Redesigning the Work of Case Management: Testing a Predictive Model for Readmission
Published Online: November 21, 2013
Penny Gilbert, MBA, BSM, BSN, RN, CPHQ; Michael D. Rutland, MBA, FHFMA, FACHE, FABC; and Dorothy Brockopp, PhD, RN
The rising cost of healthcare, along with pay-for-performance and bundled-payment initiatives, have affirmed the importance of case management in today’s healthcare market.1 The Healthcare Reform Act2 in conjunction with the Institute for Healthcare Improvement white paper, A Guide to Measuring the Triple Aim,3 encourages healthcare agencies to provide higher-quality care at a lower cost.2 According to Cesta,1 case managers have historically functioned as gatekeepers regarding patient length-of-stay (LOS) and cost per case. “The cost of inpatient utilization is commonly cited as the largest driver of healthcare expenses.”4 While LOS and cost of care remain important components of the case manager’s responsibilities, at present they have evolved to a much broader role that includes prevention of readmissions. Medicare beneficiaries readmitted to hospital within 30 days of discharge are thought to cost the healthcare system $17.4 billion annually.5 In today’s hospitals, case managers are being asked to address this issue with systems and processes developed for discharge facilitation models. Unfortunately, case managers and healthcare leaders are realizing a disconnect with the new and ever-changing expectations.
Readmissions can signal low-quality care or follow-through, can negatively affect healthcare resources, and may diminish patient satisfaction.1 Effective October 2012, the Secretary of Health and Human Services (HHS) identified 3 National Quality Forum (NQF)-endorsed 30-day readmission standards: 1) acute myocardial infarction (AMI); 2) heart failure (HF); and 3) pneumonia. QualityNet,6 a government website, identifies reduction of inpatient prospective system payments to hospitals for excessive readmissions associated with the 3 NQF-endorsed groups. As a result, case managers have globally added prevention of readmissions to their responsibilities. Patient safety related to care transition is historically a focus of their role; however, the quality and consistency of patient handoff of information may be out of their span of control.
Project Development and Implementation
In an effort to improve patient safety and meet HHS readmission requirements, case managers at Baptist Health Lexington recognized the need to move beyond the traditional case management roles and activities related to discharge planning, utilization review, and LOS management. A review of the literature revealed the following causes of hospital readmission; a) no patient-provider follow-up within 7 to 10 days; b) poor patient compliance with medication regimen; c) patients’ confusion regarding management of their disease process; and d) a lack of home care services.4
Based on Kreilkamp’s7 modification of the LACE (length of stay, acuity, comorbid conditions, and emergency department visits) risk tool, a new case management model was developed at this 383-bed Magnet redesignated community hospital. Kreilkamp’s modification of the LACE tool, including assigned scores, was used. This model, Baptist Health Case Management Model (care utilization pathways, or CUP), is patient centered and organized around the 3 major components of quality care, cost, and care delivery. These 3 components incorporate care transition planning, utilization review, and communication pathways (Figure 1). The modified LACE, a psychometrically sound instrument,7 identifies patients who pose a strong risk of readmission based on an objective scoring system (Table 1). Research to date suggests that the modified LACE index can accurately identify individuals who are likely to be readmitted within 30 days of discharge.8
In addition to identifying patients with greater risk of readmission, using the CUP model case managers intervene by (a) assuring that the planned provider follow-up occurs post discharge, (b) assuring that patients understand their medication regimens, (c) helping the patient and family members to understand the patient’s disease process, and (d) referring to home care or other support services when appropriate. The modified LACE discharge assessment tool (Figure 2) addresses the usual causes of readmission with preventive counseling and education. It also encourages the case managers to think critically regarding individualized patient discharge needs.
According to the literature describing the use of the LACE tool,7 a paper version is generally used, although the tool can be adapted to be electronic. If on hard copy, staff must input values and calculate the LACE index score into a final composite score. At Baptist Health Lexington, an automated approach has been developed that calculates the LACE index score at the patient level through the hospital intranet, identifies patients with LACE Index Scores at the threshold value of >7, and populates within a common shared electronic folder for case managers (majority at the BSN or MSN level) to view. A decision support analyst developed a) the database using internal software, b) the reports required to extract the needed data elements for the calculations, and c) the report retrieved daily by case management. Identified through our pilot program, receiving reports in a timely fashion is important in order to develop appropriate plans for transition of care for patients. While the modified LACE risk tool is used for all adult and pediatric patients at this hospital, neonates, hospice patients, and patients who are mentally incapacitated with state guardianship are excluded due to variable hospital stays.
The daily modified LACE risk report initially identified patients who had a composite modified score of 10 or greater (maximum score of 19). Examination of data collected 90 days post model implementation resulted in lowering the capture score to 7 or greater. During the first 90 days readmissions were slightly reduced, by an average of 6%. Analysis of the data showed that scores for a number of the patients readmitted to the hospital fell between modified LACE scores of 7 and 9. Lowering the score to 7 created a larger “at-risk” population, which ultimately resulted in a greater decrease in number of readmissions (50% reduction).
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