1. The Impact of an Epilepsy Self-Management Program on Health Care Utilization Emily Dwyer, Nursing Student, University of New Hampshire Karen Secore MS, APRN, CNRN, Dartmouth-Hitchcock Medical Center RECOMMENDATIONS OUTCOMES INTRODUCTION METHOD REFERENCES ACKNOWLEDGEMENTS CONCLUSIONS LIMITATIONS HOBSCOTCH (Home Based Self-Management & Cognitive Training Changes Lives) is an epilepsy self-management program developed at Dartmouth-Hitchcock and funded by the CDC. Its purpose is to improve the memory and attention of those with epilepsy through the use of problem solving therapy. The initial study found that the program is effective in terms of improving memory and quality of life. When determining whether or not to implement an intervention, cost is an important consideration. One method to assess cost is by measuring and analyzing subsequent health care utilization. The simplest method is to measure the change in the number of encounters 5. The data cane be related directly to health care cost 2,4 or can be combined with secondary measures such as quality of life survey data 6 Similar studies have been conducted in the primary care setting 1 with positive results. Data can be further analyzed by comparing those with a higher baseline number of health care interactions to the rest of the sample. 3 Fifty-seven patient records were retrospectively analyzed for the six months before and after the intervention. Twenty-one patients were enrolled in the control group, nineteen to the intervention group, and seventeen to the intervention plus computerized cognitive training group. Of these, thirty fit the high frequency criteria. These patients had five or more total health care interactions in the six months before the intervention. Eleven of these were controls, eleven were in the intervention group and eight received computerized cognitive training and the intervention. Data collected included all health care interactions that were not study related. These included phone calls, office visits, emergency department visits, admissions, diagnostic tests, and surgeries. This data was then analyzed using SPSS statistics software version twenty-one. Total Encounters: p=0.246Neurology Encounters: p=0.548 Total Encounters: p=0.001*Neurology Encounters: p=0.886 No statistically significant difference was found in the number of encounters before and after the intervention when looking at the combined treatment groups (N= 35). When the high frequency sample (N=19) was analyzed separately, there was a statistically significant decrease in the total number of health care encounters. 6 Months Pre: Total Group Depression and Total Neurology Encounters Positive Correlationp=0.03 Quality of Life and Total Neurology Encounters Negative Correlationp=0.017 6 Months Post: Intervention Group Depression and Total Neurology Encounters No Correlationp=0.291 Quality of life and Total Neurology Encounters No Correlationp=0.765 6 Months Post: Control Group Depression and Total Neurology Encounters Positive Correlationp=0.001 Quality of life and Total Neurology Encounters No Correlationp=0.856 Correlations Between Depression, Quality of Life, and Total Neurology Encounters Total Encounters and Neurology Encounters: The Effect of the Intervention After completion of the study there was no longer a correlation between depression and total neurology encounters or quality of life and total neurology encounters. Similar results were found in the high frequency group. PATIENT POPULATION Inclusion Criteria Age: 18 to 65 Subjective memory or attention complaints IQ > 70 No difficulty reading or writing Reliable telephone access Stable antiepileptic and antidepressant medication regime for one month  While all patients with both epilepsy and memory impairment may benefit from this intervention, it is particularly helpful for those with a greater than average number of health care encounters.  Further research with larger sample sizes is needed to further validate the cost effectiveness of the intervention and allow for the generalization of results.  The patient sample as a whole did not have a statistically significant decrease in the number of health care encounters after receiving the intervention.  In patients with a higher than average number of encounters, the number of total encounters decreased significantly.  Before the intervention, the number of neurology encounters was correlated to patients’ self-reported levels of depression and quality of life. Depression continued to correlate with the number of neurology encounters in the control group, but no correlation existed between the number of neurology encounters and depression or quality of life in the intervention group. 1. Bodenheimer, T., Lorig, K., Holman, H., & Grumbach, K. (2002). Patient self-management of chronic disease in primary care. Jama,288(19), 2469-2475. 2. Fitch, K., Kosuke, I., & Villa, K. F. (2014). Resource Utilization and Cost in a Commercially Insured Population with Schizophrenia. American Health & Drug Benefits, 7(1), 18-26. 3. Hansagi, H., Allebeck, P., & Edhag, O. (1989). Health care utilization after referral from a hospital emergency department. Scandinavian Journal Of Social Medicine, 17(4), 291-299. 4. Hynes, D., Reda, D., Giobbie-Hurder, A., Abdellatif, M., Weinberger, M., Oddone, E., &... Henderson, W. (1999). Measuring costs in multisite randomized controlled trials: lessons from the VA Cooperative Studies Program. Medical Care, 37(4 Suppl Va), AS27-AS36. 5. Mcconnachie, A., Walker, A., Robertson, M., Marchbank, L., Peacock, J., Packard, C., &... Ford, I. (2014). Long-term impact on healthcare resource utilization of statin treatment, and its cost effectiveness in the primary prevention of cardiovascular disease: A record linkage study. European Heart Journal, 35(5), 290-298. 6. Räsänen, P., Sintonen, H., Ryynänen, O., Blom, M., Semberg-Konttinen, V., & Roine, R. P. (2005). Measuring cost-effectiveness of secondary health care: feasibility and potential utilization of results. International Journal Of Technology Assessment In Health Care,21(1), 22-31. Arm Average Age Percent Female Baseline QOLIE-31 Score C (Control) 40.38+11.1 8 61.90%3.85 + 2.34 H (Intervention)44.73+8.6163.16%5.15 + 1.81 H+ (Intervention Plus Computerized Cognitive Training) 51.41+9.2182.35%5.37 + 1.89 ASSESSMENT TOOLS QOLIE-31, Modified: Assessment of patient’s memory Depression Score: Patient’s perception of his or her depression Quality of Life: Patient’s perception of his or her quality of life Sample Size: When looking at subgroups of patients, especially in the high frequency group, small sample sizes limit the generalizability of the results. The definition of “high frequency” was established by the researchers. It cannot be said definitively that their greater number of encounters and subsequent decreases are not random. A special thanks to Paula Johnson, Dr. Barbara Jobst, Lindsay Schommer, Samantha Schmidt, Peter Horak, and Wenyan Zhao for their guidance and support throughout the research process. This presentation was made possible by the IDeA Program, NIH Grant No. P20GM103506 (National Institute of General Medical Sciences) PURPOSE To assess the cost effectiveness of HOBSCOTCH by measuring health care utilization. It is hypothesized by the researchers that addressing patients’ memory impairments and problem solving skills will decrease their number of health care encounters, as they will be better equipped to address their own needs. NH-INBRE * Statistical Significance, p<0.05 -26.8% -11.6% -28.7% -39.6%*