The need for Long-Term Care (LTC) arises in the elderly population, especially those reaching age 65 each year. This elderly population will grow tremendously in the United States over the next decade, resulting in short-and long-term challenges of matching resource capacity with uncertain demand for hospitals and other healthcare providers. This paper describes research involving the development of a simulation model of patient flow in order to understand the relationship between capacity and demand, and to investigate the impacts on performance measures such as average wait times for LTC patients. We propose an aggregate capacity model to consider patient flow among various types of care providers by integrating hospitals, nursing homes, assisted living facilities, and home health care. Using the data including patient demographics and service provider information, we forecast patient demand for LTC. The computational results demonstrate the efficacy of a simulation-based optimisation solution approach for capacity planning.

Success in testing research outcomes requires identification of effective recruitment strategies in the targeted population. In this paper, we present the protocol for our NIH-funded study as well as success rates for the various recruitment strategies employed. This longitudinal observational study is: developing a phenotyping algorithm for asthma in older adults, exploring the effects of the asthma phenotype and of volatile organic compounds on asthma control, and developing a predictive model of asthma quality of life. A sub-aim is to characterize barriers to successful medication management in older adults with asthma. Individuals are eligible if they are ≥60 years, have a positive response to at least 1 of 6 asthma screening questions, non-smokers, and demonstrate bronchodilator reversibility or a positive bronchial challenge test with methacholine. Exclusion criteria are smokers who quit <5 years ago or with a >20 pack year smoking history, and those having other chronic pulmonary diseases. Participants (N=190) complete baseline pulmonary function testing, questionnaires, sputum induction, skin prick testing, and have blood drawn for Vitamin D and Immunoglobulin E. Home environmental assessments are completed including 24-hour particulate and volatile organic compound measurements. At 9-months post-baseline, home spirometry, medication assessment, and assessment of asthma quality of life and asthma control are assessed. At 18-months post-baseline, home spirometry, completion of baseline questionnaires, and a home environmental assessment are completed. We have employed multiple recruitment efforts including referrals from clinical offices, no-cost media events, flyers, and ads. The most successful efforts have been referrals from clinical offices and media events.

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Background: The diagnosis of asthma is not always straightforward and can be even more challenging in older adults. Asthma is ideally confirmed by demonstration of variable expiratory airflow limitation. However, many patients with asthma do not demonstrate airflow obstruction nor show bronchodilator reversibility. We aimed to investigate predictors for a positive bronchial challenge test with methacholine in older adults being evaluated for asthma. Methods: This is a diagnostic accuracy study with a cross-sectional design. Participants ≥ 60 years with suspected asthma and a negative postbronchodilator response on spirometry were included. All participants underwent a methacholine challenge test (MCT). We assessed the value of standard asthma screening questions and additional clinical questions to predict the MCT results. A multivariable logistic regression model was developed to assess the variables independently impacting the odds of a positive MCT result. Results: Our study included 71 participants. The majority were female (n=52, 73.2%) and the average age was 67.0 years. Those with a positive MCT (n=55, 77.5%) were more likely to have wheezing or coughing due to allergens (n=51, 92.7% vs. n=12, 75.0%; P=0.004) and difficulty walking several blocks (n=14, 25.5% vs. n=1, 6.3%, P=0.009). After adjustment, having wheezing or coughing due to allergens (OR=4.2, 95% CI 1.7–7.8, P=0.012) remained the only significant independent predictor of a positive MCT. Conclusions: In older adults with suspected asthma, questioning about wheezing or coughing due to allergens provides a modest independent value to predict a MCT result in those who previously had a negative postbronchodilator response on spirometry.