Assessing Risk of Readmission. NoCVA Preventing Avoidable Readmission Collaborative Laura Maynard, MDiv, NCQC Amanda Hobbs, NCQC July 31, 2013
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1 Assessing Risk of Readmission NoCVA Preventing Avoidable Readmission Collaborative Laura Maynard, MDiv, NCQC Amanda Hobbs, NCQC July 31, 2013
2 Collaborative Goals Reduce readmission rates by 20% Increase the number of patients in the pilot unit or population who undergo assessment for risk of readmission to 95% Increase the number of patients in the pilot unit or population who are assessed to be at high risk of readmission whose primary care physician is informed of their hospitalization within 48 hours of admission to 80% Increase number of patients in the pilot unit or population who are assessed to be at high risk of readmission who are scheduled for a follow-up physician visit within 7 days of discharge from hospital to 80% 10% improvement or national 25 th percentile in scores on four HCAHPS dimensions
3 Why assess risk of readmission? Limited resources, time and financial, available for care transitions interventions Reduce readmissions to improve population health, care experience, and costs (Triple Aim)
4 Poll / chat Does your hospital use a tool to assess risk of readmission? a. Yes, hospital-wide b. On some units c. No
5 Poll / chat What types of factors does your readmission risk assessment consider? a. Clinical factors only b. Psychosocial factors only c. Both clinical and psychosocial factors d. N/A (no readmission risk assessment)
6 Poll / chat Please chat in some of the predictors (clinical, psychosocial, or both) considered in your hospital s readmission risk assessment.
7 Multiple, complicated risk factors inconsistencies regarding which characteristics are most predictive STAAR How-to Guide, IHI Efforts are needed to improve the ability to identify the likelihood of readmission RED Toolkit, AHRQ Post-hospital Care Access Diagnosis and Comorbidities Readmission <30-Days Patient Activation Psychosocial Support Step 4: Identify Which Patients Should Receive the RED. Tool 2: How to Begin the Re-Engineered Discharge Implementation at Your Hospital RED Toolkit. Agency for Healthcare Research & Quality toolkit/redtool2.html#step4 STAAR How-to Guide: Transitions from the Hospital to Community Setting to Reduce Avoidable Rehospitalizations. Institute for Healthcare Improvement ideimprovingtransitionstoreduceavoidablerehospi talizations.aspx
8 Multiple, complicated risk factors Do not let perfect be the enemy of good. high- and low-risk scores were associated with clinically meaningful gradient of readmission rates up to an 0.83 C-statistic (proportion of time a model correctly discriminates a pair of high- and low-risk patients, thus 0.50 is no better than chance) Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306(15):
9 Characteristics of good readmission risk assessments Good predictive ability o Considers relevant predictors related to both clinical and psychosocial factors of readmission Easily interpreted results o Stratification of risk groups o Targeted interventions Time-manageable Cost-manageable
10 Stratification of outcomes Each tool analyzes differently o Some have two strata, high-risk or not o Some use stoplight, three-strata system using scores Beneficial to identify high-risk patients o Include in intensive programs i.e. home visits
11 How have these been measured? Post-hospital Care Access Patient Activation Diagnosis and Comorbidities Readmission <30-Days Psychosocial Support
12 Variables considered Specific medical diagnosis or comorbidity index Mental health comorbidities o Mental illness o Alcohol or substance abuse Illness severity o Severity index (acuity of admission) o Lab results Prior use of medical services o Hospitalizations (non-elective) or ED visits o Clinic visits or missed clinic visits Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306(15):
13 Variables considered (cont.) Overall functional status o Functional status, ADL dependence, and mobility o Cognitive impairment o Visual or hearing impairment o Self-rated health or quality of life Sociodemographic factors o Age o Sex o Race/ethnicity Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306(15):
14 Variables considered (cont.) Social determinants of health o SES, income, and employment status o Insurance status o Education o Marital status or number of people in home o Caregiver ability/other social support o Access to care o Discharge destination (home, nursing home, SNF, etc.) Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306(15):
15 Interrelation of factors Some predictors used are affected by multiple factors o Polypharmacy and problem medications o PCP access, relationship, or history o Patient or caregiver activation o Length of stay Clinical Factors Readmission <30-Days Psychosocial Factors
16 LACE tool Length of Stay Acuity of Admission o Inpatient or outpatient Comorbidity ER Visits o Previous 6 months Readmission Risk Calculator. Modified LACE tool. Mobile application, RAADplan.com
17 HOSPITAL score Hemoglobin level Oncology Sodium level Procedure Index admission Type no. of Admissions in past year Length of stay Donze J, Aujesky D, et al. Potentially Avoidable 30-Day Hospital Readmissions in Medical Patients: Derivation and Validation of a Prediction Model
18 8Ps Risk Assessment Tool: the 8Ps. BOOSTing Care Transitions. Society of Hospital Medicine R_CareTransitions/html_CC/06Boost/03_Assessment.cfm
19 8Ps Problem medications (warfarin, digoxin, insulin, etc.) Psychological (depression) Principal diagnosis (cancer, stroke, DM, HF, COPD) Polypharmacy (>5 medications) Poor health literacy (inability to TeachBack) Patient support (caregiver absence) Prior hospitalization (non-elective, prior 6 months) Palliative care (progressive serious illness) Risk Assessment Tool: the 8Ps. BOOSTing Care Transitions. Society of Hospital Medicine RR_CareTransitions/html_CC/06Boost/03_Assessment.cfm
20 STAAR STAAR How-to Guide: Transitions from the Hospital to Community Setting to Reduce Avoidable Rehospitalizations. Institute for Healthcare Improvement
21 PAM Patient Activation Measure. Insignia Health
22 Developing new approaches Discharge Risk Assessment. EQ Health Solutions: The Medicare QIO for Louisiana s/dxriskassessment_rev5_12.pdf
23 Developing new approaches Discharge Risk Assessment. EQ Health Solutions: The Medicare QIO for Louisiana _Rev5_12.pdf
24 New Hanover Regional Medical Center Readmission Risk Assessment Scale July 31 st, 2012 Eva Pittman, RN, MSN, CCRN
25 PDSA: Develop a Readmission Risk Assessment Scale Cycle 1: Retrospective Study 90% success at predicting readmission Concurrent study 91% accurate with clinical estimate Almost all patients ruled in high risk Cycle 2: Retrospective Study 71% success at predicting readmission Concurrent study 92% accurate with clinical estimate Cycle 3: More Selective Retrospective Study 95% success at predicting readmission
26 PDSA Cycle 4: Test Readmission Risk Assessment Scale on Other Units Nephrology 3 rd Floor: Concurrent study 84% accurate with clinical estimate Percent of patient population identified as high risk 65% Cape Fear 2 nd Floor: Concurrent study 100% accurate with clinical estimate Percent of patient population identified as high risk 37% CMTU 8 th Floor: Concurrent Study 86% success at predicting readmission Percent of patient population identified as high risk 69% Staff Feedback: Psychosocial is the biggest factor for readmissions Consider using a Likert Scale Add ESRD to scale Add Smoking and diet issues to psychosocial as it plays a big part in CHF patients Scale easy to use
27 Common pitfalls Unnecessary length / complication is not feasible to incorporate into existing workflow Inappropriate stratification, too high or too low too few or too many patients categorized as high risk Deficient criteria does not cover both clinical and psychosocial factors Vagueness in definitions of predictors affects repeatability and reproducibility
28 Suggested methods Work within feasibility constraints o Time, cost, existing workflow for assessment o Resources available for interventions from results of assessment Include both clinical and psychosocial factors Clarify definitions of predictors Identify high-risk and target interventions
29 Going forward Choose, create, and/or reevaluate the pilot unit s risk assessment tool to identify high-risk patients using the suggested methods Apply risk assessment and appropriate process methods (follow up with primary care doc, etc.) Remember: best choice of model may depend on setting and the population (Kansagra et al) assessment is an ongoing process that requires the multidisciplinary team (STAAR) Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306(15): STAAR How-to Guide: Transitions from the Hospital to Community Setting to Reduce Avoidable Rehospitalizations. Institute for Healthcare Improvement itionstoreduceavoidablerehospitalizations.aspx
30 Resources Coleman E, Min S, Chomiak A, et al. Posthospital Care Transitions: Patterns, Complications and Risk Identification. Health Service Research Discharge Risk Assessment. EQ Health Solutions: The Medicare QIO for Louisiana Donze J, Aujesky D, et al. Potentially Avoidable 30-Day Hospital Readmissions in Medical Patients: Derivation and Validation of a Prediction Model Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306(15): Patient Activation Measure. Insignia Health Readmission Risk Calculator. Modified LACE tool. Mobile application, RAADplan.com Risk Assessment Tool: the 8Ps. BOOSTing Care Transitions. Society of Hospital Medicine ment.cfm STAAR How-to Guide: Transitions from the Hospital to Community Setting to Reduce Avoidable Rehospitalizations. Institute for Healthcare Improvement ons.aspx Step 4: Identify Which Patients Should Receive the RED. Tool 2: How to Begin the Re-Engineered Discharge Implementation at Your Hospital RED Toolkit. Agency for Healthcare Research & Quality
31 Contact For more information, contact: Laura Maynard, Director of Collaborative Learning, Amanda Hobbs, Collaborative Learning Intern, Dean Higgins, Project Manager,
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