Maternal Clinical Diagnoses and Hospital Variation in the Risk of Cesarean Delivery: Analyses of a National US Hospital Discharge Database
Background:
Cesarean delivery is the most common inpatient surgery in the United States, where 1.3 million cesarean sections occur annually, and rates vary widely by hospital. Identifying sources of variation in cesarean use is crucial to improving the consistency and quality of obstetric care. We used hospital discharge records to examine the extent to which variability in the likelihood of cesarean section across US hospitals was attributable to individual women's clinical diagnoses.
Methods and Findings:
Using data from the 2009 and 2010 Nationwide Inpatient Sample from the Healthcare Cost and Utilization Project—a 20% sample of US hospitals—we analyzed data for 1,475,457 births in 1,373 hospitals. We fitted multilevel logistic regression models (patients nested in hospitals). The outcome was cesarean (versus vaginal) delivery. Covariates included diagnosis of diabetes in pregnancy, hypertension in pregnancy, hemorrhage during pregnancy or placental complications, fetal distress, and fetal disproportion or obstructed labor; maternal age, race/ethnicity, and insurance status; and hospital size and location/teaching status.
The cesarean section prevalence was 22.0% (95% confidence interval 22.0% to 22.1%) among women with no prior cesareans. In unadjusted models, the between-hospital variation in the individual risk of primary cesarean section was 0.14 (95% credible interval 0.12 to 0.15). The difference in the probability of having a cesarean delivery between hospitals was 25 percentage points. Hospital variability did not decrease after adjusting for patient diagnoses, socio-demographics, and hospital characteristics (0.16 [95% credible interval 0.14 to 0.18]). A limitation is that these data, while nationally representative, did not contain information on parity or gestational age.
Conclusions:
Variability across hospitals in the individual risk of cesarean section is not decreased by accounting for differences in maternal diagnoses. These findings highlight the need for more comprehensive or linked data including parity and gestational age as well as examination of other factors—such as hospital policies, practices, and culture—in determining cesarean section use.
Please see later in the article for the Editors' Summary
Vyšlo v časopise:
Maternal Clinical Diagnoses and Hospital Variation in the Risk of Cesarean Delivery: Analyses of a National US Hospital Discharge Database. PLoS Med 11(10): e32767. doi:10.1371/journal.pmed.1001745
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pmed.1001745
Souhrn
Background:
Cesarean delivery is the most common inpatient surgery in the United States, where 1.3 million cesarean sections occur annually, and rates vary widely by hospital. Identifying sources of variation in cesarean use is crucial to improving the consistency and quality of obstetric care. We used hospital discharge records to examine the extent to which variability in the likelihood of cesarean section across US hospitals was attributable to individual women's clinical diagnoses.
Methods and Findings:
Using data from the 2009 and 2010 Nationwide Inpatient Sample from the Healthcare Cost and Utilization Project—a 20% sample of US hospitals—we analyzed data for 1,475,457 births in 1,373 hospitals. We fitted multilevel logistic regression models (patients nested in hospitals). The outcome was cesarean (versus vaginal) delivery. Covariates included diagnosis of diabetes in pregnancy, hypertension in pregnancy, hemorrhage during pregnancy or placental complications, fetal distress, and fetal disproportion or obstructed labor; maternal age, race/ethnicity, and insurance status; and hospital size and location/teaching status.
The cesarean section prevalence was 22.0% (95% confidence interval 22.0% to 22.1%) among women with no prior cesareans. In unadjusted models, the between-hospital variation in the individual risk of primary cesarean section was 0.14 (95% credible interval 0.12 to 0.15). The difference in the probability of having a cesarean delivery between hospitals was 25 percentage points. Hospital variability did not decrease after adjusting for patient diagnoses, socio-demographics, and hospital characteristics (0.16 [95% credible interval 0.14 to 0.18]). A limitation is that these data, while nationally representative, did not contain information on parity or gestational age.
Conclusions:
Variability across hospitals in the individual risk of cesarean section is not decreased by accounting for differences in maternal diagnoses. These findings highlight the need for more comprehensive or linked data including parity and gestational age as well as examination of other factors—such as hospital policies, practices, and culture—in determining cesarean section use.
Please see later in the article for the Editors' Summary
Zdroje
1. US Centers for Disease Control and Prevention (2014) FastStats: inpatient surgery. Available: http://www.cdc.gov/nchs/fastats/inpatient-surgery.htm. Accessed 15 September 2014.
2. MenackerF, HamiltonBE (2010) Recent trends in cesarean delivery in the United States. NCHS Data Brief 35: 1–8.
3. OstermanMJK, MartinJA (2013) Changes in cesarean delivery rates by gestational age: United States, 1996–2011. NCHS Data Brief 124: 1–8.
4. HamiltonBE, MartinJA, VenturaSJ (2012) Births: preliminary data for 2011. Natl Vital Stat Rep 61: 1–18.
5. EckerJ, FrigolettoF (2007) Cesarean delivery and the risk-benefit calculus. N Engl J Med 356: 885–888.
6. Lydon-RochelleM, HoltVL, MartinDP, EasterlingTR (2000) Association between method of delivery and maternal rehospitalization. JAMA 283: 2411–2416.
7. PriorE, SanthakumaranS, GaleC, PhilippsLH, ModiN, et al. (2012) Breastfeeding after cesarean delivery: a systematic review and meta-analysis of world literature. Am J Clin Nutr 95: 1113–1135.
8. Lewis RM, Mckoy JN, Andrews JC, Jerome RN, Likis FE, et al. (2012) Future research needs for strategies to reduce cesarean birth in low-risk women. Rockville (Maryland): Agency for Healthcare Research and Quality. Available: http://www.effectivehealthcare.ahrq.gov/ehc/products/481/1297/FRN22_C-Section_FinalReport_20130107.pdf. Accessed 15 September 2014.
9. SilverRM, LandonMB, RouseDJ, LevenoKJ, SpongCY, et al. (2006) Maternal morbidity associated with multiple repeat cesarean deliveries. Obstet Gynecol 107: 1226–1232.
10. SilverRM (2012) Implications of the first cesarean: perinatal and future reproductive health and subsequent cesareans, placentation issues, uterine rupture risk, morbidity, and mortality. Semin Perinatol 36: 315–323.
11. MenackerF, MacDormanMF, DeclercqE (2010) Neonatal mortality risk for repeat cesarean compared to vaginal birth after cesarean (VBAC) deliveries in the United States, 1998–2002 birth cohorts. Matern Child Health J 14: 147–154.
12. De LucaR, BoulvainM, IrionO, BernerM, PfisterRE (2009) Incidence of early neonatal mortality and morbidity after late-preterm and term cesarean delivery. Pediatrics 123: e1064–e1071.
13. QueenanJT (2011) How to stop the relentless rise in cesarean deliveries. Obstet Gynecol 118: 199–200.
14. ScottJR (2011) Vaginal birth after cesarean delivery: a common-sense approach. Obstet Gynecol 118: 342–350.
15. LoweNK (2013) The overuse of cesarean delivery. J Obstet Gynecol Neonat Nurs 42: 135–136.
16. ShortenA (2007) Maternal and neonatal effects of caesarean section. BMJ 335: 1003–1004.
17. RobsonM, HartiganL, MurphyM (2013) Methods of achieving and maintaining an appropriate caesarean section rate. Best Pract Res Clin Obstet Gynaecol 27: 297–308.
18. ClarkSL, BelfortMA, HankinsGD, MeyersJA, HouserFM (2007) Variation in the rates of operative delivery in the United States. Am J Obstet Gynecol 196: 526.e1–5.
19. KozhimannilKB, LawMR, VirnigB (2013) Cesarean delivery rates vary tenfold among US hospitals; reducing variation may address quality and cost issues. Health Aff (Millwood) 32: 527–535.
20. CáceresI, ArcayaM, DeclercqE, BelanoffCM, JanakiramanV, et al. (2013) Hospital differences in cesarean deliveries in Massachusetts (US) 2004–2006: the case against case-mix artifact. PLoS ONE 8: e57817.
21. BraggF, CromwellDA, EdozienLC, Gurol-UrganciI, MahmoodTA, et al. (2010) Variation in rates of caesarean section among English NHS trusts after accounting for maternal and clinical risk: cross sectional study. BMJ 341: c5065.
22. ParanjothyS, FrostC, ThomasJ (2005) How much variation in CS rates can be explained by case mix differences? BJOG 112: 658–666.
23. Newhouse JP, Garber A, Graham RP, McCoy MA, Mancher M, et al., editors (2013) Interim report of the Committee on Geographic Variation in Health Care Spending and Promotion of High-Value Care: preliminary committee observations. Washington (District of Columbia): National Academies Press.
24. FisherES, BynumJP, SkinnerJS (2009) Slowing the growth of health care costs—lessons from regional variation. N Engl J Med 360: 849–852.
25. Agency for Healthcare Research and Quality (2013) Introduction to the HCUP nationwide inpatient sample (NIS): 2011. Rockville (Maryland): Agency for Healthcare Research and Quality. Available: http://www.hcup-us.ahrq.gov/db/nation/nis/NIS_Introduction_2011.pdf. Accessed 18 September 2014.
26. Healthcare Cost and Utilization Project (2014) NIS database documentation: the National (Nationwide) Inpatient Sample (NIS). Rockville (Maryland): Agency for Healthcare Research and Quality. Available: http://www.hcup-us.ahrq.gov/db/nation/nis/nisdbdocumentation.jsp. Accessed 15 September 2014.
27. DimickJB, NicholasLH, RyanAM, ThummaJR, BirkmeyerJD (2013) Bariatric surgery complications before vs after implementation of a national policy restricting coverage to centers of excellence. JAMA 309: 792–799.
28. BarbashGI, GliedSA (2010) New technology and health care costs: the case of robot-assisted surgery. N Engl J Med 363: 701–704.
29. Kuklina EV, WhitemanMK, HillisSD, JamiesonDJ, MeikleSF, et al. (2008) An enhanced method for identifying obstetric deliveries: implications for estimating maternal morbidity. Matern Child Health J 12: 469–477.
30. KuklinaEV, MeikleSF, JamiesonDJ, WhitemanMK, BarfieldWD, et al. (2009) Severe obstetric morbidity in the United States: 1998–2005. Obstet Gynecol 113: 293–299.
31. Agency for Healthcare Research and Quality (2014) AHRQ Inpatient Quality Indicator #33: primary cesarean delivery rate, uncomplicated. Technical specifications. Washington (District of Columbia): Agency for Healthcare Research and Quality.
32. RobsonM (2001) Classification of caesarean sections. Fetal Matern Med Rev 12: 23–39.
33. SpiegelhalterDJ (2005) Funnel plots for comparing institutional performance. Stat Med 24: 1185–1202.
34. Subramanian SV, Jones K, Duncan C (2003) Multilevel methods for public health research. In: Kawachi I, Berkman L, eds. Neighborhoods and health. New York: Oxford University Press.
35. Rasbash J, Charlton C, Browne WJ, Healy M, Cameron B (2009) MLwiN version 2.1. Bristol: Centre for Multilevel Modelling, University of Bristol.
36. CoonrodDV, DrachmanD, HobsonP, ManriquezM (2008) Nulliparous term singleton vertex cesarean delivery rates: institutional and individual level predictors. Am J Obstet Gynecol 198: 694.e1–11.
37. LintonA, PetersonMR, WilliamsTV (2005) Clinical case mix adjustment of cesarean delivery rates in U.S. military hospitals, 2002. Obstet Gynecol 105: 598–606.
38. CoralloAN, CroxfordR, GoodmanDC, BryanEL, SrivastavaD, et al. (2014) A systematic review of medical practice variation in OECD countries. Health Policy 114: 5–14.
39. SchoenC, OsbornR, SquiresD, DotyMM (2013) Access, affordability, and insurance complexity are often worse in the United States compared to ten other countries. Health Aff (Millwood) 32: 2205–2215.
40. McCourtC, WeaverJ, StathamH, BeakeS, GambleJ, et al. (2007) Elective cesarean section and decision making: a critical review of the literature. Birth 34: 65–79.
41. American College of Obstetricians and Gynecologists, Society for Maternal–Fetal Medicine (2014) Obstetric care consensus no. 1: safe prevention of the primary cesarean delivery. Obstet Gynecol 123: 693–711.
42. BrennanDJ, RobsonMS, MurphyM, O'HerlihyC (2009) Comparative analysis of international cesarean delivery rates using 10-group classification identifies significant variation in spontaneous labor. Am J Obstet Gynecol 201: 308.e1–8.
43. AngoodPB, ArmstrongEM, AshtonD, BurstinH, CorryMP, et al. (2010) Blueprint for action steps toward a high-quality, high-value maternity care system. Womens Health Issues 20 (Suppl 1) S18–S49.
44. SpongCY, BerghellaV, SaadeGR, WenstromKD, MercerBM (2012) Preventing the first cesarean delivery. Obstet Gynecol 120: 1181–1193.
45. CarterMC, CorryM, DelbancoS, FosterTC, FriedlandR, et al. (2010) 2020 vision for a high-quality, high-value maternity care system. Womens Health Issues 20 (Suppl 1) S7–S17.
46. MainEK, MortonCH, MelsopK, HopkinsD, GiulianiG, et al. (2012) Creating a public agenda for maternity safety and quality in cesarean delivery. Obstet Gynecol 120: 1194–1198.
47. MartinJA, HamiltonBE, OstermanMJK, CurtainSC, MatthewsTJ, et al. (2013) Births: final data for 2012. Natl Vital Stat Rep 62: 1–72 Available: http://www.cdc.gov/nchs/data/nvsr/nvsr62/nvsr62_09.pdf. Accessed 18 September 2014.
48. MarkusAR, RosenbaumS (2010) The role of Medicaid in promoting access to high-quality, high-value maternity care. Womens Health Issues 20 (Suppl 1) S67–S78.
49. SakalaC, YangYT, CorryMP (2013) Maternity care and liability: pressing problems, substantive solutions. Womens Health Issues 23: e7–13.
50. KozhimannilKB, ShippeeTP, AdegokeO, VimigB (2013) Trends in hospital-based childbirth care: the role of health insurance. Am J Manag Care 19: e125–e132.
51. ShortenA (2010) Bridging the gap between mothers and medicine: “new insights” from the NIH Consensus Conference on VBAC. Birth 37: 181–183.
52. MainEK (2009) New perinatal quality measures from the National Quality Forum, the Joint Commission and the Leapfrog Group. Curr Opin Obstet Gynecol 21: 532–540.
53. JamesBC, SavitzLA (2011) How intermountain trimmed health care costs through robust quality improvement efforts. Health Aff (Millwood) 30: 1185–1191.
54. MazzaF, KitchensJ, KerrS, MarkovichA, BestM, et al. (2007) Eliminating birth trauma at Ascension Health. Jt Comm J Qual Patient Saf 33: 15–24.
55. GholitabarM, UllmanR, JamesD, GriffithsM (2011) Caesarean section: summary of updated NICE guidance. BMJ 343: d7108.
56. BailitJ (2012) Impact of non-clinical factors on primary cesarean deliveries. Semin Perinatol 36: 395–398.
57. LipkindHS, DuzyjC, RosenbergTJ, FunaiEF, ChavkinW, et al. (2009) Disparities in cesarean delivery rates and associated adverse neonatal outcomes in New York City hospitals. Obstet Gynecol 113: 1239–1247.
58. MurthyK, GrobmanW, LeeT, HollJL (2007) Association between rising professional liability insurance premiums and primary cesarean delivery rates. Obstet Gynecol 110: 1264–1269.
59. EpsteinAJ, NicholsonS (2009) The formation and evolution of physician treatment styles: an application to cesarean sections. J Health Econ 28: 1126–1140.
60. RosenblattRA, DobieSA, HartLG, SchneeweissR, GouldD, et al. (1997) Interspecialty differences in the obstetric care of low-risk women. Am J Public Health 87: 344–351.
61. KozhimannilKB, AveryMD, TerrellCA (2012) Recent trends in clinicians providing care to pregnant women in the United States. J Midwifery Womens Health 57: 433–438.
62. KozhimannilKB, HardemanRR, AttanasioLB, Blauer-PetersonC, BrienMO (2013) Doula care, birth outcomes, and costs among Medicaid beneficiaries. Am J Public Health 103: 113–121.
63. HodnettED, GatesS, HofmeyrGJ, SakalaC (2013) Continuous support for women during childbirth. Cochrane Database Syst Rev 7: CD003766.
64. GoyertGL, BottomsSF, TreadwellMC, NehraPC (1989) The physician factor in cesarean birth rates. N Engl J Med 320: 706–709.
65. BurnsLR, GellerSE, WholeyDR (1995) The effect of physician factors on the cesarean section decision. Med Care 33: 365–382.
66. MainEK, MooreD, FarrellB, SchimmelLD, AltmanRJ, et al. (2006) Is there a useful cesarean birth measure? Assessment of the nulliparous term singleton vertex cesarean birth rate as a tool for obstetric quality improvement. Am J Obstet Gynecol 194: 1644–1651.
67. MazzaF, KitchensJ, AkinM, ElliottB, FowlerD, et al. (2008) The road to zero preventable birth injuries. Jt Comm J Qual Patient Saf 34: 201–205.
68. MannS, PrattS, GluckP, NielsenP, RisserD, et al. (2006) Assessing quality in obstetrical care: development of standardized measures. Jt Comm J Qual Patient Saf 32: 497–505.
69. GreeneSM, ReidRJ, LarsonEB (2012) Implementing the learning health system: from concept to action. Ann Intern Med 157: 207–210.
70. BerthelsenCL (2000) Evaluation of coding data quality of the HCUP Nationwide Inpatient Sample. Top Health Inf Manage 21: 10–23.
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