Dataset Information

Selecting long-term care facilities with high use of acute hospitalisations: issues and options.

ABSTRACT:

Background

This paper considers approaches to the question "Which long-term care facilities have residents with high use of acute hospitalisations?" It compares four methods of identifying long-term care facilities with high use of acute hospitalisations by demonstrating four selection methods, identifies key factors to be resolved when deciding which methods to employ, and discusses their appropriateness for different research questions.

Methods

OPAL was a census-type survey of aged care facilities and residents in Auckland, New Zealand, in 2008. It collected information about facility management and resident demographics, needs and care. Survey records (149 aged care facilities, 6271 residents) were linked to hospital and mortality records routinely assembled by health authorities. The main ranking endpoint was acute hospitalisations for diagnoses that were classified as potentially avoidable. Facilities were ranked using 1) simple event counts per person, 2) event rates per year of resident follow-up, 3) statistical model of rates using four predictors, and 4) change in ranks between methods 2) and 3). A generalized mixed model was used for Method 3 to handle the clustered nature of the data.

Results

3048 potentially avoidable hospitalisations were observed during 22 months' follow-up. The same "top ten" facilities were selected by Methods 1 and 2. The statistical model (Method 3), predicting rates from resident and facility characteristics, ranked facilities differently than these two simple methods. The change-in-ranks method identified a very different set of "top ten" facilities. All methods showed a continuum of use, with no clear distinction between facilities with higher use.

Conclusion

Choice of selection method should depend upon the purpose of selection. To monitor performance during a period of change, a recent simple rate, count per resident, or even count per bed, may suffice. To find high-use facilities regardless of resident needs, recent history of admissions is highly predictive. To target a few high-use facilities that have high rates after considering facility and resident characteristics, model residuals or a large increase in rank may be preferable.

SUBMITTER: Broad JB

PROVIDER: S-EPMC4118262 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Publications

Selecting long-term care facilities with high use of acute hospitalisations: issues and options.

Broad Joanna B JB Ashton Toni T Lumley Thomas T Boyd Michal M Kerse Ngaire N Connolly Martin J MJ

BMC medical research methodology 20140722

<h4>Background</h4>This paper considers approaches to the question "Which long-term care facilities have residents with high use of acute hospitalisations?" It compares four methods of identifying long-term care facilities with high use of acute hospitalisations by demonstrating four selection methods, identifies key factors to be resolved when deciding which methods to employ, and discusses their appropriateness for different research questions.<h4>Methods</h4>OPAL was a census-type survey of a ...[more]

PMID: 25052433

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Project description:BackgroundShared decision-making, a communicative process to reach decisions based on informed preferences, evidence, and co-created goals, improves care satisfaction and patients' quality of life. However, shared decision-making has not been widely implemented in long-term care facilities, and few studies have examined how to promote the shared decision-making practice. This study aimed to identify the influencing factors of shared decision-making based on the Person-centered Practice Framework in long-term care facilities.MethodsA total of 300 staff (nursing staff, social workers, and personal care workers) in 13 Korean long-term care facilities participated in this study. Data from 280 respondents were finally analyzed, excluding respondents with missing values. Data were collected using structured questionnaires that included items on shared decision-making, personal factors (e.g., knowledge about dementia, person-centered care education, person-centered attitude, communication behavior, and job tenure), and care environment factors (e.g., person-centered climate, staffing level, effective staff relationships, supportive supervisors, and power-sharing). Multilevel linear regression analyses were performed using Mplus Version 8.8.ResultsThe mean shared decision-making score was 35.78 (range 8-45). Staff with experience of person-centered care education (β = 0.198, p = 0.034), a higher person-centered attitude score (β = 0.201, p = 0.007), and a higher communication behavior score (β = 0.242, p < 0.001) were more likely to report a higher shared decision-making score. In addition, staff who viewed their care environment as more person-centered were more likely to report a higher shared decision-making score (β = 0.416, p < 0.001).ConclusionsThis study highlights that personal (e.g., person-centered care education, person-centered attitude, and communication behavior) and care environment (e.g., person-centered climate) factors could influence shared decision-making for long-term care residents. These findings could be foundational evidence for facilitating shared decision-making practice in long-term care settings.

Project description:Long-term care (LTC) facilities are an important part of the health care industry, providing care to the fastest-growing group of the population. However, the adoption of electronic health records (EHRs) in LTC facilities lags behind other areas of the health care industry. One of the reasons for the lack of widespread adoption in the United States is that LTC facilities are not eligible for incentives under the Meaningful Use program. Implementation of an EHR system in an LTC facility can potentially enhance the quality of care, provided it is appropriately implemented, used, and maintained. Unfortunately, the lag in adoption of the EHR in LTC creates a paucity of literature on the benefits of EHR implementation in LTC facilities.The objective of this systematic review was to identify the potential benefits of implementing an EHR system in LTC facilities. The study also aims to identify the common conditions and EHR features that received favorable remarks from providers and the discrepancies that needed improvement to build up momentum across LTC settings in adopting this technology.The authors conducted a systematic search of PubMed, Cumulative Index of Nursing and Allied Health (CINAHL), and MEDLINE databases. Papers were analyzed by multiple referees to filter out studies not germane to our research objective. A final sample of 28 papers was selected to be included in the systematic review.Results of this systematic review conclude that EHRs show significant improvement in the management of documentation in LTC facilities and enhanced quality outcomes. Approximately 43% (12/28) of the papers reported a mixed impact of EHRs on the management of documentation, and 33% (9/28) of papers reported positive quality outcomes using EHRs. Surprisingly, very few papers demonstrated an impact on patient satisfaction, physician satisfaction, the length of stay, and productivity using EHRs.Overall, implementation of EHRs has been found to be effective in the few LTC facilities that have implemented them. Implementation of EHRs in LTC facilities caused improved management of clinical documentation that enabled better decision making.

Dataset Information

Selecting long-term care facilities with high use of acute hospitalisations: issues and options.

Background

Methods

Results

Conclusion

Publications

Selecting long-term care facilities with high use of acute hospitalisations: issues and options.

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