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IIR 16-075 – HSR&D Study

 
IIR 16-075
Patient Centered Care for Individuals with Advanced Liver Disease
Fasiha Kanwal MBBS MD
Michael E. DeBakey VA Medical Center, Houston, TX
Houston, TX
Funding Period: May 2018 - April 2022

BACKGROUND/RATIONALE:
Ensuring that Veterans with serious illness receive patient-centered care is a fundamental goal of medical care. Advanced liver disease (AdvLD) is a serious illness that disproportionately affects Veterans and carries high rates of morbidity and mortality. As many as half of AdvLD patients develop liver complications (e.g., ascites, encephalopathy, or liver cancer) within 5 years of diagnosis; half of these patients die within 2 years of developing complications. Despite notable advances in the care of patients with AdvLD, many gaps remain. Liver transplantation offers an opportunity to cure AdvLD, however, few patients receive it; most patients, even those on the transplant waiting list, live with and die of their AdvLD. Their clinical course is marked by declining health, increasing symptom burden and frequent hospitalizations. However, supportive care for AdvLD is often episodic and reactive, and palliative care is rare.

Recent patient-centered models of care in other conditions, like cancer, have promoted early integration of supportive, palliative and curative care. These models can improve quality and even length of life. Integrated care models may be even more important in non-cancer conditions such as AdvLD where disease course and care trajectories can be more prolonged and uncertain, yet much can be done with patients to reduce complications and maintain both function and well-being.

There are several reasons why patient-centered integrated models for AdvLD have been slow to develop. First, a precise and complete understanding of disease severity and progression is lacking. Existing prognostic scores, like Model for End Stage Liver Disease (MELD) or Child Pugh are disease-specific and do not account for a wide range of psychosocial and clinical factors that are likely to be associated with suboptimal outcomes in AdvLD. Incorporation of non-liver disease factors in prognostication is especially important for VA patients, as many are impoverished and have multiple comorbidities, often with drug or alcohol use disorders. Conversely, the general prognostic models that take psychosocial and clinical factors into account (such as Charlson or Care Assessment Need score) do not incorporate liver disease severity and miss AdvLD-specific outcomes. Second, Veterans' experiences with VA health care likely shape how they access and engage in AdvLD care. However, there have been no studies characterizing Veterans' illness-specific health care needs, their understanding of illness severity, as well as the goals of care that matter to them across the spectrum of disease severity. Third, although clinicians' current approaches to supportive care for AdvLD are the starting point for developing more patient-centered models, little is known about their experiences, expectations, and perceived barriers to delivering AdvLD care.

OBJECTIVE(S):
To use a multi-method approach to fill knowledge gaps in the care of advanced liver disease (AdvLD) patients that are crucial to integrated care for AdvLD.

Aim 1: To develop risk stratification models of advanced liver disease prognosis.

Aim 2: To describe Veteran patients' experiences and goals of advanced liver disease care.

Aim 3:To identify clinicians' perceptions of opportunities and barriers to patient-centered advanced liver disease care.

METHODS:
Aim 1: To develop risk stratification models of AdvLD prognosis. We will develop models that combine liver severity indices (e.g., MELD, Child Pugh) with psychosocial (e.g., age, race, homelessness), clinical (e.g., physical and mental health comorbidity, alcohol use), and healthcare resource use (e.g., emergency room visits) factors to estimate the risk of developing AdvLD complications, requiring AdvLD related hospitalizations, and overall mortality. We will use existing automated data from a national cohort of Veterans with AdvLD (n~45,000) enrolled in the VA between 2011 and 2015. Aim 1 will provide estimates of AdvLD Veterans' risk (e.g., low, intermediate or high) of developing AdvLD-specific outcomes. These data will allow patients, caregivers and clinicians to understand patients' illness severity and future risks.

Aim 2: To describe patients' experiences and goals of AdvLD care. We will conduct in-depth interviews with a representative sample of AdvLD patients (and their caregivers) from three VA centers to understand patients' experiences with care; perceptions of illness severity including preferences for the amount and type of risk information needed; and desired health outcome goals. Aim 2 will identify the range of goals that patients in different risk strata perceive as important. Data from Aims 1 and 2 will allow clinicians to place their patients' perspectives in context and deliver clinical care consistent with patients' prognosis and goals.

Aim 3: To identify clinicians' perceptions of opportunities and barriers to patient-centered AdvLD care. We will conduct in-depth interviews with clinicians involved with AdvLD treatment planning at three VA centers to examine their experiences in communicating risk and making treatment plans; perceptions of their and patients' roles in treatment planning; and barriers to and facilitators of providing care aligned with patients' goals. Aim 3 will complement the first two by identifying problems that clinicians face delivering patient-centered AdvLD care as well as possible solutions to these problems. Combined with Aim 2, data from Aim 3 will provide design elements for intervention strategies to improve patient-centered AdvLD care.

FINDINGS/RESULTS:
There are no findings at this time.

IMPACT:
This study will develop a patient-centered model of collaborative care for AdvLD that may be applicable to other serious illness conditions. It will develop Veteran-specific risk stratification models for AdvLD care that will provide clinicians with a practical method for predicting risks of major clinical outcomes in AdvLD.

Interviews with Veterans and their caregivers will reveal how patients with AdvLD experience care and to what extent such care meets their needs and preferences.


External Links for this Project

NIH Reporter

Grant Number: I01HX002204-01A2
Link: https://reporter.nih.gov/project-details/9398766

Dimensions for VA

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If you have VA-Intranet access, click here for more information vaww.hsrd.research.va.gov/dimensions/

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    Search Dimensions for this project

PUBLICATIONS:

Journal Articles

  1. Hagström H, Adams LA, Allen AM, Byrne CD, Chang Y, Grønbaek H, Ismail M, Jepsen P, Kanwal F, Kramer J, Lazarus JV, Long MT, Loomba R, Newsome PN, Rowe IA, Ryu S, Schattenberg JM, Serper M, Sheron N, Simon TG, Tapper EB, Wild S, Wong VW, Yilmaz Y, Zelber-Sagi S, Åberg F. Administrative Coding in Electronic Health Care Record-Based Research of NAFLD: An Expert Panel Consensus Statement. Hepatology (Baltimore, Md.). 2021 Jul 1; 74(1):474-482. [view]
  2. Do A, Ilagan-Ying YC, Taddei TH. Analysis of weekend effect in severe acute liver injury: A nationwide database study. Health science reports. 2020 Mar 1; 3(1):e139. [view]
  3. Zhang Y, Weinreb JC, Czeyda-Pommersheim F, Taddei TH. Assessing the Impact of Referral on Multidisciplinary Tumor Board Outcomes in Patients With Hepatocellular Carcinoma. Journal of the American College of Radiology : JACR. 2020 Dec 1; 17(12):1636-1643. [view]
  4. Chen Q, Ayer T, Adee MG, Wang X, Kanwal F, Chhatwal J. Assessment of Incidence of and Surveillance Burden for Hepatocellular Carcinoma Among Patients With Hepatitis C in the Era of Direct-Acting Antiviral Agents. JAMA Network Open. 2020 Nov 2; 3(11):e2021173. [view]
  5. Kim HS, Yang JD, El-Serag HB, Kanwal F. Awareness of chronic viral hepatitis in the United States: An update from the National Health and Nutrition Examination Survey. Journal of Viral Hepatitis. 2019 May 1; 26(5):596-602. [view]
  6. Kanwal F, Tapper EB, Ho C, Asrani SK, Ovchinsky N, Poterucha J, Flores A, Ankoma-Sey V, Luxon B, Volk M. Development of Quality Measures in Cirrhosis by the Practice Metrics Committee of the American Association for the Study of Liver Diseases. Hepatology (Baltimore, Md.). 2019 Apr 1; 69(4):1787-1797. [view]
  7. Kanwal F, Taylor TJ, Kramer JR, Cao Y, Smith D, Gifford AL, El-Serag HB, Naik AD, Asch SM. Development, Validation, and Evaluation of a Simple Machine Learning Model to Predict Cirrhosis Mortality. JAMA Network Open. 2020 Nov 2; 3(11):e2023780. [view]
  8. McDonald MF, Barrett SC, Malik TH, Anand A, Keeling SS, Christmann CR, Goff CR, Galvan T, Kanwal F, Cholankeril G, Goss J, Rana A. Elevated serum sodium in recipients of liver transplantation has a substantial impact on outcomes. Transplant international : official journal of the European Society for Organ Transplantation. 2021 Oct 1; 34(10):1971-1983. [view]
  9. Tefera J, Revzin M, Chapiro J, Savic LJ, Mulligan D, Batra R, Taddei T, Jain D, Zhang X. Fibronodular hepatocellular carcinoma-a new variant of liver cancer: clinical, pathological and radiological correlation. Journal of clinical pathology. 2021 Jan 1; 74(1):31-35. [view]
  10. Mahmud N, Sundaram V, Kaplan DE, Taddei TH, Goldberg DS. Grade 1 Acute on Chronic Liver Failure Is a Predictor for Subsequent Grade 3 Failure. Hepatology (Baltimore, Md.). 2020 Jul 1; 72(1):230-239. [view]
  11. Cholankeril G, Goli K, Rana A, Hernaez R, Podboy A, Jalal P, Da BL, Satapathy SK, Kim D, Ahmed A, Goss J, Kanwal F. Impact of COVID-19 Pandemic on Liver Transplantation and Alcohol-Associated Liver Disease in the USA. Hepatology (Baltimore, Md.). 2021 Dec 1; 74(6):3316-3329. [view]
  12. Naik AD, Arney J, Clark JA, Martin LA, Walling AM, Stevenson A, Smith D, Asch SM, Kanwal F. Integrated Model for Patient-Centered Advanced Liver Disease Care. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association. 2020 May 1; 18(5):1015-1024. [view]
  13. Celli R, Saffo S, Kamili S, Wiese N, Hayden T, Taddei T, Jain D. Liver Pathologic Changes After Direct-Acting Antiviral Agent Therapy and Sustained Virologic Response in the Setting of Chronic Hepatitis C Virus Infection. Archives of pathology & laboratory medicine. 2021 Apr 1; 145(4):419-427. [view]
  14. Kanwal F, Kramer JR, Asch SM, Cao Y, Li L, El-Serag HB. Long-Term Risk of Hepatocellular Carcinoma in HCV Patients Treated With Direct Acting Antiviral Agents. Hepatology (Baltimore, Md.). 2020 Jan 1; 71(1):44-55. [view]
  15. Xiao KY, Hubbard RA, Kaplan DE, Taddei TH, Goldberg DS, Mahmud N. Models for acute on chronic liver failure development and mortality in a veterans affairs cohort. Hepatology international. 2020 Jul 1; 14(4):587-596. [view]
  16. Cholankeril G, Kanwal F. NAFLD and HCC: Time to Bridge the Gap. Hepatology (Baltimore, Md.). 2021 Nov 1; 74(5):2336-2338. [view]
  17. Styskel B, Natarajan Y, Kanwal F. Nutrition in Alcoholic Liver Disease: An Update. Clinics in liver disease. 2019 Feb 1; 23(1):99-114. [view]
  18. Wai-Sun Wong V, Kanwal F. On the Proposed Definition of Metabolic-Associated Fatty Liver Disease. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association. 2021 May 1; 19(5):865-870. [view]
  19. Joshi T, Rana A, Vierling JM, Kanwal F, Goss JA, Cholankeril G. Practical Consideration for Drug Monitoring of Tacrolimus in Liver Transplantation Recipients with SARS-CoV-2 Infection. Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society. 2022 Jan 1; 28(1):127-130. [view]
  20. Kanwal F, Shubrook JH, Younossi Z, Natarajan Y, Bugianesi E, Rinella ME, Harrison SA, Mantzoros C, Pfotenhauer K, Klein S, Eckel RH, Kruger D, El-Serag H, Cusi K. Preparing for the NASH epidemic: A call to action. Obesity (Silver Spring, Md.). 2021 Sep 1; 29(9):1401-1412. [view]
  21. Kanwal F, El-Serag HB. Presentation of the AGA William Beaumont Prize in Gastroenterology to David Y. Graham, MD. Gastroenterology. 2021 Jul 1; 161(1):333-335. [view]
  22. Ketwaroo G, Sealock RJ, Freedman S, Hart PA, Othman M, Wassef W, Banks P, Vege SS, Gardner T, Yadav D, Sheth S, Kanwal F. Quality of Care Indicators in Patients with Acute Pancreatitis. Digestive diseases and sciences. 2019 Sep 1; 64(9):2514-2526. [view]
  23. Rich NE, Noureddin M, Kanwal F, Singal AG. Racial and ethnic disparities in non-alcoholic fatty liver disease in the USA. The lancet. Gastroenterology & hepatology. 2021 Jun 1; 6(6):422-424. [view]
  24. Hernaez R, Liu Y, Kanwal F. Reply to: "Model for end-stage liver disease-sodium in acute-on-chronic liver failure". Journal of Hepatology. 2020 Dec 1; 73(6):1579-1580. [view]
  25. Hernaez R, Kanwal F. Reply to: "The role of the model for end-stage liver disease sodium score and joint models for 90-day mortality prediction in in patients with acute-on-chronic liver failure". Journal of Hepatology. 2021 Feb 1; 74(2):477. [view]
  26. Onken J, Chang L, Kanwal F. Reply. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association. 2022 Mar 1; 20(3):714-715. [view]
  27. Shen Y, Risch H, Lu L, Ma X, Irwin ML, Lim JK, Taddei T, Pawlish K, Stroup A, Brown R, Wang Z, Jia W, Wong L, Mayne ST, Yu H. Risk factors for hepatocellular carcinoma (HCC) in the northeast of the United States: results of a case-control study. Cancer Causes & Control : Ccc. 2020 Apr 1; 31(4):321-332. [view]
  28. Mahmud N, Fricker Z, Hubbard RA, Ioannou GN, Lewis JD, Taddei TH, Rothstein KD, Serper M, Goldberg DS, Kaplan DE. Risk Prediction Models for Post-Operative Mortality in Patients With Cirrhosis. Hepatology (Baltimore, Md.). 2021 Jan 1; 73(1):204-218. [view]
  29. Mahmud N, Hubbard RA, Kaplan DE, Taddei TH, Goldberg DS. Risk prediction scores for acute on chronic liver failure development and mortality. Liver International : Official Journal of The International Association For The Study of The Liver. 2020 May 1; 40(5):1159-1167. [view]
  30. Tansel A, Kramer J, Feng H, El-Serag HB, Kanwal F. Risk Trajectories for Readmission and Death After Cirrhosis-Related Hospitalization. Digestive diseases and sciences. 2019 Jun 1; 64(6):1470-1477. [view]
  31. Kaplan DE, Mehta R, Garcia-Tsao G, Albrecht J, Aytaman A, Baffy G, Bajaj J, Hernaez R, Hunt K, Ioannou G, Johnson K, Kanwal F, Lee TH, Monto A, Pandya P, Schaubel D, Taddei TH. SACRED: Effect of simvastatin on hepatic decompensation and death in subjects with high-risk compensated cirrhosis: Statins and Cirrhosis: Reducing Events of Decompensation. Contemporary clinical trials. 2021 May 1; 104:106367. [view]
  32. Kanwal F, Singal AG. Surveillance for Hepatocellular Carcinoma: Current Best Practice and Future Direction. Gastroenterology. 2019 Jul 1; 157(1):54-64. [view]
  33. Kanneganti M, Mahmud N, Kaplan DE, Taddei TH, Goldberg DS. Survival Benefit of Liver Transplantation for Hepatocellular Carcinoma. Transplantation. 2020 Jan 1; 104(1):104-112. [view]
  34. El-Serag HB, Christie IC, Puenpatom A, Castillo D, Kanwal F, Kramer JR. The effects of sustained virological response to direct-acting anti-viral therapy on the risk of extrahepatic manifestations of hepatitis C infection. Alimentary pharmacology & therapeutics. 2019 Jun 1; 49(11):1442-1447. [view]
  35. Onken J, Chang L, Kanwal F. Unconscious Bias in Peer Review. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association. 2021 Mar 1; 19(3):419-420. [view]
Journal Other

  1. Verma M, Taddei T, Volk M, Navarro V. Advance Care Planning: A Convincing Argument to Make It Part of Liver Transplant Evaluation. [Letter to the Editor]. Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society. 2021 Feb 1; 27(3):461-462. [view]


DRA: Health Systems, Kidney Disorders
DRE: TRL - Development, Technology Development and Assessment
Keywords: Healthcare Algorithms, Outcomes - Patient, Patient Preferences, Patient-Provider Interaction, Predictive Modeling
MeSH Terms: none

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