Identifying and Intervening on High Risk Physicians: The PARS® Project

Center for Patient andProfessional Advocacyat Vanderbilt

Identifying and Intervening on High Risk Physicians: The PARS® Project

Gerald B. Hickson, MDDirector, Center for Patient and Professional Advocacy

Associate Dean for Clinical Affairs

Center for Patient & Professional AdvocacyVanderbilt University School of Medicine

[email protected]/cppa

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The PARS® Project

• Fair, systematic process involves surveillance for all professionals; IDs & intervenes with outliers:• Promotes fair/just culture• Addresses and reduces malpractice risk/cost and

unprofessional behavior• Helps satisfy regulatory requirements

• Can help improve interactions among pts and care providers, leading to better outcomes

• Helps competitive advantage by IDing and helping address threats to reputation and patient safety

PARS® SitesDevelopment SitesProspective SitesMajor Educ. Sites

3Cogent Healthcare


• 1-6%+ hosp. pts injured due to negligence• ~2% of all pts injured by negligence sue• ~2-7 x more pts sue w/o valid claims• Non-$$ factors motivate pts to sue• Some MDs/units attract more suits• High risk today = high risk tomorrow• Unsolicited comment/concerns predict claims• PARS® risk profiles make effective intervention tools

Med Mal Research Background Summary

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Center for Patient andProfessional Advocacyat Vanderbilt6

Four Hypotheses

• Attract a litigation-prone population• Attract medically high-risk patients• Are technically incompetent• Have difficulty “connecting” with pts

Physicians who attract a disproportionate share of malpractice claims:


Perceptions of Care During L&D

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Communication 8 18 27*Care/treatment 5 15 22*Access/availability 7 11 15*Humaneness of Phys 5 6 17*

Hickson GB, et al. JAMA 1994; 272:1583-1587.

Patient Concerns (%) 0 1-3 FreqPhys Lawsuit Hx

* Statistically significant difference

(Open-Ended Questions)


Can high risk physicians be identified by means other than counting

lawsuits?

Unsolicited complaints link to malpractice risk.

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Patient Complaints

• “I had questions about my medical condition and treatment. Dr.__ looked up and asked, ‘Are you illiterate?’ I said, “No.” Dr.__ responded, ‘Oh, I just gave you several pamphlets that explain all of this. Since you didn’t get it, I thought that maybe you were illiterate.’”

• “Dr. __ was rude. I was 7 minutes late and apologized. He looked at his watch and said, ‘That’s 7 minutes I won’t be able to talk with you.’ He seemed very annoyed.”

Academic vs Community Medical Center50% of concerns associated with 9-14% of Physicians

30 35 40 45 50 55 60 65 70 75 80 85 90 95 1000

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50

75

100Academic Med CtrCommunity Med Ctr

% of Physicians

% o

f Con

cern

s

Note: 35-50% are associated with NO concernsHickson, et al., SMJ, 2007; Hickson et al, JAMA. 2002 Jun 12;287(22):2951-7 10Cogent Healthcare


Predictors of Risk Outcomes

• Gender• Physician specialty• Volume of service• Unsolicited patient complaints

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Predictive concordance of risk models ranges from 81-92%

Hickson et al, JAMA. 2002 Jun 12;287(22):2951-7.

(logistic regression)

Incurred Expense By Risk CategoryPredicted Risk

Category# (%)

PhysiciansRelative Expense

% of Total Expense

Score (range)

1 (low) 318 (49) 1 4% 0

2 147 (23) 6 13% 1 - 20

3 76 (12) 4 4% 21 - 40

4 52 (8) 42 29% 41 - 50

5 (high) 51 (8) 73 50% >50

Total 644 (100) 100%

* In multiples of lowest risk groupMoore, Pichert, Hickson, Federspiel, Blackford. Vanderbilt Law Review, 200612


Analysis of Claims and PARS® Risk Score

Specialty Group

# of Physicians

PARS® Risk Score

Specialty Group

Clinical Activity (RVUs)

Med n=684 = .15*** ns = .07 (p<.10)

Surgeons* n=267 = .42*** ns = .10 (p<.10)** p<.01

*** p<.001

Major Medical Center’s Claims AnalysisClaims Data 2000-2008

*Note: =relative weight, so Risk Score was 4.2x more predictive of claims than clinical activity for surgeons


Conceptual Framework – Professionalism• Professionals commit to:

• Technical and cognitive excellence• Professionals also commit to:

• Confidentiality• Clear and effective communication• Modeling respect• Being available

• Professionalism promotes teamwork

Professionalism and Self-Regulation


Professionalism and Self-Regulation

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Professionalism demands self-regulation• Personal

• Discipline specific

• Group

• Systems focused

All require the skills to provide and receive feedback


Critical Questions:

• If you were at high risk and there was a reliable method to identify and make you aware, would you want to know?

• If a member of your group was at high risk and you had a reliable system to identify and provide opportunity for improvement (and risk reduction), would you want her or him to know?

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MMC Forms a Committee

• Are committed to confidentiality• Are respected by colleagues• Are willing to serve (8 hours of training)• Have risk scores that are mostly okay (but at several

sites physicians intervened upon are messengers)• Agree to review, then take data to 1-3 physicians at

request of local messenger committee chair

“Messenger” Physician Peers:

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(Committee formed under existing QA/Peer review)17


Intervention on Dr. __

• Letter with standings, assurances prior to & at meeting• “You are here” graph with

4-yr Risk Scores• Complaint Type Summary

“Concerns bullet list”– Redacted narrative reports

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Representative Complaints by Category

Concern for Patient/Family• I never felt like he cared whether [my spouse] lived or died. He

does NOT live up to your mottoCommunication• He did not keep us informed about my daughter’s condition…

and didn’t answer our questions• “Dr. X offered no information. I felt he was hiding information.

Never even tried to speak to my husband.”• Pt upset with lack of info from Dr. __...no one is able to tell him

what his x-rays showCare and Treatment• Dr.___ delay in care made my mother’s medical status worse

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0

25

50

75

100

125

150

175

200

UrologistsAll Non-Uro Surgeons

Percentage of Surgeons

Ris

k Sc

ore

Risk Score of 114 puts Dr. __ in the top 3% of urologists

Risk Score vs. Percent of PARS® Physicians at all Institutions

Stimson, et al. J Urol, May 2010

Urologists

The Risk Score reflects the complaints with which each physician was associated. It is based on an algorithm that weighs complaints recorded in the past year more heavily than those recorded in prior years.

(n = 268)

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But does any of this

actually work?


Observations

• More than 1,900 interventions completed• All messengers emerged intact (so far)• <5% responded with hostility• Common responses:

• “I never knew…”• “It’s the system…”• “These complaints are trivial…”• “I’m overscheduled…”

• ~10% go to Level II Interventions (persistent pattern needing an improvement plan)

• Follow-ups ongoing22


Total # of high complaint physicians 666Departed after initial intervention 41First follow-up later in 2011 –2012 136

Total with follow-up results 489 Results for those with follow-up data: Good – Intervention visits suspended 218 45% Good – Anticipate suspension in 2011-2012 99 20% Some improvement – Still need tracking 35 7%

Subtotal 352 72% Unimproved/worse 95 19% Departed Unimproved 42 9%Total follow-up results 489

PARS® Progress Report

This material is confidential and privileged information under the provisions set forth in T.C.A. §63-6-219 and shall not be disclosed to unauthorized persons.


PARS® & Claims Experience

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What about the impact of a peer-based intervention process on claims

experience?



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Assessing an impact on claims is challenging:• Claims are relatively rare events• Changes in external environment (frequency,

legislative initiatives, tort reform, etc)• Changes in internal environment (other

Quality/Safety initiatives, growth, case mix, etc)

Let’s look at claims in Middle Tennessee per 100 MDs (non-Vanderbilt physicians)


Malpractice Claims (per 100 MDs)FY1998 – 2009



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1990’s mindset: “our claims experience is above average”

(in a good sense)Was our assumption correct?

• We had (have) lots of physicians who wear multiple hats (teaching, research, clinical care)

• Used MGMA data on RVU production to convert VUMC productivity to FTEs

• Compared our claims/FTE to claims/100 MDs in Middle Tennessee


(We were wrong)




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Since 1998 VUMC:• PARS®• Leadership Claims Awareness meetings• ELEVATE program (leadership program to promote

core principles of excellence, integrity and ongoing improvement)

• Required Disclosure training• Allocation Rebate program

And the Tennessee Medical Malpractice Notice and Certificate of Merit Bill passed

Malpractice Claims (per 100 MDs)

FY1998 – 2009


6 - Certificate of Merit Bill


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34 5 6

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5 - Allocation Rebate Program 4 - Disclosure Training 3 - ELEVATE 2 - Claims Awareness Meetings 1 - PARS® Interventions



- - - - - - - - - - - - - Trend Line


Comments and QuestionsNow or Later

www.mc.vanderbilt.edu/cppa [email protected]

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http://www.mc.vanderbilt.edu/cppa

mailto:[email protected]

Apparent pattern

Single or isolated“unprofessional"

event (merit?)

Intervention Pyramid

Mandated Issues

"Informal" Cup of Coffee Intervention

Level 1 "Awareness" Intervention

Level 3 "Disciplinary" Intervention

Pattern persists

No ∆

Vast majority of professionals - no issues

Adapted from Hickson GB, Pichert JW, Webb LE, Gabbe SG, Acad Med, Nov, 2007

Level 2 “Guided" Intervention by Authority

Identifying and Intervening on High Risk Physicians: The PARS® Project

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