The impact of risk calculation on treatment recommendations made by glaucoma specialists in cases of ocular hypertension

Journal of Glaucoma

Volumn 17, Issue 8, 2008, Pages 631-638

  Boland, Michael V ^a,b   Quigley, Harry A ^a,b   Lehmann, Harold P ^b,c  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b JOHNS HOPKINS UNIVERSITY   (United States)

^c JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Decision support; Ocular hypertension; Risk calculation

Indexed keywords

ADULT; ARTICLE; CALCULATION; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; EYE EXAMINATION; FEMALE; GLAUCOMA; HUMAN; INTRAOCULAR HYPERTENSION; INTRAOCULAR PRESSURE; MAJOR CLINICAL STUDY; MALE; MEDICAL DECISION MAKING; MEDICAL SPECIALIST; OUTCOME ASSESSMENT; PRIORITY JOURNAL; RISK FACTOR; MEDICINE; METHODOLOGY; MIDDLE AGED; OPHTHALMOLOGY; PATHOPHYSIOLOGY; PRACTICE GUIDELINE; RISK ASSESSMENT; VISUAL DISORDER; VISUAL FIELD;

FEMALE; GLAUCOMA; HUMANS; INTRAOCULAR PRESSURE; MALE; MIDDLE AGED; OCULAR HYPERTENSION; OPHTHALMOLOGY; PRACTICE GUIDELINES AS TOPIC; RISK ASSESSMENT; RISK FACTORS; SPECIALTIES, MEDICAL; VISION DISORDERS; VISUAL FIELDS;

EID: 60749097806     PISSN: 10570829     EISSN: None     Source Type: Journal    
DOI: 10.1097/IJG.0b013e3181659e6a     Document Type: Article

References (22)

1. Mansberger SL. A risk calculator to determine the probability of glaucoma. J Glaucoma. 2004;13:345-347.
2. Medeiros FA, Weinreb RN, Sample PA, et al. Validation of a predictive model to estimate the risk of conversion from ocular hypertension to glaucoma. Arch Ophthalmol. 2005;123:1351-1360.
3. Gordon MO, Torri V, Miglior S, et al., Ocular Hypertension Treatment Study Group, European Glaucoma Prevention Study Group. Validated prediction model for the development of primary open-angle glaucoma in individuals with ocular hypertension. Ophthalmology. 2007;114:10-19.
4. Wilson PW, Castelli WP, Kannel WB. Coronary risk prediction in adults (the Framingham Heart Study). Am J Cardiol. 1987;59: 91G-94G.
5. Gordon MO, Beiser JA, Brandt JD, et al. The Ocular Hypertension Treatment Study: baseline factors that predict the onset of primary open-angle glaucoma. Arch Ophthalmol. 2002;120:714-720; discussion 829-830.
6. Brindle P, Beswick A, Fahey T, et al. Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: a systematic review. Heart. 2006;92:1752-1759.
7. Mansberger SL, Cioffi GA. The probability of glaucoma from ocular hypertension determined by ophthalmologists in comparison to a risk calculator. J Glaucoma. 2006;15:426-431.
8. Bobbio M, Fubini A, Detrano R, et al. Diagnostic accuracy of predicting coronary artery disease related to patients' characteristics. J Clin Epidemiol. 1994;47:389-395.
9. Poses RM, Cebul RD, Wigton RS. You can lead a horse to water - improving physicians' knowledge of probabilities may not affect their decisions. Med Decis Making. 1995;15:65-75.
10. Haas JS, Kaplan CP, Gregorich SE, et al. Do physicians tailor their recommendations for breast cancer risk reduction based on patient's risk? J Gen Intern Med. 2004;19:302-309.
11. Gordon MO, Kass MA. The Ocular Hypertension Treatment Study: design and baseline description of the participants. Arch Ophthalmol. 1999;117:573-583.
12. Nagelkerke NJD. A note on a general definition of the coefficient of determination. Biometrika. 1991;78:691-692.
13. Harrell FE. Design: S functions for biostatistical/epidemiologic modeling, testing, estimation, validation, graphics, prediction, and typesetting. 2005.
14. Weinreb RN, Friedman DS, Fechtner RD, et al. Risk assessment in the management of patients with ocular hypertension. Am J Ophthalmol. 2004;138:458-467.
15. Kymes SM, Kass MA, Anderson DR, et al. Management of ocular hypertension: a cost-effectiveness approach from the Ocular Hypertension Treatment Study. Am J Ophthalmol. 2006;141: 997-1008.
16. Friedman DS, Nordstrom B, Mozaffari E, et al. Variations in treatment among adult-onset open-angle glaucoma patients. Ophthalmology. 2005;112:1494-1499.
17. Osheroff JA, Pifer EA, Teich JM, et al. Improving Outcomes With Clinical Decision Support: An Implementer's Guide. USA: Healthcare Information and Management Systems Society; 2005.
18. Randolph AG, Haynes RB, Wyatt JC, et al. Users' Guides to the Medical Literature: XVIII. How to use an article evaluating the clinical impact of a computer-based clinical decision support system. JAMA. 1999;282:67-74.
19. Hunt DL, Haynes RB, Hanna SE, et al. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. JAMA. 1998;280:1339-1346.
20. Kawamoto K, Houlihan CA, Balas EA, et al. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005;330:765.
21. Garg AX, Adhikari NK, McDonald H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005;293: 1223-1238.
22. Chaudhry B, Wang J, Wu S, et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144:742-752.