Implementation of the Patient Centered Medical Home and Quality of - - PowerPoint PPT Presentation

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Implementation of the Patient Centered Medical Home and Quality of - - PowerPoint PPT Presentation

Nov 15, 2022 466 likes •666 views

Implementation of the Patient Centered Medical Home and Quality of Life in Patients with Multimorbidity Linnaea Schuttner, MD VA Puget Sound Healthcare System 1 MULTIMORBID PATIENTS ARE COMMON, VULNERABLE Multimorbidity: > 2 chronic

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Implementation of the Patient Centered Medical Home and Quality of Life in Patients with Multimorbidity

Linnaea Schuttner, MD VA Puget Sound Healthcare System

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MULTIMORBID PATIENTS ARE COMMON, VULNERABLE

 Multimorbidity: > 2 chronic diseases in > 2 body systems

  • National prevalence (~55-83%)

 High-cost, high-risk population  Different interaction with primary care

  • More in-person visits
  • Competing demands from illness, acute needs

 How to measure impact of care?

  • Not applicable for many quality metrics, diverse
  • Universal, patient-centered outcomes

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6,012,186 Primary care patients 5,095,532 (84.8%) Multimorbid in the VA

Marengoni et al., Aging Research, 2011

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AIMS Was implementation of the VA’s medical home model associated with health-related quality of life for multimorbid patients? Was this effect moderated by illness severity? Or by primary care visit number (i.e. “dose” of care)?

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ASSESSING CARE FOR MM PATIENTS

2010 2011 2012 2013 2014

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Implementation

  • f the

VA PCMH Measure exposure to PCMH Measure HRQoL for patients

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RETROSPECTIVE COHORT STUDY

  • Inclusion criteria, from administrative data
  • > 2 chronic conditions in > 2 body systems
  • Primary care empaneled, 2012
  • Responded to patient experience survey 2013/14

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27,813 Survey respondents 6,012,186 Primary care in ‘13-14 22,095 (95.4%) MM patients included Excluded: 60 Non-Veterans 4,585 Non-MM 521 Not enrolled in PC 677 Missing covariates

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EXPOSURE: PCMH IMPLEMENTATION

 Patient Aligned Care Team (PACT) model is the

VA’s version of the PCMH

 PI2: The PACT Implementation Progress Index

  • Clinic-level measure of PCMH implementation
  • Composed of survey and administrative data
  • 8 domains (access, continuity, care coordination, comprehensiveness, self-management support,

communication, shared decision making, staffing)

  • Higher scores associated with clinical quality, patient satisfaction, lower staff burnout

 Total score divided into 5 categories (lowest to highest implementation) for our study

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Nelson et al., JAMA Int Med 2014, 2017

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OUTCOMES: HEALTH-RELATED QUALITY OF LIFE (HRQOL)

 Patient experiences survey (PCMH-CAHPS) of outpatients

  • Stratified random sample of outpatients with encounters in past 1 month

 Average response rate 45.4% in 2014  Includes validated measure of HRQoL: Short Form-12 (SF-12)

  • Raw scores transformed with validated algorithm
  • Physical and Mental component scores (PCS, MCS), 0-100
  • MCID 2.2 points for PCS, 2.0 points for MCS

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Ware et al., 1996 Samsa et al., 1999

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STATISTICAL ANALYSIS

  • Generalized estimating equation models
  • Clustered by clinic
  • Exchangeable correlation, identity link
  • Outcomes as marginal means
  • Test of trend by ANOVA
  • Missing responses imputed with

modified estimation regression

  • Survey weighting for non-response bias

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Patient characteristics Clinic Factors Age MDs / 10k patients Sex Hospital/community Race Rural or urban Marital status Census Division Location Co-pay exemption Household income (by county) Education

Covariates

*Quarter of survey response also included Spiro et al., 2004

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ADDITIONAL ANALYSES

  • Domains of PACT
  • Comparing 3 levels of implementation

❖ Lowest (< 25%) v. Average (25-75%) v. Highest (> 75%) implementation

  • Effect moderation as interactions
  • Hospitalizations (2012) = Proxy for illness severity, differences in care
  • Total primary care clinic visits (2012) = Dose-relationship

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PATIENT DEMOGRAPHICS (2012)

Overall Mean (SD)* N = 22,095 Lowest Implementation N = 1,879 Highest Implementation N = 2,075 Age, y 68.4 (11.1) 67.5 (11.2) 69.1 (10.9) Male, No. (%) 21,189 (96) 1,796 (96) 2,018 (97) Non-Hispanic white, No. (%) 18,345 (83) 1,481 (79) 1,784 (86) Total chronic diagnoses 4.4 (1.7) 4.2 (1.6) 4.3 (1.7) Primary care visits 4.6 (4.4) 4.6 (4.6) 4.8 (4.5) Mental health visits 2.9 (10.0) 2.8 (8.8) 2.4 (7.5) Hospitalizations 0.09 (0.41) 0.08 (0.36) 0.09 (0.41)

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Mean, SD except where indicated

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CHANGE IN HRQOL BY LEVEL OF PCMH IMPLEMENTATION (ADJUSTED MARGINAL MEANS)

11 36.00 36.30 36.00 36.20 35.20 40.3 40.4 40.8 40.3 42.3 33.00 35.00 37.00 39.00 41.00 43.00 45.00

2 1 3 4 5

MCS/PCS Score Physical HRQoL: P trend < 0.001 Low to High: 2.1 Mental HRQoL P trend = 0.03 Low to High: -0.8

Implementation quintile of PCMH

High Low

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PRIOR HOSPITALIZATIONS (2012) MODERATE EFFECT FOR MCS

12 No Hosp

  • 1.2

2.7 2.1 0.1

  • 4.0
  • 2.0

0.0 2.0 4.0 6.0 Change in Score P = 0.94 P = 0.01 No Hosp Hosp Hosp No Hosp Physical HRQoL Mental HRQoL

No findings for primary care visits

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DOMAIN ANALYSES

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PCS Domain Average PI2 Mean, SE Top PI2 Mean, SE P Trend Continuity 0.20 (0.40) 0.64 (0.52) 0.01 Communication 0.47 (0.42) 0.69 (0.46) <0.001 Shared decision-making 0.63 (0.44) 1.06 (0.51)* <0.001

No findings for remaining 5 domains

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LIMITATIONS

 Observational study (Unobserved/hidden bias)  Limited to those surviving over study period / retained in care  Limited to receipt of care in

VA only

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CONCLUSIONS

 Greater PCMH implementation associated with higher physical quality of life

  • Driven by domains of shared decision making, communication, and continuity
  • No difference when varied threshold to 3+ chronic diseases
  • Difference of 2.1 ~ minimal clinical difference

 Effect for mental quality of life did not meet threshold for minimal clinical difference

  • Until effect moderated by prior hospitalizations (2.7 points higher) – qualitatively different interaction?
  • PCMH not same as behavioral health integration, no specific processes for MH in PI2

 No differences in effect from number of visits to primary care (exposure dose)

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IMPLICATIONS

 Implementation of the medical home model is associated with higher HRQoL for MM patients, but

may be variation in subgroups by severity of illness, prior utilization

 Outcomes in multimorbid patients challenging, but important – vulnerable, diverse, high prevalence

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ACKNOWLEDGEMENTS

  • Karin Nelson, MD, MSHS
  • Ashok Reddy, MD, MS
  • Ann-Marie Rosland, MD, MS
  • Edwin Wong, PhD, MA
  • VA HSR&D Fellowship (David Au, K. Nelson, Ann O’Hare)
  • Primary Care Analytics Team (PCAT; esp. L. Taylor, I. Curtis, A. Mori, & R. Orlando)
  • PCAT High-Risk Investigator Network (esp. E. Chang, D. Zulman, & M. Maciejewski)

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Questions/comments: linnaea.schuttner@va.gov @LSchuttner Disclosures: This work was undertaken as part of the Veterans Administration’s Primary Care Analytics Team (PCAT), with funding provided by the VA Office of Primary Care. Funding for the primary author was through an Advanced Physician Fellowship through the VA Office of Academic Affairs. The views expressed are those of the authors and do not necessarily reflect those of the VA.

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QUESTIONS: ADJUSTING FOR DISEASE SEVERITY

 Conceptual model  PCMH → total disease burden  Sensitivity analysis including total diseases, CAN

  • No difference

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PCMH Quality Burden

?

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DOMAIN ANALYSIS

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PCS MCS Domain Average PI2 Mean, SE Top PI2 Mean, SE P Trend Average PI2 Mean, SE Top PI2 Mean, SE P Trend Continuity 0.20 (0.40) 0.64 (0.52) 0.01

  • 0.23 (0.31)
  • 0.67 (0.41)

<0.01 Communication 0.47 (0.42) 0.69 (0.46) <0.001

  • 0.19 (0.32)
  • 0.48 (0.39)

<0.001 Shared decision- making 0.63 (0.44) 1.06 (0.51)* <0.001

  • 0.43 (0.35)
  • 0.79 (0.43)

<0.01