Skip Navigation

International Journal for Quality in Health Care 2004 16(5):407-416; doi:10.1093/intqhc/mzh064
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (34)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Delpierre, C.
Right arrow Articles by Lang, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Delpierre, C.
Right arrow Articles by Lang, T.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

International Journal for Quality in Health Care vol. 16 no. 5 © International Society for Quality in Health Care and Oxford University Press 2004; all rights reserved

Review Article

A systematic review of computer-based patient record systems and quality of care: more randomized clinical trials or a broader approach?

Cyrille Delpierre1,2, Lise Cuzin1, Judith Fillaux1, Muriel Alvarez1, Patrice Massip1 and Thierry Lang2

1 Centre Hospitalo Universitaire Purpan, Service des Maladies Infectieuses et Tropicales, Toulouse, 2 INSERM, U558, Épidémiologie et Santé Publique, Toulouse, France

Purpose. To analyse the impact of computer-based patient record systems (CBPRS) on medical practice, quality of care, and user and patient satisfaction.

Data sources. Manual and electronic search of the Medline, Cochrane, and Embase databases.

Study selection. Selected articles were published from 2000 to March 2003. CBPRS was defined as computer software designed to be used by clinicians as a direct aid in clinical decision making. To be included, the systems should have recorded patient characteristics and offered online advice, or information or reminders specific to clinicians during the consultation.

Data extraction. Keywords used for the search were: electronic record, informatic record, electronic medical record, electronic patient record, patient order entry, computer-based patient system, clinical decision support systems, and evaluation.

Results. Twenty-six articles were selected. Use of a CBPRS was perceived favourably by physicians, with studies of satisfaction being mainly positive. A positive impact of CBPRS on preventive care was observed in all three studies where this criterion was examined. The 12 studies evaluating the impact on medical practice and guidelines compliance showed that positive experiences were as frequent as experiences showing no benefit. None of the six studies analysing the impact of CBPRS on patient outcomes reported any benefit.

Conclusions. CBPRS increased user and patient satisfaction, which might lead to significant improvements in medical care practices. However, the studies on the impact of CBPRS on patient outcomes and quality of care were not conclusive. Alternative approaches considering social, cultural, and organizational factors may be needed to evaluate the usefulness of CBPRS.

Keywords: computer-based patient record system, evaluation, medical practice, patient outcomes, quality of care, randomized controlled trials, systematic review

Address reprint requests to C. Delpierre, Centre Hospitalo Universitaire Purpan, Service des Maladies Infectieuses et Tropicales, Toulouse, France. E-mail: cisih{at}chu-toulouse.fr or cyrildelpierre{at}yahoo.fr

Accepted for publication May 25, 2004.

The evolution of medicine during the three past decades is characterized by a paradox. Medical information needed for clinical decision making has increased; however, the organization and accessibility of health data are still poor, resulting in inappropriate decisions and medical errors [1,2]. To increase the accessibility and management of medical information, the use of informatic tools has been promoted [3]. First used for management and administrative purposes, computer-based patient record systems (CBPRS) have been developed to collect and synthesize medical information [2].

Many experiences have been published regarding general practice [4], surgery [5], cardiology [6], psychiatry [7], or HIV infection [8,9] based on electronic medical records. These systems have common characteristics [10,11]. Medical data are conceptually organized as the patient’s paper medical record, and synthesize clinical and therapeutic patient history. CBPRS are designed to be used directly by physicians during consultation and to provide online information and messages to help physicians in their practice.

The aim of CBPRS is to offer support in medical decision making, to increase coordination between different health care providers, and to promote the use of guidelines, thereby improving global quality of care [12,13]. Development of CBPRS in a care unit has even been proposed as a criterion of quality [14,15]. The aim of CBPRS is also: to improve the speed of retrieval of medical records, allowing many persons to have simultaneous access to the same medical record; to improve data confidentiality while tracing who has accessed it; and finally to collect routine data [16–18].

During the past three decades, the introduction and development of CBPRS in the health sector has followed the development of data processing [19]. However, few systems have been evaluated with regard to their impact on clinical performance and patient outcomes [2,20–22]. Results from the few studies that evaluated CBPRS were not concordant. A systematic review that analysed 28 randomized controlled trials (RCTs) from 1983 to 1992 concluded that compliance with guidelines increased; however, patient outcomes were unchanged [20]. Another systematic review, which analysed 25 studies from 1992 to 1998, confirmed the positive effect of these tools’ compliance with guidelines, but was inconclusive on patient outcomes and quality of care due to lack of data [13]. The last systematic review, which analysed studies until 1999, confirmed these results and concluded that new approaches were needed to evaluate the impact of these tools on medical practice and quality of care [23]. Several studies since then have tried to fill this gap. Our objective was to carry out a systematic review of studies analysing the impact of CBPRS on medical practice, quality of care, and user and patient satisfaction, using papers published since 2000.

Methods

Study selection
Studies published between January 2000 and March 2003 were identified by searching the US National library of Medicine Medline electronic bibliographic database, and the electronic Cochrane and Embase databases. A manual search of studies most frequently cited in automatically selected studies was also performed. The keywords used for the search were electronic record, informatic record, electronic medical record, electronic patient record, patient order entry, computer-based patient system, clinical decision support systems, and evaluation.

To be selected, studies had to pertain to an evaluation of the impact of CBPRS on medical practice and/or quality of care and/or user satisfaction and/or patient satisfaction.

CBPRS was defined as follows: ‘computer software designed to be used by a clinician involved in patient care as a direct aid to clinical decision making. Patient data were recorded into the system. Patient-specific information in the form of assessments or recommendations, or alerts or reminders was presented to the clinician during the consultation’.

Descriptive studies and analyses concerning the quality of CBPRS, such as accuracy or completeness of data, were not included. No criteria with respect to trial methodology were defined.

Results

Thirty-nine articles were identified at the end of this process. After careful analysis, 13 of them were excluded: eight did not evaluate the impact of CBPRS on clinician performance and five did not meet the criteria for the definition of a CBPRS. Eventually, 26 articles were selected, corresponding to 25 studies. One of them was published in two papers [24,25]. Selected studies are presented in Tables 1–GoGo4.


View this table:
[in this window]
[in a new window]
  		Table 1 Randomized controlled trials studies

 

View this table:
[in this window]
[in a new window]
  		Table 2 Before–after studies

 

View this table:
[in this window]
[in a new window]
  		Table 3 Cross-sectional studies

 

View this table:
[in this window]
[in a new window]
  		Table 4 Qualitative studies

 

Study designs
Several study designs were used: 10 were RCTs [24–32], 11 were before–after studies [33–43], three were cross-sectional studies [44–46], and two were based on qualitative interviews [10,47].

Criteria of judgment
Sixteen studies attempted to assess the process of care. Five studies used patient outcomes as a criterion of judgment. Fifteen studies used satisfaction among users and/or patients as the endpoint.

Process of care
Length of the consultation. Six studies analysed the impact of CBPRS on the length of the consultation [31,33,37,39,41,45]. An increase in this length was observed in three studies [31,33,45]. This increase was found to range between 2.2 and 9.3 minutes per patient [31,33]. Makoul et al. [45] found discordant results according to the variety of consultation. Initial visits had a mean length of 35 minutes when using CBPRS compared with 25 minutes without (P < 0.05). No difference was observed during subsequent visits. The length of the consultation was found to be reduced in one study [41] and unchanged in another study [37].

Content of the consultation. Three studies analysed the impact of CBPRS on the content of the consultation [31,33,45]. Some variables, such as questions regarding mental health or behaviour such as tobacco consumption were more frequently recorded as items of the CBPRS than when these tools were not used [33,45]. Clinicians were significantly more likely to address routine health care maintenance topics, including psychosocial issues [relative risk (RR) = 1.4] and smoking at home (RR = 15.6) in a paediatric primary care practice using CBPRS than in one using paper records [33].

Clinical performance
Twelve studies analysed modification of medical practice [25–30,33–36,40,48]. Three studies analysed the impact of CBPRS on preventive care [26,28,33], and an improvement was observed in all of them. Dexter et al. [26] analysed pneumococcal and influenza vaccination, and prophylactic heparin and aspirin use. An increase was observed in vaccination rates from 0.8% to 35.8% for pneumococcal vaccination, and from 1% to 51.4% for influenza vaccination. Likewise, prophylactic heparin and aspirin prescription at discharge increased from 18.9% to 32.2%, and from 27.6% to 36.4%, respectively.

Eight studies analysed compliance with guidelines [25, 27–29,35,36,48]. An increase in the application of guidelines was observed in three studies of the management of breast cancer, venous thromboembolism, and blood test ordering [35,36, 48]. This increase was 14% (85% versus 62%, respectively; P < 10–4) with respect to breast cancer guidelines and 12% (95% versus 83%, respectively; P < 0.001) with respect to venous thromboembolism guidelines [35,36]. In a study of blood test ordering, general practitioners who used CBPRS requested 20% fewer blood tests [48]. Results regarding the management of acute respiratory distress syndrome showed that 95% of computer-generated instructions were followed [29]. However, compliance with guidelines on the management of asthma, angina, diabetes mellitus, and major depression was not found to increase [25,27,28].

Nine studies analysed the impact of CBPRS on treatment prescriptions [25,27,30,34–36,40,43,48]. Prescription rates concordant with recommendations increased by 31% for chemotherapy prescriptions and by 61% for prescriptions for venous thromboembolism. Accordingly, the error rate decreased [35,36]. Improvements in appropriateness for prescription of drugs with CBPRS was reported in one study [43]. No significant evolution could be observed in the remaining five studies [25,27,30,34,40].

Patient outcomes
Five studies used patient outcomes as a criterion of judgment [25,27–30]. The results were not improved for cardiovascular risk [28,30], survival, length of hospitalization, or acute respiratory distress syndrome [29]. However a significant decrease of 2.3 mmHg diastolic pressure was observed in one study [28]. In two studies, outcomes were assessed by the patients. No benefit with respect to the management of asthma and angina, or major depression was observed [25,27].

User and patient satisfaction
Physician satisfaction. Thirteen studies analysed physician perception for CBPRS use [10,28,31–33,37–41,44–46]. Physician satisfaction with the system was reported in nine studies [10,31,33,39–41,44–46]. The positive points reported were improved knowledge of patients’ medical history, better medical examination, and improvement in quality of care. In four studies, physicians were asked if they wanted to continue working with CBPRS: all studies reported positive responses [31,39,40,46]. Nevertheless, four studies raised some points of dissatisfaction [28,32,37,38]. CBPRS was perceived as a physical barrier [33,37,38,45] that could have a negative impact on the patient–physician relationship [37,38,46], particularly by reducing eye-to-eye contact [33]. Concerns were expressed about data confidentiality [37–39], personal and professional privacy, bug management [32,38,44], and the additional work for physicians [28,31,32]. Factors influencing perception of the system were its characteristics, such as its interface and ease of use, as well as users’ characteristics. Perception of CBPRS was better for community-based physicians than for academic-based physicians. Physicians accustomed to working with a computer had a better perception of CBPRS [46].

Nurse satisfaction. Three studies analysed nurse satisfaction with the introduction of CBPRS in their practice [32,40,47]. A global increase in satisfaction was observed in two studies [32,40]. In another study, reduced administrative work and increased accessibility to care protocols, especially for young nurses, were reported. Negative points were the lack of flexibility of these tools, the loss of nurses’ judgment, and the additional workload [47]. Nevertheless, nurses stated their desire to continue working with an informatic system in all three studies.

Patient satisfaction. Two studies analysed patient satisfaction [37,49], and patients were found to have a positive opinion of CBPRS in both. A mean score of 4.6 on a general satisfaction scale of 0–5 was reported [37]. Patients did not report a reduction in eye-to-eye contact with the use of CBPRS, and found medical visits more effective. However, fear concerning data confidentiality was observed in both studies.

Discussion

Use of a CBPRS seems to be perceived favorably by physicians, with user satisfaction being mainly positive despite some limits and concerns regarding its use [31,39,40,46]. The main constraints reported were the physical barrier and the impact on the patient–physician relationship that could result from the use of CBPRS during the consultation. Technical characteristics of the system and knowledge of data processing by physicians were criteria related to satisfaction with, and thus implementation of, CBPRS [50]. Future research is needed considering qualitative factors that could influence the use of CBPRS [7,51].

Physicians wanted to continue working with CBPRS once such tools were in place in their wards [31,39,40,46], as once exposed, physicians felt a need for an information system. To improve the quality of CBPRS it is essential that the quality of data collected is certified and controlled [52]. Furthermore, to prepare for technical problems with the computer it is advisable always to keep a paper print-out of patient records [53].

Only two studies analysed patient satisfaction. Generally, patients were satisfied and did not complain about changes to their relationship with their physicians [37]. Their greatest fear concerned data confidentiality. It is therefore essential to reassure patients about the confidentiality of their data. Physicians must be able to explain how data confidentiality can be maintained with the system they use. Additional patient-focused studies are thus necessary to explore their feelings about the use of CBPRS in consultation rooms and its consequences with respect to the patient–physician relationship.

The impact of CBPRS on medical practice was more balanced. A clear positive impact of CBPRS on preventive care was noted. This finding is consistent with other systematic reviews [13,20,54]. Improvements in medical practice and the adoption of guidelines was less certain. Positive experiences were as frequent as experiences showing no benefit. In studies of arterial hypertension and major depression [25,30,55–58], there was no improvement in medical practice and compliance with guidelines. The recent systematic review of Kaushal et al. showed that CBPRS could decrease prescription error, although most studies were inconclusive [59]. Possible reasons for these inconclusive findings were underuse of the tool, inadequate study design, and lack of study power [28].

Only six studies analysed the impact of the use of CBPRS on patient outcomes and did not show any benefit of CBPRS. In a systematic review [13], 25 RCTs evaluating the contribution of CBPRS to medical practice were analysed. Only eight of these studies used patient outcomes as a criterion of judgment. The relationship between the process of care and health outcomes might explain why improved outcomes are difficult to relate to the implementation of CBPRS [60].

Users of CBPRS acknowledge the usefulness of such tools, whereas the results of clinical performance or patient outcomes are not always conclusive. This paradox draws the attention to the criteria and methodologies used in various studies. RCTs are usually considered the methodological reference [61]. However, this methodological approach has several limits in evaluating the impact of CBPRS on medical practice. In order to organize RCTs and select a criterion of judgment, tracers have to be chosen within complex and multifactorial diseases (e.g. hypertension, depression). Moreover, even if positive results are found in some narrow clinical fields, generalization to the more complex clinical situations is generally difficult [62]. Controlled conditions required by RCTs do not reflect the diversity of medical practices and working conditions. Due to these limitations, RCTs do not offer a sound enough methodology to evaluate the contribution of CBPRS in medical practice, and its impact on clinical performance and patient outcomes [61,63,64].

Two systematic reviews [23,65] describing methodological approaches to the evaluation of systems designed to improve medical decision making emphasized the lack of diversity in the design of studies that evaluate these tools. This phenomenon could lead to lack of conclusive results. Alternatives approaches centered on social, cultural, and organizational factors are thus advocated. Structure of care (general practice, hospital), organization of the ward, and the relationships between various health professionals seem to be key factors to consider when evaluating the impact of CBPRS on medical practice [65].

It is recognized that systematic review may be subject to a possible selection bias. Studies presenting negative findings are indeed published less often [13]. Nevertheless, a high proportion of articles showing no effect of CBPRS on quality of care were found [25,27,28]. A wide range of keywords to find systems with the same characteristics had to be used. A well defined operating definition of CBPRS, sharing the same characteristics, could facilitate future research and produce more exhaustivity [66].

Conclusion

This systematic review, based on 25 papers published between 2000 and 2003, has contributed to a better understanding of the relationship between the use of CBPRS and medical practice. Increased satisfaction of users and patients was noted, which could lead to significant changes in medical practice. However, as in previous reviews, the impact of CBPRS on medical practice and quality of care was not well demonstrated. It is noteworthy that most of the studies did not include qualitative factors such as characteristics of the disease and the tool, the ward in which it is developed, and the relationship between various health care professionals, which can impact upon the use of CBPRS.

A broad review including all the factors that could influence the success or failure of the use of CBPRS in medical practice is indicated in the future.

References

  1. TRW uses AI tools to control system problems. Aviat Week Space Technol 1986: 79–81.

  2. Tierney W. Improving clinical decisions and outcomes with information: a review. Int J Med Informat 2001; 62: 1–9.

  3. Bleich H, Beckley R, Horowitz G et al. Clinical computing in a teaching hospital. N Engl J Med 1985; 312: 756–764.[Abstract]

  4. Walton R, Gierl C, Yudkin P et al. Evaluation of computer support for prescribing (CAPSULE) using simulated cases. Br Med J 1997; 315: 791–795.[Abstract/Free Full Text]

  5. Castelden W, Lawrence-Brown M, Lam H, McLoughlin B, Thompson D, Lopez J. The hollywood surgical-audit programme: a computer-based discharge and data-collection system for surgical audit. Med J Aust 1988; 149: 70–74.[Web of Science][Medline]

  6. Rossi R, Every N. A computerised intervention to decrease the use of calcium channel blockers in hypertension. J Gen Intern Med 1997; 12: 672–678.[CrossRef][Web of Science][Medline]

  7. Lee F, Teich J, Spurr C, Bates D. Implementation of physician order entry: user satisfaction and self-reported usage patterns. J Am Med Inform Assoc 1996; 3: 42–55.[Abstract/Free Full Text]

  8. Pugliese P, Cuzin L, Enel P et al. Nadis 2000, développement d’un dossier médical informatisé pour les patients infectés par VIH, VHB et VHC. Presse Med 2003; 32: 299–303.[Web of Science][Medline]

  9. Safran C, Rind D, Davis R et al. Guidelines for management of HIV infection with computer-based patient’s record. Lancet 1995; 346: 341–346.[CrossRef][Web of Science][Medline]

  10. Matsumura Y, Kuwata S, Kusuoka H et al. Dynamic viewer of medical events in electronic medical record. Medinfo 2001; 10: 648–652.[Medline]

  11. Sujansky W. The benefits and challenges of an electronic medical record: much more than a ‘word-processed’ patient chart. West J Med 1998; 169: 176–183.[Web of Science][Medline]

  12. Pringle M. Using computers to take patient histories. Br Med J 1988; 297: 697–698.[Free Full Text]

  13. Shiffman R, Liaw Y, Brandt C, Corb G. Computer-based guideline implementation systems: a systematic review of functionality and effectiveness. J Am Med Inform Assoc 1999; 6: 104–114.[Abstract/Free Full Text]

  14. Safran C. Electronic medical record: a decade of experience. J Am Med Assoc 2001; 285: 1766.[Free Full Text]

  15. Tsai C, Starren J. Patient participation in electronic medical records. J Am Med Assoc 2001; 285: 1765.[Free Full Text]

  16. Barrows R, Clayton P. Privacy, confidentiality, and electronic medical records. J Am Med Inform Assoc 1996; 3: 139–148.[Abstract/Free Full Text]

  17. Gillies J, Holt A. Anxious about electronic health records? No need to be. NZ Med J 2003; 116: U604.

  18. Rind D, Kohane I, Szolovits P, Safran C, Chueh H, Barnett G. Maintaining the confidentiality of medical records shared over the Internet and the World Wide Web. Ann Intern Med 1997; 127: 138–141.[Abstract/Free Full Text]

  19. Benson T. Why general practitioners use computers and hospital doctors do not. Br Med J 2002; 325: 1090–1093.[Free Full Text]

  20. Johnston M, Langton K, Haynes R, Mathieu A. Effects of computer-based clinical decision support systems on clinician performance and patient outcome: a critical appraisal of research. Ann Intern Med 1994; 120: 135–142.[Abstract/Free Full Text]

  21. Wyatt J, Spiegelhalter D. Evaluating medical expert systems: what to test and how? Med Inform 1990; 15: 205–217.

  22. Sim I, Gorman P, Greenes R et al. Clinical decision support systems for the practice of evidence-based medicine. J Am Med Assoc 2001; 8: 527–534.

  23. Kaplan B. Evaluating informatics applications—clinical decision support systems literature review. Int J Med Inform 2001; 64: 15–37.[CrossRef][Web of Science][Medline]

  24. Rollman B, Hanusa B, Gilbert T, Lowe H, Kapoor W, Schulberg H. The electronic medical record. A randomized trial of its impact on primary care physicians’ initial management of major depression. Arch Intern Med 2001; 161: 189–197.[Abstract/Free Full Text]

  25. Rollman B, Hanusa B, Lowe H, Gilbert T, Kapoor W, Schulberg H. A randomized trial using computerized decision support to improve treatment of major depression in primary care. J Gen Intern Med 2002; 17: 493–503.[CrossRef][Web of Science][Medline]

  26. Dexter P, Perkins S, Overhage J, Maharry K, Kohler R, McDonald C. A computerized reminder system to increase the use of preventive care for hospitalized patients. N Engl J Med 2001; 345: 965–970.[Abstract/Free Full Text]

  27. Eccles M, McColl E, Steen N et al. Effect of computerised evidence based guidelines on management of asthma and angina in adults in primary care: cluster randomised controlled trial. Br Med J 2002; 325: 941.[Abstract/Free Full Text]

  28. Hetlevik I, Holmen J, Kruger O, Kristensen P, Iversen H, Furuseth K. Implementing clinical guidelines in the treatment of diabetes mellitus in general practice. Evaluation of effort, process, and patient outcome related to implementation of a computerized based decision support system. Int J Technol Assess Health Care 2000; 16: 210–227.[CrossRef][Web of Science][Medline]

  29. McKinley B, Moore F, Sailors R et al. Computerized decision support for mechanical ventilation of trauma induced ARDS: results of a randomized clinical trial. J Trauma 2001; 50: 415–424.[Web of Science][Medline]

  30. Montgomery A, Fahey T, Peters T, MacIntosh C, Sharp D. Evaluation of computer based clinical decision support system and risk chart for management of hypertension in primary care: randomised controlled trial. Br Med J 2000; 320: 686–690.[Abstract/Free Full Text]

  31. Overhage J, Perkins S, Tierney W, McDonald C. Contolled trial of direct physician order entry: effects on physicians’ time utilization in ambulatory primary care internal medicine practices. J Am Med Inform Assoc 2001; 8: 361–371.[Abstract/Free Full Text]

  32. Rousseau N, McColl E, Newton J, Grimshaw J, Eccles M. Practice based, longitudinal, qualitative interview study of computerised evidence based guidelines in primary care. Br Med J 2003; 326: 314–322.

  33. Adams W, Mann A, Bauchner H. Use of an electronical medical record improves quality of urban pediatric primary care. Pediatrics 2003; 111: 626–632.[Abstract/Free Full Text]

  34. Bansal P, Aronsky D, Talbert D, Miller R. A computer based intervention on the appropriate use of arterial blood gas. Proc AMIA Symp 2001: 32–36.

  35. Bouaud J, Seroussi B, Antoine E, Zelek L, Spielmann M. A before after study using OncoDoc, a guideline based decision support system on breast cancer management: impact upon physician prescribing behaviour. Medinfo 2001; 10: 420–424.[Medline]

  36. Durieux P, Nizard R, Ravaud P, Mounier N, Lepage E. A clinical decision support system for prevention of venous thromboembolism: effect on physician behaviour. J Am Med Assoc 2000; 283: 2816–2821.[Abstract/Free Full Text]

  37. Gadd C, Penrod L. Dichotomy between physicians’ and patients’ attitudes regarding EMR use during outpatient encounters. Proc AMIA Symp 2001: 275–279.

  38. Gadd C, Penrod L. Assessing physician attitudes regarding use of an outpatient EMR: a longitudinal, multi-practice study. Proc AMIA Symp 2001: 194–198.

  39. Mikulich V, Yi-Ching A, Steinfeldt J, Schriger D. Implementation of clinical guidelines through an electronic medical record: physician usage, satisfaction and assessment. Int J Med Informat 2001; 63: 169–178.[CrossRef]

  40. Rocha B, Christenson J, Evans R, Gardner R. Clinicians’ response to computerized detection of infections. J Am Med Inform Assoc 2001; 8: 117–125.[Abstract/Free Full Text]

  41. Rodriguez N, Murillo V, Borges J, Ortiz J, Sands D. A usability study of physicians interaction with a paper-based patient record system and a graphical-based electronic patient record system. Proc AMIA Symp 2002: 667–671.

  42. Sanders D, Miller R. The effects on clinician ordering patterns of a computerized decision support system for neuroradiology imaging studies. Proc AMIA Symp 2001: 583–587.

  43. Teich J, Merchia P, Schmiz J, Kuperman G, Spurr C, Bates D. Effects of computerized physician order entry on prescribing practices. Arch Intern Med 2000; 160: 2741–2747.[Abstract/Free Full Text]

  44. Laerum H, Ellingsen G, Faxvaag A. Doctor’s use of electronic medical records systems in hospitals: cross sectional survey. Br Med J 2001; 323: 1344–1348.[Abstract/Free Full Text]

  45. Makoul G, Curry R, Tang P. The use of electronic medical records: communication patterns in outpatient encounters. J Am Med Inform Assoc 2001; 8: 610–615.[Abstract/Free Full Text]

  46. Penrod L, Gadd C. Attitudes of academic-based and community-based physicians regarding EMR use during outpatient encounters. Proc AMIA Symp 2001: 528–532.

  47. Lee T, Yeh C, Ho L. Application of a computerized nursing care plan system in one hospital: experience of ICU nurses in Taiwan. J Adv Nurs 2002; 39: 61–67.[CrossRef][Web of Science][Medline]

  48. Van Wijk M, Van der Lei J, Mosseveld M, Bohnen A, Van Bemmel J. Assessment of decision support for blood test ordering in primary care: a randomized trial. Ann Intern Med 2001; 134: 274–281.[Abstract/Free Full Text]

  49. Goldberg H, Morales A, Gottlieb L, Meador L, Safran C. Reinventing patient-centered computing for the twenty-first century. Medinfo 2001; 10: 1455–1458.[Medline]

  50. Murff H, Kannry J. Physician satisfaction with two order entry systems. J Am Med Inform Assoc 2001; 8: 499–509.[Free Full Text]

  51. Loomis G, Ries J, Saywell RJ, Thakker N. If electronical medical records are so great, why aren’t family physicians using them? J Fam Pract 2002; 51: 636–641.[Web of Science][Medline]

  52. Thiru K, Hassey A, Sullivan F. Systematic review of scope and quality of electronic patient record data in primary care. Br Med J 2003; 326: 1070.[Abstract/Free Full Text]

  53. Kilbridge P. Computer crash—lessons from a system failure. N Engl J Med 2003; 348: 881–882.[Free Full Text]

  54. Sullivan F, Mitchell E. Has general practitioner computing made a difference to patient care? A systematic review of published reports. Br Med J 1995; 311: 848–852.[Abstract/Free Full Text]

  55. Hunt D, Haynes S, Hanna S, Smith K. Effects of a computer-based clinical decision support systems on physician performance and patients outcomes: a systematic review. J Am Med Assoc 1998; 280: 1339–1346.[Abstract/Free Full Text]

  56. Magruder-Habib K, Zung W, Feussner J. Improving physicians’ recognition and treatment of depression in general medical care. Results from a randomized clinical trial. Med Care 1990; 28: 239–250.[CrossRef][Web of Science][Medline]

  57. Montgomery A, Fahey T. A systematic review of the use of computers in the management of hypertension. J Epidemiol Commun Health 1998; 52: 520–525.[Abstract]

  58. Shapiro S, German P, Skinner E. An experiment to change detection and management of mental morbidity in primary care. Med Care 1987; 25: 327–339.[CrossRef][Web of Science][Medline]

  59. Kaushal R, Shojania K, Bates D. Effects of computerized physician order entry and clinical decision support systems on medication safety. Arch Intern Med 2003; 163: 1409–1416.[Abstract/Free Full Text]

  60. Mant J, Hicks N. Detecting differences in quality of care: the sensitivity of measures of process and outcome in treating acute myocardial infarction. Br Med J 1995; 311: 793–796.[Free Full Text]

  61. Heathfield H, Pitty D, Hanka R. Evaluating information technology in health care: barrriers and challenges. Br Med J 1998; 316: 1959–1961.[Free Full Text]

  62. Rotman B, Sullivan A, McDonald T et al. A randomized controlled trial of a computer-based physician workstation in an outpatient setting: implementation barriers to outcome evaluation. J Am Med Inform Assoc 1996; 3: 340–348.[Abstract/Free Full Text]

  63. Forsythe D, Buchanan B. Broadening our approach to evaluating medical information systems. Proc Annu Symp Comput Appl Med Care 1991: 8–12.

  64. Mongerson P. Patient’s perspective of medical informatics. J Am Med Inform Assoc 1995; 2: 79–84.[Abstract/Free Full Text]

  65. Kaplan B. Evaluating informatics applications—some alternative approaches: theory, social interactionism, and call for methodological pluralism. Int J Med Inform 2000; 64: 39–56.

  66. Hogan W, Wagner M. Accuracy of data in computer-based patient records. J Am Med Inform Assoc 1997; 4: 342–355.[Abstract/Free Full Text]


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 J Am Board Fam MedHome page
J. S. Irani, J. L. Middleton, R. Marfatia, E. T. Omana, and F. D'Amico
The Use of Electronic Health Records in the Exam Room and Patient Satisfaction: A Systematic Review
J Am Board Fam Med, September 1, 2009; 22(5): 553 - 562.
[Abstract] [Full Text] [PDF]

Home page
 J Am Med Inform AssocHome page
J. Hu, H. Yu, E. Luo, E. Song, X. Xu, H. Tan, and Y. Wang
Are Chinese Dentists Ready for the Computerization of Dentistry? A Population Investigation of China's Metropolises
JAMIA, May 1, 2009; 16(3): 409 - 412.
[Abstract] [Full Text] [PDF]

Home page
 J Am Med Inform AssocHome page
K. Zheng, R. Padman, M. P Johnson, and H. S Diamond
An Interface-driven Analysis of User Interactions with an Electronic Health Records System
JAMIA, March 1, 2009; 16(2): 228 - 237.
[Abstract] [Full Text] [PDF]

Home page
 PediatricsHome page
S. A. Spooner and D. C. Classen
Data Standards and Improvement of Quality and Safety in Child Health Care
Pediatrics, January 1, 2009; 123(Supplement_2): S74 - S79.
[Abstract] [Full Text] [PDF]

Home page
 J Am Med Inform AssocHome page
I. Shcherbatykh, A. Holbrook, L. Thabane, L. Dolovich, and COMPETE III investigators
Methodologic Issues in Health Informatics Trials: The Complexities of Complex Interventions
JAMIA, September 1, 2008; 15(5): 575 - 580.
[Abstract] [Full Text] [PDF]

Home page
 J Am Med Inform AssocHome page
H. G Lo, L. P Newmark, C. Yoon, L. A Volk, V. L Carlson, A. F Kittler, M. Lippincott, T. Wang, and D. W Bates
Electronic Health Records in Specialty Care: A Time-Motion Study
JAMIA, September 1, 2007; 14(5): 609 - 615.
[Abstract] [Full Text] [PDF]

Home page
 Ann Fam MedHome page
J. C. Crosson, P. A. Ohman-Strickland, K. A. Hahn, B. DiCicco-Bloom, E. Shaw, A. J. Orzano, and B. F. Crabtree
Electronic Medical Records and Diabetes Quality of Care: Results From a Sample of Family Medicine Practices
Ann. Fam. Med, May 1, 2007; 5(3): 209 - 215.
[Abstract] [Full Text] [PDF]

Home page
 Health Aff (Millwood)Home page
L. G. Pawlson
Health Information Technology: Does It Facilitate Or Hinder Rapid Learning?
Health Aff., March 1, 2007; 26(2): w178 - w180.
[Abstract] [Full Text] [PDF]

Home page
 JAMAHome page
S. Kripalani, F. LeFevre, C. O. Phillips, M. V. Williams, P. Basaviah, and D. W. Baker
Deficits in Communication and Information Transfer Between Hospital-Based and Primary Care Physicians: Implications for Patient Safety and Continuity of Care
JAMA, February 28, 2007; 297(8): 831 - 841.
[Abstract] [Full Text] [PDF]

Home page
 J Am Med Inform AssocHome page
C. P Schade, F. M Sullivan, S. de Lusignan, and J. Madeley
e-Prescribing, Efficiency, Quality: Lessons from the Computerization of UK Family Practice
JAMIA, September 1, 2006; 13(5): 470 - 475.
[Abstract] [Full Text] [PDF]

Home page
 J Am Med Inform AssocHome page
T. K. Schleyer, T. P Thyvalikakath, H. Spallek, M. H Torres-Urquidy, P. Hernandez, and J. Yuhaniak
Clinical Computing in General Dentistry
JAMIA, May 1, 2006; 13(3): 344 - 352.
[Abstract] [Full Text] [PDF]

Home page
 J Am Med Inform AssocHome page
J. Hsu
Reply to "Health Information Technology and Physician-Patient Interactions: Impact of Computers on Communication During Outpatient Primary Care Visits"
JAMIA, March 1, 2006; 13(2): 237 - 237.
[Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (34)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Delpierre, C.
Right arrow Articles by Lang, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Delpierre, C.
Right arrow Articles by Lang, T.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?