Improving walking speed reduces hospitalization costs in outpatients with cardiovascular disease. An analysis based on a multistrata non-parametric test

Abstract

Background To assess the association between walking speed (WS) and its improvement on hospitalization rates and costs in outpatients with cardiovascular disease. Methods Six hundred forty-nine patients participating in an exercise-based secondary prevention program were studied. Patients were divided at baseline into two groups characterized by low and high WS based on the average WS maintained during a moderate 1-km treadmill-walking test. WS and other covariates were grouped into three domains (demographic factors, medical history and risk factors), and used to estimate a propensity score, in order to create homogeneous groups of patients. All-cause hospitalization was assessed 3 years after baseline as a function of WS. Hospitalization and related costs were also assessed during the fourth-to-sixth years after enrollment. To test whether the hospitalization costs were related to changes in WS after 36 months, a multistrata permutation test was performed by combining within strata partial tests. Results The results support the hypothesis that hospitalization costs are significantly reduced in accordance with an improvement in WS. This effect is most evident among older patients, overweight or obese, smokers, and those without a history of coronary artery bypass surgery. Conclusions The present study supports growing evidence of an inverse association between WS, risk of hospitalization and consequent health-care costs. The joint use of propensity score and multistrata permutation approaches represent a flexible and robust testing method which avoids the possible effects of several confounding factors typical of these studies.

The value of walking: a systematic review on mobility and healthcare costs

“…Detailed information on the individual studies is shown in Table 2 . Six studies were observational cohort studies [ 21 – 23 , 28 , 29 ], two were cross-sectional studies [ 25 , 27 ], one was a decision analysis using a Markov Model [ 24 ], and one was a microsimulation [ 26 ]. All studies ( n = 10) examined the economic impact of mobility in middle-aged to aged populations.…”

“…Walking (never, seldom, sometimes, often, always) during leisure-time and healthcare expenditure in primary care Total medical expenditures Expenditure on consultations, laboratory tests and medical consultations transformed into currency by standard table (provided by Brazilian government) Walking Speed Purser et al 2005 [ 23 ] Walking speed predicts health status and hospital costs for frail elderly male veterans USA n = 1,388 Department of Veterans Affairs (VA) multicenter clinical trial Cohort study Medical or surgical patients > 65 years. Geriatric Evaluation and Management (GEM) program Multivariate models to adjust for the effect of potential socio economic confounders, assessing baseline in gait speed and absolute change over 1 year Inpatient health services use, and total costs Data on length of stay, number, and charges of inpatient consultations, rehabilitation and social work visits as available from Veterans Affairs databases Bonnini et al 2020 [ 28 ] Improving walking speed reduces hospitalization costs in outpatients with cardiovascular disease. An analysis based on a multistrata non-parametric test Italy n = 649 Exercise-based secondary prevention program Prospective cohort study Patients participating in an exercise-based secondary prevention program (average age 63) Multi-strata permutation test after propensity score matching.…”

“…Costs that should be included in an analysis depend on the study perspective (refers to the point of view one takes when assessing costs), so failing to state the perspective meant that some of these studies lacked a clear rationale for the types of cost included. Five studies [ 24 , 26 , 28 , 29 ] did not adjust costs that occurred at different points in time, and two studies [ 23 , 26 ] conducted a sensitivity analysis to address a certain variety of their assumptions.…”

“…The cost reduction associated with a daily increase of 3,000 steps walked was calculated as 0,000,014 $ for each step Turi et al 2015 [ 25 ] PRO: Activity of daily living (walking during leisure time as self-reported in retrospective questionnaire ‘Baecke Questionnaire’) Not reported Participants inserted in the category of higher involvement in walking were 41% less likely to be inserted into the group with higher total expenditure (r = 0.59; 95% CI 0.39–0.89) Kabiri et al 2018 [ 26 ] Step Count No direct mobility measure (derived from MARCHE trial) The model predicted that a 554-step-per-day increase in mobility would reduce nursing home utilization by 2.8% The model predicted an increase of 554-step per day increase would reduce total medical expenditures by 0.9% Karl et al 2018 [ 27 ] DMO: Step Count (Self-reported hours of exercise per week. Accelerometer (worn during waking hours for 7 days) for uniaxial counts (counts/min) on the vertical axis for the deduction of activity levels and step counts) Not reported No significant results (Inactive participants (less than 10,000 steps per day), had higher direct healthcare costs as compared to active subjects) Bonnini et al 2020 [ 28 ] PerfO: Walking speed (maintained during a moderate 1-km treadmill-walking test) Every 1 km/hour increase in walking speed was associated with a 21% reduction in risk of hospitalization (HR 0.79) Hospitalization costs in the first, second and third propensity score tertile per patient were reduced from 1,281 to 341 $, from 904 to 383 $, and from 1,197 to 334 $ among low and high improvers in walking speed Okayama et al 2021 [ 29 ] PerfO: Walking speed (distance covered by walking up and down a 10 m course at a different dictated velocities, termed “incremental shuttle walking distance” (ISWD)) The mobile group had shorter cumulative lengths of hospital stay (41.3 vs. 72.9 days/person) than the less mobile group The mobile group had lower inpatient medical costs (16,680 $ vs. 25,458 $ /person) than the less mobile group Hirai et al 2021 [ 30 ] PRO: Walking Time (categorized average minutes of walking per week by questionnaire) Not reported Cumulative LTCI costs were USD 3200 for those who walked for less than 30 min, USD 2400 for those who walked for 30 to 60 min, and USD 2100 for those who walked fo...…”

Pattern Changes in the Heart Rate Variability of Patients Undergoing Coronary Artery Bypass Grafting Surgery

“…Imbalances in the ANS have been shown to increase the risk of arrhythmia in CAD patients. Increments in the sympathetic nervous system (SNS) activity in CAD patients may lead to greater myocardial ischemia, which in turn, increases the SNS activity while decreasing the parasympathetic nervous system (PSNS) activity [ 25 , 26 ].…”