A Mixed Methods Study of Information Availability on Pregnancy Outcomes

Chad Meyerhoefer, Susan Sherer, Mary Deily,Shin-Yi Chou

Lehigh University

Donald Levick, Michael SheinbergLehigh Valley Health Network

Acknowledgements

This research received financial support from Agency for Healthcare Research and Quality (AHRQ) Grant PARA-08-270 and from a Lehigh University Faculty Innovation Grant

Objective

Determine the value of timely clinical information at the point of care during pregnancy– Inpatient labor and delivery (L&D) unit– Outpatient OB/GYN offices– Change in data availability due to EHR implementation

Quantitative methods to measure impact of data availability on pregnancy outcomes & payments– 3 rounds of data collection on the L&D and at OB/GYN

offices– Adverse outcomes data collected through chart review

Other measures extracted from billing data

Qualitative methods to measure barriers to data access and perceptions

Data & patient flow during pregnancy

Outpatient practice

CPO

Triage UnitCPN

Labor & DeliveryCPN

Mother - Baby UnitLastword / CPN

Discrete

Discrete

Summary

Patient flow

Data flow

HOSPITAL DOCTOR’S OFFICE

Increase in data availability in Triage

2009 39965 39995 40026 40057 40087 2010 40330 40360 40391 2011 40705 40725 40756 407870%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Cervical ExamBlood Pressure Antenatal Prob. List Group B Strep

2009 39965 39995 40026 40057 40087 2010 40330 40360 40391 2011 40705 40725 40756 407870%

10%

20%

30%

40%

50%

60%

70%

80%

Non-stress

Prior Incision Type

Tubal Steril. (Medicaid)

Average monthly N = 119, Max = 193, Min = 16

Empirical models

Model 1: Linear probability model (LPM) & regression Outcomes (Triage: N=1,324; Offices: N=1,809)

– Obstetric trauma (0/1), mean = 0.06

– Log(payments), mean = 8.8 ($6,336)

Model 2: Two-part model (LPM & Log OLS) Outcomes (Triage: N=1,324 / 99; Offices: N=1,809 / 119)

– Weighted adverse outcome score (WAOS) (0/1) > 0, mean = 0.08

– Log(WAOS), mean = 3.1

Control variables– DCG/HCC risk score quartile, age, race/ethnicity, insurance type,

admission type, multiple birth, pre-existing condition, non-preventable complication, c-section, instrument assisted delivery, indicators for data elements in system (Triage), physician fixed effects

WAOS > 0

Clinical data elements WAOS > 0 Log(WAOS)

(=1 if available for review in L&D Triage)

Parsimoniousmodel

Saturated model

Parsimoniousmodel

Saturated model

Cervical exam -0.01 -0.02 -0.32 0.08

[0.02] [0.02] [0.31] [0.42]

Blood pressure 0.00 0.02 -0.78** -0.54

[0.02] [0.03] [0.31] [0.65]

Antenatal prob. list -0.00 0.00 -0.74*** -0.76**

[0.02] [0.03] [0.26] [0.33]

Nonstress test -0.01 0.01 -0.05 0.34

[0.03] [0.03] [0.39] [0.52]

Prior uterine incision type -0.05 -0.06 0.10 0.24

[0.03] [0.04] [0.61] [0.64]

Group B strep status -0.01 -0.01 -0.63 -0.62

[0.03] [0.03] [0.49] [0.41]

Tubal sterilization -0.06** -0.05** 0.03 1.18

request (Medicaid) [0.03] [0.03] [1.54] [1.35]

Notes: Percentage pt. and percentage effects with clustered standard errors in brackets

Clinical data elements Obstetric trauma Log(Payments)

(=1 if available for review in L&D Triage)

Parsimoniousmodel

Saturated model

Parsimoniousmodel

Saturated model

Cervical exam -0.03* -0.02 -0.08 -0.08

[0.02] [0.02] [0.06] [0.06]

Blood pressure -0.04* -0.02 -0.06 0.10*

[0.02] [0.03] [0.06] [0.05]

Antenatal prob. list -0.01 0.02 -0.15** -0.16**

[0.02] [0.03] [0.07] [0.07]

Nonstress test -0.06** -0.06 -0.03 -0.00

[0.03] [0.03] [0.10] [0.12]

Prior uterine incision type 0.00 0.03 -0.22 -0.18

[0.03] [0.04] [0.16] [0.18]

Group B strep status -0.02 0.00 0.00 0.11

[0.02] [0.03] [0.09] [0.11]

Tubal sterilization -0.05* -0.06* 0.00 0.00

request (Medicaid) [0.03] [0.03] [0.21] [0.21]

Notes: Percentage pt. and percentage effects with clustered standard errors in brackets

Office models - WAOI

Clinical data elements WAOS > 0 Log(WAOS)

(=1 if available for review in the OB/GYN Office)

Parsimoniousmodel

Saturated model

Parsimoniousmodel

Saturated model

New diagnoses 0.02 0.04 -0.23 -1.50***

[0.03] [0.03] [0.74] [0.53]

Cervical exam -0.02 0.02 -0.05 1.44

[0.02] [0.03] [0.48] [1.40]

Nonstress test -0.03 -0.07 -0.20 0.59

[0.02] [0.04] [0.54] [0.89]

Lab work -0.02 -0.01 0.98* 0.85

[0.02] [0.02] [0.49] [1.53]

Notes: Percentage pt. and percentage effects with clustered standard errors in brackets

Office models – Obst. trauma & payments

Clinical data elements Obstetric trauma Log(Payments)

(=1 if available for review in the OB/GYN Office)

Parsimoniousmodel

Saturated model

Parsimoniousmodel

Saturated model

New diagnoses 0.01 0.05 0.14* 0.19*

[0.03] [0.04] [0.08] [0.09]

Cervical exam -0.02 -0.02 -0.28* -0.29*

[0.02] [0.02] [0.15] [0.16]

Nonstress test -0.03 -0.04* -0.22 -0.06

[0.02] [0.02] [0.14] [0.14]

Lab work -0.02 -0.02 0.00 0.12

[0.02] [0.02] [0.12] [0.14]

Notes: Percentage pt. and percentage effects with clustered standard errors in brackets

Provider interviews

Barrier to data access: TrustI don’t trust anything or anyone or anything automatically flowing - Physician

Greater data availability through EHRMany times a patient would be seen in Triage in the interval between their visits, and you wouldn’t even know it. So at least seeing that document triggers you to say, “oh, well she was in … triage. Why was she there?” - Physician

Physician vs. staff perceptions

Information Accessibil-ity

Documentation Availability

Test Availability Diagnosis Availability Ease of Use0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Physicians

Staff

2010 Office Data: N=89 (74 staff; 15 physicians))

Physicians perceive limited availability of information from Triage at offices & find it more difficult to use EHR (1 = Agree strongly that EMR improves [ ]; 5 = Disagree strongly)