Anil Kapur, Jon Hyett, and H. David McIntyre
Brief introduction to health economics and cost-effectiveness analysis
Cost and cost-effectiveness analysis (CEA) are health economic tools that measure costs of a health condition and the monetized health benefits associated with an intervention relative to its implementation cost.
The costing of health conditions has several components and layers. The first and simplest layer estimates the direct cost of the illness: How much does it cost to diagnose and treat the condition? This typically includes costs of medical consultations; laboratory and other diagnostic tests; and treatment including drugs, counseling sessions, and monitoring visits. The second layer of the cost of illness is the indirect cost of illness including productivity loss (work-days due to the illness), disability payments, social security, tax rebate, etc. The third layer of cost of illness is the intangible costs including the psychosocial components that are more difficult to monetize such as overall quality of life, lack of enjoyment, discrimination, pain, anxiety, depression, isolation, etc., as a consequence of the disease or its treatment. Because of the complexity of modeling and assessing economic value, most often only direct costs of illness and intervention costs are estimated. These estimates often do not suffice to make informed public health policy decisions, particularly when an intervention has cascading effects over the life course and even transgenerational impact, as in the case of pregnancy-related interventions. Taking a societal perspective in health economic studies in evaluating interventions in pregnancy is very relevant as described later in the chapter.
Whether an intervention is cost effective or not is calculated by determining the cost-effectiveness ratio (CE ratio) that is calculated using the following equation:
The benefit of an intervention can be measured in different ways such as an adverse outcome or complication averted or as quality-adjusted life-years (QALYs) gained or disability-adjusted life-years (DALYs) prevented. According to the World Health Organization (WHO) CHOICE analysis, any intervention in a given country is considered highly cost-effective if its cost is less than the annual gross domestic product (GDP) per capita of that country, cost effective when it is between one and three times GDP per capita, and not cost effective when it is more than three times GDP per capita (1).
It is important to understand that health interventions do not occur in isolation, and different interventions for the same objective may have differing costs and outcomes depending on the interplay with other elements of the health system. In order to assess which of the interventions is more beneficial, a comparative cost-benefit analysis for different interventions compared to the base case, i.e., the current practice in case there is an existing practice, or to no intervention in case there is no existing practice, is undertaken. This analysis is called the incremental CEA, and it is expressed as a ratio that is called the incremental cost-effectiveness ratio (ICER). It is defined as the difference in costs between two interventions divided by the difference in benefits of the two interventions:
When the benefits are valued in monetary terms using valuations of people’s observed or stated preferences, such as the willingness-to-pay (WTP) approach, the CEA is termed as cost utility analysis.
The perception of cost benefit varies based on the viewpoint of the person making the judgement. Therefore, any cost benefit or cost utility evaluation must describe the perception. The viewpoint may be that of the patient or his or her family, hospital/clinic, healthcare system, or society. So while a specific intervention may be cost beneficial from an individual’s perspective, it may not be from a societal perspective; for example, general CEA shows that treating tuberculosis with the directly observed treatment, short-course (DOTS) strategy is highly cost effective, and providing liver transplants in cases of alcoholic cirrhosis is highly cost ineffective from a societal perspective (2), but to the affected person or his or her family, this would be perfectly justified and rational. Thus, CEA based on a proper perspective is useful in making policies on resource allocations.
Sectorial versus societal
The growing use of CEA to evaluate the costs and health effects of specific interventions is dominated by studies of prospective new interventions compared to current practice. This type of analysis does not explicitly take a sectorial or societal perspective where the costs and effectiveness of all possible interventions are compared in order to select the mix that maximizes health benefits for the population as a whole with a given set of resource constraints. The estimated cost-effectiveness of a single proposed new intervention is compared either with the cost effectiveness of a set of existing interventions reported in the literature or with a fixed price cut-off point representing the assumed social willingness to pay for an additional unit of health. The implicit assumption that the required additional resources would need to be transferred from another health intervention or from another sector is rarely discussed (2). These considerations require calculating the opportunity costs. On the flip side, there are interventions that may cascade a set of further interventions that spill into other health sectors and create health benefits in the life course of individuals and sometimes into the life course of the next generations such as interventions related to maternal and newborn child health (MNCH) and future noncommunicable disease (NCD) prevention. If the health benefits accruing in the future from these actions are not taken into account because of compartmentalization, then the initial intervention may seem of lower value, resulting in missed opportunities to create overall health benefits and save costs from a societal perspective over the longer term.
Traditionally, the opportunity cost of investing in a healthcare intervention is the estimation of health benefits from the other healthcare programs and interventions that are displaced by the introduction of the new program. This is best measured by the health benefits that could have been achieved had the money been spent on the next best alternative healthcare intervention. In the example of MNCH and NCD mentioned previously, failure to invest in the interventions because of a limited perspective focused on short-term benefit may result in very high opportunity cost due to failure to gain future health benefits.
In the context of cost-benefit analysis, it is important to understand that costs and benefits incurred today are usually valued more highly than costs and benefits occurring in the future. In CEA, this is accounted for through discounting. Discounting health benefits reflects society’s preference for benefits to be experienced in the present rather than the future. Discounting costs reflects society’s preference for costs to be experienced in the future rather than the present. To ensure that cost-benefit analyses are comparable, a standard discounting rate must be used. The standard approach is to use WHO CHOICE recommendations, with both costs and health effects discounted at 3%. In the sensitivity analysis, the sensitivity of the results can be tested at a 0% discount rate for health effects and a rate of 6% for costs (2).
Modeling and its limitation
Cost-benefit analyses are done using mathematical modeling where input costs are based on actual consumption of direct resources, and allocated costs of common manpower and material resources are based on actual utilization (activity-based costing). Benefits are estimated based on published studies and their applicability in the given context. The quality of existing evidence, its applicability in the given context, and weight given to the evidence as well as apportioning of the costs of common resources results in unavoidable bias and some degree of arbitrariness to CEA. Standardization of methods of data collection and applying sensitivity analysis can correct some of these biases; nonetheless, CEA should primarily be used in conjunction with other sources of information to make policy decisions.
The cost-effectiveness plane (CE plane) (Figure 11.1) is an important tool to present CEA visually. It illustrates the differences in costs and effects between different strategies. By visually representing the relative value of strategies, the CE plane helps its viewer evaluate multiple strategies and make informed choices. The CE plane consists of a four-quadrant diagram where the x-axis represents the incremental level of effectiveness of an outcome, and the y-axis represents the additional total cost of implementing this outcome. For example, the further right one moves on the x-axis, the more effective the outcome. Importantly, the x-axis also allows less-effective interventions to be represented on the left-hand side of the graph. Similarly, the further up one moves on the y-axis, the more costly the outcome. Cost-saving interventions are in the lower half of the graph.
Figure 11.1 The cost-effectiveness plane. (Note that the origin is the reference intervention.)
When considering both parameters together, the CE plane allows one to determine the relative cost and relative effectiveness. The fact that the four quadrants represent all combinations of possible outcomes is important, since sensitivity analyses will produce a cloud of results that may span multiple quadrants. In fact, the spread of results can be an important aspect of the ICER to understand, since it is a measure of the ICER’s degree of uncertainty. This is one reason why the CE plane is such a valuable visual tool, since it provides a quick visual snapshot of the distribution of the ICER and a summary of how cost and outcomes are likely to behave. Interventions that are more effective and cost less than the base case are called dominant and have a compelling argument for implementation. Interventions that cost slightly more than the base case but are relatively more effective, as well as interventions that are slightly less effective but cost considerably less are also cost effective. An intervention that has higher costs and worse outcomes than an alternative intervention is referred to as dominated. When the ICER for a given treatment alternative is higher than that of the next, more effective, alternative (that is, it is dominated by the combination of two alternatives), it is called extended dominance, and this alternative should not be used.
Costs associated with noncommunicable diseases and pregnancy complications
Of the approximately 130 million pregnancies resulting in live births globally every year, an estimated 21 million are impacted by hyperglycemia, about 7–8 million by hypertension, about 42 million by maternal overweight and obesity, 26 million by maternal undernutrition, and 56 million by maternal anemia (3). Not only do these conditions increase the risk of adverse pregnancy outcomes and increase perinatal morbidity and mortality, but they also identify both the mother and the offspring at being at very high risk for future diabetes, obesity, hypertension, cardiovascular disease (CVD), and stroke.
Hemorrhage, preeclampsia, sepsis, and obstructed labor directly account for significant maternal morbidity and mortality. Maternal undernutrition, overweight and obesity, high blood pressure, and gestational hyperglycemia significantly increase the risks of these events. They also impact fetal growth (intrauterine growth restriction [IUGR], small for gestational age [SGA], macrosomia, and large for gestational age [LGA]) and increase risks of prematurity, stillbirths, congenital malformations, birth injuries, respiratory distress, hypoglycemia, etc., at birth. Additionally, indirect causes, including medical conditions that are exacerbated by pregnancy such as obesity, diabetes, CVD, etc., now account for over 28% of maternal deaths worldwide (4). The economic costs of NCD-related pregnancy complications are likely to be very high but are unfortunately not adequately researched and documented. Overweight and obesity in pregnancy not only cause problems on their own but also increase the risk of hyperglycemia, hypertension, and preeclampsia; similarly, hyperglycemia in pregnancy (HIP) increases the risk of hypertension and preeclampsia, thereby compounding adverse pregnancy outcomes. While there are studies addressing the costs of individual NCDs, their combined impact in causing pregnancy complications and increasing costs has rarely been studied, despite their clear interconnectedness.
Moreover, occurrence of these conditions during pregnancy is a highly reliable marker for future NCDs in both the mother and offspring. Thus, overweight or obese pregnant women without gestational diabetes or gestational hypertension continue to be at high risk for future type 2 diabetes, hypertension, and CVD later in life. Similarly, women with gestational diabetes, apart from being at very high risk of type 2 diabetes, are at high risk of future hypertension and CVD, as are women with gestational hypertension and preeclampsia. In addition, offspring of pregnancies impacted by any of these NCDs are also at risk of obesity and cardio-metabolic problems. Whether treatment during pregnancy will prevent or reduce long-term maternal and offspring risks is currently unknown and requires further well-designed long-term intervention studies. Nonetheless, identifying “at-risk” mothers and offspring opens up the opportunity for targeted early preventive action. It is therefore important to keep in mind that interventions to address NCDs in pregnancy have beneficial effects in both the mother and offspring in the short term as well as in the long term, particularly when accompanied by additional low-cost preventive actions postpregnancy. Since preventive actions to address obesity, hypertension, type 2 diabetes, and CVDs have a common lifestyle approach, identifying any one of these problems in pregnancy provides an opportunity to address them all. Cost-benefit analyses that only focus on the short term do not capture the full value of future long-term benefits.
Noncommunicable disease cost-effectiveness model
As explained earlier, health economics studies, particularly the cost-benefit analyses, use mathematical models based on decision trees. A comprehensive screening and integrated care cost-effectiveness model must, on the cost side, take into account the cost of identifying the condition, the cost of the intervention during pregnancy, and the cost of preventive actions postpregnancy; on the benefits side, the cost savings are due to reduced complications in the short term and discounted cost saving from deffering or preventing the disease and reducing its complications in the long term.
Figure 11.2 shows the various elements of input costs and health benefits that must be included in such a model based on (as an example) intervention for HIP and taking into account different perspectives—immediate short term based on the maternal and child health perspective, long term from the NCD and health system perspective, and overall from the societal perspective (5).
Figure 11.2 (a) Short-term only, maternal and child health perspective; (b) long-term health system perspective; (c) long-term societal perspective.
Screening and Diagnosis: This is a key input cost, and the efficacy of public health programs to screen and correctly identify women with the condition (gestational diabetes mellitus [GDM]) who will most benefit from treatment is a key element. The criteria, technology, and human resources required; the specificity and sensitivity of the test; the cut-off value to correctly identify all women who may benefit from the proposed intervention; and the prevalence of the condition in the given population are important determinants of this cost.
Treatment: The proportion of women with different degrees of hyperglycemia requiring different types of treatment, the efficacy of treatment, and the level of monitoring and follow-up visits required to ensure euglycemia and to prevent fetal and maternal complications determine the next set of input costs.
The prevention of perinatal complications provides the immediate health benefit of the intervention and resultant savings.
A model that limits itself to the short term, the CE analysis is limited to this time point.
Life Course Approach: In an integrated model, the life course approach, including the postpartum period and/or the preconception period, is used. Here, in addition to the costs and benefits previously described, additional input costs include preconception and/or postpartum screening and lifestyle/pharmacological intervention to prevent diabetes and CVD in the mother and appropriate counseling and follow up of the offspring to prevent or delay type 2 diabetes/metabolic syndrome. The costs depend on the type, intensity, and efficacy of the interventions, and benefits are calculated based on QALYs gained or DALYs averted free from diabetes/CVD and their debilitating and costly complications in both the mother and offspring. These costs and benefits are discounted at appropriate rates for the duration of intervention (5).
Costing and cost-effectiveness studies of common NCDs causing pregnancy complications
Overweight and obesity
Globally, overweight and obesity among reproductive-age women is rising. An estimated 42 million pregnancies are impacted by maternal overweight or obesity with wide regional variance, ranging from approximately 20% in South Asia to over 65% in North and Central America, Northern and Southern Africa, and West Asia (6). The number of reproductive-age women who are overweight now exceeds the number of underweight women (7).
Complications of overweight and obesity during pregnancy include hypertensive disorders, coagulopathies, GDM, respiratory problems, and fetal complications such as LGA babies, congenital malformations, stillbirth, and shoulder dystocia. The risk of preeclampsia increases two- to threefold in women overweight in early pregnancy (8). Obesity is associated with an increased risk of preeclampsia (adjusted odds ratio [aOR] 4.46), induction of labor (aOR 1.97), postpartum hemorrhage (aOR 3.04), intensive care admission (aOR 3.86), GDM (aOR 7.89), thrombosis (aOR infinity), shoulder dystocia (aOR 1.89), cesarean section (C-section) (aOR 3.50) (9), maternal infection (aOR 3.35), prolonged hospital stay (aOR 2.84), and instrument-assisted delivery (aOR 1.17) (10).
Maternal overweight and obesity (body mass index [BMI] >25 kg/m2) is the most important modifiable risk factor for stillbirths in high-income countries, contributing to around 8,000 stillbirths (22 weeks of gestation) annually (11). In developing countries, apart from stillbirths, complications relate to the two- to threefold increased risk of macrosomia, requiring institutional and assisted delivery. If these services are not available, a significantly higher maternal morbidity and mortality may ensue (12).
Given the additional risks of pregnancy complications associated with overweight and obesity, it can safely be assumed that these pregnancies require additional tests, clinic visits, and higher level of care resulting in additional costs. Very few studies have assessed the economic costs of overweight and obesity associated with pregnancy. A study from the United Kingdom estimated that even considering only the additional maternity care needs, costs (mean [95% CI], adjusted analyses) for women who were overweight, obese, or severely obese were £59.89 (£41.61–£78.17), £202.46 (£178.61–£226.31), and £350.75 (£284.82–£416.69), respectively (13). It has been estimated that the total costs for overweight and obese pregnant women with GDM during pregnancy and up to 2 months following delivery increase by 23% and 37%, respectively, as compared to women with normal BMI (13,14).
Not only are the maternity costs higher in overweight and obese women, but there is a strong association between infant healthcare usage cost and maternal BMI. This is attributed to a significantly greater number and duration of inpatient visits and a higher number of general practitioner visits. Total mean additional resource cost in a study from within the National Health Service (NHS) UK was estimated at £65.13 for infants born to overweight mothers and £1138.11 for infants born to obese mothers, when compared with infants of healthy weight mothers (15).
Hypertension and preeclampsia
Hypertension is a significant contributor to pregnancy-related complications. It can occur as gestational hypertension, preeclampsia, chronic hypertension, or preeclampsia superimposed on chronic hypertension. Although the incidence varies in different parts of the world, overall nearly 10% of normotensive women experience abnormally elevated blood pressure at some point during pregnancy. Hypertensive disorders of pregnancy (HDP) complicate 5%–10% of pregnancies and are increasing with the rising prevalence of overweight, obesity, diabetes, and metabolic disorders in younger reproductive-age women (16).
Worldwide, high blood pressure with or without proteinuria is a major cause of maternal morbidity and mortality (17), and HDPs account for 10%–15% of maternal deaths in low-/middle-income countries (18–20), as well as to increased perinatal morbidity and mortality as a consequence of prematurity and poor fetal growth. Preeclampsia is a multisystem disorder that typically affects 2%–5% of pregnant women and is one of the leading causes of maternal and perinatal morbidity and mortality, especially when the condition is of early onset (21,22). Globally, 76,000 women and 500,000 babies die each year from this disorder (23). Furthermore, women in developing countries are at a higher risk of developing preeclampsia compared to those in developed countries (24).
Women who develop gestational hypertension and preeclampsia during pregnancy have a greater chance of developing CVD and type 2 diabetes in later life (25). Despite this, they do not routinely receive long-term follow-up (26), counseling, or risk factor stratification and evaluation.
Compared to an uncomplicated pregnancy, costs associated with preeclampsia are significantly higher, for both the mother and the neonate, in any given regional setting. This is because of its severity and life-threatening nature requiring advanced intensive care. The cost of an uncomplicated vaginal delivery in California in 2011 was estimated to be about US$4,500 (27), and the average incremental cost for a pregnancy complicated by hypertensive disease was estimated to be US$8,200, amounting to an additional cost of US$200 million for all Californian births. Costs were highest for women who had severe disease requiring early delivery (<34 weeks’ gestation). In this particular cohort, the incremental cost was US$70,100 per pregnancy (27).
In Ireland, although the costs for an uncomplicated delivery are lower (US$3,000) compared to California, the cost escalation for pregnancies affected by preeclampsia was similar (increment of US$3,300) (28). The predominant driver for increased cost is neonatal care for preterm birth (29). While costs of maternal care increased 2.7-fold for women delivering before 32 weeks of gestation, costs of neonatal care increased 35-fold.
The annual financial burden of preeclampsia including the care of mother and child for the first 12 months after delivery in the United States in 2012 was US$2.18 billion: $1.03 billion for mothers and $1.15 billion for infants. The cost burden per infant is dependent on gestational age, ranging from US $150,000 at 26 weeks’ gestational age to US $1,311 at 36 weeks’ gestational age (30).
In the economic evaluation of the Magpie trial, the cost-effectiveness of using magnesium sulfate to prevent eclampsia in women with preeclampsia was evaluated (31). Cost-effectiveness was estimated for three categories of countries grouped by gross national income (GNI) into high-, middle-, and low-GNI countries using a regression model. Uncertainty was explored in sensitivity analyses. The number of women with preeclampsia who needed to receive magnesium sulfate to prevent one case of eclampsia was 324 (95% confidence interval [CI] 122, infinity) in high-GNI, 184 (95% CI 91, 6798) in middle-GNI, and 43 (95% CI 30, 68) in low-GNI countries. The additional hospital care cost per woman receiving magnesium sulfate was $65, $13, and $11, respectively. The incremental cost of preventing one case of eclampsia was $21,202 in high-GNI, $2,473 in middle-GNI, and $456 in low-GNI countries. Reserving treatment for severe preeclampsia would lower these estimates to $12,942, $1,179, and $263 (31).
Using a decision analysis model, three strategies for use of magnesium sulfate to prevent convulsions in women with preeclampsia were evaluated: no therapy, selective prophylaxis for patients with severe preeclampsia, and universal prophylaxis for all patients with preeclampsia. Selective prophylaxis prevented 21% of seizures. The estimated cost for each seizure prevented was estimated to be $3,333, and the cost for each death averted was $166,667. Universal prophylaxis prevented 35% seizures; cost $6,024 for each seizure prevented; and cost $301,205 for each death averted. In a cost-effective comparison of the two strategies, the incremental cost of universal prophylaxis was estimated to be $9,994 for every additional seizure prevented and $469,000 for each additional death averted (32).
A Dutch study evaluating health and economic benefits of expectant monitoring or induction of labor in women with gestational hypertension or mild preeclampsia at term reported that induction of labor is less costly than expectant monitoring because of differences in resource use in the antepartum period. Induction of labor also resulted in less progression to severe disease without increasing the cesarean section rate. In this study, both clinical and economic consequences favored induction of labor in these women (33).
Use of low-dose aspirin to prevent preeclampsia in women at risk is well accepted, and the ASPRE trial conclusively proved its value in preventing preterm preeclampsia. ASPRE was a multicenter, randomized, placebo-controlled trial involving women with singleton pregnancies who were identified by means of first-trimester screening as being at high risk for preterm preeclampsia. Administration of aspirin at a dose of 150 mg per day from 11 to 14 weeks of gestation until 36 weeks of gestation was associated with a significantly lower incidence of preterm preeclampsia than was placebo. There was no significant between-group difference in the incidence of other pregnancy complications or of adverse fetal or neonatal outcomes (34). Administration of aspirin, however, reduced the length of stay in the neonatal intensive care unit (NICU) by about 70%. This reduction could essentially be attributed to a decrease in the rate of births at <32 weeks’ gestation, mainly because of prevention of early preeclampsia. The findings have implications for both short- and long-term healthcare costs as well as infant survival and handicap (35).
Using a decision analysis model, the clinical and economic benefits of a first-trimester screening program based on the Fetal Medicine Foundation algorithm for prediction of early onset preeclampsia coupled with early (<16 weeks) use of low-dose aspirin in those at high risk was simulated and tested with current practice in Canada (36). Among the theoretical 387,516 births per year in Canada, the estimated prevalence of early preeclampsia based on first trimester screening and aspirin use declined 1.5-fold to 705 cases compared to 1,801 cases based on current practice. This resulted in an estimated savings of C$13,130 per case averted (C$14.39 million annually). Universal implementation of a first-trimester screening program for preeclampsia and early intervention with aspirin in women at high risk for early preeclampsia has the potential to prevent a significant number of early onset preeclampsia cases with a substantial cost savings to the healthcare system in Canada (37).
A study from Nepal (38) shows the cost-effectiveness of a pilot project to provide calcium supplementation through the public sector to pregnant women during antenatal care in addition to the existing practice for preeclampsia/eclampsia prevention. Effects were calculated as DALYs averted for mothers and newborns. A decision tree model was used to estimate the cost-effectiveness of three strategies delivered through the public sector: (1) calcium supplementation in addition to the existing standard care practice of treating with magnesium sulfate to prevent eclampsia (MgSO4), (2) standard care practice (MgSO4), and (3) no treatment. The cost to start up calcium introduction in the program in addition to MgSO4 was estimated to be US$44,804, while the costs to support ongoing program implementation was US$72,852. Collectively, the total cost per person per year was $0.44. The calcium supplementation program corresponded to a societal cost of $25.33 ($25.22–$29.50) per DALY averted compared to MgSO4 treatment alone. Primary cost drivers included rate for facility delivery, costs associated with hospitalization, and the probability of developing preeclampsia/eclampsia. The addition of calcium was associated with slight increases in both effect and cost, and an 84% probability of cost-effectiveness above the WTP threshold of US$40. The study concluded that calcium supplementation for pregnant mothers to prevent preeclampsia/eclampsia along with MgSO4 for treatment holds promise for cost-effective reduction of maternal and neonatal morbidity and mortality associated with preeclampsia/eclampsia in Nepal. The findings of this study compare favorably with other low-cost, high-priority interventions recommended for South Asia (38).
A cost-effectiveness study using a decision analysis model assessed a screening strategy for early preeclampsia relative to no screening in Israel (39). The testing strategy with a false-positive rate of 10% and a false-negative rate of 23% cost US$112 per case. The intervention involved prescription of low-dose aspirin and/or calcium. The strategy achieved an 18% reduction in preeclampsia cases in a population where the prevalence of preeclampsia was 1.7%. The cost per case of preeclampsia averted was US$67,000, which was equivalent to US$19,000/QALYs, generally considered cost effective. Using a preeclampsia prevalence of 3%, the cost-effectiveness improved further.
A UK study from the healthcare payer perspective compared the cost effectiveness of adding phosphatidylinositol-glycan biosynthesis class F protein (PlGF) and soluble fms-like tyrosine kinase-1 (sFt-1) for assessment of risk of preeclampsia in a hypertensive patient to standard practice of admission, testing, and treatment in the NHS setting (36). The additional test cost £31.13 and had a false-positive rate of 5% and a false-negative rate of 18%. Standard practice also included an element of screening but used tests with poor accuracy. The modeled population had a preeclampsia rate of 4%. The new approach resulted in a cost saving of £945 per pregnancy and was considered cost effective (36). Several other groups have also examined the health economic rationale for using biomarkers to discriminate between women who develop gestational hypertension or preeclampsia based on the high negative predictive value of the screening tool (40–42).
These recent studies should also be compared to the findings of the 2008 National Institute for Health Research Health Technology Assessment (HTA) that published a detailed consideration of the evidence relating to screening for preeclampsia (43). This group assessed the accuracy of 27 potential screening tests, and working with the Cochrane Collaboration, the evidence on the effectiveness of 16 potential interventions was examined. Like other economic evaluations, it used modeling to assess the cost-effectiveness of interventions in a population at low risk of preeclampsia (2.5%). Unlike other modeling exercises, it systematically considered all possible tests and management interventions available at that time in a variety of different strategies rather than a single one. In particular, it considered strategies in which treatments were applied without any previous testing (“No test/Treat all”). The results led to the conclusion that the most cost-effective approach to reducing preeclampsia was the provision of an effective, affordable, and safe intervention (such as low-dose aspirin) applied to all mothers without previous testing.
From a short-term perspective, the No test/Treat all strategy will always be most effective when the cost of the intervention is less than the cost of the test, and when there is an assumption that all women who could benefit from the intervention will receive and take it. The Test/Treat if positive strategy can only match this if its sensitivity is 100%. The key provisos are that there are no adverse events from the intervention, and pregnant women are willing to take a treatment (however safe and low cost) without being confirmed to being at risk. The best available evidence suggests that only 70% of high-risk women are compliant with low-dose aspirin therapy (44). Moreover, despite its general safety, the use of aspirin in pregnancy for any indication (and not necessarily low dose) has been shown to be associated with a small increase in prevalence of cerebral palsy (45); therefore, its use for preeclampsia may be better restricted to pregnancies at true risk of preterm delivery. Also, if the long-term implications of preeclampsia such as future risk of CVD and type 2 diabetes are taken into account, the No test/Treat all strategy will probably be deemed inferior, as it would fail to identify women at risk who would benefit from intensive postpartum follow-up and lifestyle interventions.
The No test/Treat all strategy may be useful in low-resource settings where assessing risk even through simple history and clinical examination may be constrained because of access, resources, capacity, poor health awareness and literacy, etc. Even in these settings, the No test/Treat all strategy for preventing preterm preeclampsia may still be problematic due to the fundamental issue of poor antenatal coverage and delayed first antenatal visit.
Hyperglycemia in pregnancy
Diabetes mellitus is a now a serious public health problem globally with rising prevalence among all age groups. According to the International Diabetes Federation, diabetes affects an estimated 415 million people globally and is projected to increase to 642 million by 2040; there is also an equally high burden of prediabetes, approximately 318 million people, likely to increase to 481 million by 2040 (46).
The age of onset of prediabetes and diabetes is declining, thereby also affecting younger people at reproductive age; at the same time, the childbearing age is increasing; thus, more women entering pregnancy have risk factors that make them vulnerable to HIP; additionally, both women born low birth weight and women who are overweight and obese are at increased risk of HIP.
More than one-third of people with diabetes and a majority of people with prediabetes remain undiagnosed and unaware (46), particularly the young and women. These groups are frequently not tested at all, because diabetes is mistakenly believed to affect only the elderly.
Hyperglycemia is now the most common medical condition seen during pregnancy. The International Diabetes Federation (IDF) estimates that 21 million live births, one in six (16.8%), occur to women with some form of HIP (46), of which 2.5% may be due to overt diabetes in pregnancy. The other 14.3% (one in seven pregnancies) is due to GDM, a condition that may reflect preexisting prediabetes or may develop due to hormonal changes of pregnancy and is confined to the duration of pregnancy.
HIP significantly increases the risk of pregnancy complications—hypertension, preeclampsia, stillbirths, premature delivery, both large and small for gestational age babies, obstructed labor, postpartum hemorrhage, infections, birth injuries, congenital anomalies, and newborn deaths due to respiratory problems, hypoglycemia, etc. Perinatal complications are listed in Table 11.1.
Table 11.1 Risks associated with hyperglycemia in pregnancy
Spontaneous abortion, intrauterine death, and
Lethal or handicapping congenital malformation
Pregnancy-induced hypertension and preeclampsia
Shoulder dystocia and birth injuries
Prolonged labor, obstructed labor, assisted delivery and cesarean section
Uterine atonia and postpartum hemorrhage
Infant respiratory distress syndrome (IRDS)
Progression of retinopathy