Bypassing primary care clinics for childbirth: a cross-sectional study in the Pwani region, United Republic of Tanzania
Margaret E Kruk a, Sabrina Hermosilla a, Elysia Larson a & Godfrey M Mbaruku b
a. 600 West 168th Street, Room 606, Mailman School of Public Health, Columbia University, New York, NY 10032, United States of America.
b. Ifakara Health Institute, Dar es Salaam, United Republic of Tanzania.
Correspondence to Margaret E Kruk (e-mail: email@example.com).
(Submitted: 20 June 2013 – Revised version received: 12 November 2013 – Accepted: 13 December 2013 – Published online: 05 February 2014.)
Bulletin of the World Health Organization 2014;92:246-253. doi: http://dx.doi.org/10.2471/BLT.13.126417
Although maternal mortality is declining globally, it remains persistently high in sub-Saharan Africa, with 56% of the 287 000 maternal deaths worldwide in 2010 occurring in this area.1 Reducing maternal mortality requires that women deliver with a skilled health-care professional who can detect and manage or refer obstetric complications that can arise without warning.2,3 However, only half of all deliveries in sub-Saharan Africa are attended by health professionals. This is a central obstacle to reaching Millennium Development Goal 5, which calls for reducing maternal mortality by 75% between 1990 and 2015.4,5 To increase coverage, countries in Africa and other low-income areas have focused on expanding the primary care system, typically through outpatient clinics staffed with nurses and midwives who can provide basic obstetric care.6,7 These clinics represent the base of a service pyramid in which most women deliver at first-level clinics and women with high-risk pregnancies or those who develop complications are referred to hospitals. This service delivery model is supported by global policy guidance.8–10
The United Republic of Tanzania is the largest country in eastern Africa. Its population is 34.4 million and life expectancy is 51 years.11 The country has a maternal mortality ratio of 460 deaths per 100 000 live births, similar to the sub-Saharan African average, and a fertility rate of 5.4 children per woman.11 Ninety-six per cent of women attend at least one antenatal care visit but just over half deliver in a health facility, with substantial regional variation.11 Since independence, the United Republic of Tanzania has built up an extensive primary care system, with most people living 5 to 10 km from a clinic.12 Primary care clinics (referred to locally as “dispensaries”) are outpatient facilities consisting of several rooms and are staffed by nurses and clinical officers who provide basic preventive and curative services, including delivery care. National policy states that primary care clinics should provide basic emergency care for delivery complications.13 However, primary care clinics tend to have poor infrastructure, to lack equipment and to be understaffed, particularly in rural areas.14
In this study, we explored women’s revealed preference for the primary-care-focused model of obstetric care. Specifically, we assessed the extent to which women in rural areas with good access to primary care clinics that offered obstetric services choose to deliver in health centres or hospitals and examined the individual and health system determinants of bypassing. We further explored the costs and quality of care received by women who bypassed. We then discuss the implications of our findings for health system organization.
Study setting and participants
This survey was based on baseline data collected for a cluster-randomized study that tested models for improving the quality of maternal health care in four districts of Pwani region in the United Republic of Tanzania: Bagamoyo, Kisarawe, Kibaha Rural and Mkuranga (ISRCTN 17107760). Pwani region is in the eastern part of the United Republic of Tanzania, north and east of the largest city, Dar es Salaam. The region is primarily rural and most of the population is employed in agriculture or unskilled manual labour.
The Ministry of Health assigns each village to a local primary care clinic (hereafter referred to as “clinics”). Clinics are open from 7:30 to 15:30, with providers available for emergency after-hours care, including delivery. Staff are trained and expected to perform basic emergency obstetric care and to refer patients with emergency conditions to hospital.15 In addition, each administrative division has health centres with inpatient services that serve from 6000 to 10 000 people and are staffed by nurses and assistant medical officers. Each district has at least one district hospital staffed by a few physicians and with an operating theatre.
Study facilities were 24 government-managed clinics with the highest volumes of deliveries between January and June 2011 in their districts. The clinics had a mean of four health-care workers, at least one of whom was a medically trained staff member (e.g. clinical officer or nurse midwife).
Women were selected to complete a structured interview from a full census of all households in the study clinic catchment areas (total, 30 076 households). Eligibility was limited to those who had delivered between 6 weeks and 1 year before the interview, were at least 15 years of age and lived within the catchment area of a study facility. Eligible women were informed of the purpose of the study and their right to refuse participation. Interviews were performed after receipt of written consent from the participant or, in the case of minors, upon receipt of assent from the participant and consent from their guardian.
The study was approved by the ethics review boards at Columbia University, the Ifakara Health Institute in the United Republic of Tanzania and the Tanzanian National Institute for Medical Research.
The survey composing the structured interview and the consent forms were developed in English, translated to Swahili, back-translated to English and pre-tested to ensure accuracy. Questions covered demographic and household characteristics, child and maternal health and health-care characteristics, health system use and satisfaction and health-care preferences. The survey lasted 45 to 60 minutes and was conducted in Swahili by six teams of local interviewers using hand-held tablet computers with Pendragon Forms VI software (Pendragon Software Corporation, Chicago, United States of America). All interviewers underwent 11 days of training in research ethics, data collection methods and the survey instrument. Supervisors observed one interview per day and conducted partial re-interviews for 3% of interviews. The population-based survey of women, conducted as part of the baseline assessment for the cluster-randomized study, was conducted between 13 February and 28 April 2012.
Assessment of the 24 clinics was conducted from 5 December 2011 to 15 May 2012. This was done using a structured questionnaire adapted from the needs assessment created by the Averting Maternal Death and Disability Program and the United Nations system that has been previously used in more than 30 countries, including the United Republic of Tanzania.8 The survey included questions regarding human resources, infrastructure and the services available.
We conducted two separate analyses. In the first we explored the determinants of bypassing clinics and in the second we used bivariate analyses to compare the transaction costs and quality of care of bypassers and non-bypassers. Bypassers were defined as women who delivered their youngest child at a health centre or hospital (secondary or tertiary level facility) and were not referred there by a health-care provider; non-bypassers were defined as women who delivered their most recent child at a clinic.
On the basis of a literature review and the utilization model of Andersen, we identified the following determinants of bypassing: demographic and household characteristics, women’s experience with and perceptions of the health system and health system characteristics.16–20 Variables were categorized to test hypotheses suggested by the extant literature and/or to reflect the distribution of our variables with the intent to create a parsimonious model. Demographic and household variables included age (teenage mothers and older mothers, who are potentially at higher risk, were compared to women aged 20–35 years); marital status; parity, because first-time mothers have been shown to seek higher-level facilities and may be counselled by providers to use those facilities; literacy; and television exposure, because media exposure has been shown to promote urban behavioural norms. A relative index of wealth was constructed using principal component analysis of a set of 18 questions on ownership of household assets.21 Women in the 80th wealth percentile or above were compared with those in lower wealth strata to assess whether wealth is an independent enabler of bypassing.
To assess the influence of clinics on bypassing, we also included women’s experience with their local clinics and subjective perceptions of quality of care. We compared respondents who reported a quality of care rating of fair or poor with those who reported alternate ratings. Frequent users of health care were defined as women who used their clinic for any reason more than five times over the previous year (frequency of use, 80th percentile or above). Objective measures indicative of quality of care at clinics were based on the framework first articulated by Donabedian.22 We selected the following structure and process measures: clinic infrastructure, performance of basic emergency obstetric care and participation in community outreach.
To build a multivariate model predicting bypassing, we conducted bivariate logistic regression analyses between bypassing and variables derived from the literature and categorized as described above. For the adjusted model, we retained variables that were significant at an α level of 0.10. We then performed multivariable logistic regression to estimate adjusted associations between potential determinants and bypasser status. We included a fixed effect for the woman’s district to account for between-district differences in population density, availability of a road network and availability and quality of higher-level facilities, all of which are managed by the district. Standard errors were adjusted using robust variance estimation to account for dependence of women living in the same clinic catchment area.
To compare transaction costs and delivery experience of women who bypassed versus those who did not, we asked women about the services they received, their perception of quality, their satisfaction with the services received, payment and the distance they travelled. Questions regarding each subject’s perception of the quality of care were asked using a five-point Likert scale ranging from “excellent” to “poor”. The subjects’ satisfaction with the care received was determined using a four-point Likert scale ranging from “very satisfied” to “very dissatisfied”. Their responses were then dichotomized into “excellent or very good” versus “good, fair or poor” for questions regarding quality and into “very satisfied” versus “somewhat satisfied, somewhat dissatisfied or very dissatisfied” for questions regarding satisfaction.
To determine the cost of each subject’s most recent delivery, we asked about specific costs for relevant goods and services. These costs were converted to United States dollars using the average exchange rate for the year before data collection.23 We calculated a measure of distance to the delivery facility by using average speeds of travel (5 km/h by foot, 10 km/h by bicycle, 25 km/h by motorcycle and 50 km/h by car/bus) for the subject’s stated transportation method. We then conducted bivariate logistic regression to assess the association between bypasser status and variables related to women’s delivery experience.
Data were imported into Stata, version 12 (StataCorp LP, College Station, USA), for analysis and variables were examined for missing values and outliers. Univariate statistics were calculated for individual and clinic-level characteristics.
We interviewed 3019 of 3238 eligible women (93%). Non-response was predominantly attributable to non-availability of the respondent after three attempts to locate her (204/3238 [6%]) and rarely because of refusal (15 [< 1%]). Of the interviewed women, 71.0% (2144) delivered their most recent child in a health facility; this proportion is consistent with population-representative data from Pwani region (73.1%).11
A total of 246 women who delivered in a facility (11.5%) were referred to the health centre where they delivered. This left 1898 women for inclusion in the analysis. Of these, 794 (41.8%) bypassed their clinic and 1104 (58.2%) delivered at their clinic. Among the 794 interviewees who bypassed, 73.4% delivered in government hospitals. Additional characteristics of the 1898 participants, as well as information about their local health systems, are summarized in Table 1.
Table 1. Characteristics of the study population and local health system, United Republic of Tanzania, 2012
Among study participants, 1667 (87.8%) had complete information for all the variables of interest for the final regression model. Because the findings resulting from imputed analysis did not significantly differ from those resulting from non-imputed analysis, results of non-imputed analysis are presented. In the final adjusted model, bypassers were more likely than non-bypassers to be delivering their first child (odds ratio, OR: 2.53; 95% confidence interval, CI: 1.93–3.30; P < 0.001), to have used their clinic for any reason more than five times within the past year (OR: 1.23; 95% CI: 1.00–1.50; P = 0.045) and to have rated the quality of care at their clinic as poor (OR: 1.29; 95% CI: 1.00–1.66; P = 0.049) (Table 2). Bypassers were less likely than non-bypassers to be living in the catchment area of a clinic that had received an upgrade or renovation of some type within the past year (OR: 0.39; 95% CI: 0.18–0.84; P = 0.016) or had performed four or more signal functions (the most common of which was administration of parenteral oxytocics) for obstetric and neonatal care (OR: 0.19; 95% CI: 0.08–0.41; P < 0.001).
Table 2. Multivariable associations between bypasser status and characteristics of subjects and local primary care clinics, United Republic of Tanzania, 2012
More bypassers than non-bypassers reported receiving a blood transfusion (P = 0.049) and an examination before their own discharge (P < 0.001) and their neonates’ (P = 0.007; Table 3). Although they travelled significantly longer and paid significantly more for delivery, bypassers were more likely than non-bypassers to report being very satisfied with the overall delivery experience (P < 0.001). Bypassers’ ratings of quality of care were significantly higher than those reported by non-bypassers in six of seven quality measures.
Table 3. Bivariate analysis comparing travel, payment, and quality of care among bypassers and non-bypassers, United Republic of Tanzania, 2012
We found that 41.8% of women who delivered children in a health-care facility in rural parts of the United Republic of Tanzania chose to deliver in a hospital or health centre rather than a local primary care clinic. This is striking because all women lived near a functioning clinic with delivery services and the sample excluded women who were referred to hospital by health providers.
Bypassing involved substantial logistical challenges and higher costs, largely driven by expenses related to transportation. Nearly 16% of bypassers reported having to borrow money or sell household assets to finance delivery, a measure of financial hardship that can lead to impoverishment.24 These data underline that access to higher-level facilities is inequitable, with the wealthiest women more likely to obtain secondary services, and that despite the United Republic of Tanzania’s policy of free delivery, out-of-pocket costs for transport lead to financial hardship for families seeking hospital care.
Among women delivering their first child, the odds of bypassing were more than twice the odds of not bypassing. This may be because women and/or their antenatal care providers consider first deliveries risky and seek out advanced obstetric care for these pregnancies. Other evidence suggests that in the United Republic of Tanzania, first deliveries are associated with higher use of hospitals and, in China, with higher rates of maternal request for Caesarean delivery.17,25
A total of 66% of subjects made four or more antenatal care visits and 31% had visited their clinic more than five times in the previous year for reasons of any type, but this did not encourage subjects to return to their clinic for delivery. This decision was not mediated by poor self-reported health and thus may have been prompted by having more information about the deficiencies of the clinic. Women’s reported rating of poor quality at their clinic further increased bypassing. Other studies have found that quality of care in hospitals is better than in lower-level facilities14,26 and that the infrastructure and equipment at primary care clinics in the United Republic of Tanzania and other countries in the region is inadequate.27,28 Dissatisfaction with quality of care at local facilities has been shown to motivate bypassing in other studies but the sole study that examined bypassing for delivery did not include objective measures of clinic quality.17–19
In terms of the quality of their health care experience, bypassers were more likely than non-bypassers to be examined before discharge and they rated the quality of care significantly higher than non-bypassers on six of seven measures. Overall, women who delivered in hospitals or health centres were nearly twice as likely to be very satisfied with their birth experience as women who delivered in primary care. Other studies have similarly documented better quality of care in hospitals versus lower-level facilities.15,29
A strength of this study was the availability of objective data on the quality of the structure and process of care in the primary care facilities. We found that recent facility upgrades in a woman’s catchment clinic reduced her probability of bypassing and that the number of basic emergency obstetric services performed in the clinic in the previous three months was a strong and consistent predictor of women’s behaviour. These results support the notion that Tanzanian women have good information about the obstetric care available in clinics and act on this information.18
The study has several potential limitations. Our analysis is based on cross-sectional data, which makes it impossible to draw causal inferences about the determinants of bypassing. However, since most predictors preceded the delivery, reverse causation is unlikely. ORs may overestimate likelihood when the outcome is relatively common, as in this analysis. The health system characteristics investigated are indicators of the capacity of the health system available to women and are not linked to the time at which the women delivered. Because our study participants were selected on the basis of good access to primary health care, our results are not generalizable to the rest of the United Republic of Tanzania, where bypassing is even higher. Because data were obtained via survey, recall bias is possible, although the potential for such bias is low because women delivered within one year of the survey. Finally, our data did not permit us to assess the availability of hospitals/health centres and the availability of transportation in bypassing decisions.
Our findings have important implications for health system organization. Although primary care serves many important functions, it may not be the optimal platform for providing high-quality delivery care. Policy-makers should consider gradually shifting the provision of obstetric care to health centres and hospitals, with primary care clinics playing a back-up role. This would have several advantages over the current model. First, it could improve health outcomes for mothers and neonates by concentrating obstetric care in high-volume settings with more competent providers and better equipment. Second, it would better match the expectations of pregnant women and thus strengthen the responsiveness of the health system to users. Finally, it could improve efficiency in the health system and free the funds invested, in maintaining the infrastructure and providers needed to attend (infrequent) deliveries, to be spent on other priorities. Such reorganization would require careful consideration of health system funding, transportation and referral. Health centres and hospitals would probably need to expand their maternity wards and vehicle fleets and improve transport protocols and communication. To promote equitable access to higher-level care, poor women will need to be given transport subsidies, vouchers and other support. Useful models for this exist in other countries.29–32
Obstetric care needs to be of high quality and should be used universally to reduce maternal mortality. The preferences and experiences of women should thus inform health system design. Looking into the future, as Tanzanian families become wealthier, smaller and more experienced with the health-care system, bypassing is likely to rise. Shifting the focus of delivery care to health centres and hospitals could both save more lives and inspire greater confidence in the health system while making best use of scarce resources.
We thank Angela Kimweri and Festo Mazungani and our team of interviewers, for their research assistance; Drs. Beatrice Byalugaba and Neema Rusibamayila and the Bagamoyo, Kisarawe, Kibaha Rural and Mkuranga district health authorities, for their continual support of the project; and the participating women, for generously sharing their health system experiences.
This study was funded by the National Institute of Allergy and Infectious Diseases (grant 1R01 AI093182). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The sponsor of the study had no role in study design; data gathering, analysis and interpretation; or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.
- Trends in maternal mortality: 1990 to 2010: WHO, UNICEF and The World Bank estimates. Geneva: World Health Organization; 2012. Available from: http://whqlibdoc.who.int/publications/2012/9789241503631_eng.pdf [accessed 16 December 2013].
- Ronsmans C, Graham WJ, Lancet Maternal Survival Series steering group. Maternal mortality: who, when, where, and why. Lancet 2006; 368: 1189-200 http://dx.doi.org/10.1016/S0140-6736(06)69380-X pmid: 17011946.
- World health report 2005: make every mother and child count. Geneva: World Health Organization; 2005. Available from: http://www.who.int/whr/2005/en/ [accessed 10 January 2013].
- Bryce J, Daelmans B, Dwivedi A, Fauveau V, Lawn JE, Mason E, et al., Countdown Coverage Writing Group, Countdown to 2015 Core Group, et al. Countdown to 2015 for maternal, newborn, and child survival: the 2008 report on tracking coverage of interventions. Lancet 2008; 371: 1247-58 http://dx.doi.org/10.1016/S0140-6736(08)60559-0 pmid: 18406859.
- Bhutta ZA, Chopra M, Axelson H, Berman P, Boerma T, Bryce J, et al., et al. Countdown to 2015 decade report (2000–10): taking stock of maternal, newborn, and child survival. Lancet 2010; 375: 2032-44 http://dx.doi.org/10.1016/S0140-6736(10)60678-2 pmid: 20569843.
- Campbell O, Graham WJ, Lancet Maternal Survival Series steering group. Strategies for reducing maternal mortality: getting on with what works. Lancet 2006; 367: 368 pmid: 16443045.
- Brazier E, Andrzejewski C, Perkins ME, Themmen EM, Knight RJ, Bassane B. Improving poor women’s access to maternity care: Findings from a primary care intervention in Burkina Faso. Soc Sci Med 2009; 69: 682-90 http://dx.doi.org/10.1016/j.socscimed.2009.06.023 pmid: 19596165.
- Paxton A, Bailey P, Lobis S, Fry D. Global patterns in availability of emergency obstetric care. Int J Gynaecol Obstet 2006; 93: 300-7 http://dx.doi.org/10.1016/j.ijgo.2006.01.030 pmid: 16682039.
- Pearson L, Shoo R. Availability and use of emergency obstetric services: Kenya, Rwanda, Southern Sudan, and Uganda. Int J Gynaecol Obstet 2005; 88: 208-15 http://dx.doi.org/10.1016/j.ijgo.2004.09.027 pmid: 15694109.
- Koblinsky M, Matthews Z, Hussein J, Mavalankar D, Mridha MK, Anwar I, et al., Lancet Maternal Survival Series steering group, et al. Going to scale with professional skilled care. Lancet 2006; 368: 1377-86 http://dx.doi.org/10.1016/S0140-6736(06)69382-3 pmid: 17046470.
- Tanzania Demographic and Health Survey 2010. Dar es Salaam & Calverton (MD): National Bureau of Statistics Tanzania & ICF Macro; 2011. Available from: http://www.measuredhs.com/pubs/pdf/FR243/FR243%5B24June2011%5D.pdf [accessed 16 December 2013].
- Tanzania Demographic and Health Survey 1996. Dar es Salaam: Bureau of Statistics Planning Commission of Tanzania; 1997.
- National health policy. Dar es Salaam: Ministry of Health of the United Republic of Tanzania; 2003.
- Hsia RY, Mbembati NA, Macfarlane S, Kruk ME. Access to emergency and surgical care in sub-Saharan Africa: the infrastructure gap. Health Policy Plan 2012; 27: 234-44 http://dx.doi.org/10.1093/heapol/czr023 pmid: 21441566.
- Lobis S, Mbaruku G, Kamwendo F, McAuliffe E, Austin J, de Pinho H. Expected to deliver: alignment of regulation, training, and actual performance of emergency obstetric care providers in Malawi and Tanzania. Int J Gynaecol Obstet 2011; 115: 322-7 http://dx.doi.org/10.1016/j.ijgo.2011.09.008 pmid: 22036057.
- Yaffee AQ, Whiteside LK, Oteng RA, Carter PM, Donkor P, Rominski SD, et al., et al. Bypassing proximal health care facilities for acute care: a survey of patients in a Ghanaian Accident and Emergency Centre. Trop Med Int Health 2012; 17: 775-81 http://dx.doi.org/10.1111/j.1365-3156.2012.02984.x pmid: 22519746.
- Kruk ME, Mbaruku G, McCord CW, Moran M, Rockers PC, Galea S. Bypassing primary care facilities for childbirth: a population-based study in rural Tanzania. Health Policy Plan 2009; 24: 279-88 http://dx.doi.org/10.1093/heapol/czp011 pmid: 19304785.
- Leonard KL, Mliga GR, Haile Mariam D. Bypassing health centres in Tanzania: revealed preferences for quality. J Afr Econ 2002; 11: 441-71 http://dx.doi.org/10.1093/jae/11.4.441.
- Akin JS, Hutchinson P. Health-care facility choice and the phenomenon of bypassing. Health Policy Plan 1999; 14: 135-51 http://dx.doi.org/10.1093/heapol/14.2.135 pmid: 10538717.
- Aday LA, Andersen R. A framework for the study of access to medical care. Health Serv Res 1974; 9: 208-20 pmid: 4436074.
- Filmer D, Pritchett LH. Estimating wealth effects without expenditure data–or tears: an application to educational enrollments in states of India. Demography 2001; 38: 115-32 pmid: 11227840.
- Donabedian A. The quality of care. How can it be assessed? JAMA 1988; 260: 1743-8 http://dx.doi.org/10.1001/jama.1988.03410120089033 pmid: 3045356.
- Oanda. Historical exchange rates (USD – Tanzanian shilling) [Internet]. Singapore: Oanda; 2013. Available from: http://www.oanda.com/currency/historical-rates/ [accessed 13 March 2013].
- Kruk ME, Goldmann E, Galea S. Borrowing and selling to pay for health care in low- and middle-income countries. Health Aff (Millwood) 2009; 28: 1056-66 http://dx.doi.org/10.1377/hlthaff.28.4.1056 pmid: 19597204.
- Zhang J, Liu Y, Meikle S, Zheng J, Sun W, Li Z. Cesarean delivery on maternal request in southeast China. Obstet Gynecol 2008; 111: 1077-82 http://dx.doi.org/10.1097/AOG.0b013e31816e349e pmid: 18448738.
- Audo MO, Ferguson A, Njoroge PK. Quality of health care and its effects in the utilisation of maternal and child health services in Kenya. East Afr Med J 2005; 82: 547-53 pmid: 16463747.
- Gilson L, Magomi M, Mkangaa E. The structural quality of Tanzanian primary health facilities. Bull World Health Organ 1995; 73: 105-14 pmid: 7704920.
- Hsia RY, Mbembati NA, Macfarlane S, Kruk ME. Access to emergency and surgical care in sub-Saharan Africa: the infrastructure gap. Health Policy Plan 2012; 27: 234-44 pmid: 21441566.
- Lim SS, Dandona L, Hoisington JA, James SL, Hogan MC, Gakidou E. India’s Janani Suraksha Yojana, a conditional cash transfer programme to increase births in health facilities: an impact evaluation. Lancet 2010; 375: 2009-23 http://dx.doi.org/10.1016/S0140-6736(10)60744-1 pmid: 20569841.
- Schmidt JO, Ensor T, Hossain A, Khan S. Vouchers as demand side financing instruments for health care: a review of the Bangladesh maternal voucher scheme. Health Policy 2010; 96: 98-107 http://dx.doi.org/10.1016/j.healthpol.2010.01.008 pmid: 20138385.
- Ir P, Horemans D, Souk N, Van Damme W. Using targeted vouchers and health equity funds to improve access to skilled birth attendants for poor women: a case study in three rural health districts in Cambodia. BMC Pregnancy Childbirth 2010; 10: 1 http://dx.doi.org/10.1186/1471-2393-10-1 pmid: 20059767.
- Barker CE, Bird CE, Pradhan A, Shakya G. Support to the Safe Motherhood Programme in Nepal: an integrated approach. Reprod Health Matters 2007; 15: 81-90 http://dx.doi.org/10.1016/S0968-8080(07)30331-5 pmid: 17938073.