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Oral clefts and wellbeing: a lifelong perspective and an agenda for comparative effectiveness research Prevalence & etiology
Oral clefts of the lip and/or palate are one of the most common birth defects worldwide affecting approximately one in 700 children, with varying estimates by ancestry and socioeconomic status. In the USA, approximately 7000 children are born with oral clefts annually [1]. The etiology of oral clefting etiology comprises a complex interplay of genetic and environmental factors including common maternal factors, such as smoking and folic acid consumption [2–6]. Isolated cases (without other birth defects) are the most common forms (~70% of cases), yet clefts can co-occur with other birth defects or syndromes (~30%). Lifelong impact
Oral clefts have a long-lasting impact on the health and wellbeing of affected individuals and their families that may extend from fetal development throughout the lifespan. Even though oral clefts are surgically repaired beginning very early in life, follow-up surgeries continue into late childhood and possibly adolescence and young adulthood. Affected children may experience reduce fetal growth and lower birthweight, especially those born at lower birthweight percentiles [7]. Early in infancy, feeding problems and ear infections can significantly slow infant development and weight gain, increasing hospitalization risk and early growth problems. In less developed countries, these complications increase the neonatal mortality risk; for example in South America, neonatal mortality is as high as 2% among isolated cases and 20% among nonisolated cases [8]. During childhood, speech and dental problems, as well as a lack of psycho social adjustment, mostly driven by speech problems and lack of satisfaction with facial appearance, are commonly reported. Recent studies showed greater risk of attention/hyperactivity [9] and separation anxiety [10] among children with clefts. Concerns regarding social adjustment have also been reported for adolescents [11]. Gaps in academic achievement have also been reported [12]. During adulthood, reduced marriage rates and shorter life expectancy (partly due to higher suicide rates) have been reported [13,14]. There are also concerns about an increased risk of certain cancers, although, this remains controversial [15]. Individuals with oral clefts utilize more hospital services throughout most of their lifespan. Average hospitalization days per affected child exceed those of an unaffected child by over 200% in Denmark; higher hospitalization rates extended until the late 1950s [16]. Greater healthcare use has also been reported in the USA, with ten-times higher healthcare expenditures per affected [17]. Studying the consequences of oral clefts
The literature on the impact of oral clefts on health and wellbeing offers several insights, but it has two main limitations that warrant brief discussion given their implications for comparative effectiveness research. The first limitation is utilizing small clinic-based samples that may be prone to ascertainment bias and provide limited power. This has been a common limitation for several studies
10.2217/CER.13.80 © 2014 Future Medicine Ltd
3(1), 23–28 (2014)
George L Wehby*1,2
Lina M Moreno3 Department of Health Management & Policy, College of Public Health, University of Iowa, 105 River Street, N248 CPHB, Iowa City, IA 52242, USA 2 The National Bureau of Economic Research, 1050 Massachusetts Avenue, Cambridge, MA 02138-5398, USA 3 Department of Orthodontics & Dows Institute, College of Dentistry, University of Iowa, 401 DSB, Iowa City, IA 52242, USA *Author for correspondence: Tel.: +1 319 384 3814 Fax: +1 319 384 4371 [email protected] 1
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that collected survey data, especially for adolescents and adults, which are harder to locate and recruit through clinics resulting in even smaller samples than studies of children. Linking data from national registries of children with oral clefts to secondary data sources, such as administrative datasets that capture health conditions, healthcare use, and indicators for psychosocial wellbeing and academic achievement available for the entire population, is ideal for outcome studies. National registries also enable obtaining representative samples for surveys. However, such registries and data sets are currently unavailable in the USA on a nationwide scale. An example of such a resource is the populationbased registry of virtually the entire population of individuals with oral clefts in Denmark that can be linked to several administrative registers on various aspects of health, healthcare use and socioeconomic outcomes obtained for the entire Danish population through Statistics Denmark; in this data system, individuals can be followed throughout most of their lifespan [16]. The capacity provided by such data systems highlights the need to further expand the data infrastructure for both birth defect surveillance and outcome data sets on a nationwide scale in the USA. “Linking data from national registries of children with oral clefts to secondary data sources ... is ideal for outcome studies.” The second limitation is potential confounding owing to family socioeconomic backgrounds and maternal risk factors that may affect both cleft risk and subsequent outcomes. For example, both low socioeconomic status and maternal smoking during pregnancy are associated with a higher cleft risk, but they may also reduce infant neurodevelopment and possibly subsequent human capital attainment and health status [18,19]. Accounting for this potential confounding is critical for capturing consequences caused by having a cleft, which are the main effects of interest when designing interventions and evaluating their effectiveness in improving patient outcomes. Findings based on correlation/association may result in inefficient/ineffective treatment and policy initiatives. For example, studies of interventions to improve social adjustment among children with oral clefts as a way to improve their psychosocial status and educational achievement might not
24
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be appropriately designed or calibrated, if the higher prevalence of social adjustment problems is mostly due to the greater exposure to prenatal smoking rather than the presence of a cleft. Employing regression analyses that control as much as possible for measured confounders is a first approach to address this concern. However, several environmental/social confounders may be unobservable or inadequately measured. Comparing affected individuals to their una ffected siblings controls for unobservable family-level factors shared by siblings, such as parental socioeconomic background and timeinvariant health preferences. However, comparing siblings does not account for potential time variant parental/household characteristics, such as maternal health and prenatal health behaviors, household income and geographic location, which would still bias the analysis if unobserved. Another concern is a potential effect of having a sibling with oral clefting on unaffected siblings. Household psychosocial stressors and greater allocation of parents’ time and financial resources towards caring for the affected child (if parents compensate less health-endowed children) may negatively affect siblings. In this case, one would underestimate the full effect of clefting on affected individuals when comparing to siblings. By contrast, if parents reinforce differences between their children, they may invest more in the unaffected siblings, resulting in overestimating the effect of clefting. Another approach to deal with confounding would be to instrument for oral clefts using genetic variants that affect cleft risk but are otherwise unrelated to the outcomes of interest [20]. This instrumental variables (IV) analysis would provide unbiased estimates if the genetic instruments meet these assumptions. To date, only a few variants have been found to have unequivocal effects on oral clefts, and it is unclear whether these genes influence other health conditions and neurological and cognitive development, making it difficult to evaluate with confidence if they could be appropriate instruments. Furthermore, the IV model is ideally estimated in one sample/data set of affected and unaffected individuals with data on the instruments and outcomes, which may not be feasible. An alternative is a two-sample/data set IV model, one for predicting cleft risk based on the instruments (without data on outcomes), and another for estimating the instrument effects on outcomes (without data on clefting).
future science group
Oral clefts & wellbeing: a lifelong perspective & an agenda for comparative effectiveness research
Health services & comparative effectiveness research
In the remaining sections of the paper, we highlight specific areas for comparative effectiveness research. We focus on volume–outcome relationships and variation in provider type and standards of care. ■■ Volume–outcome relationship
Many studies have reported a positive relationship between hospital/provider volume of treatment – the number of patients or cases receiving treatment for a certain health condition – and outcomes. For example, in-hospital mortality among very low birthweight (VLBW) infants has been shown to decrease with an increase in the number of VLBW infants treated at the hospital [21]. The theory is simple: practice makes perfect. This research area is highly relevant for understanding the effectiveness and cost–effectiveness of the current organizational structure of the healthcare delivery system for individuals with oral clefts and contractual arrangements between payers and providers. Surgeries for children with oral clefts in the USA, including primary cleft repair surgeries and follow-up surgeries, tend to be concentrated at large pediatric or general hospitals within each state that typically have interdisciplinary cleft/craniofacial teams involving multiple specialties. However, many surgeries are performed in hospitals with low volumes of children with oral clefts, especially in less urbanized settings where patients may have to travel long distances to access higher volume hospitals. Approximately a quarter of cleft palate surgeries occur in nonaccredited pediatric hospitals with an average volume of seven surgeries per year, 36% are in accredited pediatric hospitals performing 50 surgeries on average per year and 39% are in general hospitals with an average annual volume of 18 surgeries [22]. An important question, therefore, is whether hospital volume improves patient outcomes and whether volume effects are nonlinear with changes in incremental effects beyond certain thresholds. For example, an increase in VLBW volume above high thresholds in South American hospitals was not associated with a survival gain [23]. In one of the first studies to examine the effects of hospital characteristics on outcomes of cleft palate surgery in the USA, using a large nationally representative inpatient data set based on discharge records from the Healthcare Cost and Utilization Project, Nguyen et al. reported
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that an increase in hospital volume was associated with a decrease in length-of-stay beyond 2 days – an indicator for more complications and greater cost – controlling for the number of hospital beds, which was not significant [22]. While interesting and important, this result may suffer from two biases. The first bias is from not controlling for certain hospital characteristics correlated with both hospital volume and lengthof-stay, including hospital type. The second is from self-selection into hospitals based on their volume (or other correlated characteristics) and patient risk factors including cleft severity, other clinical and health characteristics, and socio economic background that are not well observed or measured in secondary data sets, such as the Healthcare Cost and Utilization Project. “Given the multifaceted long-term effects
of oral clefts on health and wellbeing, outcomes would ideally include detailed measures of care quality, short-term health indicators ... and long-term outcomes...”
The first bias from omitted hospital characteristics probably results in overestimating the benefits of hospital volume. The bias from self-selection based on unobservable patient factors may result in underestimating the hospital volume benefit if more severe cases are more likely to seek care at higher volume hospitals, such as the case for VLBW [21]. However, an opposite bias can occur if cases from higher socioeconomic background (and, therefore, with possibly better health outcomes) obtain care disproportionally more often at higher volume hospitals. Therefore, the net bias direction is hard to sign a priori based on theory alone and requires empirical investigation. The first bias can be substantially reduced by controlling for as many relevant hospital characteristics as possible, while checking for and dealing with any colinearity issues. Accounting for self-selection is more challenging, but can be achieved by an IV model that instruments for hospital volume based on the differential distance from patient’s residence to the nearest low- and high-volume hospitals, which has been successfully implemented for other infant health conditions including VLBW [21]. However, this would require having data on a patient’s address (at least at zip code level), which can be accessed in several state inpatient discharge data sets. Given the multifaceted long-term effects of oral clefts on health and wellbeing, outcomes
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would ideally include detailed measures of care quality, short-term health indicators (beyond length-of-stay), such as child health status and development, and long-term outcomes, such as speech or schooling achievement. Unfortunately, such data linkages are practically impossible for a US nationwide sample and are very challenging for selective statewide samples, mostly owing to the lack of data, but also for obtaining institutional and institutional review board permissions to link data sets overseen by different entities. This challenge applies to studying the longterm consequences of any child health condition in the USA, not just oral clefts or birth defects. “Understanding the value of team-based care for individuals with oral clefts is important for designing an effective care delivery system...”
Medicaid claims data allow for tracking enrolled children over time, but issues with sample representativeness, dropouts and availability of data only on medical and dental care services limit the utility of this data source for long-term studies and other outcomes. Therefore, investments in registries and data systems that capture health conditions and information on major health, healthcare and socioeconomic outcomes for the entire population or large nationally representative samples are critical for advancing health services research in general, and comparative effectiveness research in particular, for studying the long-term consequences of early life health conditions in the USA and effectiveness of treatments to improve both short- and long-term health and wellbeing outcomes. This research is relevant for all cleft types including cleft lip alone, as variation in surgery and dental care may impact facial esthetics, symmetry and dental outcomes. The volume–outcome question also extends to outpatient healthcare services for patients with oral clefts besides surgery, such as pediatrics, general dentistry, orthodontics, oral surgery, speech pathology and mental health providers. Of course, the data needs are even greater for outpatient services, which are generally not as well measured as inpatient services. ■■ Provider type & standards of care
A related question is how variation in provider type and standards of care affect outcomes of individuals with oral clefts. There is a general perception that care based on interdisciplinary
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and multispecialty teams is associated with better outcomes for individuals with oral clefts compared with nonteam care. In one of the most recent studies, Austin et al. reported that children receiving team-based care (based on maternal reporting) had more services and better maternal rating for care; there were no differences in health outcomes, such as speech, overall perception of facial appearance and general health status [24]. However, the literature is based on only a few studies that vary widely in their design, definition of team care and outcomes, and are nonrandomized and mostly based on small samples [25]. Estimates of the percentage of patients receiving team-based care vary between the 30s and upper 80s, with extensive variation in team composition and functioning [25]. Understanding the value of team-based care for individuals with oral clefts is important for designing an effective care delivery system, and is best achieved using large-scale data sets from surveys or secondary data sources for population-based samples that ideally would measure long-term outcomes. Randomized clinical trials are not necessarily optimal for addressing this question due to their cost and the challenge of defining a control group due to both ethical and practical reasons. But again, similar to the volume–outcome relationship question, the lack of population-based secondary data sets with detailed health and wellbeing outcome measures that capture the type of care (team-based or not) received at different stages of life remains a challenge. Large-scale surveys for population-based samples may be the only way to test the effectiveness of team care in the near future. Systematic measurement of team care that captures the variation in team care definitions and processes, and team composition and functioning and its effects on patient outcomes is important. Selfselection bias is also a challenge here as unobservable/unmeasured patient factors may influence the choice of providers and team care. IV analysis using distance to the nearest team (including by team type/category) is one potential approach to deal with this bias. Understanding the role of other healthcare providers, such as pediatricians or dentists who are not part of cleft/craniofacial teams, is also of interest given that many patients may have easier access to such providers in their local communities instead of specialized teams. Little is known about the experiences of these providers in treating children with oral clefts. In a recent study, Damiano
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Oral clefts & wellbeing: a lifelong perspective & an agenda for comparative effectiveness research
et al. reported that more than 30% of surveyed primary care physicians in three states reported little experience in providing cleft-specific care [26]. However, 80% of these physicians had access to cleft teams. Designing new models for the delivery of healthcare services to individuals with oral clefts, which integrate teams with local providers including primary care providers, general dentists, orthodontists, and speech therapists, is one potential approach for enhancing continuity of care and access to quality healthcare services for individuals with oral clefts. Teams can share their expertise with local providers and help in coordinating care for individuals with oral clefts to make sure that the various treatment (medical, surgical, dental, speech and psychological) are timely achieved. This can be facilitated by advances in health information technology and telehealth. The effectiveness (and cost–effectiveness) of such models can be tested in prospective studies, including possibly clinical trials that randomize cleft teams nationwide into different models for networking and interacting with community-based providers and collect data on multiple patient outcomes over a long enough period. Variation in defining and adopting standards of care for oral clefts is common worldwide. In the USA, the American Cleft Palate-Craniofacial Association has published parameters of care for individuals with oral clefts [101]. However, little is known about the extent of variation in adopting these parameters as standards of care in the USA. Significant variation in cleft team composition and processes has been reported [25,27], suggesting potential variation in standards of care. Substantial variation in timeliness of cleft palate surgery has been reported among children enrolled in Medicaid in North Carolina [28]. Although several individual-level factors predicted the timeliness of surgery, geographic differences were also References
Commentary
observed, suggesting a potential role for access to team care, but also potential v ariation in team care and functioning. Studying variation in standards of care requires surveying teams to obtain data on their parameters of care, and correlating these with patient services and outcomes, which can be partly captured in existing databases, such as Medicaid and private insurance data sets. Longitudinal surveys of population-based and representative samples of individuals with oral clefts can also be employed to obtain detailed information on healthcare services and outcomes. Establishing interteam networks and collaborations to obtain and compare data on parameters of care and outcomes is another approach to studying parameters of care and outcomes. An example is the Americleft Outcomes Project, a collaboration between multiple cleft/craniofacial teams, aimed at developing reliable and valid measures of clinical outcomes in several areas including orthodontics, surgery, speech and psychology [102]. Disclosure LM Moreno serves as the orthodontist on the cleft palate team at the University of Iowa. She provides orthodontic treatment to children with oral clefts and coordinates t r eatment plans with providers in local patient communities.
Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.
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Parker SE, Mai CT, Canfield MA et al. Updated national birth prevalence estimates for selected birth defects in the United States: 2004–2006. Birth Defects Res. A Clin. Mol. Teratol. 88, 1008–1016 (2010).
Shi M, Wehby GL, Murray JC. Review on genetic variants and maternal smoking in the etiology of oral clefts and other birth defects. Birth Defects Res. C Embryo Today 84, 16–29 (2008).
Wehby GL, Nyarko KA, Lopez-Camelo JS. Fetal health shocks and early inequalities in health capital accumulation. Health Econ. doi:10.1002/hec.2901 (2013) (Epub ahead of print).
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Lidral AC, Moreno LM. Progress toward discerning the genetics of cleft lip. Curr. Opin. Pediatr. 17, 731–739 (2005).
Wehby GL, Murray JC. Folic acid and orofacial clefts: a review of the evidence. Oral Dis. 16, 11–19 (2010).
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Dixon MJ, Marazita ML, Beaty TH, Murray JC. Cleft lip and palate: understanding genetic and environmental influences. Nat. Rev. Genet. 12, 167–178 (2011).
Wehby G, Jugessur A, Murray JC, Moreno L, Wilcox A, Lie RT. Genes as instruments for studying risk behavior effects: an application to maternal smoking and orofacial clefts. Health Serv. Outcomes Res. Methodol. 11, 54–78 (2011).
Wehby G, Castilla E, Goco N et al. The effect of systematic pediatric care on neonatal mortality and hospitalizations of infants born with oral clefts. BMC Pediatrics 11, 121 (2011).
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Wehby GL, Tyler MC, Lindgren S, Romitti P, Robbins J, Damiano P. Oral clefts and behavioral health of young children. Oral Dis. 18, 74–84 (2012).
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10 Tyler MC, Wehby GL, Robbins JM,
Damiano PC. Separation anxiety in children ages 4 through 9 with oral clefts. Cleft Palate Craniofac. J. 50, 520–527 (2013). 11 Kapp-Simon KA, Simon DJ, Kristovich S.
Self-perception, social skills, adjustment, and inhibition in young adolescents with craniofacial anomalies. Cleft Palate Craniofac. J. 29, 352–356 (1992). 12 Persson M, Becker M, Svensson H. Academic
achievement in individuals with cleft: a population-based register study. Cleft Palate Craniofac. J. 49, 153–159 (2012). 13 Ramstad T, Ottem E, Shaw WC. Psychosocial
adjustment in Norwegian adults who had undergone standardised treatment of complete cleft lip and palate. I. Education: employment and marriage. Scand. J. Plast. Reconstr. Surg. Hand Surg. 29, 251–257 (1995). 14 Christensen K, Juel K, Herskind AM, Murray
JC. Long term follow up study of survival associated with cleft lip and palate at birth. Br. Med. J. 328, 1405 (2004). 15 Dietz A, Pedersen DA, Jacobsen R, Wehby
GL, Murray JC, Christensen K. Risk of breast cancer in families with cleft lip and palate. Ann. Epidemiol. 22, 37–42 (2012). 16 Wehby G, Pedersen D, Murray J, Christensen
K. The effects of oral clefts on hospital use throughout the lifespan. BMC Health Serv. Res. 12, 58 (2012). 17 Boulet SL, Grosse SD, Honein MA,
Correa-Villasenor A. Children with orofacial
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clefts: health-care use and costs among a privately insured population. Public Health Rep. 124, 447–453 (2009). 18 Wehby GL, Prater K, McCarthy AM, Castilla
EE, Murray JC. The impact of maternal smoking during pregnancy on early child neurodevelopment. J. Hum. Cap. 5, 207–254 (2011). 19 Wehby GL, McCarthy AM. Economic
gradients in early child neurodevelopment: a multi-country study. Soc. Sci. Med. 78, 86–95 (2013). 20 Wehby GL, Ohsfeldt RL, Murray JC.
‘Mendelian randomization’ equals instrumental variable analysis with genetic instruments. Stat. Med. 27, 2745–2749 (2008). 21 Wehby GL, Ullrich F, Xie Y. Very low birth
weight hospital volume and mortality an instrumental variables approach. Med. Care 50, 714–721 (2012). 22 Nguyen C, Hernandez-Boussard T, Davies
SM, Bhattacharya J, Khosla RK, Curtin CM. Cleft palate surgery: an evaluation of length of stay, complications, and costs by hospital type. Cleft Palate Craniofac. J. doi:10.1597/12150 (2013) (Epub ahead of print). 23 Wehby GL, Lopez-Camelo J, Castilla EE.
Hospital volume and mortality of very low-birthweight infants in South America. Health Serv. Res. 47, 1502–1521 (2012). 24 Austin AA, Druschel CM, Tyler MC et al.
Interdisciplinary craniofacial teams compared
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with individual providers: is orofacial cleft care more comprehensive and do parents perceive better outcomes? Cleft Palate Craniofac. J. 47(1), 1–8 (2010). 25 McGrattan K, Ellis C. Team-oriented care
for orofacial clefts: a review of the literature. Cleft Palate Craniofac. J. 50, 13–18 (2013). 26 Damiano PC, Tyler MC, Romitti PA et al.
Primary care physician experience with children with oral clefts in three states. Birth Defects Res. A Clin. Mol. Teratol. 88, 1050–1056 (2010). 27 Strauss RP. Cleft palate and craniofacial
teams in the United States and Canada: a national survey of team organization and standards of care. Cleft Palate Craniofac. J. 35, 473–480 (1998). 28 Cassell CH, Daniels J, Meyer RE.
Timeliness of primary cleft lip/palate surgery. Cleft Palate Craniofac. J. 46, 588–597 (2009).
■■ Websites 101 American Cleft Palate–Craniofacial
Association. Parameters for evaluation and treatment of patients with cleftlip/palate or other craniofacial anomalies (2009). www.acpa-cpf.org/uploads/site/Parameters_ Rev_2009.pdf 102 American Cleft Palate–Craniofacial
Association. The Americleft Outcomes Project. www.acpa-cpf.org/research/the_americleft_ outcomes_project
future science group
Oral clefts and wellbeing: a lifelong perspective and an agenda for comparative effectiveness research Prevalence & etiology
Oral clefts of the lip and/or palate are one of the most common birth defects worldwide affecting approximately one in 700 children, with varying estimates by ancestry and socioeconomic status. In the USA, approximately 7000 children are born with oral clefts annually [1]. The etiology of oral clefting etiology comprises a complex interplay of genetic and environmental factors including common maternal factors, such as smoking and folic acid consumption [2–6]. Isolated cases (without other birth defects) are the most common forms (~70% of cases), yet clefts can co-occur with other birth defects or syndromes (~30%). Lifelong impact
Oral clefts have a long-lasting impact on the health and wellbeing of affected individuals and their families that may extend from fetal development throughout the lifespan. Even though oral clefts are surgically repaired beginning very early in life, follow-up surgeries continue into late childhood and possibly adolescence and young adulthood. Affected children may experience reduce fetal growth and lower birthweight, especially those born at lower birthweight percentiles [7]. Early in infancy, feeding problems and ear infections can significantly slow infant development and weight gain, increasing hospitalization risk and early growth problems. In less developed countries, these complications increase the neonatal mortality risk; for example in South America, neonatal mortality is as high as 2% among isolated cases and 20% among nonisolated cases [8]. During childhood, speech and dental problems, as well as a lack of psycho social adjustment, mostly driven by speech problems and lack of satisfaction with facial appearance, are commonly reported. Recent studies showed greater risk of attention/hyperactivity [9] and separation anxiety [10] among children with clefts. Concerns regarding social adjustment have also been reported for adolescents [11]. Gaps in academic achievement have also been reported [12]. During adulthood, reduced marriage rates and shorter life expectancy (partly due to higher suicide rates) have been reported [13,14]. There are also concerns about an increased risk of certain cancers, although, this remains controversial [15]. Individuals with oral clefts utilize more hospital services throughout most of their lifespan. Average hospitalization days per affected child exceed those of an unaffected child by over 200% in Denmark; higher hospitalization rates extended until the late 1950s [16]. Greater healthcare use has also been reported in the USA, with ten-times higher healthcare expenditures per affected [17]. Studying the consequences of oral clefts
The literature on the impact of oral clefts on health and wellbeing offers several insights, but it has two main limitations that warrant brief discussion given their implications for comparative effectiveness research. The first limitation is utilizing small clinic-based samples that may be prone to ascertainment bias and provide limited power. This has been a common limitation for several studies
10.2217/CER.13.80 © 2014 Future Medicine Ltd
3(1), 23–28 (2014)
George L Wehby*1,2
Lina M Moreno3 Department of Health Management & Policy, College of Public Health, University of Iowa, 105 River Street, N248 CPHB, Iowa City, IA 52242, USA 2 The National Bureau of Economic Research, 1050 Massachusetts Avenue, Cambridge, MA 02138-5398, USA 3 Department of Orthodontics & Dows Institute, College of Dentistry, University of Iowa, 401 DSB, Iowa City, IA 52242, USA *Author for correspondence: Tel.: +1 319 384 3814 Fax: +1 319 384 4371 [email protected] 1
part of
ISSN 2042-6305
23
Commentary
Wehby & Moreno
that collected survey data, especially for adolescents and adults, which are harder to locate and recruit through clinics resulting in even smaller samples than studies of children. Linking data from national registries of children with oral clefts to secondary data sources, such as administrative datasets that capture health conditions, healthcare use, and indicators for psychosocial wellbeing and academic achievement available for the entire population, is ideal for outcome studies. National registries also enable obtaining representative samples for surveys. However, such registries and data sets are currently unavailable in the USA on a nationwide scale. An example of such a resource is the populationbased registry of virtually the entire population of individuals with oral clefts in Denmark that can be linked to several administrative registers on various aspects of health, healthcare use and socioeconomic outcomes obtained for the entire Danish population through Statistics Denmark; in this data system, individuals can be followed throughout most of their lifespan [16]. The capacity provided by such data systems highlights the need to further expand the data infrastructure for both birth defect surveillance and outcome data sets on a nationwide scale in the USA. “Linking data from national registries of children with oral clefts to secondary data sources ... is ideal for outcome studies.” The second limitation is potential confounding owing to family socioeconomic backgrounds and maternal risk factors that may affect both cleft risk and subsequent outcomes. For example, both low socioeconomic status and maternal smoking during pregnancy are associated with a higher cleft risk, but they may also reduce infant neurodevelopment and possibly subsequent human capital attainment and health status [18,19]. Accounting for this potential confounding is critical for capturing consequences caused by having a cleft, which are the main effects of interest when designing interventions and evaluating their effectiveness in improving patient outcomes. Findings based on correlation/association may result in inefficient/ineffective treatment and policy initiatives. For example, studies of interventions to improve social adjustment among children with oral clefts as a way to improve their psychosocial status and educational achievement might not
24
J. Comp. Eff. Res. (2014) 3(1)
be appropriately designed or calibrated, if the higher prevalence of social adjustment problems is mostly due to the greater exposure to prenatal smoking rather than the presence of a cleft. Employing regression analyses that control as much as possible for measured confounders is a first approach to address this concern. However, several environmental/social confounders may be unobservable or inadequately measured. Comparing affected individuals to their una ffected siblings controls for unobservable family-level factors shared by siblings, such as parental socioeconomic background and timeinvariant health preferences. However, comparing siblings does not account for potential time variant parental/household characteristics, such as maternal health and prenatal health behaviors, household income and geographic location, which would still bias the analysis if unobserved. Another concern is a potential effect of having a sibling with oral clefting on unaffected siblings. Household psychosocial stressors and greater allocation of parents’ time and financial resources towards caring for the affected child (if parents compensate less health-endowed children) may negatively affect siblings. In this case, one would underestimate the full effect of clefting on affected individuals when comparing to siblings. By contrast, if parents reinforce differences between their children, they may invest more in the unaffected siblings, resulting in overestimating the effect of clefting. Another approach to deal with confounding would be to instrument for oral clefts using genetic variants that affect cleft risk but are otherwise unrelated to the outcomes of interest [20]. This instrumental variables (IV) analysis would provide unbiased estimates if the genetic instruments meet these assumptions. To date, only a few variants have been found to have unequivocal effects on oral clefts, and it is unclear whether these genes influence other health conditions and neurological and cognitive development, making it difficult to evaluate with confidence if they could be appropriate instruments. Furthermore, the IV model is ideally estimated in one sample/data set of affected and unaffected individuals with data on the instruments and outcomes, which may not be feasible. An alternative is a two-sample/data set IV model, one for predicting cleft risk based on the instruments (without data on outcomes), and another for estimating the instrument effects on outcomes (without data on clefting).
future science group
Oral clefts & wellbeing: a lifelong perspective & an agenda for comparative effectiveness research
Health services & comparative effectiveness research
In the remaining sections of the paper, we highlight specific areas for comparative effectiveness research. We focus on volume–outcome relationships and variation in provider type and standards of care. ■■ Volume–outcome relationship
Many studies have reported a positive relationship between hospital/provider volume of treatment – the number of patients or cases receiving treatment for a certain health condition – and outcomes. For example, in-hospital mortality among very low birthweight (VLBW) infants has been shown to decrease with an increase in the number of VLBW infants treated at the hospital [21]. The theory is simple: practice makes perfect. This research area is highly relevant for understanding the effectiveness and cost–effectiveness of the current organizational structure of the healthcare delivery system for individuals with oral clefts and contractual arrangements between payers and providers. Surgeries for children with oral clefts in the USA, including primary cleft repair surgeries and follow-up surgeries, tend to be concentrated at large pediatric or general hospitals within each state that typically have interdisciplinary cleft/craniofacial teams involving multiple specialties. However, many surgeries are performed in hospitals with low volumes of children with oral clefts, especially in less urbanized settings where patients may have to travel long distances to access higher volume hospitals. Approximately a quarter of cleft palate surgeries occur in nonaccredited pediatric hospitals with an average volume of seven surgeries per year, 36% are in accredited pediatric hospitals performing 50 surgeries on average per year and 39% are in general hospitals with an average annual volume of 18 surgeries [22]. An important question, therefore, is whether hospital volume improves patient outcomes and whether volume effects are nonlinear with changes in incremental effects beyond certain thresholds. For example, an increase in VLBW volume above high thresholds in South American hospitals was not associated with a survival gain [23]. In one of the first studies to examine the effects of hospital characteristics on outcomes of cleft palate surgery in the USA, using a large nationally representative inpatient data set based on discharge records from the Healthcare Cost and Utilization Project, Nguyen et al. reported
future science group
Commentary
that an increase in hospital volume was associated with a decrease in length-of-stay beyond 2 days – an indicator for more complications and greater cost – controlling for the number of hospital beds, which was not significant [22]. While interesting and important, this result may suffer from two biases. The first bias is from not controlling for certain hospital characteristics correlated with both hospital volume and lengthof-stay, including hospital type. The second is from self-selection into hospitals based on their volume (or other correlated characteristics) and patient risk factors including cleft severity, other clinical and health characteristics, and socio economic background that are not well observed or measured in secondary data sets, such as the Healthcare Cost and Utilization Project. “Given the multifaceted long-term effects
of oral clefts on health and wellbeing, outcomes would ideally include detailed measures of care quality, short-term health indicators ... and long-term outcomes...”
The first bias from omitted hospital characteristics probably results in overestimating the benefits of hospital volume. The bias from self-selection based on unobservable patient factors may result in underestimating the hospital volume benefit if more severe cases are more likely to seek care at higher volume hospitals, such as the case for VLBW [21]. However, an opposite bias can occur if cases from higher socioeconomic background (and, therefore, with possibly better health outcomes) obtain care disproportionally more often at higher volume hospitals. Therefore, the net bias direction is hard to sign a priori based on theory alone and requires empirical investigation. The first bias can be substantially reduced by controlling for as many relevant hospital characteristics as possible, while checking for and dealing with any colinearity issues. Accounting for self-selection is more challenging, but can be achieved by an IV model that instruments for hospital volume based on the differential distance from patient’s residence to the nearest low- and high-volume hospitals, which has been successfully implemented for other infant health conditions including VLBW [21]. However, this would require having data on a patient’s address (at least at zip code level), which can be accessed in several state inpatient discharge data sets. Given the multifaceted long-term effects of oral clefts on health and wellbeing, outcomes
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would ideally include detailed measures of care quality, short-term health indicators (beyond length-of-stay), such as child health status and development, and long-term outcomes, such as speech or schooling achievement. Unfortunately, such data linkages are practically impossible for a US nationwide sample and are very challenging for selective statewide samples, mostly owing to the lack of data, but also for obtaining institutional and institutional review board permissions to link data sets overseen by different entities. This challenge applies to studying the longterm consequences of any child health condition in the USA, not just oral clefts or birth defects. “Understanding the value of team-based care for individuals with oral clefts is important for designing an effective care delivery system...”
Medicaid claims data allow for tracking enrolled children over time, but issues with sample representativeness, dropouts and availability of data only on medical and dental care services limit the utility of this data source for long-term studies and other outcomes. Therefore, investments in registries and data systems that capture health conditions and information on major health, healthcare and socioeconomic outcomes for the entire population or large nationally representative samples are critical for advancing health services research in general, and comparative effectiveness research in particular, for studying the long-term consequences of early life health conditions in the USA and effectiveness of treatments to improve both short- and long-term health and wellbeing outcomes. This research is relevant for all cleft types including cleft lip alone, as variation in surgery and dental care may impact facial esthetics, symmetry and dental outcomes. The volume–outcome question also extends to outpatient healthcare services for patients with oral clefts besides surgery, such as pediatrics, general dentistry, orthodontics, oral surgery, speech pathology and mental health providers. Of course, the data needs are even greater for outpatient services, which are generally not as well measured as inpatient services. ■■ Provider type & standards of care
A related question is how variation in provider type and standards of care affect outcomes of individuals with oral clefts. There is a general perception that care based on interdisciplinary
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and multispecialty teams is associated with better outcomes for individuals with oral clefts compared with nonteam care. In one of the most recent studies, Austin et al. reported that children receiving team-based care (based on maternal reporting) had more services and better maternal rating for care; there were no differences in health outcomes, such as speech, overall perception of facial appearance and general health status [24]. However, the literature is based on only a few studies that vary widely in their design, definition of team care and outcomes, and are nonrandomized and mostly based on small samples [25]. Estimates of the percentage of patients receiving team-based care vary between the 30s and upper 80s, with extensive variation in team composition and functioning [25]. Understanding the value of team-based care for individuals with oral clefts is important for designing an effective care delivery system, and is best achieved using large-scale data sets from surveys or secondary data sources for population-based samples that ideally would measure long-term outcomes. Randomized clinical trials are not necessarily optimal for addressing this question due to their cost and the challenge of defining a control group due to both ethical and practical reasons. But again, similar to the volume–outcome relationship question, the lack of population-based secondary data sets with detailed health and wellbeing outcome measures that capture the type of care (team-based or not) received at different stages of life remains a challenge. Large-scale surveys for population-based samples may be the only way to test the effectiveness of team care in the near future. Systematic measurement of team care that captures the variation in team care definitions and processes, and team composition and functioning and its effects on patient outcomes is important. Selfselection bias is also a challenge here as unobservable/unmeasured patient factors may influence the choice of providers and team care. IV analysis using distance to the nearest team (including by team type/category) is one potential approach to deal with this bias. Understanding the role of other healthcare providers, such as pediatricians or dentists who are not part of cleft/craniofacial teams, is also of interest given that many patients may have easier access to such providers in their local communities instead of specialized teams. Little is known about the experiences of these providers in treating children with oral clefts. In a recent study, Damiano
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Oral clefts & wellbeing: a lifelong perspective & an agenda for comparative effectiveness research
et al. reported that more than 30% of surveyed primary care physicians in three states reported little experience in providing cleft-specific care [26]. However, 80% of these physicians had access to cleft teams. Designing new models for the delivery of healthcare services to individuals with oral clefts, which integrate teams with local providers including primary care providers, general dentists, orthodontists, and speech therapists, is one potential approach for enhancing continuity of care and access to quality healthcare services for individuals with oral clefts. Teams can share their expertise with local providers and help in coordinating care for individuals with oral clefts to make sure that the various treatment (medical, surgical, dental, speech and psychological) are timely achieved. This can be facilitated by advances in health information technology and telehealth. The effectiveness (and cost–effectiveness) of such models can be tested in prospective studies, including possibly clinical trials that randomize cleft teams nationwide into different models for networking and interacting with community-based providers and collect data on multiple patient outcomes over a long enough period. Variation in defining and adopting standards of care for oral clefts is common worldwide. In the USA, the American Cleft Palate-Craniofacial Association has published parameters of care for individuals with oral clefts [101]. However, little is known about the extent of variation in adopting these parameters as standards of care in the USA. Significant variation in cleft team composition and processes has been reported [25,27], suggesting potential variation in standards of care. Substantial variation in timeliness of cleft palate surgery has been reported among children enrolled in Medicaid in North Carolina [28]. Although several individual-level factors predicted the timeliness of surgery, geographic differences were also References
Commentary
observed, suggesting a potential role for access to team care, but also potential v ariation in team care and functioning. Studying variation in standards of care requires surveying teams to obtain data on their parameters of care, and correlating these with patient services and outcomes, which can be partly captured in existing databases, such as Medicaid and private insurance data sets. Longitudinal surveys of population-based and representative samples of individuals with oral clefts can also be employed to obtain detailed information on healthcare services and outcomes. Establishing interteam networks and collaborations to obtain and compare data on parameters of care and outcomes is another approach to studying parameters of care and outcomes. An example is the Americleft Outcomes Project, a collaboration between multiple cleft/craniofacial teams, aimed at developing reliable and valid measures of clinical outcomes in several areas including orthodontics, surgery, speech and psychology [102]. Disclosure LM Moreno serves as the orthodontist on the cleft palate team at the University of Iowa. She provides orthodontic treatment to children with oral clefts and coordinates t r eatment plans with providers in local patient communities.
Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.
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K. The effects of oral clefts on hospital use throughout the lifespan. BMC Health Serv. Res. 12, 58 (2012). 17 Boulet SL, Grosse SD, Honein MA,
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■■ Websites 101 American Cleft Palate–Craniofacial
Association. Parameters for evaluation and treatment of patients with cleftlip/palate or other craniofacial anomalies (2009). www.acpa-cpf.org/uploads/site/Parameters_ Rev_2009.pdf 102 American Cleft Palate–Craniofacial
Association. The Americleft Outcomes Project. www.acpa-cpf.org/research/the_americleft_ outcomes_project
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