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Improving congestive heart failure care with a clinical decision unit.

ACROSS THE NATION, hospitals are realizing the financial impact of altered Medicare reimbursement processes based on pay-for-performance programs called Value-Based Purchasing (VBP) and the Readmissions Reduction Program (RRP). These evolving Centers for Medicare & Medicaid Services (CMS) initiatives incorporate methods to realign hospital reimbursement rates based on algorithms that utilize scores for quality, patient satisfaction measures, mortality, and readmission rates. VBP payment reductions of up to 1% of eligible Medicare reimbursement began October 1, 2012, with planned 0.5% annual increases up to a level of 3% by approximately 2017. With VBP, organizations can receive improved reimbursement for performance better than national rates at levels similar to penalties (Department of Health and Human Services, 2011).

The RRP, rates of patients readmitted within 30 days of hospital discharge, began affecting hospitals in October 2012 (the beginning of CMS fiscal year 2013) with a potential rate reduction on all Medicare admissions of up to 1% (CMS, 2013). The RRP is CMS's most significant program, with up to a 3% reduction in future reimbursement beginning October 2014. Unlike VBP, the RRP offers no opportunity to exceed performance expectations and increase reimbursement. There is an inverse relationship between readmission rates and payments: performance at or above national levels allows a hospital to retain the at-risk amount, while below standard rates decrease reimbursement. The combined impact of VBP and RRP will be up to a 6% reduction in all hospital Medicare reimbursement when the programs fully deploy in 2017. This is an important point for hospitals to consider, as all future CMS reimbursements are at risk based on penalties earned, not just the diagnostic categories performing below target. Jencks, Williams, and Coleman (2009) provide context for the CMS focus on readmissions. These authors identified 19.6% of Medicare patients discharged from hospitals were readmitted within 30 days. The authors found that patients with a diagnosis of congestive heart failure (CHF) had a 30-day readmission rate of 26.9%, the highest of all diagnostic categories reported. The estimated annual cost to Medicare of unplanned readmissions was $17.4 billion in 2004.

Norton Audubon Hospital (NAH), Louisville, KY, is a 275-bed community hospital that is part of Norton Healthcare, the largest not-for-profit integrated health care system in the state. Cardiology is the major service line for NAH and it provides tertiary-level care for patients from local and extended service areas. In addition, the local community has a large base of patients with Medicare as their primary payer. Based on its service line focus and community demographics, NAH cares for more than 50% (>7,000 annual admissions) of all Medicare patients for the entire Norton system. Stellar performance in all categories of VBP and RRP is of paramount importance for NAH and the health system in terms of optimizing CMS reimbursement and quality care for patients.

The NAH readmission rate for CHF is 25.35% for January and February 2013, representing 18 readmissions out of 71 patient index admissions. To retain full reimbursement, a hospital must not experience excess readmissions. An excess readmission is defined as "a hospital's readmission performance compared to the national average for the hospital's set of patients with that applicable condition" (CMS, 2013, para. 5). The addition of strategies to address CHF readmissions is now critical due to the future impact on Medicare reimbursement.

Literature Review and Synthesis

Evidence supporting the development of Clinical Decision Units (CDUs) to impact CHF readmission rates comes from several categories of literature, including disease management and patient education programs, CDU/Observation Unit efficacy studies, and reports on the use of predictive index tools. A summary of pertinent literature supporting the development of a CDU specifically for patients with CHF is provided in Table 1.

CDU Development and Design Factors

Norton Healthcare has been exploring new systems in chronic disease management, including the development of an outpatient, nurse practitioner-run CHF clinic on the NAH campus. The NAH leadership and case management teams visited a successful CHF clinic at Piedmont Hospital, Atlanta, GA, and learned they were in the process of strengthening their program through the addition of a CDU. Further, key members of a leading cardiology practice voiced an interest in managing patients with CHF in a CDU based on prior experiences and knowledge of care trends in their specialty. Deployment of an outpatient CHF clinic and a CDU as a bundled approach to CHF management emerged as a viable plan. This project is designed to bring about significant change in care delivery for patients with CHF and provides a foundation through which leadership seeks to create a vision and program for patient care that serves as a basis for future work around chronic disease management. The primary aim of the CDU development project is to improve care and reduce NAH's overall 30-day readmission rate for patients with CHF. Table 2 provides a summary of the components of this project identified as contributory to its success.

At the time of this project, Norton Healthcare used Microsoft Amalga[TM] Readmissions Manager (Redmond, WA) as a predictive index tool to aggregate data and provide analysis via a set of markers designed to predict the probability of an individual patient's risk for readmission. Examples of markers include patient age, history of prior admissions, number of emergency department (ED) visits in the prior year, presence of certain chronic diseases, and marital status. Based upon analysis of historical data, Norton Healthcare has established any predictive index score above 26 as higher risk for readmission (scores can range from below zero to greater than 100). The predictive index determines individual patient risk for readmission and triggers aggressive discharge planning, including a followup visit with a primary care or cardiology provider within 24-48 hours post-discharge.

An at-risk patient receives education based on RN assessment of risk factors from the predictive index elements and/or failures of the prior discharge plan, as well as planned transitions to home care or other post-discharge care sources. If a CDU patient is unable to discharge home safely, nursing and case management make alternate arrangements such as transfer to a rehabilitation or skilled nursing facility. This scenario typically prompts conversion to an inpatient admission and transfer to an inpatient unit so that adequate time can be devoted to proper discharge planning.

Project Resources

A summary of the project implementation costs is shown in Table 3. The major capital expenses were new cardiac monitoring and nurse call systems, as well as patient room furniture. Other miscellaneous costs included computers, medication and supply distribution systems, and additional small care delivery items. Nurse and patient care support spaces were also outfitted, such as a staff lounge and offices. Staffing consists of 8.6 RN full-time equivalents (sufficient coverage for two RNs/12-hour shift daily and backfill) and support staff as needed (reallocated from other units). Staffing expense included orientation time and participation in planning activities prior to unit opening. CDU characteristics that may be helpful to those seeking to replicate this project are presented in Table 4.


A pre-post design with a comparison group was used to evaluate the effectiveness of the NAH CDU. The rate of CHF 30-day readmissions and other key elements (see Table 5) provided the basis of comparison between NAH and a similar hospital within the Norton system. The rationale for this comparison was to provide control for external "noise" around CHF management in the system and isolate the impact of the project relative to a like hospital that is similar in most ways except the existence of the CDU. The comparison hospital is also an adult, medical-surgical facility that cares for tertiary-level cardiology patients. Statistical analyses were performed utilizing SAS[R] analytic software (Cary, NC). Also of note in Table 5 are the varying date ranges for metric analyses, each of which was chosen to optimize the use of post-CDU implementation data.

Norton Healthcare uses the CMS methodology for calculating risk-adjusted readmission rates which by definition include "... readmissions for any reason within 30 days of discharge from a hospital stay. Readmissions are counted regardless of whether patients are readmitted to the same hospital or to a different acute care facility" (Department of Health and Human Services, 2011, p. 6). Due to the delayed nature of the hospital-specific CMS reports (which can be many months in arrears), Norton Healthcare calculates internal readmission rates utilizing CMS methodologies to drive performance improvement. Though not completely accurate due to readmissions outside of the system, these rates provide timely data and help determine the effectiveness of the CDU. As shown in Table 5, CHF readmission rates for NAH did not decrease during the analysis period and are not statistically different from the comparison hospital (logistical regression hospital x pre-post interaction Wald chi-square(1)=0.37; p=0.54).

Norton Healthcare routinely collects observation data for a variety of administrative, financial, and quality purposes. Specific to the NAH CDU, patients with CHF are admitted in observation status. Patients are also admitted into observation status with a CHF diagnosis outside of the CDU at NAH and to inpatient units at the control hospital. The rationale for considering this outcome measure is the belief the admission of patients with CHF presenting to the ED into the CDU in observation status will result in a more rapid increase in observations as opposed to lagging readmission rates. As demonstrated in Table 5, the percentage of CHF patient encounters in observation status increased at NAH post initiation of the CDU. This change was both greater than the comparison hospital and statistically significant (logistical regression hospital x pre-post interaction Wald chi-square(1)=6.11; p=0.01).

A cost/discharge comparison for CHF inpatient and observation encounters provides an assessment of the financial performance of the CDU (see Table 5). Both NAH and the comparison hospital experienced an increase in cost, but the cost of caring for patients with CHF increased by a lesser amount at NAH. The difference, however, was not statistically significant (GLM hospital x pre-post interaction F (1, 912) < 1; p=0.37).

Predictive index scores were compared for NAH and the comparison hospital pre and post initiation of the CDU. As illustrated in Table 5, NAH predictive index scores for all patients with CHF increased while those in the comparison hospital decreased slightly. The difference in these changes is not statistically significant (GLM hospital x pre-post interaction F (1, 925)=2.31; p=0.13).


A major objective of this quality improvement project, reduction in the CHF readmission rate for NAH, has not been realized. This finding is not particularly surprising at this point due to the lagging nature of the data. The CHF readmission rate is decreasing in raw numbers when compared to the prior year results for January (2012: 29.8; 2013: 26.2) and February (2012: 21.8; 2013: 19.6), albeit slowly and not at a statistically significant level. A longer period of analysis is needed (probably 6 months to a year) to allow the unit and its care processes to mature, as well as to collect additional readmission results.

Observation encounters are increasing in both hospitals, but at a significantly higher rate at NAH. This is in alignment with the planned analysis for this project and the projection this measure would increase prior to seeing a readmission rate reduction. Providing a venue for focused observation care is proving to be a successful strategy that is well accepted by clinicians and patients. Early financial results for the CDU are promising. Though not statistically significant to date, there is decreased cost associated with providing observation care due to decreased length of stay, as well as additional positive financial impacts from the cost structure of the CDU (smaller unit with less overhead).

During the first month of operation, the CDU project committee determined CHF volume was inadequate to either support unit functioning or provide inpatient capacity relief for NAH. The project committee added patients with simple chest pain as a CDU population and developed admission/ discharge criteria and order sets along the same lines as those for CHF. This addition boosted the CDU volume and provided capacity relief for the inpatient units and the ED.

A volume analysis and comparison of CDU cost/day versus similar care provided in a NAH inpatient unit offers additional information regarding the creation of capacity and a different view of financial impact. An overview of volume reduction and cost avoidance projections is provided in Table 6. It is important to note CDU staffing is not an added expense for NAH. The volume projections for the CDU were based on historical observation admission data for NAH inpatient units. Volume and associated staffing allocations were transferred to the CDU cost center, thereby creating a cost-neutral staffing and volume budget for the project. For the cost-avoidance calculations, the average length of stay in hours was determined for CDU patients and those admitted to a NAH inpatient unit in observation status with diagnoses and clinical presentation that would have met CDU admission criteria. Savings calculations utilized the cost/day of caring for a patient on an inpatient unit ($395) applied to the number of days of care saved. The annualized cost and hospital day savings are conservative since the volume of patients admitted to CDU is increasing monthly. To change physician practice patterns, such as the use of the CDU, ongoing communication with key groups must occur to help them gain comfort with the unit and care protocols. The CDU project team continues to seek input from all stakeholders, especially those physicians not involved in unit development, to improve unit performance and grow volume.

Financially, the CDU shows promising results. Given the increasing pressures on hospital reimbursement from all payers, cost control is the primary avenue for mitigating eroding margins. Early cost-reduction indicators for the CDU will strengthen the ability for the facility to continue CDU operation and allow time for care processes to mature.

Since the opening of the CDU, the CHF patient predictive index scores at NAH increased slightly as opposed to the comparison hospital. This finding is not surprising and actually provides a measure of support for the new care processes implemented. Observation status use is increasing at NAH since the CDU opened and patient risk for readmission remains statistically stable. Additionally, the readmission risk of patients with CHF presenting to each facility is comparable, providing information about this patient population as a whole served by Norton Healthcare. Predictive index scores are important to trend going forward, in conjunction with readmission rates, to ensure patients are not experiencing an increase in their readmission risk because of a CDU discharge. Significant increases in the predictive index score could be an early indicator of discharges occurring too soon, before patients are stable and ready for transition to home. The scores also provide an ongoing gauge of the status of the CHF population served. All CDU patients who are discharged to home have followup arranged with a primary care or cardiology provider. During February 2013, the physician order sets were adjusted and every CHF discharge from NAH (CDU or otherwise) was referred to the nurse practitioner in the outpatient CHF clinic. This change provided additional support for the patient post discharge, as well as synchronized reinforcement of patient discharge teaching through shared educational materials and processes.

Consideration of patient satisfaction measures provides additional context for this project. Followup phone calls are routine procedure for most NAH inpatient discharges and outpatient encounters. These calls occur within 72 hours of discharge to determine the patient's service experience, as well as offer an opportunity for the patient to ask clarifying questions about discharge instructions. CDU nurses make these calls and note responses on a discharge phone call sheet, which also serves as an outline of questions for the caller. Of the 32 patients with a diagnosis of CHF discharged from the CDU during the period December 3, 2012 through March 31, 2013, staff successfully made contact with 14, for a 44% rate of response. Typical results throughout NAH range from 40% 50%. Patients discharged from the CDU report satisfaction with their care experience during the discharge phone calls.

Implications for Nurse Leaders

Implementation of a CDU provides many opportunities for nurse leaders to positively impact clinical care and financial performance within their institutions, to include:

* Definition of a patient population to aggressively manage

* Improved throughput, both through the ED and inpatient units

* Improved patient outcomes and satisfaction

* Engagement of a interdisciplinary teams

* Comparing and evaluating multiple dimensions of performance using strong statistical analysis

* Improved financial performance through cost management

Strengths, Limitations, and Future Implications

There are many strengths within Norton Healthcare that provided a foundation for the success of the CDU. The system has long been in the forefront of transparency and began publically reporting health care outcomes March 31, 2005, long before CMS and other agencies developed such reports. To support this culture, the Norton Healthcare Clinical Information Analysis Department was developed and is staffed by statisticians and analysts who ensure data integrity and provide analysis support, including the CDU statistical analysis. Because of its commitment to quality improvement, Norton Healthcare was the recipient of the 2011 National Quality Forum Award (National Quality Forum, 2011). NAH is designated as a Cycle 4 Chest Pain Center by the Society of Cardiovascular Patient Care. During the 2013 reapplication site visit, the NAH CDU was recognized as a best practice. Being part of a large system and having access to robust data to compare the NAH CDU results with a comparison hospital adds strength to the analysis design, a benefit not available to all hospitals.

Readmission rates in hospitals are a complex phenomenon not easily impacted by singular interventions like a CDU. Programs designed to provide stronger community-based care for patients with CHF, therefore decreasing need for hospitalization, are next steps for Norton Healthcare and are in development. In addition to the nurse practitioner-led CHF clinic discussed previously, strategic partnership negotiations are occurring with regional post-acute care providers such as long-term care and home health agencies. Norton Healthcare is also collaborating with Humana, a prominent payer in the regional market, on an Accountable Care Organization pilot. Aggregately, all of these initiatives will construct the safety net needed to provide care to multiple vulnerable patient populations, including those with CHF. When projects such as the CDU provide margin support and some relief on cost pressures, the organization gains time to continue to develop the larger structure necessary to provide comprehensive care within the community and maintain viability as new payment methodologies evolve. The plan for the NAH CDU is to maintain a cardiac focus and to continue to identify observation status populations for which similar processes are appropriate until unit capacity and efficiency become optimal. The success thus far appears to be associated with a singular focus on a patient type (cardiac), dedicated nursing staff and providers with expertise in cardiology, and duplication and deployment of strict patient management by order sets and protocols.

There are several limitations associated with this project. First, improving readmission rates is a complicated endeavor requiring a systematic approach to mitigating a multitude of contributing factors. The CDU is promising, but more time must elapse to truly understand its value to the organization and integrate it into the larger safety net for chronic disease management that is currently under construction for Norton Healthcare. The predictive index score is a valuable tool that the organization is just beginning to understand how to apply to patient management. More work must occur to integrate this tool fully into broader workflows, which includes the development of a predictive index tool to embed into Norton Healthcare's new electronic medical record (Epic, Verona, WA). This project is also limited by its singular site. Current plans are underway to duplicate the CDU concept in another system hospital. This will strengthen the organization's ability to understand the contribution of this unit and further study the impact on the care delivery model.

The CDU is a good fit with the strategic and service-line focus of NAH and has a high likelihood of being a sustainable innovation for the organization and its parent system. The early unit successes are expected to continue and will be evaluated at regular intervals so that optimization can occur. This initiative has already spawned many others and is now part of a system-wide project plan to improve CHF patient population management. Organizational support is strong and planned unit replication speaks to the value added to Norton Healthcare's ongoing mission and vision of providing care to the community.


Centers for Medicare & Medicaid Services (CMS). (2013). Readmissions reduction program. Retrieved from http:// InpatientPPS/ReadmissionsReduction-Program.html

Daly, S., Campbell, D.A., & Cameron, P.A. (2003). Short-stay units and observation medicine: A systematic review. The Medical Journal of Australia, 378(11) 559-563.

Department of Health & Human Services Centers for Medicare & Medicaid Services. (2011). Medicare hospital quality chartbook 2011: Performance report on readmission measures for acute myocardial infarction, heart failure, and pneumonia [Issue brief). Retrieved from Medicare/Quality-Initiatives-PatientAssessment-Instruments/Hospital Qualitylnits/downloads/Hospital ChartBook2011.pdf

Gohler, A., Januzzi, J.L., Worrell, S.S., Osterziel, K.J., Gazelle, G.S., Dietz, R., & Siebert, U. (2006). A systematic meta-analysis of the efficacy and heterogeneity of disease management programs in congestive heart failure. Journal of Cardiac Failure, 32(7), 554-567.

Iannone, P., & Lenzi, T. (2009). Effectiveness of a multipurpose observation unit: Before and after study. Emergency Medicine Journal, 26(6), 407414. doi:10.1136/emj.2007.057539

Jencks, S.F., Williams, M.V., & Coleman, E.A. (2009). Rehospitalizations among patients in the Medicare fee-for-service program. The New England Journal of Medicine, 360(14), 1418-1428.

Jessup, M., Abraham, W.T., Casey, D.E., Feldman, A.M., Francis, G.S., Ganiats, T.G., ... Yancey, C.W. (2009). 2009 focused update: ACCF/AHA guidelines for the diagnosis and management of heart failure in adults. Journal of the American College of Cardiology, 53(15), 1343-1382. doi:10. 1016/j.jacc.2008.11.009

Jovicic, A., Holroyd-Leduc, J.M., & Straus, S.E. (2006). Effects of self-manage ment intervention on health outcomes of patients with heart failure: A systematic review of randomized controlled trials. BMC Cardiovascular Disorders, 6(43), 1-8. doi: http://www.

Kansagara, D., Englander, H., Salanitro, A., Kagen, D., Theobald, C., Freeman, M., & Kripalani, S. (2011). Risk prediction models for hospital readmission: A systematic review. Journal of the American Medical Association, 306(15), 1688-1698.

National Quality Forum (2011). National Quality Forum names Norton Healthcare winner of 2011 NGF national quality healthcare award. Washington, DC: Author.

Roberts, M.V., Baird, W., Kerr, P., & O'Reilly, S. (2010). Can an emergency department-based clinical decision unit successfully utilize alternatives to emergency hospitalization? European Journal of Emergency Medicine, 3 7(2), 89-96.

Ross, J.S., Mulvey, G.K., Stauffer, B., Patlolla, V., Bernheim, S.M., Keenan, P.S., & Krumholz, H.M. (2008). Statistical models and patient predictors of readmission for heart failure: A systematic review. Archives of Internal Medicine, 368(13), 1371-1386.

Sg2. (2010, August). Improvement guide: Implementing a clinical decision unit to reduce avoidable admissions (White Paper). Skokie, IL: Author.

Sochalski, J., Jaarsma, T., Krumholz, H.M., Laramee, A., McMurray, J.J., Naylor, M.D., ... Stewart, S. (2009). What works in chronic care management: The case of heart failure. Health Affairs, 28(1), 179-189.

JO ELLEN CARPENTER, DNP, MBA, RN, NEA-BC, CENP, is Assistant Vice President, Nursing Operations, MedStar Georgetown University Hospital, Washington, DC.

NANCY SHORT, DrPH, MBA, RN, is Associate Professor, Duke University School of Nursing, Durham, NC.

TRACY E. WILLIAMS, DNP, RN, is Senior Vice President and System Chief Nursing Officer, Norton Healthcare, Louisville, KY.

BEN YANDELL, PhD, is System Associate Vice President of Clinical Information Analysis, Norton Healthcare, Louisville, KY.

MARGARET T. BOWERS, DNP, RN, FNP-BC, AACC, is Assistant Professor Coordinator, Adult/Gerontology Nurse Practitioner Program, and Lead Faculty, Cardiovascular Concentration, Duke University School of Nursing, Durham, NC.
Table 1.

Relevant Literature and Clinical Decision Unit (CDU) Application

                       Main Conclusions/
Study/Citation         Relevance              CDU Design Elements

Short-stay units and   Found positive         Support for
observation            impacts on avoiding    development of unit.
medicine: A            hospital admissions,
systematic review      cost effectiveness,
(Daly, Campbell, &     and patient
Cameron, 2003)         satisfaction.

A systematic meta-     Identified program     Transition
analysis of the        components most        management and use
efficacy and           effective in           of multidisciplinary
heterogeneity of       decreasing mortality   team for inpatient
disease management     and readmissions:      care, discharge
programs in            Personal contact       planning, and post-
congestive heart       with the patient       discharge phone
failure (Gohler et     (home or phone         calls.
al., 2006)             visits) post
                       management of
                       transitions to the
                       next level of care,
                       use of a
                       team to manage
                       hospital care and
                       discharge plans.

Effectiveness of a     Found a                Development of
multipurpose           statistically          admission and
observation unit:      significant decrease   discharge criteria
Before and after       in observational       and clinical
study (lannone &       unit length of stay    protocols.
Lenzi, 2009).          after implementation
                       of prescribed unit
                       criteria and
                       clinical protocols.

2009 focused update:   Update of national     Level I
ACCF/AHA guidelines    guidelines,            recommendations for
for the diagnosis      incorporating new      comprehensive
and management of      evidence.              discharge
heart failure in                              instructions, care
adults (Jessup et                             transitions,
al., 2009).                                   medication
                                              reconciliation, and
                                              primary care
                                              provider office

Effects of self-       Identified decreased   Patient education
management             readmission risk       and post-discharge
intervention on        with intensive         phone calls.
health outcomes of     disease/drug
patients with heart    education, self/
failure: A             management of
systematic review of   medicines/symptoms
randomized             and home visits/
controlled trails      calls.
(Jovicic, Holroyd-
Leduc, & Straus,

Risk prediction        Found predictive       Use of predictive
models for hospital    index tools can be     index score to
readmission: A         useful in directing    direct focused
systematic review      care transitions by    attention on
(Kansagara et al.,     allowing resources     discharge plans.
2011)                  to be applied toward
                       patients with higher

Can an emergency       Found the use of a     Support for
department-based       CDU significantly      development of the
clinical decision      decreased hospital     unit and discharge
unit successfully      admissions and         plans to include
utilize alternatives   improved discharge     referrals to primary
to emergency           to post-hospital       care providers.
hospitalization?       services.
(Roberts, Baird,
Kerr, & O'Reilly,

Statistical models     Support the use of     Use of predictive
and patient            predictive index       index tool.
predictors of          tools to guide care
readmission for        transitions.
heart failure (Ross
et al., 2008)

Improvement guide:     Provided background    Development of care
Implementing a         on CDUs as well as     protocols (order
clinical decision      program development    sets, patient
unit to reduce         insights.              education materials,
avoidable                                     etc.).
readmissions (Sg2,

What works in          American Heart         Multidisciplinary
chronic care           Association's          team management and
management: The case   Taxonomy of Disease    patient education.
of heart failure       Management framework
(Sochalski et al.,     used to classify
2009)                  program components.
                       Two components of
                       the framework
                       impacted  read-
                       missions: (a)
                       Delivery personnel:
                       Utilizing a
                       team; (b) Method of
                       communication: In-

Table 2.

Clinical Decision Unit Critical Project Components

                                  Norton Audubon Hospital
Key Design Elements                   Success Factors

Identified key          *  Multidisciplinary, including nurses,
stakeholders and          physicians, diagnostic area leaders
project team.

Identified physical     *  Ten-bed unit adjacent to telemetry
space, capital, and       unit (see Table 4 for more detailed unit
operational budget        characteristics)
                        *  Some renovation required

                        *  Capital costs, mainly cardiac
                          monitoring and updated nurse call

Developed               *  Admission criteria include prior
evidence-based            history of congestive heart failure (new
admission/discharge       diagnosis excluded), vital signs and
criteria, order           pulse oximetry within defined
sets, nursing             parameters, and a clinical assessment by
workflows, and            treating provider and nurses indicating
documentation tools.      high likelihood of symptom correction to
                          baseline within 24 hours.

                        *  Medical protocols include aggressive
                          diuresis, diagnostics, and medication
                          regimen calibration for symptom control
                          and electrolyte balance.

Recruitment and         *  RN-to-patient ratio 1:5. Addition of
onboarding of core        support staff as volumes increase
cardiology and/or
emergency department
registered nurses

Evidence-based          *  Use of predictive index to guide
nursing                   discharge plans
                        *  Additional assessment if patient is a
                          mitigated 30-day readmission or
                          identified as high risk

                        *  Areas assessed include follow-up
                          appointments, adherence to medication
                          regimen, home services provided,
                          understanding of signs and symptoms that
                          require additional follow-up

Table 3.

Clinical Decision Unit Year 1 Start Up Costs

Budget Item                Actual Cost   Year 1 Projection

Capital and renovations     $304,104

Operations                                   $736,544
(staffing and supplies)

Table 4.

Norton Audubon Hospital Clinical Decision Unit

* 10-bed unit (6 private rooms/4-bed bay)

* Located on 3rd Floor (emergency department on 1st)

* Adjacent to telemetry unit

* Nurse manager shared with telemetry unit

* RN-to-patient ratio 1:5

* Patients managed by cardiology practice

Table 5.

Clinical Decision Unit Analysis

                         Comparison Hospital             NAH

Variable                Pre    Post    Change    Pre    Post    Change

Congestive heart        26      17      (8)      21      23       2
failure readmission
percent (1)

Percent of selected    4.48    4.83     0.35    1.15    9.02     7.86
encounters that are
observation (2)

Cost/CHF inpatient     3,644   5,304   1,660    3,469   3,904    435
or observation
encounter ($) (2)

Predictive             23.63   21.64   (1.99)   22.18   24.71    2.53
index (3)

                         NAH vs. Comparison

Variable               in Change    p Value *

Congestive heart           10         0.54
failure readmission
percent (1)

Percent of selected       7.51        0.01
encounters that are
observation (2)

Cost/CHF inpatient      (1,225)       0.37
or observation
encounter ($) (2)

Predictive                4.52       0.1293
index (3)


(1) Pre = 1/1/12-11/31/12; Post = 12/3/12-2/28/13

(2) Pre = 12/3/11-5/31/12; Post = 12/3/12-5/31/13.
Inpatient or observation only, excludes emergency
department, lab only, outpatient. Principal diagnosis of
heart failure only. Includes Norton strategic service lines
of medical cardiology or cardiology only (excludes cardiac
surgery, invasive cardiology). Excludes replace/implant
cardiac defibrillator. Excludes any case with variable cost
below $100. Changed any cost below $300 to $300 and any cost
over $40,000 to $40,000 to reduce impact of outliers.
Excluded if 3+ days in intensive care/cardiac care unit.

(3) Pre = 9/1/12-11/31/12; Post = 12/3/12-3/31/13

* of difference in change

Table 6.

Direct Cost Avoidance Impact of Clinical Decision Unit (CDU)
on Congestive Heart Failure (CHF) and Simple Chest Pain Care
January 1, 2012-March 31, 2013

                                            CDU        Unit

Observation patients (CHF, chest pain)      302         57
Length of stay (hours)                     16.29       42.97
Hours saved                                8,058
Days saved quarter 1 2013                   336
Annualized days saved                      1,344
Actual cost reduction * quarter 1 2013    $132,621
Annualized cost reduction *               $530,484

* NOTE: Quarter 1 and Annualized cost reduction = Days saved
in each category multiplied by $395 cost/day. Excludes
capital cost.
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Author:Carpenter, Jo Ellen; Short, Nancy; Williams, Tracy E.; Yandell, Ben; Bowers, Margaret T.
Publication:Nursing Economics
Article Type:Report
Date:Sep 1, 2015
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