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

An information technology governance (ITG) program has helped the National Institutes of Health (NIH) Clinical Center (CC) in the implementation of many systems and has guided the organization through the maturity of its project management methodology. The NIHCC Department of Clinical Research Informatics (DCRI) maintains an electronic health record (EHR) called the clinical research information system (CRIS) along with many clinical information systems (CIS) and research information systems, supporting approximately 3,200 users. ITG involves establishing processes to guide the review, selection, implementation, management, and setting of the IT strategy representing the business owners, stakeholders, and IT.¹ Research conducted by Levstek, Hovelja, and Pucihar² identified that different organizations may need different ITG structures, frameworks, and strategies. The path to achieving strong ITG is a continuous journey. This paper reviews the evolution of the NIHCC IT governance strategy.

This article discusses the emerging trends and challenges related to automatic clinical coding. We introduce an automatic coding system, which assigns short ICD-10 codes (restricted to the first three symbols, which define the category of the disease) based only on drugs prescribed to patients. We show that even with limited input data, the accuracy levels are comparable to those achieved by entry-level clinical coders as depicted by Seyed Nouraei et al.¹ We also examine the standard method for performance estimation and speculate that the actual accuracy of our coding system is even higher than estimated.

Objective: Thirty-day readmission rates are closely monitored in today's healthcare ecosystem to prevent higher-than-average rates in inpatient settings. Excess readmission rates result in decreased reimbursement for healthcare facilities. Additionally, feedback from patients about their hospital experience may indicate areas of improvement for healthcare facilities. This feedback is a national survey that collects data on patient experience through a standardized survey called Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). The objective of this study is to identify significant patterns between readmission rates and HCAHPS survey data through the application of association rules.

Materials and methods: Publically accessible HCAHPS survey data and 30-day readmission rates provided by the Centers for Medicare and Medicaid Services (CMS) were utilized for this study. Through the implementation of association rules using SAS Enterprise Miner, significant rules were identified in the data.

Results: Association rules were developed in SAS Enterprise Miner and produced three significant rules associated with high heart failure (HF) readmission as the right-hand rule. The rules indicated that a high pneumonia readmission, a low cleanliness star rating, and a low medication communication star rating were associated with a high readmission rate for heart failure.

Conclusions: The rules provided strong associations between HCAHPS star ratings and determining a high readmission rate for HF. It was interesting to find that pneumonia readmissions exist as well with a high HF readmission. Hospitals should work on improving their star ratings for the HCAHPS domains identified and work on lowering pneumonia readmissions to lower their HF readmissions.

We conducted a national survey of Health Information Exchanges (HIEs), targeting both not-for profit geographic and enterprise or federated exchanges. The aim of this study is to identify current best practices when exchanging information between Veterans Affairs (VA) systems and non-VA health systems. We identified and classified current interactions between HIEs and VA systems given recent passage of the MISSION Act. The MISSION Act allows veterans to seek care outside the VA health system, necessitating the need to reconcile care planning between VA systems and private care settings. We identified several differing best practices concerning information exchange between VA health systems and HIEs and assessed capabilities for HIEs to appropriately identify eligible VA participants within extant databases.

Background: The availability of accurate, reliable, and timely clinical data is crucial for clinicians, researchers, and policymakers so that they can respond effectively to emerging public health threats. This was typified by the recent SARS-CoV-2 pandemic and the critical knowledge and data gaps associated with novel Coronavirus 2019 disease (COVID-19).We sought to create an adaptive, living data mart containing detailed clinical, epidemiologic, and outcome data from COVID-19 patients in our healthcare system. If successful, the approach could then be used for any future outbreak or disease.

Methods: From 3/13/2020 onward, demographics, comorbidities, outpatient medications, along with 75 laboratory, 2 imaging, 19 therapeutic, and 4 outcome-related parameters, were manually extracted from the electronic medical record (EMR) of SARS-CoV-2 positive patients. These parameters were entered on a registry featuring calculation, graphing tools, pivot tables, and a macro programming language. Initially, two internal medicine residents populated the database, then professional data abstractors populated the registry. Clinical parameters were developed with input from infectious diseases and critical care physicians and using a modified COVID-19 worksheet from the U.S. Centers for Disease Control and Prevention (CDC). Registry contents were migrated to a browser-based, metadata-driven electronic data capture software platform. Eventually, we developed queries and used various business intelligence (BI) tools which enabled us to semi-automate data ingestion of 147 clinical and outcome parameters from the EMR, via a large U.S. hospital-based, service-level, all-payer database. Statistics were performed in R and Minitab.

Results: From March 13, 2020 to May 17, 2021, 549,691 SARS-CoV-2 test results on 236,144 distinct patients, along with location, admission status, and other epidemiologic details are stored on the cloud-based BI platform. From March 2020 until May 2021, extraction of clinical-epidemiologic parameter had to be performed manually. Of those, 543 have had >/=75 parameters fully entered in the registry. Ten clinical characteristics were significantly associated with the need for hospital admission. Only one characteristic was associated with a need for ICU admission. Use of supplemental oxygen, vasopressors and outpatient statin were associated with increased mortality.Initially, 0.5hrs -1.5 hours per patient chart (approximately 450-575 person hours) were required to manually extract the parameters and populate the registry. As of May 17, 2021, semi-automated data ingestion from the U.S. hospital all-payer database, employing user-defined queries, was implemented. That process can ingest and populate the registry with 147 clinical, epidemiologic, and outcome parameters at a rate of 2 hours per 100 patient charts.

Conclusion: A living COVID-19 registry repre

In the World Health Congress in May 2019, ICD-11 was approved, This study aims to analyze the classification system of the 11th revision of the International Classification of Disease mapping with the ICD-10-KM-7th (ICD-10 Korean Modification 7th) to identify the characteristics of ICD-11 so that it can be flexibly linked to KCD-7 when introduced in Korea. The mapping was conducted based on the ICD-11 frozen version (April 2019). Most of the ICD-11 codes were mapped to a single ICD-10 or KCD-7 code. However, for the diabetes code, more than 80 percent of KCD-7 codes needed to be mapped to one or two post-coordination codes, along with one stem code in ICD-11. ICD-11 is a great classification that has an excellent taxonomy system to express detailed information. For the codes that have been changed or removed, a proper guideline might also be useful for users to understand the changes made in KCD-7 or ICD-10 code.

The ultimate goal for most health information management (HIM) program graduates is successful passage of the Registered Health Information Administrator (RHIA) exam. As educators, it is our goal to successfully prepare our students for this endeavor. Past studies in this area have resulted in many recommendations for further research. The current study builds on this past research to provide further insight into predictors of graduate success on the RHIA exam. This study assessed variables impacting student success on the RHIA exam using data from students from one HIM academic program who graduated between 2014 and 2019. Variables included in the study were the dependent variable of the first-time RHIA exam score/pass or fail, and the independent variables of student mock exam score, time between graduation and examination, student self-report of English as a second language (ESL) status, introductory HIM course grade, introductory coding and intermediate coding course grades, overall GPA, and major GPA. The study found that introductory HIM course grade, mock exam score, and time between graduation and examination were significant predictive factors in HIM graduate success on the RHIA exam. The study also revealed some interesting findings regarding student ESL status and exam success that merit further study. The results of this study provide educators with further insight into predictors of student success on the RHIA exam, as well as provide information that can be used by educators to aid in student RHIA exam success.

Insomnia and sleep apnea are associated with a variety of comorbid conditions and carry a symptom burden to patients. As the prevalence of insomnia and sleep apnea continue to rise, it is imperative that appropriate tools are implemented to accurately capture their prevalence in acute care settings. A retrospective chart review was conducted on 3,074 inpatient charts in Calgary, Alberta. The estimated prevalence of insomnia was 10.36 percent, and sleep apnea was 6.56 percent in inpatient visits between January 1, 2015, and June 30, 2015. The sensitivity of insomnia and sleep apnea were low, and the specificity was high when comparing the chart review to the ICD-10. As both insomnia and sleep apnea were associated with various comorbid conditions, it would be imperative that alternate methods are identified to capture and code them. This would enable clinicians to better identify and treat them, and ultimately improve patient care.

As the healthcare industry continues to push for better patient care at a lower cost, it is essential that healthcare professionals develop skills in collaboration and teamwork. These skills should be practiced by students in post-secondary institutions, as they also learn to master content and technical skills. Participation of health information management (HIM) students in such activities helps to promote the value of HIM on the healthcare team. This study provides an example of integrating undergraduate HIM students into an interprofessional capstone course with other healthcare majors, summarizing student perceptions of learning activities in applying interprofessional education competencies. The results indicate a positive student perception of activities supporting application of at least three of the four competencies. Comments also highlight the struggles students have with group work, particularly in virtual teams. Sharing these activities and perceptions may contribute to further integration of undergraduate HIM students in interprofessional learning opportunities.