Improved efficiency of coding systems with health information technology

Trends in cancer and heart failure related mortality in adult US population: A CDC WONDER database analysis from 1999 to 2020

BACKGROUND

With the advent of novel chemotherapy, survival of patients with cancer has improved. However, people with cancer have an increased risk of heart failure (HF). Conversely, HF-related mortality may undermine survival among people with cancer. We aim to analyze the trends of mortality in people with HF and cancer in the adult US population.

METHODS

We conducted an examination of death certificates sourced from the CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) database, from the years 1999 to 2020. Mortality in adults with HF and cancer was assessed. Age-adjusted mortality rates (AAMRs) per 100,000 persons and annual percent change were reported.

RESULTS

Between 1999 and 2020, 621,783 deaths occurred from HF in people with cancer. The AAMR declined from 16.4 in 1999 to 11.9 in 2017, after which an increase to 14.5 was observed in 2020. Men had consistently higher overall AAMR as compared to women (men = 18.1 vs women = 9.9). Similar AAMR was observed between non-Hispanic (NH) Blacks/African Americans (13.9) and NH Whites (13.3), with lower in American Indian/Alaska Native (9.6) and Hispanics (7.4). Asian/Pacific Islanders reported the lowest AAMR (5.7). The Midwestern region reported the highest AAMR (14.8). We observed the highest AAMR amongst the older population (61.4).

CONCLUSION

The mortality rates of people with HF and cancer are increasing in the adult U.S.

POPULATION

This underscores the need for increased screening, aggressive management, and subsequent surveillance of people at risk or with manifested HF in people with cancer.

The electronic health record: does it enhance or distract from patient safety?

PURPOSE OF REVIEW

The electronic health record (EHR) is an invaluable tool that may be used to improve patient safety. With a variety of different features, such as clinical decision support and computerized physician order entry, it has enabled improvement of patient care throughout medicine. EHR allows for built-in reminders for such items as antibiotic dosing and venous thromboembolism prophylaxis.

RECENT FINDINGS

In anesthesiology, EHR often improves patient safety by eliminating the need for reliance on manual documentation, by facilitating information transfer and incorporating predictive models for such items as postoperative nausea and vomiting. The use of EHR has been shown to improve patient safety in specific metrics such as using checklists or information transfer amongst clinicians; however, limited data supports that it reduces morbidity and mortality.

SUMMARY

There are numerous potential pitfalls associated with EHR use to improve patient safety, as well as great potential for future improvement.

Analysis of Publications on Health Information Management Using the Science Mapping Method: A Holistic Perspective

OBJECTIVE

In the age of digital transformation, there is a need for a sustainable information management vision in health. Understanding the accumulation of health information management (HIM) knowledge from the past to the present and building a new vision to meet this need reveals the importance of understanding the available scientific knowledge. With this research, it is aimed to examine the scientific documents of the last 40 years of HIM literature with a holistic approach using science mapping techniques and to guide future research.

METHODS

This study used a bibliometric analysis method for science mapping. Co-citation and co-occurrence document analyses were performed on 630 academic publications selected from the Web of Science core collection (WoSCC) database using the keyword "Health Information Management" and inclusion criteria. The analyses were performed using the R-based software Bibliometrix (Version 4.0; K-Synth Srl), Python (Version 3.12.1; The Python Software Foundation), and Microsoft® Excel® 2016.

RESULTS

Co-occurrence analyses revealed the themes of personal health records, clinical coding and data quality, and health information management. The HIM theme consisted of five subthemes: "electronic records", "medical informatics", "e-health and telemedicine", "health education and awareness", and "health information systems (HISs)". As a result of the co-citation analysis, the prominent themes were technology acceptance, standardized clinical coding, the success of HISs, types of electronic records, people with HIM, health informatics used by consumers, e-health, e-mobile health technologies, and countries' frameworks and standards for HISs.

CONCLUSIONS

This comprehensive bibliometric study shows that structured information can be helpful in understanding research trends in HIM. This study identified critical issues in HIM, identified meaningful themes, and explained the topic from a holistic perspective for all health system actors and stakeholders who want to work in the field of HIM.

Artificial Intelligence Models in Health Information Exchange: A Systematic Review of Clinical Implications

Electronic health record (EHR) systems collate patient data, and the integration and standardization of documents through Health Information Exchange (HIE) play a pivotal role in refining patient management. Although the clinical implications of AI in EHR systems have been extensively analyzed, its application in HIE as a crucial source of patient data is less explored. Addressing this gap, our systematic review delves into utilizing AI models in HIE, gauging their predictive prowess and potential limitations. Employing databases such as Scopus, CINAHL, Google Scholar, PubMed/Medline, and Web of Science and adhering to the PRISMA guidelines, we unearthed 1021 publications. Of these, 11 were shortlisted for the final analysis. A noticeable preference for machine learning models in prognosticating clinical results, notably in oncology and cardiac failures, was evident. The metrics displayed AUC values ranging between 61% and 99.91%. Sensitivity metrics spanned from 12% to 96.50%, specificity from 76.30% to 98.80%, positive predictive values varied from 83.70% to 94.10%, and negative predictive values between 94.10% and 99.10%. Despite variations in specific metrics, AI models drawing on HIE data unfailingly showcased commendable predictive proficiency in clinical verdicts, emphasizing the transformative potential of melding AI with HIE. However, variations in sensitivity highlight underlying challenges. As healthcare's path becomes more enmeshed with AI, a well-rounded, enlightened approach is pivotal to guarantee the delivery of trustworthy and effective AI-augmented healthcare solutions.

Current Trends in Autologous Breast Reconstruction and the Implications of Impending Changes to Insurance Reimbursement

Introduction In 2019, the Centers for Medicare & Medicaid Services (CMS) combined all autologous breast flap procedures under one billing code, effective from December 31, 2024. This change will result in equal insurance reimbursement rates for popular flap options, such as transverse rectus abdominis muscle (TRAM) and deep inferior epigastric perforator (DIEP) flaps, which were previously billed separately using S-codes based on complexity. Methods This study aimed to analyze insurance code changes for autologous breast reconstruction flap procedures. Data were collected from the American Society of Plastic Surgeons' annual plastic surgery statistics reports, including specific insurance codes and case volumes from 2007 to 2020. A comprehensive analysis was conducted to assess recent trends in flap utilization rates, documenting any modifications or additions to the existing codes and their implementation years. Results The study analyzed billing codes and case volumes for autologous breast reconstruction procedures, with a focus on the DIEP flap and other alternatives. Non-autologous breast reconstruction procedures showed consistently higher case volumes compared to autologous procedures from 2007 to 2020. Notably, the popularity of the DIEP flap surpassed that of other flap options after 2011. Conclusion The removal of S-codes for autologous breast reconstruction by CMS and the subsequent potential decrease in insurance coverage for the DIEP flap may lead to a decrease in its utilization and a shift toward more invasive options, like the TRAM flap. This change could result in financial burdens for patients and widen socioeconomic disparities in breast reconstruction, limiting access to preferred reconstructive methods and impacting patient autonomy and overall well-being.