- An Ehr Users Manual Is Accessed Through The Blank Feature
- An Ehr User's Manual Is Accessed Through The __ Feature Tv
The Composite Health Care System (CHCS) is a medical informatics system designed by Science Applications International Corporation (SAIC) and used by all United States and OCONUS military health care centers. In 1988, SAIC won a competition for the original $1.02 billion contract to design, develop, and implement CHCS.[1]
Components and characteristics[edit]
Start studying EOC CH 1. Learn vocabulary, terms, and more with flashcards, games, and other study tools. PrimeSUIITE's User Guide is accessed through the feature a. The is an example of clinical information that is collection through an EHR a. Insurance policy b. Plan of care c. Research effects d. EHR Manual Version 4.81 EHR Manual Modified:26-May-10 1 of 54 Contents. The Perio items displayed can be changed (if the user‟s security level permits) by right clicking on the Perio lines to access the change menu. The EHR Perio Conditions to Display window will open. Select the conditions to display for each of the available.
CHCS is module based: modules include RAD (radiology), LAB (Laboratory), PHR (Pharmacy), PAS (Patient Appointing & Scheduling), MCP (Managed Care Program; used to support TRICARE enrollees by enrolling them to Primary Care Managers), PAD (Patient Administration): MRT (Medical Records Tracking), MSA (Medical Service Accounting) medical billing, WAM (Workload Assignment Module), DTS (Dietetics), CLN (CLinical: Nursing, Physician, and Allied Health), DAA (Database Administration), ADM (Ambulatory Data Module) Medical Coding of outpatient visits, and TOOLS (FileMan).
Currently all appointments are booked in CHCS, except for Walk-Ins and Telephone Consults, which can now be booked in AHLTA. CHCS is a text based BBS/ANSI like display accessed via DEC VT320 terminal emulation. CHCS supports outpatient Order Entry (LAB, RAD, PHR, Consults (ancillary procedures), one-time and scheduled/multiple appointment consults. CHCS can also support Inpatient charting and Order Entry with multi-paging with a page for each ward the patient is transferred, but this feature is not fielded/enabled at many medical centers. Instead Clinicomp's Essentris product is deployed at all MHS hospitals and has replaced the use of CHCS Inpatient module for nurse charting. An interface solution to allow Essentris Orders to be transferred into CHCS order entry is being deployed.
AHLTA[edit]
Armed Forces Health Longitudinal Technology Application (commonly referred to as AHLTA) is the clinical documentation engine for the Physicians to write their notes, put in orders, document procedures performed and provide the basis of medical coding information. This information is then sent into CHCS and its subsystems (ADM - ambulatory data module) provide the official repository of the medical coding information and handle the transmission of those encounters via the Comprehensive Ambulatory Patient Encounter Record (CAPER) interface. The clinical data is brought into the M2 DataMart for use in research, operational metrics, trend analysis, and many other business intelligence processes/products. AHLTA information is also contained in a Central Data Repository (CDR). This CDR contains information from AHLTA, CHCS, and AHLTA-Theater. The AHLTA CDR is a comprehensive full scale world-wide EHR repository.
CHCS shares its original codebase with the VA's VistA system. Since its inception it has been customized for supporting the Military and their family members.
Security in CHCS works by a number of mechanisms and includes the concept of least privilege. Is there a gab user manual download. You are assigned the minimum needed for your work duties. This limits your access to sensitive data both protected by the Privacy Act 1974 and PHI protected under HIPAA.
AdHoc reports can be written using the FileMan tools and can be quite powerful if the files are designed with that in mind. Many CHCS files are now more easily accessed with MUMPS routinues that can make more efficient use of the internal data structures. More information about FileMan can be found at www.hardhats.org. CHCS, which now runs on InterSystems Caché with the MUMPS globals being converted into Caché objects and the MUMPS routines accessing them, now can be accessed with .NET tools to query the Caché database. Many facilities have developed special queries of CHCS or new tools to facilitate workflow and processes. One such tool is an intranet web application to facilitate printing of lab specimen labels to special printers with formats not possible with the regular CHCS print devices and label printing methods.
CITPO (now known as Defense Health Information Management Systems (DHIMS)) began the implementation of AHLTA, the DoD's Electronic Health Record(EHR) system, in January 2004. The system links the 481 Military Treatment Facilities (MTF) worldwide as well as service members deployed abroad to the EHR, ultimately supporting 9.2 million MHS beneficiaries. The introduction of AHLTA, previously known as the Composite Health Care System II, ushered in a significant new era in health care for the MHS and the nation. AHLTA Version 3.3.3.X with client update 9.1 currently fielded to physician and clinic staff workstations. DHIMS also manages the AHLTA-Theater program that provides EHR capabilities to deployed users with important store and forward capabilities when communications are unavailable.
AHLTA and a significant portion of CHCS are slated to be replaced by a VA/DoD interagency iEHR program. The iEHR will bring together the strong Health IT resources of both the VA and the DoD to acquire the next generation EHR capabilities for both departments.
Record Duplication[edit]
As with all large hospital information systems, there are occasions that despite training and best intentions, duplicate patient records are created. CHCS has a function to merge patients, but not to unmerge. AHLTA also has merges performed on patients in its Oracle database and successful attempts are made to un-merge patients and their associated medical/encounter data where diligent research has determined that mistakes were made with the identification of patients and to split off encounter records from patients that are blended into the single AHLTA record. Master Patient Indexing is a feature of the AHLTA Clinical Data Repository (CDR). Over 100 CHCS host systems, DEERS (Defense Enrollment Eligibility Reporting System), and AHLTA Theater (the version being used in Iraq and other areas) all contributed patients into the CDR when it was created from 25 month data pulls back in 2004. Each CHCS patient registration links into AHLTA, some link to existing patients, but others are newly created. Complexity with patient names and methods of identifying them with other demographics can lead to duplication, both in a local CHCS system and in the central AHLTA CDR. There is currently a DHIMS contract working on improving the processes and automating the routines to resolve duplicate patients and prevent their creation in future.
References[edit]
- ^Dr. J. Robert Beyster with Peter Economy, The SAIC Solution: How We Built an $8 Billion Employee-Owned Technology Company, John Wiley & Sons (2007) p.88
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Composite_Health_Care_System&oldid=922013089'
Published online 2016 Dec 22. doi: 10.4137/BII.S40208
PMID: 28050128
This article has been cited by other articles in PMC.
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.
Keywords: immunization, immunization information system, biomedical informatics, clinical decision support, electronic health record, Minnesota
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.
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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.
An Ehr Users Manual Is Accessed Through The Blank Feature
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.
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.
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An Ehr User's Manual Is Accessed Through The __ Feature Tv
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