Medical Society of Virginia Final Report
Patientcare Device for Asthma: Utility and Acceptability in Primary Care Settings
Investigators: Kurt Elward, MD, MPH, Scott Strayer, MD, MPH
University of
Project Description
The project involved recruiting local (Charlottesville-area) clinicians to use and evaluate a clinical decision support tool for asthma care. The tool is based on the National Heart, Lung, and Blood Institute (NHLBI) and National Asthma Education Program (NAEP) guidelines; it installs on the clinician's handheld computer (PDA). The asthma tool was designed to assist physicians with classifying patients according to the guidelines and detail the specific treatments that are indicated for each level of asthma (see figs. 1 and 2). The tool also incorporates a peak flow calculator (see fig. 3) and prompts physicians to identify triggers and to schedule patient education visits (see fig. 4). In addition, it contains dosing information for asthma medications for adult and pediatric patients (see fig. 5).
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| Fig. 1: Main Screen | Fig. 2: Asthma Classifications | |
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| Fig. 3: Asthma Patient Education | ||
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| Fig. 4 Peak Flow Calculator | Fig. 5 Asthma Drug Dosing |
We asked participants to use the tool in their practice – however and as often (or not) as they wished – for four months. We collected asthma care-specific knowledge and practice trends as well as basic demographics from participants both before (pre-test) and after (post-test) the four-month study period. We also interviewed participants post-study to further explore their opinions on the user-friendliness, relevancy, and efficacy of the tool. No patient information was collected.
Participants
Fourteen clinicians gave consent to be in the study and provided baseline data. Nine were male, two were faculty in the Department of Pediatrics at the
Statistics
All data are reported as mean standard deviation unless otherwise noted. Continuous variables, including the pre- and post-test items with 7-point answer scales (comfort and attitude items), were analyzed as continuous variables using the Wilcoxon Rank Sum test. Categorical variables, including the behavior items, were analyzed using Fisher's Exact test. Statistical significance was assumed at alpha < 0.05. All analyses were conducted using S-Plus 6.1 for Windows (Insightful Corporation,
Results
Ten participants provided useable follow up data (i.e., post-test), with complete data (post-test and interview) available for seven. One of the ten who provided end-of-study data was never able to load the tool onto his PDA, though he answered the post-survey questions that do not deal directly with the tool. Because the goal was to measure knowledge, comfort, and behavioral changes after exposure to the tool, his post-test answers have been omitted from the analysis, leaving nine subjects who had both used the tool and completed the post-test.
Of the four who withdrew from the study, one did not use the tool and asked to be withdrawn, one went on maternity leave and was unable to complete the study, one never got the program loaded onto her PDA, and one was lost to follow up.
Of the nine participants from whom we have post-test data, seven were male, the mean age was 45.4 ± 9.2 years, the mean time since completion of medical training was 16.9 ± 9.1 years, and the median percent of patients with asthma was 10%. This group was not significantly different than those who did not complete the study on any demographic data.
Knowledge change: Three questions on our pre- and post-tests were designed to measure asthma care knowledge. The first two asked participants if they were familiar with the NHLBI asthma guidelines and classification system. The third asked participants to list the classes of asthma currently used by the NHLBI. While all nine participants claimed to be familiar with the NHLBI guidelines on both the pre- and post-tests, only 4 were aware of the classification system at the beginning of the study. On the post-test, all participants claimed awareness of the classification system (p = 0.029). Furthermore, only two participants correctly named the classes on the pre-test, but all nine were able to do so on the post-test.
Comfort change: Six questions addressed participants' comfort levels in dispensing asthma care. Topics addressed included comfort with the NHLBI guidelines, in providing asthma education to patients, in developing asthma care action plans, in discussing inhaled steroids, with the available pharmacological agents available for asthma care, and in managing patients with persistent asthma. No change was seen between the pre- and post-tests for comfort with the NHLBI guidelines. Participants' comfort levels increased slightly for providing asthma education (5.1 ± 1.1 pre, 5.7 ± 1.0 post, on a 7-point scale, with higher numbers indicating increased comfort) and in developing an asthma care action plan (4.7 ± 1.0 pre, 5.1 ± 1.4 post), but decreased slightly for discussing inhaled steroids (6.2 ± 0.9 pre, 5.9 ± 1.5 post), pharmacological agents (6.3 ± 1.0 pre, 5.8 ± 1.5 post), and managing patients with persistent asthma (6.3 ± 0.8 pre, 5.8 ± 1.5 post). None of these changes was statistically significant.
Behavior change: Ten questions asked about practice behavior. Because of our small sample size, we were unable to see effects of the tool on practice behavior for most items (advising patients on the use of controller medications, assessing triggers, evaluating patients in the use of drug delivery devices, scheduling regular follow-up visits, providing asthma teaching, having sufficient time with asthma patients, and providing long-term management information to patients). However, we did find that after using our tool for four months, practitioners were more likely to classify patients according to NHLBI guidelines (p = 0.0476).
Attitude: One question asked participants about the importance they place on classifying patients with asthma; answer options consisted of a 7-point scale, with higher numbers signifying greater importance. The mean score on the pre-test was 4.3 ± 1.3, and this increased to 5.2 ± 1.6 on the post-test. This increase was significant at p = 0.052.
INTERVIEWS
User-friendliness: The clinicians we interviewed (n = 7) all found the tool to be user-friendly and easy to use. They said the tool was “intuitive,” “easy to navigate,” “straightforward,” “well-organized,” “really easy to use,” “very readable,” and “a better presentation of the guidelines [than the printed version].”
Most useful parts of the tool: Clinicians agreed that the tool was useful for reminding them of the classification guidelines. Some mentioned the peak flow calculator as a nice feature, though some complained that it is a pediatrics-only calculator (entering a height > 67 inches gives an error message). Some found the medication and dosing information helpful, though others claimed not to use those screens, instead preferring to use other handheld software pharmacological applications (such as ePocrates). One clinician found the tool to be excellent for “customizing therapy”; another found it “helpful as a patient ed[ucation] tool – [I would] run through it with the patient looking [at the screen] too.” One clinician found the information on pediatrics especially helpful.
Least useful parts of the tool: Study participants did not have much to say in this category – one person said the “Special Situations” section was not helpful (“just didn't come up”). Another thought that the “Home Action Plan” section was not too useful, though he did admit to making more home action plans now with his asthmatic patients. One physician commented that the tool was “not as useful as [he] expected” in the exam room. He said that it was good for a reference but that he did not use it during patient encounters as much as he had anticipated.
Design problems: Two of the interviewees denied noticing any design problems. Of the remaining five, one thought there were some sections that had a “bit much scrolling”; the others all noted the peak flow calculator problem discussed above.
Suggestions for additions/improvements: Clinicians agreed that adding ICD-9 codes to the tool would help them in their practice (two suggested this on their own, three agreed to the idea when prompted). One particularly technologically ambitious physician suggested going one step further and linking the tool to an electronic medical record (EMR), thus allowing the clinician to directly record what type of visit it is. One clinician suggested adding differential diagnosis information (i.e., a decision tree); another suggested adding color. More/better patient education resources would also be helpful, according to one participant. One would like to see a simplified (tabular) version of the guidelines as the first screen, and another suggested linking the system to drug databases such as ePocrates.
Did the tool change your usual asthma care?: Four clinicians said that the tool increased their understanding of the guidelines/increased their use of the classification system. One said “I am more aggressive, getting more control.” Two clinicians make more action plans now than they used to; one does more peak flow calculations. One said “seeing the algorithm for care” helped her better understand the process, while another liked seeing the “template for treatment.” One physician felt he is now “better at interpreting the pulmonary function test.” One physician said the tool made him “pay more attention to prevention [of exacerbations], [which] might influence outcomes.”
Was the tool more helpful for planned visits or for acute care?: Of the five who answered this question, four said it was more helpful during planned/maintenance visits, while the fifth found it more helpful for acute visits. One remarked that it was helpful with documentation.
Reasons not to use the tool: Two reasons given for not using the tool with every patient with asthma were not enough time during the visit and the participant felt s/he already knew the required information.
PDA use in front of patients: Only one participant did not use her PDA in front of patients; she said she “would feel comfortable [doing so], but [I] just never do it.” Other participants claim to use their PDAs in front of patients on a regular basis (not just with our tool), and have had only positive reactions from patients. Patients that are seen by the clinicians in this study apparently think a clinician using a PDA is “on the ball” or that it “adds validity” to his/her decision(s). One participant claimed that using the tool in the exam room saves time.
Discussion
Guideline based care has been shown to improve outcomes and the low rates of use of proven therapy for asthma reinforces the need for adherence to guidelines.1-6 Moving guidelines into practice can be a slow and often difficult task. Although national evidence based guidelines were published in 1997 and then revised in 2002, fewer than half of asthma patients appear to have care based on those guidelines.7 Primary care physicians have identified several barriers to implementation of the asthma guidelines including competing demands, uncertainty about severity scoring, the complexity of the guidelines, concerns about steroids, and the perception that the guidelines address more complex patients than the practitioner sees.5, 7-10 Indeed, less than 63% of asthma specialists and 46% of primary care physicians could appropriately score severity of asthma in patient vignettes.7 This supports the basic premise that physicians do not have functional systems to support their implementation of the guidelines.11 Unfortunately, many of the published and funded programs designed to improve asthma guideline implementation in primary care are intensive. They require extensive investment of time and personnel and have shown only limited sustainable improvement, in part because they do not have an easily accessible tool for sustained use.12-14 Often these either have short-term effects or are not generalizable to the large majority of primary care physicians.15-18
One of the major barriers with the current guidelines is creating a usable format for the guidelines to be understood. Our participants were more likely to classify patients according to the guidelines using the PDA tool – in fact, 100% were able to correctly name the steps of classification. Moreover, there was a significant increase in their appreciation of the process of classification. Thus, this research has indicated that the PDA tool seems to offer easy to use clinical support that helps address one of the major barriers to successful guideline implementation.7-11
We should note several limitations of this project that were anticipated. First, the project was intended to understand the actual user-friendliness and assistance of this handheld software in circumstances that closely resembled real world settings. Thus, we made a conscious decision not to engage the users on a regular basis or “coach” them to use it regularly. Nonetheless, we retained 70% of our participants and obtained useful information from them. This study was not intended to evaluate actual effect on care, but rather the user-friendliness of a handheld tool and its ability to facilitate incorporation of national guidelines into practice. For these goals, our study indicates a reasonable level of success for the PDA tool. It is notable that few of the current handheld software programs for asthma have had any end-user evaluations done outside of their own marketing departments.
We learned two additional features which practicing clinicians would find helpful in outpatient asthma management tools – coding support and direct links to pharmacology tools.
All the respondents felt that the PDA tool changed their asthma care for the better. It is not surprising that there were a variety of ways in which the tool did so, and that besides the increased understanding and use of the classification system, there were many individual comments in our interviews. We believe that this indicates a strength of the tool, in that it helped physicians’ asthma care in different ways and was diverse in its ability to support the unique needs of clinicians.
Our study found that practicing physicians generally accepted handheld software as a means of delivering guideline-based care to their asthmatic patients. All interviewed physicians found the tool user-friendly and easy to use. They found the tool particularly useful for the classification of asthmatic patients and actually demonstrated an increase in knowledge related to the classification system after use of the tool.
Conclusion
- This pilot research finds evidence on the utility of using the PDA handheld software tool for the translation of asthma guidelines into practice.
- 100% of clinicians who provided follow-up data were able to correctly name the step classification of asthma.
- The participants were significantly more likely to classify patients according to the NHLBI guidelines and place more importance on doing so. Thus, the tool seems to successfully address one of the critical barriers in current asthma care.
- The tool also seems to be helpful in customizing therapy and in patient education.
- Future research should evaluate health outcomes as a result of this improved care and should include sufficient participants to fully evaluate the changes in knowledge, attitudes, behavior, and comfort with guidelines.
We appreciate the support of the MSV Foundation in this project. This project has provided the foundation for a larger proposal to evaluate the use of the tool for patient outcomes in underserved populations. The knowledge we obtained with the MSV Foundation support will be instrumental in assuring that we can provide a tool that is helpful to clinicians in their care of patients with asthma.
References
1. Haahtela T, Jarvinen M, Kava T, Kiviranta K, Koskinen S, Lehtonen K, et al. Effects of reducing or discontinuing inhaled budesonide in patients with mild asthma. N Engl J Med 1994; 331:700-705.
2. Anonymous. Long-term effects of budesonide or nedocromil in children with asthma. The Childhood Asthma Management Program Research Group. N Engl J Med 2000; 343:1054-1063.
3. Hartert TV, Windom HH, Peebles RS, Jr., Freidhoff LR, Togias A. Inadequate outpatient medical therapy for patients with asthma admitted to two urban hospitals. Am J Med 1996; 100:386-394.
4. Lara M, Rosenbaum S, Rachelefsky G, Nicholas W, Morton SC, Emont S, et al. Improving childhood asthma outcomes in the United States: a blueprint for policy action. Pediatrics 2002; 109:919-930.
5. Cabana MD, Rand CS, Becher OJ, Rubin HR. Reasons for pediatrician nonadherence to asthma guidelines. Arch Pediatr Adolesc Med 2001; 155:1057-1062.
6. Diette GB, Skinner EA, Nguyen TT, Markson L, Clark BD, Wu AW. Comparison of quality of care by specialist and generalist physicians as usual source of asthma care for children. Pediatrics 2001; 108:432-437.
7. Doerschug KC, Peterson MW, Dayton CS, Kline JN. Asthma guidelines: an assessment of physician understanding and practice. Am J Respir Crit Care Med 1999; 159:1735-1741.
8. Cabana MD, Rand CS, Powe NR, Wu AW, Wilson MH, Abboud PA, et al. Why don't physicians follow clinical practice guidelines? A framework for improvement. JAMA 1999; 282:1458-1465.
9. Senturia Y, Rosenstreich D, Bauman L. Pediatric primary care for asthma: how does content of the office visit relate to NIH guidelines? Am J Respir Crit Care Med 98 A.D.; 157:A540.
10. Homer CJ. Asthma disease management. N Engl J Med 1997; 337:1461-1463.
11. Davis DA, Taylor-Vaisey A. Translating guidelines into practice. A systematic review of theoretic concepts, practical experience and research evidence in the adoption of clinical practice guidelines. CMAJ Canadian Medical Association Journal 1997; 157:408-416.
12. L'Enfant C. National Asthma Meeting 2003. Available at: http://www.videocast.nih.gov.
13. Elward K. Proceedings of the National Asthma Meeting 2003, Washington, DC. Available at: http://www.videocast.nih.gov.
14. National Initiative for Child Health Quality, Program descriptions. Available at: http://www.nichq.org.
15. Bailey WC, Richards JM, Jr., Brooks CM, Soong SJ, Windsor RA, Manzella BA. A randomized trial to improve self-management practices of adults with asthma. Arch Intern Med 1990; 150:1664-1668.
16. 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; 325:941.
17. TRIPP II. Available at: http://www.ahrq.gov/fund/tripconf.htm.
18. Meurer J. Experience of the Allies for Asthma in Wisconsin. Proceedings of the National Asthma Meeting 2003, Washington, DC. Available at: http://www.asthma2003.net/conf.asp.