but with varying ability to integrate data across MIIC and EHR, which impacts immunization data reconciliation. Study findings will lead to better understanding of immunization data display, clinical decision support, and user functionalities with the ultimate goal of promoting IIS CDSi to improve vaccination rates.

Introduction

Immunization information systems

Immunization information systems (IIS) are population-based and confidential computerized systems maintained by public health agencies containing individual data on immunizations from participating health care providers.¹ Individual providers, health care systems, and public health stakeholders in a given jurisdiction access these systems to provide appropriate immunizations and to improve individual- and population-based vaccination rates. IIS offer numerous functionalities such as comprehensive history of vaccinations given across multiple providers and over time, vaccine forecasting algorithms to predict immunizations/clinical decision support for immunizations (CDSi), immunization assessment reports, client follow-up with reminder/recall, vaccine management tools, and state-supplied vaccine ordering capability.

IIS currently operate in a health care ecosystem empowered by electronic health records (EHRs) and other health information technology (HIT). Adoption of these different electronic infrastructures is supported by incentives from the Centers for Medicare and Medicaid Services (CMS)² through the federal Meaningful Use (MU) program. MU includes recommendations on standards to represent and exchange needed patient data and facilitate interoperability guided by Office of the National Coordinator for Health Information Technology (ONC).³ The three-stage MU program recognized the role of IIS in improving vaccination rates and requires standards-based reporting of immunizations to IIS in Stages 1 and 2 and recommendations to access IIS CDSi in Stage 3. The emerging health care reform under Medicare Access and CHIP Reauthorization Act (MACRA),⁵ which comprises Merit-Based Incentive Payment System (MIPS), does incorporate immunization registry reporting and receipt of immunization forecasts and histories from the public health IIS.

CDSi in IIS

The recommendations issued by the Advisory Committee on Immunization Practices (ACIP)⁶ serve as the gold standard for guidelines related to immunizations. These ACIP recommendations are disseminated through various modalities including IIS. An important aspect to IIS is CDSi, which contains computable logic/vaccine forecasting algorithms based on ACIP recommendations that recognize gaps in immunizations and predict needed immunizations. This CDSi evaluation is complex, including factors such as age for vaccine administration, sex, the number of doses, their intervals, precautions, and contraindications.

With increase in use of EHRs, some of these complex immunization CDSi rules have been built directly into EHRs as CDS modules and/or accessed from IIS (through EHRs or directly via IIS interface). Due to immunization schedule complexity and need for a comprehensive vaccination history for accurate predictions, current recommendation is to access CDSi from IIS instead of locally in the EHR as types of CDS vary across provider groups and across EHR implementations.

Minnesota context

IIS in Minnesota (Minnesota Immunization Information Connection [MIIC])⁷ has been operational since 2002 and currently holds 75 million immunizations for 7.6 million individuals with 4,852 organizations as registered users. Minnesota has a strong e-Health environment with a state-wide eHealth Initiative⁸ led by an Advisory Committee and various laws related to e-Health.⁹ Minnesota also has high EHR adoption rate in clinics and hospitals (97% clinics and 100% hospitals),¹⁰ which presents a need and opportunity to better understand the access and use of IIS functions, including CDSi access through EHRs.

MIIC currently offers an option branded as “Alternate Access” to query and access MIIC and the CDSi from within the provider EHR.⁷ This solution offers the ability to generate a query to MIIC for vaccination history and forecasting based on demographics of the EHR record. The display of query results and capability for reconciliation of immunization data vary across EHR platforms and implementation of this functionality.

EHRs and IIS

To date, EHR-IIS research includes concept papers,^11, single clinical setting reports,^13, assessment of automated reporting from EHR to IIS,^, creation of computable CDSi logic,¹⁷ impact of IIS-supplemented EHR reminders on flu vaccination, responses to regulations,^19,20 and refinement of relevant standards.^21, Literature review reveals limited studies on exchange of data across public health systems and clinical care and these have focused primarily on clinician alerts for diseases.^, Studies with emphasis on data interchange between IIS and EHRs have been limited with a paucity of research on CDSi offered by IIS. Prior research by the authors has focused on understanding the technological context around reporting of immunization from EHRs to IIS and in characterizing the access to CDSi in IIS based on volume of queries to the IIS.

The objective of this study was to analyze the CDSi presentation by MIIC IIS through direct access by IIS interface and by access through EHRs to outline similarities and differences. This will lead to better understanding of the display of immunization-related information, clinical decision support, and available user functionalities, with the ultimate goal of promoting IIS CDSi to improve vaccination rates.

Methods

The study was conducted in Minnesota using its IIS, the MIIC. Review of CDSi representation was completed through two modes: interviews of subject matter experts and by review of CDSi-related system functionalities in MIIC and EHRs. The experts for the study were chosen based on their knowledge of CDSi in MIIC and in selected EHR systems. Staff members from the following four organizations were included: the MIIC program, a large non-profit health care system, a local public health department, and an EHR vendor. The interviews were conducted during the time period of March–May 2015 in semi-structured format. The objective was to solicit information on access to MIIC CDSi, fit within the workflow, display of immunization data in user interface of MIIC and EHRs, representation of immunization data elements (including vaccine forecasting) from query of MIIC CDSi, and functional capability of EHRs to incorporate MIIC CDSi data and to understand the process of reconciliation of immunizations across the two systems. Topics included in the semi-structured interview are displayed in Table 1.

Table 1

→
Participants and their role	Demonstration of access to CDSi and its fit within workflow
←
Representation of immunization data elements (including vaccine forecasting) from query of MIIC CDSi	Display and presentation of immunization data in user interface of IIS and EHRs
→
Functional capability of EHRs to incorporate MIIC CDSi data and the Immunization Reconciliation Process	Other relevant information

The EHR systems (Epic©, PH-Doc©) examined in this process were selected based on high adoption in Minnesota with Epic© being used by 49% of clinics²⁷ in the state and PH-Doc© used by 56% of local public health departments.²⁸ Apart from being the dominant market product in private and public health care, these products also had varying functionality with Epic© offering a static (read-only) view of MIIC CDSi and PH-Doc© offering an interactive option for movement of data across MIIC and EHR. Screenshots of the various user interfaces relevant to CDSi were collected from MIIC and from the two EHR systems as part of this process. Analysis focused on the data elements presented, categories of information, presentation of data and ability for reconciliation of immunization data with capabilities for data comparison, data edits, and data input into EHR from MIIC.

Results

Both the EHR products examined (Epic©, PH-Doc©) had access to MIIC positioned within the immunization workflow. Both EHRs offered the ability to generate a query to MIIC for vaccination history and forecasting based on demographics of the EHR record. This option addresses the issue of repeat data entry for the query and also does not require logging into the MIIC system separately. Data displayed from MIIC and the two EHR systems are presented in Table 2. There is overlap of displayed immunization history and vaccine forecasting data elements between MIIC and the EHR systems, as the EHR system draws in response data from MIIC and displays it for the user. The MIIC CDSi through its user interface presented immunization information composed of data elements in three distinct categories: individual demographic data (19), vaccination history (7), and vaccine forecasting recommendations (5). Figure 1 presents the 31 data elements presented by MIIC in the direct interface access. Figures 2 and ​and33 highlight the vaccination history and vaccine forecasting display provided by MIIC.

Clinical Decision Support for Immunizations (CDSi) presented by MIIC.

Vaccination history display in MIIC.

Screenshot: Courtesy of MIIC.

Vaccine forecasting display in MIIC.

Screenshot: Courtesy of MIIC.

Table 2

DISPLAY ELEMENT	MIIC	PH-Doc©	EPIC©
Individual information
Name	✓	✓	✓
Birthdate	✓	✓	✓
Gender	Stored elsewhere	Stored elsewhere
Address	✓	✓	✓
Mother’s maiden name	✓	✓	✓
Chart#/MIIC ID	✓	✓	✓
VFC eligible	✓	✓	✓
Schedule name	✓	✓	✓
Client comment	✓
Vaccination history
Date administered	✓	✓	✓
Series	✓	Stored elsewhere	✓
Vaccine group	✓	✓	✓
Vaccine/trade name	✓	✓	✓
Dose	✓	✓	✓
Owned?	✓	Stored elsewhere	✓
Reaction	Stored elsewhere	Stored elsewhere	✓
Historical?	✓	✓	✓

The variation was in presentation of the vaccination history and the ability to integrate data across the two EHR products examined. The MIIC CDSi data displayed by the PH-Doc© system (Fig. 4) holds much of the same data elements as the MIIC display. A key functionality of PH-Doc© is the dynamic data exchange between MIIC data from query of IIS and the EHR system. Data can be reconciled by incorporating data from the MIIC query directly into the EHR without the need for manual data entry. PH-Doc© provided the capability to compare immunization differences between MIIC and the EHR system in a side-by-side view of both systems. In addition, it highlighted differences in immunizations between the two systems, which is essential for reconciliation of immunization data. Review of Epic© pointed to a read-only view of the MIIC data obtained from Alternate Access query (Fig. 5) and did not support side-by-side comparison of data from the two systems. The data display utilized the same formatting options as in MIIC with similar display of vaccination history and forecasting.

Dynamic data display provided by PH-Doc©.

Notes: MCCC confidential. These materials contain copyrighted confidential and/or proprietary information of Minnesota Counties Computer Cooperative. Reproduction, distribution, or other use of this information requires the prior written consent of MCCC. ©2011 Minnesota Counties Computer Cooperative. All rights reserved.

MIIC CDSi data display in Epic.

Notes: Copyright © Epic Systems Corporation. Screenshot: Courtesy of MIIC.

Discussion

As immunization guidelines are increasingly embedded into various electronic tools, including EHRs, there is a need to decrease the variability due to varying logic (CDSi rules) across the variety of clinical decision support options. IIS CDSi incorporates ACIP recommendations and presents a great opportunity to increase the uniformity in implementation of immunization guidelines. Both current efforts to promote EHR adoption/use (MU) and emerging⁵ payment reform efforts ensure use of interoperable and certified EHRs. Given this EHR landscape, there is a growing need for research on access and use of CDSi at the point of care, specifically through EHRs.

An Ehr User's Manual Is Accessed Through The __ Feature Lyrics

This study contribution is to analyze and present information about the IIS CDSi through various access options, both directly through the IIS interface and by access through EHRs. Study limitations are that it presents functionality during early 2015 and does not describe current EHR product upgrades. Additionally, current Epic© and PH-Doc© installations do support dynamic data movement between MIIC and EHR, which is essential for reconciliation of the immunization data. Another limitation is that the study focuses on presentation of immunization data and does not validate the rules/decision logic in both MIIC and the two EHR systems.

Identifying how best to utilize decision support and immunization data available through IIS will be of high importance as bidirectional exchange across EHRs and IIS is implemented. Recent projects have evaluated the capability of select EHR products in their ability to submit data to the IIS and query the IIS²⁹ and in the process of developing usability guidance documents.³⁰ Vendors and users should participate in the usability review process and also utilize the guidance for product enhancements and EHR review/selection. It will be of great benefit if national organizations such as the American Immunization Registry Association³¹ can work collaboratively with IIS and EHR communities to develop best practices around presentation of IIS data in the EHR and issue guidelines on reconciliation of immunization data across the two systems.

As delivery of certain preventive services including immunizations have spread beyond the confines of traditional health care organizations, IIS serve as a hub for immunization data by holding immunization information across providers and over time. In addition, they can serve as a central resource for decision support logic based on current ACIP recommendations. It is essential to understand the access and use of the IIS CDSi functionality, given the increasing adoption and use of EHRs. Findings will help to guide best practices in immunization data integration and data display and, ultimately, support clinical decisions on immunizations.

Acknowledgments

The authors would like to thank Dr Genevieve Melton-Meaux, MD, PhD, FACMI, for her guidance with the project grant. The authors express their gratitude to Emeritus Professor Laël C. Gatewood, PhD, FACMI, for her editorial assistance with the manuscript. In addition, the authors would like to thank Deb Castellanos and Mary Thompson from Xerox Corporation for sharing their expertise related to immunization decision support by PH-Doc©. Finally, the authors acknowledge the support of Minnesota Counties Computer Cooperative for providing permission to utilize the screenshot from PH-Doc© and to MIIC Leadership for allowing usage of various screenshots.

Footnotes

ACADEMIC EDITOR: John P. Pestian, Editor in Chief

PEER REVIEW: Two peer reviewers contributed to the peer review report. Reviewers’ reports totaled 435 words, excluding any confidential comments to the academic editor.

FUNDING: This project was supported by an On the Horizon grant from the University of Minnesota Informatics Institute (UMII). The authors confirm that the funder had no influence over the study design, content of the article, or selection of this journal.

COMPETING INTERESTS: Authors disclose no potential conflicts of interest.

Paper subject to independent expert blind peer review. All editorial decisions made by independent academic editor. Upon submission manuscript was subject to anti-plagiarism scanning. Prior to publication all authors have given signed confirmation of agreement to article publication and compliance with all applicable ethical and legal requirements, including the accuracy of author and contributor information, disclosure of competing interests and funding sources, compliance with ethical requirements relating to human and animal study participants, and compliance with any copyright requirements of third parties. This journal is a member of the Committee on Publication Ethics (COPE).

Author Contributions

Conceived and designed the project: SR. Participated in project: SW, AB, DJ, TW, MM. Wrote the first draft of the manuscript: SR. Contributed to the writing of the manuscript: SW, MM. Provided content for manuscript: AB, DJ, TW. All authors reviewed and approved the final manuscript.

REFERENCES

In collaboration with leading market research company Research Now, Software Advice has conducted its annual electronic health records (EHR) survey. This survey polled users of EHR software, asking questions about which system they use, their level of satisfaction and the key benefits and challenges they face.

We collected nearly 600 responses in 2014 from users from a diverse range of medical specialties and practice sizes to discover the top EHR software user trends. Here’s what we found.

Key Findings

1. Mobile users reported higher levels of satisfaction and fewer challenges with their EHR than non-mobile users.
2. Investing more in patient portals was a top priority, partially due to the need to improve patient engagement.
3. Over half of users reported having difficulties integrating data from external systems with their EHR system.

Mobile Users More Satisfied With EHR System

Despite an increase in the availability of mobile applications offered by EHR vendors, a majority of users were accessing their EHR from a desktop or laptop computer (which, in a clinical setting, is typically attached to a cart—thus limiting mobility).

Only 26 percent of users were accessing their EHR from a tablet or smartphone, compared to a combined 76 percent using desktops or laptops. Users were allowed to select multiple devices, so responses were non-exclusive.

Device Used to Access EHRs

Despite the prevalence of computer usage, those in our sample who were using tablets and smartphones expressed higher levels of overall satisfaction with their EHR system. Fifty-eight percent of users who accessed their EHR from a mobile device were “very satisfied” with their EHR, compared to 28 percent of non-mobile users.

Satisfaction With EHR, by Device Type Used

Mobile Users Experienced Fewer EHR Challenges

The fact that mobile users were more satisfied with their systems is likely tied to our next finding: that mobile users were less affected by common EHR software challenges than non-mobile users were.

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Difficulty in learning to use the system and with decreased productivity were two areas where the differences between mobile and non-mobile users were greatest.

Only 39 percent of mobile users expressed that learning how to use their EHR system was challenging, versus 58 percent of non-mobile users.

This discrepancy could be attributed in part to mobile users taking their devices home with them to learn the system outside of normal working hours—and in part to the fact that 47 percent of physicians already use mobile devices for clinical purposes.

Difficulty of Learning EHR System

Interestingly, mobile users also reported fewer problems with their EHR decreasing productivity: 73 percent said this was not a challenge, compared to just 42 percent of non-mobile users who said the same.

Effect of Slowed Productivity Due to EHR

A 2013 survey by Black Book Rankings showed that 89 percent of primary care and internal medicine physicians were already using their smartphones to communicate with hospital staff.

Since many physicians are already familiar with using mobile devices to improve communication, it follows that EHR users’ productivity would be less impacted when accessing the software via a mobile application.

Thus, the familiarity and portability of mobile devices seems to go a long way towards ensuring doctors’ ultimate satisfaction with their EHR.

Patient Portal, E-Prescribing Are Top Future Investments

With this in mind, we asked users what their future EHR-related investment plans looked like. Twenty-eight percent of users responded that they would be increasing their investment in EHR software throughout 2014, and 54 percent indicated that they would keep their level of investment the same.

Only 5 percent of users plan on decreasing their investment, while 13 percent stated that they were unsure.

Expected Future EHR Investment

This is in line with our 2014 EHR BuyerView: We found that an increasing number of buyers were looking to replace existing EHR software, which may account for a portion of the 28 percent of users looking to increase their investment. Next, we asked physicians which EHR modules and applications they planned to invest in more heavily in the future.
As we’ve observed previously, physicians surveyed were most interested in increasing their investment in patient portals (36 percent), defined by healthIT.gov as “secure online website[s] that [give] patients convenient 24-hour access to personal health information.”
Patient portals are a requirement for achieving Meaningful Use Stage 2, and increased investment demonstrates a noticeable push to meet 2015 government deadlines.
Furthermore, many practices are hoping that providing patients access to their medical records via a patient portal will increase patient engagement (more on this later).

EHR Investment Plan, by Category

Electronic prescribing (“e-prescribing”), included as part of Meaningful Use Stage 1 requirements, has risen in priority since our early results report; 29 percent of users say they plan to invest more heavily in this.

The true value of e-prescribing, however, lies in its ability to protect patients from harmful medication mixups. E-prescribing has been shown to decrease the rate of prescribing errors, which are the most prevalent type of medication error among primary care practices.

As with patient portals, health information exchange applications are included in Meaningful Use Stage 2 requirements. The term “health information exchange” broadly covers the transfer of health information between healthcare professionals, facilities and government entities.

Twenty-nine percent of users in our sample indicated that they would be investing more in these applications.

Under one-quarter of respondents plan to invest in business intelligence, picture archiving system (PACS) or radiology information system (RIS) functionality.

Business intelligence and the large amount of data it generates have been shown to cut healthcare costs and improve patient care, but a system with these pricier, more advanced data-analytic capabilities may not yet be considered a worthwhile investment for smaller practices.

Integration, Productivity Are Top EHR Challenges

Over half of users surveyed (56 percent) responded that integrating their EHR with other systems presented a “major” or “moderate challenge.”

This is a common complaint among healthcare professionals, as integrating data from external systems, such as outside laboratories, state/government organizations and other medical systems using a different EHR, has proven more challenging for many organizations.

Top Challenges of EHR System

Problems with EHRs slowing productivity—reported by 49 percent of users—have been part of the discourse surrounding EHRs since the passage of the HITECH Act in 2009. Part of this problem could be due to practices using non-portable devices to access their EHR, as described above.
Further, a UC Davis study from 2010 attributed losses in productivity to adopting an EHR that had not been customized for the user’s specialty, a problem that can be addressed by using a system with specialty-specific templates.
Indeed, customization itself was the next most challenging item, selected by exactly half of respondents—suggesting that these templates are not being widely used.
Significantly fewer users were concerned with instability, bugs and latency; end-user adoption; and achieving Meaningful Use. Although the Center for Medicare and Medicaid Services has reported a lower than expected number of doctors and hospitals attesting for Meaningful Use Stage 2, only 32 percent responded that they believed meeting Meaningful Use was a challenge.
Since deadlines to achieve Stage 2 have been extended several times already, EHR users may feel less urgency due to the belief they could again be granted more time.

Most Users Benefited From Improved, Easy-to-Access Records

Unsurprisingly, a majority of respondents indicated that the key benefits their EHR delivered were improved records that were easier to access (87 percent said this benefit was delivered “well” or “very well”) and to interpret (85 percent said the same).

Ability of EMR to Deliver Key Benefits

Despite recent criticism about drug interaction alerts overloading physicians (dubbed “alert fatigue”), a combined 79 percent of users praised their EHR for the quality of its drug interaction alerts. Drug interaction alerts, a feature of e-prescribing, help prevent the adverse effects caused by mixing two or more incompatible drugs.
Physicians were significantly less satisfied with another type of alert: preventive care reminders. This indicates that vendors should seek to improve this feature in order to better assist physicians in scheduling preventative care appointments, a key component of the Affordable Care Act.
Users were also dissatisfied with their EHR’s ability to improve patient engagement, which has been prioritized in Meaningful Use Stage 2 requirements. Based on our future investment results, it appears that physicians are attempting to solve this problem by increasing their investment in patient portals.

Smaller Practices Expressed Higher Levels of Satisfaction

We found that users from smaller practices were more satisfied with their EHR system than those from larger practices. Forty-three percent of small-practice users reported being “very satisfied,” compared to just 31 percent of large practices that said the same.

EHR Satisfaction, by Practice Size

This is in line with other findings across the industry, in which smaller organizations of 50 or fewer practitioners reported being more satisfied with the implementation of their EHR system than larger ones.

Despite the challenges faced by some users, overall satisfaction rates were high. Seventy-five percent of users were at least “somewhat satisfied” with their EHR system, with 35 percent reporting that they were “very satisfied.”

Overall Degree of EHR Satisfaction

Demographics

Our respondents represented a variety of medical specialties, practice sizes and EHR systems used. EpicCare EMR was used by 15 percent of respondents—aligning with the 20 percent share of the ambulatory EHR market this product had in our EHR Meaningful Use Market Share report earlier this year.

Demographics: EHR Systems Used

Forty-two percent of responses came from users at small practices, defined as those with fewer than three doctors on staff. Medium-sized practices, with between four and 10 doctors, made up 26 percent of the sample, and large practices of 11 or more doctors comprised 32 percent.

Demographics: User Size by Number of Doctors

Eighteen percent of users surveyed specialized in internal medicine or primary care. Doctors from health centers and “multiple specialties” were next, with 7 and 6 percent, respectively. Forty-one percent of survey takers did not list a specialty, and are represented as “other” in the figure below.

Demographics: EHR Users by Practice Type

Methodology
We used several approaches to collect responses for this survey. First, we emailed survey invitations to EHR software buyers who contacted Software Advice for guidance in their software-selection process. We also posted the survey on social networking sites, including Twitter, LinkedIn and Google Plus.

An Ehr User's Manual Is Accessed Through The __ Feature Youtube

Additionally, we contacted leading EHR software vendors and asked them to share the survey with their users. These included vendors that both are and are not current clients of Software Advice, but client status was not used as a basis for inclusion of responses.

Finally, the majority of the responses to the survey were obtained by our third-party research partner, Research Now.

To discuss the results or gain access to any of these charts, contact gaby@softwareadvice.com.