To evaluate the effectiveness of an eHealth intervention on recovery and return to work, after gynaecological surgery.
To evaluate the effectiveness of an eHealth intervention on recovery and return to work, after gynaecological surgery.
Randomised multicentre trial that ran from March 2010 until September 2011.
Secondary care in seven general and university hospitals in the Netherlands.
A cohort of 215 women (aged 18–65 years) who had a hysterectomy and/or laparoscopic adnexal surgery for a benign indication.
The women were randomly assigned to the intervention group (n = 110) or the control group (n = 105). The intervention group received an eHealth programme that provided personalised tailor-made pre- and postoperative instructions on the resumption of daily activities, including work, and tools to improve self-empowerment and to identify recovery problems. The control group was provided with access to a control website.
The primary outcome was the duration of sick leave until a full sustainable return to work. Secondary outcome measures were quality of life, general recovery, and pain intensity.
In intention-to-treat analysis the eHealth intervention was effective on time to return to work (hazard ratio 1.43; 95% confidence interval 1.003–2.040; P = 0.048). The median duration of sick leave until a full sustainable return to work was 39 days (interquartile range 20–67 days) in the intervention group and 48 days (interquartile range 21–69 days) in the control group. After 26 weeks pain intensity was lower (visual analogue scale, cumulative odds ratio 1.84; 95% confidence interval 1.04–3.25; P = 0.035) and quality of life was higher (Rand-36 health survey, between-group difference 30, 95% confidence interval 4–57; P = 0.024) in the intervention group, compared with the control group.
The use of the eHealth intervention by women after gynaecological surgery results in a faster return to work, with a higher quality of life and less pain.
A delayed recovery and delayed return to work after surgery reduces the quality of life (QoL) of postoperative women, and generates unnecessary yet substantial costs for society.[1, 2] It has been reported that recovery and return to work time following (laparoscopic) gynaecological surgery frequently exceeds what can be reasonably expected from a medical perspective.[3-5] This has been explained by a substantial variation in convalescence recommendations regarding the resumption of work and daily activities between different healthcare providers, and by fragmented perioperative care.[6, 7] A strong need was therefore felt for the development of a stepped care programme to empower women during the perioperative period, with a special focus on recovery and return to work. Women that had undergone a hysterectomy (abdominal, vaginal, laparoscopic) and/or laparoscopic adnexal surgery for a benign indication were chosen as the target group for this new programme. Detailed multidisciplinary guidelines on well-defined postoperative recovery recommendations were developed in collaboration with the medical boards of gynaecologists, occupational physicians (OPs), and general practitioners (GPs) through a modified Delphi consensus method with experts and a literature study. To explore the needs, illness beliefs, preferences, and important behaviour determinants of women regarding recovery, perioperative care, and resumption of (work) activities, focus group discussions were performed with women who had undergone these procedures. Based on these data, an eHealth programme was developed aimed at empowering women during the perioperative period by supporting them with personalised tailor-made pre- and postoperative instructions on the resumption of work and daily activities, and tools to improve self-empowerment and identify recovery problems. The aim of the present study was to compare the effectiveness of the eHealth intervention with a control website on return to work, QoL, general recovery, and pain intensity, through a multicentre randomised controlled trial (RCT).
A randomised, single-blinded, controlled trial was carried out in six general and/or teaching hospitals and one university hospital located in the Netherlands. Women eligible to participate in this study were aged 18–65 years, were scheduled for laparoscopic adnexal surgery and/or hysterectomy for benign disorders, and were employed for at least 8 hours per week (paid or unpaid). The main exclusion criteria were: (1) malignancy or suspicion of malignancy; (2) pregnancy (intrauterine or ectopic); (3) deep infiltrating endometriosis; (4) concomitant surgical procedures or major health problems/psychiatric disorders affecting recovery or daily activities; (5) being signed off work for more than 4 weeks or – when the surgery aimed to cure the reason for the absence from work – being signed off work for more than 2 months; (6) working temporarily for an employment agency; (7) dealing with a lawsuit against the employer; (8) not able to understand or complete the questionnaires written in Dutch; and (9) no access to the internet. Participants were recruited from the waiting lists of participating hospitals and received an invitation letter to take part in the study. Consenting women who met all selection criteria, who completed the baseline questionnaire, and who were scheduled for surgery within 4 weeks were allocated to the intervention or control groups. A detailed description of the intervention and design of this multicentre RCT has been published elsewhere.
Participants allocated to the control group received access to a control eHealth intervention, besides the usual health care. This website provided the women with the telephone numbers of their hospitals and with patient leaflets from the Dutch Society of Obstetrics and Gynaecology (NVOG), which amounts to almost all of the leaflets provided in Dutch hospitals for a hysterectomy or a laparoscopic adnexal surgery for a benign indication.[12, 13]
|eHealth intervention (from 4 weeks before to 7 weeks after surgery)||Control eHealth intervention (from 4 weeks before to 7 weeks after surgery)|
|Detailed personalised pre- and postoperative instructions on the resumption of work and daily activities||Usual care given by gynaecologists, occupational physicians, and general practitioners|
|Extensive list of answers to the most frequently asked questions about the applied surgical procedure and practical issues, with pictures||Patient leaflets of the Dutch Society of Obstetrics and Gynaecology concerning the applied surgery|
|Evaluation of complications, with online feedback from the gynaecologist if necessary||Telephone numbers of participating hospitals|
|Instructional video for employee and employer to illustrate common pitfalls during the perioperative and reintegration period|
|Advice for employee and employer about a successful work reintegration|
|Evaluation of recovery and advice on which care provider or providers to approach in case of problems|
|Forum enabling contact with other patients|
|Links to other relevant websites|
|Glossary with frequently used medical terms|
The intervention group had access to an eHealth intervention, with detailed tailored pre- and postoperative instructions on the resumption of work and daily activities, and with tools (e.g. a video) to improve self-empowerment, communication with care providers and employer, and to identify recovery problems. Furthermore, the eHealth intervention supplied general information on the surgical procedure itself, an extensive list of frequently asked questions, and a forum enabling contact with other women. The eHealth intervention was part of a stepped care programme that is described elsewhere. Box 1 presents the detailed content of the interventions.
The primary outcome measure in this study was the duration of sick leave until a full sustainable return to work, which was a continuous outcome measure, and was defined as the duration of sick leave in calendar days from the day of surgery until a full return to work to the same job, or to other work with equal pay, for at least 4 weeks without recurrence (partial or full).[14, 15] Recurrences of sick leave within 4 weeks of the first full day of a return to work were considered as part of the preceding period of sick leave if this was caused by the surgical treatment. A monthly self-reported calendar of sickness absence per post was chosen to measure the return to work.
Secondary outcome measures were: functional and general health status (QoL), as assessed by the Rand-36 Health Survey[17, 18]; recovery, as measured by a validated recovery-specific QoL questionnaire, RS-QoL (RI10); and pain intensity, measured using a visual analogue scale (VAS) questionnaire. Prognostic factors that may influence the duration of sick leave were recorded for adjustment in case of dissimilarities between the intervention group and the control group. Among these factors were sociodemographic data, type of surgery, complications during or related to the surgery (defined as an enlargement of the wound to ≥8 cm or re-surgery within 2 weeks of the initial surgery, assessed by questions based on the NVOG complication registration form), work-related factors, measured by the Job Content Questionnaire (JCQ) and specific additional work-related questions, pain perception, and fear avoidance belief, assessed by the Tampa scale, duration of sick leave in the previous 3 months before baseline, and expectations and intention of the employee concerning returning to work after surgery. The secondary outcome measures and prognostic factors were evaluated by self-reported online questionnaires, which were taken at baseline, and at 2, 6, 12, and 26 weeks after surgery.
Through user authentication, the use of the eHealth intervention by each woman was registered by date and time: e.g. web-page requests, duration of page views, use of particular tools, etc. Any overestimation of the activity time was limited through a stop in the time registration whenever the woman was not active for a period of 8 minutes.
A power calculation was performed on the primary outcome: return to work. To achieve a power of 80%, with a two-sided significance level of 5%, and considering a hazard ratio of 1.5 in favour of the intervention group, approximately 191 women would be needed in the study. Anticipating a 10% drop-out rate, a total sample size of at least 212 women was required.
To prevent unequal randomisation between hospitals and type of surgery, women were pre-stratified by hospital and type of surgery (laparoscopic adnexal surgery, and total laparoscopic or laparoscopic-assisted, vaginal, and abdominal hysterectomy). A computer-generated block randomisation was performed at the individual level. The blocks consisted of four characters to ensure roughly equal group sizes within each stratum, and were randomly varied in sequence. An independent research assistant performed the randomisation.
Women were blinded for the allocated treatment. Although all women received access to an eHealth intervention, after logging into the website with their personal login credentials, the kind of information provided by the eHealth intervention depended on the group the woman was assigned to. The differing content of the eHealth interventions for both groups meant that therapists and researchers could not be blinded to the treatment allocation of the women.
The analyses were performed using spss 16.0 and stata 11.2. All statistical analyses were performed at the individual level, according to the intention-to-treat (ITT) and per protocol (PP) principles. P values were two-tailed and P ≤ 0.05 was considered to be significant. The Cox proportional hazard model was used to estimate hazard ratios for the return to work after surgery. Both crude and adjusted analyses were performed.
In the adjusted analyses, hospital and type of surgical procedure were included in the model as design covariates, given the fact that randomisation was pre-stratified for these factors.[25, 26]
Furthermore, the Cox regression analyses were adjusted for prognostic factors when they showed a coincidental and meaningful difference between groups. As the recommendations provided by the eHealth interventions were limited to the first 7 weeks after surgery, the hazard ratio for this period was presented. The assumption that the hazard ratio remained constant over time was checked.
To assess whether protocol deviations have caused any bias, participants from both groups who logged into the eHealth intervention at least once were included in the PP analyses. The median duration of sick leave until the first period of full sustainable return to work was analysed by descriptive statistics. Differences in secondary outcome measures (i.e. QoL and recovery) between the groups were assessed by mixed models, using measurements at 2, 6, 12, and 26 weeks, with the baseline score as a covariate. As a result of skewness, pain intensity was analysed with generalised mixed ordered logistic regression models, using all measurements available at 6, 12, and 26 weeks. The pain intensity scores were divided into four score categories: 0 (no pain), 1–3, 4–6, and ≥7 (moderate to severe pain). The transformation of weblogs into user and page statistics was performed using matlab 7.10.
From March 2010 till January 2011, 673 women were scheduled for a hysterectomy and/or laparoscopic adnexal surgery for a benign indication in the participating hospitals. Of these 673 women, 194 declined to participate in this study for unknown reasons, and 49 women were not accessible before their surgery took place. Of the remaining 430 women, 215 were excluded. The main exclusion reasons were: not meeting the inclusion criteria (n = 99); an insufficient command of Dutch (n = 43); no access to the internet (n = 25); and concomitant surgical procedures or serious comorbidity (n = 18). As a result, 215 women were randomised, with 110 women allocated to the intervention group and 105 women allocated to the control group. Figure 1 presents the flow chart for women during the trial.
The baseline characteristics, prognostic factors, and data on sick leave (i.e. primary outcome measure) were available for all 215 women. Secondary outcome measures after 2, 6, 12, and 26 weeks were respectively complete for 97, 97, 96, and 97% of the women. There were no differences in the dropout rates for secondary outcome measures between the intervention group and the control group.
In the intervention group 110 women (100%) logged into the eHealth intervention at least once, whereas for the control group this figure was 99 women (94%). The median time spent on the eHealth intervention was 118 minutes (interquartile range 66–173 minutes) in the intervention group and 11 minutes (interquartile range 5–22 minutes) in the control group.
Table 1 presents the baseline characteristics and prognostic factors of the intervention and control groups. In the intervention group there were more complicated surgeries than in the control group, which is a coincidental but meaningful difference. It has been shown that this factor affects the outcome measure, but has no relation to the eHealth intervention studied.
|Baseline characteristics||Intervention group (n = 110)||Control group (n = 105)|
|Laparoscopic adnexal surgery (n [%])||51 (46.4)||45 (42.9)|
|Laparoscopic surgery (n [%])||17 (15.5)||18 (17.1)|
|Vaginal surgery (n [%])||25 (22.7)||24 (22.9)|
|Abdominal surgery (n [%])||17 (15.5)||18 (17.1)|
|Age (years) (mean [SD])||43.5 (7.8)||43.2 (8.5)|
|Level of education (n [%])a|
|Low||10 (9.1)||6 (5.7)|
|Intermediate||50 (45.5)||51 (48.6)|
|High||50 (45.5)||48 (45.7)|
|Most representative daily work description (n [%])|
|Salaried employment||89 (80.9)||86 (81.9)|
|Voluntary employment||2 (1.8)||3 (2.9)|
|Self-employed||19 (17.3)||16 (15.2)|
|Work sector (n [%])|
|Business and financial services||46 (41.8)||46 (43.8)|
|Health care and public welfare||30 (27.3)||30 (28.6)|
|Government, public safety, and security||13 (11.8)||10 (9.5)|
|Education||11 (10.0)||13 (12.4)|
|Industry||5 (4.5)||2 (1.9)|
|Other||5 (4.5)||4 (3.8)|
|Kind of work (n [%]) (DMQ)|
|Often manually lift loads > 20 kg||13 (11.8)||13 (12.4)|
|Often manually carry loads > 20 kg||9 (8.2)||7 (6.7)|
|Work hours per week (mean (SD) )||30.3 (9.2)||30.9 (9.3)|
|Job content questionnaire (mean [SD])b|
|Decision latitude (range: 24–96)||73.5 (14.4)||72.0 (14.4)|
|Social support (range: 8–32)||25.1 (3.2)||24.7 (3.4)|
|Psychological job demands (range: 12–48)||30.2 (7.3)||30.2 (7.5)|
|Physical job demands (range: 5–20)||8.8 (3.2)||9.2 (3.2)|
|Absence from work during the last 3 months (work days) (median [interquartile range])||5 (2–10)||4 (2–6)|
|Tampa scale for kinesiophobia (mean [SD]) c||32.6 (5.5)||33.5 (5.4)|
|Absence from work before surgery (n [%])||12 (10.9)||6 (5.7)|
|Return to work expectation (days) before surgery (mean [SD])||28.2 (17.9)||30.5 (20.1)|
|Intention to return to work, despite symptoms (1–5) (mean [SD]) d||3.0 (1.0)||2.9 (1.1)|
|Complicated surgery (n [%]) e||7 (6.4)||1 (1.0)|
Regarding the return to work, a hazard ratio of 1.43 (95% confidence interval 1.003–2.040; P = 0.048) in favour of the eHealth intervention was found, which remained constant over time. The PP analyses resulted in a hazard ratio of 1.54 (95% confidence interval 1.07–2.22; P = 0.022), comparable with the ITT analyses (Table 2).
|Model||HR||95% confidence interval||P|
|Univariate crude analyses (ITT)||1.34||0.94–1.90||0.108|
|Adjusted analyses (ITT)a||1.43||1.003–2.040||0.048|
|Adjusted analyses (PP)a||1.54||1.07–2.22||0.022|
The median duration of sick leave until a full sustainable return to work was 39 days (interquartile range 20–67 days) in the intervention group and 48 days (interquartile range 21–69 days) in the control group.
Table 3 presents the long-term effects of the intervention on QoL and recovery. Both physical and mental QoL improved more in the intervention group than in the control group. No difference between both groups was measured for the recovery index.
|Outcome||Mean (standard error)a||Between-group difference (95% confidence interval)b||P|
|Total||660 (17)||630 (19)||30 (4 to 57)||0.024|
|Physical health||345 (9)||330 (10)||15 (2 to 29)||0.028|
|Mental health||317 (10)||301 (11)||16 (0 to 32)||0.044|
|Recovery (RI-10)||40.8 (1.1)||39.3 (1.2)||1.5 (−0.2 to 3.3)||0.091|
Table 4 presents the pain intensity. The cumulative odds ratio of 1.84 at 26 weeks implies that the women in the intervention group were 1.84 times more likely to be included in a lower pain intensity category compared with the control group.
|Outcome||Mean (standard error)||Cumulative odds ratioa,b||95% confidence intervalc||P c|
|VAS pain score||1.92 (0.41)||3.52 (0.58)||1.84||1.04–3.25||0.035|
The use of the eHealth intervention had a significant beneficial effect on the rate of a sustainable return to work, pain intensity, and QoL (both physical health and mental health scales) in women after a hysterectomy and/or laparoscopic adnexal surgery for a benign indication, compared with the use of the control intervention. The median duration of sick leave until a full sustainable return to work was 39 days in the intervention group and 48 days in the control group.
The first strength of this study is the high internal validity through the proactive method of inviting all women scheduled for a hysterectomy and/or laparoscopic adnexal surgery to participate in the RCT, and through selection being based on clearly defined inclusion and exclusion criteria alone. In addition, the execution of this study in six general or teaching hospitals and one university hospital is a good reflection of the Dutch healthcare situation. Moreover, this RCT is of high quality, because of the high compliance with the eHealth intervention (100%), no loss to follow-up on the primary outcome measure, and only a 3–4% loss to follow-up on the secondary outcomes. In addition, the blinding of the women to their allocation to the intervention minimised the Hawthorne and placebo effects. This is confirmed by the fact that 32 (31%) of the women in the control group indicated that the control website contributed to their recovery. Furthermore, the primary outcome measure of a full sustainable return to work takes into account recurrences of sick leave within 4 weeks of a return to work, and therefore reduces any underestimation in the number of work days lost. Finally, according to the International Classification of Functioning, Disability and Health (ICF) model, both participation and the clinical outcomes for the women were measured to evaluate the clinical as well as the societal benefits.
A weakness of this study is the randomisation at the level of the individual: contamination between the intervention group and control group cannot be excluded. Care providers were not blinded to the intervention, and may have used acquired insights received through the convalescence recommendations for the intervention group to adapt their recommendations to the control group. Furthermore, women had to provide their GPs and OPs with the standardised convalescence recommendations, which may have restricted the implementation of the guidelines in some cases if women failed to do so. However, considering the results of this study, these limitations may only have led to an underestimation of the effect of the intervention.
Although care providers and researchers could not be blinded to the allocated treatment for the women, they were not involved in measuring the outcomes, as all outcome measures were self-reported and the questionnaires were sent by email or post to the women and filled out at home. The self-reported duration of sick leave might be susceptible to information bias. Nevertheless, a monthly recall is generally considered as reliable, and there is no reason why women should report their sick leave differently in the intervention or the control groups.[33, 34]
Regarding the secondary outcomes, an effect of the intervention in the second step of the stepped care programme cannot be ruled out; however, it is not plausible that this was of influence, because no one received the workplace intervention in the second step. Finally, the external validity could be reduced as a result of women being excluded and the higher educational level of the women included in the study, compared with the average female working population in the Netherlands. Both living in the city (participating hospitals were located in the urban agglomeration of the Netherlands) and a higher educational level are associated with more frequent use of the internet for health or illness matters. Therefore, the results can not automatically be generalised to all Dutch gynaecological patients.
This is the first study to evaluate the effect of an eHealth intervention aimed at improving care and the return to work after surgery. The result of a faster return to work in the intervention group is in line with other (cohort) studies in our target group that have reported a shorter return to work time when women received clear and unambiguous convalescence recommendations at discharge, and return-to-work advice, which was one of the main components of this eHealth intervention.[6, 37] Another study revealed, however, that the majority of women extend their sick leave beyond the recommended period on their own initiative. Therefore, an explanation for the effect of this intervention on the return to work may also be found in the fact that tailored eHealth interventions make women more actively engaged in their own recovery and improve the communication between women, healthcare providers and their (work) environment.[38, 39] Moreover, this eHealth intervention aimed to empower both women and employers to discuss a return to work, which is experienced as being difficult, and helped them to arrange a timely return to work, with modified duties if necessary. Besides enhancing these skills and reducing barriers, this intervention also aimed to influence the woman's intention to return to work by affecting attitudinal beliefs, social influence, and self-efficacy beliefs about their recovery and return to work.
The larger improvement of QoL and reduction of pain in the intervention group compared with the control group is in line with a review that described that work improves QoL, and may have a beneficial influence on outcomes such as pain.[2, 41]
Considering the positive influence of this eHealth intervention on the return to work, pain intensity, and QoL, it has the potential to induce a considerable improvement of perioperative care. Because sick leave costs are the main cost drivers after surgery, this eHealth intervention also has a high potential to reduce costs drastically for women undergoing hysterectomy and/or laparoscopic adnexal surgery for a benign indication. It has been developed to be used with minimal burden to care providers, and can even reduce the number of postoperative consultations. Therefore, the use of the eHealth intervention is cheap compared with other medical interventions, and its implementation is expected to be relatively easy, partly because 95 (91%) women in the intervention group would recommend the eHealth intervention to other women.
The generalisability of this eHealth model should be evaluated by external validation in another population of gynaecological patients. Furthermore, a cost-effectiveness study is recommended to evaluate the potential savings from this intervention. Finally, taking into consideration the positive results, it is also recommended to adapt this eHealth intervention for other types of surgery.
Return to work recommendations do not take priority among doctors, but in view of the great relevance of providing clear convalescence recommendations regarding a return to work, shown through this intervention, more attention for this aspect of health care is recommended.
In conclusion, this article presents a valuable effect of this eHealth intervention on the rates of a sustainable return to work, pain intensity, and QoL for women undergoing a hysterectomy and/or laparoscopic adnexal surgery for a benign indication in the Netherlands.
All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for this work; no financial relationships with any organisations that might have an interest in this work in the previous 3 years; and no other relationships or activities that could appear to have influenced this work.
All authors made substantial contributions to this study and article. AVN, JRA, WvM, HB, and JH participated in the design and/or execution of the study, the interpretation of the data, and the drafting and/or revision of the article. DK was involved in the statistical data analyses and interpretation, and in the revision of the article. PvK and MvB contributed to the execution of the study and to the revision of the article. All authors approve this version to be published.
This study was approved by the medical ethics committees of the participating hospitals: VU University Medical Centre (no. 2009/218); Amstelland Hospital (no. 10-54); Flevo Hospital (no. FZ09/35); Kennemer Gasthuis (no. 2010.02); Onze Lieve Vrouwe Gasthuis (no. 09.067); Sint Lucas Andreas Hospital (no. 09/114); and Spaarne Hospital (no. 561.09). The participants gave informed consent before taking part.
This study was supported by the Dutch organisation for health research and development (ZonMw, no. 150020037) and the VU University Medical Centre. The authors were independent of the funders and the funders had no involvement in the study and writing of the article.
We thank the women who participated in this study, the principal researchers of the participating hospitals (M.H. Emanuel, J. Lips, A. Mozes, and A. Thurkow), and all of the other medical specialists, nurses, administrative staff, and surgery planners involved for their collaboration in this research project. We also wish to thank the clinical occupational physician and occupational therapist for administering the intervention, and L.M. Bolten for the recruitment of, and dedicated correspondence with, the women. Finally, our appreciation goes to Z. Szlavik for translating the weblogs into user and page statistics.
Whipps Cross University Hospital, London, UK
Managed care over the past 20–30 years in the USA (DeCherney, Curr Opin Ob Gyn 1996;8:291–2) and the Enhanced Recovery Programme (ERP) over the past 5–10 years in Europe (Sjetne et al. Qual Saf Health Care 2009;18:236–40) have been widely implemented in order to optimise a patient's admission and length of stay in hospital. The average length of stay has consequently been reduced markedly for patients, with the result of freeing up the opportunity costs for the healthcare organisation. The postoperative period from the time of hospital discharge to a return to work has been a somewhat Cinderella area of care. Patients are usually provided with a discharge summary, some verbal information, plus leaflets pertaining to their surgery. The advice may be tailored to the operation, but not always to the particular individual. In a study on multidisciplinary convalescence recommendations after gynaecological surgery, Vonk Noordegraaf and colleagues gave a series of recommendations as to when it would be ‘medically possible’ for women to resume activities dependent on their type of gynaecological surgery (Vonk Noordegraaf et al. BJOG 2011;118:1557–67).
This paper looks at that much-neglected area of patient care, mainly the duration of sick leave taken by women prior to a ‘full substantial return to work’. In keeping with current trends, eHealth interventions are being evaluated as to their effect on convalescence after gynaecological surgery. In other words, can personalising online information for a patient reduce their sick leave? The study population has been restricted to what one would expect to be a computer literate group of women. The exclusion criteria within this study cohort suggest that the women included were otherwise fit and healthy, as well as being expected to be compliant with any kind of intervention. This is an interesting collaborative randomised controlled trial (RCT) in which both of the study arms appear to be well matched demographically as well as with equal numbers undergoing the same type of surgery. Despite the matching for the type of surgery, there was no mention of the length of the surgery or their average length of stay. Likewise, there was no mention of ethnicity, body mass indices, smoking history, or support at home for the women, all of which may be confounding factors in a logistic regression analysis.
In both groups, the range of the duration of sick leave was similar but the median was significantly different in the intervention group, as were the secondary outcome measures of quality of life and pain intensity at 26 weeks. This suggests that the control group found little benefit from ‘logging on’, which was reflected in their overall time online.
The economic advantages of these findings are apparent, and in the current economic climate are important for both patient and employer when a woman embarks on elective surgery; however, the exact content of these eHealth interventions is not clear, and it would be interesting to see if these findings could be replicated in other more diverse populations.
Nothing to disclose.