Of the many areas, big data and analytics will revolutionize marketing and sales, coming up next is an outline one of those that are conveying results today. How costs are characterized, overseen, managed, propagated through selling networks and optimized is a zone seeing fast gains. Attaining price optimization for a given product or service is becoming possible, thanks to advances in big data algorithms and wide analytics techniques.

Like every other industry, things are changing rapidly in the pharma sector. With just 20 years of medication patent window, there is almost no time for organizations to earn ROI. There is a reasonable request for innovative technology solutions to accelerate the way toward guaranteeing benefits.
The procedure of drug development is lengthy and complex combined with several procedures, applications, and endorsements or approvals. Unquantified and unstructured information/data is created from numerous platforms in different structures. Advances in storage system, network and technology innovations have empowered pharma organizations to conquer this issue and economically and proficiently outfit this Big Data and transform it into a powerful wellspring of business strength. Big Data is enabling joint analysis of clinical and pre-clinical information from various sources and lends transparency to translational research to achieve personalized Medicine.

In 2018, Big Data merchants have pocketed almost $4.7 Billion from hardware, software and professional administrations incomes in the medicinal services, healthcare, and pharmaceutical industry. These ventures are further anticipated that would grow at a CAGR of around 12% throughout the following three years. Enormous Data in the Healthcare and Pharmaceutical Market will represent more than $7 Billion before the finish of 2021, says Recent Study.
Owing to this growth the pharma industry is becoming increasingly patient-centric and realizing the value of patient outcomes, improved safety, and efficacy, connected research and care through largest data insights.

The growing adoption of Big Data technological advancements has likewise realized a variety of advantages for hospitals and other healthcare facilities. In view of feedback from healthcare providers around the world, these include but are not limited to cost savings in the range of 20-30%, growth in patient access to administrations by over 35%, development in income by up to 30%, a decrease in emergency visits by 10%, a drop in patient hold up times by 30-60%, changes in results by as much as 20%, a 10-50% decline in death rates for conditions such as heart failure, and a reduction in the occurrence of hospital-acquired and surgical site infections by nearly 60%.

 

IBM use cases for Big Data:

How much data a business has today and how quickly that information is developing can possibly result in an exceptionally costly IT bill. These financings include system administrators, software licenses, on-premises or deject storage, networking, security, and more. his is no small investment, but compared to the cost of losing data or having to pause business operations and applications, this price tag makes more sense.

Coding: Big data pharma data

 










    AS (npi, nppes_provider_last_org_name, nppes_provider_first_name,


    nppes_provider_mi, nppes_credentials, nppes_provider_gender,


    nppes_entity_code, nppes_provider_street1, nppes_provider_street2,


    nppes_provider_city, nppes_provider_zip, nppes_provider_state,


    nppes_provider_country, provider_type, medicare_participation_indicator,


    place_of_service, hcpcs_code, hcpcs_description, line_srvc_cnt,


    bene_unique_cnt, bene_day_srvc_cnt, average_medicare_allowed_amt, stdev_medicare_allowed_amt,


    average_submitted_chrg_amt, stdev_submitted_chrg_amt, average_medicare_payment_amt,


    stdev_medicare_payment_amt);


    


physician_records = LOAD '/user/psajjan/OPPR_ALL_DTL_GNRL_12192014.csv' USING org.apache.pig.piggybank.storage.CSVExcelStorage()


    AS (general_transaction_id, Program_Year, payment_publication_date,


    submitting_applicable_manufacturer_or_applicable_gpo_name, covered_recipient_type, teaching_hospital_id,


    teaching_hospital_name, physician_profile_id, physician_first_name,


    physician_middle_name, physician_last_name, physician_name_suffix,


    recipient_primary_business_street_address_line1, recipient_primary_business_street_address_line2, recipient_city,


    recipient_state, recipient_zip_code, recipient_country, recipient_province,


    recipient_postal_code, physician_primary_type, physician_specialty, physician_license_state_code1,


    physician_license_state_code2, physician_license_state_code3, physician_license_state_code4,


    physician_license_state_code5, product_indicator, name_of_associated_covered_drug_or_biological1,


    name_of_associated_covered_drug_or_biological2, name_of_associated_covered_drug_or_biological3,


    name_of_associated_covered_drug_or_biological4, name_of_associated_covered_drug_or_biological5,


    ndc_of_associated_covered_drug_or_biological1, ndc_of_associated_covered_drug_or_biological2,


    ndc_of_associated_covered_drug_or_biological3, ndc_of_associated_covered_drug_or_biological4,


    ndc_of_associated_covered_drug_or_biological5, name_of_associated_covered_device_or_medical_supply1,


    name_of_associated_covered_device_or_medical_supply2, name_of_associated_covered_device_or_medical_supply3,


    name_of_associated_covered_device_or_medical_supply4, name_of_associated_covered_device_or_medical_supply5,


    applicable_manufacturer_or_applicable_gpo_making_payment_name, applicable_manufacturer_or_applicable_gpo_making_payment_id,


    applicable_manufacturer_or_applicable_gpo_making_payment_state, applicable_manufacturer_or_applicable_gpo_making_payment_country,


    dispute_status_for_publication, total_amount_of_payment_usdollars, date_of_payment, number_of_payments_included_in_total_amount,


    form_of_payment_or_transfer_of_value, nature_of_payment_or_transfer_of_value, city_of_travel, state_of_travel, country_of_travel,


    physician_ownership_indicator, third_party_payment_recipient_indicator, name_of_third_party_entity_receiving_payment_or_transfer_of_value,


    charity_indicator, third_party_equals_covered_recipient_indicator, contextual_information, delay_in_publication_of_general_payment_indicator);







                        -- Medicare records


filtered_medicare = FOREACH(FILTER medicare_records BY hcpcs_code == '93015')


                    GENERATE nppes_provider_street1, nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;     







medicare_hash = FOREACH filtered_medicare


                 GENERATE REPLACE(nppes_provider_street1, '#', '') as nppes_provider_street1, REPLACE(nppes_provider_street2, '#', '') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_periods = FOREACH  medicare_hash GENERATE REPLACE(nppes_provider_street1,'\\.','') as nppes_provider_street1, REPLACE(nppes_provider_street2,'\\.','') as nppes_provider_street2, REPLACE(nppes_provider_city, '\\.', '') as nppes_provider_city, REPLACE(nppes_provider_state, '\\.', '') as nppes_provider_state, average_submitted_chrg_amt;        







medicare_space = FOREACH medicare_periods


                 GENERATE REPLACE(nppes_provider_street1, '\\s+', ' ') as nppes_provider_street1, REPLACE(nppes_provider_street2, '\\s+', ' ') as nppes_provider_street2, REPLACE(nppes_provider_city, '\\s+', ' ') as nppes_provider_city, REPLACE(nppes_provider_state, '\\s+', ' ') as nppes_provider_state, average_submitted_chrg_amt;


                    


medicare_trim_spaces = FOREACH medicare_space


                    GENERATE TRIM(nppes_provider_street1) as nppes_provider_street1, TRIM(nppes_provider_street2) as nppes_provider_street2, TRIM(nppes_provider_city) as nppes_provider_city, TRIM(nppes_provider_state) as nppes_provider_state, average_submitted_chrg_amt;







            


medicare_upper = FOREACH medicare_trim_spaces


                    GENERATE UPPER(nppes_provider_street1) as nppes_provider_street1, UPPER(nppes_provider_street2) as nppes_provider_street2, UPPER(nppes_provider_city) as nppes_provider_city, UPPER(nppes_provider_state) as nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_ste = FOREACH medicare_upper GENERATE REPLACE(nppes_provider_street1,'SUITE','STE') as nppes_provider_street1, REPLACE(nppes_provider_street2,'SUITE','STE') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;


                    


medicare_abb_st = FOREACH   medicare_abb_ste GENERATE REPLACE(nppes_provider_street1,'STREET','ST') as nppes_provider_street1, REPLACE(nppes_provider_street2,'STREET','ST') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_blvd = FOREACH medicare_abb_st GENERATE REPLACE(nppes_provider_street1,'BOULEVARD','BLVD') as nppes_provider_street1, REPLACE(nppes_provider_street2,'BOULEVARD','BLVD') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_rd = FOREACH   medicare_abb_blvd GENERATE REPLACE(nppes_provider_street1,'ROAD','RD') as nppes_provider_street1, REPLACE(nppes_provider_street2,'ROAD','RD') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_apt = FOREACH  medicare_abb_rd GENERATE REPLACE(nppes_provider_street1,'APARTMENT','APT') as nppes_provider_street1, REPLACE(nppes_provider_street2,'APARTMENT','APT') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_ave = FOREACH  medicare_abb_apt GENERATE REPLACE(nppes_provider_street1,'AVENUE','AVE') as nppes_provider_street1, REPLACE(nppes_provider_street2,'AVENUE','AVE') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_bldg = FOREACH medicare_abb_ave GENERATE REPLACE(nppes_provider_street1,'BUILDING','BLDG') as nppes_provider_street1, REPLACE(nppes_provider_street2,'BUILDING','BLDG') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_dept = FOREACH medicare_abb_bldg GENERATE REPLACE(nppes_provider_street1,'DEPARTMENT','DEPT') as nppes_provider_street1, REPLACE(nppes_provider_street2,'DEPARTMENT','DEPT') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_ln = FOREACH medicare_abb_dept GENERATE REPLACE(nppes_provider_street1,'LANE','LN') as nppes_provider_street1, REPLACE(nppes_provider_street2,'LANE','LN') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_plz = FOREACH medicare_abb_ln GENERATE REPLACE(nppes_provider_street1,'PLAZA','PLZ') as nppes_provider_street1, REPLACE(nppes_provider_street2,'PLAZA','PLZ') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_rdg = FOREACH medicare_abb_plz GENERATE REPLACE(nppes_provider_street1,'RIDGE','RDG') as nppes_provider_street1, REPLACE(nppes_provider_street2,'RIDGE','RDG') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_dr = FOREACH medicare_abb_rdg GENERATE REPLACE(nppes_provider_street1,'DRIVE','DR') as nppes_provider_street1, REPLACE(nppes_provider_street2,'DRIVE','DR') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_pkwy = FOREACH medicare_abb_dr GENERATE REPLACE(nppes_provider_street1,'PARKWAY','PKWY') as nppes_provider_street1, REPLACE(nppes_provider_street2,'PARKWAY','PKWY') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_vly = FOREACH medicare_abb_pkwy GENERATE REPLACE(nppes_provider_street1,'VALLY','VLY') as nppes_provider_street1, REPLACE(nppes_provider_street2,'VALLEY','VLY') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







medicare_abb_pl = FOREACH medicare_abb_vly GENERATE REPLACE(nppes_provider_street1,'PLACE','PL') as nppes_provider_street1, REPLACE(nppes_provider_street2,'PLACE','PL') as nppes_provider_street2, nppes_provider_city, nppes_provider_state, average_submitted_chrg_amt;







grouped_filtered_medicare = FOREACH(GROUP medicare_abb_pl BY (nppes_provider_street1, nppes_provider_street2, nppes_provider_city, nppes_provider_state) PARALLEL 1)


                    GENERATE FLATTEN(group), AVG(medicare_abb_pl.average_submitted_chrg_amt) AS medicare_billings;












                    -- Pharmaceutical records


physician_hash = FOREACH physician_records


                 GENERATE REPLACE(recipient_primary_business_street_address_line1, '#', '') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2, '#', '') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;


                    


physician_periods = FOREACH physician_hash GENERATE REPLACE(recipient_primary_business_street_address_line1, '\\.', '') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2, '\\.', '') as recipient_primary_business_street_address_line2, REPLACE(recipient_city, '\\.', '') as recipient_city, REPLACE(recipient_state, '\\.', '') as recipient_state, total_amount_of_payment_usdollars;                                                    


                    


physician_space = FOREACH physician_periods


                    GENERATE REPLACE(recipient_primary_business_street_address_line1, '\\s+', ' ') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2, '\\s+', ' ') as recipient_primary_business_street_address_line2, REPLACE(recipient_city, '\\s+', ' ') as recipient_city, REPLACE(recipient_state, '\\s+', ' ') as recipient_state, total_amount_of_payment_usdollars;           







physician_trim = FOREACH physician_space


                    GENERATE TRIM(recipient_primary_business_street_address_line1) as recipient_primary_business_street_address_line1, TRIM(recipient_primary_business_street_address_line2) as recipient_primary_business_street_address_line2, TRIM(recipient_city) as recipient_city, TRIM(recipient_state) as recipient_state, total_amount_of_payment_usdollars;







physician_upper = FOREACH physician_trim


                    GENERATE UPPER(recipient_primary_business_street_address_line1) as recipient_primary_business_street_address_line1, UPPER(recipient_primary_business_street_address_line2) as recipient_primary_business_street_address_line2, UPPER(recipient_city) as recipient_city, UPPER(recipient_state) as recipient_state, total_amount_of_payment_usdollars;







physician_abb_ste = FOREACH physician_upper GENERATE REPLACE(recipient_primary_business_street_address_line1,'SUITE','STE') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'SUITE','STE') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;


                    


physician_abb_st = FOREACH  physician_abb_ste GENERATE REPLACE(recipient_primary_business_street_address_line1,'STREET','ST') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'STREET','ST') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_blvd = FOREACH physician_abb_st GENERATE REPLACE(recipient_primary_business_street_address_line1,'BOULEVARD','BLVD') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'BOULEVARD','BLVD') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;


        


physician_abb_rd = FOREACH  physician_abb_blvd GENERATE REPLACE(recipient_primary_business_street_address_line1,'ROAD','RD') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'ROAD','RD') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_apt = FOREACH     physician_abb_rd GENERATE REPLACE(recipient_primary_business_street_address_line1,'APARTMENT','APT') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'APARTMENT','APT') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_ave = FOREACH     physician_abb_apt GENERATE REPLACE(recipient_primary_business_street_address_line1,'AVENUE','AVE') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'AVENUE','AVE') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_bldg = FOREACH physician_abb_ave GENERATE REPLACE(recipient_primary_business_street_address_line1,'BUILDING','BLDG') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'BUILDING','BLDG') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_dept = FOREACH physician_abb_bldg GENERATE REPLACE(recipient_primary_business_street_address_line1,'DEPARTMENT','DEPT') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'DEPARTMENT','DEPT') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_ln = FOREACH physician_abb_dept GENERATE REPLACE(recipient_primary_business_street_address_line1,'LANE','LN') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'LANE','LN') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_plz = FOREACH physician_abb_ln GENERATE REPLACE(recipient_primary_business_street_address_line1,'PLAZA','PLZ') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'PLAZA','PLZ') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_pl = FOREACH physician_abb_plz GENERATE REPLACE(recipient_primary_business_street_address_line1,'PLACE','PL') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'PLACE','PL') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_rdg = FOREACH physician_abb_pl GENERATE REPLACE(recipient_primary_business_street_address_line1,'RIDGE','RDG') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'RIDGE','RDG') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_dr = FOREACH physician_abb_rdg GENERATE REPLACE(recipient_primary_business_street_address_line1,'DRIVE','DR') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'DRIVE','DR') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_pkwy = FOREACH physician_abb_dr GENERATE REPLACE(recipient_primary_business_street_address_line1,'PARKWAY','PKWY') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'PARKWAY','PKWY') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;







physician_abb_vly = FOREACH physician_abb_pkwy GENERATE REPLACE(recipient_primary_business_street_address_line1,'VALLY','VLY') as recipient_primary_business_street_address_line1, REPLACE(recipient_primary_business_street_address_line2,'VALLY','VLY') as recipient_primary_business_street_address_line2, recipient_city, recipient_state, total_amount_of_payment_usdollars;


        


grouped_physician = FOREACH(GROUP physician_abb_vly BY (recipient_primary_business_street_address_line1, recipient_primary_business_street_address_line2, recipient_city, recipient_state) PARALLEL 1)


                    GENERATE FLATTEN(group), SUM(physician_abb_vly.total_amount_of_payment_usdollars) AS pharmaceutical_payments;


                


                


joined_filtered_records = JOIN grouped_filtered_medicare BY (nppes_provider_street1, nppes_provider_street2, nppes_provider_city, nppes_provider_state),


                                grouped_physician BY (recipient_primary_business_street_address_line1, recipient_primary_business_street_address_line2, recipient_city, recipient_state);


--final_records = FOREACH joined_filtered_records GENERATE recipient_primary_business_street_address_line1, recipient_primary_business_street_address_line2, recipient_city, recipient_state, grouped_filtered_medicare::medicare_billings, grouped_physician::pharmaceutical_payments;                             


final_records = FOREACH joined_filtered_records GENERATE grouped_filtered_medicare::medicare_billings, grouped_physician::pharmaceutical_payments;







STORE final_records INTO '/user/psajjan/output' USING org.apache.pig.piggybank.storage.CSVExcelStorage(',','NO_MULTILINE','WINDOWS');




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