How Can Home Care Patients and Their Caregivers Better Manage Fall Risks by Leveraging Information Technology?

Objectives: From the perspectives of home care patients and caregivers, this study aimed to (a) identify the challenges for better fall-risk management during home care episodes and (b) explore the opportunities for them to leverage health information technology (IT) solutions to improve fall-risk management during home care episodes. Methods: Twelve in-depth semistructured interviews with the patients and caregivers were conducted within a descriptive single case study design in 1 home health agency (HHA) in the mid-Atlantic region of the United States. Results: Patients and caregivers faced challenges to manage fall risks such as unmanaged expectations, deteriorating cognitive abilities, and poor care coordination between the HHA and physician practices. Opportunities to leverage health IT solutions included patient portals, telehealth, and medication reminder apps on smartphones. Conclusion: Effectively leveraging health IT could further empower patients and caregivers to reduce fall risks by acquiring the necessary information and following clinical advice and recommendations. The HHAs could improve the quality of care by adopting IT solutions that show more promise of improving the experiences of patients and caregivers in fall-risk management

Transition to the new race/ethnicity data collection standards in the Department of Veterans Affairs

BACKGROUND: Patient race in the Department of Veterans Affairs (VA) information system was previously recorded based on an administrative or clinical employee's observation. Since 2003, the VA started to collect self-reported race in compliance with a new federal guideline. We investigated the implications of this transition for using race/ethnicity data in multi-year trends in the VA and in other healthcare data systems that make the transition. METHODS: All unique users of VA healthcare services with self-reported race/ethnicity data in 2004 were compared with their prior observer-recorded race/ethnicity data from 1997 – 2002 (N = 988,277). RESULTS: In 2004, only about 39% of all VA healthcare users reported race/ethnicity values other than "unknown" or "declined." Females reported race/ethnicity at a lower rate than males (27% vs. 40%; p < 0.001). Over 95% of observer-recorded data agreed with self-reported data. Compared with the patient self-reported data, the observer-recorded White and African American races were accurate for 98% (kappa = 0.89) and 94% (kappa = 0.93) individuals, respectively. Accuracy of observer-recorded races was much worse for other minority groups with kappa coefficients ranging between 0.38 for American Indian or Alaskan Natives and 0.79 for Hispanic Whites. When observer-recorded race/ethnicity values were reclassified into non-African American groups, they agreed with the self-reported data for 98% of all individuals (kappa = 0.93). CONCLUSION: For overall VA healthcare users, the agreement between observer-recorded and self-reported race/ethnicity was excellent and observer-recorded and self-reported data can be used together for multi-year trends without creating serious bias. However, this study also showed that observation was not a reliable method of race/ethnicity data collection for non-African American minorities and racial disparity might be underestimated if observer-recorded data are used due to systematic patterns of inaccurate race/ethnicity assignments