Information Needs of Homecare Nurses during Admission and Care Planning DESCRIPTION: There are 11 million home care admissions per year. The demand for home health care is growing due to an aging population, living longer, with multiple chronic diseases and preferring to remain in their homes instead of receiving facility-based care. Home care agencies face the challenge of assuring timely and accurate data collection during the homecare admission process. The re-hospitalization rate within 14 days of hospital discharge is 26% and enhanced care planning and allocation of clinical care services based on better information may reduce this problem. However, very little is known about the homecare admission and care planning processes. Objectives: The proposed research is innovative because it will fill a knowledge gap by using a strong research design that integrates cognitive analyses with HIT evaluation analyses to examine the information requirements, decision-making needs, and workflow/efficiency in the homecare admission and care planning processes and to examine if/how health information technology (HIT) efficiently supports them. From these analyses, design and implementation recommendations will be developed, reviewed and disseminated. Methods: We will use a mixed methods data collection and analysis approach to analyze and model the information requirements, decision-making, and workflow of homecare nurses admitting patients at 3 agencies and characterize if/how HIT systems support their information requirements, decision-making, and workflow. The approach includes: observation of admissions; structured knowledge elicitation (e.g., focus groups, conversations, cognitive walkthroughs, and check-back discussion); HIT thematic, cognitive, and usability analyses to produce models as intermediary products; and analysis of electronic health record (EHR) log data related to documentation timeliness and usage from the EHR. We will use a mixed methods approach to generate recommendations about the challenges and facilitators to the admission process and the nurses' information and decision-making needs. Expected Outcomes of the study include: (1) information requirements for homecare admitting nurses; (2) models of workflow and decision-making in the homecare admission process; (3) dissemination of HIT design recommendations that efficiently fulfill information needs and support clinical decision making during the important homecare admission process to AHRQ, EHR developers, and other stakeholders. This study will inform improvements in real world homecare HIT systems that may ultimately reduce unplanned hospitalization readmission events. Study findings will also inform future HIT interventions related to transitions in care to and from homecare, such as Meaningful Use and clinical information exchange standards.
Annually 11 million older patients are admitted to home care agencies. Some of the high hospital readmission rates (i.e., 26% of patients in the first 14 days of the home care episode) can be prevented by improving clinical decision making at the point-of-care to provide more timely and appropriately targeted allocation of clinical resources. By investigating decision making during the clinical admission process and whether health information technology provides support or hindrance, this study will inform electronic health record design and future health information technology interventions related to transitions in care to and from home care.
| Sockolow, Paulina S; Yang, Yushi; Bass, Ellen J et al. (2017) Data Visualization of Home Care Admission Nurses' Decision-Making. AMIA Annu Symp Proc 2017:1597-1606 |
