POV Healthcare Payer Medical Informatics and Analytics

© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Frank Wang, WW Healthcare and Life Sciences

Healthcare Payer Medical Informatics and Analytics

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THE FACES OF HEALTHCARE Anatomy of a medical transaction

Emotional… Complex… Fragmented… Paper-based

Source: Life Magazine

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Healthcare Client Needs are Changing to Address Drivers

Cost Reduction

Consumer Engagement

Interoperability

Business Intelligence

Management

Data Management

• Pressure to reduce operating costs due to restrictions on Medial Loss Ratios• Health Exchange-enabled Individual market requires a low cost structure • Health plans will need to re-allocate capital to new product and growth initiatives• Claims processing system modernization becomes increasingly important

• Consumerism and Individual Markets are shifting the business model• Increased number of Medicare and Medicaid membership• Multi-channel customer engagement is needed• Cloud CRM

• Accountable Care Organizations will require new partnerships with providers • Greater alignment of incentives among pharma, health plans and health providers

requires collaboration • Global Network Infrastructure expansion to support growing business needs and

industry interconnectivity

• Health plans and their partners will need to manage significantly more health data • Dashboards and other insight tools can reduce operational costs• Social network analytics is emerging • Real Time Data/Knowledge in support of Strategic Decision Making

• ICD-10 is impacting critical applications and infrastructure • Individuals moving between plans increase demand for data security and integrity• Connectivity with individual end-point devices (tablets, smart phones) require increased

data security• New healthcare delivery models in support of evidence-based medicine and

personalize medicine yield data types unfamiliar to most payers

Presenter

Presentation Notes

Companies are quickly attempting to implement changes to address the drivers to defend and grow their market share. Continued pressure to reduce costs, focusing on strategic efforts and growth. Connection with clients at the individual level, responsive and informative and ease of use. Business model flexibility allowing interoperability between providers, payers, and pharma international units Ability to analyze data and drive effective decisions, real time, to the point of modeling business scenarios Explosion of data, not just where to store it, but how to manage and feed the BI capability, and SECURELY process and manage this data. Life Science : *Globalization Efforts in the Life Science Industry Will Continue to Grow and Expand, with Key Drivers Shifting from Cost Savings to Emerging Market Opportunities *Pharma CRM Will Go to the Cloud and Will Not Look Back *Mobile Technologies Will Become a Significant Contributor to Growth and Productivity Across the Life Science Industry *Hosted and Software as a Service Will Grow Rapidly as the Preferred Approach to Application and Solution Delivery in Pharmaceutical R&D *Data Integration Investments Will Finally Begin to Deliver Results as Companies Begin to Routinely Access Corporate Data Resources on a More Real-Time Basis and Extract Applicable Knowledge in Support of Strategic Decision Making *Investment in Global Network Infrastructure Will Expand to Support Growing Business Needs and Industry Interconnectivity *Translational Research Will Become a Mainstream Part of New Drug Development with Major New Insights Driving New Therapeutic Approaches to Disease Management *Pharmaceutical Manufacturers Will Step Up Product Serialization Efforts, with At Least 50% of the Industry Fully Serializing One or More Product Lines Down to the Item Level by the end of 2011

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BUSINESS VALUE ANALYSIS OF INFORMATION MANAGEMENT IN HEALTHCARE

ULTIMATE BUSINESS GOAL Speed Innovation to Practice Improve Quality of CareImprove Operational Efficiencies

COST CONTAINMENT---------------------------

Cut Operating Expense

QUALITY OF CARE----------------------------

Minimizing Medical Errors

COMPLIANCE----------------------------

100% compliance (HIPAA, HITECH etc.)

PATIENT THROUGHPUT---------------

Increase: 10% per year

ULTIMATE BUSINESS GOAL

EXECUTIVE KPIs(Direction)

COST x Claim-------------

Decrease

ERROR RATE---------------

Errors: 0% in 5 years

In-patients per bed per year

----------------------------Increase

COST x Bill-------------

Decrease

CORE KPIs(Direction)

LENGTH OF STAY----------------------------

Decrease

BUSINESS INITIATIVES(Strategy/Priority Language)

Improve efficiency of Clinical decision making and

Emergency services

Improve quality of healthcare services while reducing costs

Manage information for efficiency and compliance

Improve diagnostic process efficiency and patient data

integration

OPERATING KPIs--------------------PROCESS/ FUNCTION

Reduce time frame of medical service delivery and emergencyPatient response.--------------Improve clinical decision support and information sharing among healthcare stakeholders

Reduce diagnostic imaging/ data complexity ------------------Improve access to diagnostic information across clinical department

SAMPLESOLUTION

Enable new care management and risk modeling applications------------------Improve access to patient information from disparate sources

Design, develop and deliver a web-based interface for

information sharing

Implement cost effective storage optimization and scalable data

protection

Construct a single data ware-house to enable leveraging of

information as a corporate asset

Implement cost effective PACS/RISS integration

Mitigate potential data loss without a cost increase--------------Optimize storage capacity while protecting ‘business critical’ data

ROA(Asset Utilization)---------------Increase

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The journey to accountable care requires a Healthcare IT Transformation across the entire community of care

IntegratedHealthSystem

OptimizedHealthcareIT System

PhysicianOffice

Hospitalsand

Clinics

LabFacilities

LongTermCare

Facility

Government/Commercial

Payors

ImagingCenter

HomeHealth

OutpatientSurgeryCenter

Pharmacy/PBMs

Healthcare Transformation IT Requirements • Upgrade, automate and connect

healthcare IT systems across acute, ambulatory, clinic and home settings

• Deliver an integrated clinical and financial view of a patient on demand

• Deploy “collaborative” systems to enable “team” based community care

• Establish Business intelligence platforms for reporting, outcomes measurement and disease management

• Accelerate standardization and cost take out activities ahead of new system installs

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The 8 Building Blocks of Successful Accountable HealthcarePa

y fo

r Rep

ortin

gPa

y fo

r Out

com

es

EHR/PMS/E-Prescribing 2. Automating and Integrating Fragmented Stakeholders

InformationExchange

(HIE)3. Sharing Clinical, Operations and Financial Information

Aggregation &Analytics 4. Aggregating Siloed Data and Gaining Insight

DecisionSupport 5. Transforming collected data into clinical knowledge

HealthcarePortals and

Medical Homes6. Making clinical information accessible and “team-based” care

possible

OutcomesMeasurement &

Reporting7. Establishing Core Measures and Reporting Outcomes

RiskSharing 8. Enabling Population Based Management and Risk Sharing Models

ConvergedMedical

Infrastructure1. Establishing Standardized and Optimized IT Platforms

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Healthcare Payer Informatics and Analytics Solution Landscape

Unique Individual

- Member, Provider,

Agent, etc.

Claims

Fees

Lab

Member

Premium

Eligibility

EBM

Groupers

CM/WMProgram

EMR

Risk

Care Management / Medical ManagementProgram

EffectivenessOutcomes Analytics

Population Analysis

CM/DM/WM Analysis

Case Management

Outcomes

Member Engagement

HEDIS

Pay 4 Performance

Bundled PmtAnalytics

Shared Savings

Cost Trends

Market Analytics

Employer Engagement

Provider Engagement

ACO

HIE

HIX

Sales Forces Analytics

NCQA

many more…

Account Management

CMS

State Reporting

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Cost and Revenue AnalyticsUnderstand your financial metrics and trend analysis

Multi-faceted

• Fraud, underwriting, MLR, clinical and coding guideline

Timely

• Reporting at the time of processing claims or claim submission

What-if Scenario

• Leverage “what-if” analysis to identify effective responses to cost drivers

Presenter

Presentation Notes

Cost & Revenue Intelligence Cost and Revenue Intelligence is a broad set of offerings covering cost identification, cost trending and containment, internal admin costs, fraud, underwriting – (pricing your policies to a point where you won’t lose money from claims because of premiums set) You need to identify and understand what drives the costs to your organization– a service, particular provider group, product, location, industry, employer… What is driving up costs for your company? Is it a particular service? Particular provider group? Particular product, particular location, particular industry, or particular employer…. You need to be able to analyze right from high-level cost information to the detail that enables you to respond appropriately. And we’ll come back to actionable analytics…there’s no point understanding what drives costs but not knowing what response is needed. So, let’s provide actionable analytics embedded in business processes, take that action, and then measure the impact of that response. Operational Business Intelligence will be central to Healthcare Payers’ efforts to drive down costs and meet new legislative mandates. Operational BI should play a key role in understanding cost drivers and improving efficiency. The other piece of this get to it from the earliest onset… this means that analytics is done at the time of processing claims or claim submission, not after payment…. This ensures immediate call to action where the ROI is much more…. You can better capture fraud this way than post-payment. Our customers are increasingly interested in our help to align funding and payment with best practices and incentives for high quality clinical care. Pay for performance analytics is of key importance here. ************************ Additional notes Rising costs in the administration of healthcare as well as the cost of providing healthcare services are key factors behind the cost of U.S. healthcare. Payers are under increasing pressure to contain the cost of healthcare services provided to patients and additionally improve the efficiency of their own internal administration to bring down costs. Providers feel the pressure from providers to cut costs and work more efficiently. Pharmaceutical companies operate in a tough environment with few drugs making it through the R&D pipeline and fewer FDA approvals – most are taking radical steps to reduce costs across their organization. To achieve this all companies need to modernize the administrative and transactional aspects of health care. Payer Cost and Utilization Analysis. Often considered the “bread and butter” of healthcare business intelligence, cost and utilization reports should not be overlooked. Cost and utilization reports typically cover: Claims volume Claims lag Claims with errors Per Member Per Month (PMPM) or Per Employee Per Month (PEPM) for those reports that go to employer groups. Total membership (eligible) Utilizing membership All of these stats are good information, but one thing that most cost and utilization reports fail to have is the “so what” factor – the call to action for the report recipient so they know what key item they should be focusing on next month. That is something that BIS would provide – turning the insight into action, so to speak. We should also consider how collaborative technologies could be used to ensure easy sharing of key action items that involve multiple people/organizations.

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Supporting the BI needs of Healthcare Payers as they engage members in ongoing care management along the health continuum

Care Management Model

EvaluateMeasure outcomes and

adjust performanceIntervene

Targeted, evidence based methods to

impact the member’s condition

and health

Enroll Incentivize and engage members to participate

Identify & TargetRight member; right program

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2

3

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Presenter

Presentation Notes

So what are the typical steps that our solution supports as Healthcare Payers engage members in ongoing care management? Firstly it’s a matter of identifying and targeting the right members with the right programs and understanding where to prioritize your Care Management program spend. Second, you have to understand your members well enough to target them with the right incentives that will get them to participate in your Care Management initiatives – bringing in their employers to support programs is one way of aiding this. Third, you have to intervene in your members healthcare treatment at the point that will yield the best results for you and the member. This is where liaison with healthcare providers is absolutely key. Lastly, you must have a continuous process of evaluation and improvement for your programs that will lead to you doing a better job of identifying and targeting members in future.

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Care Management Portal

Member-centric

•Member-centric view tracking and reporting members’ health conditions, goals, recommended interventions and outcomes so that care managers can assess overall program effectiveness

Integration

•Integrates with claims data to identify members with existing or developing chronic diseases, calculates treatment plan cost savings, and track results

Easy to use•An easy to use care management portal

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Care management to reduce hospital readmission ratesCare Management

– Fraud, underwriting, cost trending, general admin costs; clinical and coding guidelines

– Identify and analyze your cost drivers

– Reporting at the time of processing claims or claim submission

– What do you do next?

– Leverage ‘what-if’ analysis to identify effective responses to cost drivers

– Analyze fraud patterns pre-payment and streamline response; early intervention

Comprehensive

•From prevention to long-term chronic disease maintenance

Predictable

•Predictive modeling at patient and population levels to reduce hospital readmission rates

Multiple data sources

•Leverage many different data sources

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Use Case: Stratification for Care Intervention

Mr. HP1 – 20 years, blood pressure 120 / 80

Mr. HP2 – 30 years, blood pressure 140 / 90, 15 lbs overweight, borderline high fasting blood sugar (115 mg/dl)

Mr. HP3 – 40 years, blood pressure 155 / 110, 50 lbs overweight, repeated high fasting blood sugar (140 mg/dl )

Is at risk of developing a chronic condition that can be minimized through better understanding and improved self care. He has a medium risk score. He is placed into a Disease Management program to optimize blood pressure control, achieve moderate weight reduction, and incorporate dietary modification.

Has a chronic condition that puts him at high risk for getting progressively worse. In this case, preventing or slowing progression is the goal. He is placed in a Case Management (CM) program.

The challenge is to correctly assess who is at risk, quantify the risk, then match the individual with the best care intervention.Is healthy and thus has a very low risk

score. Based on this, he is directed to the Wellness program.

Presenter

Presentation Notes

I want to use a case study of three patients to guide you through the Care Management processes that the solution enables – (Read through notes)

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Use Case – Case Management

– Identifying High Risk High Cost (HRHC) Members

• Identify members who are at high risk for experiencing decreased health or likely to incur high dollar cost for treatments.

• Separate long-term HRHC members (advanced chronic disease suffers) from one time high cost members (trauma)

• Stratify long-term HRHC members in order to assign appropriate intervention by Case Management (CM)

– Benefit• Lower immediate costs

• Much lower long term cost (bend the trend)

• Target intervention by Case Mangement to improve member health, keep the member healthier for longer period of time, delay the worsening of health.

Insurance Performance – Case Management

MemberID

Firstname

LastName Age Total Cost Expected Amount

Year 2

1 De-ID De-ID 60 $10,565 $109,051.00

2 De-ID De-ID 61 $27,013 $78,934.00

3 De-ID De-ID 50 $28,805 $51,971.00

4 De-ID De-ID 59 $8,372 $66,154.00

5 De-ID De-ID 86 $17,674 $65,604.00

6 De-ID De-ID 61 $420,318 $14,575.00

7 De-ID De-ID 55 $29,925 $48,609.00

8 De-ID De-ID 54 $4,828 $55,133.00

9 De-ID De-ID 87 $5,161 $55,062.00

10 De-ID De-ID 5 $620,887 $5,570.00

One time event (Blue)

• Little impact for future•Goal: encourage healthy behavior

Continued progression (Yellow)

• Slow progression, moderate affect long term costs•Goal: Extend time the member feels healthy

Sudden change for the worse (Red)

• Rapid progression into disease, large affect on long-term costs

•Goal: Stop or moderate descent into disease

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Utilization Management (UM)

Appropriateness

•Reviews prior authorization, eligibility, benefits limits and services limits

Necessity

•Provides concurrent and retrospective reviews based on evidence-based guidelines, clinical criteria (InterQual, Milliman, Solucient)

Efficiency

•Proactively manages therapeutic duplication, level of care and length of services

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Disease Management and Wellness Management

Segment and Predict

•Segments and predicts specific illness such as heart conditions, diabetes and depression

Wellness Plan

•Member centric wellness management including health risk assessment, patient education

Cost Containment

•Develop short- and long-term cost control machnism

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Cost Containment Findings

Provider #

Count Provider Name Specialty Total $

1 4836 Bing, Mark Family Practice $160,833

2 4342 Yahoo, Charles Psychiatry $143,490

3 2732 East End Urgent Care URGENT Family Practice $90,479

4 2602 Place, First MD General Practice $63,892

5 1724 Swat, Edward MD Anesthesiology $56,696

6 4312 Smith, Gregory E DPM Podiatry $54,597

7 3836 Man, Super G DPM Podiatry $49,796

8 1615 Riley, James R MD Plastic Surgery $37,970

9 3243 Avian, Bird DPM Podiatry $37,327

10 2513 Copper, Metal H DPM Podiatry $32,668

Reduce costs by identifying and eliminating un-necessary procedures

Necessity• Is the procedure necessary

Savings

•How large is the potential saving and what is the estimated cost/benefit ratio?

Nail Debridement

•Nail debridement clinical guidelines. Only 2 of 5 are directly tied to a disease •Relief of pain•Treatment of infection (bacterial, fungal and viral)•Temporary removal of an anatomic deformity …•Exposure of subungal condition …•Prophylactic measure to prevent further problems …

Fraud and Abuse DetectionAdditional investigation needed

Provider #

Count Provider Name Specialty Total $

1 4836 Bing, Mark Family Practice $160,833

2 4342 Yahoo, Charles Psychiatry $143,490

3 2732 East End Urgent Care URGENT

Family Practice $90,479

4 2602 Place, First MD General Practice $63,892

5 1724 Swat, Edward MD Anesthesiology $56,696

6 4312 Smith, Gregory E DPM

Podiatry $54,597

7 3836 Man, Super G DPM Podiatry $49,796

8 1615 Riley, James R MD Plastic Surgery $37,970

9 3243 Avian, Bird DPM Podiatry $37,327

10 2513 Copper, Metal H DPM Podiatry $32,668

Provider1

• Charges significantly higher than his peers

Provider 2

• Specialized in psychiatry, and is not generally associated with nail debridement

Provider 5

• Practiced in a specialty that is not generally associated with the nail debridement procedure

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Fraud and Abuse (F&A) Detection by Profiling Providers

Ranking Top 5 Codes by Quantity for Provider: GR0000000 – ABC Medical Group, Inc

6 Months of Service xx/xx-yy/yy, Paid in Months xx/xx-yy/yy

GR0000000Qty Rank and % Compared to

OB/GYN Groups6 Month Peer

Averages

Code Code DescTotal Dollars

Paid

Total Qty Adj Rank

% of Total Qty

Total #

Provs

Peer Avg Dollars Paid

Peer Avg Qty

81025-TC Urine pregnancy test $12,560.60 2,710 #1 or 19% 65 $1,022.93 220

Z9752Family planning counseling (15 minutes) $33,086.45 1,735 #1 or 21% 55 $2,778.90 149

Z6410Perinatal education, individual, each 15 minutes $9,511.71 1,131 #9 or 3% 91 $3,657.38 435

Z6204

Follow-up antepartum nutrition assessment, treatment and/or intervention; individual, each 15 minutes $7,569.00 900 #5 or 4% 96 $2,074.14 247

Z1034 Antepartum follow-up visit $48,625.92 804 #16 or 2% 195 $11,996.08 203

Outlier detection based on Provider profiles. Highlighted cells suggest further investigation.

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Health Information Exchange

Singular•Houses data from many clinical data sources in

a secure central structure

Enabling

•Enables key functions that reduces costs (reduced repeated testing, reduced risk of adverse events) and improves coordination of care

Payer

•Some HIE use cases have focus on sending ADTs (admissions, discharges, transfers) and discharge summaries to the health plans in lieu of manual processing

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HIE DISTRIBUTION LAYER BUILT FOR GROWTH

Collaborate regionally and cross- border with other statesOffer clear guidance and flexible access to consumers, employers, payers pharmas

Presenter

Presentation Notes

Start towards assist Medical Home, Continuum of Care: Care Management Scalable, open architecture, allows expansion – EMPI – Comply with NHIN standards, secure, level of comfort for users Internet-based, securely use the public network with proper validation/credentialling in a secure zone. Medication Management to promote meaningful use. Allows the pharmacist, providers to use functionality, share data, knowledge enhancing features (e.g., care management insight to monitor usage)

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Timely

•Analyze compliance data ahead of time to highlight problems before submission

Streamlined

•Easier to locate, access and report; new reports can be added quickly to increase regulatory adherence

Actionable

•Provide further drilldowns to identify root-causes in order to take actions to rectify the issues

Compliance Streamlining

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Transform readily available, everyday data into actionable knowledge

Healthcare Payer Medical Informatics

Eligibility

– Clinical expertise– Statistical tools– Data mining– Predictive analytics– Research methods– Database

technologies– Published papers

Optimize Quality

MedicalInpatient & Outpatient

Pharmacy

Data Sources (Structured and Unstructured)

Labs

Demographics

Medical Records

Surveys

Health Risk Assessments

Seamless Information Exchange

EnhanceCollaborative

Care

CostContainment

Enhance Health

Outcomes

PopulationHealth

Analysis

PreventFraud

Medical Informatics

Possible Actionsto Take

Presenter

Presentation Notes

Point out the multiple number of inputs that we can work with, mention we have significant experience merging disparate databases, and that much of this information is readily available. Our models use medical, pharmacy, enrollment, and demographic data while most other models use only a portion of these.

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Predictive ModelingTurning Data into Knowledge – Example

We have 35,000 individuals in our population with diabetes.

The patients cost us $7,000 this year, a 15% increase over last year.

The national prevalence rate for diabetes is 8.3%; ours is 12%.

Hypertension is a major co-morbidity for diabetes.

Assign patient-level risk scores using a statistical model to predict which diabetics will be hospitalized next year.

Efficiently allocate care management resources to help reduce avoidable hospitalizations for at-risk patients.

Wisdom

–actionable info

5

Knowledge

–goals–targets

4

Information

–benchmarks–trends

3

Secondary Data

–averages–rates

2

Primary Data

–counts–sums

1

HP ConfidentialP

Presenter

Presentation Notes

Our comprehensive, innovative approach to fraud analytics combines the use of rules, anomaly detection, predictive models, and network analysis to produce improved detection and cost avoidance. The reports available provide unique insights into provider and beneficiary activity not available in standard reporting. Also, with the frequent updating of this data, the analyst does not need to wait months to detect suspicious activity as with traditional surveillance systems. Discuss an example across the knowledge continuum. Note that at the highest level, we are trying to stop fraud before it even begins – by preventing fraudulent providers or beneficiaries from enrolling in Medicaid. This is a departure from the so-called “pay and chase” model that fraud control units have typically employed.

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Turning Data into Knowledge – ExamplesWisdom

(actionable info)5Knowledge

(goals, targets)4Information

(benchmarks, trends)3Secondary Data

(averages, rates)2Primary Data

(counts, sums)1

A total of 10,000 Medicaid enrollees received mental health services in SFY 2010.

We have 35,000 individuals in our population with diabetes.

Medicare patients cared for by our physicians have an average cost of $8800 per year.

The procedure for internal fetal monitoring was billed multiple times for the same pregnancy.

Mental health services expenditures averaged $400 pmpm in 2009.

The patients cost us $7,000 this year, a 15% increase over last year.

The No. 1 DRG for our hospitalized Medicare patients is chronic heart failure.

This amount has increased by 2% in each of the past three years.

Payments for mental health services to provider X have risen 20% YOY whereas the Statewide average is 5%.

The national prevalence rate for diabetes is 8.3%; ours is 12%. Hypertension is a major co-morbidity for diabetes.

The number of heart failure patients compared to benchmark data is high.

This is not medically justified as the procedure is only performed during active labor to monitor fetal heart rate and uterine activity.

Applying data mining to large data sets, we can automatically detect more fraudulent providers and increase our ROI.

Assign patient-level risk scores using a statistical model to predict which diabetics will be hospitalized next year.

Medicare patients with Class 4 heart failure without a cardiac specialist cost over $50,000.

This procedure was controlled solely by diagnosis, which did not prevent misuse and coding errors.

We will proactively ward off complex sets of fraudulent claims using predictive analytics.

Efficiently allocate care management resources to help reduce avoidable hospitalizations for at-risk patients.

Early referral to a “Heart Failure Specialty Clinic” may lower the Medicare cost profile.

Update medical policy to reimburse fetal internal monitoring in an inpatient setting and establish limits for reimbursement consistency.

HP ConfidentialP

25

Presenter

Presentation Notes

Our comprehensive, innovative approach to fraud analytics combines the use of rules, anomaly detection, predictive models, and network analysis to produce improved detection and cost avoidance. The reports available provide unique insights into provider and beneficiary activity not available in standard reporting. Also, with the frequent updating of this data, the analyst does not need to wait months to detect suspicious activity as with traditional surveillance systems. Discuss an example across the knowledge continuum. Note that at the highest level, we are trying to stop fraud before it even begins – by preventing fraudulent providers or beneficiaries from enrolling in Medicaid. This is a departure from the so-called “pay and chase” model that fraud control units have typically employed.

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Client A Client B Client C

Use Cases

– Client concern• Vendor proposes device for

chronic wound care claiming substantial cost effectiveness

• Need to due diligence

– We researches• Device• Medical literature for wound

care• Develops assessment study

– Our study reveals• potential for significant savings

based on prevalence of wounds

– We recommends• Pilot of new treatment

– Client concern• Is mental health utilization

below norms?

• If so, what financial penalty risk

– We examines• HEDIS methods

• Reviews medical literature for benchmarks

– We executes study• co-morbidities

• utilization trends

• confidence intervals

– Our study reveals• Client in full compliance

• At national norms

• No penalties incurred

– Client concern• Children receiving dangerous

and costly anti-psychotic drugs with no evidence of approved diagnosis

– Our study reveals• Similar disturbing patterns

– We recommends• Physician education, • Care management for patients • Consideration for a prior

authorization program

HP ConfidentialP

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Q&A

Documents

POV Healthcare Payer Medical Informatics and Analytics