1 / 73

Heart Failure Readmission Reduction Project & Summit

Heart Failure Readmission Reduction Project & Summit. Susan Schow, MPH Epidemiologist Maine Health Data Organization March 30, 2010 . Heart Failure Readmission Reduction Project and Summit. MQF- funded project using Chapter 270 data to explore link between:

fia
Download Presentation

Heart Failure Readmission Reduction Project & Summit

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Heart Failure Readmission Reduction Project & Summit Susan Schow, MPH Epidemiologist Maine Health Data Organization March 30, 2010

  2. Heart Failure Readmission Reduction Project and Summit • MQF- funded project using Chapter 270 data to explore link between: • Hospital performance on HF-1 measure, • Hospital performance on Care Transitions Measures, and • Medicare’s Hospital 30-day Readmission Rates for Heart Failure

  3. Heart Failure Readmission Reduction Project and Summit • Evaluation of data and visits to selected hospitals to: • provide opportunity to better understand the relationship between measures, patient experiences, and long-term outcomes • Share data, results of visits, and lessons learned with healthcare community (including hospitals, long term care, and home health) • “A rising tide lifts all boats”

  4. MHDO’s Hospital Quality Data:“Chapter 270” Mandated Reporting • Collect quality data measures from hospitals: • CMS core measures (AMI, HF, PN, SCIP) (July 2005) • Nursing Sensitive Indicators (Jan. 2006) • Healthcare Associated Infection data (Jan. 2007) • Care Transition Measures (Jan. 2008) • Nurse Perceptions of Culture of Safety (Jan. 2009)

  5. Heart Failure 1 - Measure • The HF-1 measure focuses on self-care teaching and six areas that need to be addressed prior to discharge: • Medications • Diet • Activity • Follow-up • Weight monitoring • Management of worsening symptoms

  6. Care Transition Measures (CTM) • CTM (3-question patient survey) measures appropriate transitional care as evaluated from patient perspective • CTM is strongly associated with post discharge use of both hospital and emergency services • Currently 18 months of CTM data available

  7. Data Evaluation • Evaluation of HF-1 Discharge Instruction measure showed an area for potential improvement • Evaluation of CTM data showed variation in patient perception of preparation for transition • Identified hospitals with mean scores significantly different than their peer group for both measures

  8. Heart Failure Readmission Reduction Project and Summit • Recognized opportunity to improve the level of “transitional care” given to patients prior to discharge • Dovetails with CMS publishing 30-day Readmission Rates for Heart Failure

  9. Hospital Visits by MQF’s QI Nurse • Selected nine hospitals for visit (9 of 36 acute care hospitals = 25%) • Ensured equal representation by peer grouping and by district • Dual goals: • Identifying best practices by asking top performers to share process improvement strategies at summit • Identifying opportunities for improvement through on–site process review meetings with heart failure teams

  10. Readmissions • 20% of Medicare Beneficiaries readmit within 30 days of discharge • 33% readmit within 90 days; 56% within year • Readmissions have a 0.6 day longer LOS than other patients in the same DRG • Medical causes dominate readmissions • Estimated cost to Medicare: $15 to $18.3 billion in annual spending Sources:1 Jencks, S., Williams, M., & Coleman, E. (2008). “Rehospitalizations among Patients in the Medicare Fee-for-Service Program,” NEJM, Volume 360:1418-1428, April 2, 2009, Number 14.2 Medpac (June 2007). "Report to the Congress: Promoting Greater Efficiency in Medicare,“ pp 103-120.

  11. Highest Rates and Most Frequent Reasons for Rehospitalization

  12. Key Area for Improvement • 50% of all patients re-hospitalized within 30 days of medical discharge had no bill by a physician between discharge and rehospitalization • 52% of CHF patients had no bill by a physician between discharge and rehospitalization • Potential implications: • Seeing a physician post discharges may have a protective effect on readmitting to the hospital. • Critical window within the 30-day period

  13. CMS Plans • Process: • Provide risk-adjusted readmission rates confidentially to hospitals • Followed by publicly report readmissions rates • Followed by payment reform (reduce payments) • Medicaid is likely to consider similar approaches • Other payers will follow • State public reporting is moving forward in many states: • Public reporting will be helpful to hospitals in addressing performance improvement Source: Medpac (June 2007). "Report to the Congress: Promoting Greater Efficiency in Medicare.“ p. 105.

  14. Transitional Care • Set of actions to ensure coordination and continuity of care as patients transfer between locations or levels of care • Patients vulnerable: • Functional loss, pain, anxiety or delirium • Unprepared for what will transpire and their roles in process (caregivers also unprepared)

  15. Literature • “Comprehensive Discharge Planning With Post Discharge Support for Older Patients with CHF” • Evaluated effects on CHF readmission rates (meta analysis: 18 studies, 8 countries) • Found 25% relative reduction in risk of readmission • A trend towards 13% relative reduction in all cause mortality • Improvement in Quality of Life scores (in a smaller subset of studies) • Without increase to cost of medical care • Specific to CHF patients, >=55 years old, moderate to severe symptoms and LV systolic dysfunction 1 Phillips C,.et al, JAMA, 2004

  16. Responsible for Care Beyond Your Care Setting • Ensure safe and effective transfers to the receiving care setting mandated per standards by: • Joint Commission for Accreditation of Healthcare Organizations • DHHS Conditions for Participation • Gaps in performance measurement identified by Institute of Medicine • to assess quality across multiple care settings • Patient and Caregiver are often the only common thread weaving across settings • Uniquely positioned to report on quality of care transition

  17. Development of Care Transition Measures Survey • Focus groups = four domains identified • Info Transfer • Confusion over appropriate Rx regimen • Patient and Caregiver Preparation • No understanding of what takes place in next care setting and their role • Care plans developed requiring caregivers participation without conferring with caregivers • Support for Self-Management • Inability to access practitioners with knowledge of recent care impedes patients’ ability to manage own care

  18. Development of Care Transition Measures Survey • Focus groups = four domains (continued) 4. Empowerment to Assert Preferences • Patients attempt to assume more active role in care or to assert preferences repeatedly discouraged by practitioners or institutions • CTM Development • Rigorous psychometric testing • Validated for poorer outcome patients (underserved, sicker and older populations) • Aligns with the tenets of patient-centered care • Items “actionable” to help guide quality improvement • Scores responsive to changes in care process

  19. Care Transition Measures • NQF endorsed 3-question survey of patients conducted 48 hrs to 6 weeks post discharge • Q1 - “The hospital staff took my preference and those of my family or caregiver into account in deciding what my health care needs would be when I left the hospital” • Q2 - “When I left the hospital, I had a good understanding of the things I was responsible for in managing my health” • Q3 - “When I left the hospital, I clearly understood the purpose for taking each of my medications”

  20. CTM: Uses Likert 4-Point Scale • Responses to questions: • “Strongly Disagree” = “1” • “Disagree” = “2” • “Agree” = “3” • “Strongly Agree” = “4” • “Don't Know” / “Don't Remember” / “Not Applicable” = “99” • Left answer blank = “9”

  21. CTM Score Associated with Post Discharge Use of Hospital and ED • Shown to discriminate between patients who did and did not have subsequent ED visit/ rehospitalization for index condition • Q2 - “When I left the hospital, I had a good understanding of the things I was responsible for in managing my health” • Significantly associated with subsequent emergency visits • Of those who agreed, 15.5% had ED visit • Of those who disagreed, 38.5% had ED visit 1 Coleman, E., et al, Medical Care, March 2005

  22. CTM Score Associated with Post Discharge Use of Hospital and ED • Studied specifically for diabetes and CHF patients following discharge because: • High likelihood of requiring follow-up care • High likelihood of requiring medication adjustment as result of hospitalization • Need for ongoing self-management • Correlation between CTM scores and subsequent use of ED • Predictive of return to ED within 30 days • p = 0.004 (hint: p-value scores <0.05 are significant ) 1 Coleman, et al, Home Health Care Services Quarterly, Vol. 26, No. 4, 2007

  23. HCAHPS® - Similar But Different • Hospital Consumer Assessment of Health Plan Survey (HCAHPS®) primarily addresses patient satisfaction • CMS developed with the Agency for Healthcare Research and Quality (AHRQ) • Since 2007, Inpatient Prospective Payment System (IPPS) hospitals must submit HCAHPS to receive full annual payment (reduced by 2% for non-reporting). Critical Access Hospitals may voluntarily report

  24. HCAHPS® - Similar But Different • The two HCAHPS discharge questions are typically summed up under the category of : • “Were patients given information about what to do during their recovery at home?” • Discharge related questions: • Q19: During your hospital stay, did hospital staff talk with you about whether you would have the help you needed when you left the hospital? • Yes, No • Studies say having opportunity to speak with doctors/nurses not rated as important as opportunity to actively prepare for care in next setting and role in self-care.

  25. HCAHPS - Similar But Different • Discharge related question: • Q20:During your hospital stay, did you get information in writing about what symptoms or health problems to look out for after you left the hospital? • Yes, No • Studies identify patient’s frustrations centered more on identifying whom to contact for symptoms rather than knowing the symptoms • Understanding medication instructions is not assessed by HCAHPS • Not known whether HCHAPS items predict recidivism (CTM does) 1 Parry, C, et al, Medical Care, March 2008

  26. CTM-3: Sufficient Number of Surveys • CTM sampling patterned after the HCAHPS survey: • CMS requires at least 300 completed HCAHPS surveys over four quarters: • “necessary to ensure adequate statistical power to compare hospitals to one another and to national benchmarks” • For those not collecting 300 completed surveys, CMS notes that: • Results are based on between 100 and 299 completed surveys or • Results are based on less than 100 completed surveys 1From: Mode and Patient-mix Adjustment of the CAHPS® Hospital Survey (HCAHPS) April 2008

  27. The 5 “Stages of Data”Where Is Your Facility? • Denial • “Those aren’t MY numbers” • Anger / Resentment • “Who got those numbers?” • Bargaining • “How about if we re-run it again??…” • Depression (?!!) • “Why are we even doing this?…” • Acceptance • “How can we get better?” “Stages of Grief” – E. Kubler-Ross – adapted by M. Albaum MD

  28. Parametric and Nonparametric Data Analysis • HF-1 data is interval (continuous) data • Intervals between any two adjacent values on a measurement scale are same • Use parametric statistics (mean, std. deviation, etc.) • CTM data is ordinal (categorical) data • Values represent a rank ordering of observations rather than precise measurements (e.g., CTM data scores of 1=strongly disagree, 2=disagree, 3=agree, 4=strongly agree) • You can count and order ordinal data, but you cannot perform mathematics on it • Use non-parametric statistics

  29. CTM Data Non-parametric Statistical Analysis • Used binomial distribution comparing proportion of patients answering with score = 4 to the proportion answering anything else (scores = 1, 2, 3) • So compared proportion answering “strongly agreed” to those answering anything else (i.e., “agree,” “disagreed,” “strongly disagreed”) • Maine is an overachiever (as usual) 

  30. CTM Data Non-parametric Statistical Analysis • Using binomial distribution (for non-parametric data) • Calculated proportion (“strongly agreed”) and upper and lower confidence intervals for: • Each hospital; • Each peer group of hospitals, and • Maine statewide • For each CTM question (1, 2, 3) and for Total CTM score

  31. Hospital Data: Evaluated by Hospital Peer Groupings • Peer Group A • 250–606 beds (MMC, EMMC, CMMC, MGMC) • Peer Group B • 79–233 beds (Aroostook, Mercy, Mid Coast, Pen Bay, SMMC, St Joseph, St Mary, York) • Peer Group C • 53-70 beds (Cary, Franklin, Goodall, ME Coast) • Peer Group D • 38-55 beds (Inland, Miles, NMMC, Parkview, Stephens)

  32. Hospital Peer Groupings - Continued • Peer Group E = Critical Access Hospitals • 25 beds or less (Blue Hill, Bridgton, CA Dean, Calais, Down East, Houlton, Mayo, Millinocket, MDI, Pen Valley, Red-Fairview, Rumford, Sebasticook, St Andrews, Waldo ) • Peer Group F = Psychiatric Hospitals • Acadia, Dorothea Dix, Riverview, Spring Harbor • Peer Group H = Rehabilitation Hospitals • New England Rehabilitation

  33. CTM Correlation With Readmissions • Performed correlation analysis using Pearson correlation coefficient - a measure of the extent to which two variables “vary together.” The value of any correlation coefficient must be between -1 and +1. • Used CTM Total score probability from each hospital • Compared to CMS 30-day Risk-adjusted Readmission Rate for Heart Failure from Hospital Compare website

  34. CTM Correlation With Readmissions • Best correlation coefficient R = 0.00347 (for CTM Question 1) • CTM Correlation (R) • Q1 = 0.00347 • Q2 = 0.00196 • Q3 = -0.01469 • Total CTM = -0.00230

  35. Evaluate Correlation Coefficient (Cohen, 1988) R = 0.003 No Correlation

  36. Why No Correlation Seen • Dates for data sets not comparable: • CTM = January 2008 to July 2009 • Readmission Rates = July 2005 to June 2008 • Literature indicates CTM predictive of risk/performance at the level of the patient, but not at level of the hospital? • If able to identify specific patient CTM survey results and track patient readmission status • “Gold standard”

  37. CHF Burden: Nursing Facilities, Residential Care Facilities, and Home Care • Medicaid Policy Cooperative Agreement Project – “Congestive Heart Failure Prevalence in Maine Long Term Care” • Prepared by Catherine McGuire, Cutler Institute and Muskie School of Public Service

  38. Nursing Home Admissions • For State Fiscal Year 2009, there were 16,073 admissions to nursing homes. The majority of admissions (88%) are from hospitals • CHF was indicated on 23% admissions • CHF prevalence was consistent for admissions from: • hospitals, • other nursing homes, • and other sources • Admissions from home and assisted living/ residential care were less likely to have a CHF diagnosis

  39. CHF Prevalence in Maine Nursing Facility Admissions by Source, SFY2009

  40. Nursing Home Discharges • In SYF 2009, there were 17,947 discharges; 24% had a CHF diagnosis • The majority of discharges from nursing facilities are to home (52%) • Residents discharged to hospital or deceased were more likely to have a CHF diagnosis: • Thirty percent of residents who died had a CHF diagnosis • Only 20% discharged home and 15% discharged to some other destination had CHF

  41. CHF Prevalence in Maine Nursing Facility Discharges by Destination, SFY 2009

More Related