Developing a Predictive Tool for Hospital Discharge Disposition of Patients Poststroke with 30-Day Readmission Validation

After short-term, acute-care hospitalization for stroke, patients may be discharged home or other facilities for continued medical or rehabilitative management. The site of postacute care affects overall mortality and functional outcomes. Determining discharge disposition is a complex decision by the healthcare team. Early prediction of discharge destination can optimize poststroke care and improve outcomes. Previous attempts to predict discharge disposition outcome after stroke have limited clinical validations. In this study, readmission status was used as a measure of the clinical significance and effectiveness of a discharge disposition prediction. Low readmission rates indicate proper and thorough care with appropriate discharge disposition. We used Medicare beneficiary data taken from a subset of base claims in the years of 2014 and 2015 in our analyses. A predictive tool was created to determine discharge disposition based on risk scores derived from the coefficients of multivariable logistic regression related to an adjusted odds ratio. The top five risk scores were admission from a skilled nursing facility, acute heart attack, intracerebral hemorrhage, admission from “other” source, and an age of 75 or older. Validation of the predictive tool was accomplished using the readmission rates. A 75% probability for facility discharge corresponded with a risk score of greater than 9. The prediction was then compared to actual discharge disposition. Each cohort was further analyzed to determine how many readmissions occurred in each group. Of the actual home discharges, 95.7% were predicted to be there. However, only 47.8% of predictions for home discharge were actually discharged home. Predicted discharge to facility had 15.9% match to the actual facility discharge. The scenario of actual discharge home and predicted discharge to facility showed that 186 patients were readmitted. Following the algorithm in this scenario would have recommended continued medical management of these patients, potentially preventing these readmissions.

Hearing Loss and Help-Seeking Behavior

Hearing Loss (HL) is common among older adults and is associated with poor health care quality outcomes include 30-day readmissions, length of stay, poorer satisfaction, and increased medical expenditures. These associations may manifest in changes in help-seeking behaviour. In the 2015 Current Medicare Beneficiary Study (MCBS) (n=10848; weighted sample=46.3 million), participants reported whether they knowingly had avoided seeking care in the past year and self-reported HL was measured as degree of trouble (none, a little, or a lot) hearing when using a hearing aid if applicable. In a model adjusted for demographic, socioeconomic, and health factors, those with a little trouble (OR= 1.612; 95% CI= 1.334-1.947; P<0.001) and a lot of trouble hearing (OR= 2.011; 95% CI= 1.443-2.801; P<0.001) had 61.2% and 101.1% higher odds of avoiding health care over the past year relative to participants with no trouble hearing. Future work should examine whether hearing care modifies this association.

Community Cancer Rates in Massachusetts, New Hampshire, and Rhode Island: Findings From Healthy Aging Data Reports

Cancer is one major health condition that affect people’s later life quality, which could be intervened from the community level. This study compares rates of lung cancer, colon cancer, breast cancer (in women), and prostate cancer (in men) among adults 65+ in 3 New England states (MA, NH, and RI). Data were from the Healthy Aging Data Report (see www.healthyagingdatareports.org), which reported on 150+ health indicators at the local community and state level. Data sources were the Current Medicare Beneficiary Summary File (years) and the American Community Survey (years). Small area estimation techniques were used to calculate age-sex adjusted community rates. Average state rates of cancers (range) are: Lung cancer MA 2.1 (1.0 – 4.4) NH 1.6 (0.9 – 2.9) RI 2.1 (1.3 – 2.9); Colon cancer MA 2.9 (1.8 – 4.1) NH 2.4 (1.8 – 3.7) RI 3.2 (1.6 – 4.5); Breast cancer MA 10.9 (5.3 – 16.4) NH 9.8 (5.4 – 14.8) RI 10.7 (7.2 – 13.9); Prostate cancer MA 13.8 (7.4 – 24.0) NH 11.5 (5.9 – 17.3) RI 13.8 (9.5 – 17.7). NH has the lowest rates on all four types of cancer; MA and NH were similar regarding average rates, but MA communities had the widest disparities for lung, breast and prostate cancer. Findings suggest within and between state variations in cancer rates. Policies and programs may target geographic areas/communities with high rates of cancers, examine environmental effects on cancer rates and develop strategies in reducing cancer rates.

Evaluating Medicare Performance: Perceptions of Performance Pre- and Post- ACA

Medicare is a national single-payer system that provides health coverage for the elderly, disabled, and terminally ill in the United States. Rising enrollment, costs, and decreases in financing options may affect the way Medicare performs. This study aimed to investigate participants’ perceptions of Medicare performance before and after the Affordable Care Act. A 3-part questionnaire was created and validated for use in this study. Respondents affiliated with several social work agencies were invited via email to participate in this study. 287 out of 519 invited questionnaires were used in data analyses. 27.5% of respondents reported being currently enrolled in Medicare, while 33.2% reported lifetime enrollment. Overall, retired/disabled, elderly and low-income participants reported currently or ever using Medicare. One’s perception of Medicare performance was determined by their status as a Medicare beneficiary. Medicare service efficacy was rated more positively over-time by current and life-time enrollees; additionally, Medicare performance was determined to be better in 2013 than in 2009. Ultimately, this study showed that health service and financial fairness factors are indicative of Medicare performance. Additional research should explore possible implications for the healthcare field as well as formulate a broad range of possible management and/or improvement strategies. Lastly, differences in performance across years can inform decision-makers and bolster the fundamental foundation of health policies at the state and national level.