Multivariate Analysis to Will Die When

Mohammed Alharbi Hap 464

The objective of the workAnalysis to Predict Who Will Die When.HOW ? Create Training and Validation set . Use the training set to calculate likelihood ratio. It’s important because it gives forecast information regarding

health outcomes. this assignment teach us to explore data and locate exact

information among big data.

Data sourceNumber of cases

What is the distribution of the data

• Data source from the Assignment Select count (*) from dbo.final • The total number of cases( 17,443,442 number of cases)• distribution of the dataThe average is -59.5318And the Standard deviation- 4.2931

Average AgeAtDx: 59.53186Standard Deviation of

AgeAtDx: 4.293136

Start Dataset (hap464.dbo.final): 17,443,442 Cases and 829,827 IDsHas visit after death Removed: 17,432,694 Cases and 829,659 IDs>365 Dx/Yr Removed: 17,379,218 Cases and 829,603 IDs This is your clean data.80% Training Set From Clean Data: 13,760,416 Cases and 657,905 IDs20% Validation Set From Clean Data: 3,619,297 Cases and 171,698 IDs

Preparation of the data

17,443,442

10,748 diagnoses removed

53,476 diagnoses removed

829,827 distinct IDs

Remove Zombies:

168 distinct IDs

Calculating Likelihood Ratios

(The number of patient who will died within 6 months /Dead Patients)

(The number of patient who will died within 6 months/ Alive Patients)

Examples of 10 most deadly and 10 least deadly diseases

10 Least Deadly: Icd9 PtsDead6 PtsAlive6 Dead Alive LR• 1 I218.9 2 2214 112710 545175 0.004369• 2 I626.2 2 1972 112710 545175 0.004906• 3 I478.0 2 1183 112710 545175 0.008177• 4 I599.7 1 544 112710 545175 0.008891• 5 I620.2 2 773 112710 545175 0.012515• 6 I717.83 1 349 112710 545175 0.01386• 7 I474.00 1 343 112710 545175 0.014102• 8 I296.42 1 338 112710 545175 0.014311• 9 I716.17 1 338 112710 545175 0.014311• 10 IV57.22 21 6150 112710 545175 0.016516

• 10 Most Deadly: icd9 PtsDead6 PtsAlive6 Dead Alive LR• 1 I853.05 3 1 112710 545175 14.51091• 2 I798.2 3 1 112710 545175 14.51091• 3 I183.2 2 1 112710 545175 9.673942• 4 I798.9 2 1 112710 545175 9.673942• 5 I194.8 2 1 112710 545175 9.673942• 6 I960.7 2 1 112710 545175 9.673942• 7 I862.21 2 1 112710 545175 9.673942• 8 I852.05 2 1 112710 545175 9.673942• 9 I718.59 2 1 112710 545175 9.673942• 10 I531.21 2 1 112710 545175 9.673942

The name of Least deadly icd9 diagnose

• 1 I218.9 : eiomyoma of uterus, • 2 I626.2 : Disorders of menstruation  • 3 I478.0 : Hypertophy of nasal turbnates • 4 I599.7 : Hekaturia • 5 I620.2 : Other and unspecified ovarian cyst • 6 I717.83 : Old disruption of anterior cruciate ligament • 7 I474.00 : Effusion, right root • 8 I296.42 : Bipolar i disorder , most recent episode • 9 I716.17 : Traumatic arthropathy, ankle and foot • 10 IV57.22 : Operation On urinary Bladeder

The name of Most deadly icd9 diagnose

• 1 I853.05 : Unspecified Intracranial hemorrhage following injury without mention of open interacranian wound

• 2 I798.2 : Death occurring in less than 24 hours from onest of symptoms • 3 I183.2 : Malingant neoplasm of fallopain tube • 4 I798.9 : Unspecified interacranial homerrhage following • 5 I194.8 : Malignant neoplasm of other endocrine gland and related Structure • 6 I960.7 : posing by antineoplastic antibiotics • 7 I862.21 : injury to Bronchus without mention of open wound into cavity • 8 I852.05 : subarachniod hermorrhage folowing injury without mention of open intracranial wound • 9 I718.59 : Ankylosis of joint ,Multiples sites • 10 IV57.21 :Acute gastric Ulcer with hemorrhage and perforation with obstruction

Calculate sensitivity and specificity of the predictions

 Posterior Odds

 

Alive Dead

True Condition

Alive True Positive False Negative  

Dead False Positive True Negative  

 

Usefulness of the project • The usefulness of the project is to practice doing SQL in a large data set by using the skills of

codes, Also to figure out Selecting appropriate method of data analysis and removal of confounding in the data, Visually present complex multivariate data and Interpret quantitative findings and relate it to specific policy issues or management decisions.

• In fact, It’s important in our future work filed