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Use of an Interactive, Telephone-based Self-management Support Program to Identify Adverse Events Among Ambulatory Diabetes Patients

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Abstract

BACKGROUND

There is growing interest in the use of interactive telephone technology to support chronic disease management. We used the implementation of an automated telephone self-management support program for diabetes patients as an opportunity to monitor patient safety.

METHODS

We identified adverse and potential adverse events among a diverse group of diabetes patients who participated in an automated telephone health-IT self-management program via weekly interactions augmented by targeted nurse follow-up. We defined an adverse event (AE) as an injury that results from either medical management or patient self-management, and a potential adverse event (PotAE) as an unsafe state likely to lead to an event if it persists without intervention. We distinguished between incident, or new, and prevalent, or ongoing, events. We conducted a medical record review and present summary results for event characteristics including detection trigger, preventability, potential for amelioration, and primary care provider awareness.

RESULTS

Among the 111 patients, we identified 111 AEs and 153 PotAEs. Eleven percent of completed calls detected an event. Events were most frequently detected through health IT–facilitated triggers (158, 59%), followed by nurse elicitation (80, 30%), and patient callback requests (28, 11%). We detected more prevalent (68%) than incident (32%) events. The majority of events (93%) were categorized as preventable or ameliorable. Primary care providers were aware of only 13% of incident and 60% of prevalent events.

CONCLUSIONS

Surveillance via a telephone-based, health IT–facilitated self-management support program can detect AEs and PotAEs. Events detected were frequently unknown to primary providers, and the majority were preventable or ameliorable, suggesting that this between-visit surveillance, with appropriate system-level intervention, can improve patient safety for chronic disease patients.

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References

  1. Hofer TP, Zemencuk JK, Hayward RA. When there is too much to do: how practicing physicians prioritize among recommended interventions. J Gen Intern Med. 2004;19(6):646–53.

    Article  PubMed  Google Scholar 

  2. Tierney WM. Adverse outpatient drug events—a problem and an opportunity. N Engl J Med. 2003;348(16):1587–9.

    Article  PubMed  Google Scholar 

  3. Wachter RM. Is ambulatory patient safety just like hospital safety, only without the “stat”? Ann Intern Med. 2006;145(7):547–9.

    PubMed  Google Scholar 

  4. Hammons T, Piland NF, Small SD, Hatlie MJ, Burstin HR. Ambulatory patient safety. What we know and need to know. J Ambul Care Manage. 2003;26(1):63–82.

    PubMed  Google Scholar 

  5. Wachter R. Understanding Patient Safety. New York, NY: McGraw Hill; 2007.

    Google Scholar 

  6. Gandhi TK, Weingart SN, Borus J, et al. Adverse drug events in ambulatory care. N Engl J Med. 2003;348(16):1556–64.

    Article  PubMed  Google Scholar 

  7. Gurwitz JH, Field TS, Harrold LR, et al. Incidence and preventability of adverse drug events among older persons in the ambulatory setting. JAMA. 2003;289(9):1107–16.

    Article  PubMed  Google Scholar 

  8. Gandhi TK, Burstin HR, Cook EF, et al. Drug complications in outpatients. J Gen Intern Med. 2000;15(3):149–54.

    Article  PubMed  CAS  Google Scholar 

  9. Elder NC, Dovey SM. Classification of medical errors and preventable adverse events in primary care: a synthesis of the literature. J Fam Pract. 2002;51(11):927–32.

    PubMed  Google Scholar 

  10. Fernald DH, Pace WD, Harris DM, West DR, Main DS, Westfall JM. Event reporting to a primary care patient safety reporting system: a report from the ASIPS collaborative. Ann Fam Med. 2004;2(4):327–32.

    Article  PubMed  Google Scholar 

  11. Rosser W, Dovey S, Bordman R, White D, Crighton E, Drummond N. Medical errors in primary care: results of an international study of family practice. Can Fam Physician. 2005;51:386–7.

    PubMed  Google Scholar 

  12. Gandhi TK, Kachalia A, Thomas EJ, et al. Missed and delayed diagnoses in the ambulatory setting: a study of closed malpractice claims. Ann Intern Med. 2006;145(7):488–96.

    PubMed  Google Scholar 

  13. Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med. 2003;138(3):161–7.

    PubMed  Google Scholar 

  14. Budnitz DS, Pollock DA, Weidenbach KN, Mendelsohn AB, Schroeder TJ, Annest JL. National surveillance of emergency department visits for outpatient adverse drug events. JAMA. 2006;296(15):1858–66.

    Article  PubMed  CAS  Google Scholar 

  15. Cullen DJ, Bates DW, Small SD, Cooper JB, Nemeskal AR, Leape LL. The incident reporting system does not detect adverse drug events: a problem for quality improvement. Jt Comm J Qual Improv. 1995;21(10):541–8.

    PubMed  CAS  Google Scholar 

  16. O’Neil AC, Petersen LA, Cook EF, Bates DW, Lee TH, Brennan TA. Physician reporting compared with medical-record review to identify adverse medical events. Ann Intern Med. 1993;119(5):370–6.

    PubMed  CAS  Google Scholar 

  17. Schmidek JM, Weeks WB. Relationship between tort claims and patient incident reports in the Veterans Health Administration. Qual Saf Health Care. 2005;14(2):117–22.

    Article  PubMed  CAS  Google Scholar 

  18. Sari AB, Sheldon TA, Cracknell A, Turnbull A. Sensitivity of routine system for reporting patient safety incidents in an NHS hospital: retrospective patient case note review. BMJ. 2007;334(7584):79.

    Article  PubMed  Google Scholar 

  19. Phillips R, Dovey S, Graham D, Elder N, Hickner J. Learning from different lenses: reports of medical errors in primary care by clinicians, staff, and patients. J Patient Saf. 2006;2:140–6.

    Article  Google Scholar 

  20. Doolan DF, Bates DW, James BC. The use of computers for clinical care: a case series of advanced U.S. sites. J Am Med Inform Assoc. 2003;10(1):94–107.

    Article  PubMed  Google Scholar 

  21. Shojania KG, Duncan BW, McDonald KM, Wachter RM, Markowitz AJ. Making health care safer: a critical analysis of patient safety practices. Evid Rep Technol Assess (Summ). 2001(43):i–x, 1–668.

  22. Classen DC, Pestotnik SL, Evans RS, Burke JP. Computerized surveillance of adverse drug events in hospital patients. JAMA. 1991;266(20):2847–51.

    Article  PubMed  CAS  Google Scholar 

  23. Field TS, Gurwitz JH, Harrold LR, et al. Strategies for detecting adverse drug events among older persons in the ambulatory setting. J Am Med Inform Assoc. 2004;11(6):492–8.

    Article  PubMed  Google Scholar 

  24. Gandhi TK, Weingart SN, Seger AC, et al. Outpatient prescribing errors and the impact of computerized prescribing. J Gen Intern Med. 2005;20(9):837–41.

    Article  PubMed  Google Scholar 

  25. Rozich JD, Haraden CR, Resar RK. Adverse drug event trigger tool: a practical methodology for measuring medication related harm. Qual Saf Health Care. 2003;12(3):194–200.

    Article  PubMed  CAS  Google Scholar 

  26. Savage SW, Schneider PJ, Pedersen CA. Utility of an online medication-error-reporting system. Am J Health Syst Pharm. 2005;62(21):2265–70.

    Article  PubMed  Google Scholar 

  27. Smith DH, Perrin N, Feldstein A, et al. The impact of prescribing safety alerts for elderly persons in an electronic medical record: an interrupted time series evaluation. Arch Intern Med. 2006;166(10):1098–104.

    Article  PubMed  Google Scholar 

  28. Gao H, McDonnell A, Harrison DA, et al. Systematic review and evaluation of physiological track and trigger warning systems for identifying at-risk patients on the ward. Intensive Care Med. 2007;33(4):667–79.

    Article  PubMed  Google Scholar 

  29. van der Sijs H, Aarts J, Vulto A, Berg M. Overriding of drug safety alerts in computerized physician order entry. J Am Med Inform Assoc. 2006;13(2):138–47.

    Article  PubMed  Google Scholar 

  30. Garg AX, Adhikari NK, McDonald H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005;293(10):1223–38.

    Article  PubMed  CAS  Google Scholar 

  31. Hillman K, Chen J, Cretikos M, et al. Introduction of the medical emergency team (MET) system: a cluster-randomised controlled trial. Lancet. 2005;365(9477):2091–7.

    Article  PubMed  Google Scholar 

  32. Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. JAMA. 1998;280(15):1339–46.

    Article  PubMed  CAS  Google Scholar 

  33. Piette JD, Schillinger D, Potter MB, Heisler M. Dimensions of patient–provider communication and diabetes self-care in an ethnically diverse population. J Gen Intern Med. 2003;18(8):624–33.

    Article  PubMed  Google Scholar 

  34. Schillinger D, Wang F, Rodriguez M, Bindman A, Machtinger EL. The importance of establishing regimen concordance in preventing medication errors in anticoagulant care. J Health Commun. 2006;11(6):555–67.

    Article  PubMed  Google Scholar 

  35. Kripalani S, LeFevre F, Phillips CO, Williams MV, Basaviah P, Baker DW. Deficits in communication and information transfer between hospital-based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831–41.

    Article  PubMed  CAS  Google Scholar 

  36. Shojania KG, Ranji SR, McDonald KM, et al. Effects of quality improvement strategies for type 2 diabetes on glycemic control: a meta-regression analysis. JAMA. 2006;296(4):427–40.

    Article  PubMed  CAS  Google Scholar 

  37. Gerber BS, Brodsky IG, Lawless KA, et al. Implementation and evaluation of a low-literacy diabetes education computer multimedia application. Diabetes Care. 2005;28(7):1574–80.

    Article  PubMed  Google Scholar 

  38. Piette J, Weinberger M, McPhee S. The effect of automated calls with telephone nurse follow-up on patient-centered outcomes of diabetes care. Med Care. 2000;38:218–30.

    Article  PubMed  CAS  Google Scholar 

  39. Piette JD, Weinberger M, Kraemer FB, McPhee SJ. Impact of automated calls with nurse follow-up on diabetes treatment outcomes in a Department of Veterans Affairs Health Care System: a randomized controlled trial. Diabetes Care. 2001;24(2):202–8.

    Article  PubMed  CAS  Google Scholar 

  40. Shea S, Weinstock RS, Starren J, et al. A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus. J Am Med Inform Assoc. 2006;13(1):40–51.

    Article  PubMed  Google Scholar 

  41. Handley M, Hammer H, Schillinger D. Navigating the terrain between research and practice: a Collaborative Research Network (CRN) case study in diabetes research. J Am Board Fam Med. 2006;19(1):85–92.

    Article  PubMed  Google Scholar 

  42. Aubert RE, Herman WH, Waters J, et al. Nurse case management to improve glycemic control in diabetic patients in a health maintenance organization. A randomized, controlled trial. Ann Intern Med. 1998;129(8):605–12.

    PubMed  CAS  Google Scholar 

  43. Chumbler NR, Neugaard B, Ryan P, Qin H, Joo Y. An observational study of veterans with diabetes receiving weekly or daily home telehealth monitoring. J Telemed Telecare. 2005;11(3):150–6.

    Article  PubMed  Google Scholar 

  44. Piette JD, McPhee SJ, Weinberger M, Mah CA, Kraemer FB. Use of automated telephone disease management calls in an ethnically diverse sample of low-income patients with diabetes. Diabetes Care. 1999;22(8):1302–9.

    Article  PubMed  CAS  Google Scholar 

  45. Weinberger M, Kirkman MS, Samsa GP, et al. A nurse-coordinated intervention for primary care patients with non-insulin-dependent diabetes mellitus: impact on glycemic control and health-related quality of life. J Gen Intern Med. 1995;10(2):59–66.

    Article  PubMed  CAS  Google Scholar 

  46. Piette JD, Weinberger M, McPhee SJ. The effect of automated calls with telephone nurse follow-up on patient-centered outcomes of diabetes care: a randomized, controlled trial. Med Care. 2000;38(2):218–30.

    Article  PubMed  CAS  Google Scholar 

  47. Piette JD, Weinberger M, McPhee SJ, Mah CA, Kraemer FB, Crapo LM. Do automated calls with nurse follow-up improve self-care and glycemic control among vulnerable patients with diabetes? Am J Med. 2000;108(1):20–7.

    Article  PubMed  CAS  Google Scholar 

  48. McLean I, Schneiderman M, Palacios J, Bhandari V, Handley M, Schillinger D. Extra Care for Diabetes: Automated Telephone Disease Management Protocol. New York, NY: Commonwealth Fund; 2004.

    Google Scholar 

  49. Chang A, Schyve PM, Croteau RJ, O’Leary DS, Loeb JM. The JCAHO patient safety event taxonomy: a standardized terminology and classification schema for near misses and adverse events. Int J Qual Health Care. 2005;17(2):95–105.

    Article  PubMed  Google Scholar 

  50. The Linnaeus-PC Collaboration. International Taxonomy of Medical Errors in Primary Care Version 2. http://www.errorsinmedicine.net/taxonomy/aafp/AAFP_taxonomyAugust19.pdf. Washington, DC: The Robert Graham Center; 2002.

  51. Victoroff M, Pace W. ASIPS-Victoroff Dimensions of Medical Outcome Taxonomy. http://www.errorsinmedicine.net/taxonomy/asips/ASIPS_Victoroff_Taxonomy_650633600_full.pdf; 2005.

  52. Dovey SM, Meyers DS, Phillips RL, Jr, et al. A preliminary taxonomy of medical errors in family practice. Qual Saf Health Care. 2002;11(3):233–8.

    Article  PubMed  CAS  Google Scholar 

  53. Bates DW, Cullen DJ, Laird N, et al. Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group. JAMA. 1995;274(1):29–34.

    Article  PubMed  CAS  Google Scholar 

  54. Forster AJ, Fung I, Caughey S, et al. Adverse events detected by clinical surveillance on an obstetric service. Obstet Gynecol. 2006;108(5):1073–83.

    PubMed  Google Scholar 

  55. Buetow S, Elwyn G. Patient safety and patient error. Lancet. 2007;369(9556):158–61.

    Article  PubMed  Google Scholar 

  56. Gardner D, Shobeck D. Greenspan’s Basic and Clinical Endocrinology. 8 ed. New York, NY: McGraw-Hill; 2007.

    Google Scholar 

  57. Golin CE, Liu H, Hays RD, et al. A prospective study of predictors of adherence to combination antiretroviral medication. J Gen Intern Med. 2002;17(10):756–65.

    Article  PubMed  Google Scholar 

  58. Paterson DL, Swindells S, Mohr J, et al. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med. 2000;133(1):21–30.

    PubMed  CAS  Google Scholar 

  59. Parker RM, Baker DW, Williams MV, Nurss JR. The test of functional health literacy in adults: a new instrument for measuring patients’ literacy skills. J Gen Intern Med. 1995;10(10):537–41.

    Article  PubMed  CAS  Google Scholar 

  60. Forster AJ, van Walraven C. Using an interactive voice response system to improve patient safety following hospital discharge. J Eval Clin Pract. 2007;13(3):346–51.

    Article  PubMed  Google Scholar 

  61. Schillinger D, Hammer H, Wang F, et al. Seeing in 3-D: examining the reach of diabetes self-management support strategies in a public healthcare system. Health Educ Behav. 2007; (in press) DOI 10.1177/1090198106296772.

  62. Elder NC, Vonder Meulen M, Cassedy A. The identification of medical errors by family physicians during outpatient visits. Ann Fam Med. 2004;2(2):125–9.

    Article  PubMed  Google Scholar 

  63. Plews-Ogan ML, Nadkarni MM, Forren S, et al. Patient safety in the ambulatory setting. A clinician-based approach. J Gen Intern Med. 2004;19(7):719–25.

    Article  PubMed  Google Scholar 

  64. Smith PC, Araya-Guerra R, Bublitz C, et al. Missing clinical information during primary care visits. JAMA. 2005;293(5):565–71.

    Article  PubMed  CAS  Google Scholar 

  65. Thomas EJ, Lipsitz SR, Studdert DM, Brennan TA. The reliability of medical record review for estimating adverse event rates. Ann Intern Med. 2002;136(11):812–6.

    PubMed  Google Scholar 

  66. American Diabetes Association. Standards of medical care in diabetes—2007. Diabetes Care. 2007;30(suppl 1):4S–41S.

    Article  CAS  Google Scholar 

  67. Hayward RA, Hofer TP. Estimating hospital deaths due to medical errors: preventability is in the eye of the reviewer. JAMA. 2001;286(4):415–20.

    Article  PubMed  CAS  Google Scholar 

  68. Brennan TA, Leape LL, Laird NM, et al. Incidence of adverse events and negligence in hospitalized patients. Results of the Harvard Medical Practice Study I. N Engl J Med. 1991;324(6):370–6.

    Article  PubMed  CAS  Google Scholar 

  69. Leape LL, Brennan TA, Laird N, et al. The nature of adverse events in hospitalized patients. Results of the Harvard Medical Practice Study II. N Engl J Med. 1991;324(6):377–84.

    Article  PubMed  CAS  Google Scholar 

  70. Thomas EJ, Studdert DM, Burstin HR, et al. Incidence and types of adverse events and negligent care in Utah and Colorado. Med Care. 2000;38(3):261–71.

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

Urmimala Sarkar is supported by National Research Service Awards Grant number 1 T32 HP19025. Dean Schillinger is supported by a NIH Mentored Clinical Scientist Award K-23 RR16539-05. Support for this research was also provided by The Commonwealth Fund and The California Health Care Foundation. The views presented here are those of the authors and should not be attributed to The Commonwealth Fund or the California Health Care Foundation or their directors, officers, or staff. Drs. Schillinger and Handley were also supported by a grant from Agency for Healthcare Research and Quality R21 HS014864. Electronic data were made available through the support of NIH grant UL1 RR024131. Dr. Shojania received salary support from the Government of Canada Research Chairs Program.

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Correspondence to Urmimala Sarkar MD, MPH.

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Sarkar, U., Handley, M.A., Gupta, R. et al. Use of an Interactive, Telephone-based Self-management Support Program to Identify Adverse Events Among Ambulatory Diabetes Patients. J GEN INTERN MED 23, 459–465 (2008). https://doi.org/10.1007/s11606-007-0398-7

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