General and Disease-Specific Health Indicator Changes Associated with Inpatient Rehabilitation

Abstract

Objectives: Rehabilitation plays a vital role in the mitigation and improvement of functional limitations associated with aging and chronic conditions. Moderating factors such as sex, age, the medical diagnosis, and rehabilitation timing for admission status, as well as the expected change related to inpatient rehabilitation, are examined to provide a valid basis for the routine assessment of the quality of medical outcomes. Design: An observational study was carried out, placing a focus on general and disease-specific health measurements, to assess representative results of multidisciplinary inpatient rehabilitation. Aspects that were possibly confounding and introduced bias were controlled based on data from a quasiexperimental (waiting) control group. Measures: Existing data or general health indicators were extracted from medical records. The indicators included blood pressure, resting heart rate, self-assessed health, and pain, as well as more diseasespecific indicators of physical function and performance (eg, activities of daily living, walking tests, blood lipids). These are used to identify moderating factors related to health outcomes. Setting and Participants: A standardized collection of routine data from 16,966 patients [61.5 AE 12.5 years; 7871 (46%) women, 9095 (54%) men] with different medical diagnoses before and after rehabilitation were summarized using a descriptive evaluation in terms of a content and factor analysis. Results: Without rehabilitation, general health indicators did not improve independently and remained stable at best [odds ratio (OR) ¼ 0.74], whereas disease-specific indicators improved noticeably after surgery (OR ¼ 3.20). Inpatient rehabilitation was shown to reduce the risk factors associated with certain lifestyles, optimize organ function, and improve well-being in most patients (>70%; cutoff: z-difference >0.20), with a standardized mean difference (SMD) seen in overall medical quality outcome of À0.48 AE 0.37 [pre-vs postrehabilitation: h p 2 ¼ 0.622; d Cohen ¼ À1.22; 95% confidence interval (95% CI) À1.24 to À1.19]. The baseline medical values obtained at the beginning of rehabilitation were influenced by indication, age, and sex (all P < .001); however, these factors have less significant effects on improvements in general health indicators (h p 2 < 0.01). According to the disease-specific results, the greatest improvements were found in older patients (SMD for patients >60 vs 60 years: 95% CI 0.08e0.11) and during the early rehabilitation stage (h p 2 ¼ 0.063).

Comparison of patient- and clinician-reported outcome measures in lower back rehabilitation: introducing a new integrated performance measure (t2D)

“…The test results show that only BMI (η p 2 = 0.041, p < 0.001) and baseline values (η p 2 = 0.182, p < 0.001) served as critical success (between) factors that contributed to significant changes in outcome measurements. Obese LBP patients with a BMI > 30 and patients with poorer FTF-initial values (t1) Normalized changes between admission (t1) to discharge (t2) are revealed by examining the effect sizes (z, SMD) and the number of patients (n [%]), which could be improved in clinically relevant ways [16]. Based on the value distributions, the individual outcome parameters were transformed into z-values.…”

“…By means of z-standardization, differently scaled quantities were summarized, and the changes were uniformly quantified. Z-differences from 0.00 ± 0.20 were classified as equal (no changes) [16,36] SMD (z-differences) classified Quality of Life Research 1 3…”

“…Difference values with no significant changes normally range randomly from 0.00 ± 0.20 (1/5 SD) [36]. Tertiles for FTF performance score were chosen, because the expected and observed improvements are around 2/3 (b bottom) [16] Quality of Life Research 1 3 studies revealed that the association of LBP and obesity seems to be weak [38]. In LBP, females seem to report more pain, higher levels of disability and lower quality of life than males, even though the values of CROMs do not seem to differ [14].…”

“…In this and in other patient populations, however, researchers have observed a divergence between selfreported outcome measurements and performance outcomes. They have also identified multiple factors that can influence this discrepancy in outcomes, including gender, education and mood [13][14][15][16]. This discrepancy needs to be considered in light of the different health conditions of the patients, in order to find a performance evaluation that also adequately considers those patients who already show satisfactory results (ceiling effects).…”

Observational study of an inpatient program for musculoskeletal disorders

“…The perceived pain (VAS; 0–10) of patients was 4.79 ± 1.85. Comparing the initial values for the averaged medical factors (MQO) with those of healthy people, a huge difference could be detected between overall MQOidx for patients (0.39 ± 0.94; Table 3 ) and that of healthy people (–1.15 [ 27 ] ) with a z -difference of –1.54.…”