Heart Disease and Stroke Prevention: Clinical Decision-Support Systems (CDSS)

The CPSTF finding is based on evidence from a broad systematic review (Bright et al. 2012, search period January 1976-January 2011) that examined the effectiveness of CDSS in improving quality of care and clinical outcomes for a variety of conditions (e.g., CVD prevention, cancer screening, immunization, antenatal care). From this broad review, CDSS studies focused on CVD prevention were identified (39 studies) and combined with evidence from an updated search (6 studies, search period January 2011-October 2012).

The systematic review was conducted on behalf of the CPSTF by a team of specialists in systematic review methods, and in research, practice and policy related to cardiovascular disease prevention.

Detailed results from the systematic review are available in the CPSTF Finding and Rationale Statement.

• CDSS led to modest improvements for three CVD-related quality-of-care outcomes associated with provider practices. When compared with usual care
  • Screening and preventive care services completed or ordered increased by a median of 3.8 percentage points (17 studies)
  • Clinical tests completed or ordered increased by a median of 4.0 percentage points (7 studies)
  • Treatments prescribed increased by a median of 2.0 percentage points (11 studies)
• Eight studies implemented CDSS in combination with other approaches such as team-based care and patient-reminders. When compared with usual care, large improvements were reported for the following quality-of-care outcomes:
  • CDSS-prompted screening and preventive care services ordered
  • CDSS-prompted clinical tests completed or ordered by providers
• Results from the broad systematic review, which examined the effectiveness of CDSS across a variety of conditions and related risk factors, found improvements for all three quality-of-care outcomes (e.g., cardiovascular disease prevention, cancer screening, immunization).

More details about study results are available in the CPSTF Finding and Rationale Statement.

An overall conclusion about the economic effectiveness of CDSS cannot be reached due to limited evidence on cost and economic benefit.

Based on the settings and populations from included studies, the CPSTF finding should be applicable to the following:

• U.S. healthcare system
• Outpatient, primary care settings
• Patients with multiple CVD risk factors

The CPSTF identified several areas that have limited information. Additional research and evaluation could help answer the following questions and fill remaining gaps in the evidence base. (What are evidence gaps?)

• How effective are longer-term programs that account for issues associated with initial integration of CDSS with clinical workflow?
• How effective are CDSS in real-world settings?
• What is the impact of CDSS on cardiovascular disease risk factor outcomes (e.g., blood pressure, cholesterol, and diabetes outcomes) and morbidity and mortality?
• Are CDSS effective with different healthcare providers (i.e., other than physicians), including nurses and pharmacists?
• How do CDSS effect patient-centered outcomes and patient involvement in decision-making?
• Do CDSS reduce health disparities and improve patient satisfaction with care?
• How well do CDSS, used in combination with other interventions, overcome barriers at the patient, provider, organizational, and community levels?
• What is the impact of CDSS when used within a multicomponent approach to improve the efficiency of healthcare delivery?
• How effective are CDSS that include public health recommendations?

• CDSS were added to pre-existing EHRs in about one-third of included studies.
• In most studies, CDSS were designed to do the following:
  • Prompt providers without user requests for information, meaning the prompts were ‘system-initiated’ (82% of included studies)
  • Deliver decision support during patient visits ‘synchronously,’ as part of the clinical workflow (84% of included studies)
• Most studies (95%) evaluated CDSS in outpatient, primary care settings, many of which were run by group practices that had multiple primary care centers.
• Many studies had large patient populations (median: 1,189).
• Studies evaluated CDSS that were targeted at a variety of CVD risk factors such as high blood pressure, diabetes, and high cholesterol.

Njie GJ, Proia KK, Thota AB, et al. Clinical decision support systems and prevention: a Community Guide cardiovascular disease systematic review. American Journal of Preventive Medicine. 2015;49(5):784-95.

Jacob V, Thota AB, Chattopadhyay SK, et al. Cost and economic benefit of clinical decision support systems for cardiovascular disease prevention: a Community Guide systematic review. Journal of the American Medical Informatics Association. 2017;Jan(3):1-9. Available at: https://academic.oup.com/jamia/article/24/3/669/2797755/Cost-and-economic-benefit-of-clinical-decision.

Community Preventive Services Task Force. Clinical decision support systems recommended to prevent cardiovascular disease. American Journal of Preventive Medicine . 2015;49(5):796-9.

Chattopadhyay SK, Jacob V, Mercer SL, Hopkins DP, Elder RW, Jones CD, Community Preventive Services Task Force. Community Guide Cardiovascular Disease Economic Reviews: Tailoring Methods to Ensure Utility of Findings. American Journal of Preventive Medicine. 2017;53(6S2):S155–63. Available at: http://www.sciencedirect.com/science/article/pii/S0749379717303227?via%3Dihub.

Wall HK, Wright JS. The role of clinical decision support systems in preventing cardiovascular disease: A commentary. American Journal of Preventive Medicine. 2015;49(5):e83-4.

Effectiveness Review

Analytic Framework

When starting an effectiveness review, the systematic review team develops an analytic framework. The analytic framework illustrates how the intervention approach is thought to affect public health. It guides the search for evidence and may be used to summarize the evidence collected. The analytic framework often includes intermediate outcomes, potential effect modifiers, potential harms, and potential additional benefits.

Economic Review

No content is available for this section.

Effectiveness Review

Summary Evidence Table – Effectiveness Review

Economic Review

Summary Evidence Table – Economic Review

The Community Preventive Services Task Force recommendation on clinical decision-support systems (CDSS) for cardiovascular disease (CVD) prevention is based on evidence from a broad systematic review and an updated search for newer CVD studies.

• 39 studies focused on CDSS for CVD prevention published between January 1976 -January 2011 (Identified from: Bright TJ, Wong A, Dhurjati R, et al. Effect of Clinical Decision-Support Systems: A Systematic Review. Ann Intern Med 2012; 157(1): 187-94.)
• 6 studies focused on CDSS for CVD prevention published between January 2011-October 2012 (update search)

The number of studies and publications do not always correspond (e.g., a publication may include several studies or one study may be explained in several publications).

Effectiveness Review

CDSS Studies Focused on CVD Prevention from Bright et al. Review

(39 studies, search period January 1976-January 2011)

Apkon M, Mattera JA, Lin Z, et al. A randomized outpatient trial of a decision-support information technology tool. Arch of Intern Med 2005;165(20):2388-94.

Bertoni AG, Bonds DE, Chen H, et al. Impact of a multifaceted intervention on cholesterol management in primary care practices: guideline adherence for heart health randomized trial. Arch Intern Med 2009;169(7):678-86.

Bosworth HB, Olsen MK, Dudley T, et al. Patient education and provider decision support to control blood pressure in primary care: a cluster randomized trial. Am Heart J 2009;157(3):450-6.

Cleveringa FG, Gorter KJ, van den Donk M, et al. Combined task delegation, computerized decision support, and feedback improve cardiovascular risk for type 2 diabetic patients: a cluster randomized trial in primary care. Diabetes Care 2008;31(12):2273-5.

Cobos A, Vilaseca J, Asenjo C. Cost effectiveness of a clinical decision support system based on the recommendations of the European Society of Cardiology and other societies for the management of hypercholesterolemia: Report of a cluster-randomized trial. Dis Manag Health Out 2005;13(6):421.

Demakis JG, Beauchamp C, Cull WL, et al. Improving residents’ compliance with standards of ambulatory care: results from the VA Cooperative Study on Computerized Reminders. JAMA 2000;284(11):1411-6.

Dorr DA, Wilcox A, Donnelly SM, et al. Impact of generalist care managers on patients with diabetes. Health Serv Res 2005;40(5 Pt 1):1400-21.

Filippi A, Sabatini A, Badioli L, et al. Effects of an automated electronic reminder in changing the antiplatelet drug-prescribing behavior among Italian general practitioners in diabetic patients: an intervention trial. Diabetes Care 2003;26(5):1497-500.

Frame PS, Zimmer JG, Werth PL, et al. Computer-based vs manual health maintenance tracking. A controlled trial. Arch Fam Med 1994;3(7):581-8.

Frank O, Litt J, Beilby J. Opportunistic electronic reminders. Improving performance of preventive care in general practice. Aust Fam Physician 2004;33(1-2):87-90.

Fretheim A, Oxman AD, Havelsrud K, et al. Rational prescribing in primary care (RaPP): a cluster randomized trial of a tailored intervention. PLoS Med 2006;3(6):e134.

Goldberg HI, Neighbor WE, Cheadle AD, et al. A controlled time-series trial of clinical reminders: using computerized firm systems to make quality improvement research a routine part of mainstream practice. Health Serv Res 2000;34(7):1519-34.

Gill JM, Chen YX, Glutting JJ, Diamond JJ, Lieberman MI. Impact of decision support in electronic medical records on lipid management in primary care. Popul Health Manag 2009;12(5):221-6.

Hetlevik I, Holmen J, Kruger O. Implementing clinical guidelines in the treatment of hypertension in general practice. Evaluation of patient outcome related to implementation of a computer-based clinical decision support system. Scand J Prim Health Care 1999;17(1):35-40.

Hetlevik I, Holmen J, Kruger O, et al. Implementing clinical guidelines in the treatment of diabetes mellitus in general practice. Evaluation of effort, process, and patient outcome related to implementation of a computer-based decision support system. Int J Technol Assess Health Care 2000;16(1):210-27.

Hicks LS, Sequist TD, Ayanian JZ, et al. Impact of computerized decision support on blood pressure management and control: a randomized controlled trial. J Gen Intern Med 2008;23(4):429-41.

Holbrook A, Thabane L, Keshavjee K, et al. Individualized electronic decision support and reminders to improve diabetes care in the community: COMPETE II randomized trial. CMAJ 2009;181(1-2):37-44.

Holt TA, Thorogood M, Griffiths F, et al. Automated electronic reminders to facilitate primary cardiovascular disease prevention: randomised controlled trial. Br J Gen Pract 2010;60(573):e137-43.

Kenealy T, Arroll B, Petrie KJ. Patients and computers as reminders to screen for diabetes in family practice. Randomized-controlled trial. J Gen Intern Med 2005;20(10):916-21.

Lobach DF, Hammond WE. Development and evaluation of a Computer-Assisted Management Protocol (CAMP): improved compliance with care guidelines for diabetes mellitus. Proc Annu Symp Comput Appl Med Care 1994:787-91.

Maclean CD, Gagnon M, Callas P, Littenberg B. The Vermont diabetes information system: a cluster randomized trial of a population based decision support system. J Gen Intern Med 2009;24(12):1303-10.

Martens JD, van der Weijden T, Severens JL, et al. The effect of computer reminders on GPs’ prescribing behaviour: a cluster-randomised trial. Int J Med Inform 2007;76 Suppl 3:S403-16.

Mc Donald CJ. Use of a computer to detect and respond to clinical events: its effect on clinician behavior. Ann Intern Med 1976;84(2):162-7.

McDowell I, Newell C, Rosser W. A randomized trial of computerized reminders for blood pressure screening in primary care. Med Care 1989;27(3):297-305.

Montgomery AA, Fahey T, Peters TJ, et al. Evaluation of computer based clinical decision support system and risk chart for management of hypertension in primary care: randomised controlled trial. BMJ 2000;320(7236):686-90.

Murray MD, Harris LE, Overhage JM, et al. Failure of computerized treatment suggestions to improve health outcomes of outpatients with uncomplicated hypertension: results of a randomized controlled trial. Pharmacotherapy 2004;24(3):324-37.

O’Connor PJ, Crain AL, Rush WA, et al. Impact of an electronic medical record on diabetes quality of care. Ann Fam Med 2005;3(4):300-6.

Ornstein SM, Garr DR, Jenkins RG, et al. Computer-generated physician and patient reminders. Tools to improve population adherence to selected preventive services. J Fam Pract 1991;32(1):82-90.

Overhage JM, Tierney WM, McDonald CJ. Computer reminders to implement preventive care guidelines for hospitalized patients. Arch Intern Med 1996;156(14):1551-6.

Overhage JM, Tierney WM, Zhou XH, et al. A randomized trial of “corollary orders” to prevent errors of omission. J Am Med Inform Assoc 1997;4(5):364-75.

Palen TE, Raebel M, Lyons E, et al. Evaluation of laboratory monitoring alerts within a computerized physician order entry system for medication orders. Am J Manag Care 2006;12(7):389-95.

Phillips LS, Ziemer DC, Doyle JP, et al. An endocrinologist-supported intervention aimed at providers improves diabetes management in a primary care site: improving primary care of African Americans with diabetes (IPCAAD) 7. Diabetes Care 2005;28(10):2352-60.

Reeve JF, Tenni PC, Peterson GM. An electronic prompt in dispensing software to promote clinical interventions by community pharmacists: a randomized controlled trial. Br J Clin Pharmacol 2008;65(3):377-85.

Rosser WW, McDowell I, Newell C. Use of reminders for preventive procedures in family medicine. CMAJ 1991;145(7):807-14.

Roumie CL, Elasy TA, Greevy R, et al. Improving blood pressure control through provider education, provider alerts, and patient education: a cluster randomized trial. Ann Intern Med 2006;145(3):165-75.

Smith SA, Shah ND, Bryant SC, et al. Chronic care model and shared care in diabetes: randomized trial of an electronic decision support system. Mayo Clin Proc 2008;83(7):747-57.

Tamblyn R, Reidel K, Huang A, et al. Increasing the detection and response to adherence problems with cardiovascular medication in primary care through computerized drug management systems: a randomized controlled trial. Med Decis Making 2010;30(2):176-88.

Toth-Pal E, Nilsson GH, Furhoff AK. Clinical effect of computer generated physician reminders in health screening in primary health care–a controlled clinical trial of preventive services among the elderly. Int J Med Inform 2004;73(9-10):695-703.

van Wyk JT, van Wijk MA, Sturkenboom MC, et al. Electronic alerts versus on-demand decision support to improve dyslipidemia treatment: a cluster randomized controlled trial. Circulation 2008;117(3):371-8.

CDSS Studies Focused on CVD Prevention from Update Search

(6 studies, search period January 2011-October 2012)

Eaton CB, Parker DR, Borkan J, et al. Translating cholesterol guidelines into primary care practice: a multimodal cluster randomized trial. Ann Fam Med 2011;9(6):528-37.

Herrin J, da Graca B, Nicewander D, et al. The effectiveness of implementing an electronic health record on diabetes care and outcomes. Health Serv Res 2012;47(4):1522-40.

Holbrook A, Pullenayegum E, Thabane L, et al. Shared electronic vascular risk decision support in primary care: Computerization of Medical Practices for the Enhancement of Therapeutic Effectiveness (COMPETE III) randomized trial. Arch Intern Med 2011;171(19):1736-44.

Kelly E, Wasser T, Fraga JD, et al. Impact of an EMR clinical decision support tool on lipid management. J Clin Outcomes Manag 2011;18(12):551

O’Connor PJ, Sperl-Hillen JAM, Rush WA, et al. Impact of electronic health record clinical decision support on diabetes care: a randomized trial. Ann Fam Med 2011;9(1):12-21.

Schnipper JL, Linder JA, Palchuk MB, et al. Effects of documentation-based decision support on chronic disease management. Am J Manag Care 2010;16(12 Suppl HIT):SP72-81.

Additional References Linked to Included Studies

(search period 1976 2012)

These additional references provide important supporting information to supplement the content available from the included studies listed above.

Bosworth HB, Olsen MK, Goldstein MK, et al. The veterans’ study to improve the control of hypertension (V-STITCH): design and methodology. Contemp Clin Trials 2005;26(2):155-68.

Fretheim A, Aaserud M, Oxman AD. Rational prescribing in primary care (RaPP): economic evaluation of an intervention to improve professional practice. PLoS Med 2006;3(6):e216.

Hetlevik I, Holmen J, Kruger O, et al. Implementing clinical guidelines in the treatment of hypertension in general practice. Blood Press 1998;7(5-6):270-6.

Holt TA, Thorogood M, Griffiths F, et al. Protocol for the ‘e-Nudge trial’: a randomised controlled trial of electronic feedback to reduce the cardiovascular risk of individuals in general practice [ISRCTN64828380]. Trials 2006;7:11.

Jean-Jacques M, Persell SD, Thompson JA, et al. Changes in disparities following the implementation of a health information technology-supported quality improvement initiative. J Gen Intern Med 2012;27(1):71-7.

Khan S, Maclean CD, Littenberg B. The effect of the Vermont Diabetes Information System on inpatient and emergency room use: results from a randomized trial. Health Outcomes Res Med 2010;1(1):e61-e6.

Martens JD, van der Aa A, Panis B, et al. Design and evaluation of a computer reminder system to improve prescribing behaviour of GPs. Stud Health Technol Inform 2006;124:617-23.

Ziemer DC, Doyle JP, Barnes CS, et al. An intervention to overcome clinical inertia and improve diabetes mellitus control in a primary care setting: Improving Primary Care of African Americans with Diabetes (IPCAAD) 8. Arch Intern Med 2006;166(5):507-13.

Economic Review

Adler-Milstein J, Bu D, Pan E, et al. The cost of information technology-enabled diabetes management. Disease Management 2007;10(3):115-28.

Apkon M, Mattera JA, Lin Z, et al. A randomized outpatient trial of a decision-support information technology tool. Archives of Internal Medicine 2005;165(20):2388-94.

Bassa A, Del Val M, Cobos A, et al. Impact of a clinical decision support system on the management of patients with hypercholesterolemia in the primary healthcare setting. Disease Management & Health Outcomes 2005;13(1):65-72.

Blanchfield BB, Grant RW, Estey GA, Chueh HC, Gazelle GS, Meigs JB. Cost of an informatics-based diabetes management program. International Journal of Technology Assessment in Health Care 2006;22(02):249-54.

Bu D, Pan E, Walker J, et al. Benefits of information technology-enabled diabetes management. Diabetes Care 2007;30(5):1137-42.

Cleveringa FG, Welsing PM, van den Donk M, et al. Cost-effectiveness of the diabetes care protocol, a multifaceted computerized decision support diabetes management intervention that reduces cardiovascular risk. Diabetes Care 2010;33(2):258-63.

Cobos A, Vilaseca J, Asenjo C, et al. Cost effectiveness of a clinical decision support system based on the recommendations of the European Society of Cardiology and other societies for the management of hypercholesterolemia: Report of a cluster-randomized trial. Disease Management & Health Outcomes 2005;13(6):421-32.

Frame PS, Zimmer JG, Werth PL, Hall WJ, Eberly SW. Computer-based vs manual health maintenance tracking. A controlled trial. Archives of Family Medicine 1994;3(7):581-8.

Fretheim A, Aaserud M, Oxman AD. Rational prescribing in primary care (RaPP): economic evaluation of an intervention to improve professional practice. PLoS Medicine 2006;3(6):e216.

Gilmer TP, O’Connor PJ, Sperl-Hillen JM, et al. Cost-effectiveness of an electronic medical record based clinical decision support system. Health Services Research 2012;47(6):2137-58.

Javitt JC, Steinberg G, Locke T, et al. Using a claims data-based sentinel system to improve compliance with clinical guidelines: results of a randomized prospective study. American Journal of Managed Care 2005;11(2):93-102.

Khan S, Maclean CD, Littenberg B. The effect of the Vermont Diabetes Information System on inpatient and emergency room use: results from a randomized trial. Health Outcomes Research in Medicine 2010;1(1):e61-e6.

Murray MD, Harris LE, Overhage JM, et al. Failure of computerized treatment suggestions to improve health outcomes of outpatients with uncomplicated hypertension: results of a randomized controlled trial. Pharmacotherapy 2004;24(3):324-37.

O’Reilly D, Holbrook A, Blackhouse G, Troyan S, Goeree R. Cost-effectiveness of a shared computerized decision support system for diabetes linked to electronic medical records. Journal of the American Medical Informatics Association 2012;19(3):341-5.

Overhage JM, Tierney WM, Zhou XH, McDonald CJ. A randomized trial of “corollary orders” to prevent errors of omission. Journal of the American Medical Informatics Association 1997;4(5): 364-75.

Shih SC, McCullough CM, Wang JJ, Singer J, Parsons AS. Health information systems in small practices. Improving the delivery of clinical preventive services. American Journal of Preventive Medicine 2011;41(6):603-9.

Smith SA, Shah ND, Bryant SC, et al. Chronic care model and shared care in diabetes: randomized trial of an electronic decision support system. Mayo Clinic Proceedings 2008;83(7):747-57.

Additional References Linked to Studies Included in the Economic Review

Cleveringa FG, Gorter KJ, Van Den Donk M, Rutten GE. Combined Task Delegation, Computerized Decision Support, and Feedback Improve Cardiovascular Risk for Type 2 Diabetic Patients A cluster randomized trial in primary care. Diabetes Care 2008;31(12):2273-5.

Fretheim A, Oxman AD, H velsrud K, Treweek S, Kristoffersen DT, Bj rndal A. Rational prescribing in primary care (RaPP): a cluster randomized trial of a tailored intervention. PLoS Medicine 2006;3(6):e134.

Grant RW, Cagliero E, Sullivan CM, et al. A controlled trial of population management diabetes mellitus: putting evidence into practice (DM-PEP). Diabetes Care 2004;27(10):2299-305.

Grant RW, Hamrick HE, Sullivan CM, et al. Impact of population management with direct physician feedback on care of patients with type 2 diabetes. Diabetes Care 2003;26(8):2275-80.

Holbrook A, Thabane L, Keshavjee K, et al. Individualized electronic decision support and reminders to improve diabetes care in the community: COMPETE II randomized trial. Canadian Medical Association Journal 2009;181(1-2):37-44.

Littenberg B, MacLean CD, Zygarowski K, Drapola BH, Duncan JA, Frank CR. The Vermedx Diabetes Information System reduces healthcare utilization. American Journal of Managed Care 2009;15(3):166-70.

MacLean CD, Gagnon M, Callas P, Littenberg B. The Vermont diabetes information system: a cluster randomized trial of a population based decision support system. Journal of General Internal Medicine 2009;24(12):1303-10.

MacLean CD, Littenberg B, Gagnon M. Diabetes decision support: initial experience with the Vermont diabetes information system. American Journal of Public Health 2006;96(4):593.

MacLean CD, Littenberg B, Gagnon M, Reardon M, Turner PD, Jordan C. The Vermont Diabetes Information System (VDIS): study design and subject recruitment for a cluster randomized trial of a decision support system in a regional sample of primary care practices. Clinical Trials 2004;1(6):532-44.

O’Connor PJ, Sperl-Hillen JM, Rush WA, et al. Impact of electronic health record clinical decision support on diabetes care: a randomized trial. Annals of Family Medicine 2011;9(1):12-21.

Implementation Product

• Best Practices for Cardiovascular Disease Prevention Programs: A Guide to Effective Health Care System Interventions and Community-Clinical Links
  Developed by CDC’s Division for Heart Disease and Stroke Prevention

The Community Preventive Services Task Force finding is based on evidence from a broad systematic review published in 2012 (Bright et al., search period January 1976-January 2011) and an updated search for newer CVD studies (search period January 2011-October 2012). The following databases were searched: CINAHL, PsycINFO, PubMed NLM, and Web of Science. The full search strategy from the Bright 2012 review is available online: http://www.ncbi.nlm.nih.gov/books/NBK97318/pdf/TOC.pdf . In updating the evidence, the same search strategy was used as in the Bright review but specific to cardiovascular disease prevention.

Effectiveness Review

Search Terms

1) Keywords for intervention of interest: Clinical Decision-Support Systems

1. 5-minute clinical consult
2. alert
3. automated information storage/retrieval
4. bedside/decision*/point-of-care
5. Clineguide
6. clinical decision support system*
7. clinical practice
8. clinical resource*
9. computer assisted decision making
10. computer assisted drug therapy
11. computer*
12. computerized medical record system*
13. computerized patient record*
14. consultation*
15. CPOE
16. dashboard
17. databases
18. decision making
19. decision support
20. decision support systems
21. digital
22. Diseasedex
23. Dynamed
24. electronic
25. email
26. Emedicine
27. epocrates
28. Essential Evidence
29. Evidence Matters
30. Firstconsult
31. guideline*
32. handheld computer
33. health resource*
34. infobutton*
35. Infopoems
36. Inforetriever
37. information dissemination
38. information resource*
39. information retrieval tool*/services/dissemination
40. Information services
41. internet
42. Isabel + diagnosis
43. just-in-time
44. knowledge base
45. knowledge resource*
46. MdConsult
47. medical order entry systems
48. Medlars
49. microcomputer*
50. Micromedex
51. National guideline clearinghouse
52. online
53. order set
54. patient practice
55. patient*
56. patient-related question*
57. personal digital assistant
58. physician/provider order entry
59. Pier
60. practice pattern*
61. PubMed
62. randomized reminder*
63. real time
64. recommendation*
65. reference book*
66. reminder*
67. Stat!Ref
68. Textbook*
69. UpToDate
70. Wireless
71. Zynx

2) Cardiovascular Disease (CVD) Keywords (used in update search):

1. antihypertensive*
2. blood pressure
3. cholesterol
4. diabetes mellitus
5. glucose intolerance
6. high blood pressure
7. high cholesterol
8. hypercholesterol*
9. hypercholesterolemia
10. hyperlipid*
11. hyperlipidemia
12. hypertension
13. impaired glucose
14. tolerance
15. insulin resistant*
16. lipids
17. metabolic syndrome
18. non insulin dependent
19. prediabetes
20. prediabetic
21. statins
22. type ii diabetes

3) Evaluation Keywords

1. case control studies
2. clinical trial
3. cohort studies
4. comparative studies
5. evaluation studies
6. experimental design*
7. follow up studies
8. intervention studies
9. longitudinal studies
10. meta-analysis
11. practice guideline
12. prospective studies
13. qualitative research
14. quantitative methods
15. quasi experimental
16. methods
17. randomized
18. retrospective studies
19. systematic review
20. treatment guidelines
21. validation studies

*=truncation symbol [Plurals and British spelling variations searched also.]

PubMed NLM

Filters: Humans; English

#1 “case-control studies”[MeSH Terms] OR “cohort studies”[MeSH Terms] OR Clinical Trial[PT] OR randomized[tiab] OR randomised[tiab] OR Multicenter Study[PT] OR Evaluation Studies[PT] OR Comparative Study[PT] OR practice guideline[PT] OR “intervention studies”[MeSH Terms] OR validation studies[PT] OR meta-analysis[PT] OR systematic[sb] OR “systematic review”[tiab]

#2 “decision support” [tiab] OR “decision support systems, clinical”[MeSH Terms] OR “therapy, computer-assisted”[Mesh:noexp] OR “reminder systems”[MeSH Terms] OR “drug therapy, computer-assisted”[MeSH Terms] OR “medical order entry systems”[MeSH Terms] OR “Decision Making, Computer Assisted”[Mesh:noexp]

#3 ((computer*[tiab] OR electronic[tiab]) AND (alert*[tiab] OR reminder*[tiab] OR recommendation*[tiab] OR dashboard[tiab] OR “order set” OR “order sets” OR guideline*))

#4 (randomized[tiab] AND reminder*[tiab]) OR (randomised [tiab] AND reminder* [tiab])

#5 (cpoe[tiab] OR “physician order entry”[tiab] OR “provider order entry”[tiab] OR “clinical decision support system”[tiab] OR “clinical decision support systems”[tiab])

#6 bedside[tiab] OR decision[tiab] OR decisions[tiab] OR “point-of-care”[tiab] OR “Decision Making”[Mesh] OR real-time OR just-in-time OR “Physician’s Practice Patterns”[Mesh] OR “Nurse’s Practice Patterns”[Mesh] OR “practice patterns”[tiab] OR “practice pattern”[tiab] OR “Point-of-Care Systems”[Mesh] OR “patient-related question” OR “patient-related questions” OR consultation [tiab] OR consultations[tiab]

#7 patient[tiab] OR patients [tiab] OR “clinical practice”[tiab] OR “point of clinical opportunity” OR “point of visit” OR “point of patient encounter”

#8 #6 AND #7

#9 infobutton OR infobuttons OR “Information Storage and Retrieval”[Mesh:noexp] OR MEDLARS [Mesh]

#10 MEDLARS [tiab] OR (PubMed [Mesh] AND PubMed [tiab]) OR “Information Services”[Mesh:noexp] OR “Information Dissemination”[Mesh] OR “Drug Information Services”[Mesh] OR “Knowledge Bases”[Mesh] OR “Computers, Handheld”[Mesh] OR “Databases as Topic”[Mesh:noexp] OR “Databases, Bibliographic”[Mesh] OR “Databases, Factual”[Mesh:noexp]

#11 Medical records systems, computerized [Mesh] OR diseasedex[tiab] OR firstconsult[tiab] OR clineguide[tiab] OR inforetriever[tiab] OR “essential evidence”[tiab] OR emedicine[tiab] OR “evidence matters”[tiab] OR UpToDate[tiab] OR dynamed[tiab] OR epocrates[tiab] OR zynx[tiab] OR micromedex[tiab] OR mdconsult[tiab] OR md-consult[tiab] OR infopoems[tiab] OR pier[tiab] OR “5-minute clinical consult”[tiab] OR MEDLARS[Mesh] OR( Isabel[tiab] AND diagnosis)

#12 MEDLARS[tiab] OR (PubMed[Mesh] AND PubMed[tiab]) OR “national guideline clearinghouse”[tiab] OR Stat!Ref [tiab] OR “Online systems”[Mesh] OR “Information Storage and Retrieval”[Mesh:noexp] OR (MEDLARS[Mesh] AND MEDLARS[tiab]) OR PubMed[Mesh]

#13 (PubMed[tiab]) OR “Information Services”[Mesh:noexp] OR “Information Dissemination”[Mesh] OR “Drug Information Services”[Mesh] OR “Knowledge Bases”[Mesh] OR “Computers, Handheld”[Mesh] OR “Databases as Topic”[Mesh:noexp] OR “Databases, Bibliographic”[Mesh] OR “Databases, Factual”[Mesh:noexp] OR “Point-of-Care Systems”[Mesh] OR Internet[Mesh:noexp]) OR ((“reference books”[Mesh] OR “Manuals as Topic”[Mesh] OR “Textbooks as Topic”[Mesh] OR textbook*[tiab])

#14 (computer* OR electronic OR online OR on-line OR wireless OR internet OR digital OR microcomputer*) AND ((“knowledge resources” OR “information resources” OR “health resources” OR clinical resources OR knowledge resource OR information resource* OR health resource OR clinical resource)

#15 hypercholesterol*[Title/Abstract] OR hyperlipid*[Title/Abstract] OR “high cholesterol”[Title/Abstract] OR “insulin resistance”[Title/Abstract] OR “diabetes mellitus”[MeSH Terms] OR “diabetes complications”[MeSH Terms] OR “metabolic syndrome x”[MeSH Terms] OR “insulin resistance”[MeSH Terms] OR “glucose intolerance”[MeSH Terms] OR “antihypertensive agents”[MeSH Terms] OR “hmg coa statins”[MeSH Terms] OR hyperlipidemia[MeSH Terms] OR hyperlipidemia OR hypertension[MeSH Terms]

#16 “insulin resistance” OR “insulin resistant” OR “type ii diabetes” OR “non insulin dependent” OR lipids OR cholesterol OR hypercholesterol* OR hyperlipid* OR “high blood pressure” OR “blood pressure” OR hypertension[Title/Abstract] OR “diabetes mellitus”[Title/Abstract] OR “sugar diabetes”[Title/Abstract] OR “diabetes complications”[Title/Abstract] OR “type 2 diabetes”[Title/Abstract] OR “blood pressure”[Title/Abstract] OR “statins”[Title/Abstract] OR “statin”[Title/Abstract]

#17 “impaired glucose tolerance”[Title/Abstract] OR “hyperglycemia”[Title/Abstract] OR “high blood sugar”[Title/Abstract] OR “glucose intolerance”[Title/Abstract] OR “glucose intolerant”[Title/Abstract] OR “pre-diabetic”[Title/Abstract] OR prediabetes OR prediabetic OR “pre-diabetes” OR “pre-diabetic” OR prediabetics OR “pre-diabetics” OR prediabetic state[MeSH Terms] OR diabetes mellitus[MeSH Terms] OR diabetes complications[MeSH Terms] OR metabolic syndrome x[MeSH Terms] OR insulin resistance[MeSH Terms] OR glucose intolerance[MeSH Terms] OR antihypertensive agents[MeSH Terms] OR hmg coa statins[MeSH Terms] OR hyperlipidemia[MeSH Terms] OR hyperlipidemia OR hypertension[MeSH Terms]

#18 #15 OR #16 OR #17

#19 #1 AND (#2 OR #3 OR #4 OR #5) AND #18

#20 #8 OR #9 OR #10 OR #11 OR #12 OR #13 OR #14

#21 #1 AND #18 AND #20

#22 #19 OR #21

[ALTERNATE STRATEGY LEAVING OUT EVALUATION COMPONENT]

#23 (#2 OR #3 OR #4 OR #5) AND #18

#24 #18 AND #20

#25 #23 OR #24

CINAHL (EBSCO)

Search modes – Boolean/Phrase

Limiters – Published Date from: 20110101-20121231 OR (EM 2011* OR EM 2012*); English Language; Exclude MEDLINE records

S1 (TI (“randomized”)) OR (AB (“randomized”)) OR (TI (“randomised”)) OR (AB (“randomised”)) OR (MH “Study Design+”) OR (MH “Multi center Studies”) OR (MH “Evaluation Research+”) OR (MH “Comparative Studies”) OR (MH “Practice Guidelines”) OR (MH “Validation Studies”) OR (MH “Meta Analysis”) OR (MH “Systematic Review”)

S2 (TI(“decision support”)) OR (AB (“decision support”)) OR (MH “Decision Support Systems, Clinical”) OR (MH “Therapy, Computer Assisted”) OR (MH “Reminder Systems”) OR (MH “Drug Therapy, Computer Assisted”) OR (MH “Electronic Order Entry”) OR (MH “Decision Making, Computer Assisted”) OR (MH “Expert Systems”)

S3 ((TI(computer*)) OR (AB (computer*)) OR (TI(electronic)) OR (AB (electronic))) AND ((TI(alert*)) OR (AB (alert*)) OR (TI(reminder*)) OR (AB (reminder*)) OR (TI(recommendation*)) OR (AB (recommendation*)) OR (TI(dashboard)) OR (AB (dashboard)) OR ( order set) OR order sets) OR (guideline))

S4 (((TI (“randomized”)) OR (AB (“randomized”))) AND ((TI (reminder*)) OR (AB (reminder*)))) OR (((TI (“randomised”)) OR (AB (“randomised”))) AND ((TI (reminder*)) OR (AB (reminder*))))

S5 (TI(cpoe)) OR (AB (cpoe)) OR (TI( physician order entry )) OR (AB ( physician order entry )) OR (TI( provider order entry )) OR (AB ( provider order entry )) OR (TI( clinical decision support system )) OR (AB ( clinical decision support system )) OR (TI( clinical decision support systems )) OR (AB ( clinical decision support systems ))

S6 S1 AND (S2 OR S3 OR S4 OR S5)

S7 “diabetes mellitus” or “type 2 diabetes” or “metabolic syndrome” or “glucose intolerance” or “impaired glucose tolerance” or hyperlipid* or antihypertensive* or statin or statins or “blood pressure” or cholesterol or hypercholesterol* or hypertension OR (MH “Diabetes Mellitus+”) OR (MH “Diabetic Angiopathies+”) OR (MH “Diabetic Coma+”) OR (MH “Diabetic Ketoacidosis”) OR (MH “Diabetic Nephropathies”) OR (MH “Diabetic Neuropathies+”) OR (MH “Pregnancy in Diabetes”) OR (MH “Glucose Intolerance”) OR (MH “Hyperglycemia+”) OR (MH “Insulin Resistance+”) OR (MH “Metabolic Syndrome X+”) OR (MH “Hyperlipidemia+”) OR (MH “Statins+”) OR statins OR (MH Hypercholesterolemia+”) OR (MH “Cholesterol”) OR (MH “Lipoproteins, HDL Cholesterol”) OR (MH “Lipoproteins, LDL Cholesterol”) OR (MH “Cholesterol, Dietary”) OR (MH “Antihypertensive Agents+”) OR (MH “Adrenergic Beta-Antagonists+”) OR (MH “Blood Pressure+”) OR (MH “Hypertension, White Coat”) OR (MH “Hypertension, Isolated Systolic”) OR (MH “Hypertension”)

S8 S6 AND S7

S9 (TI(“bedside”)) OR (AB (“bedside”)) OR (TI(“decision”)) OR (AB (“decision”)) OR (TI(“decisions”)) OR (AB (“decisions”)) OR (TI(“point-of-care”)) OR (AB (“point-of-care”)) OR (“real-time”) OR (“just-in-time”) OR (TI(“practice pattern”)) OR (AB (“practice pattern”)) OR (TI(“practice patterns”)) OR (AB (“practice patterns”)) OR (“patient-related question “) OR (“patient-related questions”) OR (((TI(“consultation “)) OR (AB (“consultations “))) AND ((TI(“patient”)) OR (AB (“patients”)))) OR (TI(“clinical practice”)) OR (AB (“clinical practice”)) OR (MH “Decision Making”) OR (MH “Practice Patterns”) OR (MH “Clinical Information Systems”)

S10 (“info button”) OR (“info buttons”) OR (“infobutton”) OR (“infobuttons”)

S11 ((MH “Information Retrieval”) OR (MH “Information Storage”) OR ((MH “Medlars”) AND ((TI(“Medlars”)) OR (AB (“Medlars “)))) OR ((MH “PubMed”) AND ((TI(“PubMed “)) OR (AB (“PubMed “)))) OR (MH “Information Services”) OR (MH “Information Management”) OR (MH “Drug Information Services”) OR (MH “Knowledge Bases”) OR (MH “Computers, Portable+”) OR (MH “Databases+”)) AND (MH “Computerized Patient Record”)

S12 (TI(“diseasedex”)) OR (AB (“diseasedex”)) OR (TI(“firstconsult”)) OR (AB (“firstconsult”)) OR (TI(“clineguide”)) OR (AB (“clineguide”)) OR (TI(“inforetriever”)) OR (AB (“inforetriever”)) OR (TI(“essential evidence”)) OR (AB (“essential evidence”)) OR (TI(“emedicine”)) OR (AB (“emedicine”)) OR (TI(“evidence matters”)) OR (AB (“evidence matters”)) OR (TI(“UpToDate”)) OR (AB (“UpToDate”)) OR (TI(“dynamed”)) OR (AB (“dynamed”)) OR (TI(“epocrates”)) OR (AB (“epocrates”)) OR (TI(“zynx”)) OR (AB (“zynx”)) OR (TI(“micromedex”)) OR (AB (“micromedex”)) OR (TI(“mdconsult”)) OR (AB (“mdconsult”)) OR (TI(“md-consult”)) OR (AB (“md-consult”)) OR (TI(“infopoems”)) OR (AB (“infopoems”)) OR (TI(“pier”)) OR (AB (“pier”)) OR (TI(“5-minute clinical consult”)) OR (AB (“5-minute clinical consult”)) OR (((TI(“Isabel”)) OR (AB (“Isabel”))) AND (“diagnosis”)) OR ((MH “Medlars”) AND ((TI(“Medlars”)) OR (AB (“Medlars “)))) OR ((MH “PubMed”) AND ((TI(“PubMed “)) OR (AB (“PubMed “)))) OR (TI(“national guideline clearinghouse”)) OR (AB (“national guideline clearinghouse”)) OR (TI(“Stat!Ref”)) OR (AB (“Stat!Ref”))

S13 (MH “Online Systems+”) OR (MH “Information Retrieval”) OR (MH “Information Storage”) OR ((MH “Medlars”) AND ((TI(“Medlars”)) OR (AB (“Medlars “)))) OR ((MH “PubMed”) AND ((TI(“PubMed “)) OR (AB (“PubMed “)))) OR (MH “Information Services”) OR (MH “Information Management”) OR (MH “Drug Information Services”) OR (MH “Knowledge Bases”) OR (MH “Computers, Portable+”) OR (MH “Databases+”) OR (MH “Clinical Information Systems”) OR (MH “Internet”)

S14 ((MH “Reference Books+”) OR (MH “Textbooks”) OR (TI(textbook*)) OR (AB (textbook*))) AND ((computer*) OR ( electronic ) OR ( online ) OR ( on-line ) OR ( wireless ) OR ( internet ) OR ( digital ))

S15 (( knowledge resources ) OR ( information resources ) OR ( health resources ) OR ( clinical resources ) OR ( knowledge resource ) OR ( information resource ) OR ( health resource ) OR ( clinical resource )) AND ((computer*) OR ( electronic ) OR ( online ) OR ( on-line ) OR ( wireless ) OR ( internet ) OR ( digital ) OR ( microcomputer ))

S16 S1 AND S9

S17 S10 OR S11 OR S12 OR S13 OR S14 OR S15

S18 S16 AND S17 AND S7

S19 S18 OR S8

[Alternate Strategy leaving out “evaluation” component]

S20 (S2 OR S3 OR S4 OR S5 OR S6) AND S7

S21 (S9 OR S10 OR S11 OR S12 OR S13 OR S14 OR S15) AND S7

S22 S20 OR S21

PsycINFO (OVID)

1. exp Hypertension/ or exp Essential Hypertension/ or hypertension.mp.
2. exp Diabetes Mellitus/ or exp Diabetes/ or type 2 diabetes.mp.
3. exp Cholesterol/ or high cholesterol.mp. or exp Lipids/
4. statins.mp. or statin.mp.or exp Statins/
5. exp Antihypertensive Drugs/ or antihypertensive*.mp.
6. beta blocker*.mp. or exp Adrenergic Blocking Drugs/
7. exp Lipid Metabolism Disorders/ or hyperlipidemia.mp. or hyperlipidaemia.mp.
8. hypercholesterol*.mp.
9. insulin resistance.mp.
10. glucose intolerance.mp.
11. impaired glucose tolerance.mp.
12. decreased glucose tolerance.mp.
13. or/1-12
14. (“Meta Analysis” or “Experimental Design” or “Clinical Trials” or “Cohort Analysis” or “Followup Studies” or “Qualitative Research” or “Quantitative Methods” or “Longitudinal Studies” or “Prospective Studies” or “Experimental Methods” or “Quasi Experimental Methods” or “Retrospective Studies” or “Treatment Guidelines”).de. or (systematic review* or randomi*ed).ti,ab
15. “Decision Support Systems”.de. and clinical.ti,ab.
16. “Computer Assisted Therapy”.de.
17. (computer* or electronic*).ti,ab. and ((alert* or reminder* or recommendation* or dashboard*).ti,ab. or order set*.mp. or guideline*.mp.)
18. (Randomi*ed and reminder*).ti,ab.
19. (cpoe or physician order entry or provider order entry or clinical decision support system*).ti,ab.
20. or/15-19
21. (“infobutton” or “infobuttons”).mp.
22. Information Retrieval Tool*.mp. or “Automated Information Storage”.de. or “Automated Information Retrieval”.de. or “Information Services”.de. or “Information Dissemination”.de. or “Databases”.de. or “Medlars”.ti,ab. or “PubMed”.ti,ab. or knowledge base*.ti,ab. or handheld computer*.ti,ab. or personal digital assistant*.ti,de.
23. (computerized medical record system* or computerized patient record*).ti,ab.
24. (Knowledge Resource* or diseasedex or firstconsult or clineguide or inforetriever or essential evidence or emedicine or evidence matters or UpToDate or dynamed or epocrates or zynx or micromedex or mdconsult or md-consult or infopoems or pier or 5-minute clinical consult or PubMed or national guideline clearinghouse or Stat!Ref or mdconsult or Medlars).mp.
25. “Isabel”.ti,ab. and “diagnosis”.mp.
26. (pubmed).hw,de.
27. (Online System* or Medlars or PubMed or Knowledge Base or Knowledge Bases or handheld computer or handheld computers or personal digital assistant or person digital assitants).ti,ab.
28. (Automated Information Storage or Automated Information Retrieval or databases or Internet).hw.
29. (“Reference Books” or “Reference Book” or textbook*).ti,ab. or textbooks.hw.
30. (computer* or electronic or online or on-line or wireless or internet or digital).ti,ab.
31. 29 and 30
32. (knowledge resources or information resources or health resources or clinical resources or knowledge resource or information resource or health resource or clinical resource).ti,ab.
33. (computer* or electronic or online or on-line or wireless or digital or microcomputer*).ti,ab.
34. 32 and 33
35. (“bedside” or “decision” or “decisions” or “point-of-care”).ti,ab. or “real-time”.mp. or “just-in-time”.mp. or “practice pattern”.ti,ab. or “practice patterns”.ti,ab. or “patient-related question”.mp. or “patient-related questions”.mp. or “consultation”.ti,ab. or “consultations”.ti,ab.
36. (“patient” or “patients” or “clinical practice”).ti,ab. or Decision Making.de.
37. 35 AND 36
38. OR/20-28
39. 31 OR 34 OR 37 OR 38
40. 13 AND 14 AND 39
41. (“2011” or “2012”).dp. OR (2011* or 2012*).up.
42. 40 AND 41

[Alternate Strategy leaving out “evaluation” component]

1. 13 AND 39 AND 41

Web of Science

References used:

1. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ 2005 Apr 2;330(7494):765.
2. Eccles M, McColl E, Steen N, Rousseau N, Grimshaw J, Parkin D, et al. Effect of computerised evidence based guidelines on management of asthma and angina in adults in primary care: cluster randomised controlled trial. BMJ 2002 Oct 26;325(7370):941.
3. Friedman C, Wyatt J. Evaluation methods in medical informatics. Springer-Verlag, editor 1997.
4. Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005 Mar 9;293(10):1223-38.
5. Grimshaw J, Freemantle N, Wallace S, Russell I, Hurwitz B, Watt I, et al. Developing and implementing clinical practice guidelines. Qual Health Care 1995 Mar;4(1):55-64.
6. Sim I, Gorman P, Greenes RA, Haynes RB, Kaplan B, Lehmann H, et al. Clinical decision support systems for the practice of evidence-based medicine. J Am Med Inform Assoc2001 Nov-Dec;8(6):527-34.
7. Bates DW, Evans RS, Murff H, Stetson PD, Pizziferri L, Hripcsak G. Detecting adverse events using information technology. J Am Med Inform Assoc 2003 Mar-Apr;10(2):115-28.
8. Bates DW, Gawande AA. Improving safety with information technology. N Engl J Med 2003 Jun 19;348(25):2526-34.
9. Ash JS, Anderson NR, Tarczy-Hornoch P. People and organizational issues in research systems implementation. J Am Med Inform Assoc 2008 May-Jun;15(3):283-9.
10. Shekelle PG, Morton SC, Keeler EB. Costs and Benefits of Health Information Technology.Evidence Report/Technology Assessment No. 132. (Prepared by the Southern California Evidence-based Practice Center under Contract No. 290-02-0003.) AHRQ Publication No. 06-E006. Rockville, MD: Agency for Healthcare Research and Quality. April 2006.
11. Gibbons MC, Wilson RF, Samal L, Lehmann CU, Dickersin K, Lehmann HP, Aboumatar H, Finkelstein J, Shelton E, Sharma R, Bass EB. Impact of Consumer Health Informatics Applications. Evidence Report/Technology Assessment No. 188. (Prepared by Johns Hopkins University Evidence-based Practice Center under contract No. HHSA 290-2007-10061-I).AHRQ Publication No. 09(10)-E019. Rockville, MD. Agency for Healthcare Research and Quality. October 2009.
12. Bright TJ, Wong A, Dhurjati R, et al. Effect of Clinical Decision-Support Systems: A Systematic Review. Ann Intern Med 2012; 157(1) : 29-43.
13. Lobach D, Sanders GD, Bright TJ, Wong A, Dhurjati R, Bristow E, Bastian L, Coeytaux R, Samsa G, Hasselblad V, Williams JW, Wing L, Musty M, Kendrick AS. Enabling Health Care Decisionmaking Through Clinical Decision Support and Knowledge Management. Evidence Report No. 203. (Prepared by the Duke Evidence-based Practice Center under Contract No. 290-2007-10066-I.) AHRQ Publication No. 12-E001-EF. Rockville, MD: Agency for Healthcare Research and Quality. April 2012.

NOTE Also searched Google Scholar for cited references from above list.

[Alternate search strategy – keyword search.]

DocType=All document types; Language=All languages; Timespan=2011-01-01 – 2012-10-22

Lemmatization=On

#1 TS=( hypertension OR diabetes OR cholesterol OR lipids OR statins OR antihypertensive* OR “beta blocker” OR “beta blockers” OR “lipid metabolism disorders” or “lipid metabolism disorder” or hyperlipidemia. or hyperlipidaemia OR hypercholesterol* OR “insulin resistance” OR “insulin resistant” OR “glucose intolerance” OR “glucose intolerant” OR “impaired glucose tolerance” OR “decreased glucose tolerance” OR “metabolic syndrome” OR prediabetes or prediabetic or “pre-diabetes” OR “pre-diabetic” OR “high cholesterol”) OR TS=(adrenergic near/1 blocking near/1 drugs)

#2 TS=(“meta analysis” OR “meta analyses” OR “experimental design” OR “experimental designs” or “clinical trials” OR “clinical trial” or “cohort analysis” OR “cohort analyses” or “followup studies” OR “follow-up studies” OR “followup study” OR “follow-up study” or “qualitative research” or “quantitative methods” OR “quantitative method” or “longitudinal studies” OR “longitudinal study” OR “prospective study” or “prospective studies” or “experimental methods” or “experimental method” or “retrospective studies” “retrospective study” or “treatment guidelines” OR “treatment guideline” OR “systematic review” or “systematic reviews” or randomi*ed) OR ts=(study near/1 design) or ts=(multi near/1 center near/1 study) OR ts=(multi near/1 center near/1 studies) or ts=(evaluation near/1 research) or ts=(validation near/1 studies) or ts=(validation near/1 study) or ts=(meta near/1 analys*s) or ts=(systematic near/1 review*) or ts=(retrospective) or ts=(treatment near/1 guideline*) or ts=(quantitative) or ts=(longitudinal) or ts=(cohort*) or ts=(control) or ts=(follow near/1 up) or ts=(prospective) or ts=(longitudinal) or ts=(experiment*) or ts=(qualitative) or ts=(guideline*)

#3 TS=(“decision support systems”) AND (clinical)

#4 TS=(“computer assisted therapy”)

#5 TS=(computer* or electronic*) AND TS=(alert* or reminder* or recommendation* or dashboard* or “order set” or “order sets” or guideline*)

#6 TS=(randomi*ed and reminder*)

#7 TS=(cpoe or “physician order entry” or “provider order entry” or “clinical decision support system” OR “clinical decision support systems”)

#8 TS=(“infobutton” or “infobuttons”)

#9 TS=(Information Retrieval Tool* OR “Automated Information Storage” or “Automated Information Retrieval”. or “Information Services”. or “Information Dissemination”. or “Databases”. or “Medlars” or “PubMed” or “knowledge base” or “knowledge bases” or “handheld computer” or “handheld computers” or “personal digital assistant*)

#10 TS=(“computerized medical record system” or “computerized medical record systems” or “computerized patient record” or “computerized patient records”)

#11 TS=(“knowledge resource” or “knowledge resources” or diseasedex or firstconsult or clineguide or inforetriever or “essential evidence” or emedicine or “evidence matters” or UpToDate or dynamed or epocrates or zynx or micromedex or mdconsult or “md-consult” or infopoems or pier or “5-minute clinical consult” or “national guidelines clearinghouse” or “national guideline clearinghouse” or Stat!Ref)

#12 TS=(“Isabel”) And ( “diagnosis”)

#13 TS=(“online system” or “online systems” or Medlars or PubMed or “Knowledge Base” or “Knowledge Bases” or “handheld computer” or “handheld computers” or “personal digital assistant” or person digital assistants”)

#14 TS=(“Automated Information Storage” or “Automated Information Retrieval” or database or databases or Internet)

#15 TS=(“Reference Books” or “Reference Book” or textbook*) AND TS=(computer* or electronic or online or “on-line” or wireless or internet or digital)

#16 TS=(“knowledge resource” or “knowledge resources” or “information resource” or “information resources” or “health resource” or “health resources” or “clinical resource” or “clinical resources”) or TS=(knowledge near/1 resource*) OR TS=(information near/1 resource*) OR TS=(health near/1 resource*) or TS=(clinical near/1 resource*)

#17 TS=(computer* or electronic or online or “on-line” or wireless or digital or microcomputer*)

#18 #16 AND #18

#19 TS=(“bedside” or “decision” or “decisions” or “point-of-care”. or “real-time”. or “just-in-time”. or “practice pattern” or “practice patterns”. or “patient-related question” or “patient-related questions” or “consultation”. or “consultations”) AND TS=(“patient” or “patients” or “clinical practice” OR “decision making”)

#20 TS=(decision near/1 support) and ts=(computer* or electronic) and ts=(clinical or health or therapy or therapies)

#21 TS=(randomi*ed near/1 reminder*)

#22 (TS=(reminder* or alert* or recommendation* or dashboard* or guideline*) OR TS=(“order set” OR “order sets”)) AND (TS=(computer* or electronic* or email*))

#23 TS=(COMPUTERIZED near/1 REMINDERS) OR TS=(decision near/1 support) OR TS=(clinical near/1 information near/1 system*) OR TS=(knowledge near/1 base*) or TS=(online near/1 system*) or ts=(information near/1 management) or TS=(portable near/1 computer*) or TS=(information near/1 retrieval) or TS=(information near/1 storage) or ts=(database*) OR ts=(diseasedex) or ts=(firstconsult) or ts=(clineguide) or ts=(inforetriever) or ts=(essential near/1 evidence) or ts=(emedicine) or ts=(micromedex) or ts=(evidence near/1 matters) or ts=(md near/1 consult) or ts=(dynamed) or ts=(epocrates) or ts=(national near/1 guideline* near/1 clearinghouse) or ts=(stat near/1 ref) or ts=(statref) or ts=(stat!ref) or ts= (infopoems) or ts=(5 near/1 minute near/1 clinical near/1 consult) or ts=(pier) or ts=(micromedex)

#24 #1 AND #2 AND (#3 OR #4 OR #5 OR #6 OR #7 OR #8 OR #9 OR #10 OR #11 OR #12 OR #13 OR #14 OR #15 OR #18 OR #19 OR #20 OR #21 OR #22 OR #23)

Economic Review

To examine the economics of effectiveness of clinical decision-support systems (CDSS) in improving provider practices for identifying and managing risk factors for cardiovascular disease such as high blood pressure, type 2 diabetes, and high cholesterol, a systematic review of the economic evidence was conducted.

Studies with economic information were identified from a broad systematic review published in 2012 (Bright et al., search period January 1976-January 2011) and an updated search for newer CVD studies (search period January 2011-October 2012).In addition, a search was conducted within specialized economics databases covering the period of January 1970 through March 2013. The details of the specialized economic search are described here.

Three bibliographic databases were searched during February-March 2013: JSTOR, EconLit, Centre for Reviews and Dissemination. The types of documents retrieved by the searched included journal articles, books, book chapters, reports, and conference papers.

Search terms (listed below) and search strategies were adjusted to each database, based on controlled and uncontrolled vocabularies and search software.

Search Terms [* = truncation]

Cardiovascular Disease (CVD) Key Terms:

antihypertensive*

blood pressure

cholesterol

diabetes mellitus

glucose intolerance

high blood pressure

high cholesterol

hypercholesterol*

hypercholesterolemia

hyperlipid*

hyperlipidemia

hypertension

impaired glucose tolerance

insulin resistan*

lipids

metabolic syndrome

non insulin dependent

prediabetes

prediabetic

statins

type ii diabetes

Decision Support Key Terms:

5-minute clinical consult

alert

automated information storage/retrieval

bedside/decision*/point-of-care

Clineguide

clinical decision support system*

clinical practice

clinical resource*

computer assisted decision making

computer assisted drug therapy

computer assisted therapy

computer*

computerized medical record system*

computerized patient record*

consultation*

CPOE

dashboard

databases

decision making

decision support

decision support systems

digital

Diseasedex

Dynamed

electronic

email

Emedicine

epocrates

Essential Evidence

Evidence Matters

Firstconsult

guideline*

handheld computer

health resource*

infobutton*

Infopoems

Inforetriever

information dissemination

information resource*

information retrieval tool*/services/dissemination

Information services

internet

Isabel + diagnosis

just-in-time

knowledge base

knowledge resource*

MDConsult

medical order entry systems

Medlars

microcomputer*

Micromedex

National guideline clearinghouse

online

order set

patient practice

patient*

patient-related question*

personal digital assistant

physician/provider order entry

Pier

practice pattern*

PubMed

randomized reminder*

real time

recommendation*

reference book*

reminder*

Stat!Ref

textbook*

UpToDate

wireless

Zynx

*=truncation symbol [Plurals and British spelling variations searched also.]

Database – EconLit

Search modes – Boolean/Phrase

S20 S13 AND S19 Limiters – Published Date from: 20110101-20131231

S19 S14 OR S15 OR S16 OR S17 OR S18

S18 micromedex or online or “information dissemination” or “information retrieval” or infobutton* or “information services” or infopoems or wireless or mdconsult or statref or stat!ref or recommendation* or reference or zynx or practice* or (isabel and diagnosis)

S17 “order set” or “order sets” or “knowledge resource” or databank* or pier or “order entries” or “order entry” or reminder* or “information resource*”

S16 “real time” or “uptodate” or zynx or “health resource” or firstconsult or evidence or epocrates or cpoe or “clinical resource” or clineguide

S15 digital or emedicine or email or diseasedex or dynamed or infobutton*

S14 computer* or database* or dashboard or automated or electronic

S13 S1 OR S2 OR S3 OR S4 OR S5 OR S6 OR S7 OR S8 OR S9 OR S10 OR S11 OR S12 OR S13

S12 prediabetes or “pre-diabetes” or prediabetic or “pre-diabetic”

S11 hyperglycemia

S10 “metabolic syndrome”

S9 “insulin resistant”

S8 “insulin resistance”

S7 antihypertensive*

S6 statins

S5 statin

S4 hypercholesterol*

S3 cholesterol

S2 “blood pressure”

S1 diabetes

Databases – Centre for Reviews and Dissemination

NHS Economic Evaluations Database (EED)

(computer* or electronic or online or email or emedicine or cpoe or digital or database* or dashboard or guideline* or practice* or wireless or internet or information or order NEAR1 set or reminder* or entry NEAR1 system* ) AND (diabet* or cholesterol or lipids or blood near1 pressure or hypertension or antihypertensive* or hypercholesterol* or hyperlipid* or glucose near1 tolerance or glucose near1 intolerance or insulin near1 resistan* or metabolic near1 syndrome or non near1 insulin near1 dependent or prediabet* or statin or statins) IN NHSEED FROM 2011 TO 2013

OR

ALL CRD-York Databases

(cost* or economic* or savings) AND (diabet* or cholesterol or lipids or blood near1 pressure or hypertension or antihypertensive* or hypercholesterol* or hyperlipid* or glucose near1 tolerance or glucose near1 intolerance or insulin near1 resistan* or metabolic near1 syndrome or non near1 insulin near1 dependent or prediabet* or statin or statins) AND (computer* or decision or digital or online or internet or database* or knowledge near1 base* or automated or cpoe or dashboard or diseasedex or epocrates or emedicine or e near1 medicine or electronic or microcomputer* or reminder* or alert* or system* or evidence or diseasedex or dynamed or email or electronic or firstconsult or guideline* or practice* or wireless or infobutton* or infopoem* or inforetriever or information or Micromedex or uptodate or statref or stat!ref or zynx or recommend* or Isabel or just near1 time or order near1 set or pier or resource*) FROM 2011 TO 2013

Database – JSTOR

Group A

(“”high cholesterol” OR “high blood pressure” OR statin OR statins OR antihypertensives OR antihypertensive OR hypercholesterol OR hypercholesterolemia or hypertension or hypercholesterolaemia or hyperlipid*) AND (year:[2011 TO 2013]) AND la:(eng) AND disc:(economics-discipline)

OR

(“glucose intolerance” or “glucose intolerant” or “insulin resistan*” or diabetes or “‘impaired glucose tolerance” or “metabolic syndrome” or prediabetes OR prediabetic or “pre-diabetes” or “pre-diabetic”) AND (year:[2011 TO 2013]) AND la:(eng) AND disc:(economics-discipline)

AND

Group B

(microcomputer OR reminder OR reminders OR alert OR alerted OR alerts OR alerting OR system OR systems OR evidence OR diseasedex OR dynamed OR email OR electronic or computer* or decision or digital or online or internet or database or databases or “knowledge base” or automated or dashboard or epocrates or emedicine)

OR

(“e-medicine” or electronic or statref or Stat!Ref or Zynx or recommend or recommended or recommendation or recommendations or Isabel or “just-in-time” or guideline or guidelines or practice or practices or wireless or infobutton or infobuttons or infoPOEMs or InfoRetriever or information or Micromedex or UpToDate or “order set” or “order sets” or pier or resource or resources)

OR

(“5-minute clinical consult” or bedside or “point-of-care” or Clineguide or “clinical practice” or consultation* or CPOE or digital or FirstConsult or handheld or internet)

OR

(MdConsult or Medlars or patient* or “order entry” or “practice pattern*” or PubMed or “real time” or “reference book*” or textbook*)

NOTE: In JSTOR, advanced search mode was used. Each set from Group A was combined separately with each set from Group B, due to the restricted number of search terms JSTOR allows. Duplicates were removed to get the final total of 161.

Bright TJ, Wong A, Dhurjati R, Bristow E, Bastian L, et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med 2012;157(1):29-43.

The following considerations are drawn from studies included in the evidence review, the broader literature, and expert opinion.

• Barriers to efficient healthcare delivery exist at multiple levels including patient-related barriers, provider-related barriers, community-related barriers, and organizational barriers. CDSS addresses provider-related barriers mainly ‘clinical inertia’, which is the failure to modify treatment when necessary. To address all barriers, CDSS may need to be used with other effective strategies such as culturally competent healthcare, team-based care, or other infrastructural improvements.
• Successful CDSS typically do the following (Bright et al., 2012):
  • Provide patient assessments and treatment recommendations automatically
  • Deliver assessments and recommendations at the time and location of decision-making
  • Give a recommendation, not just an assessment
  • Automatically incorporate patient data from electronic health records
  • Link with electronic patient charts to support workflow integration
  • Promote action rather than inaction
  • Provide research evidence to justify assessments and recommendations
  • Engage local users during system development
  • Give decision-support results to patients and providers
• The Centers for Medicare & Medicaid Services has developed a set of standards for ‘meaningful use‘ of EHR technology and offers financial incentives to individual providers and healthcare systems that adhere to the standards.
• Healthcare providers may be more accepting of CDSS if they are encouraged to provide input during system development and offered training and orientation.
• Use of CDSS changes the way patients and providers traditionally interact during a visit. It is important that new CDSS are designed in a way that fosters productive patient-provider interaction.
• Health systems should consider additional interventions that could be integrated with CDSS such as provider performance feedback reports or system-level interventions such as team-based care.

CDC’s Division for Heart Disease and Stroke Prevention developed Best Practices for Cardiovascular Disease Prevention Programs: A Guide to Effective Health Care System Interventions and Community-Clinical Links to help communities select and implement successful interventions. The guide summarizes the effectiveness and economic evidence behind eight strategies to prevent cardiovascular disease, including clinical decision-support systems. For each strategy, the guide offers information on implementation, such as settings where the strategies have been successful, resources available to support implementation, and policy considerations. “Stories from the Field” feature specific settings where strategies have been successfully implemented.

Healthy People 2030

Healthy People 2030 includes the following objectives related to this CPSTF recommendation.

• Increase cholesterol treatment in adults — HDS-07