LA TECNOLOGIA INFORMATICA APLICADA A LA SALUD REPRODUCTIVA POSIBILITA UNA MEJOR PRACTICA CLINICA

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Las novedades en el contexto de la informática aplicada a la salud expanden las posibilidades de perfeccionar los importantes servicios de la salud reproductiva en la actividad médica cotidiana.
Autor:
Suzanne Mitchell
Columnista Experto de SIIC

Institución:
Boston University School of Medicine


Artículos publicados por Suzanne Mitchell
Coautores
Timothy Bickmore* Michael Paasche-Orlow** Charles Williams*** Shaula Forsythe**** Hani Atrash***** Kay Johnson****** Brian Jack*** 
PhD, Northeastern University, Boston, EE.UU.*
MD MPH, Boston University School of Medicine, Boston, EE.UU.**
MD, Boston University School of Medicine, Boston, EE.UU.***
MPH, Boston University School of Medicine, Boston, EE.UU.****
MD MPH, Centers for Disease Control and Prevention, Atlanta, EE.UU.*****
MD MPH, Dartmouth Medical School, Lebanon, EE.UU.******
Recepción del artículo
5 de Noviembre, 2009
Aprobación
26 de Noviembre, 2009
Primera edición
8 de Abril, 2010
Segunda edición, ampliada y corregida
7 de Junio, 2021

Resumen
En abril de 2006, los US Centers for Disease Control and Prevention (CDC) publicaron normativas clínicas acerca de la salud reproductiva con el objetivo de promover mejoras en la evolución de los embarazos en Estados Unidos. La integración de la salud reproductiva en la práctica cotidiana todavía representa un desafío para los médicos clínicos. Esto se debe en parte a la percepción de que la salud reproductiva es una prestación agregada en lugar de un aspecto integral de la atención primaria de las mujeres en edad fértil. La provisión de estas prestaciones por los sistemas de atención primaria se ha limitado debido a la falta de promoción de métodos clínicos que contribuyan a la evaluación del riesgo y los procesos de intervención. Las novedades en el contexto de la informática aplicada a la salud expanden las posibilidades de perfeccionar los importantes servicios de la salud reproductiva en la actividad médica cotidiana. Una revisión de estos avances informáticos relacionados con la salud reproductiva podría contribuir a la optimización de estos servicios por parte de los médicos clínicos.

Palabras clave
salud reproductiva, informática aplicada a la salud, mortalidad infantil


Artículo completo

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Abstract
In April 2006, the US Centers for Disease Control and Prevention (CDC) published clinical guidelines for preconception health and healthcare to promote improvements in pregnancy outcomes in the US. Still, integrating preconception care (PCC) into clinical practice has proven challenging to clinicians. This is partly due to the perception that PCC is an add-on service rather than an integral aspect of primary care for women of reproductive age. Provision of these services by primary care providers has been limited by the lack of development of clinical tools that would assist in the assessment of risk and intervention processes. Novel developments in the field of Health Information Technology (HIT) are expanding opportunities for streamlining important PCC services into routine medical encounters. A review of developments in HIT as it relates to the delivery of PCC would help promote the provision of PCC services among clinicians.

Key words
preconception care, health information technology, infant mortality


Full text
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Clasificación en siicsalud
Artículos originales > Expertos del Mundo >
página   www.siicsalud.com/des/expertocompleto.php/

Especialidades
Principal: Informática Biomédica, Medicina Reproductiva
Relacionadas: Atención Primaria, Epidemiología, Medicina Familiar, Obstetricia y Ginecología, Pediatría, Salud Pública



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Enviar correspondencia a:
Suzanne Mitchell, Boston Medical Center Department of Family Medicine, MA 02118, 5 Dowling . One Boston Medical Center Place, Boston, EE.UU.
Patrocinio y reconocimiento:
El proyecto fue financiado por los subsidios R18HSO17196-01 de la Agency for Healthcare Research and Quality (Dr. Jack) y T32-HP-10028-06 del Department of Health and Human Services (Dr. Mitchell).
Bibliografía del artículo


1. Jack BW, Atrash H, Coonrod DV, Moos, MK, ODonnell J, Johnson K. The clinical content of preconception care: an overview and preparation of this supplement. AJOG 199(6):S266-S279, 2008.
2. National Center for Health Statistics. Health, United States, 2007, with Chartbook on Trends in the Health of americans. Hyattsville, MD, 2007.
3. Mathews TJ, MacDorman MF. Infant mortality from the 2005 period linked birth/infant death data set. National vital statistics reports, vol 57 no 3. Hyattsville, MD, National Center for Health Statistics 2008.
4. Institute of Medicine. Preterm birth: Causes, consequences and prevention. Washington DC, National Academy Press, 2007.
5. Klerman LV, Ramey SL, Goldenberg RL, Marbury S, Hou J, Cliver SP. A randomized trial of augmented prenatal care for multiple-risk, medicaid-eligible African American women. Am J Public Health 91(1):105-111, 2001.
6. Lu MC, Tache V, Alexander GR, Kotelchuck M, Halfon N. Preventing low birth weight: Is Prenatal care the answer? J Matern Fetal Neonatal Med 13(6):362-380, 2003.
7. Stevens-Simon C, Orleans M. Low-birthweight prevention programs: The enigma of failure. Birth 26(3):184-191, 1999.
8. Anderson JE, Ebrahim S, Floyd L, Atrash H. Prevalence of risk factors for adverse pregnancy outcomes during pregnancy and the preconception period. United States, 2002-2004. Matern Child Health J 10(5 Suppl):S101-106, 2006.
9. Petrini J, Hamner HC, Flores AL, Mulinare J, Prue C. Use of supplements containing folic acic among women of childbearing age. United States, 2007. MMWR 57(1):5-8, 2008.
10. Atrash, H, Johnson K, Adams M, Cordero JF, Howse J. Preconception care for improving perinatal outcomes: The time to act. Matern Child Health J 10:S3-S11, 2006.
11. Floyd RL, Sobell M, Velasquez MM, et al. Preventing alcohol-exposed pregnancies: a randomized controlled trial. Am J Prev Med 32:1-10, 2007.
12. Johnson K, Posner SF, Biermann J, Cordero JK, Atrash HK, Parker CS, Boulet S, Curtis MG. Centers for Disease Control and Prevention. Recommendations for improving preconception health and health care-United States: A report of the Cc/ATSDR Preconception Care Workgroup and the Select Panel on Preconception Care. MMWR 55(RR-6):1-23, 2006.
13. Jack BW, Atrash H, Coonrod DV, Moos MK, O'Donnell J, Johnson K. The clinical content of preconception care: an overview and preparation of this supplement. AJOG 199(6):S266-S279, 2008.
14. Frey KA, Files JA. Preconception Healthcare: What women know and believe. Matern Child Health J 10(5 Suppl):S73-77, 2006.
15. Morgan MA, Hawks D, Zinberg S, Schulkin J. What obstetrician-gynecologists think of preconception care. Matern Child Health J 10(5 Suppl):S59-65, 2006.
16. Henderson JT, Weisman CS, Grason H. Are two doctors better than one? Women's physician use and appropriate care. Womens Health Issues 12(3):138-149, 2002.
17. Jack BW, Culpepper L. Preconception care: Risk reduction and health promotion in preparation for pregnancy. Journal of the American Medical Association 264:1147-1149, 1990.
18. Centers for Disease Control and Prevention. Recommendations for improving preconception health and healthcare-United States: a report of the CC/ATSDR Preconception care Workgroup and the Select Panel on Preconception Care. MMWR Morb Mort Wkly Rer 55(No. RR-6):1-23, 2006.
19. Baylor AL. The role of gender and ethnicity in pedagogical agent perception. In proceedings of e-learn (World Conference on E-Learning in Corporate, Government, Healthcare, & Higher Education), Phoenix, Arizona, 2003.
20. Baylor AL, Shen E, Huang X. Which pedagogical agent do learners choose? The effects of gender and ethnicity. In proceedings of e-learn (World Conference on E-Learning in Corporate, Government, Healthcare, & Higher Education). Phoenix, Arizona, 2003.
21. Bickmore T, Pfeifer L, Yin L. The role of gesture in document explanation by embodied conversational agents. International Journal of Semantic Computing, 2, 47-70, 2008.
22. Jack BW, Atrash H, Bickmore T, Johnson K. The future of preconception care: A clinical perspective. Women's Health Issues 18S:S19-S25, 2008.
23. Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: A systematic review. JAMA 280:1339-1346, 1998.
24. Bickmore T, Pfeifer L, Jack BW, editors. Taking the time to care: empowering low health literacy hospital patients with virtual nurse agents proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Boston, MA, 2009.
25. Bickmore T, Caruso L, Clough-Gorr K, Heeren T. "It's just like you talk to a friend" - Relational agents for older adults. Interacting with computers. 17(6):711-35, 2005.
26. Bickmore T, Pfeifer L, Paasche-Orlow M. Using computer agents to explain medical documents to patients with low health literacy. Patient Education and Counseling 75(3):315-20, 2009.
27. Prochaska JO. Multiple health behavior research represents the future of preventive medicine. Preventive Medicine 46:281-285, 2008.
28. Mangunkusumo R, Brug J, Duisterhout J, de Koning H, Raat H. Feasibility, acceptability, and quality of internet-administered adolescent health promotion in a preventive-care setting. Health Educ Res 22(1):1-13, 2007.
29. Card W, Lucas R. Computer interrogation in medical practices. International Journal of Man-Machine Studies 14:49-57, 1981.
30. Ware JE, Kosinski M, Turner-Bowker D, Gandek B. How to score version 2 of the SF-12 health survey. Lincoln, RI, QualityMetric Incorporated, 2002.
31. Landkroon AP, De Weerd S, Van Vliet-Lachotzki E, Steegers EAP. Validation of an internet questionnaire for risk assessment in preconception care (under review).
32. Person NK, Graesser AC, Bautista L, Matthews EC. Evaluating student learning gains in two versions of AutoTutor. In JD Moore, CL Redfield, WL Johnsons, Eds.: Artificial intelligence in education: AI-ED in the wired and wireless future. Amsterdam, IOS Press, pp.286-293.
33. Tudor-Locke C, Bassett DR, Swartz AM, Strath SJ, Parr BB, Reis JP, et al. A preliminary study of one year of pedometer self-monitoring. Ann Behav Med 28(3):158-162, 2004.
34. Kreuter M, Wray R. Tailored and targeted health communicaiton: strategies for enhancing information relevance. American Journal Health Behavior 27(3):S227-S232, 2003.
35. Kreuter MW, McClure SM. The role of culture in health communication. Annu Rev Public Health 25:439-455, 2004.
36. Dunlop AL, Jack BW, Bottalico JN, Lu MC, James A, Shellhaus CS, Haygood-Kane Hallstrom L, Solomon BD, Feero WG, Menard MK, Prasad MR. The clinical content of preconception care: women with chronic medical conditions American Journal of Obstetrics & Gynecology 199(6):S310-S327, 2008.
37. US Department of Health and Human Services, Heallth Resources and Services Administration, Maternal and Child Health Bureau, Women's Health USA 2002. Rockville, MD, US Department of Health and Human Services 2002.
38. Trisolini M, Aggarwal J, Leung M, et al. The Medicare Physician Group practice demonstration: lessons learned on improving quality and efficiency in health care. The Commonwealth Fund, 2008.
39. Strecher VJ, McClure J, Alexander G, Chakraborty B, Nair V, Konkel J, Greene S, Couper M, Carlier C, Wiese C, Little R, Pomerleau C, Pomerleau O. The role of engagement in a tailored web-based smoking cessation program: randomized controlled trial. J Med Internet Res 10(5):e36, 2008.
40. Joseph CL, Peterson E, Havstad S, Johnson CC, Hoerauf S, Stringer S, Gibson-Scipio W, Ownby DR, Elston-Lafata J, Pallonen U, Strecher V. A web-based, tailored asthma management program for urban African American high school students. Asthma in Adolescents Research Team. Am J Respir Crit Care Med 175(9):888-95, 2007.
41. Champion VL, Springston JK, Zollinger TW, Saywell RM Jr, Monahan PO, Zhao Q, Russell KM. Comparison of three interventions to increase mammography screening in low income African American women. Cancer Detect Prev 30(6):535-44, 2006.
42. Khan SA, McFarlane DJ, Li J, Ancker JS, Hutchinson C, Cohall A, Kukafka R. Healthy Harlem: empowering health consumers through social networking, tailoring and web 2.0 technologies. A review of online social networking profiles by adolescents: implications for future research and intervention. AMIA Annu Symp Proc 11:1007, 2007.
43. Williams AL, Merten MJ. Adolescence 43(170):253-74, 2008.

 
 
 
 
 
 
 
 
 
 
 
 
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