Predicting mortality in nursing home residents with lower respiratory tract infection: The Missouri LRI Study

CONTEXT

Lower respiratory tract infection (LRI) is a leading cause of mortality and hospitalization in nursing home residents. Treatment decisions may be aided by a clinical prediction rule that identifies residents at low and high risk of mortality.

OBJECTIVE

To identify patient characteristics predictive of 30-day mortality in nursing home residents with an LRI.

DESIGN, SETTING, AND PATIENTS

Prospective cohort study of 1406 episodes of LRI in 1044 residents of 36 nursing homes in central Missouri and the St Louis, Mo, area between August 15, 1995, and September 30, 1998.

MAIN OUTCOME MEASURE

Thirty-day all-cause mortality.

RESULTS

Thirty-day mortality was 14.7% (n = 207). In a logistic analysis, using generalized estimating equations to adjust for clustering, we developed an 8-variable model to predict 30-day mortality, including serum urea nitrogen, white blood cell count, body mass index, pulse rate, activities of daily living status, absolute lymphocyte count of less than 800/microL (0.8 x 10(9)/L), male sex, and deterioration in mood over 90 days. In validation testing, the model exhibited reasonable discrimination (c =.76) and calibration (nonsignificant Hosmer-Lemeshow goodness-of-fit statistic, P =.54). A point score based on this model's variables fit to the entire data set closely matched observed mortality. Fifty-two percent of residents had low (score of 0-4) or relatively low (score of 5-6) predicted 30-day mortality, with 2.2% and 6.2% actual mortality, respectively.

CONCLUSIONS

Our model distinguishes nursing home residents at relatively low risk for mortality due to LRI. If independently validated, our findings could help physicians identify nursing home residents in need of different therapeutic approaches for LRI.

Randomized clinical trial of a quality improvement intervention in nursing homes

PURPOSE

The purpose of the study was to determine if simply providing nursing facilities with comparative quality performance information and education about quality improvement would improve clinical practices and subsequently improve resident outcomes, or if a stronger intervention, expert clinical consultation with nursing facility staff, is needed.

DESIGN AND METHODS

Nursing facilities (n = 113) were randomly assigned to one of three groups: workshop and feedback reports only, workshop and feedback reports with clinical consultation, and control. Minimum Data Set (MDS) Quality Indicator (QI) feedback reports were prepared and sent quarterly to each facility in intervention groups for a year. Clinical consultation by a gerontological clinical nurse specialist (GCNS) was offered to those in the second group.

RESULTS

With the exception of MDS QI 27 (little or no activity), no significant differences in resident assessment measures were detected between the groups of facilities. However, outcomes of residents in nursing homes that actually took advantage of the clinical consultation of the GCNS demonstrated trends in improvements in QIs measuring falls, behavioral symptoms, little or no activity, and pressure ulcers (overall and for low-risk residents).

IMPLICATIONS

Simply providing comparative performance feedback is not enough to improve resident outcomes. It appears that only those nursing homes that sought the additional intensive support of the GCNS were able to effect enough change in clinical practice to improve resident outcomes significantly.

Prevalence, incidence, management, and predictors of venous ulcers in the long-term-care population using the MDS

OBJECTIVE

To describe the prevalence, incidence, management, and predictors of venous ulcers in residents of certified long-term-care facilities using the Minimum Data Set.

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

32,221 residents admitted to long-term-care facilities in Missouri between January 1, 1996, and October 30, 1998.

MAIN OUTCOME MEASURES

Version 2.0 of the Minimum Data Set was utilized. Assessment items included selected measures from background information, disease diagnoses, physical functioning and structural problems, health conditions, oral/nutritional status, and skin condition.

MAIN RESULTS

Venous ulcer prevalence on admission was 2.5%. The incidence of venous ulcer development for long-term-care residents admitted without an ulcer at 90, 180, 270, and 365 days after admission was 1.0%, 1.3%, 1.8%, and 2.2%, respectively. The most frequent skin treatments for residents with a venous ulcer were ulcer care, dressings, and ointments. Factors associated with venous ulcer development within a year of admission were diabetes mellitus, peripheral vascular disease, and edema.

CONCLUSION

Venous ulcer prevalence and incidence are greater in the long-term-care population than in the community at-large. Residents with a venous ulcer are likely to have comorbid conditions such as diabetes mellitus, peripheral vascular disease, congestive heart failure, edema, wound infection, and pain. Based on these data, risk factors such as history of leg ulcers, recent edema, diabetes mellitus, congestive heart failure, or peripheral vascular disease should prompt clinicians to carefully plan care that will manage a resident's risk for venous ulcer development.

Setting thresholds for quality indicators derived from MDS data for nursing home quality improvement reports: an update

BACKGROUND

Determining meaningful thresholds to reinforce excellent performance and flag potential problem areas in nursing home care is critical for preparing reports for nursing homes to use in their quality improvement programs. This article builds on the work of an earlier panel of experts that set thresholds for quality indicators (QIs) derived from Minimum Data Set (MDS) assessment data. Thresholds were now set for the revised MDS 2.0 two-page quarterly form and Resource Utilization Groups III (RUGS III) quarterly instrument.

SETTING THRESHOLDS

In a day-long session in October 1998, panel members individually determined lower (good) and upper (poor) threshold scores for each QI, reviewed statewide distributions of MDS QIs, and completed a follow-up Delphi of the final results.

REPORTING MDS QIS FOR QUALITY IMPROVEMENT

The QI reports compiled longitudinal data for all residents in the nursing home during each quarter and cumulatively displayed data for five quarters for each QI. A resident roster was provided to the nursing home so that the quality improvement team could identify the specific residents who developed the problems defined by each QI during the last quarter. Quality improvement teams found the reports helpful and easy to interpret.

SUMMARY AND CONCLUSIONS

As promised in an earlier report, to ensure that thresholds reflect current practice, research using experts in a panel to set thresholds was repeated as needed. As the MDS instrument or recommended calculations for the MDS QIs change, thresholds will be reestablished to ensure a fit with the instrument and data.

Light care residents in nursing homes: why they come, why they stay

With the increasing numbers of frail elderly, why light-care nursing home (NH) residents enter and remain in NHs is important to understand. Light-care residents (n = 98) from 11 NHs and their nurses were interviewed using open-ended questionnaires. Residents' care requirements were estimated using Resource Use Groups, Version III (RUG-III). We found that residents entered and remain in NHs because of the inability to perform instrumental activities of daily living, the fear of injury, ambulation problems, health problems, the lack of daily assistance, and a recent hospitalization. Most residents and nurses did not know of other options. These problems could be managed in the community if appropriate systems were in place.

Nursing home care quality: a multidimensional theoretical model integrating the views of consumers and providers

This exploratory study was undertaken to discover the defining dimensions of nursing home care quality from the viewpoint of consumers of nursing home care. Eleven focus groups were conducted in five Missouri communities. The seven dimensions of the consumer multidimensional model of nursing home care quality are: staff, care, family involvement, communication, environment, home, and cost. The views of consumers and families are compared with the results of a previous study of providers of nursing home services. An integrated, multidimensional theoretical model is presented for testing and evaluation. An instrument based on the model is being tested to observe and score the dimensions of nursing home care quality.

Minimum Data Set and Resident Assessment Instrument. Can using standardized assessment improve clinical practice and outcomes of care?

Regulating and standardizing the assessment of residents was envisioned by the 1986 Committee on Nursing Home Reform to have many advantages for facility management, government regulatory agencies, and clinical staff to evaluate changes in resident status and adjust the care plans accordingly. Standardized assessment data was viewed as a source of management information to be used to track case mix (i.e., acuity) of residents, allocate resources such as staff, and evaluate care quality. The Resident Assessment Instrument is a clinically relevant assessment process that can facilitate effective care planning, interventions, and quality improvement. It is a clinically complex process requiring care delivery systems developed by RNs to support the implementation of individualized care.

Mortality from lower respiratory infection in nursing home residents. A pilot prospective community-based study

BACKGROUND

Lower respiratory infections (LRI) are an important cause of morbidity, mortality, and hospitalization of nursing home residents, yet treatment recommendations have primarily been based on the minority who are hospitalized. We sought to prospectively evaluate risk factors for mortality from LRI in community nursing home residents.

METHODS

We studied residents of 10 central Missouri nursing homes (910 beds) from January 1994 to September 1994. Attending physicians authorized nurse evaluations of ill residents who showed symptoms of an LRI. Those residents who met the study definition of LRI received a more detailed assessment and follow ups at 30 and 90 days.

RESULTS

The 231 evaluations identified 141 LRIs in 121 individuals. Sixteen (11%) residents died within 30 days of evaluation. The most important univariate predictor of 30-day mortality was severe activities of daily living (ADL) dependency (relative risk = 8.8, 95% confidence interval, 2.55-30.1). Several other clinical and laboratory findings were also significant predictors. In multivariable logistic regression, ADL dependency, respiratory rate, and pneumonia on chest radiograph independently predicted mortality; the model showed good discriminating ability (c = .83).

CONCLUSIONS

For nursing home residents with LRI, ADL dependency is an important mortality predictor. Further research with a larger sample should lead to a useful prediction rule for outcome from nursing home-acquired LRI.

Nursing home care quality: a multidimensional theoretical model

This exploratory study was undertaken to discover the defining dimensions of nursing home care quality and to propose a conceptual model to guide nursing home quality research and the development of instruments to measure nursing home care quality. Three focus groups were conducted in three central Missouri communities. A naturalistic inductive analysis of the transcribed content was completed. Two core variables (interaction and odor) and several related concepts emerged from the data. Using the core variables, related concepts, and detailed descriptions from participants, three models of nursing home care quality emerged from the analysis: (1) a model of a nursing home with good quality care; (2) a model of a nursing home with poor quality care; and (3) a multidimensional model of nursing home care quality. The seven dimensions of the multidimensional model of nursing home care quality are: central focus, interaction, milieu, environment, individualized care, staff, and safety. To pursue quality, the many dimensions must be of primary concern to nursing homes. We are testing an instrument based on the model to observe and score the dimensions of nursing home care quality.

Verifying nursing home care quality using minimum data set quality indicators and other quality measures

Researchers, providers and government agencies have devoted time and resources to the development of a set of Quality Indicators derived from Minimum Data Set (MDS) data. Little effort has been directed toward verifying that Quality Indicators derived from MDS data accurately measure nursing home quality. Researchers at the University of Missouri-Columbia have independently verified the accuracy of QI derived from MDS data using four different methods; 1) structured participative observation, 2) QI Observation Scoring Instrument, 3) Independent Observable Indicators of Quality Instrument, and 4) survey citations. Our team was able to determine that QIs derived from MDS data did differentiate nursing homes of good quality from those of poorer quality.

Setting thresholds for MDS (Minimum Data Set) quality indicators for nursing home quality improvement reports

BACKGROUND

Determining meaningful thresholds to reinforce excellent performance and flag potential problem areas is critical for quality improvement reports. Without thresholds, an organization may interpret its performance as superior to others because it is "better than average" and falsely assume it does not have care problems in certain areas.

SETTING THRESHOLDS

The Minimum Data Set (MDS) assessment instrument is mandated for use nationwide in all nursing homes participating in Medicaid or Medicare programs. Since 1993 a research team at the University of Missouri-Columbia has been developing and testing quality indicators (QIs) derived from MDS data as a foundation for quality improvement activities. In July 1996, a cross-section of 13 clinical care personnel from nursing homes participated on an expert panel for threshold setting for QIs derived from MDS assessment data. Panel members individually determined good and poor threshold scores for each QI, reviewed statewide distributions of MDS QIs, and, two weeks later, completed a follow-up Delphi round. Three members of the research team reviewed the results of the expert panel and set the final thresholds. With thresholds established for good and poor scores, MDS QI scores are reported to a sample of Missouri nursing homes using the thresholds.

CONCLUSIONS

To ensure that thresholds reflect current practice, threshold setting with another panel of experts will be repeated as needed, but at least biannually. The report format will be revised on the basis of user input, and a statewide study testing different educational support methods for quality improvement using MDS QIs is now underway.