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

Purpose: Because user acceptance and resistance to the use of health information technology (HIT) affects system utilization and previous studies in this area have typically excluded pharmacists, this study specifically addresses the response of institutional pharmacists to HIT.

Methods: A survey investigating pharmacists' responses to electronic medical record (EMR) system use was developed using questions modified from previously validated research. The survey was distributed electronically to the mailing list for pharmacy preceptors for the University of Tennessee College of Pharmacy. Descriptive statistics and univariate and multivariate analyses were used to analyze the collected data based on a previously validated dual-factor model.

Results: Of the 96 responses from institutional pharmacists, 64 responses (66.7 percent) were complete and usable. Of the acceptance and resistance constructs evaluated, only attitude and perceived behavior control were found to be significantly associated with acceptance of use (p = .036 and p = .025, respectively), and only transition cost was found to be significantly associated with resistance to use (p = .018). System vendor and interface integration were also significantly associated with acceptance of use. These findings suggest that attitude, perceived behavior control, and transition costs may have the most impact on pharmacists' responses to the use of EMR systems.

Conclusion: It is reasonable for hospitals to focus efforts on specific factors influencing acceptance of and resistance to EMR use and, before a system is selected, to consider the effects of vendor selection and level of interface integration on acceptance of use.

On October 1, 2015, the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) was incorporated into the US public health system. Because of significant opposition and reservations expressed by stakeholders, while the proposed rule for ICD-10-CM adoption was issued in 2009, the transition did not occur until October 2015. The purpose of this study was to identify conversion initiatives used by a public health institution during the initial and subsequent stages of ICD-10-CM implementation, to help similar institutions address future unfunded healthcare data infrastructure mandates. The data collection for this study occurred from 2015 to 2018, encompassing 20 semistructured interviews with 13 department heads, managers, physicians, and coders. Research findings from this study identified several trends, disruptions, challenges, and lessons learned that might support the industry with strategies to foster success for the transition to future coding revisions (i.e., ICD-11).

Objectives: Soft-tissue sarcoma (STS) is a heterogeneous group of rare solid tumors that arise from various soft tissues in the body, such as muscle, fat, nerves, and blood vessels. Current International Classification of Diseases (ICD) coding systems include a set of nonspecific codes for malignancies of connective and soft tissue (ICD-9-CM code 171 and ICD-10-CM code C49). The goal of this study was to evaluate the use of these codes for health services research involving patients with a diagnosis of this rare malignancy.

Methods: Two databases were utilized to explore ICD coding for STS: claims data from Truven MarketScan and electronic medical records (EMRs) from Flatiron Health. Eligible patients from claims data were those with at least two ICD-9-CM codes of 171.x on two different days between July 1, 2004, and March 30, 2014. The treatment patterns of these cases were evaluated for consistency with known therapeutic approaches for STS. Eligible patients from the Flatiron EMR system were those who received olaratumab (a drug indicated only for use in patients diagnosed with STS) after its US Food and Drug Administration approval in October 2016 through the end of the data set (November 2017). ICD-10-CM codes were evaluated for this known STS cohort.

Results: In claims data, 4,159 patients were eligible for inclusion. Although national treatment guidelines include only a limited number of drugs used to treat STS, 98 unique anticancer drugs were identified as being used to treat patients in a claims data cohort. Only 7.7 percent of patients had claims for doxorubicin-based therapy and 3.8 percent had claims for ifosfamide-based therapy as initial treatment for STS, despite these being a standard of care. In the EMR data, 350 patients were eligible; only 170 patients (48.6 percent) had any evidence in the database of a connective or soft-tissue ICD-10-CM malignancy code within 60 days before or after initiation of olaratumab.

Conclusions: ICD coding for STS using the "Malignant neoplasm of connective and soft tissue" code is not reliable as a method to identify patients diagnosed with STS. Although codes reflecting the primary site of disease may have clinical relevance, lack of consistency in ICD coding for the diagnosis and treatment of this disease is a limiting factor in the ability to conduct real-world observational research of this rare disease. In the absence of consistent use of this code, an algorithm needs to be developed and validated to accurately identify patients with STS in these databases.

Overview: As chronic disease and comorbidities increase, so does the complexity of patient care.This complexity requires interdisciplinary care teams and multifactor interventions to ensure that patients get the most efficient care. Patient navigators-defined as individuals who help patients move through the complex care continuum-can improve access to care and patient engagement, which can translate into better outcomes. Health information technology (health IT) can support timely communication and information sharing for patient navigators and the providers with whom they interact to better coordinate care. We explored the health IT that patient navigators used, how they used it, and their health IT needs in community-based interventions.

Methods: We analyzed three years of qualitative program evaluation data captured though progress reports, site visits, and telephone interviews as part of a larger evaluation of community-based demonstration projects. We used inductive analysis to identify preliminary themes to develop a codebook. Using QSR International's NVivo qualitative analysis software (version 11.0), we then used the preliminary themes in a second round of independent coding. We identified themes relevant to navigators and to barriers and facilitators for health IT. Coders achieved a final kappa of 0.8, suggesting excellent interrater reliability.

Results: Navigators used various types of health IT (e.g., health information exchanges, electronic health records, short message service) to capture and share information with the rest of the care team. Navigators used technology to document patient information, track services, and schedule appointments for patients; however, some respondents reported challenges with systems that were not integrated. Navigators must learn to use health IT systems of varying complexity to complete their job duties.

Discussion: Health IT can improve workflow by facilitating task organization and communication with the care team. Ultimately, integrating the health IT systems used by navigators with those used by other care team members was most beneficial. Because of the various types of health IT used, patient navigators should receive training to ensure that they have the technical skills to use these systems efficiently and reduce duplication of effort.

Conclusion: Managing the care of patients with chronic disease requires comprehensive care teams, which can include patient navigators. Integrating navigators' documentation into other health IT systems can keep providers updated on information while patients are outside of the providers' care. With the growth of health IT use in recent years, technical skills are becoming increasingly important. These findings can help leaders who are planning complex health interventions involving navigators to ensure that technology is used efficiently to support

Introduction: Emergency care is usually conducted within limited time and with limited resources. During emergency care processes, data quality issues should be taken into account. The aim of this study was to assess the quality of emergency care data from the perspectives of different data stakeholders.

Method: This survey study was conducted in 2017. In this research, the viewpoints of three groups of data stakeholders, including data producers, data collectors, and data consumers, were collected regarding data quality in emergency care services. Data were collected by using a standard information quality assessment questionnaire.

Results: The mean values for each dimension of data quality were as follows: sound data (6.23), dependable data (6.28), useful data (6.30), and usable data (6.35), with 0 being the lowest possible score and 10 being the highest. The role gap analysis suggested a clear gap between data producers and data customers at the university level.

Conclusion: Overall, data quality in emergency medical services was not at a high level. Although data quality was improving, the levels of data completeness, compatibility, and usability were low. To improve the usability of emergency medical service data, more attention should be paid to the dimensions of accuracy, completeness, and consistency of data sources.

Physicians spend a large portion of their time documenting patient encounters using electronic health records (EHRs). Meaningful Use guidelines have made EHR systems widespread, but they have not been shown to save time. This study compared the time required to complete an emergency department note in two different EHR systems for three separate video-recorded standardized simulated patient encounters. The total time needed to complete documentation, including the time to write and order the initial history, physical exam, and diagnostic studies, and the time to provide medical decision making and disposition, were recorded and compared by trainee across training levels. The only significant difference in documentation time was by classification, with second- and third-year trainees being significantly faster in documenting on the Cerner system than fourth-year medical student and first-year trainees (F = 8.36, p < .001). Level of training and experience with a system affected documentation time.

Coronary catheterization is the gold standard for diagnosis and treatment of cardiovascular conditions. The development of a catheterization and percutaneous coronary intervention (CathPCI) registry considering key steps of data management has a pivotal role in coronary catheterization because it could help improve CathPCI approaches, develop equipment and devices, and minimize complications of the CathPCI procedure. Data management comprises data gathering, data processing, and information distribution. Data gathering involves the collection of data elements, including demographics, episode of care, history and relevant risk factors, visits to the catheterization laboratory, diagnosis of cardiac catheterization, estimation of the coronary arterial anatomy, percutaneous coronary intervention procedures, lesions, devices, outcomes, and discharge. Data processing is performed with respect to the number of procedures performed in different circumstances, the outcomes of the performed procedures, improvement in the healthcare approach, development of devices and equipment, and the quality of the performed procedures. Information distribution involves the sharing of information and making information accessible to researchers and clinicians, relevant health care managers, and manufacturers of medical devices and equipment. This study reviewed relevant English-language publications regarding cardiac catheterization registries, data collection, data processing, and information distribution, regardless of the date of publication.

The future of clinical documentation improvement (CDI) will require expanding the reach of CDI programs into new areas of expertise because the traditional realms of CDI work are increasingly becoming automated. CDI-based research and analytics can serve as a means for demonstrating continued value to an institution. We present four studies as examples of these efforts. We explored the use of claims data to determine whether a clinical condition meets the criteria for a secondary diagnosis and to evaluate whether a clinical problem should be elevated to the status of a comorbid or complicating condition. We demonstrated a way in which CDI professionals can evaluate the impacts of changes in clinical definitions, and we explored how CDI can work with other institutional programs to decrease length of stay. We believe that these models may serve as a springboard within institutions and among the larger CDI community to make research and analytics a foundation of future CDI activities.

Research shows that exposure to community and domestic violence leads to psychological trauma from childhood through adulthood, which can lead to poor health and early death. A team of health information management (HIM) professionals reviewed existing surveys to determine their suitability for assessing the quality of life (QoL) of people in trauma-affected communities (TACs). Keywords were used to search for papers describing validated QoL surveys. The obtained papers were screened, reviewed, and summarized to determine if they include the aspects needed for assessing QoL in TACs. Survey items from 20 surveys were identified as relevant to this study. Most of these 20 surveys cover one or two domains of QoL, and none of them were specifically designed for people in TACs. Therefore, it is necessary to develop a psychometrically sound assessment tool to quantify the levels of trauma, resilience, and well-being in TACs. HIM professionals have the required skills for this task.

As healthcare systems continue to expand their use of electronic health records (EHRs), barriers to robust and successful engagement with such systems by stakeholders remain tenacious. To this effect, this research presents the results of a survey tool utilizing both original and modified constructs from the Consolidated Framework for Implementation Research to assess key points of engagement barriers and potential points of intervention for stakeholders of EHRs in a large-scale healthcare organization (500-bed level II regional trauma center). Based on the extensive assessment, the paper presents recommendations for the utility of engagement process modeling and discusses how intervention opportunities can be used to mitigate engagement barriers.