Minimum Data Set Quality Indicators Research Articles

SUSTAINING STAR-VA: EVALUATING SYSTEMIC OUTCOMES AND TEAM STRATEGIES FOR MANAGING BEHAVIOR SYMPTOMS OF DEMENTIA

The Veterans Health Administration (VHA) has invested in the implementation and evaluation of STAR-VA, a Veteran-centered, interprofessional intervention for managing behavioral symptoms of dementia (BSD), with 86 Community Living Center (CLC nursing home) teams between 2013 and 2018. Results of a VHA Quality Enhancement Research Initiative (QUERI) partnered evaluation project are presented, including a multi-site interprofessional network created to collaborate on evaluation of the longitudinal impact of STAR-VA on CLC Veteran- and site-level outcomes, and to determine factors associated with sustained implementation and positive outcomes. The development and validation of a Minimum Data Set quality indicator of behavior symptoms of dementia (BSD) is presented. Characteristics of STAR-VA trained and untrained CLCs are presented, along with facilitators and barriers to sustained program implementation. Findings support the effectiveness of implementation of STAR-VA on decreased use of psychotropic medication. Qualitative outcomes demonstrate importance of having the appropriate staff, positive team relationships, supportive usual routines, and culture as critical for STAR-VA sustainability efforts. Results emphasize the importance of using a valid, routine measure of BSD to provide feedback to CLC teams, and to develop a sustainability intervention focused on addressing reported barriers to program sustainability through interprofessional networks. Both qualitative and quantitative outcomes will inform development and recommendations for an implementation and evaluation strategy for an outcome-driven, tailored intervention to support CLC teams in sustaining STAR-VA and to improve poor-performer and maintain high-performer outcomes. The potential benefit of our findings for other interprofessional behavioral nursing home interventions will be discussed.

Quality Indicators as Predictors of Future Inspection Performance in Ontario Nursing Homes

ObjectivesThere are several mechanisms for monitoring the quality of care in long-term care (LTC), including the use of quality indicators derived from resident assessments and formal inspections. The LTC inspection process is time and resource-intensive, and there may be opportunities to better target inspections. In this study, we aimed to examine whether quality indicators could predict future inspection performance in LTC homes across Ontario, Canada. Setting and ParticipantsIn total, 594 LTC homes across Ontario. MethodsUsing a database compiling detailed inspection reports for the period from 2017 to 2018, we classified each home into 1 of 3 categories (in good standing, needing improvement, needing significant improvement). Machine learning techniques were used to examine whether publicly available Resident Assessment Instrument‒Minimum Data Set quality indicators for the period 2016‒2017 could predict facility classification based on inspection results. ResultsAfter running a wide range of models, only a weak relationship was found between quality indicators and future inspection performance. The best-performing model was able to achieve a classification accuracy of 40.1%. Feature analysis was performed on the final model to identify which quality indicators were most indicative of predicted poor performance. Experiencing worsened pain, restraint use, and worsened pressure ulcers were correlated with homes predicted as needing significant improvement. Counterintuitively, improved physical functioning had an inverse relationship with homes predicted as being in good standing. Conclusions and implicationsMost quality indicators are poor predictors of inspection performance. Further work is required to explore the limited relationship between these 2 measures of LTC quality, and to identify other quality measures that may be useful as predictors of facilities facing difficulty in meeting quality standards.

Validation of the ICU-DaMa tool for automatically extracting variables for minimum dataset and quality indicators: The importance of data quality assessment

BackgroundBig data analytics promise insights into healthcare processes and management, improving outcomes while reducing costs. However, data quality is a major challenge for reliable results. Business process discovery techniques and an associated data model were used to develop data management tool, ICU-DaMa, for extracting variables essential for overseeing the quality of care in the intensive care unit (ICU). ObjectiveTo determine the feasibility of using ICU-DaMa to automatically extract variables for the minimum dataset and ICU quality indicators from the clinical information system (CIS). MethodsThe Wilcoxon signed-rank test and Fisher’s exact test were used to compare the values extracted from the CIS with ICU-DaMa for 25 variables from all patients attended in a polyvalent ICU during a two-month period against the gold standard of values manually extracted by two trained physicians. Discrepancies with the gold standard were classified into plausibility, conformance, and completeness errors. ResultsData from 149 patients were included. Although there were no significant differences between the automatic method and the manual method, we detected differences in values for five variables, including one plausibility error and two conformance and completeness errors. Plausibility: 1) Sex, ICU-DaMa incorrectly classified one male patient as female (error generated by the Hospital’s Admissions Department). Conformance: 2) Reason for isolation, ICU-DaMa failed to detect a human error in which a professional misclassified a patient’s isolation. 3) Brain death, ICU-DaMa failed to detect another human error in which a professional likely entered two mutually exclusive values related to the death of the patient (brain death and controlled donation after circulatory death). Completeness: 4) Destination at ICU discharge, ICU-DaMa incorrectly classified two patients due to a professional failing to fill out the patient discharge form when thepatients died. 5) Length of continuous renal replacement therapy, data were missing for one patient because the CRRT device was not connected to the CIS. ConclusionsAutomatic generation of minimum dataset and ICU quality indicators using ICU-DaMa is feasible. The discrepancies were identified and can be corrected by improving CIS ergonomics, training healthcare professionals in the culture of the quality of information, and using tools for detecting and correcting data errors.

A Longitudinal Assessment of the Effect of Resident-Centered Care on Quality inVeterans Health Administration Community Living Centers.

To examine whether changes in resident-centered care (RCC) over time were associated with changes in quality. Data sources were the Minimum Dataset quality indicators (which consist of measures of both prevalence and incidence of adverse events) and the Artifacts of Culture Change Tool (which measures RCC; FYs 2009-2012) from 130 Veterans Health Administration community living centers. A retrospective longitudinal study. Data were from VA secondary data sources. The overall relationship between RCC and quality was not statistically significant (p=.22), although there was a weakly significant negative relationship (i.e., increased RCC was associated with poorer quality) in the seven quarters after implementation of an automated version of the Artifacts Tool (p=.08). In facility-specific analyses, there were 15 facilities with a weakly significant (p<.10) positive relationship between RCC and quality and 21 with a weakly significant negative relationship. Adjusted cost per patient day was over 50 percent higher in the 21 facilities with a negative relationship than in the 15 facilities with a positive relationship (p<.05). The Artifacts score is a formal performance metric in the VA, and thus, facilities were explicitly incentivized to increase RCC. Using qualitative methods to identify characteristics that distinguished those facilities able to increase both RCC and quality from those that suffered declines in quality as RCC was improved is an important follow-up to this study.

Perceptions of staff quality improvement training needs among Veterans Affairs nursing home leadership

This study seeks to describe clinical leadership’s perceptions of staff understanding of the minimum data set (MDS) quality indicators (QIs) and ways to improve staff understanding of this system, as well as specific perceived training needs among Department of Veterans Affairs (VA) nursing home care unit (NHCU) clinical leadership. This cross-sectional online survey using structured (quantitative) and open-ended (qualitative) items took place in 97 VA NHCUs nationwide. A total of 289 leadership staff including directors of nursing, medical directors, MDS coordinators participated. Qualitative analysis yielded several themes regarding why staff do/do not understand MDS QIs, and strategies to improve staff understanding included involvement, staffing/staff roles, education/training, mechanics, big picture. Regarding how to improve understanding, respondents recommended education/training, involvement, reinforcement and others. Of specific training strategies/needs, the most frequently identified were using the MDS as a clinical assessment tool. Quantitative analyses were not significant. These results highlight the range of causes identified by managers for frontline staff’s understanding (or lack thereof) of the QIs, and their preference for ways to improve staff understanding of what the MDS means. Understanding and applying these strategies may help improve staff’s use of the MDS QIs in VA and non-VA skilled nursing facilities.

An evaluation of a person-centred care programme for long-term care facilities

ABSTRACTPerson-centred approaches in long-term care focus on providing holistic care to residents in order to improve quality of life, enhance resident wellbeing and autonomy, and mitigate behavioural and/or other symptoms. The results of research on person-centred approaches to care are mixed, with very few high-quality empirical studies examining resident outcomes specifically. The purpose of this investigation was to examine a person-centred care programme implemented in three Canadian long-term care facilities to determine its effect on resident outcomes, approach to care and maintenance of the programme three years after implementation. Using the Resident Assessment Instrument Minimum Data Set (RAI-MDS) scale scores and quality indicators, we retrospectively examined resident outcomes before, after and six months following the initiation of the programme using three additional facilities as control. We did not find any effects on resident outcomes. Focus group interviews with facility staff revealed no systematic differences between the programme and control facilities in their approach to care. All facilities supported aspects of a person-centred philosophy. Focus group interview data from the programme facilities indicated partial maintenance in two facilities and more complete maintenance in one facility. Although staff members supported the programme, implementation and maintenance proved difficult and effectiveness on resident outcomes was not indicated in this research. Additional controlled studies are needed.

Association between Traditional Nursing Home Quality Measures and Two Sources of Nursing Home Complaints

To test for an association between traditional nursing home quality measures and two sources of resident- and caregiver-derived nursing home complaints. Nursing home complaints to the North Carolina Long-Term Care Ombudsman Program and state certification agency from October 2002 through September 2006 were matched with Online Survey Certification and Reporting data and Minimum Data Set Quality Indicators (MDS-QIs). We examine the association between the number of complaints filed against a facility and measures of inspection violations, staffing levels, and MDS-QIs. One observation per facility per quarter is constructed by matching quarterly data on complaints to OSCAR data from the same or most recent prior quarter and to MDS-QIs from the same quarter. One observation per inspection is obtained by matching OSCAR data to complaint totals from both the same and the immediate prior quarter. There is little relationship between MDS-QIs and complaints. Ombudsman complaints and inspection violations are generally unrelated, but there is a positive relationship between state certification agency complaints and inspection violations. Ombudsman and state certification agency complaint data are resident- and caregiver-derived quality measures that are distinctive from and complement traditional quality measures.

Thresholds for Minimum Data Set Quality Indicators Developed and Applied in Icelandic Nursing Homes

A modified Delphi method was used to determine thresholds for Minimum Data Set quality indicators for Icelandic nursing homes. The thresholds were then applied to quality outcomes in Icelandic nursing homes for the year 2009. The thresholds indicate areas of good or poor care and can be used for planning services. Icelandic nursing homes seem to be doing best in incontinence and nutritional care. However, improvement is needed in care practices for depression, medication, and activity.

Quality of care in Icelandic nursing homes measured with Minimum Data Set quality indicators: Retrospective analysis of nursing home data over 7 years

BackgroundThe increasing need for long-term care as well as diminished financial resources may compromise the quality of care of older people. Thus the need for clinically based quality of care monitoring to guide development of long-term services has been pointed out. ObjectivesThe aim of this study was to investigate trends in quality of care during 2003–2009 as reflected in the Minimum Data Set quality indicator outcome in Icelandic nursing homes and to investigate the association of Minimum Data Set quality indicators with residents’ health status (health stability, pain, depression and cognitive performance) and functional profile (activities of daily living and social engagement). DesignRetrospective analysis of nursing home data over 7 years. MethodsThe sample used for analysis was 11,034 Minimum Data Set assessments of 3694 residents living in Icelandic nursing homes in 2003–2009. Minimum Data Set quality indicators were used to measure quality of care. The chi-square test for trend and multivariate logistic regression were used to analyse the data. ResultsThe mean age of residents during the period of the study ranged from 82.3 (SD 9.1) to 85.1 (SD 8.3) and women accounted for from 65.2% to 67.8%. Findings for 16 out of 20 quality indicators indicated a decline in quality of care (p<0.05), although in 12 out of 20 indicators the prevalence was lower than 25%. One quality indicator showed improvement, i.e. for “Bladder and bowel incontinence without a toileting plan” from 17.4% in 2003 decreasing to 11.5% in 2009 (p<0.001). Residents’ health and functional status partially explain the increased prevalence of the quality indicators over time. ConclusionFurther developments in quality of care in Icelandic nursing homes need to be monitored as well as the association between residents’ health and functional status and the Minimum Data Set quality indicator outcome. The areas of care where the Minimum Data Set quality indicators showed need for improvement included treatment of depression, number of medications, resident activity level and behavioural symptoms.

Physician Intervention for Medication Reduction in a Nursing Home: The Polypharmacy Outcomes Project

To examine the effects of a medication review project by geriatricians and geriatric medicine fellows on polypharmacy in a teaching nursing home. Quality improvement intervention study Long-term care facility in Honolulu, HI PARTICIPANTS: Seventy-four patients with the Minimum Data Set quality indicator criteria of polypharmacy (9 or more medications). Geriatric medicine fellows and faculty reviewed each patient's medication list, consulted the updated Beers Criteria and Epocrates online drug-drug interaction program, and recommended medication changes to the patients' primary care physicians. Descriptive statistics, including means, standard deviations, and sums of variables were obtained for the number of medications in the following categories: total number, scheduled, pro re nata, high risk, contraindicated, with potential drug-drug interactions, and with no indication. Of 160 patients residing in a nursing home, 74 were on 9 or more medications. After the intervention, the mean number of medications per patient in the following categories decreased significantly: total number (16.64 to 15.54, P < .001), scheduled (11.3 to 10.99, P < .001), pro re nata (5.33 to 4.56, P < .001), high risk (0.94 to 0.73, P < .001), contraindicated (0.29 to 0.13, P = .004), with potential drug-drug interactions (6.1 to 4.83, P < .001), and with no indication (3.34 to 3.29, P = .045). Polypharmacy in long-term care is prevalent and can lead to increased adverse effects and potentially inappropriate prescriptions. This study demonstrates an effective geriatrician-led intervention that both reduced polypharmacy and provided core competency training for geriatric medicine fellows.

Benchmarking clinical indicators of quality for Australian residential aged care facilities

To undertake exploratory benchmarking of a set of clinical indicators of quality care in residential care in Australia, data were collected from 107 residents within four medium-sized facilities (40-80 beds) in Brisbane, Australia. The proportion of residents in each sample facility with a particular clinical problem was compared with US Minimum Data Set quality indicator thresholds. Results demonstrated variability within and between clinical indicators, suggesting breadth of assessment using various clinical indicators of quality is an important factor when monitoring quality of care. More comprehensive and objective measures of quality of care would be of great assistance in determining and monitoring the effectiveness of residential aged care provision in Australia, particularly as demands for accountability by consumers and their families increase.

Enhanced Toileting Program Decreases Incontinence in Long Term Care

Incontinence is a common problem in long term care. In March 2003, in reviewing its performance on the Minimum Data Set (MDS 3.0) quality indicators, Sea View Hospital Rehabilitation Center and Home, a 304-bed long term care facility in Staten Island, New York, discovered it was 39% above the average of the state and national means for the incontinence indicators. In response, it initiated a facilitywide performance improvement project. Processes identified in the action plan for the project, "Residents who trigger for occasional or frequent bowel and bladder incontinence on MDS will be assessed for an individualized toileting schedule," included (1) revision of assessment documentation, which improved the initial assessment of continence, with an added reassessment process; (2) documentation of the toileting plan on the Patient Care Technician Assignment Card and the Activity of Daily Living Accountability Sheet; (3) adoption of toilet-assist devices; (4) hospitalwide in-service on incontinence and toileting; and (5) revision of the bowel and bladder incontinence policy. After implementation of the revised bowel and bladder incontinence assessment tool, the rate of incontinence without a toileting plan decreased--from 79% to 38%--and remained below the yearly mean. The new assessment processes made individualized planning possible and accurate. This initiative could be easily replicated because it requires resources that are basic to most long term care facilities.

Quality Indicators in the Department of Veterans Affairs Nursing Home Care Units: A Preliminary Assessment

The authors analyzed the minimum data set quality indicators data aggregated nationally from 134 Department of Veterans Affairs nursing home care units with more than 15,000 long-stay residents (>90 days) yearly for federal fiscal years 2003, 2004, and 2005. Despite an increase in the severity of illness and complexity of services as determined by the minimum data set case-mix indices, most of the minimum data set quality indicators showed an improvement (rate decrease) from fiscal year 2003 to fiscal year 2005, whether examined on a year-to-year basis or by an overall 3-year trend. Nationally, there was a 5.1% increase in average case-mix index, while 14 of 24 quality indicators showed a decrease in the prevalence/ incidence rates and only 4 quality indicators showed increased rates. These minimum data set results provide important information for Veterans Affairs quality managers regarding areas of achievement and also identify areas to be targeted for future quality improvement.

Impact of Medicaid reimbursement on mental health quality indicators.

To examine the relationship between the use of the Minimum Data Set (MDS) for determining Medicaid reimbursement to nursing facilities and the MDS Quality Indicators examining nursing facility residents' mental health. The 2004 National MDS facility Quality Indicator reports served as the dependent variables. Explanatory variables were based on the 2004 Online Survey Certification and Reporting system (OSCAR) and an examination of existing reports, a review of the State Medicaid Plans, and State Medicaid personnel. Multilevel regression models were used to account for the hierarchical structure of the data. MDS and OSCAR data were linked by facility identifiers and subsequently linked with state-level variables. The use of the MDS for determining Medicaid reimbursement was associated with higher (poorer) quality indicator values for all four mental health quality indicators examined. This effect was not found in four comparison quality indicators. The findings indicate that documentation of mental health symptoms may be influenced by economic incentives. Policy makers should be cautioned from using these measures as the basis for decision making, such as with pay-for-performance initiatives.

Consumer Complaints and Nursing Home Quality

ver the past 2 decades, there has been significant progress in the measurement of nursing home quality using administrative data. Research in this field has transitioned from facility-level proxies for quality such as staffing1 and government-cited violations2 to resident-level Minimum Data Set (MDS) quality indicators (QIs) such as pressure ulcers3 and the use of antipsychotic medications.4 Despite this progress, several challenges continue to limit the usefulness of available data. First, despite the general perception that quality is substandard in many US nursing homes,5 several key indicators of poor quality are infrequently observed. For instance, the development of a new nursing home-acquired pressure ulcer in a three-month period is a relatively rare event,6 which makes it difficult to construct a meaningful ranking of facilities.7 Second, common sense would suggest that a facility appearing strong in one dimension of quality should also achieve good outcomes across other dimensions of care, but there is a very low correlation across the QIs.8 home quality is undoubtedly a multidimensional construct, but different indicators currently provide conflicting signals. Various measurement issues such as selection and ascertainment bias may contribute to the lack of correlation across measures. Finally, even if the measurement issues can be resolved, there remains the big picture issue of whether increased quality information can lead to a better functioning nursing home market. For example, a series of quality indicators are now published on the Centers for Medicare and Medicaid Services (CMS) Nursing Home Compare website in an effort to use market forces to encourage poorly performing homes to improve quality or face the loss of revenue (US General Accounting Office (GAO), p. 3).9 In this issue of Medical Care, David Stevenson explores nursing home consumer complaints as an alternative pathway to approximate quality.10 Complaints have strong face validity, because they represent direct feedback from consumers (or their surrogates) on what they deem important about their care. Moreover, complaints are easy to interpret, they are available from existing administrative data, and unlike the annual CMS survey and certification process, they provide a current reflection of nursing home quality, because they can be initiated at any time. Somewhat surprisingly, there is virtually no previous research evaluating complaints. Using data from Massachusetts for the period 1998 through 2002, Stevenson's study begins to address this gap in the literature. The results indicate a similar set of challenges to the existing quality measures. First, complaints are submitted infrequently. Second, they do not correlate very well with existing quality indicators and professional staffing, although they do correlate in the expected manner with deficiencies and nurse aide staffing. Finally, their value as a market-based mechanism encouraging better quality outcomes is unclear. Each of these issues is considered in turn below. First, the infrequency of complaints in Massachusetts' nursing homes was striking. Over the course of the study, the average Massachusetts nursing home received 2

The minimum data set depression quality indicator: does it reflect differences in care processes?

The objective of this work was to determine if nursing homes that score differently on prevalence of depression, according to the Minimum Data Set (MDS) quality indicator, also provide different processes of care related to depression. A cross-sectional study with 396 long-term residents in 14 skilled nursing facilities was conducted: 10 homes in the lower (25th percentile: low prevalence 0-2%) quartile and 4 homes in the upper (75th percentile: high prevalence 12-14%) quartile on the MDS depression quality indicator. Ten care processes related to depression were defined and operationalized into clinical indicators. Measurement of nursing home staff implementation of each care process and the assessment of depressive symptoms were conducted by trained research staff during 3 consecutive 12-hr days (7 a.m. to 7 p.m.), which included resident interviews (Geriatric Depression Scale), direct observations, and medical record review using standardized protocols. The prevalence of depressive symptoms according to independent assessments was significantly higher than prevalence based on the MDS quality indicator and comparable between homes reporting low versus high rates of depression (46% and 41%, respectively). Documentation of depressive symptoms was significantly more common in homes reporting a high prevalence rate; however, documentation of symptoms on the MDS did not result in better treatment or management of depression according to any care-process measure. Psychosocial prevention and intervention efforts, such as resident participation in organized social group activities, were not widely used within either group of homes. The MDS depression quality indicator underestimates the prevalence of depressive symptoms in all homes but, in particular, among those reporting low or nonexistent rates. The indicator may be more reflective of measurement processes related to detection of symptoms than of prevention, intervention, or management of depression outcomes. A depression quality indicator should not be eliminated from MDS reports because of the importance and prevalence of the condition. However, efforts to improve nursing home staff detection of depressive symptoms should be initiated prior to the use of any MDS-based depression indicator for improvement purposes. Homes that report a low prevalence of depression according to the nationally publicized MDS quality indicator should not be regarded as providing better care.

The minimum data set weight-loss quality indicator: does it reflect differences in care processes related to weight loss?

To determine whether nursing homes (NHs) that score differently on prevalence of weight loss, according to a Minimum Data Set (MDS) quality indicator, also provide different processes of care related to weight loss. Cross-sectional. Sixteen skilled nursing facilities: 11 NHs in the lower (25th percentile-low prevalence) quartile and five NHs in the upper (75th percentile-high prevalence) quartile on the MDS weight-loss quality indicator. Four hundred long-term residents. Sixteen care processes related to weight loss were defined and operationalized into clinical indicators. Trained research staff conducted measurement of NH staff implementation of each care process during assessments on three consecutive 12-hour days (7 a.m. to 7 p.m.), which included direct observations during meals, resident interviews, and medical record abstraction using standardized protocols. The prevalence of weight loss was significantly higher in the participants in the upper quartile NHs than in participants in the lower quartile NHs based on MDS and monthly weight data documented in the medical record. NHs with a higher prevalence of weight loss had a significantly larger proportion of residents with risk factors for weight loss, namely low oral food and fluid intake. There were few significant differences on care process measures between low- and high-weight-loss NHs. Staff in low-weight-loss NHs consistently provided verbal prompting and social interaction during meals to a greater proportion of residents, including those most at risk for weight loss. The MDS weight-loss quality indicator reflects differences in the prevalence of weight loss between NHs. NHs with a lower prevalence of weight loss have fewer residents at risk for weight loss and staff who provide verbal prompting and social interaction to more residents during meals, but the adequacy and quality of feeding assistance care needs improvement in all NHs.

Improving nursing home quality of care through outcomes data: the MDS quality indicators.

The quality of care provided to nursing home residents is a continuing source of concern throughout the world. In the United States, the Health Care Financing Administration mandated the use of a standardised resident assessment instrument, called the Minimum Data Set (MDS) which facilitated the development of a set of nursing home quality of care indicators. The MDS Quality Indicators were developed by a team of researchers at the University of Wisconsin-Madison and covered 12 domains, as well as associated risk factors. This initial set of indicators then went through an iterative process of review by national clinical panels, further empirical analysis, validation studies, and pilot tests, to confirm whether they were accurate, reliable and useful tools for identifying quality problems. The final set of MDS Quality Indicators includes 24 variables that include both processes and outcomes of care and prevalence and incidence measures. They are defined at both the resident and facility level. Four of the indicators are risk-adjusted. The indicators have several possible applications: a source of consumer information; to help guide policy makers; and to assist providers in conducting quality improvement initiatives and to evaluate the impact of these efforts.

Challenging the Quality of the Quality Indicator, “Depression Without Treatment”

To assess the validity of the Minimum Data Set (MDS)-based quality indicator, "depression without treatment," and examine whether a nonphysician-based educational intervention can improve the accuracy of MDS questions regarding depression and its treatment. All residents of a 538-bed urban, university affiliated, long-term-care (LTC) facility. Nursing and social work staff involved in completing the mood and behavior items on the MDS. Two retrospective chart review of psychotropic medications, psychiatric diagnoses, mental health evaluation, and treatment of all residents who were identified as displaying the MDS quality indicator, depression without treatment, before and 2 months after an educational intervention. The education consisted of three 1 1/2-hour sessions led by a psychiatric clinical nurse specialist to educate registered nurse assessment coordinators and social workers about psychotropic medications, clinical characteristics of psychiatric diagnoses, chart review, and coordination of resident medical care. The first MDS identified 66 residents as having depression without treatment. Clinical record review revealed that 11 of these residents were receiving an antidepressant. Twenty-two others were receiving a psychotropic medication consistent with their psychiatric diagnosis. Twenty-five of the remaining residents had not received mental health assessment for greater than 1 year. Two months after the educational intervention, 36 residents were identified as depression without treatment. Four of these residents were receiving an antidepressant; eight others were receiving a psychotropic medication consistent with their psychiatric diagnosis. Thirteen of the remaining residents had not received mental health assessment for greater than 1 year. This preliminary study reveals that the presence of the quality indicator, depression without treatment, may not accurately capture clinically depressed LTC residents in need of mental health intervention. An educational intervention may be able to assist staff in more accurately completing MDS questions regarding depression and its treatment.

Challenging the Quality of the Quality Indicator, ???Depression Without Treatment???

To assess the validity of the Minimum Data Set (MDS)-based quality indicator, “depression without treatment,” and examine whether a nonphysician-based educational intervention can improve the accuracy of MDS questions regarding depression and its treatment. Subjects All residents of a 538-bed urban, university affiliated, long-term-care (LTC) facility. Nursing and social work staff involved in completing the mood and behavior items on the MDS. Design Two retrospective chart review of psychotropic medications, psychiatric diagnoses, mental health evaluation, and treatment of all residents who were identified as displaying the MDS quality indicator, depression without treatment, before and 2 months after an educational intervention. The education consisted of three 11/2-hour sessions led by a psychiatric clinical nurse specialist to educate registered nurse assessment coordinators and social workers about psychotropic medications, clinical characteristics of psychiatric diagnoses, chart review, and coordination of resident medical care. Results The first MDS identified 66 residents as having depression without treatment. Clinical record review revealed that 11 of these residents were receiving an antidepressant. Twenty-two others were receiving a psychotropic medication consistent with their psychiatric diagnosis. Twenty-five of the remaining residents had not received mental health assessment for greater than 1 year. Two months after the educational intervention, 36 residents were identified as depression without treatment. Four of these residents were receiving an antidepressant; eight others were receiving a psychotropic medication consistent with their psychiatric diagnosis. Thirteen of the remaining residents had not received mental health assessment for greater than 1 year. Conclusions This preliminary study reveals that the presence of the quality indicator, depression without treatment, may not accurately capture clinically depressed LTC residents in need of mental health intervention. An educational intervention may be able to assist staff in more accurately completing MDS questions regarding depression and its treatment. To assess the validity of the Minimum Data Set (MDS)-based quality indicator, “depression without treatment,” and examine whether a nonphysician-based educational intervention can improve the accuracy of MDS questions regarding depression and its treatment. All residents of a 538-bed urban, university affiliated, long-term-care (LTC) facility. Nursing and social work staff involved in completing the mood and behavior items on the MDS. Two retrospective chart review of psychotropic medications, psychiatric diagnoses, mental health evaluation, and treatment of all residents who were identified as displaying the MDS quality indicator, depression without treatment, before and 2 months after an educational intervention. The education consisted of three 11/2-hour sessions led by a psychiatric clinical nurse specialist to educate registered nurse assessment coordinators and social workers about psychotropic medications, clinical characteristics of psychiatric diagnoses, chart review, and coordination of resident medical care. The first MDS identified 66 residents as having depression without treatment. Clinical record review revealed that 11 of these residents were receiving an antidepressant. Twenty-two others were receiving a psychotropic medication consistent with their psychiatric diagnosis. Twenty-five of the remaining residents had not received mental health assessment for greater than 1 year. Two months after the educational intervention, 36 residents were identified as depression without treatment. Four of these residents were receiving an antidepressant; eight others were receiving a psychotropic medication consistent with their psychiatric diagnosis. Thirteen of the remaining residents had not received mental health assessment for greater than 1 year. This preliminary study reveals that the presence of the quality indicator, depression without treatment, may not accurately capture clinically depressed LTC residents in need of mental health intervention. An educational intervention may be able to assist staff in more accurately completing MDS questions regarding depression and its treatment.