Optimizing Response Rates to Examine Health IT Maturity and Nurse Practitioner Care Environments in US Nursing Homes: Mixed Mode Survey Recruitment Protocol.

BACKGROUND: Survey-driven research is a reliable method for large-scale data collection. Investigators incorporating mixed-mode survey designs report benefits for survey research including greater engagement, improved survey access, and higher response rate. Mix-mode survey designs combine 2 or more modes for data collection including web, phone, face-to-face, and mail. Types of mixed-mode survey designs include simultaneous (ie, concurrent), sequential, delayed concurrent, and adaptive. This paper describes a research protocol using mixed-mode survey designs to explore health IT (HIT) maturity and care environments reported by administrators and nurse practitioners (NPs), respectively, in US nursing homes (NHs). OBJECTIVE: The aim of this study is to describe a research protocol using mixed-mode survey designs in research using 2 survey tools to explore HIT maturity and NP care environments in US NHs. METHODS: We are conducting a national survey of 1400 NH administrators and NPs. Two data sets (ie, Care Compare and IQVIA) were used to identify eligible facilities at random. The protocol incorporates 2 surveys to explore how HIT maturity (survey 1 collected by administrators) impacts care environments where NPs work (survey 2 collected by NPs). Higher HIT maturity collected by administrators indicates greater IT capabilities, use, and integration in resident care, clinical support, and administrative activities. The NP care environment survey measures relationships, independent practice, resource availability, and visibility. The research team conducted 3 iterative focus groups, including 14 clinicians (NP and NH experts) and recruiters from 2 national survey teams experienced with these populations to achieve consensus on which mixed-mode designs to use. During focus groups we identified the pros and cons of using mixed-mode designs in these settings. We determined that 2 mixed-mode designs with regular follow-up calls (Delayed Concurrent Mode and Sequential Mode) is effective for recruiting NH administrators while a concurrent mixed-mode design is best to recruit NPs. RESULTS: Participant recruitment for the project began in June 2023. As of April 22, 2024, a total of 98 HIT maturity surveys and 81 NP surveys have been returned. Recruitment of NH administrators and NPs is anticipated through July 2025. About 71% of the HIT maturity surveys have been submitted using the electronic link and 23% were submitted after a QR code was sent to the administrator. Approximately 95% of the NP surveys were returned with electronic survey links. CONCLUSIONS: Pros of mixed-mode designs for NH research identified by the team were that delayed concurrent, concurrent, and sequential mixed-mode methods of delivering surveys to potential participants save on recruitment time compared to single mode delivery methods. One disadvantage of single-mode strategies is decreased versatility and adaptability to different organizational capabilities (eg, access to email and firewalls), which could reduce response rates. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56170.

A Research Protocol: Mixed-Mode Designs to Optimize Engagement in Clinical Informatics Research.

To introduce a research protocol that utilizes mixed-mode methodology (i.e., delayed concurrent and sequential approaches) to optimize response rates of two surveys being administered to U.S. nursing homes (NHs). This protocol is being employed in a cross-sectional survey to assess for HIT maturity and nurse practitioners (NP) care environments. Survey recruitment from 3,000 NHs will be conducted from June 2023 to July 2025. Respondents included NH administrators evaluating facility-wide HIT and NPs in each NH rating their care environment.

The State of Nursing Home Information Technology Sophistication in Rural and Nonrural US Markets.

OBJECTIVE: To test for significant differences in information technology sophistication (ITS) in US nursing homes (NH) based on location. METHODS: We administered a primary survey January 2014 to July 2015 to NH in each US state. The survey was cross-sectional and examined 3 dimensions (IT capabilities, extent of IT use, degree of IT integration) among 3 domains (resident care, clinical support, administrative activities) of ITS. ITS was broken down by NH location. Mean responses were compared across 4 NH categories (Metropolitan, Micropolitan, Small Town, and Rural) for all 9 ITS dimensions and domains. Least square means and Tukey's method were used for multiple comparisons. PRINCIPAL FINDINGS: Methods yielded 815/1,799 surveys (45% response rate). In every health care domain (resident care, clinical support, and administrative activities) statistical differences in facility ITS occurred in larger (metropolitan or micropolitan) and smaller (small town or rural) populated areas. CONCLUSIONS: This study represents the most current national assessment of NH IT since 2004. Historically, NH IT has been used solely for administrative activities and much less for resident care and clinical support. However, results are encouraging as ITS in other domains appears to be greater than previously imagined.

A national report of nursing home information technology: year 1 results.

OBJECTIVE: To provide a report on year 1 results of a national study investigating nursing home information technology (IT) adoption, called IT sophistication. METHODS: A reliable and valid survey was used to measure IT sophistication. The target goal was 10% from each state in the United States, 1570 nursing homes. A random sample of homes from each state was recruited from Nursing Home Compare. RESULTS: The team reached 2627 nursing home administrators, among whom 1799 administrators agreed to participate and were sent a survey. A total of 815 surveys were completed (45.3% response rate), which was below the goal. Facilities in the participating sample have similar demographic characteristics (ownership, total population in a location, and bed size) to the remaining homes not participating. There are greater IT capabilities in resident care and administrative activities, less in clinical support. The extent of use of these capabilities appears to be highest in administrative activities and lowest in clinical support. IT in resident care appears to be the most integrated with internal and external stakeholders. IT capabilities appear to be greater than IT extent of use in all health domains, with the greatest difference in resident care. DISCUSSION: National evaluations of nursing home IT are rare. Measuring trends in IT adoption in a nationally representative sample provides meaningful analytics that could be more useful for policy makers and nursing home leaders in the future. CONCLUSION: Discovering national baseline assessments is a first step toward recognizing nursing home trends in IT adoption.