Developing and implementing a heart failure data mart for research and quality improvement

ABSTRACT Objective: The purpose of this project was to build and formatively evaluate a near-real time heart failure (HF) data mart. Heart Failure (HF) is a leading cause of hospital readmissions. Increased efforts to use data meaningfully may enable healthcare organizations to better evaluate effectiveness of care pathways and quality improvements, and to prospectively identify risk among HF patients. Methods and procedures: We followed a modified version of the Systems Development Life Cycle: 1) Conceptualization, 2) Requirements Analysis, 3) Iterative Development, and 4) Application Release. This foundational work reflects the first of a two-phase project. Phase two (in process) involves the implementation and evaluation of predictive analytics for clinical decision support. Results: We engaged stakeholders to build working definitions and established automated processes for creating an HF data mart containing actionable information for diverse audiences. As of December 2017, the data mart contains information from over 175,000 distinct patients and >100 variables from each of their nearly 300,000 visits. Conclusion: The HF data mart will be used to enhance care, assist in clinical decision-making, and improve overall quality of care. This model holds the potential to be scaled and generalized beyond the initial focus and setting.

[1]  Evans Rs,et al.  Clinical use of an enterprise data warehouse. , 2012 .

[2]  Mark D. Huffman,et al.  Heart Disease and Stroke Statistics—2016 Update: A Report From the American Heart Association , 2016, Circulation.

[3]  Christopher G. Chute,et al.  The Enterprise Data Trust at Mayo Clinic: a semantically integrated warehouse of biomedical data , 2010, J. Am. Medical Informatics Assoc..

[4]  J. Stoker,et al.  The Department of Health and Human Services. , 1999, Home healthcare nurse.

[5]  G. Fonarow,et al.  2017 ACC Expert Consensus Decision Pathway for Optimization of Heart Failure Treatment: Answers to 10 Pivotal Issues About Heart Failure With Reduced Ejection Fraction: A Report of the American College of Cardiology Task Force on Expert Consensus Decision Pathways. , 2018, Journal of the American College of Cardiology.

[6]  R. Saunders,et al.  Best Care at Lower Cost: The Path to Continuously Learning Health Care in America , 2013 .

[7]  J. James.  A New, Evidence-based Estimate of Patient Harms Associated with Hospital Care , 2013, Journal of patient safety.

[8]  Victor R. Basili,et al.  Iterative and incremental developments. a brief history , 2003, Computer.

[9]  M. Glogowska,et al.  Unplanned admissions and the organisational management of heart failure: a multicentre ethnographic, qualitative study , 2015, BMJ Open.

[10]  W. W. Royce,et al.  Managing the development of large software systems , 1970 .

[11]  Elske Ammenwerth,et al.  HerzMobil Tirol network: rationale for and design of a collaborative heart failure disease management program in Austria , 2014, Wiener klinische Wochenschrift.

[12]  C. O'connor,et al.  Influence of a performance-improvement initiative on quality of care for patients hospitalized with heart failure: results of the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF). , 2007, Archives of internal medicine.

[13]  Leslie Lenert,et al.  Leveraging a Statewide Clinical Data Warehouse to Expand Boundaries of the Learning Health System , 2016, EGEMS.

[14]  R. Scott Evans,et al.  Clinical Use of an Enterprise Data Warehouse , 2012, AMIA.

[15]  M. Stewart,et al.  You and your EMR: the research perspective: part 4. Optimizing EMRs in primary health care practice and research. , 2012, Canadian family physician Medecin de famille canadien.

[16]  Lynn A Smaha,et al.  The American Heart Association Get With The Guidelines program. , 2004, American heart journal.

[17]  P. Maurette.  [To err is human: building a safer health system]. , 2002, Annales francaises d'anesthesie et de reanimation.

[18]  L. Lingard,et al.  Adaptive practices in heart failure care teams: implications for patient-centered care in the context of complexity , 2015, Journal of multidisciplinary healthcare.

[19]  Piotr Ponikowski,et al.  Improving care for patients with acute heart failure: before, during and after hospitalization , 2014, ESC heart failure.

[20]  Sue E Bowman.  Impact of electronic health record systems on information integrity: quality and safety implications. , 2013, Perspectives in health information management.

[21]  C. Wild.  Building a safer health system , 2001 .

[22]  Alan M. Davis,et al.  A Strategy for Comparing Alternative Software Development Life Cycle Models , 1988, IEEE Trans. Software Eng..

[23]  Akshay S. Desai,et al.  Rehospitalization for heart failure: predict or prevent? , 2012, Circulation.

[24]  A. Wall,et al.  Book ReviewTo Err is Human: building a safer health system Kohn L T Corrigan J M Donaldson M S Washington DC USA: Institute of Medicine/National Academy Press ISBN 0 309 06837 1 $34.95 , 2000 .

[25]  F. Mair,et al.  Patient, Carer and Professional Perspectives on Barriers and Facilitators to Quality Care in Advanced Heart Failure , 2014, PloS one.

[26]  A. Barcelo,et al.  Using collaborative learning to improve diabetes care and outcomes: the VIDA project. , 2010, Primary care diabetes.

[27]  Naoki Sato,et al.  The global health and economic burden of hospitalizations for heart failure: lessons learned from hospitalized heart failure registries. , 2014, Journal of the American College of Cardiology.

[28]  P. Ponikowski,et al.  EURObservational Research Programme: The Heart Failure Pilot Survey (ESC‐HF Pilot) , 2010, European journal of heart failure.

[29]  L. Allen,et al.  Patient Perspectives on Communication of Individualized Survival Estimates in Heart Failure. , 2017, Journal of cardiac failure.

[30]  Henry C. Chueh,et al.  Visual query tool for finding patient cohorts from a clinical data warehouse of the partners HealthCare system , 2000, AMIA.

[31]  D. Berwick,et al.  The triple aim: care, health, and cost. , 2008, Health affairs.

[32]  K. Adams,et al.  Characteristics and outcomes of patients hospitalized for heart failure in the United States: rationale, design, and preliminary observations from the first 100,000 cases in the Acute Decompensated Heart Failure National Registry (ADHERE). , 2005, American heart journal.

[33]  L. Lingard,et al.  ‘Who is on your health‐care team?’ Asking individuals with heart failure about care team membership and roles , 2016, Health expectations : an international journal of public participation in health care and health policy.

[34]  Stephen R. Gardner.  Building the data warehouse , 1998, CACM.