Perspectives in health information management / AHIMA, American Health Information Management Association最新文献

Documentation requirements for the Indonesian integrated antenatal care (ANC) program suggest the need for electronic systems to address gaps in existing paper documentation practices. Our goals were to quantify midwives' documentation completeness in a primary healthcare center, understand documentation challenges, develop a tool, and assess intention to use the tool. We analyzed existing ANC records in a primary healthcare center in Bangkalan, East Java, and conducted interviews with stakeholders to understand needs for an electronic system in support of ANC. Development of the web-based Electronic Integrated ANC (e-iANC) system used the System Development Life Cycle method. Training on the use of the system was held in the computer laboratory for 100 midwives chosen from four primary healthcare centers in each of five regions. The Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire was used to assess their intention to adopt e-iANC. The midwives' intention to adopt e-iANC was significantly influenced by performance expectancy, effort expectancy and facilitating conditions. Age, education level, and computer literacy did not significantly moderate the effects of performance expectancy and effort expectancy on adoption intention. The UTAUT results indicated that the factors that might influence intention to adopt e-iANC are potentially addressable. Results suggest that e-iANC might well be accepted by midwives.

Objectives: The aim of this study was to survey podiatric residency directors to evaluate the proficiency of first-year podiatric medical residents in the use of electronic medical records and its potential impact on medical care.

Methods: An online survey consisting of Likert-scale, multiple-choice, and open-ended questions was sent via email to 216 podiatric residency directors. Questions were directed toward the level of proficiency in electronic medical records expected at the beginning of residency training and the impact on patient care of residents' inexperience with electronic medical records.

Results: A total of 54 of the 216 podiatric medical residency directors completed the survey. Results indicated that 70.3 percent of respondent directors expected a moderate level of proficiency in the use of electronic medical records; however, 35.2 percent indicated that less than 50 percent of the new residents had experience with electronic medical records prior to starting residency training. Only 51.5 percent of respondent directors felt that the new residents were successful or highly successful in using their hospital's electronic medical record upon arrival, but that figure increased to 98.2 percent upon completion of the first year of residency. Of importance, 29.7 percent of respondent directors reported that inexperience in electronic medical record use resulted in a more-than-average to high impact on patient care, with open-ended responses including concerns about potential HIPAA violations, data breaches, or lost data.

Conclusion: Residency directors deem it important that incoming first-year residents have a basic understanding of electronic medical records and related health informatics concepts; however, in-depth knowledge is not expected because of the high number of software programs available. Nonetheless, nearly one-third of respondents reported that inexperience in electronic medical record use does have a significant impact on patient care.

Effective decision making in the healthcare setting is highly dependent on access to reliable and robust data and information. A minimum data set is a standard assessment instrument that is used during the data collection process to ensure that decision makers have access to a consistent set of information. The objective of the current study was to develop a minimum data set for infertility patients that can be employed as the basis for an infertility registry in Iran. A systematic review resulted in the identification of 2,501 articles and 17 patient forms from infertility centers that were relevant to the study objectives. Of these, 10 articles met all the inclusion and exclusion criteria, and 232 data elements were subsequently extracted from these papers. The data elements were classified by three experts and validated via two rounds of a Delphi technique. The accessibility of the data elements was then evaluated during a focus group discussion. Finally, 146 data elements were selected as the minimum data set. The proposed minimum data set could provide the basis for standardization of infertility treatments. Synchronizing the various data sets that are currently in use will be necessary to allow sharing of data across infertility registries.

When electronic health record (EHR) data are used, multiple approaches may be available for measuring the same variable, introducing potentially confounding factors. While additional information may be gleaned and residual confounding reduced through resource-intensive assessment methods such as natural language processing (NLP), whether the added benefits offset the added cost of the additional resources is not straightforward. We evaluated the implications of misclassification of a confounder when using EHRs. Using a combination of simulations and real data surrounding hospital readmission, we considered smoking as a potential confounder. We compared ICD-9 diagnostic code assignment, which is an easily available measure but has the possibility of substantial misclassification of smoking status, with NLP, a method of determining smoking status that more expensive and time-consuming than ICD-9 code assignment but has less potential for misclassification. Classification of smoking status with NLP consistently produced less residual confounding than the use of ICD-9 codes; however, when minimal confounding was present, differences between the approaches were small. When considerable confounding is present, investing in a superior measurement tool becomes advantageous.

Background: In developing countries such as Iran, international standards offer good sources to survey and use for appropriate planning in the domain of electronic health records (EHRs). Therefore, in this study, HL7 and ASTM standards were considered as the main sources from which to extract EHR data.

Objective: The objective of this study was to propose a hospital data set for a national EHR consisting of data classes and data elements by adjusting data sets extracted from the standards and paper-based records.

Method: This comparative study was carried out in 2017 by studying the contents of the paper-based records approved by the health ministry in Iran and the international ASTM and HL7 standards in order to extract a minimum hospital data set for a national EHR.

Results: As a result of studying the standards and paper-based records, a total of 526 data elements in 174 classes were extracted. An examination of the data indicated that the highest number of extracted data came from the free text elements, both in the paper-based records and in the standards related to the administrative data. The major sources of data extracted from ASTM and HL7 were the E1384 and Hl7V.x standards, respectively. In the paper-based records, data were extracted from 19 forms sporadically.

Discussion: By declaring the confidentiality of information, the ASTM standards acknowledge the issue of confidentiality of information as one of the main challenges of EHR development, and propose new types of admission, such as teleconference, tele-video, and home visit, which are inevitable with the advent of new technology for providing healthcare and treating diseases. Data related to finance and insurance, which were scattered in different categories by three organizations, emerged as the financial category. Documenting the role and responsibility of the provider by adding the authenticator/signature data element was deemed essential.

Conclusion: Not only using well-defined and standardized data, but also adapting EHR systems to the local facilities and the existing social and cultural conditions, will facilitate the development of structured data sets.

Health systems across the nation are recovering from massive financial and resource investments in electronic health record applications. In the midst of these recovery efforts, implementations of new care models, including accountable care organizations and population health initiatives, are underway. The shift from fee-for-service to fee-for-outcomes and fee-for-value payment models calls for care providers to work in new ways. It also changes how physicians are compensated and reimbursed. These changes necessitate that healthcare systems further invest in information technology solutions. Selecting which information technology (IT) projects are of most value is vital, especially in light of recent expenditures. Return-on-investment analysis is a powerful tool used in various industries to select the most appropriate IT investments. It has proven vital in selecting, justifying, and implementing software projects. Other financial metrics, such as net present value, economic value added, and total economic impact, also quantify the success of expenditures on information systems. This paper extends the concept of quantifying project value to include clinical outcomes and nonfinancial value as investment returns, applying a systematic approach to healthcare software projects. We term this inclusive approach Value of Investment. It offers a necessary extension for application in clinical settings where a strictly financial view may fall short in providing a complete picture of important benefits. This paper outlines the Value of Investment process and its attributes, and uses illustrative examples to explore the efficacy of this methodology within a midsized health system.

Purpose: A two-dimensional barcode that includes both static information (vaccine identifier) and variable information (expiration date and lot number) can facilitate streamlined documentation and sharing of vaccine administration. We sought to identify how vaccine tracking information in the two-dimensional barcode is represented in systems that are used by pharmacies, providers, and public health agencies.

Methods: We identified and reviewed relevant information technology standards that govern data storage and exchange for providers, pharmacy systems, billing systems, and manufacturers to identify how each system codes the vaccine identifier, expiration date, and lot number. We selected standards commonly used by manufacturers, providers, and pharmacies and mapped the critical vaccine data elements across them. We shared the mapping with stakeholders to identify areas of alignment across standards and discussed how to address misalignment going forward.

Results: Data elements were not consistently formatted in each type of information system. The vaccine lot number and expiration date were consistent, which would facilitate sharing across information systems. However, the way to identify a given vaccine is not consistent in each standard and would require manual entry. This inconsistency is related to the segmentation of the National Drug Code into three components. Therefore, vaccine identification methods differ across the systems governed by different standards.

Conclusion: Patient safety can be enhanced by automated verification of the vaccine ordered versus the vaccine administered. Immunizers' back-end systems would benefit from automated documentation and reporting.

Screening for risk of unintentional falls remains low in the primary care setting because of the time constraints of brief office visits. National studies suggest that physicians caring for older adults provide recommended fall risk screening only 30 to 37 percent of the time. Given prior success in developing methods for repurposing electronic health record data for the identification of fall risk, this study involves building a model in which electronic health record data could be applied for use in clinical decision support to bolster screening by proactively identifying patients for whom screening would be beneficial and targeting efforts specifically to those patients. The final model, consisting of priority and extended measures, demonstrates moderate discriminatory power, indicating that it could prove useful in a clinical setting for identifying patients at risk of falls. Focus group discussions reveal important contextual issues involving the use of fall-related data and provide direction for the development of health systems-level innovations for the use of electronic health record data for fall risk identification.

Objective: The purpose of this survey was to understand the perceptions and educational goals of the health information management (HIM) workforce in regard to pursuing doctoral-level degrees.

Method: Survey data were collected from members of the American Health Information Management Association (AHIMA) to gain further insight into their interest in pursuing a doctoral degree, their reasons for obtaining such a degree, their methods of learning, and their financial support for an advanced degree. Descriptive characteristics were collected from AHIMA profile information.

Results: A total of 13,020 surveys were electronically sent to selected AHIMA members, of which 1,453 were returned, for an 11 percent response rate. Of the 651 respondents who indicated that they were interested in obtaining a doctoral-level degree, close to half would like to start their doctoral-level study in the next one to five years.

Discussion: This research points to recommendations for efforts to increase student funding opportunities, to increase the number of accredited HIM schools/programs, to create opportunities for doctoral-level study in HIM, to offer options for blended online learning, and to increase the number of doctorally prepared and qualified HIM faculty.