The Effect of A New Perioperative Practice Model on Patient, Nursing And Organisational Outcomes
Phase: NA
Conditions: Arthroplasties, Hip Replacement, Arthroplasties, Knee Replacement
Sponsor: Hospital District of Helsinki and Uusimaa

Title page: 
 
 
Title of the study:  
The effect of A New Perioperative Practice Model on Patient, Nursing and Organisational Outcomes 
Registration number: NCT02906033 
Last updated: August 4, 2021 
The online addresses of the publications concerning this study: 
https://doi.org/10.1002/nop2.776  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Study Protocol: 
 
 
Background  
 
Earlier research findings show that when a caring encounter is established where the nurse informs the 
patient about the perioperative process and its proceedings and educates the patient, a significant impact 
on both postoperative pain and the recovery from surgery can be achieved (Bager et al. 2015, Bailey 2015, 
Johansson et al. 2014). Also, anxiety increases the postoperative pain and slows down the recovery from 
surgery (Marks 2015). An earlier investigation comparing recovery of general surgery patients to 
orthopedic patients showed that overall, the orthopedic patients were less recovered in the acute 
recovery phase as well as after one month postoperatively. The most common reason for slow recovery 
was pain, which was ranked high in the acute recovery phase for both orthopedic and general surgery 
patients. The authors state that support for the orthopedic patients must be improved (Forsberg et al. 
2015).  
 
An investigation conducted by McHugh et al. (2013) revealed that patients experience improvement in 
psychosocial and biomedical outcomes at six months after hip replacement. The strongest predictors of 
recovery were anxiety and depression, pain, previous joint surgery and taking pain medication. By 
recognizing these factors nurses are able to identify and provide more support for patients at risk of poor 
recovery after hip replacement.  
 
Mandzuk et al. (2015) conducted a longitudinal retrospective study with total hip replacement and total 
knee replacement patients (N=851). The study examined self-reported quality of life and functional status 
over the preoperative and postoperative periods: the measurements were taken 12 months prior to 
surgery, one month prior to surgery and 12 months postoperatively. The results revealed that patients 
who had a total hip replacement tended to demonstrate higher improvement than total knee 
replacement patients. Male patients reported higher levels of physical and mental quality of life as well 
as functional status than women. Mental health scores were consistently lower in both hip replacement 
and knee replacement patients across the perioperative period and up to one year postoperatively 
compared to the reference values utilizing the SF-12 instrument (Ware et. al 1996). Thus, there is an 
opportunity for health care providers to proactively address the mental health of hip and knee 
replacement patients throughout their joint replacement trajectory. The nurses’ preoperative assessment 
may be useful in identifying and defining patients’ risk factors not only for surgery but for the entire 
perioperative care. The nurse’s role in the preoperative assessment is that of an advocate who identifies 
the patient´s needs and risk factors that may be affected by the surgical experience (Malley et al. 2015). 
The shortened hospital stays nowadays require optimizing assessment and care management by focusing 
on patients’ greater health care needs and by tailor made care information and skills to patients’ individual 
needs (Su et al. 2010). 
 
This research follows a pilot study, where a new perioperative model of caring was tested with patients 
(n=19) undergoing a hip or a knee replacement surgery under spinal anesthesia (Pulkkinen et al. 2015). In 
this new model the one and same anesthesia nurse took care of the patient during the entire perioperative 
process (pre-, intra- and postoperative phase) and visited the patient to the surgical ward the next day 
after surgery. The study findings showed that the patients experienced the new model of perioperative 
care as beneficial. Patients experienced that they were taken seriously and that they had the opportunity 
to participate in their own care. They also experienced the emotional support important. Thus, the new 
model had influence on patient satisfaction and on the individual care. The patient safety was even 

ensured; no complications or medical errors were reported concerning the patients in the study sample. 
The same nurse cared for the patient during the entire perioperative process, and this might have 
diminished the possibilities for occurring errors. For example, the reduced information transfer increases 
the patient safety (WHO 2007). 
 
There are several concerns in current specialized health care that this research will address. The length of 
hospital stay has shortened; thus, the patients must feel safe to cope with their recovery at home. Earlier 
research findings show that when a caring encounter is established where the nurse educates the patient 
about the perioperative process has significant impact on both postoperative pain and the recovery (Bager 
et al. 2015, Bailey 2015, Johansson et al. 2014. Also, the new health care legislation in Finland gives the 
patients right to choose the place of care. Therefore, patient satisfaction is an important part of 
organizations’ competitiveness. This research deals with a high-volume hospital service. Altogether the 
amount of surgical procedures performed in Finland during 2015 was 362 552 (Sjöholm/Kuntaliitto 2016). 
Further, the health care organizations have to deal with lack of nursing resources. This new practice may 
influence engagement of nurses. 
Aim and objectives 
 
The aim of this study is to improve the surgical patients’ care process. The objective is to explore the effect 
of a new perioperative practice model on 1) patient outcomes (satisfaction, surgery-related anxiety and 
quality of life), 2) nursing outcomes (organizational engagement), and 3) organization outcomes (timeline 
of surgical care process). 
 
The study is part of Dr. Junttila’s Post doc research project “Knowledge-based management in 
perioperative nursing”. At the same time it links to professor Lindwall’s research projects concerning the 
Perioperative Dialogue. 
 
Methods 
 
Study design 
 
A longitudinal untreated control group design with pre- and posttests will be followed. 
 
Study sample and setting 
The study will be conducted at the Helsinki University Hospital; more specifically at the operating 
department K of the Peijas Hospital. The study population consist of adult female and male patients 
scheduled for either total hip arthroplasty (THA) or total knee arthroplasty (TKA). A control group and an 
experimental (intervention) group will be formed. The participants are recruited at their preoperative 
visits to the outpatient clinic two to three weeks prior to their scheduled operations. The inclusion criteria: 
18 years of age or older, able to comprehend the study information and complete the questionnaires, and 
operation being performed under spinal anesthesia. One exclusion criterion for the intervention group is 
that the planned surgery is performed on Friday, because the postoperative visits cannot be performed 
during the weekend. 
 
 

Randomization and sample size  
Randomization of participants is performed by independent third parties (two nurse assistants at the 
outpatient clinic). All patients scheduled for THA and TKA attending the outpatient clinic are considered 
eligible and invited to participate in randomization if they meet the inclusion criteria. Eligible patients will 
draw one of two cards; one indicate an invitation to participate the study and the other is  blank, indicating 
no participation in the study. Patients in the control group will be  recruited every other week and patients 
for the intervention group every week between. This pattern will be repeated until the desired number 
of patients are recruited. This stratification will ensure that patients in different groups do not exchange 
information in the postoperative ward. The sample size requirement for comparing two means was 
checked with power analysis (2-sided test) with α = 0.05, β = 0.9, standard deviation 0.08, and differences 
of means 0.03 in 15D scores, which is within the slight difference of 0.015-0.035 (Alanne, Roine, Räsänen, 
Vainiola, & Sintonen, 2015).   A sufficient sample size is determined to be 152 per group.   
Intervention 
Traditionally during the intra- and postoperative phases of surgical care, the patient is cared for by several 
nurses; i.e. by an anesthetic nurse in the operating room and by a recovery room nurse in the Post 
Anesthesia Care Unit (PACU). Furthermore, the pre- and postoperative visits to the surgical patients are 
rare in Finland; mainly due to resources and new surgical processes where patients arrive to the hospital 
in the morning of the scheduled procedure.  
The new perioperative practice model denotes that the one and same nurse will meet the patient at 
his/her arrival to the operating department, and will care for the patient both in the operating room and 
in the PACU. Thus, the nursing care in the operating room and in the PACU remains the same but will be 
organized in a new way which focuses on the patient centered individual care and the continuity of care. 
Furthermore, the same nurse will visit the patient at the surgical unit on the first postoperative day.  
Data collection and Outcome Measures 
The demographic data of the participants includes age, gender, diagnosis, procedure, and ASA class (ASA 
Physical Status Classification 2014). Further patient data will be collected by 1) The Good Perioperative 
Nursing Care Scale (Leinonen & Leino-Kilpi 2001) measuring the quality of perioperative care; 2) 15D 
instrument measuring the health-related quality of life among adults (Sintonen 2001) and 3) STAI, the 
State-Trait Anxiety Inventory; measuring anxiety in adults (Spielberger et al. 2010). The schedule for 
patient data collection is presented in Table 1. 
Table 1. Schedule of patient data collection 
Instrument
Baseline (preoperative 
visit 2-3 weeks prior to 
surgery) 
Cross-section (at 
discharge) 
Post-test (three 
months after 
discharge) 
15 D
x
x
STAI
x
x

Good 
Perioperative 
Nursing Care Scale 
x
 
Primary Outcome Measures 
1. Change from baseline Health Related Quality of Life (HRQoL) at three months after the surgical 
procedure. Time Frame: Baseline 2-3 weeks prior to, and post-measurement 3 months after the 
procedure (The 15D instrument) 
Secondary Outcome Measures 
1. Change from baseline Surgery-related anxiety at three months after the surgical procedure. Time 
frame: Baseline 2-3 weeks prior to, and post-measurement 3 months after the procedure (The 
State-Trait Anxiety Inventory (STAI) 
2. Quality of perioperative care as experienced by surgical patients. Time frame: On average the 
third postoperative day, depending the time of discharge (Good Perioperative Nursing Care Scale) 
Ethical considerations 
The ethical codes and good scientific practice (TENK 2012) will be followed throughout the research. 
Participants will get written and oral information about the study, and a written informed consent will be 
asked. The participants will be informed about their right to decline from the study at any time, and they 
are told that this will not affect their care in any way. They also have the right to withdraw their consent 
in which case their data will not be used in the study. This clinical trial has been approved by the Operative 
(surgical) Ethical Committee of Helsinki University Hospital (decision number §16/27.7.2016). Permissions 
to use instruments (15D, STAI, Good Perioperative Nursing Care Scale) have been asked from the copyright 
holders. 
 
 
 
 
 
 
 
 
 
 
 
 

References 
Bager L, Konradsen H, Sander Dreyer P. 2015. The patient’s experience of temporary paralysis from spinal 
anaesthesia, a part of total knee replacement. Journal of Clinical Nursing, 24, 3503-3510. 
Bailey L. 2010. Strategies for Decreasing Patient Anxiety in the Perioperative Setting. AORN Journal 92 (4), 
445-457. 
Forsberg A, Vikman I, Wälivaara B-M, Engström Å. 2015. Patients’ perceptions of their postoperative 
recovery for one month. Journal of Clinical Nursing 24, 1825-1836. 
Johansson-Stark Å, Ingadottir B, Salanterä S, Sigurdadottir A, Valkeapää K, Bachrach-Lindström M, 
Unosson M. 2014. Fulfilment of knowledge expectations and emotional state among people undergoing 
hi 
replacement: 
A 
multi-national 
survey. 
International 
Journal 
of 
Nursing 
Studies. 
http://dx.doi.org/10.1016/j.ijnurstu.2014.03.006 
Sjöholm M. 2016. Sairaaloiden ja sairaanhoitopiirien tammi-joulukuu 2015. Yhteenveto kysynnästä, 
tuotannosta ja taloudesta. Kuntaliitto. 
www.kunnat.net/fi/kunnat/sairaanhoitopiirit/katsaukset/Sairaaloiden-jasairaanhoitopiirien-tammi-
joulukuu-2015.pdf 
 
Leinonen T, Leino-Kilpi H, Ståhlberg M-R & Lertola K. 2001. The quality of perioperative care: 
development of a tool for the perceptions of patients. Journal of Advanced Nursing 35, 294-306. DOI: 
10.1046/j.1365-2648.2001.01846.x 
 
Malley A, Kenner C, Kim T, Blakeney B. 2015. The Role of the Nurse and the Preoperative Assessment in 
Patient Transitions. AORN Journal 102(2) 181 e1-181e9. 
 
Mandzuk LL, MacMillan DE, Bohm ER. 2015. A longitudinal study of quality of life and functional status in 
total hip and total knee replacement patients.  International Journal of Orthopedic Trauma Nursing 
19(2), 102-113.  
 
Marks R. 2015. Anxiety and its impact on Osteoarthritis Pain: An Update. Journal of Rheumatic Diseases 
and Treatment. 1:2, 1-6. 
 
McHugh GA, Campbell M, Luker KA. 2013. Predictors of outcomes of recovery following total hip 
replacement surgery. Bone & Joint Research Journal 2(11), 248-254. 
 
Pulkkinen M, Junttila K & Lindwall L. 2016. The Perioperative Dialogue - A model of caring for the patient 
undergoing a hip or a knee replacement surgery under spinal anesthesia. Scandinavian Journal of Caring 
Sciences 30, 145-153. https://dx.doi.org/10.1111/scs.12233.  
 
Sjöholm M. 2016. Sairaaloiden ja sairaanhoitopiirien tammi-joulukuu 2015. Yhteenveto kysynnästä, 
tuotannosta 
ja 
taloudesta. 
Kuntaliitto. 
www.kunnat.net/fi/kunnat/sairaanhoitopiirit/katsaukset/Sairaaloiden-jasairaanhoitopiirien-tammi-
joulukuu-2015.pdf 
 

Spielberger CD. 2010. State-Trait Anxiety Inventory for Adults. http://www.mindgarden.com/145-state-
trait-anxiety-inventory-for-adults.  
Su H-H, Tsai y-F, Chen W-J, Chen M-C. 2010. Health care needs of patients during early recovery after total 
knee-replacement surgery. Journal of Clinical Nursing 19, 673-681. 
WHO 2007. Patient Safety Solutions. Volume 1, solution 3, May 2007. World Health Organization. 
Available at http://www.who.int/patientsafety/solutions/patientsafety/PS-Solution3.pdf.  
15D Instruments. www.15d-instrument.net. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Statistical Analysis Plan: 
 
Descriptive statistics will be used to present characteristics of the study participants. One- and multi-way 
analysis of variance will be used to compare means of groups. Interaction terms will be used to compare 
means of the groups defined by combinations of categorical independents. Tukey’s adjustment will be 
used to account for multiple comparison if necessary. Statistical significance of dependencies between 
categorical variables are tested using Chi-square tests. SAS® statistical software, version 9.4 (SAS Institute 
Inc., Cary, NC, USA) will be used in statistical analysis.  
In the analysis of the patient data, collected with the GPNCS, if a respondent answers to less than 50% of 
the quality statements, his or her response will be excluded from the analysis. Frequencies and 
percentages obtained with the Pearson chi-square test are calculated for the background data. Non-
parametric tests are used when comparing background factors with quality categories. The reliability of 
the scale is checked with a Cronbach’s alpha coefficient. In the analysis of data sets, the non-parametric 
tests will include the Kruskall-Wallis test and Mann Whitney U-test with Bonferroni corrections. A p-value 
of 0.05 is considered statistically significant.