Aligning the American Health Information Management Association Entry-level Curricula Competencies and Career Map With Industry Job Postings: Cross-sectional Study.

BACKGROUND: The field of health information management (HIM) focuses on the protection and management of health information from a variety of sources. The American Health Information Management Association (AHIMA) Council for Excellence in Education (CEE) determines the needed skills and competencies for this field. AHIMA's HIM curricula competencies are divided into several domains among the associate, undergraduate, and graduate levels. Moreover, AHIMA's career map displays career paths for HIM professionals. What is not known is whether these competencies and the career map align with industry demands. OBJECTIVE: The primary aim of this study is to analyze HIM job postings on a US national job recruiting website to determine whether the job postings align with recognized HIM domains, while the secondary aim is to evaluate the AHIMA career map to determine whether it aligns with the job postings. METHODS: A national job recruitment website was mined electronically (web scraping) using the search term "health information management." This cross-sectional inquiry evaluated job advertisements during a 2-week period in 2021. After the exclusion criteria, 691 job postings were analyzed. Data were evaluated with descriptive statistics and natural language processing (NLP). Soft cosine measures (SCM) were used to determine correlations between job postings and the AHIMA career map, curricular competencies, and curricular considerations. ANOVA was used to determine statistical significance. RESULTS: Of all the job postings, 29% (140/691) were in the Southeast, followed by the Midwest (140/691, 20%), West (131/691,19%), Northeast (94/691, 14%), and Southwest (73/691, 11%). The educational levels requested were evenly distributed between high school diploma (219/691, 31.7%), associate degree (269/691, 38.6%), or bachelor's degree (225/691, 32.5%). A master's degree was requested in only 8% (52/691) of the postings, with 72% (42/58) preferring one and 28% (16/58) requiring one. A Registered Health Information Technologist (RHIT) credential was the most commonly requested (207/691, 29.9%) in job postings, followed by Registered Health Information Administrator (RHIA; 180/691, 26%) credential. SCM scores were significantly higher in the informatics category compared to the coding and revenue cycle (P=.006) and data analytics categories (P<.001) but not significantly different from the information governance category (P=.85). The coding and revenue cycle category had a significantly higher SCM score compared to the data analytics category (P<.001). Additionally, the information governance category was significantly higher than the data analytics category (P<.001). SCM scores were significantly different between each competency category, except there were no differences in the average SCM score between the information protection and revenue cycle management categories (P=.96) and the information protection and data structure, content, and information governance categories (P=.31). CONCLUSIONS: Industry job postings primarily sought degrees, with a master's degree a distant fourth. NLP analysis of job postings suggested that the correlation between the informatics category and job postings was higher than that of the coding, revenue cycle, and data analytics categories.

Assessing the Prevalence of Ahima-Identified Health Informatics and Information Management Careers and Related Skills: A Cross-Sectional Study.

This study's objective was to identify the prevalence of the American Health Information Management Association (AHIMA) career map jobs and determine which job categories, degrees, and skills are associated with higher pay. We extracted data from SimplyHired, a major employment website, from December 2018 to December 2019. We retrieved 12,688 career posts. We found differences in average salary by career category (p-value 0.00). Most jobs were in coding and revenue cycle (CRC) and information governance (IG) categories. The highest average salaries were in data analytics (DA) and informatics (IN). Each career category had a unique set of skills associated with the highest paying jobs. Eighty-two percent of CRC, 67 percent of IG, 65 percent of IN, and 83 percent of DA jobs listed in the AHIMA career map were present in the extracted dataset. These results can help employees, academics, and industry leaders understand the health informatics and information management (HIM) workforce landscape.

Increases in multimorbidity with weight class in the United States.

Little is known regarding how multimorbidity combinations associated with obesity change with increase in body weight. This study employed data from the national Cerner HealthFacts Data Warehouse to identify changes in multimorbidity patterns by weight class using network analysis. Networks were generated for 154 528 middle-aged patients in the following categories: normal weight, overweight, and classes 1, 2, and 3 obesity. The results show significant differences (P-value<0.05) in prevalence by weight class for all but three of 82 diseases considered. The percentage of patients with multimorbidity (excluding obesity) increases from in 55.1% in patients with normal weight, to 57.88% with overweight, 70.39% with Class 1 obesity, 73.99% with Class 2 obesity, and 71.68% in Class 3 obesity, increasing most substantially with the progression from overweight to class 1 obesity. Most prevalent disease clusters expand from only hypertension and dorsalgia in normal weight, to add joint disorders in overweight, lipidemias in class 1 obesity, diabetes in class 2 obesity, and sleep disorders and chronic kidney disease in class 3 obesity. Recognition of multimorbidity patterns associated with weight increase is essential for true precision care of obesity-associated chronic conditions and can help clinicians identify and address preclinical disease before additional complications arise.

Identifying obesity-related multimorbidity combinations in the United States.

Interest in understanding the effects of multimorbidity on outcomes has increased in recent years. This paper presents the most common obesity-related groupings of multimorbidity in the United States. Using Cerner HealthFacts data, we applied the frequent pattern growth algorithm to identify prevalent multimorbidity groupings of 3 or more diseases (one being obesity) by race using a dataset of 574 172 patients with obesity from all over the United States. We set the minimum prevalence to 10% and identified groupings of ICD10-CM diagnoses that occur in our dataset at or above the minimum prevalence level. We provide binomial proportion confidence interval estimates to demonstrate the validity of the proportions. We performed g-test for independence to validate differences in prevalence by race. We found 18 multimorbidity combinations with prevalence higher than or equal to 10%. Our results indicate that there are multiple common multimorbidities groupings for patients with obesity. Each multimorbidity combination is composed of diseases from the following clinical categories: endocrine, nutritional and metabolic diseases; diseases of the circulatory system; diseases of the digestive system; diseases of the nervous system; and diseases of the musculoskeletal system and connective tissue. For each multimorbidity pattern, the prevalence was found to be significantly different by race according to the g-test with P-value < .001. Most frequent patterns include essential hypertension or disorder of lipid metabolism. This study identifies common groupings of multimorbidity. We believe our data can be useful for those developing integrated care plans, particularly for those serving diverse communities.

A Survey-based Study of Pharmacist Acceptance and Resistance to Health Information Technology.

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.