Factors Associated With Discharge Destination in Older Patients: Finnish Community Hospital Cohort Study.

OBJECTIVES: Primary care physician-led community hospitals provide basic hospital care for older people in Finland. Yet little is known of the outcomes of the care. We investigated factors associated with discharge destination after hospitalization in a community hospital and the role of active rehabilitation during the stay. DESIGN: Prospective observational study. SETTING AND PARTICIPANTS: Short-term community hospital stays of older adults (≥65 years) living in the Kuopio University Hospital district in central and eastern Finland. METHODS: Data on short-term (1-31 days) hospital stays from 51 community hospitals were collected with an electronic survey between January and June 2016. Physicians, secretaries, and rehabilitation staff from each community hospital completed the data collection form. Discharge destination was defined as home, residential care or death, and active rehabilitation as frequency of rehabilitation at least once a day. Analyses were conducted using the Bayesian approach and the BayesiaLab 9.1 tool. RESULTS: Data of 11,628 community hospital stays were analyzed. The patients' mean age was 81.6 years (SD 7.9), and 57.5% were women. A younger age (65-74 years), a high number of rehabilitation staff (>2 per 10 patients), and receiving rehabilitation at least once a day were associated with discharging patients to their own homes. Daily rehabilitation was associated with returning to home in all patient groups. CONCLUSIONS AND IMPLICATIONS: Older patients admitted to a community hospital for any reason may benefit from active rehabilitation. The role of community hospitals in the acute care and rehabilitation of older patients is important in aging societies.

Factors Associated with 5-Year Costs of Care among a Cohort of Alcohol Use Disorder Patients: A Bayesian Network Model.

OBJECTIVES: To examine the direct effects of risk factors associated with the 5-year costs of care in persons with alcohol use disorder (AUD) and to examine whether remission decreases the costs of care. METHODS: Based on Electronic Health Record data collected in the North Karelia region in Finland from 2012 to 2016, we built a non-causal augmented naïve Bayesian (ANB) network model to examine the directional relationship between 16 risk factors and the costs of care for a random cohort of 363 AUD patients. Jouffe's proprietary likelihood matching algorithm and van der Weele's disjunctive confounder criteria (DCC) were used to calculate the direct effects of the variables, and sensitivity analysis with tornado diagrams and analysis maximizing/minimizing the total cost of care were conducted. RESULTS: The highest direct effect on the total cost of care was observed for a number of chronic conditions, indicating on average more than a €26,000 increase in the 5-year mean cost for individuals with multiple ICD-10 diagnoses compared to individuals with less than two chronic conditions. Remission had a decreasing effect on the total cost accumulation during the 5-year follow-up period; the percentage of the lowest cost quartile (42.9% vs. 23.9%) increased among remitters, and that of the highest cost quartile (10.71% vs. 26.27%) decreased compared with current drinkers. CONCLUSIONS: The ANB model with application of DCC identified that remission has a favorable causal effect on the total cost accumulation. A high number of chronic conditions was the main contributor to excess cost of care, indicating that comorbidity is an essential mediator of cost accumulation in AUD patients.

Bayesian Network Model to Evaluate the Effectiveness of Continuous Positive Airway Pressure Treatment of Sleep Apnea.

OBJECTIVES: The association between obstructive sleep apnea (OSA) and mortality or serious cardiovascular events over a long period of time is not clearly understood. The aim of this observational study was to estimate the clinical effectiveness of continuous positive airway pressure (CPAP) treatment on an outcome variable combining mortality, acute myocardial infarction (AMI), and cerebrovascular insult (CVI) during a follow-up period of 15.5 years (186 ± 58 months). METHODS: The data set consisted of 978 patients with an apnea-hypopnea index (AHI) ≥5.0. One-third had used CPAP treatment. For the first time, a data-driven causal Bayesian network (DDBN) and a hypothesis-driven causal Bayesian network (HDBN) were used to investigate the effectiveness of CPAP. RESULTS: In the DDBN, coronary heart disease (CHD), congestive heart failure (CHF), and diuretic use were directly associated with the outcome variable. Sleep apnea parameters and CPAP treatment had no direct association with the outcome variable. In the HDBN, CPAP treatment showed an average improvement of 5.3 percentage points in the outcome. The greatest improvement was seen in patients aged ≤55 years. The effect of CPAP treatment was weaker in older patients (>55 years) and in patients with CHD. In CHF patients, CPAP treatment was associated with an increased risk of mortality, AMI, or CVI. CONCLUSIONS: The effectiveness of CPAP is modest in younger patients. Long-term effectiveness is limited in older patients and in patients with heart disease (CHD or CHF).