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Address correspondence to Vincent Grote, PhD, Ludwig Boltzmann Institute of Rehabilitation Research, Reizenpfenninggasse 1, 1140 Vienna, Austria; or Elke Böttcher, MD, Humanomed Center Althofen, Moorweg 30, 9330 Althofen, Austria.
Ludwig Boltzmann Institute for Rehabilitation Research, Vienna, AustriaDivision of Physiology, Otto Loewi Research Center, Medical University of Graz, Graz, Austria
Address correspondence to Vincent Grote, PhD, Ludwig Boltzmann Institute of Rehabilitation Research, Reizenpfenninggasse 1, 1140 Vienna, Austria; or Elke Böttcher, MD, Humanomed Center Althofen, Moorweg 30, 9330 Althofen, Austria.
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 quasi-experimental (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 disease-specific 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 ± 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) = 0.74], whereas disease-specific indicators improved noticeably after surgery (OR = 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 −0.48 ± 0.37 [pre- vs post-rehabilitation: ηp2 = 0.622; dCohen = −1.22; 95% confidence interval (95% CI) −1.24 to −1.19]. 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 (ηp2 < 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 0.08–0.11) and during the early rehabilitation stage (ηp2= 0.063).
Conclusions and Implications
Compared with those who received no inpatient rehabilitation, patients who received rehabilitation showed greater improvements in 2 independent areas, general and disease-specific health measures, regardless of their diagnosis, age, and sex. Due to the study design and the use of a nonrandomized waiting group, causal conclusions must be drawn with caution. However, the comparability and stability of the presented results strongly support the validity of the observed improvements associated with inpatient rehabilitation.
According to the Global Burden of Diseases report, 39.8 to 40.5 million deaths occur per year that can be assigned to 4 main categories (cardiovascular, metabolic, oncological, and pulmonary diseases) of noncommunicable diseases.
GBD 2015 Mortality and Causes of Death Collaboration Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: A systematic analysis for the Global Burden of Disease Study 2015.
Physical activity prescription: A critical opportunity to address a modifiable risk factor for the prevention and management of chronic disease: A position statement by the Canadian Academy of Sport and Exercise Medicine.
The amelioration of the physical constitution leads to health-promoting effects, such as a reduction in hypertension due to improvements in the cardiovascular system, a better glucose profile, and reduced blood lipids, but also to important improvements in the quality of life.
A systematic review and meta-analysis of adherence to physical activity interventions among three chronic conditions: Cancer, cardiovascular disease, and diabetes.
International Conference on Primary Health Care, World Health Organization, United Nations Children's Fund. Primary health care: report of the International Conference on Primary Health Care, Alma-Ata, USSR, 6–12 September 1978. World Health Organization,
Geneva1978
developed to achieve and maintain population health. Rehabilitation therapy can restore functions that have been reduced or eliminated by diseases, injuries, or other health conditions, can ameliorate the impact capacity of the reduction, and can minimize other initial health problems.
According to the WHO definition, the rehabilitative process can be divided into 4 phases: phase I includes the early mobilization in primary treatment (provided in acute care hospitals), phase II provides follow-up treatments or post-acute therapy in specialized rehabilitation centers, phase III includes the integration and stabilization of long-term life modifications, and phase IV addresses long-term rehabilitation that often includes outpatient aftercare.
Much evidence exists that rehabilitation is a beneficial part of the treatments provided for patients with inflammatory or degenerative diseases, as well as for those with postoperative conditions or injuries. Maximally effective rehabilitation programs include physical therapy, multidisciplinary interventions to modify behavior, and psychological and educational support. Clinical standards for rehabilitation recommend the routine collection of standardized outcome measures to evaluate the impact of rehabilitation, including individual, detailed results from the point of admission up to the point of discharge.
Pre-post changes in main outcomes of medical rehabilitation in Germany: Protocol of a systematic review and meta-analysis of individual participant and aggregated data.
Therefore, we carried out a quasi-experimental study to investigate the relationship between inpatient rehabilitation and improvements in general and disease-specific results.
Methods
In this study, a pre-post design with a nonrandomized control group (waiting list) was used to take monocentric routine outcome measurements in an inpatient medical rehabilitation setting. The medical quality outcome measurements established in the performance profile of the Austrian social security institutions served as the basis for this work.
Based on a common and mandatory routine data collection process, general health and disease-specific medical measurements were extracted from the electronic patient records to obtain data on pre-rehabilitation medical conditions and expected changes related to inpatient rehabilitation. The personal and health-related data were collected as part of routine medical care, as well as the quality assurance and evaluation of doctors and health care professionals, in accordance with national legislative guidelines. These data were stored in a clinical information system. The scientific data collected in this study could be exported directly from the electronic and verified patient records. The standardized clinical characteristics of the patients were recorded systematically at the points of admission and discharge (see Table 1).
Table 1Indicators of MQOs
MQOidx and Individual Success Factors
GHI
ISI (Disease-specific Health Outcomes [z])
MED 1
BMI
[kg/m2]
Walk test
6-MWT
[m]
Waist circumference
[cm]
ADL
EQ-5D
[%]
ADL
EQ-5D
[%]
SHAPE
[z]
ISIonc
Oncology Rehab.
[z]
Motoric
Roland-Morris
[0–24]
MED 2
Systolic blood pressure Diastolic blood pressure
[mm Hg]
Lipids
Cholesterol HDL
[mg/dL] [mg/dL]
function
WOMAC Constant-Murley
[0–240] [0–100]
Resting heart rate
[bpm]
LDL
[mg/dL]
Walk test
Timed up and go Test
[sec]
CARDIOVASCULAR
[z]
Triglycerides
[mg/dL]
10-Meter Walk Test
[sec]
ISIort
Orthopedic Rehab.
[z]
MED 3
VAS (pain)
[cm; 0–10]
Blood glucose
HBA1C
[mmol/m]
EQ-VAS (self-rated health)
[%; 0–100]
Blood sugar
[mg/dL]
Clinical classification
CCS/NYHA
[1–4]
SUBJECTIVE
[z]
ISIMET
Metabolic Rehab.
[z]
ADL
EQ-5D
[%]
O2
Oxygen saturation
[%]
LDL
GHI
General Health Index mean (MED1, MED2, MED3)
[z]
Respiratory
COPD Assessment Test
[0–40]
Lipids
HDL
[mg/dL]
Function
Asthma Control Test
[5–25]
Triglycerides
Walk test
6-MWT
[m]
Ergometer
Watts
[W]
All indications(ONC, MET, PUL, ORT, CAR)
ISIpul
Pulmonary Rehab.
[z]
Rate Pressure (Double) Product
ISIcar
Cardiovascular Rehab.
[z]
CAR, cardiovascular; CCS, Canadian Cardiovascular Society; COPD, chronic obstructive pulmonary disease; EQ-5D, EuroQol-5D; HDL, high density lipoprotein; LDL, low density lipoprotein; MET, metabolic; NYHA, New York Heart Association; ONC, oncology; ORT, orthopedic; PUL, pulmonary; Rehab., rehabilitation; WOMAC, Western Ontario and McMaster Universities Arthritis Index; 6-MWT, 6-minute walk test.
GHI, ISI, and MQOidx were calculated for each patient for the admission (pre) and discharge (post) statuses and the difference between these (difference: post − pre) was used as an individual success factor for rehabilitation.
The units or scaling are highlighted in italics. The summarized outcome measures for a homogeneous medical indicator or factor are highlighted in bold.
Outcome measurements shown in Table 1 include general health characteristics of the patients, such as their body measurements and cardiovascular indicators, psychological indicators such as pain, and subjective health in all indications. These form the general outcome indicators [General Health Index (GHI)]. Specific outcome measurements are given for each of the different indications, such as activities of daily living [(ADL); questionnaires], motor skills, or physical performance. These form the indication-specific outcome indicators [Indication-Specific Index (ISI)]. The data were summarized using a descriptive evaluation in terms of respective content and factor analyses. This simple evaluation model enabled the use of independent factors to carry out a simplified evaluation of the outcome quality.
Medizinische Ergebnisqualität: Unspezifische Outcome-Parameter einer stationären Rehabilitation des Stütz- und Bewegungsapparates in Österreich [Medical quality outcomes: unspecific outcome parameters of an inpatient musculoskeletal system rehabilitation in Austria].
Rehabilitation Sample at the Clinical Trial Center
During the study period from 2016 to 2018, 16,966 patients with different medical indications [61.5 ± 12.5 years, 7871 (46%) women, 9095 (54%) men; Table 2 and Supplemental Figure 3] were enrolled in a specialized interdisciplinary hospital for rehabilitation (CTC: Humanomed Center Althofen, Austria).
Table 2Sample: Number of Patients by Indication, Age, and Sex
Absolute (no.) and n (%)
Age, y
≤40
41–50
51–60
61–70
71+
Total
Mean
SD
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
Orthopedic
Female
62.8
13.4
216
4.9
548
12.4
1195
27.1
968
21.9
1489
33.7
4416
51.8
50.2%
Male
59.0
13.4
350
8.5
632
15.4
1326
32.3
906
22.1
893
21.7
4107
48.2
Total
61.0
13.5
566
6.6
1180
13.8
2521
29.6
1874
22.0
2382
27.9
8523
100.0
Cardiovascular
Female
66.6
11.7
18
1.7
75
7.3
224
21.7
253
24.5
461
44.7
1031
28.4
21.4%
Male
62.8
11.4
72
2.8
255
9.8
804
30.9
724
27.8
749
28.8
2604
71.6
Total
63.9
11.6
90
2.5
330
9.1
1028
28.3
977
26.9
1210
33.3
3635
100.0
Metabolic
Female
57.7
10.7
16
6.1
39
14.9
106
40.6
66
25.3
34
13.0
261
36.5
4.2%
Male
56.7
9.7
20
4.4
89
19.6
191
42.1
120
26.4
34
7.5
454
63.5
Total
57.1
10.1
36
5.0
128
17.9
297
41.5
186
26.0
68
9.5
715
100.0
Oncology
Female
59.2
11.5
57
4.1
245
17.6
499
35.8
326
23.4
266
19.1
1393
64.2
12.8%
Male
59.8
11.5
46
5.9
97
12.5
276
35.5
208
26.8
150
19.3
777
35.8
Total
59.5
11.5
103
4.7
342
15.8
775
35.7
534
24.6
416
19.2
2170
100.0
Pulmonary
Female
63.1
10.2
12
1.6
67
8.7
238
30.9
257
33.4
196
25.5
770
40.0
11.3%
Male
63.6
10.0
23
2.0
74
6.4
334
29.0
419
36.3
303
26.3
1153
60.0
Total
63.4
10.1
35
1.8
141
7.3
572
29.7
676
35.2
499
25.9
1923
100.0
Overall
Female
62.5
12.7
319
4.1
974
12.4
2262
28.7
1870
23.8
2446
31.1
7871
46.4
100.0%
Male
60.6
12.3
511
5.6
1147
12.6
2931
32.2
2377
26.1
2129
23.4
9095
53.6
Total
61.5
12.5
830
4.9
2121
12.5
5193
30.6
4247
25.0
4575
27.0
16,966
100.0
The total sample included 18,398 patients; the analytical sample consisted of 16,966 patients (92.2%) who attended the rehabilitation program for at least 17 days and for whom valid measurements for admission and discharge were available. In the total sample, 4.1% of patients had missing values, and 3.7% discontinued their inpatient treatment prematurely. Influence of age on: Indication: ηp2 = 0.023, Sex: ηp2 = 0.002, Indication × Sex: ηp2 = 0.006 (all P < .001).
The average length of stay was 21.0 ± 3.5 days, and 3.7% of all patients discontinued their inpatient treatment prematurely due to a loss of rehabilitation capacity, acute illness, or for private reasons (criterion <18 days).
In Austria, an insured person is entitled to receive medical rehabilitation care.
Applications for patients who need post-acute care after discharge from the hospital are submitted by a specialist to the treating hospital or can be submitted by the patient him- or herself with a medical statement from a general practitioner or specialist. The social security administration reviews the application and makes rehabilitation assignment decisions. The inferred reasons for inpatient rehabilitation are based on the referral diagnosis listed on the application. Reasons for referral to a specialized rehabilitation center may include the need for post-acute care after discharge from the hospital (follow-up procedure), for example, after an accident or surgery. Assignment to rehabilitation is also possible for the conservative treatment of stable patients who have not experienced such an acute event to restore or maintain their health. These patients include those with chronic disorders (eg, dorsalgia, chronic obstructive pulmonary disease exacerbations), which can affect their ability to work and result in a need for early retirement or long-term care. The patient must fulfill 3 conditions to be eligible for medical rehabilitation: demonstrate a need for rehabilitation, be suitable for rehabilitation (motivated and able to participate in rehabilitation care), and be able to achieve the specific goal of rehabilitation care within a certain time frame.
The comparison group comprised patients who were waiting to enter rehabilitation. The mean period between acute care (surgery, chemotherapy) and rehabilitation was 13.8 ± 24.2 weeks (see Supplemental Table 2); however, orthopedic patients who had undergone a surgery of the knee, hip, or shoulder and cardiovascular patients with chronic ischemic heart disease and nonrheumatic aortic valve disorders progressed more quickly from phase I to phase II (10.7 ± 18.4 weeks).
Ethical Aspects and Data Collection
This study (Routine Outcome Measurements of an Inpatient Rehabilitation in Austria) was reviewed and approved by an ethics committee (vote by the Ethics Committee of the Medical University of Graz, Graz, Austria, dated 02.05.2019, EC Protocol Number: 31–321 ex 18/19). Person-related and health-related data were collected as part of routine medical care and quality management in compliance with all regulations of the General Data Protection Regulation, and in accordance with the Declaration of Helsinki in the currently valid version and the national legislation.
Medical Outcome Quality
Medical outcome quality is defined as the “measurable change in the professionally assessed state of health, the quality of life and the satisfaction of a patient” (see the Austrian Federal Act on the Quality of Health Care).
A comparison is thus possible between baseline rates before rehabilitation (pre: admission) with after rehabilitation rates (post: after discharge) or the mean differences between these rates (post − pre). (Instead of a dependent comparison of the pre-post values within a patient group, an independent comparison with an untreated control group can also be carried out.)
The aim of conducting the present work was to investigate differences of success depending on timing of rehabilitation and to provide a valid basis for the routine assessment of the quality of medical outcomes. The focus was placed on assessing general (nonspecific) and indication-specific measurements (Table 1).
Quantifying “medical outcome quality”
Our success indicators are formed by summarizing the compulsory clinical data.
Medizinische Ergebnisqualität: Unspezifische Outcome-Parameter einer stationären Rehabilitation des Stütz- und Bewegungsapparates in Österreich [Medical quality outcomes: unspecific outcome parameters of an inpatient musculoskeletal system rehabilitation in Austria].
The GHI is the arithmetic mean of 3 independent variables: body shape [body mass index (BMI) and waist circumference], cardiovascular measurements (blood pressure and resting heart rate), and discomfort [visual analog scales for pain (VASpain, 0–10) and subjective self-evaluation (EQ-VAS, 0–100)]. An analysis of these indicators enables us to obtain a simple and quick overview of the effectiveness of rehabilitation treatment with regard to general health characteristics (see Supplemental Table 3).
2.
The ISI corresponds to the z-normalized means of homogeneous medical content areas such as daily activities, motor skills, or physical performance for each indication (see Table 1 and the example calculation in supplemental Statistical Methods). It corresponds to a disease-specific medical outcome.
3.
Both indices together form the overall Medical Quality Outcome (MQOidx) in equal parts: The summarized standardized mean differences (SMD) or changes (improvements) from the admission to the discharge of an inpatient in rehabilitation thus correspond to the MQOidx, the mean value of GHI and ISI without further weighting.
Results
The total sample included 18,398 patients; the analytical sample consisted of 16,966 patients (92.2%) who attended the rehabilitation program for at least 17 days and for whom valid measurements for admission and discharge were available (see Table 2). In general, all available participants were included in the analysis [Depending on the statistics performed, data from N = 16,966 patients were used for calculations “within” the patients, and when comparing the data “between” patients, the waiting group of orthopedic and cardiovascular patients with n = 5453 was used. The latter comparison with the control group was carried out to validate the results observed across the entire sample and to evaluate the start of rehabilitation after the surgery (untreated control group: n1 = 4577; treated rehabilitation patients: n2 = 5161)]. The quasi-experimental control group comprised 4577 orthopedic and cardiovascular patients who were waiting to start post-acute care (rehabilitation) after surgery. These patients were independently compared with 5161 participants who had already completed inpatient rehabilitation (see Supplemental Table 6).
The most frequent International Classification of Diseases, 10th Revision (ICD-10)
diagnoses noted at the study center were those for chronic ischemic heart disease, osteoarthritis of knee and hip, chronic obstructive pulmonary disease, dorsalgia, and malignant neoplasm of the breast (see Supplemental Table 1).
Baseline Data (Pre-rehabilitation)
The assessed baseline measurements (pre) associated with rehabilitation clearly show the medical deficits of the affected patients. The average BMI was 28.7 ± 5.7 kg/m2 (35.1% of patients had a BMI >30 kg/m2) and 77.4% of patients had a “high-normal” (22.2%) or “hypertonic” (52.2%) blood pressure (mean RRsystolic/diastolic: 131.1/77.3 ± 14.3/8.4 mm Hg). The perceived pain (VAS; 0–10) of the patients was 2.8 ± 2.4 and the subjective health status (EQ-VAS; 0–100) was estimated as 62.1% ± 17.0% on average [On request, the authors may provide descriptive data on individual medical measurements for admission and discharge or the expected change (eg, data on basic clinical, labor, and performance measurements, like ergometer tests) due to inpatient rehabilitation for various groups and diagnoses.]
Outcome Measurements
An examination of specific and general outcomes shows a comparable change sensitivity (main effect time, P < .001: ηp2general = 0.497 (GHI) vs ηp2specific = 0.475 (ISI), Tables 3 and 4). The SMD for overall MQOidx (mean of GHI and ISI) was −0.48 ± 0.37 (centroid, dCohen
= −1.216, P < .001, Figure 1). The observed results can be classified as highly stable and reliable, because they apply equally to different patient (sub) groups (Table 4 and Supplemental Table 5).
Table 3Effect Sizes for MQO and Moderating Factors
Differences (improvements; post − pre) from admission to discharge (corresponds to the interaction: time × factor).
Main Effect
Between-factors
Sex
Age
IND
No. diag.
Dropout
ICD
Sex
Age
Age
IND
No. diag.
ICD
ICD
Pre
Time
MQO variables
f/m
5-stage
5-stage
3-stage
2-stage
32-stage
f/m
5-stage
cov. pre
5-stage
3-stage
32-stage
cov. pre
3-stage
2-stage
MED 1: Shape
0.032
0.012
0.077
0.007
0.000
0.141
0.008
0.002
0.004
0.046
0.002
0.055
0.054
0.008
0.079
MED 2: Cardiovascular
0.014
0.009
0.045
0.004
0.000
0.062
0.002
0.003
0.004
0.010
0.002
0.016
0.021
0.027
0.149
MED 3: Subjective
0.018
0.012
0.044
0.002
0.002
0.070
0.009
0.001
0.001
0.030
0.000
0.040
0.042
0.044
0.564
General Health (GHI)
0.010
0.016
0.055
0.010
0.001
0.087
0.000
0.002
0.005
0.004
0.001
0.011
0.017
0.069
0.497
Indication Specific (ISI)
0.026
0.079
0.006
0.018
0.007
0.063
0.007
0.009
0.002
0.035
0.023
0.069
0.062
0.109
0.475
Overall MQOidx
0.003
0.055
0.021
0.022
0.006
0.054
0.003
0.005
0.001
0.016
0.009
0.030
0.028
0.156
0.622
Between-factors: sex (female, male), age (≤40, 41–50, 51–60, 61–70, 71+), IND, indication (orthopedic, cardiovascular, pulmonary, metabolic, oncology); no.diag., number of diagnoses (1,2, >2); dropout (regular vs <18 days); ICD, 32 main-diagnoses (see Supplemental Table 1), pre, pre-rehabilitation value of MQO (tertile); cov., covariate; within-factor, main effect “time” (pre, post); a part. Eta2 (ηp2) between 0.01–0.06 corresponds to a small effect, occurrences of 0.06–0.14 a middle effect, and values >0.14 a large effect; N = 16,966.
∗ Admission state (pre-rehabilitation data) at the beginning of rehabilitation.
† Differences (improvements; post − pre) from admission to discharge (corresponds to the interaction: time × factor).
Pre-rehabilitation values (pre) at the beginning of rehabilitation for monocentric normative data from the study center. A positive z-value corresponds to a below-average (worse) value in the sample (n = 16,966). A z-value of 0 corresponds to the mean value of pre and post values and no significant changes between pre vs post. z-values were calculated according to the PCA (formula see Supplementary Table 3). The baseline value (pre) plus the mean difference (post − pre) gives the outcome value after rehabilitation (post).
ISI could not be effectively compared between indications, because different medical parameters were used.
(cf. ISI Tab. 1)
Cardiovascular
0.16 ± 0.79
−0.36 ± 0.46
[−0.38 to −0.34]
0.375
Metabolic
0.16 ± 0.64
−0.38 ± 0.43
[−0.42 to −0.34]
0.438
Oncology
0.19 ± 0.80
−0.47 ± 0.51
[−0.49 to −0.44]
0.451
Pulmonary
0.19 ± 0.75
−0.45 ± 0.53
[−0.48 to −0.43]
0.424
Indication-Specific Index(isi)
0.23 ± 0.80
−0.50 ± 0.53
[−0.51 to −0.49]
0.475
Orthopedic
0.23 ± 0.58
−0.45 ± 0.43
[−0.46 to −0.44]
0.522
Cardiovascular
0.13 ± 0.63
−0.45 ± 0.49
[−0.46 to −0.43]
0.450
General
Metabolic
0.61 ± 0.83
−0.58 ± 0.55
[−0.61 to −0.55]
0.522
Oncology
−0.15 ± 0.65
−0.48 ± 0.45
[−0.50 to −0.46]
0.537
Pulmonary
0.24 ± 0.69
−0.43 ± 0.48
[−0.45 to −0.41]
0.449
General Health Index(ghi)
0.17 ± 0.64
−0.45 ± 0.46
[−0.46 to −0.45]
0.497
mean (MED1, MED2, MED3)
Orthopedic
0.10 ± 0.96
−0.05 ± 0.18
[−0.05 to −0.05]
0.072
Cardiovascular
0.17 ± 0.92
−0.09 ± 0.24
[−0.10 to −0.09]
0.132
MED1
Metabolic
1.22 ± 1.41
−0.21 ± 0.21
[−0.22 to −0.19]
0.496
Oncology
−0.38 ± 0.97
−0.01 ± 0.16
[−0.01 to 0.00]
0.001 (P = .142)
Pulmonary
0.11 ± 1.19
−0.02 ± 0.15
[−0.03 to −0.01]
0.018
Shape(bmi, wc)
0.09 ± 1.03
−0.06 ± 0.19
[−0.06 to −0.05]
0.079
Orthopedic
0.14 ± 0.89
−0.37 ± 1.01
[−0.40 to −0.35]
0.120
Cardiovascular
0.11 ± 1.2
−0.59 ± 1.34
[−0.62 to −0.55]
0.160
MED2
Metabolic
0.56 ± 1.08
−0.64 ± 1.29
[−0.73 to −0.56]
0.199
Oncology
−0.18 ± 1.12
−0.52 ± 1.14
[−0.57 to −0.47]
0.172
Pulmonary
0.67 ± 1.22
−0.66 ± 1.25
[−0.71 to −0.61]
0.219
Cardiovascular (RR, rp)
0.17 ± 1.06
−0.48 ± 1.15
[−0.50 to −0.46]
0.149
Orthopedic
0.44 ± 0.91
−0.91 ± 0.75
[−0.93 to −0.90]
0.598
Cardiovascular
0.12 ± 0.94
−0.66 ± 0.62
[−0.69 to −0.64]
0.533
MED3
Metabolic
0.06 ± 1.14
−0.89 ± 1.00
[−0.94 to −0.84]
0.443
Oncology
0.11 ± 0.91
−0.92 ± 0.69
[−0.95 to −0.89]
0.638
Pulmonary
−0.07 ± 0.79
−0.61 ± 0.62
[−0.64 to −0.58]
0.490
Subjective(vas, eq-vas)
0.26 ± 0.94
−0.83 ± 0.73
[−0.84 to −0.81]
0.564
N = 16,966 patients from 2016 to 2018; 0-age: 61.52 ± 12.51 years; 46.4% female, 53.6% male.
The summarized medical quality outcomes for all indications are highlighted in bold.
EQ-VAS, self-rated health; RP, resting heart rate; RR, blood pressure systolic/diastolic; VAS, Visual Analog Scale; WC, waist circumference.
∗ Pre-rehabilitation values (pre) at the beginning of rehabilitation for monocentric normative data from the study center. A positive z-value corresponds to a below-average (worse) value in the sample (n = 16,966). A z-value of 0 corresponds to the mean value of pre and post values and no significant changes between pre vs post. z-values were calculated according to the PCA (formula see Supplementary Table 3). The baseline value (pre) plus the mean difference (post − pre) gives the outcome value after rehabilitation (post).
† Average improvement from admission (pre) to discharge (post): Standardized Mean z-Difference (SMD) = zpost − zpre.
‡ Within-factor time (for SMD): all P < .001.
§ ISI could not be effectively compared between indications, because different medical parameters were used.
Fig. 1Improvements in general and indication-specific medical outcome indicators. The plot shows a marked improvement due to rehabilitation in specific as well as general health indicators. A value of zero ±0.20 (z-difference) represents no significant changes from admission (pre) to discharge (post). Negative z-differences (SMD) correspond to an improvement of the indicators. The SMD for GHI is −0.45 ± 0.46 and for ISI −0.50 ± 0.53. The overall MQOidx (mean of GHI and ISI) is −0.48 ± 0.37 (centroid); MQOidx: dCohen = −1.216, rpre−post = 0.77, 95% CI −1.24 to −1.19.
The relationship between the specific and general outcome characteristics (changes) is small (r < 0.20, P < .001, Figure 1), which is reflected in the results of a multivariate analysis of temporal changes in the variance (ηp2multivariat = 0.624, P < .001).
The general and indication-specific outcome data (Tables 3 and 4, Figure 1) for inpatients who had received rehabilitation strongly differed from pre-rehabilitation values (pre) at the beginning of rehabilitation, with overall medical quality outcomes (MQOidx: ηp2 = 0.622, P < .001) improving markedly over a 3- to 4-week period. The indication played a role in these improvements, especially with regard to the shape indicators (MED1: ηp2 = 0.046, P < .001), subjective complaints (MED3: ηp2 = 0.030, P < .001). Improvements in the GHI showed only a slight dependency on indication (ηp2 = 0.004, P < .001). The general score, the GHI (Table 1 and Supplemental Table 3), shows that 71.4% of patients benefited directly from the rehabilitation stay, whereas 21.8% of the patients showed no improvement and the status of 6.8% worsened from the beginning to the end of the rehabilitation period (see Supplemental Table 7). This corresponds to a standardized improvement (mean z-difference; SMD) in general health measurements of −0.45 ± 0.46 with a 95% confidence interval (CI) between −0.46 and −0.45 (ηp2 = 0.497, P < .001; Table 4). A detailed analysis of this improvement in GHI by 13.3 percentile points shows that shape features, such as BMI and waist circumference, remained unchanged over the 3-week period in most of the patients (83.1%; SMDMED1 = −0.06 ± 0.19, P < .001). In contrast, cardiovascular features such as blood pressure and resting heart rate seemed to be directly influenced by inpatient rehabilitation, with an average improvement of −0.48 ± 1.15 (SMDMED2; 95% CI −0.50 to −0.46; P < .001) observed. The most pronounced effects of inpatient rehabilitation could be seen by measuring the subjective features, whereby almost every patient reported a significant improvement (SMDMED3 = −0.83 ± 0.73, P < .001).
A similarly positive change is revealed by the indication-specific score (ISI: +14.70 percentile points; SMDISI = −0.50 ± 0.53, 95% CI −0.51 to −0.49; P < .001), whereby 70.5% of patients improved markedly (ηp2 = 0.475, P < .001).
The observed changes depend on the pre-rehabilitation values used (time × preMQO: ηp2GHI = 0.069, P < .001; GHI: rpre vs post−pre = −0.492, P < .001), which differ significantly according to the diagnosis used for general baseline values (ICDpre: ηp2GHI = 0.087, P < .001). Improvements are clearly visible for all factors, indications, and diagnoses (Tables 3 and 4). These findings indicate that rehabilitation is generally successful (time: ηp2GHI = 0.497, P < .001) along a comparable scale between diagnoses (time × ICD: ηp2GHI = 0.011, P < .001).
Age as an Influencing Factor
On the examination of further grouping characteristics (between-factors), we observed that sex (ηp2multivariat = 0.071, P < .001) and age (ηp2multivariat = 0.026, P < .001) contributed significantly to the pre-rehabilitation values, which are lower within the general than within the specific measurements. In contrast, age and sex played minor roles in influencing medical outcome indicators (age: ηp2MQO = 0.005, P < .001 sex: ηp2MQO = 0.003, P < .001, Table 3).
Patients older than 60 years showed an equal or even more favorable symptom-specific outcome [z-difference, SMDISI for 60+: 0.55 ± 0.55 vs ≤60 years: 0.45 ± 0.50; age 2-stage: ηp2 = 0.008, 95% CI for mean difference of SMDISI between patients >60 vs ≤60 years: (0.08, 0.11, P < .001; Supplemental Figure 1). Patients younger than 51 years] showed better baseline values for all medical measurements (see Supplemental Table 4 and Supplemental Figure 1), which are associated with a lower potential for change. Nevertheless, the equal or even more marked descriptive overall improvements seen in patients older than 60 years (SMDMQO: 0.50 ± 0.38 vs patients ≤60 years: 0.45 ± 0.36, ηp2 = 0.004, P < .001) are significant for the indication-specific outcome, even when the baseline values are taken into account (P = .010, Table 3 and Supplemental Table 5). The effects of age on rehabilitative outcome is not the same in all indications. Especially older orthopedic patients obtained the strongest benefit from rehabilitation in terms of overall MQOidx, whereas younger cardiovascular patients showed the lowest response to rehabilitation therapy (Supplemental Figures 1 and 2).
Timing of Rehabilitation
In the subsample of orthopedic patients who had undergone knee, hip, or shoulder surgery and cardiovascular patients with chronic ischemic heart disease and nonrheumatic aortic valve disorders (Supplemental Tables 2 and 6), we observed that changes occurred in the GHI independent of the time delay from discharge to rehabilitation (beta coefficient = −0.008, 95% CI −0.013 to −0.003; interaction: time × postsurgery week: ηp2 = 0.003, P = .084; Supplemental Table 5).
Patients who began rehabilitation later have initially better specific indicators than general health indicators (pre-rehabilitation value: ηp2ISI = 0.042, P < .001 vs ηp2GHI = 0.009, P < .001; Figure 2). However, the later these patients entered phase II rehabilitation, the lower their observational specific success was (beta coefficient = 0.056, 95% CI 0.050–0.063, ηp2ISI = 0.062, P < .001), indicating that an early onset of medical rehabilitation is beneficial. These results were found to be almost equal for orthopedic and cardiovascular patients and roughly for all patient (sub) groups (by age, sex, and diagnoses; Supplemental Table 5).
Fig. 2Influences of time delay between surgery and rehabilitation on the medical outcome. Whereas general health indicators (left) worsened (going up) as the time delay after surgery increased (beta = 0.018; ORGHI = 0.74), specific indicators (right) improved (beta = −0.060; ORISI = 3.20) spontaneously without rehabilitation (red diamonds). The within-subjects analysis (green arrows) shows results similar to the analysis between different patients (dashed black line). Specific health indicators indicating that an early onset of medical rehabilitation is beneficial (n = 5453; Supplemental Tables 5 and 6).
Using the quasi-experimental (waiting) control group for the same period, the results of the analysis between untreated patients and patients after rehabilitation were similar to the results of the conventional within-subjects analysis (Figure 1, Table 4). Within patients, the SMDGHI in this subsample was −0.44 (−0.46 to −0.43) and between patients it was −0.45 (−0.47 to −0.43); for SMDISI, it was −0.50 (−0.51 to −0.48) within patients versus −0.52 (−0.55 to −0.49) between patients (Figure 2).
Discussion
Strong evidence exists that rehabilitation is necessary as part of treatments for inflammatory or degenerative diseases, as well as for postoperative conditions or injuries.
In this article, we describe the results of an observational study, presenting nationally representative results of inpatient rehabilitation. We used existing data from medical records to improve the quality of medical care and identify moderating factors related to health outcomes. We controlled for possible confounding and bias effects by referencing data from a nonrandomized untreated (waiting) control group.
Our data show that most patients clearly benefited from inpatient rehabilitation, independent of their indications, diagnoses, and ages. All patients showed similar improvements in terms of general and indication-specific outcome indicators. These study findings show that general and disease-specific outcomes behave differently. They also show that the timing of post-acute rehabilitation plays an important role in disease-specific but not in general health changes.
The selection of outcome indicators needs to take into account evidence-based and economic considerations to guarantee a comparable standard of quality medical treatment. Indication-specific indicators are central to rehabilitative treatment and restore the patient's ability to work or reintegrate into social and professional environments. This score cannot be effectively compared between indications because different medical measurements are used for medical assessment, but it can be used to evaluate general relationships with relevant factors that influence the healing and recovery process. Another focus is placed on general health features, such as obesity, blood pressure, and physical inactivity. These characteristics are associated with poorer health, cardiovascular disease, and metabolic disorders.
A systematic review and meta-analysis of adherence to physical activity interventions among three chronic conditions: Cancer, cardiovascular disease, and diabetes.
Dose-response associations of cardiorespiratory fitness with all-cause mortality and incidence and mortality of cancer and cardiovascular and respiratory diseases: the UK Biobank cohort study.
In addition to determining the individual, symptomatic treatment of a patient, an important task in inpatient rehabilitation is to sustainably reduce these risk factors. Quality of life and functioning are characterized by positive lifestyle modifications (eg, an increase in physical activity); therefore, a reduction in the recorded general health indicators, such as BMI,
waist circumference, blood pressure, heart rate, and pain, is also highly relevant for the inpatient rehabilitation of patients with different diagnoses and indications.
To work meaningfully and deductively, it is helpful to reduce the abundance of partially redundant information to a manageable, uniform level. The use of the GHI, ISI, and overall MQOidx enables us to gain simple and quick overviews of the “general” and “specific” effectiveness of the rehabilitative stay for certain treatment programs. The 2 former result factors allow us to distinguish between constitutional, regulatory areas (GHI) and the functional level (ISI). General health measures (GHI) correspond to basic measurements, which are almost always recorded during the routine medical assessment. On the other hand, disease-specific measures (ISI) are examined only if certain diagnoses or physical restrictions are present, particularly in functional areas where improvement or healing is defined as the treatment goal (Table 1). Therefore, a broad definition is used for the term “indication or disease-specific” in this work, including the functional and mobility status,
which most geriatricians and physiotherapists would consider nonspecific and not necessarily disease-specific.
General versus Specific Quality of Outcomes
When assessing the effectiveness of inpatient rehabilitation based on the nonspecific (“general”) features of the health outcome, it is not as important to differentiate between medical indications, as effect sizes are similar. Sex and age are also of minor importance. If general health indicators at discharge are compared with the baseline medical evaluation data (SMDGHI = −0.45) or a quasi-experimental control group (SMDGHI = −0.44), we observe that 71.4% of patients benefited directly from inpatient rehabilitation (GHI). Significant interactions with further grouping features can be classified as “small” compared with the main effect time (rehabilitation). Therefore, the observed strong general rehabilitation effect was similar among all subgroups and could be responsible for cost-saving effects of rehabilitation observed in the health system.
We predict that this general success could occur in all inpatient rehabilitation stays and programs due to the provision of a series of regular therapeutic stimuli, physical activity, and exercise training as well as recovery periods over a defined period. These would potentially lead to functional adaptation, which is characterized by improvements in regulatory qualities and the economization and normalization of physiological functions. Changes of general health outcomes are independent of the delay between medical treatment (surgery) and rehabilitation. In an untreated control group without rehabilitation, therefore, no positive spontaneous change in the constitutional state of health would be expected (odds ratio = 0.74).
Unlike general health scores, our findings indicate that moderating factors play more important roles in the specific outcome quality than previously thought. Patients older than 60 years showed equal or even more favorable rehabilitation outcomes than other patients, especially with regard to symptom-specific indicators (ISI). As the nature and severity of the underlying disease influences the outcome, it is not surprising that the relationship between age and outcome differed among the indications. One interesting finding of this study is that older orthopedic and cardiovascular patients obtained the largest benefit in terms of overall medical quality outcome. It has already been shown that older patients can achieve greater improvements through exercise training and cardiac rehabilitation than younger patients.
To our knowledge, this is the first time this benefit has been observed in orthopedic patients.
Our results indicate that inpatient rehabilitation should be initiated as quickly as possible after discharge from the hospital to achieve favorable disease-specific outcomes. In particular, patients who entered Phase II earlier (<6 weeks) after undergoing surgery and patients with poorer health (pre-rehabilitation medical evaluations) showed better success as measured by their symptom-specific characteristics.
These findings underline the importance of taking a multidimensional view of specific and general outcome quality and of describing 2 independent components of rehabilitation. A multidisciplinary rehabilitation is based on the reduction of risk factors (primary and secondary prevention, general health indicators), an increase in fitness,
Dose-response associations of cardiorespiratory fitness with all-cause mortality and incidence and mortality of cancer and cardiovascular and respiratory diseases: the UK Biobank cohort study.
and a specific medical treatment of the symptoms and functional physical limitations (tertiary prevention, specific health indicators).
The most pronounced effects of inpatient rehabilitation could be seen for the measurements of subjective complaints and ISI. More than two-thirds of the patients experienced significant improvements regarding symptoms and specific characteristics; however, 24.8% did not show significant changes, and 4.7% showed symptoms and specific characteristics that worsened from the beginning to the end of rehabilitation. Therefore, our findings indicate that not all patients can directly benefit from this treatment. Overall (MQOidx), rehabilitation therapy leads to improvement in the vast majority of patients (77.9%, SMD = 0.48 ± 0.37, dCohen = −1.22).
Despite the large international differences observed in kinds of rehabilitative health care teams and treatment measures, the observed effect sizes can support individual evaluation. It is also important to consider the medical focus, the rehabilitative practice, and performance profiles, as documented outcomes depend on different treatment programs and the associated uses of health care resources. The absolute values and individual profiles of the medical quality outcome should always be evaluated according to the given setting and at the doctor's discretion. Single measurements are subject to a variety of moderating influences and measurement errors. The presented continuous measures of MQOidx, therefore, have advantages in terms of their (scale) properties and sensitivity to frequently applied categorical criteria. When using the presented clinical values of the MQOidx, the monocentric character of the work has to be considered.
Due to the prescribed performance profiles and that assignment modalities are centrally controlled by the insurers, we can assume that the pre-rehabilitation values presented, and especially the changes in the MQO, are representative of the inpatient rehabilitation setting in Austria. Different individual baseline values must always be taken into account, as poorer outcome measurements at the beginning of rehabilitation are accompanied by greater potentials for improvement. Such improvement is, of course, statistically given if difference values (post − pre) are applied (eg, for MQOidx: rpre vs post−pre = −0.44).
The presented results suggest that the expected rehabilitation effects on the medical quality outcome are universal. Nonresponders still need to be more closely characterized.
Limitations
The practical significance of the Medical Quality Outcome or relationships with external criteria (endpoints), such as the incapacity for work, still needs to be investigated. To further develop research in this direction, it may be helpful to perform a global evaluation between medical outcome factors and socio-medical–relevant external criteria. One limiting factor is the lack of physical activity or cardiorespiratory fitness markers, which were not included in this study.
Which observed changes in medical outcome factors are significant to the sustainability of rehabilitative measures and the extent to which optimized treatment pathways can influence them, these are aspects that still need to be clarified. Improvements in 1 outcome may well be accompanied by the deterioration of other outcomes. Therefore, multidimensional approaches to quality outcomes should be taken.
For ethical, practical, and economic reasons, it was not possible to include a randomized control group in this study; for this reason, a nonrandomized waiting group was included in the study design, which was statistically controlled ex post facto (Supplemental Tables 5 and 6). Before rehabilitation was initiated and during the period after the surgery, activities and circumstances were not controlled. Therefore, causal conclusions must be drawn with caution. Patients do not usually enter rehabilitation immediately after their discharge from the hospital. We expected that the health of patients in a randomized control group would not improve without training and, at best, would remain stable.
However, the comparability and stability of the rehabilitation success between the different patient groups (Table 4 and Supplemental Table 5) and the constant (temporal) course of the nonspecific indicators (GHI) without rehabilitation treatment (see Figure 2) provide evidence for the external validity of the study.
Conclusions and Implications
Rehabilitation plays a vital role in preventing and minimizing the functional limitations associated with aging and chronic conditions. Results of multiple individual medical outcomes from larger samples of patient data for different diagnoses are unavailable. We define 2 general medical success indicators for multidisciplinary rehabilitation that can be obtained from routine documentation: a general and a disease-specific health indicator. These main components show similar improvements due to rehabilitation across different indications, but behave differently during the time delay between surgery and inpatient medical rehabilitation. Rehabilitation contributes to the greatest positive changes in older patients (>60 years) and during the early rehabilitation stage. The medical outcome factors presented in this work represent valuable adjuncts to the assessment of the quality of medical outcomes.
Data Availability Statement
The datasets analyzed and referred to in this manuscript are not publicly available. The authors can provide descriptive data on individual medical indicators for admission and discharge or the expected change due to inpatient rehabilitation for various groups and diagnoses upon request. Requests to access anonymized datasets should be directed to corresponding author.
Acknowledgments
The authors thank the Humanomed Group and their colleagues and the Medical University of Graz as well as the Human Research Institute for their support in the development and execution of this study. The Division of Physiology, Otto Loewi Research Center for Vascular Biology, Immunology and Inflammation and the Doctoral School for Lifestyle-Related Diseases of the Medical University of Graz have provided financial support for the open access publication.
Author Contributions
Each author of our work was significantly involved in the conception, design, data acquisition, data analysis, and interpretation. All authors contributed to the writing of the manuscript and have released the final version for publication. All authors take responsibility for the accuracy and integrity of all aspects of research. The individual authors had the following respective main tasks:
1.
Study concept and design: VG, AU, EB, MMu, HP, WM, EM, and WK
2.
Acquisition of data: EB, HP, and MMu
3.
Analysis and interpretation of data: VG, HP, WM, EM, WK, SH, PH, HL, and MMo
4.
Drafting of the manuscript: VG, AU, PH, and MMo
5.
Critical revision of the manuscript for important intellectual content: HP, WM, EM, WK, SH, PH, HL, MMo, and NG.
Based on the value distributions, the individual outcome parameters were transformed into z-values, which allowed a conversion into percentiles. By means of z-standardization, differently scaled quantities were summarized, and the changes were uniformly quantified. A value of 50% (median) or a z-value of zero corresponded to the representative mean of admission and discharge data of all patients at the clinical trial center. Difference values with no significant changes normally range randomly from 0.00 ± 0.20. Changes between admission to discharge are revealed by examining the effect sizes and the number of patients (n [%]), which could be improved in clinically relevant ways (categorical presentation: better, equal, worse). The threshold used was an average z-difference (SMD) of >0.20 for unspecific general health parameters and for disease-specific parameters. A larger positive z-value or a negative percentile corresponds to a below-average (worse) value in the sample. Negative z-differences generally correspond to an improvement.
Statistical data processing was performed using IBM (Armonk, NY) SPSS Statistics (version 22). The statistical analysis included parametric methods such as multifactorial variance analyses for repeated measurements and the calculation of Pearson correlations. Individual missing values were not replaced for the per-protocol analysis. The specification of P values was given a lower priority, and instead effect sizes (partial Eta2 [ηp2] and standardized mean differences [SMD]) were used. The representation of the ηp2 was chosen because very small numerical differences became statistically significant even if they were not relevant in terms of content and clinical relevance. An ηp2 that ranges from 0.01 to 0.06 corresponds to a small effect. Ranges of 0.06 to 0.14 correspond to a middle effect, and values >0.14, to a large effect.
Example calculation
The following is an example calculation for the ISI in orthopedic rehabilitation.
Standard scores, also called z-values (z), are calculated by subtracting the (population) mean (μORT) from an observation (X−̅pre or X−̅post) and dividing this difference by the standard deviation seen for all orthopedic patients at admission and discharge (SDμ). As shown in the results section, deviations from zero and respectively mean differences in z-values (SMD) can be interpreted as an effect size (cf. Cohen's d). The values were placed along an axis so that a positive absolute z-value corresponded to a below-average (worse) value in the sample and a negative z-difference corresponded to an improvement. A z-value of zero corresponded to the mean value of pre and post values and for SMD no significant changes between pre versus post were seen.
The “Specific Ortho Index” (ISIORT; see Table 1) corresponds to a z-normalized mean of the “activities of daily living” (ADL-Score out of EQ-5D), “motoric function” (Roland-Morris, WOMAC or Constant-Murley, depending on the affected body region) and the “physical ability” (walking tests).
The ADL-Score (sum score for EQ-5D) measured on admission to the orthopedic rehabilitation program (X−̅pre) was 75.29 ± 15.40 [0–100] versus 84.54 ± 14.16 after rehabilitation (X−post). Pre- and post-scores together result in a value range of 79.77 ± 15.68 (μORT ± SDμ) for orthopedic patients. Hence, the standardized z-difference (SMD = zpost − zpre) was 0.305 to −0.286 = 0.59 (∗ −1; along axis). For example, a healthy person would have an ADL score of approximately 97.5. Therefore, the corresponding z-value would be 1.13 (∗ −1). This is a big difference, encompassing nearly 1.5 standard deviations (0.29 to −1.13 = 1.42), as compared with orthopedic patients before rehabilitation.
For Roland and Morris Disability (back patients), the value range was 6.83 ± 5.39 [0–24] with an SMD of −0.59 (corresponding to an improvement of: SMD ∗ SDμ = −0.59 ∗ 5.39 = −3.18 units), for WOMAC (hip and knee patients) 57.53 ± 42.13 [0–240] with an SMD of −0.78, for Constant Score (shoulder patients) 50.04 ± 19.75 [0–100] with an SMD of 0.91 (∗ −1; along axis) and for a time required to rise and move (Timed Up and Go Test) of 9.72 ± 5.71 [seconds] or complete a 10-m walking test of 8.57 ± 4.57 [seconds] with an SMD of −0.45 or −0.43.
The indication-specific outcome for orthopedic patients (ISIORT) is the aggregated mean z-difference of these ortho-specific outcome measurements: mean (ADL, motoric function, walk tests) = (−0.59 + [(−0.59 ∗ n1 + −0.78 ∗ n2 + −0.91 ∗ n3)/n1–3] + [−0.45 + −0.43]/2)/3 = (−0.59 + −0.73 + −0.44)/3 = −0.59 (see Table 4).
The general health outcome for orthopedic patients (GHIORT; cf. formula Supplementary Table 3) was −0.45, so the MQOidx is equal to the mean z-differences (GHI, ISI) = (−0.59 + −0.45)/2 = −0.52. If the GHI is calculated for a healthy person with a BMI of 22 kg/m2, a waist circumference of 85 cm, a resting blood pressure of 119/79 mm Hg, a resting heart rate of 70 bpm, a VAS (pain score) of 0.5 [0–10] and a self-rated health of 95% (EQ-VAS; [0–100]), results of MED1 = −1.10, MED2 = −0.33, MED3 = −1.47 and a GHI = −0.97 are obtained; yielding a z-score of approximately −1 (corresponding to a difference >1 SD to the baseline rates of rehabilitation patients).
Supplemental Fig. 1Changes due to rehabilitation in summarized factors of medical outcome indicators, depending on the subjects' ages. Age contributed significantly to the pre-rehabilitation data, which were lower within general than within specific parameters. Improvements in older subjects were equal or even stronger than in younger patients, especially in terms of specific health indicators. Changes due to inpatient rehabilitation were strong in all age groups (N = 16,966).
Supplemental Fig. 2Improvements in overall MQO depending on indication (color) and age (abscissa). All rehabilitation types were medically successful and improved the patients' conditions by an average of −0.48 ± 0.37 (MQOidx; N = 16,966). The strongest increase in improvement with age was observed for the orthopedic, followed by cardiovascular and oncologic rehabilitation patients. Metabolic rehabilitation seemed to yield the best results for patients aged 41 to 50. The effects of pulmonary and metabolic rehabilitation did not show clear associations with age.
Supplemental Fig. 3Age distribution of the sample. From the age of 40, the inpatient rehabilitation of patients with chronic diseases in the study center increased significantly. There are 3 age peaks near 60, 70, and 80 years. In general, there was no patient exclusion for statistical analysis except for the control group calculations, in which only patients with a defined starting point (surgery) and the same diagnosis were taken into account (cf. Supplemental Table 6).
Influence of Age: ICD: ηp2 = 0.144, Sex: ηp2 = 0.004, Sex × ICD: ηp2 = 0.007; number of diagnoses: ICD: ηp2 = 0.382, on sex: ηp2 = 0.000, sex × ICD: ηp2 = 0.005; no. of diagnoses female 1.56 ± 0.72, male 1.53 ± 0.79.
ICD-10 diagnoses are dependent on age (diagnosis explained by age: ηp2 = 0.144, P < .001) and are related to the number of additional diagnoses (ηp2 = 0.382, P < .001). Of all patients, 57.4% have 1 ICD-10 diagnosis; 33.3%, 2 diagnoses; 7.0%, 3 diagnoses; and 2.2%, 4 or more diagnoses on admission (mean number of diagnoses: 1.55 ± 0.75). The most frequent diagnoses at the study center are chronic ischemic heart disease, osteoarthritis of the knee and hip, chronic obstructive pulmonary disease, dorsalgia, and malignant neoplasm of the breast. Orthopedic patients with fractures of the femur (S72), spondylopathies (M48), and osteoarthritis of the knee and hip were older, as well as patients with nonrheumatic aortic valve disorders (I35), interstitial pulmonary diseases (J84), and malignant neoplasm of the bladder (C67). Younger patients were more frequently diagnosed with dorsalgia and disc disorders, asthma, and malignant neoplasm of the breast. Sex played a minor role regarding the types of diagnoses (ηp2 < 0.01), with the exception of the oncological area and for J84, I25, and I48.
Post-OP Time: Time From Surgery (OP) to Rehabilitation Phase II, d
OP
Total No. % With OP
≤42 (6 wk)
43–70
71–105
106–366
>1 y
Mean
SD
Orthopedic
M17
no.
661
391
253
152
16
66.4 ± 105.8
1473
1584
Osteoarthritis of knee
%
44.9
26.5
17.2
10.3
1.1
20.7
93.0
M16
no.
533
403
199
124
23
67.4 ± 111.8
1282
1359
Osteoarthritis of hip
%
41.6
31.4
15.5
9.7
1.8
18.0
94.3
M54
no.
14
37
59
85
26
203.9 ± 366.3
221
1087
Dorsalgia
%
6.3
16.7
26.7
38.5
11.8
3.1
20.3
M51
no.
23
97
103
141
19
136.9 ± 247.7
383
724
Thoracic, tl., and Is. Iv. disc disorders
%
6.0
25.3
26.9
36.8
5.0
5.4
52.9
M75
no.
165
195
105
134
16
91.9 ± 134.0
615
711
Shoulder lesions
%
26.8
31.7
17.1
21.8
2.6
8.6
86.5
S72
no.
47
80
68
62
10
102.1 ± 114.1
267
277
Fracture of femur
%
17.6
30.0
25.5
23.2
3.7
3.8
96.4
S82
no.
7
39
86
96
10
149.2 ± 201.0
238
276
Fracture of low er leg, including ankle
%
2.9
16.4
36.1
40.3
4.2
3.3
86.2
M19
no.
46
75
52
45
9
122.6 ± 299.0
227
275
Other and unspecified osteoarthritis
%
20.3
33.0
22.9
19.8
4.0
3.2
82.5
M48
no.
15
34
81
82
8
119.9 ± 103.7
220
261
Cardiovascular
Other spondylopathies
%
6.8
15.5
36.8
37.3
3.6
3.1
84.3
I25
no.
731
273
306
468
29
85.6 ± 153.6
1807
2397
Chronic ischemic heart disease
%
40.5
15.1
16.9
25.9
1.6
25.4
75.4
I35
no.
187
28
27
32
2
50.6 ± 114.0
276
319
Nonrheumatic aortic valve disorders
%
67.8
10.1
9.8
11.6
0.7
3.9
86.5
I42
no.
6
11
15
25
1
119.1 ± 77.6
58
142
Cardiomyopathy
%
10.3
19.0
25.9
43.1
1.7
0.8
40.8
I48
no.
9
5
12
9
0
95.2 ± 75.2
35
119
Atrial fibrillation and flutter
%
25.7
14.3
34.3
25.7
0.0
0.5
29.4
OP (41.9% of sample)
no.
2444
1668
1366
1455
169
89.3 ± 161.6
7102
9531
Orthopedic & cardiac diagnoses
%
34.4
23.5
19.2
20.5
2.4
100.0
74.5
Orthopedic patients who had undergone knee, hip, or shoulder surgery and cardiovascular patients with chronic ischemic heart disease and nonrheumatic aortic valve disorders progressed from phase I to phase II within 10.7 ± 18.4 weeks on average. This subsample of patients formed a quasi-experimental waiting group via different onsets for inpatient rehabilitation (cf. Supplemental Table 6).
Supplemental Table 3Factor Formation for General Health Outcome
Principal Component Analysis Varimax With Data of Admission and Discharge (60,844 Measurements in 33,501 Patients)
Factor
Parameter
Communality
Loading (Rotated)
% VAR
Beta-coefficient
Regression
MED 1 [z]: SHAPE
BMI [kg/m2]
0.931
0.958
0.516
MED1 = −6.249 +
WC [cm]
0.933
0.957
32.259
0.509
BMI ∗ 0.095 + WC ∗ 0.036 R = 0.991
MED 2 [z]: CARDIOVASCULAR
RRsys [mm Hg]
0.737
0.857
0.517
MED2 = −11.730 + RRdia ∗ 0.069
RRdia [mm Hg]
0.752
0.842
18.811
0.551
+ RRsys ∗ 0.040 + RP ∗ 0.017
RP [bpm]
0.141
0.327
0.21
R = 0.988
MED 3 [z]: SUBJECTIVE
VAS [cm; 0–10]
0.64
0.799
0.614
MED3 = 1.723 +
EQ-VAS [%; 0–100]
0.642
−0.795
17.165
−0.607
VAS ∗ 0.255 + EQ-VAS ∗ −0.035 R = 0.987
General Health Index
GHI
mean MED1, MED2 and MED3
three factors
68.24% VAR
EQ-VAS, self-rated health (0–100); RP, resting heart rate; VAS, Visual Analog Scale (Pain; 0–10); RRsys/dia, blood pressure systolic/diastolic; WC, waist circumference.
High (positive) values [z] correspond to a worse expression.
Principal component analysis (PCA) with 68.24% explained variance (VAR); MED1: 32.26%, MED2: 18.81%, MED3: 17.17%. General health outcomes build 3 factors, which were combined to an overall result, the GHI. There are no multiple loadings on other factors. The factor structure is stable in terms of content and time: PCA with admission, discharge, or difference values (discharge vs admission) or factor solutions within one indication show similar results. ∗Retest reliability: rMED1 = .985, rMED1 = .320, rMED1 = .678, rGHI = .731.
General effects of inpatient rehabilitation stay are calculated on the basis of monocentric normative data from the study center, including all patients who underwent a 3- to 4-week inpatient medical rehabilitation. The selection of clinical parameters complies with the requirements of Main Association of Austrian Social Security Institutions in the performance profiles of accredited Austrian institutions regarding the quality of results, which should guarantee a comparable medical service quality standard. The GHI was calculated by summarizing the clinical data of all patients from different indications.
Within-factor time (mean z-difference = post − pre): all P < .001 (N = 16,966).
time (ηP2)
≤40
−0.12 ± 0.55
−0.41 ± 0.36
[−0.44 to −0.39]
0.564
Overall
41–50
0.04 ± 0.57
−0.44 ± 0.36
[−0.46 to −0.43]
0.598
MQOidx
51–60
0.14 ± 0.55
−0.46 ± 0.36
[−0.47 to −0.45]
0.623
GHI & ISI
61–70
0.22 ± 0.55
−0.49 ± 0.37
[−0.51 to −0.48]
0.643
71+
0.38 ± 0.57
−0.51 ± 0.39
[−0.52 to −0.50]
0.627
Medical Quality Outcome (MQOidx)
0.20 ± 0.57
−0.48 ± 0.37
[−0.48 to −0.47]
0.622
≤40
−0.10 ± 0.71
−0.46 ± 0.51
[−0.49 to −0.42]
0.447
Disease-specific
41–50
−0.02 ± 0.73
−0.44 ± 0.52
[−0.46 to −0.41]
0.416
(cf ISI Tab 1)
51–60
0.08 ± 0.71
−0.46 ± 0.50
[−0.48 to −0.45]
0.461
61–70
0.23 ± 0.77
−0.52 ± 0.51
[−0.53 to −0.50]
0.504
71+
0.57 ± 0.84
−0.57 ± 0.57
[−0.59 to −0.56]
0.501
Indication-Specific Index(isi)
0.23 ± 0.80
−0.50 ± 0.53
[−0.51 to −0.49]
0.475
≤40
−0.15 ± 0.67
−0.37 ± 0.43
[−0.40 to −0.34]
0.423
41–50
0.10 ± 0.71
−0.45 ± 0.45
[−0.47 to −0.43]
0.499
General
51–60
0.20 ± 0.67
−0.47 ± 0.46
[−0.48 to −0.46]
0.511
61–70
0.22 ± 0.61
−0.47 ± 0.46
[−0.48 to −0.46]
0.510
71+
0.20 ± 0.57
−0.44 ± 0.46
[−0.46 to −0.43]
0.481
General Health Index(ghi)
0.17 ± 0.64
−0.45 ± 0.46
[−0.46 to −0.45]
0.497
Age contributed a significant amount to baseline (pre-rehabilitation) states but played a minor role in altering medical outcome indicators. Older patients (>60 years) showed equal or even more favorable symptom-specific outcomes. Younger patients (<51 years) showed better baseline values in all medical indicators.
The averaged medical quality outcomes across all age groups are highlighted in bold.
MQO, medical quality outcome.
∗ Pre-rehabilitation values (pre) at the beginning of rehabilitation for monocentric normative data from the study center (cf. Table 4).
† Standardized average improvement (z-difference) from admission (pre) to discharge (post).
‡ Within-factor time (mean z-difference = post − pre): all P < .001 (N = 16,966).
Interaction of within-factor time (post, pre; improvements from admission to discharge) with categorization of timing of rehabilitation (between factor: “post-OP”).
GHI
.003
.002
.006
.003
.003
.003
.007
.012
.001
.004
.069
.009
0 to +
Time × post-OP
ISI
.062
.042
.070
.061
.054
.085
.084
.047
.070
.087
.049
.094
++
Effects time (2-stage)
within
Main effect (post vs. pre)
GHI
.486
.488
.485
.475
.494
.516
.519
.540
.522
.451
.347
.437
+++
Time (unifactorial)
ISI
.534
.500
.555
.584
.499
.639
.630
.640
.634
.354
.520
.375
+++
Multivariat (GHI & ISI)
.651
.644
.657
.664
.645
.708
.701
.715
.706
.563
.614
.568
+++
The time delay between surgery and rehabilitation (factor “post-OP”) played a minor role for general health indicators (pre: ηp2GHI = 0.009, P < .001; post: ηp2GHI = 0.005, P = .001), whereas specific indicators improved after surgery, even without rehabilitation (pre: ηp2ISI = 0.042, P < .001). If initial values (pre) were not taken into account, the absolute values (outcome indicators) at the end of rehabilitation (post) were only slightly influenced by the timing of the rehabilitation (cf. post: ηp2 ∼ 0.01). Interaction time × post-OP showed that changes occurred in the general factor independent of the time of rehabilitation (time × post-OP: ηp2GHI = 0.003, P = .084), differing from the disease-specific outcome characteristics (ISI), for which the time of onset (post-OP week) played a more important role (ηp2ISI = 0.063, P < .001). The within effect “time” (post vs pre; rehabilitation success) was strong in all subsamples (all ηp2 > 0.35, P < .001), whereby the comparison with the quasi-experimental control group between patients (untreated control group: n1 = 4577; treated rehabilitation patients: n2 = 5161) showed a methodologically lower effect size (ηp2GHI = 0.141, ηp2ISI = 0.120, ηp2multivariat = 0.186, all P < .001; cf. Figure 2) and an identical SMD (SMDGHI of −0.45 [−0.47 to −0.43], P < .001 and SMDISI of −0.52 [−0.55 to −0.49], P < .001, N = 5453; cf. Figure 2). Therefore, these results were evaluated as stable and reliable, as they apply equally to all patient (sub-) groups. The outcomes (interaction: time × post-OP) were found to be almost equally for orthopedic and cardiovascular patients (indication × post-OP week: ηp2multivariat = 0.005, P < .001) and roughly the same for all patient (sub) groups (by sex and diagnoses). The ages of the patients had a minor influence on the effect sizes with regard to the timing of rehabilitation (factor “post-OP”), as these seemed to be more pronounced in older patients (60+: ηp2post-OP = 0.050, P < .001, for pre-rehabilitation measurements and ηp2time × post-OP = 0.070, P < .001, for changes vs. for patients ≤60 years: ηp2post-OP = 0.018, P < .001, ηp2time × post-OP = 0.042, P < .001).
Subsample of patients with M16, M17, M75, or I25, I35 diagnosis and previous surgery (n = 5453; cf. Supplemental Table 6); indication: orthopedic (ORT) versus cardiovascular (CAR) patients.
Categorization effect size: 0, no (significant); +, small (significant); ++, middle; +++, strong.
† Baseline data (pre-rehabilitation; absolute values of outcome indicators) at the beginning of rehabilitation.
‡ Interaction of within-factor time (post, pre; improvements from admission to discharge) with categorization of timing of rehabilitation (between factor: “post-OP”).
These orthopedic patients (M75) are on average 10 years younger than patients with an M16 or M17 diagnosis.
ORT
Mean ± SD
Female (no.)
I25
I35
CAR
Mean ± SD
Female (no.)
≤3
876
66.8 ± 10.3
317
132
109
47
288
68.3 ± 10.0
162
428
160
588
66.0 ± 10.4
155
3–6
1401
66.4 ± 10.7
680
529
424
118
1071
67.5 ± 10.3
596
303
27
330
63.1 ± 11.3
84
6–9
1024
64.8 ± 11.3
487
311
328
160
799
64.8 ± 11.2
419
206
19
225
64.9 ± 11.6
68
9–12
661
64.4 ± 11.3
278
182
175
84
441
64.8 ± 10.9
221
202
18
220
63.6 ± 12.0
57
12–15
495
64.4 ± 11.8
206
151
99
56
306
64.3 ± 11.6
153
171
18
189
64.4 ± 12.1
53
15–18
384
65.0 ± 11.5
163
73
64
43
180
63.8 ± 11.4
100
189
15
204
66.0 ± 11.6
63
18–21
220
63.5 ± 11.3
78
35
32
31
98
62.7 ± 10.5
54
117
5
122
64.1 ± 11.9
24
21–24
100
64.3 ± 10.7
32
16
7
22
45
62.6 ± 11.3
18
52
3
55
65.7 ± 10.0
14
24–27
292
63.4 ± 11.3
116
44
44
54
142
61.7 ± 11.5
65
139
11
150
65.0 ± 10.9
51
Total
5453
65.3 ± 11.1
2357
1473
1282
615
3370
65.6 ± 11.0
1788
1807
276
2083
64.8 ± 11.3
569
Older orthopedic patients tended to start rehabilitation earlier (factor postsurgery week “post-OP” × indication for age: ηp2 = 0.010, P < .001) and earlier than cardiovascular patients (mean difference ORT vs. CAR: 9.5 ± 3.5 days, ηp2 = 0.001, P = .013; cf. Supplemental Table 2). No significant sex differences were observed that correlated with timing of rehabilitation (ηp2 = 0.000, P = .547).
Average improvement (percentile) from admission to discharge; N = 16,966; 46.4% female, 53.6% male.
≤40
16.7
74.3
22.0
3.6
12.5 ± 10.9
41–50
8.8
75.4
22.0
2.6
12.9 ± 10.5
Overall GHI and ISI
51–60
3.9
77.9
19.5
2.6
13.7 ± 10.6
61–70
−0.1
78.6
19.3
2.0
14.5 ± 10.9
71+
7.9
79.2
18.4
2.4
14.7 ± 11.2
Medical Quality Outcome(MQOidx)
1.0
77.9
19.6
2.5
MQOIndex: 14.0 ± 10.9
≤40
13.8
67.8
26.3
5.9
13.9 ± 15.2
41–50
10.7
65.6
28.6
5.8
13.0 ± 14.9
Disease-specific
51–60
7.1
69.3
25.5
5.2
13.9 ± 14.5
61–70
1.8
71.5
24.8
3.7
15.3 ± 15.0
71 +
−10.2
73.6
22.0
4.4
16.1 ± 15.7
Indication-Specific Index(isi)
1.9
70.5
24.8
4.7
ISI: 14.7 ± 15.1
≤40
14.5
67.6
23.5
8.9
11.1 ± 12.6
41–50
3.9
71.4
22.1
6.5
12.8 ± 12.8
General
51–60
−0.7
72.6
20.9
6.5
13.6 ± 13.2
61–70
−1.4
72.1
21.4
6.5
13.7 ± 13.4
71 +
−0.6
70.1
22.9
7.0
13.4 ± 13.6
General Health Index(ghimed1–3)
0.5
71.4
21.8
6.8
GHI: 13.3 ± 13.3
Threshold for classification (better, equal, worse) z-diff. (SMD) > 0.20
Alternative presentation of results to Table 4 and Supplemental Table 4. Changes between admission to discharge are revealed by the number of patients (%) who could be improved in clinically relevant ways (categorical presentation: better, equal, worse). The threshold used was an average z-difference (SMD) of >0.20. A negative percentile corresponds to a below-average (worse) value in the sample. Based on the value distributions, z-values were converted into percentiles for the calculation of improvements (post − pre). Aggregated medical outcome factors (GHI and ISI) showed a clear success (SMD > 0.20) in 77.9% of patients during the rehabilitation stay. The total mean percentile difference was 14.0 ± 10.9, which corresponds to a SMDMQOidx of −0.48 ± 0.37 (95% CI [−0.48 to −0.47], ηp2 = 0.622, P < .001; Table 4). The indication (upper part of the table) and age (lower part of the table) played a decisive role for the baseline values, but generally had a much smaller impact on their improvements (cf. Table 3). The extents of improvement observed in the medical outcome and the effect size (as percentiles) are similar in all areas.
NOTE. The summarized medical quality outcomes for all indications are highlighted in bold.
∗ Premeasurements at the beginning of rehabilitation: A negative percentile corresponds to a below-average (worse) value in the total sample.
† Average improvement (percentile) from admission to discharge; N = 16,966; 46.4% female, 53.6% male.
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