Seeding information management capacity to support operational management in hospitals.

There are vast amounts of regularly reported data in the information systems of hospitals, state and federal governments. The increase in accessibility offered by platforms such as the Health Information Exchange (HIE) in New South Wales (NSW) creates a new level of opportunity. Administrative data can also speak to clinical and managerial issues. The capacity to mine these data and use the information for improving quality and efficiency has not been well developed at the "coal face" of operational management. Whilst it has been both possible and useful to track utilisation of services to hospitals and patients as cost and volume, it has not been of interest to track these same data to the operational locus of care--the nursing unit, the operating room, the imaging department. With HIE-type systems, the information is now more readily available and operational managers know this. The challenge is to develop the interdisciplinary capacity to query administrative data to facilitate clinical and managerial decision-making. We report here a possible model of a systematic approach to developing this capacity and some of the results of equipping operational and clinical managers to study problems in their own work settings. These efforts have required no additional internal resources, while the payoffs have been considerable.

From I.T. to information management with casemix data.

The Australian investment in technological support for the collection and analysis of hospital data has paid off in the creation of data depositories that can be used for system and policy analysis. Yet the inquiries that would inform decision for quality and efficiency improvement are made at the operational levels where there has not been equivalent investment in developing human capacity. This article suggests strategies and methods for using standard healthcare information that is now so much more readily available.

Bringing decision support to nurse managers.

Modern hospital nursing management requires timely and accurate information to allow nurse managers to adjust resources to patient requirements. We report an experience using production theory to provide the framework for the development of Decision Support Objects: graphic displays of nursing hours budgeted, scheduled, and worked within institution-specific control limits. Every month, nurse managers follow an analytic algorithm to understand nursing resources and trends on their units. Exception reporting closes the accountability loop. The essentials of education for nurse managers include skill training in the use of the decision-support tools and supportive lecture/seminars for understanding the managerial implications of using them.

Teaching information management.

Managing in the present chaotic hospital financing environment requires integrated clinical/financial data systems and people who know how to use them. Health care management students of the present and future will need to understand how these information systems are structured and used. This article describes a graduate course in integrated clinical/financial information management as it has evolved at Yale University. The course provides students a vicarious experience in information management through class sessions and exercises using a database of real patient and cost center level information. Health care management of the future will depend on interdisciplinary collaboration and partnerships in education between provider organizations and academic programs. Both are modeled in the course.

Casemix and nursing.

The American Nurses' Association did not embrace the introduction of diagnosis related groups, believing they would not recognise nursing activity nor acuity and would bring about the economic demise of nursing. Australian nurses, by contrast, recognised the window of opportunity that the work towards Australian national diagnosis related groups and funding mechanisms provided to move nursing resources into the political and policy mainstream. This paper reviews the American and Australian nursing experience with casemix, acuity and cost weighting. It uses examples from more recent work to argue for the use of casemix information in new ways, for 'process improvement' or 'evidence-based management'. The paper concludes that the next great leap forward in casemix may require attention to building the information and human infrastructures, so that the valuable clinical-financial information produced by casemix-based information systems can truly inform management and policy.

The effect of staff nursing on length of stay and mortality.

OBJECTIVES: Specialized hospital units developed historically for the efficiency of physicians, but their existence has created an opportunity for staff nurses to specialize as well. This study was done to test the hypothesis that specialized staff nursing has an effect on patient outcome as length of stay (LOS) and mortality, using casemix information and controlling for physician volume. METHODS: Sixteen Diagnosis Related Groups associated with particular specialty units in Yale New Haven Hospital were selected. Five years of data (FY 1987-FY 1993) from a period in which specialized unit configuration was relatively stable were obtained (N = 11,316). Data elements included basic patient characteristics, especially diagnosis and procedure codes, physician identifiers as scrambled code numbers, length of stay, length of intensive care unit stay, and discharge disposition. Specialized nursing units were defined by the percentage of patients in a given diagnosis related group discharged from that unit. Patient age and differential intensive care unit use were used for risk adjustment. RESULTS: In 13 of the 16 diagnosis related groups, patients cared for on specialized nursing units had shorter lengths of stay; the difference was statistically significant in nine. In the seven Diagnosis Related Groups with any deaths, the mortality on the specialized unit(s) was lower; the difference was statistically significant in four. Physician volume, defined as more or fewer than 20 discharges per diagnosis related group had little or no effect on either length of stay or mortality. CONCLUSIONS: The notion that nurses improve at caring for similar patients of a stable group of physicians as their experience increases has common sense appeal. If the findings of this study can be replicated in other institutions, with the refinements suggested here, it may be possible to separate the effects of multidisciplinary practice on outcomes and to track the effect of hospital reengineering projects that change patient mix or nursing specialization. Studying one hospital in depth suggested that interhospital studies of cost and quality may need to consider nursing specialization along with other comparisons.

Using hospital data systems to find target populations: new tools for clinical nurse specialists.

A newly appointed diabetes clinical nurse specialist/nurse practitioner at Yale-New Haven Hospital was charged with redesigning the diabetes nursing role. For help, she turned to a special information management service within the Nursing and Operational Finance departments. This article describes the project that used an integrated financial and clinical information system to locate and characterize adult patients with diabetes mellitus. Patients with principal and secondary diagnoses of diabetes were identified by ICD-9-CM codes and tracked across inpatient and outpatient services. These data were used to identify opportunities for case management and for managing the costs related to diabetes care. The data also supported proposals made by the clinical nurse specialist/nurse practitioner to management to allocate clinical resources for the care of patients with diabetes. When the clinical wisdom of advanced practice nurses is joined with nursing information management expertise and technology, opportunities for understanding and advancing nursing's work are revealed.

Understanding nursing resources in intensive care: a case study.

OBJECTIVE: We describe the use of a measurement of nursing acuity in an ICU based on data from an integrated clinical and financial information system to shed light on the problem of a perceived change in the work of the unit. SETTING: A surgical-neurosurgical ICU in a teaching hospital with more than 800 beds. DESIGN: Changes in the work of nursing, defined by nursing acuity and by case mix and use of ancillary services in this unit for an 18-month period, were reviewed. RESULTS: The caseload was unpredictable. The lack of a systematic pattern of use of hospital resources burdened the nurses. CONCLUSION: For the first time at this institution, timely clinical and financial information has been brought together in an understandable format that can be used to explain trends and variances, to plan for the future, and to manage for cost and quality. The model for information management described here might serve other hospitals as well.

Building a nursing management analysis capacity in a teaching hospital.

The authors describe one institution's efforts to create the capacity to use standard hospital information systems to address clinical and operational nursing questions. This work involved not only technical aspects of information management system creation but also building the human currency to make the information available and useful. Because the information available to nursing comes from the same data sources that feed operational management and finance departments, nursing can now speak in the same language at the policy tables.

Understanding the unmanageable nursing unit with casemix data. A case study.

The unmanageable nursing unit is one that has the reputation of being wastefully over budget, not using nursing resources well, not cost effective, and certainly not well managed. Serendipity led us to discover ways to understand the unmanageable unit in one institution. The nurse manager knew the unit was not working well, but had no way to describe this in clinical management terms that would be understood by others. When data from before and after major structural and system redesign initiatives became available, they showed a situation in which decisions were made without data that worked. How much better might it have been had the data that was now accessible been used? We suggest a design for using standard hospital data to define alleged problems of inefficient nursing units, the design is also the structure for monitoring the effects of management changes.

Nursing resource definition in DRGs. RIMS/Nursing Acuity Project Group.

The use of traditional nurse-specific patient classification/acuity systems for staffing are obsolete as they do not interact with other elements of hospital information systems (HIS). In the face of rapidly advancing managed care penetration the challenge for nursing has become the capability to measure and manage cost, quality, and outcomes by integrating nursing resource information into the standard HIS spawned by DRGs. Earlier efforts to quantify nursing relative intensity measures and correlate them with DRGs were not successful. New health care software technology (as well as combined financial and clinical department support) can now provide integrated clinical information and financial information by DRG for each patient's clinical record. Expert clinician medical-surgical and ICU nursing panels were empowered to evaluate and arrive at group consensus placing designated DRGs in clusters according to their average nursing care resource requirements. The method was tested and validated.

Data as textbook.

Hospital information systems have been collecting patient-related data systematically for years. This article describes a course developed at the Yale University School of Nursing that uses hospital data as "textbook" to teach graduate nursing students to navigate a large hospital data set, enabling a multitude of nursing questions to be addressed. The approach used in this course is easily transferrable to the practice setting as demonstrated by the authors. Through understanding patient-level data, their aggregate patterns, and overall database construction, nurses can expand their contributions to clinical practice and management.

Clinical scholarship.

Clinical research in nursing is well known and well described. Clinical scholarship is an alternative, but not a substitutable, form of nursing's intellectual activity. Clinical scholarship is described with examples. It is argued that for some kinds of nursing work, clinical scholarship is the appropriate method.

Finding nursing management data.

Hospitals have been collecting and storing patient information for many years. Although these data are used for reporting purposes, they are often overlooked as a rich source for the clinical and administrative management of patients. Nurse managers better then anyone recognize the diversity and complexity of patient care. Examples illustrate how an investigation of these data can provide the nurse manager with a wealth of important information critical in effectively managing within an acute care institution.

"Where have all the children gone"? Inpatient pediatric care in Connecticut.

Admission of children to hospitals in Connecticut dropped precipitously from 1981 to 1991. Regionalization of pediatric inpatient care is happening without plan. Connecticut data show a change in case-mix of pediatric cases, especially in surgical services and child mental illness categories. Planning for pediatric inpatient services should include considerations of case-mix, cost, and especially, quality of care in general hospital pediatric units with very low volume.

The effect of staff stress on patient behavior.

A "natural experiment" examined the effects of staff turmoil caused by personal and group issues during and after the merger of two formerly separate neuropsychiatric evaluation units, on patient acting-out behaviors. Interviews with staff members identified the periods of high staff stress, and then two periods of personal resolution (3 to 4 months after the merger) and group reconstitution (8 to 12 months later). Patient acting-out behaviors (1:1 supervision, length of time on 1:1, use of the quiet room, seclusion, and restraints) tended to peak at times of staff peace. Behaviors under patient control (72-hour notices and discharges against medical advice) were also frequent during these periods, but showed additional activity in the time between personal and organizational resolution. While the relationship between staff issues and patient behavior is by no means straightforward, analysis of quantitative and qualitative data gathered here provides some support to the "reverse hypothesis" that when staff are upset, patients will not act out and vice versa. Implications for management, clinical practice, and research are presented.