The Many Lives of Data

The Many Lives of Data

James H. Willig, MD, MSPHAssociate Professor, Dpt of Medicine

Division of Infectious Disease University of Alabama at Birmingham

Outline for today

The first life – Clinical Intermezzo

The second life – Research Intermezzo

The third life – Enterprise Intermezzo

The value of data

Data Life #1: In the clinical setting

Document in the electronic medical record Some free text: HPI, A&P Some quantifiable fields: Exam, S&S Updates: Medication list, diagnoses/problem list Other sources: VS, laboratories, imaging, pathology, etc.

Good documentation Assists other allied health professionals (Social services, RN,

etc.) Assists other providers: Other specialists, hospital providers, etc. Informs appropriate billing


Accuracy on which we all depend My errors = your problem

Patient safety Failing to document an allergy or an adverse event…. So much for your fancy clinical decision support algorithm… New data published – medication combination no longer safe….

Shared record = shared responsibilities How much time do we talk about data quality?

Documentation of Diagnosis; Accuracy1: 53 to 78%

0

10

20

30

40

50

60

70

80

4 to 5/ 06 6 to 7/ 06 8 to 9/06 10 to 11/06 12/ 06 to 1/ 07

1Accuracy % = Made/Mentioned (changes)

Documentation of medications; Accuracy1: 88-93%

85

86

87

88

89

90

91

92

93

4 to 5/ 06 6 to 7/ 06 8 to 9/06 10 to 11/06 12/ 06 to 1/ 07

1Accuracy % = Made/Mentioned (changes)

Documentation Errors – Medications*

OR 95% CITotal Changes 1.01 0.93 – 1.1

Experience< 6 mo vs > 6 mo

1.6 1.01 – 2.5

Sick call Y vs N 1.6 0.7 – 3.3

Attending vs NP 4.3 2.0 – 9.4

Fellow vs NP 2.5 1.6 – 3.8

*n = 2,078 observations


If you are at all involved in patient care, the first life of data is central to your practice

Shared responsibility for accurate documentation Decisions are only as good as the data they are based on High data quality helps your patient receive better care/service in

your office and throughout the health system My poor documentation may hurt YOUR patient and vice versa High quality data allows you to rapidly ID patients in need of

changed therapy

Take pride in your documentation; Be > copy/paste!

Information integrity – Data quality Establish and maintain a culture of data quality

Add to training! Look for opportunities to provide feedback We do this! Critical review of outside or inpatient records.

Electronic documentation does not uniformly equal quality documentation Local quality as well as centralized quality both have roles (best

sources, best practices, common patterns of errors, etc.) Every dataset is perfect! Until you analyze it…

Systems to gauge data quality need to be in place Others have found solutions - Old concept other industries Break incremental mold, seek interdisciplinary junctions

Intermezzo: What’s the ‘so what’?

40% discharged pts have pending studies neither outpt providers or pts aware of despite requiring action

1 in 5 pts discharged from hospital will suffer an adverse event related to medical management within 3 wks 66% related to medications

Medication discrepancies outpt vs. prescribed at discharge 14% elderly pts with this are rehospitalized within 14 days vs. 6%

without discrepancies When med rec led by pharmacists medication related AEs in 30

days 1% vs. 11% in controls

Closer to home…

Chronic SC pain pump not documented

Admitted for renal failure To MICU (2 days) To floor, teams change next day

Patient complains of pain, PO opiates started Met call Subsequent aspiration pneumonia

Outline for today




The value of data

Data Life #2: Research

In aggregate, your data can be transformed into information

Individual documentation, done in a systematic fashion We all agree on template beforehand We all respect common documentation

Individual level documentation, unlocks population level insights!

1988

Demographic

Therapeutic

Concurrent Treatments

Clinical – HIV/AIDS events

Clinical – Comorbidities

Laboratory – HIV associated

Using REPO# and link to basicDocumentation:

• Collaborative basic science

• Disease pathogenesis

• Laboratory parameters

1988 1995Demographic

Therapeutic





Laboratory – General

Socioeconomic

Health services utilization

Adherence – Self report

• Data collection is manual

• Simple software

• Data accumulating

• Processes established

• MS Access DB started

1988 1995 1999

Demographic

Therapeutic






Socioeconomic



1988 1995 1999 2004Demographic

Therapeutic






Socioeconomic



1988 1995 1999 2004 2008

Demographic

Therapeutic






Socioeconomic



Patient Reported Outcomes

Resistance Data

Interval cohort era

Clinic cohort era begins – 1917 Clinic CPR

Data Life#2: Research 1917 Clinic 2008-2012 Processes put in place to access clinic data

Pace of local research accelerates● 2000-2006: 2.85 manuscripts published per year● 2007-2012: 15.66 manuscripts published per year

Large numbers of new grants and collaborators

New data types added Resistance data, patient reported outcomes data

New data type added 2008: Patient Reported Outcomes

The Medical Record is a relational database!

Innovation Area

Innovation area =

DT x MEDa

ta Ty

pes (

DT)

Methodological Expertise (ME)

Factors associated with 30 day readmission in patients with CHF?

LR

PH

Descriptive

DxLabsDemo Admit Co- morbid

OR

Meds

Demo

Labs

Meds

Dx

Co- morbid

LogisticRegression Admit

The Three Stages and Six Steps of Quantitative Analysis

Keeping up with the quants: your guide to understanding and using analytics. Thomas H. Davenport and Jinho Kim. Harvard business review press 2013.

Logistic Regression model: Outcome is self-reported SI – Yes.1

Unadjusted Adjusted

Age (per 10 years) 0.81 (0.69-0.96) 0.74 (0.58-0.96)

Depression (PHQ9) No Depression (0-4) Mild (5-9) Moderate (10-14) Mod/Severe (15-19) Severe (≥20) Unknown

0.06 (0.02-0.16)1.03.89 (2.16-7.02)9.16 (4.85-17.31)21.70 (11.37-41.43)2.12 (0.23-19.86)

0.08 (0.03-0.21)1.03.91 (2.12-7.22)9.08 (4.67-17.63)25.55 (12.73-51.30)2.05 (0.20-21.64)

Substance Abuse Never Yes – Historical Yes – Current

1.02.60 (1.73-3.90)6.32 (4.06-9.82)

1.01.15 (0.66-1.98)1.88 (1.03-3.44)

1. Model also adjusted for: Gender, race, insurance, location, CD4, alcohol use.2. Published in CID April 2010

PRO data

Advantages Decreased social desirability bias enhances quality of data

captured for sensitive domains Buying data directly from the manufacturer? (Adjunct?) Patient updates status of chronic diagnoses – now rather than

“Yes or No” from problem list, “current, prior, never” Clinical benefits (gain time, layer systems to enhance care) –

implementation into existing workflow is paramount

All research endeavors benefit from new data type

Today… The 1917 Clinic is an international leader in several lines

of research

The 1917 Clinic is a flexible “research platform” where investigators can bring their ideas, run them through our processes and gain quality data to power analyses

Note Growth of a research enterprise tied to data at every step A vision towards growth of data powers continued expansion and

enable clinic to become relevant in a “multicohort world”

How to remain relevant in a multicohort world? Research area = DT x ME

DT = Data types ME = methodological expertise (innovation)

Agility Cruise ships vs. speed boats Don’t get into a pushing contest with a wall

Search out the edges Interdisciplinary interstitium

Outline for today




The value of data

Data Life #3: Enterpise

Enterprise Data Warehouse

POWERINSIGHT

EDUCATION

RESEARCH

PATIENT CAREData

Aggregation

Data Access

DataExploration

Basics: Aims

Hospital/Clinic

Admission Date

MedicalRecordNumber(MRN)

Patient encounter, for a specific admission date, and a specific clinic

Basics: Slice and Dice

Data Life #3: Enterpise

PowerInsight Cerner product Provides a clinical data warehouse

Let’s take a look at some operational questions answered with PowerInsight

37

Clinical Operational Financial

Neurology Patients Tracking

New visits report by various dimensions

Revenue per admission by facility

Diabetic patients with HgA1C > 7

Order sets used by facility and physician

Total charges by payer

Turnaround time for ECG completion

Patients came through ER

Revenue per outpatient per facility

Inpatient admissions by nursing unit

Time between admit order and admission

Admission per health plan organization

Alerts overridden analysis Pastoral care referrals and consults

Revenue summary by health plan

Turnaround time for door to aspirin

Discharges by encounter -summary

Gross revenue by age group, facility, county.

Sample Questions

Why neurology patients end up in off-service beds?

• Is there an association between the time a discharge is entered and the time when a patient

is discharged?

Showcase: Neurology

Showcase: Neurology

Showcase: Neurology

What was the hourly traffic of patients arriving in the ED during a specific month?

• Goal: A need to better plan and allocate resources to better serve incoming patients.

Showcase: Emergency Dept.

Showcase: Emergency Dept.

Research

CSV

PDF

Excel

POWERINSIGHTDATA

Dashboard

Report

Interactive

Custom

Ad Hoc

Oper’tnl Strategic Analytic

PowerInsight = DATA



“Business” Intelligence?

Maybe better titled “Clinical Business Intelligence”

What does that mean to us?• Measuring efficiency • Measuring clinical effectiveness• Measuring safety and quality• Measuring compliance

Outline for today

The first life – Clinical Intermezzo:

The second life – Research Intermezzo:

The third life – Enterprise Intermezzo:

The value of data

How do I play?

The value of data Data are data

Questions are questions

Economists call data a “non-rivalrous” good One person’s use of it does not impede another’s Data can be re-used limitlessly – how much can the information

produced be worth?

Facebook’s worth in 2011 prior to IPO Under accounting standards (equipment, physical assetts) $6.3 B Initial market value $ 104 B. Intangible assets make up gap User’s worth of data estimated at $100. Pt data worth?

http://www.google.com/url?sa=i&source=images&cd=&cad=rja&docid=cBvjefZ9vx7bAM&tbnid=lj-kN3Qrf6w4jM:&ved=0CAgQjRwwAA&url=http://www.how-to-draw-funny-cartoons.com/cartoon-tomato.html&ei=Amw0UvXmL4PA8AT6yoHoCw&psig=AFQjCNFgYQr1fs1ZldFEaDR2lvq2-68zEA&ust=1379253634831328

Examples Wallmart, old sales receipts, hurricanes and PopTarts

“Target,” unscented lotions and reproduction

Value of our misspelling Microsoft Word approach ($$, cross referencing to databases,

etc.). Google approach (did you mean “x”? User teaches system correct spelling)

Credit card companies, others… Data on purchase patterns more important than commissions on

purchases

Three ways to unlock value: Reuse of data Search terms and google flu trends

Outpaces CDC by 1 week, spread to other conditions

Giant AOL hires amazon to handle technology end e-commerce business Seemed like outsourcing, Was data mining to improve

recommendation engine.

Security cameras in stores Now gauging traffic to reorganize store layout, gauge efficacy of

advertising campaigns

Three ways to unlock value: Recombinant Data Do cellphones increase cancer risk? (Thankfully no!)

Danish Cancer Society links nationwide cancer registry to commercial data on all cellphone subscribers since 1987

Hospital readmissions Finding of high prevalence of depression led to expansion of

mental health services

Remember the Innovation Area Data’s true power is unlocked when linked Unexpected correlations await if we can only analyze them…

Three ways to unlock value: Build extensibly Bringing a new tool into our milieu adds value, but

adding a new tool into our network more so

Consider secondary uses of new data source at the outset Google street view cars: capture GPS data, confirm map

information, took pictures of houses and roads Multiple secondary uses from these data streams ongoing



Big data mindset: You are all data scientists Each of you have domain expertise

Think critically on what to “datafy” to add competive advantage Work in teams and support data holders (IT), and data specialists

(statisticians) to bring new insights forward

Remember: “What we are is merely a steppingstone to what we may become1”

1. Deus Ex: Human Revolution, 2012

Framing the problem

Solving the problem

Communicating and acting on result

Equation for getting up in the morning – what’s yours?

X= Patient Care

R = Research I = Informatics

E = Education

XRIE= Lives positively influenced