Phlebology OnlineFirst, published on July 1, 2015 as doi:10.1177/0268355515580233
Original Article
A multilevel regression of patientreported outcome measures after varicose vein treatment in England
Phlebology 0(0) 1–9 ! The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0268355515580233 phl.sagepub.com
Joseph El-Sheikha
Abstract Introduction: The relationship between patient and hospital characteristics and their influence on quality of life (QoL) variance following varicose vein treatment is little understood. Whilst Patient-reported outcome measures (PROMs) can record postoperative outcomes, the actual comparison of PROMs between hospitals can be misleading when the clustered nature of varicose vein care is overlooked. Multilevel models can accommodate hierarchical data and therefore can provide a more accurate reflection of the relationship between patients and hospitals when investigating postoperative outcomes. Methods: A multilevel model of PROMs was developed to analyse the relationship of patient characteristics (gender, age), postoperative outcomes (complications, postoperative satisfaction, treatment success) and hospital type (operative volume and if private or NHS institution) with the change in Aberdeen Varicose Vein Score (AVVQ) six months after varicose vein treatment. Results: Between April 2010 and July 2014, some 24,460 PROMs from 162 hospitals were analysed. Whilst the majority of variance in AVVQ improvement was due to patient factors, a small but statistically significant amount of variance was detected due to differences between hospitals. Multilevel regression revealed that females saw a greater improvement in AVVQ, as did those who reported greater levels of treatment success and satisfaction. Patient age, complications, intervention, readmission, hospital size and hospital type were not significantly associated with AVVQ improvement. Conclusion: Although QoL is intrinsically tied to an individual, hospitals can provide a small but potentially important benefit in AVVQ improvement following vein treatment. A patient-centred approach is therefore recommended to optimise patient outcomes.
Keywords Multilevel model, PROMs, patient-reported outcome measures, varicose veins
Introduction Varicose veins are a common disease and estimated to affect up to half of all adults.1–4 Whilst compression of the afflicted limb may provide some symptomatic relief, most patients find that treatment of the underlying venous incompetence by surgery or ablation results in better symptom resolution and enhanced quality of life.5–7 Consequently, intervention for varicose veins is in high demand in the UK with at least 30,000 procedures performed annually.8 Since 2009, the Department of Health England has collected national statistics on the varicose vein service provided in England. A two-part questionnaire, the Patient Reported Outcome Measures (PROMs), is offered to all patients undergoing elective varicose vein treatment.8 The PROMs measure several patient outcomes such as postoperative satisfaction, treatment success, complications and, most importantly, quality
of life (QoL). There are two measures of QoL used in the PROMs; the EuroQol 5-Dimension (EQ5D)9 and the Aberdeen Varicose Vein Questionnaire (AVVQ).10,11 The EQ5D is a common general QoL instrument while the AVVQ is a more specific venous disease QoL instrument. Both are valid and sensitive measurements of QoL in patients with venous disease.7,12,13 While all PROMs outcomes can be considered valuable, the National Institute for Health and Care Excellence (NICE) regards QoL improvement as one of the most important measures of a treatment outcome.14 Academic Vascular Surgery Unit, Hull Royal Infirmary, Hull, Humberside, UK Corresponding author: Joseph El-Sheikha, Academic Vascular Unit, 1st Floor Tower Block, Hull Royal Infirmary, Hull HU3 2JZ, UK. Email: [email protected]
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While a cursory analysis of the PROMs data provides an overview of venous outcomes across the country and may even allow for a superficial comparison of care between hospital units, this ignores that these patients had, by definition, ‘‘clustered’’ into hospital groups for their vein treatment. Populations served by hospitals tend to be more similar when compared to a population as a whole and by not taking this into account, inaccurate conclusions can be drawn. By performing a multilevel linear regression, the stratification of the patient and hospital units can be controlled and the significance of certain patient and hospital characteristics correctly quantified.15 The aim of this study was to investigate the effect of patient and hospital characteristics as measured by PROMs on improvement of patient QoL as determined by the AVVQ.
Methods Between April 2010 and July 2014, patients undergoing elective primary varicose vein treatment (as coded as per the Appendix) were offered the opportunity to complete pre- and post-treatment PROMs under the auspices of the Health and Social Care Information Centre (HSCIC).16 The preoperative PROMs record baseline demographics (age and gender) and baseline QoL using the EQ5D and AVVQ. After six months, the postoperative PROMs record complications, the treatment success, patient satisfaction and repeat the QoL using EQ5D and AVVQ. The AVVQ consists of 13 questions which calculate the level of disease severity on a scale of 0–100. A score of 0 would indicate no QoL impairment due to venous disease and a score of 100 would indicate significant QoL impairment due to venous disease. However, AVVQ scores close to 100 are unusual and most patients with uncomplicated varicose veins typically scoring between 10 and 30, and even patients with venous ulcers normally scoring between 30 and 60.13 The AVVQ reacts well to QoL improvement after venous intervention and consequently is one of the most popular disease-specific QoL measures used in venous research.17–19 The EQ5D is a general measure of QoL and calculates an individual’s health state by asking five three-level ordinal questions. An EQ5D score of 1 is classed as a perfect health state without any impairment of the domains which determine QoL. Health states of 0 would represent a zero health state (i.e. death) and below 0 would represent a health state worse than death. Post-operative complications were self-reported by patients and recorded any incidence of allergy or reaction to a drug, post-operative bleeding, wound problems, urine problems or any need for further treatment or readmission after their initial treatment over the subsequent six months. Success and satisfaction
were self-reported by patients on a five-level ordinal scale with 1 representing the best outcome and 5 the worst outcome. Individuals were censored of age and gender when fewer than six records were returned from a single provider to reduce the potential risk of patient identification. The HSCIC database also recorded the volume of varicose vein operations performed at each individual institution using the national Hospital Episode Statistic (HES) database.8 Hospital units were classed as ‘‘NHS’’ if it was a NHS institution or ‘‘Private’’ if it was run by a private healthcare concern.
Outcomes The primary outcome of this study was to explore AVVQ change following varicose vein treatment using a multilevel linear regression model. By treating all units of analysis as independent observations, a conventional linear regression model could inaccurately calculate the standard errors of the regression coefficients and therefore overstate statistical significance. By allowing for residual components to vary at different levels, a multilevel model will avoid this pitfall and provide a more reliable statistical conclusion.
Statistics Descriptive statistics were calculated for both the patient-level and hospital-level variables. Hypothesis testing was performed using paired and unpaired t-tests for normally distributed data and Mann– Whitney U and Wilcoxon Signed Rank tests for nonnormally distributed data. Correlation was performed using Spearman’s Rank testing, and if significant was further explored using linear regression for continuous data. Multivariable regression was performed to explore PROMs variables prior to multilevel regression. Multilevel linear regression is elaborated as follows.
Multilevel regression model A series of multilevel hierarchical models were built in sequence to investigate the variance in AVVQ change. Models were of two levels, whereby patients constitute the first (lower) level and hospitals constitute the second (higher) level. The analysis was completed in three stages with each iteration increasing the model complexity and therefore explanatory capacity. The first model (Model 1) is a simple variance component model which measures the amount of variance in AVVQ observed across the two levels. This indicates how much of the overall variance observed is due to first- (patient) or second-level (hospital) characteristics.
Downloaded from phl.sagepub.com by guest on November 19, 2015
El-Sheikha
3
The second model (Model 2) introduced independent variables at the first (patient) level to examine how much of the variance is due to the patient characteristics as follows: age, gender, allergy or reaction to drug, postoperative bleeding, wound problems, urine problems, further treatment, readmission and also selfreported success and treatment satisfaction scores. The third model (Model 3) introduced independent variables at the second higher (hospital) level to determine how much variance can be explained by the hospital size (varicose vein procedures performed per annum) and the hospital designation as either an NHS or Private hospital. Preliminary analysis was first undertaken in SPSS (Chicago, Version 22) while MLwiN (University of Bristol, Version 2.30) was used for subsequent multilevel analysis.
Results Between April 2010 and July 2014, some 24,460 patients treated by 162 UK hospitals had returned varicose vein PROMs to the HSCIC. Baseline measurements and follow-up results are detailed in Tables 1 and 2, respectively. Overall, varicose vein treatment was associated with a significant improvement in patient QoL. Median (i.q.r.) AVVQ significantly improved from 17.9 (12.3–25.4) to 9.5 (4.0–17.6) (P < 0.001) with a mean (s.d.) improvement of 8.1 (9.8). Median (i.q.r) EQ5D also improved from 0.796 (0.725–0.848) to 1.000 (0.760–1.000), a mean (s.d.) increase of 0.093 (0.216).
Gender A significant difference in quality of life was noted between the genders. Females reported worse AVVQ compared to males at baseline [female: 18.6 (13.5– 25.5) vs male: 15.6 (10.1–23.2) P < 0.001] and worse scores after treatment [female: 10.6 (5.0–17.8) vs male: 6.7 (2.4–14.3) P < 0.001]. However, both groups saw an improved AVVQ score after treatment (P < 0.001 Wilcoxon) and mean improvement in AVVQ score was similar for both genders [female: 7.8 (9.4) vs male: 8.0 (9.9) P ¼ 0.344]. This disparity in QoL between the genders was confirmed in EQ5D scores. Both the preoperative [female: 0.796 (0.725–0.796) vs male: 0.796 (0.725–1.000) P < 0.001] and postoperative [female 0.850 (0.760–1.000) vs male: 1.000 (0.796– 1.000) P < 0.001] EQ5D scores showed females at a disadvantage. However, again, there was no difference in actual improvement for either genders [female þ 0.052 (0.000–0.204) vs male þ 0.033 (0.000–0.204) P ¼ 0.053].
Age As shown in Figure 1, there was a significant difference in median AVVQ across the age groups preoperatively
Table 2. Follow-up outcomes. Variable Satisfaction
Treatment success Table 1. Baseline characteristics. Variable Gender Age
Hospital class
Frequency (%) Female Male 20–29 30–39 40–49 50–59 60–69 70–79 80–89 NHS Private Operative volume
a Median (interquartile range). EQ5D: EuroQol 5 dimension.
10530 (68.8) 4783 (31.2) 156 (1.0) 1815 (11.9) 3670 (24.0) 3888 (25.4) 4159 (27.2) 1545 (10.1) 80 (0.5) 23349 (95.5) 1111 (4.5) 91 (39–194)a
Allergy problem Bleeding problem Wound problem Urine problem Further treatment Readmission
Frequency (%) Excellent Very good Good Fair Bad Much better A little better About the same A little worse Much worse Yes No Yes No Yes No Yes No Yes No Yes No
a Mean (standard deviation). EQ5D: EuroQol 5 dimension.
Downloaded from phl.sagepub.com by guest on November 19, 2015
3731 (21.8) 6217 (36.4) 4506 (26.4) 1953 (11.4) 671 (3.9) 11772 (69.0) 3466 (20.3) 1249 (7.3) 399 (2.3) 185 (1.1) 454 (2.8) 15550 (97.2) 2306 (14.2) 13889 (85.8) 2389 (14.6) 13982 (85.4) 0 (0.0) 15770 (100.0) 2596 (15.3) 14367 (84.7) 861 (5.0) 16207 (95.0)
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Figure 1. Preoperative and postoperative Aberdeen Varicose Vein Score (AVVQ) and patient age.
and postoperatively (Kruskal Wallis P < 0.001). Older age groups typically reported higher AVVQ scores when compared to younger age groups. Most age groups were not drastically dissimilar in AVVQ score from their neighbouring age group except for a significant step in AVVQ severity noted between the age groups 40–49 to 50–59 in both preoperative (P < 0.001) and postoperative (P ¼ 0.015) AVVQ scores. Although older age groups typically saw greater falls in AVVQ compared to younger patients (P < 0.001), no significant step in AVVQ improvement was detected across the age groups.
Private vs pubic healthcare sectors Private patients had less severe AVVQ scores compared to NHS patients in both preoperative [private 16.15 (11.29–22.88) vs NHS 18.00 (12.34–25.54) P < 0.001] and postoperative scores [private 7.09 (2.43–14.36) vs 9.41 (4.01–17.12) P < 0.001]. However, both private and NHS patients saw a similar amount of improvement after vein treatment [private 8.52 (8.81) vs NHS 8.07 (9.89) P ¼ 0.144]. As shown in Table 3, no difference in postoperative complications was reported between NHS and private healthcare institutions. However, private patients did appear to be more satisfied and reported higher levels of treatment success compared to those treated in NHS hospitals.
Unit size and outcomes The number of procedures performed at an institution correlated significantly with AVVQ change (r2 ¼ 0.041, P < 0.001). Exploration of this relationship using linear regression suggested that every additional 10 vein treatments worsen the expected AVVQ improvement by 0.02 points.
Multivariable regression model A multivariable linear regression model is detailed in Table 4. Gender, satisfaction, treatment success and requirement for additional treatments were significantly associated with AVVQ improvement. In holding all other variables constant, females improved an additional 0.542 AVVQ points compared to males, those ‘‘Excellently’’ satisfied improved an additional 5.325 AVVQ points compared to those ‘‘Badly’’ satisfied, those with a ‘‘Much better’’ treatment success improved an additional 11.397 AVVQ points compared to those with a ‘‘Much worse’’ treatment success and those who avoided additional treatments improved 0.629 AVVQ points more than those who did require further treatments. Age, allergy or drug reactions, bleeding problems, wound problems, readmission, hospital class and hospital size were not associated with AVVQ change.
Downloaded from phl.sagepub.com by guest on November 19, 2015
El-Sheikha
5 Table 4. Multivariable linear regression.
Table 3. Complications. Complication
NHS
Private
Pa
Allergy or reaction to drug Bleeding Wound problem Urine problem Further treatment Readmission Satisfaction Success
2.8% 14.2% 14.7% 0% 15.3% 5.1% 2 (2–3) 1 (1–2)
3.4% 15.1% 12.9% 0% 16.3% 3.7% 2 (1–3) 1 (1)
0.367 0.495 0.188 – 0.422 0.078
Original Article
A multilevel regression of patientreported outcome measures after varicose vein treatment in England
Phlebology 0(0) 1–9 ! The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0268355515580233 phl.sagepub.com
Joseph El-Sheikha
Abstract Introduction: The relationship between patient and hospital characteristics and their influence on quality of life (QoL) variance following varicose vein treatment is little understood. Whilst Patient-reported outcome measures (PROMs) can record postoperative outcomes, the actual comparison of PROMs between hospitals can be misleading when the clustered nature of varicose vein care is overlooked. Multilevel models can accommodate hierarchical data and therefore can provide a more accurate reflection of the relationship between patients and hospitals when investigating postoperative outcomes. Methods: A multilevel model of PROMs was developed to analyse the relationship of patient characteristics (gender, age), postoperative outcomes (complications, postoperative satisfaction, treatment success) and hospital type (operative volume and if private or NHS institution) with the change in Aberdeen Varicose Vein Score (AVVQ) six months after varicose vein treatment. Results: Between April 2010 and July 2014, some 24,460 PROMs from 162 hospitals were analysed. Whilst the majority of variance in AVVQ improvement was due to patient factors, a small but statistically significant amount of variance was detected due to differences between hospitals. Multilevel regression revealed that females saw a greater improvement in AVVQ, as did those who reported greater levels of treatment success and satisfaction. Patient age, complications, intervention, readmission, hospital size and hospital type were not significantly associated with AVVQ improvement. Conclusion: Although QoL is intrinsically tied to an individual, hospitals can provide a small but potentially important benefit in AVVQ improvement following vein treatment. A patient-centred approach is therefore recommended to optimise patient outcomes.
Keywords Multilevel model, PROMs, patient-reported outcome measures, varicose veins
Introduction Varicose veins are a common disease and estimated to affect up to half of all adults.1–4 Whilst compression of the afflicted limb may provide some symptomatic relief, most patients find that treatment of the underlying venous incompetence by surgery or ablation results in better symptom resolution and enhanced quality of life.5–7 Consequently, intervention for varicose veins is in high demand in the UK with at least 30,000 procedures performed annually.8 Since 2009, the Department of Health England has collected national statistics on the varicose vein service provided in England. A two-part questionnaire, the Patient Reported Outcome Measures (PROMs), is offered to all patients undergoing elective varicose vein treatment.8 The PROMs measure several patient outcomes such as postoperative satisfaction, treatment success, complications and, most importantly, quality
of life (QoL). There are two measures of QoL used in the PROMs; the EuroQol 5-Dimension (EQ5D)9 and the Aberdeen Varicose Vein Questionnaire (AVVQ).10,11 The EQ5D is a common general QoL instrument while the AVVQ is a more specific venous disease QoL instrument. Both are valid and sensitive measurements of QoL in patients with venous disease.7,12,13 While all PROMs outcomes can be considered valuable, the National Institute for Health and Care Excellence (NICE) regards QoL improvement as one of the most important measures of a treatment outcome.14 Academic Vascular Surgery Unit, Hull Royal Infirmary, Hull, Humberside, UK Corresponding author: Joseph El-Sheikha, Academic Vascular Unit, 1st Floor Tower Block, Hull Royal Infirmary, Hull HU3 2JZ, UK. Email: [email protected]
Downloaded from phl.sagepub.com by guest on November 19, 2015
2
Phlebology 0(0)
While a cursory analysis of the PROMs data provides an overview of venous outcomes across the country and may even allow for a superficial comparison of care between hospital units, this ignores that these patients had, by definition, ‘‘clustered’’ into hospital groups for their vein treatment. Populations served by hospitals tend to be more similar when compared to a population as a whole and by not taking this into account, inaccurate conclusions can be drawn. By performing a multilevel linear regression, the stratification of the patient and hospital units can be controlled and the significance of certain patient and hospital characteristics correctly quantified.15 The aim of this study was to investigate the effect of patient and hospital characteristics as measured by PROMs on improvement of patient QoL as determined by the AVVQ.
Methods Between April 2010 and July 2014, patients undergoing elective primary varicose vein treatment (as coded as per the Appendix) were offered the opportunity to complete pre- and post-treatment PROMs under the auspices of the Health and Social Care Information Centre (HSCIC).16 The preoperative PROMs record baseline demographics (age and gender) and baseline QoL using the EQ5D and AVVQ. After six months, the postoperative PROMs record complications, the treatment success, patient satisfaction and repeat the QoL using EQ5D and AVVQ. The AVVQ consists of 13 questions which calculate the level of disease severity on a scale of 0–100. A score of 0 would indicate no QoL impairment due to venous disease and a score of 100 would indicate significant QoL impairment due to venous disease. However, AVVQ scores close to 100 are unusual and most patients with uncomplicated varicose veins typically scoring between 10 and 30, and even patients with venous ulcers normally scoring between 30 and 60.13 The AVVQ reacts well to QoL improvement after venous intervention and consequently is one of the most popular disease-specific QoL measures used in venous research.17–19 The EQ5D is a general measure of QoL and calculates an individual’s health state by asking five three-level ordinal questions. An EQ5D score of 1 is classed as a perfect health state without any impairment of the domains which determine QoL. Health states of 0 would represent a zero health state (i.e. death) and below 0 would represent a health state worse than death. Post-operative complications were self-reported by patients and recorded any incidence of allergy or reaction to a drug, post-operative bleeding, wound problems, urine problems or any need for further treatment or readmission after their initial treatment over the subsequent six months. Success and satisfaction
were self-reported by patients on a five-level ordinal scale with 1 representing the best outcome and 5 the worst outcome. Individuals were censored of age and gender when fewer than six records were returned from a single provider to reduce the potential risk of patient identification. The HSCIC database also recorded the volume of varicose vein operations performed at each individual institution using the national Hospital Episode Statistic (HES) database.8 Hospital units were classed as ‘‘NHS’’ if it was a NHS institution or ‘‘Private’’ if it was run by a private healthcare concern.
Outcomes The primary outcome of this study was to explore AVVQ change following varicose vein treatment using a multilevel linear regression model. By treating all units of analysis as independent observations, a conventional linear regression model could inaccurately calculate the standard errors of the regression coefficients and therefore overstate statistical significance. By allowing for residual components to vary at different levels, a multilevel model will avoid this pitfall and provide a more reliable statistical conclusion.
Statistics Descriptive statistics were calculated for both the patient-level and hospital-level variables. Hypothesis testing was performed using paired and unpaired t-tests for normally distributed data and Mann– Whitney U and Wilcoxon Signed Rank tests for nonnormally distributed data. Correlation was performed using Spearman’s Rank testing, and if significant was further explored using linear regression for continuous data. Multivariable regression was performed to explore PROMs variables prior to multilevel regression. Multilevel linear regression is elaborated as follows.
Multilevel regression model A series of multilevel hierarchical models were built in sequence to investigate the variance in AVVQ change. Models were of two levels, whereby patients constitute the first (lower) level and hospitals constitute the second (higher) level. The analysis was completed in three stages with each iteration increasing the model complexity and therefore explanatory capacity. The first model (Model 1) is a simple variance component model which measures the amount of variance in AVVQ observed across the two levels. This indicates how much of the overall variance observed is due to first- (patient) or second-level (hospital) characteristics.
Downloaded from phl.sagepub.com by guest on November 19, 2015
El-Sheikha
3
The second model (Model 2) introduced independent variables at the first (patient) level to examine how much of the variance is due to the patient characteristics as follows: age, gender, allergy or reaction to drug, postoperative bleeding, wound problems, urine problems, further treatment, readmission and also selfreported success and treatment satisfaction scores. The third model (Model 3) introduced independent variables at the second higher (hospital) level to determine how much variance can be explained by the hospital size (varicose vein procedures performed per annum) and the hospital designation as either an NHS or Private hospital. Preliminary analysis was first undertaken in SPSS (Chicago, Version 22) while MLwiN (University of Bristol, Version 2.30) was used for subsequent multilevel analysis.
Results Between April 2010 and July 2014, some 24,460 patients treated by 162 UK hospitals had returned varicose vein PROMs to the HSCIC. Baseline measurements and follow-up results are detailed in Tables 1 and 2, respectively. Overall, varicose vein treatment was associated with a significant improvement in patient QoL. Median (i.q.r.) AVVQ significantly improved from 17.9 (12.3–25.4) to 9.5 (4.0–17.6) (P < 0.001) with a mean (s.d.) improvement of 8.1 (9.8). Median (i.q.r) EQ5D also improved from 0.796 (0.725–0.848) to 1.000 (0.760–1.000), a mean (s.d.) increase of 0.093 (0.216).
Gender A significant difference in quality of life was noted between the genders. Females reported worse AVVQ compared to males at baseline [female: 18.6 (13.5– 25.5) vs male: 15.6 (10.1–23.2) P < 0.001] and worse scores after treatment [female: 10.6 (5.0–17.8) vs male: 6.7 (2.4–14.3) P < 0.001]. However, both groups saw an improved AVVQ score after treatment (P < 0.001 Wilcoxon) and mean improvement in AVVQ score was similar for both genders [female: 7.8 (9.4) vs male: 8.0 (9.9) P ¼ 0.344]. This disparity in QoL between the genders was confirmed in EQ5D scores. Both the preoperative [female: 0.796 (0.725–0.796) vs male: 0.796 (0.725–1.000) P < 0.001] and postoperative [female 0.850 (0.760–1.000) vs male: 1.000 (0.796– 1.000) P < 0.001] EQ5D scores showed females at a disadvantage. However, again, there was no difference in actual improvement for either genders [female þ 0.052 (0.000–0.204) vs male þ 0.033 (0.000–0.204) P ¼ 0.053].
Age As shown in Figure 1, there was a significant difference in median AVVQ across the age groups preoperatively
Table 2. Follow-up outcomes. Variable Satisfaction
Treatment success Table 1. Baseline characteristics. Variable Gender Age
Hospital class
Frequency (%) Female Male 20–29 30–39 40–49 50–59 60–69 70–79 80–89 NHS Private Operative volume
a Median (interquartile range). EQ5D: EuroQol 5 dimension.
10530 (68.8) 4783 (31.2) 156 (1.0) 1815 (11.9) 3670 (24.0) 3888 (25.4) 4159 (27.2) 1545 (10.1) 80 (0.5) 23349 (95.5) 1111 (4.5) 91 (39–194)a
Allergy problem Bleeding problem Wound problem Urine problem Further treatment Readmission
Frequency (%) Excellent Very good Good Fair Bad Much better A little better About the same A little worse Much worse Yes No Yes No Yes No Yes No Yes No Yes No
a Mean (standard deviation). EQ5D: EuroQol 5 dimension.
Downloaded from phl.sagepub.com by guest on November 19, 2015
3731 (21.8) 6217 (36.4) 4506 (26.4) 1953 (11.4) 671 (3.9) 11772 (69.0) 3466 (20.3) 1249 (7.3) 399 (2.3) 185 (1.1) 454 (2.8) 15550 (97.2) 2306 (14.2) 13889 (85.8) 2389 (14.6) 13982 (85.4) 0 (0.0) 15770 (100.0) 2596 (15.3) 14367 (84.7) 861 (5.0) 16207 (95.0)
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Figure 1. Preoperative and postoperative Aberdeen Varicose Vein Score (AVVQ) and patient age.
and postoperatively (Kruskal Wallis P < 0.001). Older age groups typically reported higher AVVQ scores when compared to younger age groups. Most age groups were not drastically dissimilar in AVVQ score from their neighbouring age group except for a significant step in AVVQ severity noted between the age groups 40–49 to 50–59 in both preoperative (P < 0.001) and postoperative (P ¼ 0.015) AVVQ scores. Although older age groups typically saw greater falls in AVVQ compared to younger patients (P < 0.001), no significant step in AVVQ improvement was detected across the age groups.
Private vs pubic healthcare sectors Private patients had less severe AVVQ scores compared to NHS patients in both preoperative [private 16.15 (11.29–22.88) vs NHS 18.00 (12.34–25.54) P < 0.001] and postoperative scores [private 7.09 (2.43–14.36) vs 9.41 (4.01–17.12) P < 0.001]. However, both private and NHS patients saw a similar amount of improvement after vein treatment [private 8.52 (8.81) vs NHS 8.07 (9.89) P ¼ 0.144]. As shown in Table 3, no difference in postoperative complications was reported between NHS and private healthcare institutions. However, private patients did appear to be more satisfied and reported higher levels of treatment success compared to those treated in NHS hospitals.
Unit size and outcomes The number of procedures performed at an institution correlated significantly with AVVQ change (r2 ¼ 0.041, P < 0.001). Exploration of this relationship using linear regression suggested that every additional 10 vein treatments worsen the expected AVVQ improvement by 0.02 points.
Multivariable regression model A multivariable linear regression model is detailed in Table 4. Gender, satisfaction, treatment success and requirement for additional treatments were significantly associated with AVVQ improvement. In holding all other variables constant, females improved an additional 0.542 AVVQ points compared to males, those ‘‘Excellently’’ satisfied improved an additional 5.325 AVVQ points compared to those ‘‘Badly’’ satisfied, those with a ‘‘Much better’’ treatment success improved an additional 11.397 AVVQ points compared to those with a ‘‘Much worse’’ treatment success and those who avoided additional treatments improved 0.629 AVVQ points more than those who did require further treatments. Age, allergy or drug reactions, bleeding problems, wound problems, readmission, hospital class and hospital size were not associated with AVVQ change.
Downloaded from phl.sagepub.com by guest on November 19, 2015
El-Sheikha
5 Table 4. Multivariable linear regression.
Table 3. Complications. Complication
NHS
Private
Pa
Allergy or reaction to drug Bleeding Wound problem Urine problem Further treatment Readmission Satisfaction Success
2.8% 14.2% 14.7% 0% 15.3% 5.1% 2 (2–3) 1 (1–2)
3.4% 15.1% 12.9% 0% 16.3% 3.7% 2 (1–3) 1 (1)
0.367 0.495 0.188 – 0.422 0.078
