Abstract

Preventive care measures remain underutilized despite recommendations to increase their use. The objective of this review was to examine the characteristics, types, and effects of paper- and computer-based interventions for preventive care measures. The study provides an update to a previous systematic review. We included randomized controlled trials that implemented a physician reminder and measured the effects on the frequency of providing preventive care. Of the 1,535 articles identified, 28 met inclusion criteria and were combined with the 33 studies from the previous review. The studies involved 264 preventive care interventions, 4,638 clinicians and 144,605 patients. Implementation strategies included combined paper-based with computer generated reminders in 34 studies (56%), paper-based reminders in 19 studies (31%), and fully computerized reminders in 8 studies (13%). The average increase for the three strategies in delivering preventive care measures ranged between 12% and 14%. Cardiac care and smoking cessation reminders were most effective. Computer-generated prompts were the most commonly implemented reminders. Clinician reminders are a successful approach for increasing the rates of delivering preventive care; however, their effectiveness remains modest. Despite increased implementation of electronic health records, randomized controlled trials evaluating computerized reminder systems are infrequent.

Introduction

The U.S. Preventive Task Force developed guidelines to facilitate the dissemination and implementation of preventive care measures among health care providers.1,2 Opportunities for offering patients preventive care measures exist during most encounters with the health care system,3 such as vaccinations during primary care visits,4 prophylactic aspirin and vaccinations prior to discharge from the hospital,5 or vaccinations during an emergency department visit.6 However, preventive care measures remain underutilized5,7,8 and clinicians struggle with finding time to be compliant with offering the numerous recommended examinations and procedures when a patient's primary visit reason is unrelated to prevention.9 For example, the U.S. Department of Health and Human Services' Healthy People 2010 target for colorectal cancer screening is 50%, but only 35% of eligible people have a screening examination.1 Similarly, the 70% influenza and 65% pneumococcal vaccination rate for patients aged 65 years and older are considerably below the 90% target.10 In a US study examining 38 different preventive care quality indicators patients received only 54.9% of recommended preventive care measures.8

Different implementation approaches to increase preventive care measures have demonstrated various levels of success. Successful approaches include organizational change interventions, financial incentives, or patient and provider reminders.11–13 With the increased implementation of clinical information systems, broader adoption and application of information technology for patient care, including preventive care applications, can be expected. In the ambulatory setting computer-based reminders increased the implementation of some preventive care measures, but failed in others.14,15 In an outpatient setting computerized prompts were more effective at increasing influenza vaccination rates when compared to paper-based reminders.16 Balas et al. examined the effect of various intervention techniques for prompting physicians.17 The study included reports from 1966 to 1996 and found that the average rate difference for adherence to recommended preventive care strategies using computer-generated reminders did not differ from non-computerized prompting approaches.

Although a recent US national survey18 suggested that the application of information technology is associated with increased physician reminder use, there is limited information whether the recent focus on implementing clinical information systems has provided the infrastructure to support the development and application of computer-based reminder systems for preventive care. The goal of this systematic literature review was to update the study by Balas et al.,17 which included 16 preventive care measures from the US Preventive Task Force, and to examine whether the amount of computerized reminder systems for preventive care have changed as clinicians increasingly utilize electronic health record systems when providing patient care.

Methods

Literature Search

The study methodology from Balas et al. was adopted to perform a systematic review of the literature regarding 16 preventive medicine reminders to clinicians.17 Eligible studies included randomized controlled trials that targeted clinicians and applied a reminder system for at least one of 16 preventive medicine procedures: fecal occult blood testing; mammography; Papanicolaou smear; influenza, pneumococcal or tetanus vaccination; diabetes mellitus management; cholesterol screening; hemoglobin or blood pressure management; cardiac care; smoking cessation; glaucoma screening; alcohol abuse counseling; prenatal care; and tuberculin testing.

For the period January 1, 1997 to December 31, 2004, we queried the electronic literature databases PUBMED® (MEDLINE®),19 OVID CINAHL®,20 ISI Web of Science™,21 Health and Psychosocial Instruments,20 and the Health Reference Center.22 The search was limited to studies published in English. In each database we searched for the combination of the following three concepts: (1) preventive care measure; (2) reminder system; and (3) randomized clinical trial. In MEDLINE, all search terms were defined as Medical Subject Headings (MeSH®) unless otherwise noted and were searched as they appear below; in the remaining databases, the search terms were defined only as keywords.

  1. Preventive care measure: preventive health services, immunization, vaccination, smoking, smoking cessation, mass screening, mammography, prenatal care, hypertension, blood pressure, diabetes mellitus, alcoholism, substance-related disorders, vaginal smears, hypercholesterolemia, glaucoma, or occult blood.

  2. Reminder system: checklist (text word), encounter forms (text word), tags (text word), triggers (text word), reminder systems, alert (text word), reminder (text word), leaflets (text word), stickers (text word), messages (text word), or tailored messages (text word).

  3. Randomized clinical trial: random' (truncated text word), group' (truncated text word), random allocation, randomized controlled trial (publication type), or clinical trial (publication type).

Review of Identified Studies

The title and abstract of all articles identified using the keyword searches were retrieved and reviewed by two of four independent reviewers (JWD, DLS, SR, DA). Disagreements between two reviewers were resolved by consensus among all four participating reviewers. The bibliographies of identified systematic reviews and meta-analyses were reviewed and additional relevant studies were included. The full text of included articles was obtained and two reviewers (JWD, DA) independently scored each article using the quality assessment instrument that was applied during the previous study.17 Disagreements were resolved by consensus discussion. The assessment instrument included ten criteria evaluating the study characteristics (randomization techniques, testing, withdrawals, effect variables) and assigned a summary score between 0 and 100.23 Five criteria examine the methodology and characteristics of the study design. Following the previous review methodology articles scoring below 50 were excluded from further consideration.23 All included studies were examined for redundancy and duplicate results were removed.

Reminder implementations were classified as “paper-based,” “computer-generated,” or “computerized.” Paper-based reminders included the use of memos, stickers, or a slip of paper within the patient's chart. Computer-generated reminders included application of computerized algorithms to identify eligible patients, but the prompt was printed out and placed in the patient chart to remind the clinician. Computerized reminders included prompts that were entirely electronic, i.e., computerized algorithms identified eligible patients, and prompts were provided upon access to the electronic clinical information system.

Analysis

We combined the articles from the previous review (1966 to 1996)17 with the newly identified articles (1997 to 2004). In studies with more than one preventive care prompt, each intervention was analyzed separately for the effect of the prompt on the given procedure. For example, if a vaccination study compared a paper-based versus a computer-based implementation approach, each approach was counted and examined individually. For each study, the intervention effect was calculated by subtracting the control or baseline data from the largest increase in effect. The unweighted difference in rates of each study was averaged to create the average effect for each implementation strategy, reminder strategy, or intervention. Odds ratios were converted into percentages for data analysis measures. Agreement among reviewers to consider articles based on title and abstract was high (0.96 to 0.99), as determined by Yule's Q.24 

graphic

Results

Search Results

The literature search produced 1,535 articles during the time period from 1997 to 2004 (Figure 1). The MEDLINE search contributed 1,308 articles, CINAHL 148, Health and Psychological Instruments three, the Health Reference Center two, and ISI Web of Knowledge 74. After removing 131 duplicate articles, 1,396 were further excluded based on the review of the abstracts. Of the remaining 35 reports, 11 were excluded from further analysis (nine scored less than 50 in the quality assessment, one examined only the system design, and one had no clinician prompt). Reviews of reference lists accounted for an additional 9 articles with 4 meeting inclusion criteria, for a total of 28 included studies. One paper had no numerical results and was not included in the average effect calculations.25 One paper had redundant results and these were removed for analysis.26 We combined the 28 trials with the previous 33 studies for a total of 61 studies.4,5,25–83Table 1 shows the detailed characteristics of the included studies.

Figure 1

Flow diagram of included and excluded studies (1997 to 2004).

Figure 1

Flow diagram of included and excluded studies (1997 to 2004).

Table 1

Study Characteristics, Grouped by Implementation Strategy

Source  Reminder    Clinicians  
Reference Author Year Targeted Action a Paper-based Computer-generated Computerized Institution Study setting Patients Clinicians Provider type Specialty Study Locations 
27 Bankhead 2001 CaScr In Chart   non-acad 1158 13 MDa GP Birmingham; North of London; West of London 
28 Cheney 1987 Immun, CaScr, Chol Front   acad 200 75 MDr IM University of California, San Diego 
29 Cohen 1982 Immun, CaScr Front   acad 2138 22 MDr GP Case Western 
30 Costanza 2000 CaScr MD Letter   acad 1655 480 MDa, MDr GP, IM University of Massachusetts Medical School 
31 Cowan 1992 Immun, CaScr, Chol Front   acad 107 29 MDa GP University of Illinois 
4 Frame 1994 Immun, CaScr, Chol Front   non-acad 1666 12 MDa, PA GP University of Rochester (NY) 
32 Hambidge 2004 Immun In Chart   non-acad 2665 NS MDa, MDr GP Denver Health Medical Center 
33 Myers 2004 CaScr Letter   non-acad 2992 470 MDa GP 318 primary care practices Pennsylvania, and NJ 
34 MacIntyre 2003 Immun MD Letter   non-acad 131 NS MDa GP The Royal Melbourne Hospital 
35 Manfredi 1998 CaScr Tagged   non-acad 4554 87 MDa GP Primary care practices in the Chicago area 
36 Pierce 1989 CaScr Tagged   non-acad 276 MDa GP Guy's and St Thomas's Hospitals 
37 Pritchard 1995 CaScr Tagged   non-acad 383 12 MDa GP University of Western Australia 
38 Robie 1988 CaScr Front   acad 356 41 MDr IM Wake Forest University 
39 Rodewald 1999 Immun Tagged   non-acad 2741 NS MDa PED Primary care practices in the Rochester area 
40 Roetzheim 2004 CaScr Tagged   non-acad 1196 NS MDa GP Hillsboro County Clinics 
41 Shevlin 2002 Immun In Chart   acad 534 NS MDr, MDa  Grady Memorial Hospital, Atlanta, Georgia 
42 Simon 2001 CaScr In Chart   non-acad 1717 NS MDa GP Detroit Health Department Primary Care Clinics 
43 Somkin 1997 CaScr In Chart   non-acad 7077 NS MDa GP Kaiser Permanente Medical Care Program of Northern California 
44 Thompson 2000 CaScr Patient List   non-acad 1109 MDa, MDr, LPN IM Veterans Affairs Medical Center Puget Sound, Seattle Washington 
45 Barnett 1983 BP  Front  non-acad 115 48 MDa, RN IM Massachusetts General Hospital 
46 Becker 1989 Immun, CaScr, GS  Front  acad 563 80 MDr IM University of Virginia 
47 Burack 1994 CaScr  In chart  non-acad 2725 25 MDa GP, IM, OBG Wayne State University 
48 Burack 2003 CaScr  In chart  non-acad 2471 20 MDa GP, IM, OBG HMO Practice sites in Detroit, Michigan 
49 Burack 1998 CaScr  In chart  non-acad 1471 20 MDa GP, IM, OBG HMO Practice sites in Detroit, Michigan 
50 Burack 1997 CaScr  In chart  non-acad 2890 25 MDa GP, IM, OBG Wayne State University 
51 Buschbaum 1993 Alcohol  Front  acad 214 83 MDr GP Medical College of Virginia 
52 Chambers 1989 CaScr  Front  acad 1262 30 MDr, MDa GP Thomas Jefferson University 
53 Chambers 1991 Immun  Front  acad 686 30 MDr, MDa GP Thomas Jefferson University 
54 Cummings 1989 NoSmok  Front  non-acad 916 44 MDa GP, IM University of California, San Francisco 
55 Daley 2004 Immun  Front  acad 420 NS MDa, MDr PED The Children's Hospital, Denver, CO 
56 Headrick 1992 Chol  Front  acad 240 33 MDr IM Case Western 
57 Landis 1992 CaScr  Front  acad 57 24 MDa, MDr GP Mt Area Health Education Center 
58 Litzelman 1993 CaScr  Front  acad 5407 176 MDr, MDa IM Regenstrief 
59 Lobach 1994 DiabM  Front  acad 359 58 MDr, MDa, PA, NP GP Duke Family Medicine Center 
25 McDonald 1976 BP, Chol, HgB, DiabM  Front  acad 189 MDr IM Regenstrief 
60 McDonald 1976 BP, DiabM, CC  Front  acad 301 63 MDa, MDr, RN IM Regenstrief 
61 McDonald 1984 Immun, CaScr, HgB, TB  Front  acad 775 115 MDr, MDa IM Regenstrief 
62 McDowell 1989 CaScr  Front  acad 789 32 MDa, MDr, RN GP University of Ottawa 
63 McDowell 1989 BP  Front  acad 2803 32 MDa, MDr, RN GP University of Ottawa 
64 McPhee 1989 CaScr  Front  acad 1936 62 MDr IM University of California, San Francisco 
65 Morgan 1978 Prenatal care  Front  non-acad 279 MDa/RN teams OBG Massachusetts General Hospital 
66 Nilasena 1995 DiabM  Front  acad 164 35 MDr IM Salt Lake Veterans Affairs Hospital, University of Utah 
67 Ornstein 1991 Immun, CaScr, Chol  Front  acad 7397 49 MDr, MDa GP Medical University of South Carolina 
68 Rhew 1999 Immun  Front  non-acad 3502 NS RN, MDa GP West Los Angeles VA General Medicine ambulatory clinic 
26 Rosser 1991 NoSmok  Front  acad 5883 36 MDa, MDr GP University of Toronto/University of Ottawa 
69 Rosser 1992 Immun  Front  acad 5242 32 MDr, MDa, RN GP University of Toronto/University of Ottawa 
70 Rossi 1997 BP  Front  non-acad 719 71 MDa, NP, MDr IM Veterans Affairs Medical Center Puget Sound, Seattle Washington 
71 Shaw 2000 Immun  Front  acad 595 52 MDr PED Children's Hospital, Boston 
72 Soljak 1987 Immun  Patient List  non-acad 2988 40 MDa GP New Zealand 
73 Taylor 1999 CaScr  Front  acad 314 49 MDr, MDa  University of Washington, Seattle 
74 Tierney 1986 Immun, CaScr  In chart  acad 6045 138 MDr GP Regenstrief 
75 Turner 1990 Immun, CaScr  Front  acad 423 24 MDr IM East Carolina University 
76 Williams 1998 CaScr  Front  non-acad 5789 507 MDr GP Primary Care Practices in the Southeast 
77 Ansari 2003 CC   Display non-acad 169 301 MDa, MDr, NP IM, Card San Francisco Veterans Affairs Medical Center 
78 Demakis 2000 BP, DiabM, CC, NoSmok   Display non-acad 12989 275 MDr GP Veterans Affairs Medical Centers (12) 
5 Dexter 2001 Immun, Heparin, Aspirin   Display acad 6371 202 MDa, MDr, RN GP Wishard Memorial Hospital 
79 Dexter 2004 Immun   Display acad 3777 212 MDa, MDr, RN GP Wishard Memorial Hospital 
80 Eccles 2002 Angina   Display non-acad 4851 NS MDa GP North East England General Practices 
81 Filippi 2003 Antiplatlet drugs for Diab   Display non-acad 15343 300 MDa GP Italy 
82 Murray 2004 BP   Display acad 712 NS MDr, MDa  Indiana University School of Medicine 
83 Tape 1993 Immun, CaScr   Display acad 1809 49 MDr, MDa IM University of Nebraska 
Source  Reminder    Clinicians  
Reference Author Year Targeted Action a Paper-based Computer-generated Computerized Institution Study setting Patients Clinicians Provider type Specialty Study Locations 
27 Bankhead 2001 CaScr In Chart   non-acad 1158 13 MDa GP Birmingham; North of London; West of London 
28 Cheney 1987 Immun, CaScr, Chol Front   acad 200 75 MDr IM University of California, San Diego 
29 Cohen 1982 Immun, CaScr Front   acad 2138 22 MDr GP Case Western 
30 Costanza 2000 CaScr MD Letter   acad 1655 480 MDa, MDr GP, IM University of Massachusetts Medical School 
31 Cowan 1992 Immun, CaScr, Chol Front   acad 107 29 MDa GP University of Illinois 
4 Frame 1994 Immun, CaScr, Chol Front   non-acad 1666 12 MDa, PA GP University of Rochester (NY) 
32 Hambidge 2004 Immun In Chart   non-acad 2665 NS MDa, MDr GP Denver Health Medical Center 
33 Myers 2004 CaScr Letter   non-acad 2992 470 MDa GP 318 primary care practices Pennsylvania, and NJ 
34 MacIntyre 2003 Immun MD Letter   non-acad 131 NS MDa GP The Royal Melbourne Hospital 
35 Manfredi 1998 CaScr Tagged   non-acad 4554 87 MDa GP Primary care practices in the Chicago area 
36 Pierce 1989 CaScr Tagged   non-acad 276 MDa GP Guy's and St Thomas's Hospitals 
37 Pritchard 1995 CaScr Tagged   non-acad 383 12 MDa GP University of Western Australia 
38 Robie 1988 CaScr Front   acad 356 41 MDr IM Wake Forest University 
39 Rodewald 1999 Immun Tagged   non-acad 2741 NS MDa PED Primary care practices in the Rochester area 
40 Roetzheim 2004 CaScr Tagged   non-acad 1196 NS MDa GP Hillsboro County Clinics 
41 Shevlin 2002 Immun In Chart   acad 534 NS MDr, MDa  Grady Memorial Hospital, Atlanta, Georgia 
42 Simon 2001 CaScr In Chart   non-acad 1717 NS MDa GP Detroit Health Department Primary Care Clinics 
43 Somkin 1997 CaScr In Chart   non-acad 7077 NS MDa GP Kaiser Permanente Medical Care Program of Northern California 
44 Thompson 2000 CaScr Patient List   non-acad 1109 MDa, MDr, LPN IM Veterans Affairs Medical Center Puget Sound, Seattle Washington 
45 Barnett 1983 BP  Front  non-acad 115 48 MDa, RN IM Massachusetts General Hospital 
46 Becker 1989 Immun, CaScr, GS  Front  acad 563 80 MDr IM University of Virginia 
47 Burack 1994 CaScr  In chart  non-acad 2725 25 MDa GP, IM, OBG Wayne State University 
48 Burack 2003 CaScr  In chart  non-acad 2471 20 MDa GP, IM, OBG HMO Practice sites in Detroit, Michigan 
49 Burack 1998 CaScr  In chart  non-acad 1471 20 MDa GP, IM, OBG HMO Practice sites in Detroit, Michigan 
50 Burack 1997 CaScr  In chart  non-acad 2890 25 MDa GP, IM, OBG Wayne State University 
51 Buschbaum 1993 Alcohol  Front  acad 214 83 MDr GP Medical College of Virginia 
52 Chambers 1989 CaScr  Front  acad 1262 30 MDr, MDa GP Thomas Jefferson University 
53 Chambers 1991 Immun  Front  acad 686 30 MDr, MDa GP Thomas Jefferson University 
54 Cummings 1989 NoSmok  Front  non-acad 916 44 MDa GP, IM University of California, San Francisco 
55 Daley 2004 Immun  Front  acad 420 NS MDa, MDr PED The Children's Hospital, Denver, CO 
56 Headrick 1992 Chol  Front  acad 240 33 MDr IM Case Western 
57 Landis 1992 CaScr  Front  acad 57 24 MDa, MDr GP Mt Area Health Education Center 
58 Litzelman 1993 CaScr  Front  acad 5407 176 MDr, MDa IM Regenstrief 
59 Lobach 1994 DiabM  Front  acad 359 58 MDr, MDa, PA, NP GP Duke Family Medicine Center 
25 McDonald 1976 BP, Chol, HgB, DiabM  Front  acad 189 MDr IM Regenstrief 
60 McDonald 1976 BP, DiabM, CC  Front  acad 301 63 MDa, MDr, RN IM Regenstrief 
61 McDonald 1984 Immun, CaScr, HgB, TB  Front  acad 775 115 MDr, MDa IM Regenstrief 
62 McDowell 1989 CaScr  Front  acad 789 32 MDa, MDr, RN GP University of Ottawa 
63 McDowell 1989 BP  Front  acad 2803 32 MDa, MDr, RN GP University of Ottawa 
64 McPhee 1989 CaScr  Front  acad 1936 62 MDr IM University of California, San Francisco 
65 Morgan 1978 Prenatal care  Front  non-acad 279 MDa/RN teams OBG Massachusetts General Hospital 
66 Nilasena 1995 DiabM  Front  acad 164 35 MDr IM Salt Lake Veterans Affairs Hospital, University of Utah 
67 Ornstein 1991 Immun, CaScr, Chol  Front  acad 7397 49 MDr, MDa GP Medical University of South Carolina 
68 Rhew 1999 Immun  Front  non-acad 3502 NS RN, MDa GP West Los Angeles VA General Medicine ambulatory clinic 
26 Rosser 1991 NoSmok  Front  acad 5883 36 MDa, MDr GP University of Toronto/University of Ottawa 
69 Rosser 1992 Immun  Front  acad 5242 32 MDr, MDa, RN GP University of Toronto/University of Ottawa 
70 Rossi 1997 BP  Front  non-acad 719 71 MDa, NP, MDr IM Veterans Affairs Medical Center Puget Sound, Seattle Washington 
71 Shaw 2000 Immun  Front  acad 595 52 MDr PED Children's Hospital, Boston 
72 Soljak 1987 Immun  Patient List  non-acad 2988 40 MDa GP New Zealand 
73 Taylor 1999 CaScr  Front  acad 314 49 MDr, MDa  University of Washington, Seattle 
74 Tierney 1986 Immun, CaScr  In chart  acad 6045 138 MDr GP Regenstrief 
75 Turner 1990 Immun, CaScr  Front  acad 423 24 MDr IM East Carolina University 
76 Williams 1998 CaScr  Front  non-acad 5789 507 MDr GP Primary Care Practices in the Southeast 
77 Ansari 2003 CC   Display non-acad 169 301 MDa, MDr, NP IM, Card San Francisco Veterans Affairs Medical Center 
78 Demakis 2000 BP, DiabM, CC, NoSmok   Display non-acad 12989 275 MDr GP Veterans Affairs Medical Centers (12) 
5 Dexter 2001 Immun, Heparin, Aspirin   Display acad 6371 202 MDa, MDr, RN GP Wishard Memorial Hospital 
79 Dexter 2004 Immun   Display acad 3777 212 MDa, MDr, RN GP Wishard Memorial Hospital 
80 Eccles 2002 Angina   Display non-acad 4851 NS MDa GP North East England General Practices 
81 Filippi 2003 Antiplatlet drugs for Diab   Display non-acad 15343 300 MDa GP Italy 
82 Murray 2004 BP   Display acad 712 NS MDr, MDa  Indiana University School of Medicine 
83 Tape 1993 Immun, CaScr   Display acad 1809 49 MDr, MDa IM University of Nebraska 

Care Measure: CaScr = Cancer Screening; Chol = Cholesterol Management; Immun = Immunizations; HgB = hemoglobin management; CC = Cardiac Care; NoSmok = Smoking Cessation; BP = Blood Pressure management; GS = Glaucoma Screening; TB = Tuberculosis testing; DiabM = Diabetes Management; Alcohol = Alcohol abuse counseling; NS = Not Specified Institution: acad = Academic, non-acad = Non-Academic Provider Type: MDa = Attending Physician; MDr = Resident Physicians; NP = Nurse Practitioner; PA = Physician Assistant; RN = registered nurse; LPN = Licensed Practical Nurse Specialty: IM = Internal Medicine; Card = Cardiology; OBG = Obstetrics/Gynecology; PED = Pediatrics; GP = General Practitioner Number: NS – not specified Setting: o – outpatient; i – inpatient

Number of Studies

Figure 2 displays the number and type of published studies, grouped by intervention's start year. The total number of computerized studies increased in the 2000–2004 period as compared to previous periods. From 2000–2004, nine studies applied paper-based interventions and seven computerized methods, while the number of computer-generated approaches declined to three reports.

Figure 2

Preventive care reminder studies by intervention year. If the intervention's start year was not mentioned in the paper, the publication year − 1 was used to estimate an intervention year.

Figure 2

Preventive care reminder studies by intervention year. If the intervention's start year was not mentioned in the paper, the publication year − 1 was used to estimate an intervention year.

Interventions

The 61 studies examined a total of 264 preventive care interventions (maximum: 16). Nineteen (30%) studies evaluated three or more preventive measures, three (5%) examined two measures, and the remaining 39 (64%) assessed the impact of one measure. With a total of 110 studied interventions cancer screening (fecal occult blood testing, Papanicolaou smears, and mammograms) was the most frequent type of preventive care measure targeted by clinician reminders, followed by 64 interventions targeting vaccination.

Study Setting

The setting of 33 studies was an academic medical center, while the remaining 28 studies were conducted at non-academic hospitals and clinics. Five studies (9.6%) were performed in an inpatient setting, and the remaining 56 studies were in primary care clinics. In the inpatient setting the delivery of vaccinations were the most frequently studied reminders. The number of facilities in each study ranged from one (39 studies) to 1,655 hospitals or practice groups.

Prompting Clinicians

The methods of prompting clinicians are shown in Table 1. Paper-based combined with computer-generated prompts were the most frequent clinician reminder approach and accounted for 34 studies (52%), followed by 19 paper-based (34%), and 8 computerized studies (13%). The three examined prompting approaches demonstrated a similar average increase in completing preventive care measures (Table 2). Paper-based reminders were applied in 80 interventions and resulted in a 14% average increase of preventive care compliance. Computer-generated reminders were implemented 136 times and had an average increase of 12%. Computerized reminders were employed in 48 interventions and resulted in a 13% average increase.

Table 2

Comparison of Primary Implementation Reminder Strategies

Implementation strategy Number of interventions (number of studies) Average difference % (min, max) Standard deviation 
Paper-based 80 (19) 14 (−18 to 46) 15 
Computer-generated 136 (34) 12 (−24 to 59) 13 
Computerized 48 (8) 13 (−8 to 60) 18 
Implementation strategy Number of interventions (number of studies) Average difference % (min, max) Standard deviation 
Paper-based 80 (19) 14 (−18 to 46) 15 
Computer-generated 136 (34) 12 (−24 to 59) 13 
Computerized 48 (8) 13 (−8 to 60) 18 

min = minimum; max = maximum

Prompting Methods

Of the 61 studies, 35 examined interventions that prompted only the clinician, 17 combined the clinician prompt with a patient reminder, and 9 studies examined the effects of prompting the clinician in one study group compared to reminding both the clinician and patient in the other study group. To remind patients, 15 mailed reminder letters, and eight studies notified patients via telephone. One study put up fliers and posters for the patients, one study visited patients at their homes to encourage vaccinations, and another study chose to educate patients on the importance of preventive care to encourage return visits. Table 3 summarizes the effectiveness of clinician reminders only, and the combined approach of clinician and patient reminders. The average increase in preventive care procedure compliance was larger when prompting only the clinician (14%) compared to prompting both the clinician and the patient (10%) All but two of the studies prompted the physician before the patient appointment or at the time of order entry.

Table 3

Comparison of Clinician Only versus Combined Clinician–Patient Reminder Strategy

 Number of Interventions (Number of studies) Average difference % (min, max) Standard deviation 
Clinician only 175 (44) 14 (−18 to 60) 16 
Clinician and patient 105 (26) 10 (−24 to 45) 12 
 Number of Interventions (Number of studies) Average difference % (min, max) Standard deviation 
Clinician only 175 (44) 14 (−18 to 60) 16 
Clinician and patient 105 (26) 10 (−24 to 45) 12 

min = minimum, max = maximum

The total number of interventions exceeds 264 because nine studies, evaluating various numbers of preventive care measures, compared the effect of a unique prompting technique in a clinician only group versus a combined clinician and patient group.

Average Effect

Table 4 displays the effect for measures that were examined by three studies or more. The average effects for measures examined by fewer than three studies ranged from 5% for prenatal care to 14% for alcohol abuse counseling. Prompting clinicians was most effective for smoking cessation (average: 23%), cardiac care (average: 20%), blood pressure screening (average: 16%), followed by vaccinations, diabetes management, and cholesterol (averages: 15%). Mammography reminders had the smallest average effect (10%).

Table 4

Effect of Prompting Clinicians for Preventive Care Procedures in Studies with Three or More Interventions

Preventive care measure  Number of interventions (number of studies)  Average difference % ± sd (min, max)  Distribution   
Vaccination  64 (24)  15 ± 14 [−15 to 50]   
Fecal occult blood testing  23 (16)  12 ± 13 [−11 to 37]   
Papanicolaou smear  36 (20)  12 ± 18 [−24 to 48]   
Mammogram  51 (23)  10 ± 15 [−18 to 49]   
Blood pressure  22 (9)  16 ± 19 [−8 to 59]   
Cholesterol  8 (6)  15 ± 17 [−1 to 54]   
Diabetes management  27 (8)  15 ± 10 [5 to 51]   
Smoking cessation  6 (3)  23 ± 16 [3 to 44]   
Cardiac care  25 (4)  20 ± 11 [−8 to 59]   
Preventive care measure  Number of interventions (number of studies)  Average difference % ± sd (min, max)  Distribution   
Vaccination  64 (24)  15 ± 14 [−15 to 50]   
Fecal occult blood testing  23 (16)  12 ± 13 [−11 to 37]   
Papanicolaou smear  36 (20)  12 ± 18 [−24 to 48]   
Mammogram  51 (23)  10 ± 15 [−18 to 49]   
Blood pressure  22 (9)  16 ± 19 [−8 to 59]   
Cholesterol  8 (6)  15 ± 17 [−1 to 54]   
Diabetes management  27 (8)  15 ± 10 [5 to 51]   
Smoking cessation  6 (3)  23 ± 16 [3 to 44]   
Cardiac care  25 (4)  20 ± 11 [−8 to 59]   

sd – standard deviation; min – minimum; max – maximum

Discussion

This systematic review summarized findings from 61 randomized controlled clinical trials that investigated the use of reminders to increase preventive care. Overall the prompting of clinicians continued to demonstrate a positive effect on the delivery of the 16 preventive care measures. In recent years, however, the clinician reminder strategies shifted from paper- to computer-based approaches.

Approaches that included a paper-based reminder component (paper-based or computer-generated) remained the most frequent implementation strategies (87%) and had a similar average effect as computerized reminders (14% versus 13%). In studies that included a paper-based component, a reminder sheet is attached on the front of the patient chart or tagged the paper chart in some form, indicating that the paper-record remains an important source of information and documentation instrument in many hospitals and clinics. To implement preventive care measures that require multiple steps during a visit, paper-based solutions may be easier integrated with the clinical workflow as compared to designing an information technology solution that depends on the provider's workstation use. Paper-based implementation strategies are effective when the number of targeted preventive care measures is limited. With an increasing number of recommended preventive care measures, a paper-based process may quickly encounter implementation challenges due to the limited scalability. However, clinical workflow processes that rely on paper charts may continue to favor paper-based implementation strategies.

Computer-generated reminders were most common (52%). In recent years, however, studies on the impact of computer-generated prompts tended to decrease, while computerized reminders increased. The recent increase in applying computerized reminder strategies suggests that clinical information systems are increasingly providing the infrastructure to implement preventive care reminders. Computerized reminder systems require an electronic medical record throughout the practice or hospital; however, only 23.9% of physicians in the US are using an electronic medical record system and 5% of hospitals are using computerized provider order entry systems.84 Implementing preventive care measures using computerized reminders may overcome some of the paper-based implementation challenges. Although clinical information systems may provide an easier to scale and more sustainable infrastructure, they work best when clinicians can complete all steps involved in offering preventive care measures, avoiding the need to switch between paper-based and electronic means. For example, adoption of computerized reminders may be higher if systems apply computerized algorithms for eligibility screening, prompt clinicians at the right time, offer quick ordering processes, and facilitate documentation. Unfortunately the availability of such advanced information system environments remain the exception rather than the rule.

The prompts offered through the reminder systems were heterogeneous. Some preventive care procedures would be easier to perform during the visit, such as vaccinations or blood pressure screening, while others may require a separate appointment, such as mammograms. Cardiac care measures and discussion about smoking cessation were most frequently studied. These preventive measures can be performed during the same visit and are more likely to be completed.

One of the goals of any reminder system is providing the right information at the right time, to the right person, and in the right format. Each study did not report a comprehensive description of the environment and clinical workflow; thus, the effectiveness of a prompt may differ depending on the existing workflow and the effectiveness of a support infrastructure, such as additional personnel or the availability of information technology. Any of the approaches used to implement a reminder system should be examined in combination with the support infrastructure within which the reminder system is implemented.

The review has limitations that may influence the interpretation of the findings. First, it is conceivable that preventive care measures have become an accepted standard of care and further studies examining the effects of reminder strategies are not warranted any more. Many commercial health information systems provide the means of implementing reminders for preventive care measures. By prompting the clinicians, there may be behavioral changes that are not documented as outcomes and may therefore influence the preventive care procedure. Second, the possibility of publication bias exists in the studies we included, there may be less negative studies available. We have not excluded the possibility that publication bias may exist, however, we scored the study design of randomized controlled trials for inclusion in the review. It is possible that only including randomized controlled trials may have excluded some computerized systems which may have used historical controls instead of a concurrent control group. And our choice of using the average difference between baseline and intervention could potentially dilute findings related to specific patient populations. The average differences calculated in each study were not weighted by sample size of patients or clinicians. Lastly, this review only considered studies that involved clinicians in the process of offering patients preventive care measures. It is possible that other implementation strategies exist that do not involve the clinicians. The effectiveness of these approaches may differ in providing preventive care.

The average effect for all of the prompting methods was modest, the act of providing a prompt may modify behaviors that are not measured by the system. The clinicians may have been more aware of the preventive care procedures and may have considered them for more patients. By calculating the average effect by using the historical or concurrent control groups, we sought to make the groups as comparable as possible.

Each encounter with the healthcare system provides an opportunity to offer preventive care measures. However, keeping pace with the many different recommendations and various schedules remains a major challenge for busy clinicians that are expected to focus on a patient's current reason for the visit. Although clinical information systems can keep track of the various recommendations and schedules, they may lead to “prompting fatigue” as an unintended consequence.85 An additional challenge is the fragmentation of health care information,86 which requires providers to repeatedly verify the patient's eligibility for a preventive care measure, a time-consuming task even for one measure. As the healthcare sector applies more information technology, the exchange and sharing of electronic health record information among various providers may lessen that burden in the future.

Conclusion

In summary, this review showed an increase in applying computerized reminder systems for prompting clinicians to offer preventive care measures. As information technology reminder solutions may provide a better scalable and more sustainable model for the increasing burden of following different preventive care guidelines, we saw only a moderate increase in the number of randomized controlled trials looking at computerized reminder systems for preventive care.

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JWD was supported by training grant from the National Library of Medicine (LM T15 007450-03). STR was supported by a National Library of Medicine grant (LM K22 08576-02).
Preliminary results from this work were presented at the 2005 AMIA Annual Symposium (ref: Dexheimer JW, Sanders DL, Rosenbloom ST, Aronsky D. Prompting clinicians: a systematic review of preventive care reminders. AMIA Annu Symp Proc. 2005;:938.)

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