Currently Viewing:
The American Journal of Accountable Care March 2016
Currently Reading
Cognitive Impairment and Reduced Early Readmissions in Congestive Heart Failure?
Mark W. Ketterer, PhD; Jennifer Peltzer, PsyD; Usamah Mossallam, MD; Cathy Draus, RN; John Schairer, DO; Bobak Rabbani, MD; Khaled Nour, MD; Gayathri Iyer, MD; Michael Hudson, MD; and James McCord, MD
Inpatient and 90-Day Postdischarge Outcomes in Cardiac Surgery
Donald E. Fry, MD; Michael Pine, MD, MBA; Susan M. Nedza, MD, MBA; David G. Locke, BS; Agnes M. Reband, BS; and Gregory Pine, BA
Will Regional Differences in Family Practice Procedures Impact Reimbursement Rates? A National Study of Medicare Part B
Man Hung, PhD; Jerry Bounsanga, BS; Anthony B. Crum, BS; and Maren W. Voss, MS
Employer-Led Efforts to Improve the Value of Health Spending
Megan McHugh, PhD; Claude R. Maechling, PhD; Dorothy D. Dunlop, PhD; Linda O’Dwyer, MSLIS, MA; Dustin D. French, PhD; Rahul K. Khare, MD, MS; Anna P. Nannicelli, MPH, MSW; Alexandra R. Brown, BA; a
The Future of Case Management - GPS for Patients?
Morey Menacker, DO
Top 10 Ways to Improve Your Physician Quality Reporting System/Group Practice Reporting Option
Amy Holm, MHA, and Hymin Zucker, MD
What It Means to Be a Physician Leader: A Q&A With Dr Anthony Slonim
Laura Joszt, MA

Cognitive Impairment and Reduced Early Readmissions in Congestive Heart Failure?

Mark W. Ketterer, PhD; Jennifer Peltzer, PsyD; Usamah Mossallam, MD; Cathy Draus, RN; John Schairer, DO; Bobak Rabbani, MD; Khaled Nour, MD; Gayathri Iyer, MD; Michael Hudson, MD; and James McCord, MD
Proactive identification of cognitive impairment and compensatory destigmatized patient/familial psychoeducation regarding “forgetfulness” in hospitalized patients with congestive heart failure may reduce readmission rates substantially.
For I5, the average monthly 30-day readmission rate was 16%. For H5 it was 21.5%, and for the remainder of the hospital, it was 22.8%. Nationally reported figures from CMS average about 23%. A 1-tailed Student's t test (N = 12) comparing average monthly 30-day rates for I5 versus non-I5H5 yielded P = .007. For I5 versus H5, P = .052 (see Figure).


Present results suggest a significant reduction in early (30-day) readmissions among hospitalized CHF patients on an inpatient service where patients were proactively identified and evaluated, and subsequently underwent intervention for cognitive impairment, relative to national averages reported by CMS and hospital averages. Present results are congruent with other studies documenting CI as a prospective predictor of readmissions and nonadherence. In addition, these results complement several dozen published studies that found spontaneously reduced medical utilization (eg, hospital stays, length-of-stay, overall costs), as well as our own finding of reduced early readmissions in patients with acute myocardial infarction who screened positive for anxiety/depression and were receiving a psychiatric consult versus those not receiving one.52

We believe the present analyses represent a weak test of our hypothesis. Because we only intervened with about 20% of all CHF patients admitted to I5, when 50% or more were known to have CI, 4,5,18 the present results may be a conservative test of the effect. Might a greater reduction have been observed if we saw 30%, 40%, or 50% of the CHF sample?

Cultural Contamination?

On the other hand, is there a plateauing of this effect by the “cultural change” caused by the presence of a behavioral clinician on the care provided by the team to other patients, sometimes referred to as a “cultural change,” “paradigm shift,” “contamination,” or “transfer effect.”53 The presence of a behavioral clinician likely changes the care of not just the patients seen, but of the patients seen by collaborating clinicians whose interest and understanding is altered by cases shared with the behavioral clinician.

Proactive Identification

We believe it is likely that the apparent success of our intervention resulted, in part, because we were proactive about early case-finding of patients with various characteristics that made the presence of CI likely. These included early readmission, comorbid conditions, and clinical characteristics (eg, being a “poor historian,” unexplained metabolic derangements). Because spontaneous identification of CI is extremely poor4,21,22 such proactive identification of at-risk patients is almost certainly a necessity for timely recognition, evaluation, and intervention. Early identification enables time to evaluate the patient, educate the patient and family, and plan efforts to avoid another medical crisis.

Return on Investment

The professional time required for our proposal is currently reimbursable under all insurance programs, including Medicare and Medicaid. If the intervention reduces readmissions on 100 patients from about 23% to 9% in the first month, we project savings of $151,200 (14 admissions avoided × 4.5 days/admission × $2400/day) in the first month alone (not to mention a significant improvement in quality of life, reduced medical crises and, perhaps, deaths), for a net expenditure of $33,500 (100 patients × $335/patient for in-patient psychiatric care and first month’s costs). Net savings in the first month then would be $117,700 to the payer. The net savings over longer periods can only be guessed at currently, but may prove substantial. Regardless of the net cost/savings, this intervention improves clinical outcomes for patients by decreasing potentially fatal medical crises. For the hospital, the cost of the system of care being provided is covered by billing for the psychological services rendered.

Thus, the introduction of a health psychology service to a treatment team caring for CHF patients produces a higher “value” of care—better outcomes with reduced costs. We do not yet know whether other populations with high early readmission rates (eg, end-stage renal disease, chronic obstructive pulmonary disease) would display a similar increase in value. We suspect the prevalence rates of various behavioral factors affecting readmission may vary across medical populations.


We must note that the present study was not a randomly assigned, controlled clinical trial. Therefore, we cannot be certain that all known or unknown potential selection/historical confounds (eg, average age, active smokers, exercisers, psychiatric history, number and kind of comorbidities, substance abuse, sex ratios, educational level) were not different across our groupings in a manner that biased the results in favor (or against) our results. For funding agencies, such a trial should have the highest priority.


If evidence-based care of CHF patients that maximizes effectiveness, safety, and efficiency is the goal, enhanced recognition of cognitive impairment and more proactive management of adherence is a necessity.

Author Affiliations: Henry Ford Hospital (MWK, JS, JPJ, BR, MH, CD, JM), Henry Ford Health System (GI, UM, KN), Detroit, MI.

Source of Funding: Partial support from the Blue Cross/Blue Shield of Michigan Foundation, and Health Resources & Services Administration Grant 1-D40HP25715-01-00.

Author Disclosures: Dr Peltzer Jones received an HRSA grant, which funded the clinical time. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (MWK, MH, UM, CD); acquisition of data (MWK, JPJ, MH, CD); analysis and interpretation of data (MWK, JPJ, MH); drafting of the manuscript (MWK, JPJ); critical revision of the manuscript for important intellectual content (MWK, JPJ, MH, UM, CD); statistical analysis (MWK); provision of study materials or patients (MWK, JPJ, MH, BR, CD, JS, GI, KN, JM); obtaining funding (JPJ); administrative, technical, or logistic support (MWK, UM); and supervision (MWK, BR, GI, UM, JM).

Send correspondence to: Mark W. Ketterer, PhD, Henry Ford Hospital/PP=T117, 2799 West Grand Blvd, Detroit MI 48202. E-mail:

1. Report to the Congress: Promoting greater efficiency in Medicare. Medicare Payment Advisory Commission website. Published June 2007. Accessed January 2016.

2. Readmissions reduction program. CMS website.
Updated November 16, 2015. Accessed January 2016.

3. Krumholz HM, Normand SL, Wang Y. Trends in hospitalization and outcomes for acute cardiovascular disease and stroke 1999-2011. Circulation. 2014;130(12):966-975. doi:10.1161/CIRCULATIONAHA.113.007787.

4. Ketterer MW, Draus C, McCord J, Mossallam U, Hudson M. Behavioral factors and hospital admissions/readmissions in patients with CHF. Psychosomatics. 2014;55(1):45-50. doi:10.1016/j.psym.2013.06.019.

5. Pressler SJ. Cognitive functioning and chronic heart failure: a review of the literature (2002-July 2007). J Cardiovasc Nurs. 2008;23(3):239-249. doi:10.1097/

6. Bugnicourt JM, Godefroy O, Chillon JM, Choukroun G, Massy ZA. Cognitive disorders and dementia in CKD: the neglected kidney-brain axis. J Am Soc Nephrol. 2013;24(3):353-363. doi:10.1681/ASN.2012050536.

7. Ketterer MW, Soman S, Mossallam U. Psychosocial risk factors and admissions/readmissions in end stage renal disease patients. J Behav Health. 2014;3(4):230-233.

8. Dodd JW, Getov SV, Jones PW. Cognitive function in COPD. Eur Respir J. 2010;35(4):913-922. doi:10.1183/09031936.00125109.

9. Hung WW, Wisnivesky JP, Siu AL, Ross JS. Cognitive decline among patients with chronic obstructive pulmonary disease. Am J Resp Crit Care Med. 2009;180(2):134-137. doi:10.1164/rccm.200902-0276OC.

10. Li J, Fei GH. The unique alterations of hippocampus and cognitive impairment in chronic obstructive pulmonary disease. Respir Res. 2013;14:140. doi:10.1186/1465-9921-14-140.

11. Mudge AM, Kasper K, Clair A, et al. Recurrent readmissions in medical patients: a prospective study. J Hosp Med. 2011;6(2):61-67. doi:10.1002/jhm.811.

12. Singh B, Mielke MM, Parsaik AK, et al. A prospective study of chronic obstructive pulmonary disease and the risk of mild cognitive impairment. JAMA Neurol. 2014;71(5):581-588. doi:10.1001/jamaneurol.2014.94.

13. Thakur N, Blanc PD, Julian LJ, et al. COPD and cognitive impairment: the role of hypoxemia and oxygen therapy. Int J Chron Obstruct Pulmon Dis. 2010;5:263-269.

14. Villaneuve S, Pepin V, Rahavel S, et al. Mild cognitive impairment in moderate to severe
COPD: a preliminary study. Chest. 2012;142(6):1516-1523. doi:10.1378/chest.11-3035.

15. Fields SD, MacKenzie CR, Charlson ME, Sax FL. Cognitive impairment. can it predict the course of hospitalized patients? J Am Geriatr Soc. 1986;34(8):579-585.

16. McLennan SN, Pearson SA, Cameron J, Stewart S. Prognostic importance of cognitive impairment in chronic heart failure patients: does specialist management make a difference?
Eur J Heart Fail. 2005;8(5):494-501.

17. Watson AJ, O’Rourke J, Jethwani K, et al. Linking electronic health record-extracted psychosocial data in real-time to risk of readmission for heart failure. Psychosomatics. 2011;52(4):319-327. doi:10.1016/j.psym.2011.02.007.

18. Dodson JA, Truong TT, Towle VR, Kerins G, Chaudhry SI. Cognitive impairment in older adults with heart failure: prevalence, documentation, and impact on outcomes. Am J Med. 2013;126(2):120-126. doi:10.1016/j.amjmed.2012.05.029.

19. Cameron J, Worrall-Carter L, Page K, Riegel B, Lo SK, Stewart S. Does cognitive impairment predict poor self-care in patients with heart failure? Eur J Heart Fail. 2010;12(5):508-515. doi:10.1093/eurjhf/hfq042.

20. Hwang B, Moser DK, Dracup K. Knowledge is insufficient for self-care among heart failure patients with psychological distress. Health Psychol. 2014;33(7):588-596. doi:10.1037/A0033419.

21. Robins LN, Regier DA. Psychiatric Disorders in America: The Epidemiological Catchment Area Study. New York, NY: Free Press; 1991.

22. Raymont V, Bingley W, Buchanon A, et al. Prevalence of mental incapacity in medical inpatients and associated risk factors: cross-sectional study. Lancet. 2004;364(9443):1421-1427.

23. Valcour VG, Masaki KH, Curb JD, Blanchette PL. The detection of dementia in the primary care setting. Arch Intern Med. 2000;160(19):2964-2968.

24. Ackerly DC, Grabowski DC. Post-acute care reform—beyond the ACA. N Engl J Med. 2014;370:689-691. doi:10.1056/NEJMp1315350.

25. Behforouz HL, Drain PK, Rhatigan JJ. Rethinking the social history. N Engl J Med. 2014;371(14):1277-1279. doi:10.1056/NEJMp1404846.

26. Boling PA. Managing posthospital care transitions for older adults: challenges and opportunities. JAMA. 2014;312(13):1303-1304. doi:10.1001/jama.2014.12360.

27. Bosworth HB. Enhancing Medication Adherence: The Public Health Dilemma. London, UK: Springer Healthcare; 2012.

28. Butler J, Kalogeropoulas A. Hospital strategies to reduce heart failure readmissions: where is the evidence? J Am Coll Cardiol. 2012;60(7):615-617. doi:10.1016/j.jac.2012.03.066.

29. Chaudury SI, McAvay G, Chen S, et al. Risk factors for hospital admission among older persons with newly diagnosed heart failure: findings from the Cardiovascular Health Study. J Am Coll Cardiol, 2013;61(6):635-642. doi:10.1016/j.jacc.2012.11.027.

30. Al Hamid A, Ghaleb M, Aljadhey H, Aslanpour Z. A systematic review of qualitative research on the contributory factors leading to medicine-related problems from perspectives of adult patients with cardiovascular diseases and diabetes mellitus. BMJ Open. 2014;4(9):e005992. doi:10.1136/bmjopen-2014-005992.

31. Krumholz HM. Post-hospital syndrome—an acquired, transient condition of generalized risk. N Engl J Med. 2013;368(2):100-102. doi:10.1056/NEJMp1212324.

32. Schwarz KA, Elman CS. Identification of factors predictive of hospital readmissions for patients with heart failure. Heart Lung. 2003;32(2):88-99.

33. Smith DM, Giobbie-Hurder A, Weinberger M, et al. Predicting non-elective hospital readmissions: a multi-site study. Department of Veterans Affairs Cooperative Study Group on Primary Care and Readmissions. J Clin Epidemiol. 2000;53(11):1113-1118.

34. Williams MV. A requirement to reduce readmissions: take care of the patient, not just the disease. JAMA. 2013;309(4):394-396. doi:10.1001/jama.2012.233964.

35. Coburn KD, Marcantonio S, Lazansky R, Keller M, Davis N. Effect of a community-based nursing intervention on mortality in chronically ill older adults: a randomized controlled trial. PLoS Med. 2012;9(7):E1001265e1001265. doi:10.1371/journal.pmed.1001265.

36. Coleman EA, Parry C, Chalmers S, Min SJ. The care transitions intervention: results of a randomized controlled trial. Arch Intern Med. 2006;166(17):1822-1828.

37. Greenwald JL, Denham CR, Jack BW. The hospital discharge: a review of high risk care transition with highlights of a re-engineered discharge process. J Patient Saf. 2007;3(2):97-106.

38. Jack BW, Chetty VK, Anthony D, et al. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009;150(3):178-187.

39. Naylor MD, Brooten D, Campbell R, et al. Comprehensive discharge planning and home follow-up of hospitalized elders: a randomized clinical trial. JAMA. 1999;281(7):613-620.

40. Ostrovsky A. Community-based health coaches and care coordinators reduce readmissions using information technology to identify and support at-risk Medicare patients after discharge.
Agency for Healthcare Research and Quality website. Published July 30, 2014. Accessed January 2016.

41. Rich MW, Beckham V, Wittenberg C, Leven Cl, Freedland KE, Carney RM. A multidisciplinary intervention to prevent the readmission of elderly patients with congestive heart failure. N Engl J Med. 1995;333(18):1190-1195.

42. Shaughnessy PW, Hittle DF, Crisler KS, et al. Improving patient outcomes of home health care: findings from two demonstration trials of outcome-based quality improvement. J Am Geriatric Soc. 2002;50(8):1354-1364.

43. Eze-Nliam C, Cain K, Bond K, et al. Discrepancies between the medical record and the reports of patients with acute coronary syndrome regarding important aspects of the medical history. BMC Health Serv Res. 2012:12:78. doi:10.1186/1742-6963-12-78.

44. Rowe T, Ziegelstein RC, Jones J. Those who forget their history are condemned to repeat it. Am J Med. 2010;123(9):796-798. doi:10.1016/j.amjmed.2010.05.004.

45. Ketterer MW, Smith TW. Self-reported versus other-reported distress and coronary artery calcification. Psychosom Med. 2011;73(8): 721; author reply 721-722. doi:10:1097/PSY.0b013e318230a553.

46. Borson S, Scanlan JM, Chen P, Ganguli M. The Mini-Cog as a screen for dementia: validation in a population-based sample. J Am Geriatr Soc. 2003:51(10):1451-1454.

47. Borson S, Scanlan JM, Watanabe J, Tu SP, Lessig M. Simplifying detection of cognitive impairment: comparison of the Mini-Cog and the Mini-Mental State Examination in a multiethnic sample. J Am Geriatr Soc. 2005;53(5):871-874.

48. Lessig MC, Scanlan JM, Nazemi H, Borson S. Time that tells: critical clock-drawing errors for dementia screening. Int Psychogeriatr. 2008;20(3):459-470.

49. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. Journal Psychiatr Res. 1975;12(3):189-198.

50. Gauthier S, Reisberg B, Zaudig M, et al; International Psychogeriatric Association Expert Conference on mild cognitive impairment. Mild cognitive impairment. Lancet. 2006;367(9518):1262-1270.

51. Peterson RC. Mild cognitive impairment. N Engl J Med. 2011;364:2227-2234. doi:10;1056/NEJMcp09102237.

52. Ketterer MW, Fitzgerald F, Keteyian S, et al. Chest pain and the treatment of psychosocial/emotional distress in CAD patients. J Behav Med. 2000;23(5):437-450.

53. Strain JJ, Hammer JJ, Fulop G. APM task force on psychosocial interventions in the general hospital setting: a review of cost-offset studies. Psychosomatics. 1994;35(3):253-262.
Copyright AJMC 2006-2017 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
Welcome the the new and improved, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up

Sign In

Not a member? Sign up now!