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Personalization of Surgeries The tool for minimizing the number of readmissions to hospitals and patient safety Personalization of Surgeries The tool for.

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Presentation on theme: "Personalization of Surgeries The tool for minimizing the number of readmissions to hospitals and patient safety Personalization of Surgeries The tool for."— Presentation transcript:

1 Personalization of Surgeries The tool for minimizing the number of readmissions to hospitals and patient safety Personalization of Surgeries The tool for minimizing the number of readmissions to hospitals and patient safety Zbigniew W. Ras College of Computing and Informatics, UNC-Charlotte & James Studnicki College of Health and Human Services, UNC-Charlotte Zbigniew W. Ras College of Computing and Informatics, UNC-Charlotte & James Studnicki College of Health and Human Services, UNC-Charlotte

2 22 1. Failures of care delivery 2. Failures of care coordination 3. Overtreatment 4. Administrative complexity 5. Pricing failures 6. Fraud and abuse 7. Readmissions & - our area Patient Safety of research 1 Berwick DM, Hackbarth AD. Eliminating waste in US health care. JAMA. 2012;307(14):E1-E4. 2 Lowe TJ, Partovian C, Kroch E, Martin J, Bankowitz R. Measuring cardiac waste: the Premier Cardiac Waste Measures. Am J Med Qual. 2013 May 29, DOI: 10.1177/1062860613487923. Primary Areas of Healthcare Waste Research 1 PREMIER primary area of research 2

3 3 We focus on: -decreasing the number of readmissions to hospitals caused by side effects -improving patient safety Expected outcome: - significant reduction of the cost

4 Florida State Inpatient Databases (SID), part of the Healthcare Cost and Utilization Project (HCUP) A total of over 2.5 million visit discharges from 1.5 million patients Patients are diagnosed with a maximum of 31 diagnostic codes. Demographic data: age, gender, race,…….. 4

5 5 Patient has 7 diagnostic codes discovered by doctor Where is the problem? Surgery(i) is recommended because of these 3 (marked) diagnostic codes Surgery(i)Surgery(i) Surgery successful?? Patient readmitted to the hospital because of the side effects caused by surgery New diagnostic codes 15 readmissions – worst case Average – between 5 and 6

6 66 All patients in SID database having d1,d2,d3 diagnostic codes assigned to them. Where is the problem? Surgery(i) is recommended because of d1,d2,d3 diagnostic codes Surgery(i)Surgery(i) d1,d2,d3 {d1,d2,d3} -> empty set {d1,d2,d3} -> {d1,d3} {d1,d2,d3} -> {d1,d3,d5} {d1,d2,d3} -> {d1, d5,d6} {d1,d2,d3} -> {d5,d7} Personalized Surgeries (up to 300 per surgery) We partitioned all patients having Surgery(i) Into clusters: 2 patients are in the same cluster if they confirm the same rule. Rules

7 7 77 All patients in SID database having all 7 diagnostic codes assigned to them. Where is the problem? Surgery(i) is recommended because of d1,d2,d3 diagnostic codes Surgery(i)Surgery(i) d1,d2,d3 d4,d5,d6,d7 {d1,d2,d3} -> empty set {d1,d2,d3} -> {d1,d3} {d1,d2,d3} -> {d1,d3,s5} {d1,d2,d3} -> {d1, s5,s6} {d1,d2,d3} -> {s5,s7} Personalized Surgeries (up to 20 per surgery) s5 – listed in ALL personalized surgeries We should take care of s5 during Surgery(i) To take care of s5 may require additional personalized surgery which may cause new side effects Much smaller DB

8 8 -------------------------------------------------------------------------------------------------------------- Patient ID Visit-Number Main-Procedure-Code Set-of-Diagnoses-Codes -------------------------------------------------------------------------------------------------------------- 1 1 11 {11, 20, 234} 1 2 44 {11, 234} 1 3 98 {22, 234} -------------------------------------------------------------------------------------------------------------- 2 1 44 {11, 34, 99} 2 2 122 {4; 34} -------------------------------------------------------------------------------------------------------------- 3 1 44 {11, 20, 44, 101} 3 2 92 {20, 44, 4} 3 3 122 {4, 34} -------------------------------------------------------------------------------------------------------------- 4 1 11 {11, 22, 89} 4 2 44 {11, 234, 89} 4 3 122 {11, 22, 89} -------------------------------------------------------------------------------------------------------------- Red color – Negative side effect ; Green - Neutral ; Black color - positive

9 9 9 99 All patients in SID database having all 7 diagnostic codes assigned to them. Assume that d4 – hyperthyroid and without d4 personalized surgeries are much safer and have less number of side effects. It means d4 has to be fixed first. Quite interesting? Surgery(i) is recommended because of d1,d2,d3 diagnostic codes Surgery(i)Surgery(i) d1,d2,d3 d4,d5,d6,d7 Surgery unsuccessful {d1,d2,d3} -> {s5,s6} {d1,d2,d3} -> {d1,d3,s5} {d1,d2,d3} -> {d1, s5,s6} {d1,d2,d3} -> {s5,s7} Personalized Surgeries (up to 20 per surgery) d4

10 10 All patients in SID database having all 7 diagnostic codes assigned to them. Assume that d8 – high blood pressure and with d8 added to {d1,d2,d3,d4,d5,d6,d7} personalized surgeries are much safer and have less number of side effects. It means d8 has to be invoked before Surgery(i) takes place. Quite surprising? Surgery(i) is recommended because of d1,d2,d3 diagnostic codes Surgery(i)Surgery(i) d1,d2,d3 d4,d5,d6,d7 Surgery unsuccessful {d1,d2,d3} -> {s5,s6} {d1,d2,d3} -> {d1,d3,s5} {d1,d2,d3} -> {d1, s5,s6} {d1,d2,d3} -> {s5,s7} Personalized Surgeries (up to 20 per surgery) d4 d8

11 11 All patients in SID database having all 7 diagnostic codes assigned to them. Assume that d8 – high blood pressure and with d8 added to {d1,d2,d3,d4,d5,d6,d7} personalized surgeries are much safer and have less number of side effects. It means d8 has to be invoked before Surgery(i) takes place. Maybe d4 should fixed first? What we have done wrong? Surgery(i) is recommended because of d1,d2,d3 diagnostic codes Surgery(i)Surgery(i) d1,d2,d3 d4,d5,d6,d7 Surgery unsuccessful d4 d8

12 12 Surgery(i)Surgery(i) Surgery(i3)Surgery(i3) Surgery(i2)Surgery(i2) Surgery(i6)Surgery(i6) Passed Away 50 500 200 10 30 20 D1 D2 Split 500 patients using all stable features (not comorbid conditions) using minimal average entropy approach. Repeat this step for all surgeries. The trees defining different levels of personalization will differ but the same attributes will be used on the lowest level of these trees. Use J48 (WEKA) on all stable attributes to split

13 13 Surgery(i)Surgery(i) Surgery(i5)Surgery(i5) Surgery(i4)Surgery(i4) Surgery(i3)Surgery(i3) Surgery(i2)Surgery(i2) Surgery(i8)Surgery(i8) Surgery(i7)Surgery(i7) Surgery(i6)Surgery(i6) Passed Away 50 500 50 200 10 30 150 50 20 150 20 Passed Away 10 Probability of the path: 2/5 * 3/4 cost, length of stay, …, side effects D1 D2 D3 D4 D5 Assume that Surgery(i), Surgery(i2), Surgery(i6) is the optimal path

14 14 Surgery(i)Surgery(i) Surgery(i3)Surgery(i3) Surgery(i2)Surgery(i2) Surgery(i7)Surgery(i7) Surgery(i6)Surgery(i6) 50 500 200 10 30 150 20 D1 D2 We would like to move 200 patients following the path Surgery(i), D2 to Surgery(i), D1. P1P2P3P4D pat1XXXD2 pat2XXXD2 pat3XXXD2 pat200XXXD2 pat201XXD1 pat250XXXD1 Diagnostic Codes (Diagnoses) p1.p2.p3 -> p1.p2 p1.p3.p4 -> p1.p2 Placing patients on a different path

15 Questions ? 15


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