2016 Hospitalist Clinical Performance Registry (H-CPR) Measure Specifications Manual

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2016 Hospitalist Clinical Performance Registry (H-CPR) Measure Specifications Manual Measure # Measure Title 2 Mean Length of Stay for Inpatients All Patients 3 Mean Length of Stay for Inpatients Pneumonia
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2016 Hospitalist Clinical Performance Registry (H-CPR) Measure Specifications Manual Measure # Measure Title 2 Mean Length of Stay for Inpatients All Patients 3 Mean Length of Stay for Inpatients Pneumonia 4 Mean Length of Stay for Inpatients CHF 5 Mean Length of Stay for Inpatients COPD 6 30 Day All Cause Readmission Rate for All Discharged Inpatients 7 30 Day All Cause Readmission Rate Following Pneumonia Hospitalization 8 30 Day All Cause Readmission Rate Following CHF Hospitalization 9 30 Day All Cause Readmission Rate Following COPD Hospitalization 10 In-Hospital Mortality Rate for Inpatients with Pneumonia 11 In-Hospital Mortality Rate for Inpatients with CHF 12 In-Hospital Mortality Rate for Inpatients with COPD 13 Stroke Venous Thromboembolism (VTE) Prophylaxis 14 Stroke Patients Discharged on Statin Medication 15 Venous Thromboembolism (VTE) Prophylaxis 16 Venous Thromboembolism (VTE) Patients with Anticoagulation Overlap Therapy 1 H-CPR (Hospitalist Clinical Performance Registry) Measure #2 Measure Title: Mean Length of Stay for Inpatients All Patients Inverse Measure: Yes Measure Description: Weighted, Risk-Adjusted Mean LOS for All Inpatients National Quality Strategy Domain: Efficiency and Cost Reduction Type of Measure: Outcome Number of Performance Rates: 1 Measure Scoring: Continuous Risk Adjustment: Yes Numerator: [Note: This outcome measure does not have a traditional numerator and denominator like a core process measure (e.g., percentage of adult patients with diabetes aged years receiving one or more hemoglobin A1c tests per year); thus, we use this field to define the measure outcome.] The Outcome for This Measure Is Mean Time (in Days) from Admission to Inpatient Status to Hospital Discharge for All Patients Denominator: Patients Evaluated by the Eligible Professional with E/M Codes , , , and AND Place of Service Indicator: 21 (Note: please see weighting methodology below) PLUS LOS 120 days PLUS E/M admission code (99221, or 99223) AND E/M discharge code (99238 or 99239) by Eligible Professional or one of Eligible Professional s associates treating these patients PLUS Provider of record ( AI ) modifier specified for Medicare patients with E/M Codes or Patients who expired during inpatient care or left AMA are excluded Denominator Exclusions: None Denominator Exceptions: None Risk Adjustment: The purpose of the risk-adjustment is to determine the provider and system level contributions to the outcome after adjusting for patient-level demographic and clinical characteristics. Length of stay times are risk-adjusted for the overall and subgroups as continuous variables after normalization. Risk-adjustment derivation: Model: A regression model with fixed-effects (patient age, sex, and presence of comorbidities) and DRG severity weight (CMS geometric mean LOS for the DRG) is used. Normal distribution is ensured and then a linear regression performed. 2 Dataset: The most current Health Care Utilization Project (HCUP) national dataset is utilized. This dataset contains over 20 million records per year and is a rich source for the derivation and validation of the model. The derivation dataset is a 75% random sample of the dataset. The co-morbidities are derived by mapping the ICD9/ICD10 to the relevant Charlson comorbidity index categories. Risk-adjustment validation: The results of the risk-adjustment derivation are used as a model with the relative patient level factors and a beta-coefficient weight for each of those factors. These coefficients are applied to the 25% validation sample to evaluate the discriminant value (c-statistic) and calibration (Hosmer-Lemeshow) of the riskadjustment model. Risk-adjustment application: The coefficient weights from the risk-adjustment model are applied to the performance data to provide an expected outcome for each patient. For each provider, the observed outcome over the expected outcome is summed to produce and observed/expected ratio. Eligible Professional Weighting Methodology: When multiple hospitalist Eligible Professionals have provided care during the patient s inpatient stay (i.e. all contributing to a portion of the patient s LOS), a weighting methodology is utilized to calculate the portion of the LOS attributed to each Eligible Professional on the case via the following formula: Observed LOS = Attribution proportion XCase LOS Expected LOS All cases for which provider had 1 encounter Encounters by provider for case = ( ) X Case LOS Total encounters for case = Attribution proportion X Expected case LOS All cases for which provider had 1 encounter Encounters by provider for case = ( ) X Expected case LOS Total encounters for case Note: For purposes of weighting, encounters are defined as consisting of visit codes: , , , and Reporting Measure: Mean Time (in Days) from Admission to Inpatient Status to Hospital Discharge Observed/Expected Ratio Rationale: Universally hospitals across the United State utilize mean length of stay (LOS) measures as surrogate outcome measures for overall care because evidence-based inpatient medical care reduces hospital inpatient LOS while improving outcomes. Evidence-based hospital treatments of Congestive Heart Failure (CHF), Pneumonia (PNA) and Acute Exacerbations of Chronic Bronchitis (AECB) along with supportive care (e.g. venous thromboembolism prophylaxis) reduce hospital LOS, inpatient complications, and 30-day mortality rates. Elderly patients along with those admitted for CHF, COPD, and AECB account for over 60% of inpatient admissions. Reducing inpatient LOS addresses utilization, improves hospital throughput, increases inpatient bed capacity, and reduces Emergency Department crowding. 3 Selected References: Landefeld CS. Care of hospitalized older patients: opportunities for hospital-based physicians. J Hosp Med 2006; 1:42. Wald H, Huddleston J, Kramer A. Is there a geriatrician in the house? Geriatric care approaches in hospitalist programs. J Hosp Med 2006; 1:29. Flaherty JH, Tariq SH, Raghavan S, et al. A model for managing delirious older inpatients. J Am Geriatr Soc 2003; 51:1031. Older patients treated with antipsychotics are at increased risk for developing aspiration pneumonia. Curr Infect Dis Rep 2011; 13:262. Arbaje AI, Maron DD, Yu Q, et al. The geriatric floating interdisciplinary transition team. J Am Geriatr Soc 2010; 58:364. Vidán M, Serra JA, Moreno C, et al. Efficacy of a comprehensive geriatric intervention in older patients hospitalized for hip fracture: a randomized, controlled trial. J Am Geriatr Soc 2005; 53:1476. Global strategy Wald H, Huddleston J, Kramer A. Is there a geriatrician in the house? Geriatric care approaches in hospitalist programs. J Hosp Med 2006; 1:29.for the diagnosis, management, and prevention of COPD: Revised Global initiative for Chronic obstructive lung disease (GOLD). (Accessed on April 11, 2014). Stoller JK. Clinical practice. Acute exacerbations of chronic obstructive pulmonary disease. N Engl J Med 2002; 346:988. Ntoumenopoulos G. Using titrated oxygen instead of high flow oxygen during an acute exacerbation of chronic obstructive pulmonary disease (COPD) saves lives. J Physiother 2011; 57:55. Albert RK, Martin TR, Lewis SW. Controlled clinical trial of methylprednisolone in patients with chronic bronchitis and acute respiratory insufficiency. Ann Intern Med 1980; 92:753. Kiser TH, Allen RR, Valuck RJ, et al. Outcomes associated with corticosteroid dosage in critically ill patients with acute exacerbations of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2014; 189:1052. Mandell LA, Wunderink RG, Anzueto A, et al. Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults. Clin Infect Dis 2007; 44 Suppl 2:S27 McCabe, C, Kirchner, C, Zhang, H, et. al. Guideline-Concordant Therapy and Reduced Mortality and Length of Stay in Adults With Community-Acquired Pneumonia, Arch Intern Med. 2009;169(16): Fine M, Pratt H, Obrosky DS, et.al. Relation between length of hospital stay and costs of care for patients with community-acquired pneumonia. Am Jnl Med 2000; 109: 378. National Quality Forum Measure #1611-Pneumonia Episode Treatment Group Cost of Care. Ashton CM, Kuykendall DH, Johnson ML, et al. The association between the quality of inpatient care and early readmission. Ann Intern Med 1995; 122:415. Konstam MA. Relating quality of care to clinical outcomes in heart failure: in search of the missing link. J Card Fail 2001; 7:299. Gheorghiade M, Zannad F, Sopko G, et al. Acute heart failure syndromes: current state and framework for future research. Circulation 2005; 112:3958. Heart Failure Society of America, Lindenfeld J, Albert NM, et al. HFSA 2010 Comprehensive Heart Failure Practice Guideline. J Card Fail 2010; 16:e1. 4 Pines M, Hollander J, et. al. The Association between Emergency Department Crowding and Hospital Performance on Antibiotic Timing for Pneumonia and Percutaneous Intervention for Myocardial Infarction. Acad Em Med 2008; 13:873. Hiller D, Parry G, et. al. The Effect of Hospital Bed Occupancy on Throughput in the Pediatric Emergency Department. Ann Emrg Med 2009; 53:767 5 H-CPR (Hospitalist Clinical Performance Registry) Measure #3 Measure Title: Mean Length of Stay for Inpatients Pneumonia Inverse Measure: Yes Measure Description: Risk-Adjusted Mean LOS for All Inpatients Diagnosed with Pneumonia National Quality Strategy Domain: Efficiency and Cost Reduction Type of Measure: Outcome Number of Performance Rates: 1 Measure Scoring: Continuous Risk Adjustment: Yes Numerator: [Note: This outcome measure does not have a traditional numerator and denominator like a core process measure (e.g., percentage of adult patients with diabetes aged years receiving one or more hemoglobin A1c tests per year); thus, we use this field to define the measure outcome.] The Outcome for This Measure Is Mean Time (in Days) from Admission to Inpatient Status to Hospital Discharge for Pneumonia Patients Denominator: Patients Evaluated by the Eligible Professional with E/M Codes , , , and AND Place of Service Indicator: 21 (Note: please see weighting methodology below) PLUS LOS 120 days PLUS E/M admission code (99221, or 99223) AND E/M discharge code (99238 or 99239) by Eligible Professional or one of Eligible Professional s associates treating these patients PLUS Provider of record ( AI ) modifier specified for Medicare patients with E/M Codes or PLUS Discharge diagnosis of pneumonia o ICD-10: J12.0, J12.1, J12.2, J12.81, J12.89, J12.9, J15.1, J14, J15.4, J15.4, J15.20, J15.211, J15.212, J15.29, J15.8, J15.5, J15.6, A48.1, J15.8, J15.9, J15.7, J16.0, J16.8, J18.0, J17, J11.00, J11.08 Patients who expired during inpatient care or left AMA are excluded Denominator Exclusions: None Denominator Exceptions: None Risk Adjustment: The purpose of the risk-adjustment is to determine the provider and system level contributions to the outcome after adjusting for patient-level demographic and clinical characteristics. Length of stay times are risk-adjusted for the overall and subgroups as continuous variables after normalization. 6 Risk-adjustment derivation: Model: A regression model with fixed-effects (patient age, sex, and presence of comorbidities) and DRG severity weight (CMS geometric mean LOS for the DRG) is used. Normal distribution is ensured and then a linear regression performed. Dataset: The most current Health Care Utilization Project (HCUP) national dataset is utilized. This dataset contains over 20 million records per year and is a rich source for the derivation and validation of the model. The derivation dataset is a 75% random sample of the dataset. The co-morbidities are derived by mapping the ICD9/ICD10 to the relevant Charlson comorbidity index categories. Risk-adjustment validation: The results of the risk-adjustment derivation are used as a model with the relative patient level factors and a beta-coefficient weight for each of those factors. These coefficients are applied to the 25% validation sample to evaluate the discriminant value (c-statistic) and calibration (Hosmer-Lemeshow) of the riskadjustment model. Risk-adjustment application: The coefficient weights from the risk-adjustment model are applied to the performance data to provide an expected outcome for each patient. For each provider, the observed outcome over the expected outcome is summed to produce and observed/expected ratio. Eligible Professional Weighting Methodology: When multiple hospitalist Eligible Professionals have provided care during the patient s inpatient stay (i.e. all contributing to a portion of the patient s LOS), a weighting methodology is utilized to calculate the portion of the LOS attributed to each Eligible Professional on the case via the following formula: Observed LOS = Attribution proportion XCase LOS Expected LOS All cases for which provider had 1 encounter Encounters by provider for case = ( ) X Case LOS Total encounters for case = Attribution proportion X Expected case LOS All cases for which provider had 1 encounter Encounters by provider for case = ( ) X Expected case LOS Total encounters for case Note: For purposes of weighting, encounters are defined as consisting of visit codes: , , , and Reporting Measure: Mean Time (in Days) from Admission to Inpatient Status to Hospital Discharge Observed/Expected Ratio Rationale: Universally hospitals across the United State utilize mean length of stay (LOS) measures as surrogate outcome measures for overall care because evidence-based inpatient medical care reduces hospital inpatient LOS while improving outcomes. Evidence-based hospital treatments of Congestive Heart Failure (CHF), Pneumonia (PNA) and Acute Exacerbations of Chronic Bronchitis (AECB) along with supportive care (e.g. venous thromboembolism prophylaxis) reduce hospital LOS, inpatient complications, and 30-day mortality rates. Elderly patients along 7 with those admitted for CHF, COPD, and AECB account for over 60% of inpatient admissions. Reducing inpatient LOS addresses utilization, improves hospital throughput, increases inpatient bed capacity, and reduces Emergency Department crowding. Selected References: Landefeld CS. Care of hospitalized older patients: opportunities for hospital-based physicians. J Hosp Med 2006; 1:42. Wald H, Huddleston J, Kramer A. Is there a geriatrician in the house? Geriatric care approaches in hospitalist programs. J Hosp Med 2006; 1:29. Flaherty JH, Tariq SH, Raghavan S, et al. A model for managing delirious older inpatients. J Am Geriatr Soc 2003; 51:1031. Older patients treated with antipsychotics are at increased risk for developing aspiration pneumonia. Curr Infect Dis Rep 2011; 13:262. Arbaje AI, Maron DD, Yu Q, et al. The geriatric floating interdisciplinary transition team. J Am Geriatr Soc 2010; 58:364. Vidán M, Serra JA, Moreno C, et al. Efficacy of a comprehensive geriatric intervention in older patients hospitalized for hip fracture: a randomized, controlled trial. J Am Geriatr Soc 2005; 53:1476. Global strategy Wald H, Huddleston J, Kramer A. Is there a geriatrician in the house? Geriatric care approaches in hospitalist programs. J Hosp Med 2006; 1:29.for the diagnosis, management, and prevention of COPD: Revised Global initiative for Chronic obstructive lung disease (GOLD). (Accessed on April 11, 2014). Stoller JK. Clinical practice. Acute exacerbations of chronic obstructive pulmonary disease. N Engl J Med 2002; 346:988. Ntoumenopoulos G. Using titrated oxygen instead of high flow oxygen during an acute exacerbation of chronic obstructive pulmonary disease (COPD) saves lives. J Physiother 2011; 57:55. Albert RK, Martin TR, Lewis SW. Controlled clinical trial of methylprednisolone in patients with chronic bronchitis and acute respiratory insufficiency. Ann Intern Med 1980; 92:753. Kiser TH, Allen RR, Valuck RJ, et al. Outcomes associated with corticosteroid dosage in critically ill patients with acute exacerbations of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2014; 189:1052. Mandell LA, Wunderink RG, Anzueto A, et al. Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults. Clin Infect Dis 2007; 44 Suppl 2:S27 McCabe, C, Kirchner, C, Zhang, H, et. al. Guideline-Concordant Therapy and Reduced Mortality and Length of Stay in Adults With Community-Acquired Pneumonia, Arch Intern Med. 2009;169(16): Fine M, Pratt H, Obrosky DS, et.al. Relation between length of hospital stay and costs of care for patients with community-acquired pneumonia. Am Jnl Med 2000; 109: 378. National Quality Forum Measure #1611-Pneumonia Episode Treatment Group Cost of Care. Ashton CM, Kuykendall DH, Johnson ML, et al. The association between the quality of inpatient care and early readmission. Ann Intern Med 1995; 122:415. Konstam MA. Relating quality of care to clinical outcomes in heart failure: in search of the missing link. J Card Fail 2001; 7:299. Gheorghiade M, Zannad F, Sopko G, et al. Acute heart failure syndromes: current state 8 and framework for future research. Circulation 2005; 112:3958. Heart Failure Society of America, Lindenfeld J, Albert NM, et al. HFSA 2010 Comprehensive Heart Failure Practice Guideline. J Card Fail 2010; 16:e1. Pines M, Hollander J, et. al. The Association between Emergency Department Crowding and Hospital Performance on Antibiotic Timing for Pneumonia and Percutaneous Intervention for Myocardial Infarction. Acad Em Med 2008; 13:873. Hiller D, Parry G, et. al. The Effect of Hospital Bed Occupancy on Throughput in the Pediatric Emergency Department. Ann Emrg Med 2009; 53:767 9 H-CPR (Hospitalist Clinical Performance Registry) Measure #4 Measure Title: Mean Length of Stay for Inpatients CHF Inverse Measure: Yes Measure Description: Risk-Adjusted Mean LOS for All Inpatients Diagnosed with Congestive Heart Failure (CHF) National Quality Strategy Domain: Efficiency and Cost Reduction Type of Measure: Outcome Number of Performance Rates: 1 Measure Scoring: Continuous Risk Adjustment: Yes Numerator: [Note: This outcome measure does not have a traditional numerator and denominator like a core process measure (e.g., percentage of adult patients with diabetes aged years receiving one or more hemoglobin A1c tests per year); thus, we use this field to define the measure outcome.] The Outcome for This Measure Is Mean Time (in Days) from Admission to Inpatient Status to Hospital Discharge for CHF Patients Denominator: Patients Evaluated by the Eligible Professional with E/M Codes , , , and AND Place of Service Indicator: 21 (Note: please see weighting methodology below) PLUS LOS 120 days PLUS E/M admission code (99221, or 99223) AND E/M discharge code (99238 or 99239) by Eligible Professional or one of Eligible Professional s associates treating these patients PLUS Provider of record ( AI ) modifier specified for Medicare patients with E/M Codes or PLUS Discharge diagnosis of CHF o ICD-10: I11.0, I13.0, I13.2, I50.1, I50.20, I50.21, I50.22, I50.23, I50.30, I50.31, I50.32, I50.33, I50.40, I50.41, I50.42, I50.43, I50.9 Patients who expired during inpatient care or left AMA are excluded Denominator Exclusions: None Denominator Exceptions: None Risk Adjustment: The purpose of the risk-adjustment is to determine the provider and system level contributions to the outcome after adjusting for patient-level demographic and clinical characteristics. Length of stay times are risk-adjusted for the overall and subgroups as continuous variables after normalization. 10 Risk-adjustment derivation: Model: A regression model with fixed-effects (patient age, sex, and presence of comorbidities) and DRG severity weight (CMS geometric mean LOS for the DRG) is used. Normal distribution is ensured and then a linear regression performed. Dataset: The most current Health Care Utilization Project (HCUP) national dataset is utilized. This dataset c
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