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Value-Based Resource Management A Model for Best Value Nursing Care

Barbara A. Caspers, MS, BSN, RN; Beth Pickard, BSN

With the health care environment shifting to a value-based payment system, Catholic Health Initiatives nursing leadership spearheaded an initiative with 14 hospitals to establish best nursing care at a lower cost. The implementation of technology-enabled business processes at point of care led to a new model for best value nursing care: Value-Based Resource Management. The new model integrates clinical patient data from the electronic medical record and embeds the new information in care team workflows for actionable real-time decision support and predictive forecasting. The participating hospitals reported increased patient satisfaction and cost savings in the reduction of overtime and improvement in length of stay management. New data generated by the initiative on nursing hours and cost by patient and by population (Medicare severity diagnosis- related groups), and patient health status outcomes across the acute care continuum expanded business intelligence for a value-based population health system. Key words: acuity, cost, length of stay, population health management, resource management, staffing

The essential question for the leader is now not so much about how much good work has been done, but, instead, whether the work made any difference.

—Rich and Porter-O’Grady1(p278)

C ARE FOR OUR PATIENTS, families, andcommunities has become increasingly complex and fragmented, resulting in ris- ing health care costs for providers, payers, and consumers. The Institute of Medicine responded to these growing challenges by proposing actions that a health care system

Author Affiliations: Nursing Operations and Acute Care Practice, Catholic Health Initiatives, Denver, Colorado (Ms Caspers); and Clairvia, Cerner Corporation, Kansas City, Kansas (Ms Pickard).

The authors thank Drs John M. Welton and Kathleen Sanford for providing the cornerstone for their work and passion to operationalize the economic value of nursing.

The authors declare no conflict of interest.

Correspondence: Barbara A. Caspers, MS, BSN, RN, Catholic Health Initiatives, 198 Inverness Dr West, En- glewood, CO 80112 (BarbaraCaspers@CatholicHealth .net).

DOI: 10.1097/NAQ.0b013e3182869e17

can take to (a) achieve major improvements in performance, (b) meet the needs of pa- tients and other users of health care services, and (c) provide affordable care. The Institute of Medicine describes best care as care that uses available evidence, takes appropriate ac- count of individual preferences, and care that is delivered reliably and efficiently. The Insti- tute of Medicine identifies opportunities for health care systems to address the complexity and escalating costs of care including the vast computational power and connectivity now widely available through the digitalization of the electronic medical record and other IT systems. Human and organization capabilities can improve care process efficiencies with the recognition that care must be delivered by col- laborative care teams composed of clinicians, patients, and all users of health care services.2

The new available patient data require inte- gration technology that embeds the new in- formation into operations and the care teams’ workflow for actionable decision making and predictive modeling.

Nurses play a critical role in the prescribed collaborative care teams. Hospital labor

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represents approximately 68% of all inpatient operational cost, with all nursing labor cost representing approximately 30%.3 As health care systems respond to a pay for value en- vironment and strive to achieve best care at a lower cost, nursing will have a major im- pact on the success of these efforts and will be the most transformed by pay for value changes. Two nursing imperatives identified for value-based nursing care include the fol- lowing: first, articulating the nursing prod- uct and prices for the provided services, and second, determining the economic value of nursing care to the health care system.4 Most nursing resource studies have focused on ag- gregate nurse staffing levels such as nursing hours per patient day (NHPPD) or nurse-to- patient ratios; however, there is a renewed fo- cus on the characteristics of individual nurses and how to optimize nursing care within the patient assignment to provide the best nurse to meet patient needs.5 An additional consid- eration when determining nursing care value is that nursing can no longer rely on the value of nursing care being the amount of good work done but must instead evaluate whether the work made a difference and ultimately de- termine the outcomes of nursing care.1 The purpose of this article is to describe a strate- gic initiative of 1 health care system to pio- neer innovative methods for improving the quality and value of patient care while reduc- ing the overall costs of care. Key components of the model and the steps to operationalize the model with technology-enabled business processes will be defined. The performance results will be discussed and implications for nursing will be identified.

THE INITIATIVE

In 2009, with the economic downturn and the approaching national agenda to control costs and purchase health care based on value, Catholic Health Initiatives (CHI) nursing lead- ership partnered with finance to take the lead in providing best care at a lower cost. Leader- ship from 14 hospitals formed an initiative to demonstrate how nurses could improve care

value by providing care aimed at creating indi- vidual desired patient outcomes (best care) at a lower care cost. The participating hospitals included an inner city hospital, several com- munity hospitals, and 1 critical access hospi- tal with licensed bed capacity ranging from 25 beds to more than 1000 beds. The average licensed bed capacity of 6 of the hospitals is 255 beds. The initiative included 3 midmarket multihospital health systems.

The hospitals organized around a plan to

implement standardized business processes sup- ported by real-time information about the quality, cost and outcomes of care enabling frontline nurs- ing staff to collaborate with care managers and physicians to better manage patient care, resources used in providing care, length of stay and clinical outcomes.

A collaborative governance model between CHI national, the participating hospitals, and the technology partner was established. This collaborative model supports the initiative at the national, system level and at the hospital, local market level. Mutual expectations of par- ticipation were defined for senior CHI system sponsors, hospital sponsors, and the technol- ogy partner.

CHI’s system chief nursing officer (CNO), chief information officer, and the 2 senior vice presidents of operations, governing the regions of the participating hospitals, with the chief executive of the technology part- ner serve as system coexecutive sponsors for the initiative. Hospital CNOs and CFOs serve as coexecutive sponsors at the hospital, lo- cal market level. This governance structure bolstered by the CNO chief financial officer dyad at the local market level defined the ini- tiative strategic vision, accountabilities, and measures of success. Today, it provides the structure for continuing dialogue, planning, and outcomes to align technology enhance- ments with CHI’s strategic and operational business objectives.

Six standardized business processes with enabling technology were implemented across all participating hospitals to deliver new improved reliability and efficiencies

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Table 1. Catholic Health Initiatives’ Technology-Enabled Standardized Business Processes

Nurse scheduling Staffing management Demand management Productivity management Care management Patient assignment

in care delivery. These processes, listed in Table 1, bring together a collaborative care team composed of the patient and his fam- ily, frontline nursing leaders, care managers, physicians, and other key ancillary health pro- fessionals and care partners around an elec- tronic database, with useful information from actual patient care.

A real-time chart illustrates the patient’s progress along the acute care continuum com- pared with established benchmarks for the levels of acute care for similar patients. The number of individual patient care hours re- quired for each patient based on nurses’ clin- ical documentation is displayed next to pa- tients’ names. These data enable nurses to as- sign the right caregiver to the right patient at the right time and to implement staffing pat- terns that produce the most effective resource utilization and optimal patient outcomes.

This is powerful information for both clini- cians and care partners in providing best value care. For CHI, these robust patient-level data available in real time represent new opportu- nities to benchmark performance and trans- fer learning and best practices across multi- ple hospitals and markets. This new capability is a major innovation in understanding how organized nursing is performing across CHI toward achievement of a system goal to op- timize nursing processes to improve overall outcomes of care, therefore care value.

Learning from the initiative, hospital nurs- ing and finance leaders determined that the old traditional resource management pro- cesses, measures, and reporting are inade- quate in a pay for value environment. The need to shift from a staffing perspective to a

focus on patient assignment became evident. The staffing perspective that if 4 nurses are available to care for 16 patients, each nurse will care for 4 patients assumes that, on aver- age, each of the 4 patients requires about the same amount of care. This thinking is limited in a value-based environment.

Working together, CHI nursing and finance leaders from the participating hospitals are developing a new model for best value care: Value-Based Resource Management. This new model offers a framework for value-based nursing care by linking individual nurses with individual patients within the electronic health record creating a new database. These new data are available to use in calculating re- source use (hours and dollars of direct care time) and overall resource patterns and to compare nurses and nursing care within and across CHI settings. These data are providing important new information to determine ac- tual nursing costs and to align payment for nursing care to achieve best value.

THE MODEL

CHI’s Value-Based Resource Management Model, depicted in Figure 1, integrates 4 core clinical operations concepts: productiv- ity, cost, acuity, and outcomes. Building on available evidence, the underlying assump- tion is that integration and management of these 4 ideals together result in clinical and operational excellence. Although most nurs- ing leaders have managed to these ideals in the

Figure 1. Catholic Health Initiatives’ model for Value-Based Resource Management.

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past, the capability to provide evidence that integrates these core concepts at the point of care and incorporates the information into fundamental nursing and patient care work- flows provides the platform for a value-based approach to resource management. In short, actualization of this model results in new data and information from actual patient care avail- able at the point of care. This new model sup- ports actionable decision making by frontline nursing leaders and other clinicians.

Productivity

CHI nursing leaders, like most, are skilled at managing nursing productivity for each shift, using a census driven NHPPD model with an expectation to flex nursing hours to accommodate changes in nursing unit census. Following each payroll period, they are provided retrospective reports that doc- ument nursing resource utilization and cost variances. However, little data are available that describe the actual patient demand on the units or reflect the actual nursing hours re- quired to meet the patient demand. With the new enabling point of care technology, the demands for patient care, including patient admissions, discharges, and transfers, are

captured real time and individual patient-level care hours, based on nurses’ documentation, and individual nurses’ workload are captured. These new data provide more informed decisions about the demand for patient care and the associated costs.

Using this real-time admissions, discharges, and transfers information, time periods of over- and underutilization are discovered.6 As a result, new processes and staffing patterns are implemented to decrease the demand vari- ability and to ensure effective staffing through- out the day. Electronic and virtual bed and staffing huddles using real-time information provide a forum for better enterprise dialogue on staffing and patient flow decision making. The technology-enabled productivity process also includes predictive algorithms so that nursing is not only reacting to current demand but also focusing on better planning for near- term resource management.

Productivity is displayed for frontline lead- ers at point of care on the electronic patient assignment illustrated in Figure 2. NHPPD are managed for each patient and the character- istics of the nurses providing the care are available for decision support. The point of care technology with its real-time information

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based on actual patient demand and individual patient care requirements enables CHI’s front- line nursing leaders to better manage produc- tivity while also ensuring fair and equitable assignments for caregivers.

Cost

As the technology-enabled business pro- cesses were implemented and new informa- tion became available at point of care, partic- ipating hospital nursing and finance leaders noted obvious limitations to current business processes and reporting. Current resource management and reporting focused on shift and daily resource utilization with no impact on resource cost, by patient, across the acute continuum of care. The new business pro- cesses and technology enabled not only real- time productivity management but also real- time resource cost management, by patient, directed by a collaborative care team that in- cludes care managers, bedside nurses, physi- cians, ancillary health professionals, patients, families, and other care partners. New col- laborative care rounds prescribed in the new business process were implemented across all hospitals. These “touch base” rounds have a singular focus in determining whether the pa- tient is clinically ready to transition to another level of acute care, ready for departure to the post–acute care continuum, or ready to care for himself at home. Based on available, real- time clinical and cost information from actual patient care, the collaborative care team de- termines patient progress along the acute care continuum and his expected length of stay (LOS) in the acute care setting. Available LOS benchmark data, the Centers for Medicare & Medicaid Services geometric mean by Medi- care severity diagnosis-related groups (MS- DRGs), guide the patterns of care and the care team decision process. The MS-DRG, which groups patients with similar clinical problems that are expected to require similar amounts of hospital resources, provides the means to analyze expected reimbursements for Centers for Medicare & Medicaid Services populations against actual LOS for the patient and to com- pare populations across hospitals.

With technology-enabled capability to man- age resource cost at point of care, new LOS management processes were put in place. Each fiscal year, the participating hospitals now select 20 MS-DRGs for improved per- formance and hospital inpatient nursing units identify the 5 most common patient popu- lations (MS-DRGs) admitted to the unit for optimal LOS management. The patient pop- ulations targeted for improved management are identified and vetted by both nursing and finance leadership. The MS-DRGs may represent high-cost cases, high-volume cases, physician preference, or cases that represent population-based service line opportunities. The decision process is local and focuses on meeting the unique population health man- agement needs of each hospital market.

In 1 hospital market, the total joint replace- ment population is a key strategic surgical population and is targeted for future growth. In June 2010, this hospital implemented the new standard care management process with enabling technology for 100 days. This effort achieved improved LOS outcomes and signif- icant increases in overall patient satisfaction with hospital care and with information at dis- charge. In late 2011, using on demand trend- ing capability, an increase in LOS among to- tal joint replacement patients was forecasted. Once again, this population was targeted for care management using the point of care en- abling technology to optimize planning for departure to another level of acute care, to the post–acute care continuum or home. In March 2012, management of the total joint replacement population had again improved resulting in a significant drop in LOS for this population, with improved patient satisfac- tion. The capability to use this point of care technology to manage populations across the acute care continuum has been demonstrated in the initiative. The opportunities continue to evolve in the management of population health across the acute care continuum to the post–acute care continuum.

Figure 3 depicts improvements in LOS management driven by 1 participating hospi- tal’s collaborative care teams. An unexpected

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Figure 3. Participating hospitals’ length of stay (LOS) savings. Abbreviation: DRGs, diagnosis- related groups.

outcome of the new business process was consistent improvement in Hospital Con- sumer Assessment of Healthcare Providers and Systems scores for patient satisfaction with information at discharge during the same time period as shown in Figure 4. The new col- laborative care team process also improved re- liability and efficiency in care delivery by pro- viding better information for resource man- agement. New reports on patient demand, illustrated in Table 2, include resource cost

by patient population (MS-DRG), allowing the collaborative care team to identify opportuni- ties for performance improvement. This re- port enables a new comparison of actual di- rect nursing costs per case by MS-DRG across the acute care continuum. Actual direct nurs- ing costs for each care level along the contin- uum are identified. The analysis of these data identifies potential over utilization of nurs- ing care hours in high-cost care levels such as intensive care. In addition, the NHPPD by MS-DRG allow comparison with the unit- budgeted NHPPD to ensure that budgeted nursing resources reflect the actual care needs of the patient population.

Participating hospitals established that traditional productivity models and standards are important for fiscal planning and align- ment; however, they provide little actionable information for frontline nursing leaders and clinicians to manage unit operations and pa- tients across the acute care continuum. New available information with better predictive data about individual patient populations improved clinical decision making. New ways to improve the total resource cost for each patient across the acute care continuum led to new cost savings opportunities.

Figure 4. Graph displays participating Hospital A top box scores for patient satisfaction: Discharge information. Hospital Consumer Assessment of Healthcare Providers and Systems increased during 12 month period following go-live of new business processes with enbling technology. Source: Health- stream Data reported as rolling annual values through June 2012.

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Value-Based Resource Management 101

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Acuity

Methods for establishing patient acu- ity were inconsistent across participating hospitals. Most were traditional and relied on individuals’ clinical intuition and judg- ment. This led to variation in assessment of individual patient acuity and often ineffec- tive resource management. Some hospitals used “home grown” acuity systems to bol- ster census-driven resource management deci- sions. For all hospitals, maintaining these tra- ditional methods was data intensive for nurs- ing personnel and, moreover, the data seldom aligned with hospital financial reporting.

The digital data available in the electronic record contain a vast array of patient-specific indicators that have been shown to determine variation in nursing workload.7,8 The partici- pating hospitals supported this approach for establishing nursing workload and agreed to leverage available patient data in the elec- tronic health record to establish individual pa- tient acuity and individual patient care needs. To accomplish this with no additional or du- plicative work for frontline nurses, the acu- ity score and associated workload are calcu- lated from existing available patient indica- tors in the electronic health record, includ- ing nursing assessments, interventions, labo- ratory results, and medications. This decision simplified resource management workflows for nursing personnel, already challenged to maintain top quartile productivity, and elim- inated the subjectivity inherent in individual clinical judgment.

An outcomes approach, versus a task ori- entation, was selected to ensure that acuity- driven workloads and resource management decisions were based on progressing each pa- tient’s health status to the desired outcomes at each transition or level of care along the acute care continuum.9 Patient outcomes experts, nurses, and clinicians from all participating hospitals identified and standardized individ- ual health status outcomes for their specific patient populations using Nursing Outcomes Classification taxonomy.10 Electronic health record indicators representing the various populations health status outcomes were then

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mapped across multiple electronic records and across all participating hospitals. The data are standardized across like populations in all participating hospitals for comparability across CHI.

Frontline nursing leaders evaluate new data on the progression of each patient to de- sired nursing outcomes. Nursing leaders eval- uate individual patient care needs and actual available hours by individual nurse as well as the competencies and characteristics of the nurses available to perform the work. This approach to resource management supports the professional practice obligation of nurses and clinicians to provide the appropriate care for the needs of the individual health care consumer, families, and populations served, while matching a nurse’s expertise with the needs of the recipient of nursing services.11

Patient health status outcomes

Creating value requires bringing cost and quality together, the 2 factors of the value

equation, and defining them around out- comes. To measure performance improve- ment resulting from the new business pro- cesses and technology, the participating hos- pitals aligned project outcomes with key CHI strategic and operations metrics. These out- comes metrics included patient satisfaction, LOS performance of hospital-selected MS- DRGs, and nursing overtime. Figure 5 repre- sents the total cost savings of the participating hospitals over a 2-year period.

The outcomes were measured and re- ported to both nursing and finance stakehold- ers on a monthly basis through a Web-based analytics tool. The analytics provided each hospital with their own performance metrics and with a comparison of their individual hos- pital performance with peer hospitals. Partic- ipating hospitals experienced lower resource cost, lower patient lengths of stay, and im- proved patient satisfaction scores. With the new technology-enabled point of care busi- ness processes, they outperformed their CHI

Figure 5. Participating hospitals’ fiscal years 2011 and 2012 overtime and length of stay (LOS) savings. Abbreviations: FY, fiscal year; OT, overtime.

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peer hospitals. LOS data were also shared with hospital care management leaders at their monthly meetings. These data provided a source of rich dialogue and formed the ba- sis for knowledge exchange and transfer and for collaborative performance improvement activities.

The point of care technology has provided CHI with new patient population analyses using patient-level data. Data are available to analyze each transition across the acute care continuum and to analyze patient populations by MS-DRG within and across participating CHI hospitals. Data are available about total resource hours and unit population health status outcomes. These analyses will lead to new care delivery models and to process improvement.

To prove the initiative business case and to demonstrate the value of technology-enabled care in supporting better resource and cost management, participating hospitals aligned with CHI’s traditional enterprise performance metrics. Participating hospitals also agreed that a primary goal was to develop the infras- tructure and capability to extract and man- age the new evolving point of care database and analytics. These new data will ultimately provide the more meaningful information in a pay for value environment. This new infor- mation will lead to the transformation of care delivery including new models of care and in- formation about the characteristics and com- petencies of those nurses and caregivers that create the optimal outcomes for select patient populations.

Hospital and system CHI health care fi- nance leaders continue to work in partner- ship with CHI nursing leadership to create new business intelligence that is being used to optimize care value throughout CHI. The new, standard technology-enabled business processes allow CHI to allocate actual nurs- ing hours and cost data to individual patients and to develop new analytic models to better understand the value of care. The focus of this work is on measuring nursing’s contribution to creating desired health status outcomes for patient populations beginning with best care

and management of acute care populations at a lower cost.

IMPLICATIONS FOR NURSING

CHI nursing leadership continues to collab- orate with research colleagues to determine the impact of nurse staffing on CHI organi- zational goals, such as LOS, mortality rates, falls, and readmissions.12 Most of the out- comes measured are outcomes that “Should- Not” occur or are sometimes referred to as “Never Events.” These events have significant impact to the safety of our patients and fami- lies. A future consideration includes research to demonstrate the impact of nursing care in moving patients to their desired health status.

The new available data and analytics will drive new analyses about the impact of nurs- ing care hours related to the health status of each patient. In a pay-for-value environment, the ability to understand and interpret the contribution of nursing to individual health status outcomes is essential in developing new models of care, resourcing the models, and ultimately isolating the cost of nursing care. These data will shape nursing care deliv- ery in the future and have direct implications for identifying and measuring nursing’s con- tribution in bundled care payments and the evolving risk-bearing entities such as account- able care organizations.

To continue to drive lower cost and im- prove care efficiencies, resource management cannot be isolated as an operational silo. A new CHI nursing leadership initiative is to integrate other operational management pro- cesses that impact cost and care outcomes, in- cluding care management, revenue cycle, pa- tient flow, and patient tracking. The new ini- tiative integrates these core operational pro- cesses into 1 unified business process with technology that enables collective data man- agement and interpretation to drive improve- ment in acute care population health manage- ment. The current focus on population health and surveillance will require extending the business processes and technology across the full continuum of care, including extended care, ambulatory clinics, and medical homes.

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