healthcare data analytics implementation

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ALTEN Calsoft Labs Corporate Overview

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March 31, 2016

PREDICITIVE ANALYTICS IN HEALTHCARE

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HIMSS describes healthcare analytics as the systematic use of data and related clinical and business (C&B) insights developed through applied analytical disciplines such as statistical, contextual, quantitative, predictive, and cognitive spectrums to drive fact-based decision making for planning, management, measurement and learningObjectivesHealthcare providers are improving the clinical outcomes of patients via treatments and protocolsPromotion of wellness and disease management

OverviewThe key objective of healthcare analytics is to gain insight for making informed healthcare decisions.

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Patient Re-admission within 30 days A case studyBusiness ProblemA healthcare facility wants to identify a patient's chance of getting re-admitted upon discharge within 30 days.

BenefitsClinicians can be prepared to provide better post-discharge care for patients who are likely to get re-admitted and hospitals can avail benefits from Government.

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Patient admission If a patient is hospitalized for more than 24 hrs, it is considered as Patient admission.

Re-Admission Patient gets admitted for more than 24 hrs within 30 days of the last discharge date. If a patient comes back to the hospital after 30 days, it is not considered as Re-Admission.

Definitions

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Data Analysis ProcessThe below figure shows the typical processes of Data analysis of a Dataset.

Receive the Datasets (.csv)Process the Datasets for AnalysisAnalyse the DatasetsBuild the ModelVisualize the Analysed data

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In order to predict the re-admission, following data fields/predictors were considered. Demographics Age, SexLab data Includes lab testsVitals Includes BP, Sugar, Weight, etc.Visit types Emergency, In-patient, OutpatientDiagnosis Diseases/ailments Heart,PnuemoniaPrevious hospital visitLength of stay

The Predictors Predictive Analytics

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The data was received as a set of .csv files which gave the complete details of Demographics, Admission, vitals, lab tests of selected sample of patients over a period of time.The processing of the data included the following activities: Removing commas, uploading .csv files to HDFS (Horton works)The required DDL scripts were written in HiveThe necessary joins were writtenThe result was refined datasetsThe refined datasets are passed on to Data Analysis team for analysis

Data Processing

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Predictive Analysis ProcessUse the Module Analyse the datasetIdentify the Suitable Algorithm

Build the model

Evaluate/Deploy the model

Monitor/Refactor the model

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DatasetsThe refined datasets are divided into train and test datasets in order to build the Model

30%70%

Train

Test

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The best model is arrived at by testing the data under different classifiers and precision, recall and F1 score metrics calculated for each classifier. Gradient Boosting Random Forest Support Vector Machines Logistic Regression K-Nearest Neighbor RidgeEvaluate Models

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Model - Process

ModelTrainingDataset

TestDatasetModel

Final Analyzed Dataset

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Model Fine tuning K- Fold MeansFor tuning parameters and model selection, k-Fold cross validation was used where data was split into K equal partitions. 1 fold was used for testing and the remaining for training. This was repeated K( K=4) times and using the average testing accuracy. Dataset

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AccuracyAccuracy is measured by area under the ROC curve as shown below0.77 accuracy is achieved by Random Forest as shown in the below curve

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Process Data AnalysisThe below figure shows the typical processes of Data analysis of a dataset.

1.Offline Processed data is dumped into Staging Data MartRest ClientCAF Analytics Engine

Rest API

Builds Model running Python scriptsScores model

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Data Visualization Report on the Model

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Actual Report on a Dataset

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Screen shots

Write to US @ Business@Altencalsoftlabs.comALTEN Calsoft Labs

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Copyright 2016 ALTEN Calsoft Labs. All such documents and related graphics are provided "as is" without warranty of any kind and are subject to change without prior notice. ALTEN Calsoft Labs reserves the right, in its sole discretion, to correct any errors or omissions in any portion of this documentVisit: www.Altencalsoftlabs.com

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