Dataset Information

The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review.

ABSTRACT:

Background

The Resident Assessment Instrument-Minimum Data Set (RAI-MDS) 2.0 is designed to collect the minimum amount of data to guide care planning and monitoring for residents in long-term care settings. These data have been used to compute indicators of care quality. Use of the quality indicators to inform quality improvement initiatives is contingent upon the validity and reliability of the indicators. The purpose of this review was to systematically examine published and grey research reports in order to assess the state of the science regarding the validity and reliability of the RAI-MDS 2.0 Quality Indicators (QIs).

Methods

We systematically reviewed the evidence for the validity and reliability of the RAI-MDS 2.0 QIs. A comprehensive literature search identified relevant original research published, in English, prior to December 2008. Fourteen articles and one report examining the validity and/or reliability of the RAI-MDS 2.0 QIs were included.

Results

The studies fell into two broad categories, those that examined individual quality indicators and those that examined multiple indicators. All studies were conducted in the United States and included from one to a total of 209 facilities. The number of residents included in the studies ranged from 109 to 5758. One study conducted under research conditions examined 38 chronic care QIs, of which strong evidence for the validity of 12 of the QIs was found. In response to these findings, the 12 QIs were recommended for public reporting purposes. However, a number of observational studies (n = 13), conducted in "real world" conditions, have tested the validity and/or reliability of individual QIs, with mixed results. Ten QIs have been studied in this manner, including falls, depression, depression without treatment, urinary incontinence, urinary tract infections, weight loss, bedfast, restraint, pressure ulcer, and pain. These studies have revealed the potential for systematic bias in reporting, with under-reporting of some indicators and over-reporting of others.

Conclusion

Evidence for the reliability and validity of the RAI-MDS QIs remains inconclusive. The QIs provide a useful tool for quality monitoring and to inform quality improvement programs and initiatives. However, caution should be exercised when interpreting the QI results and other sources of evidence of the quality of care processes should be considered in conjunction with QI results.

SUBMITTER: Hutchinson AM

PROVIDER: S-EPMC2914032 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review.

Hutchinson Alison M AM Milke Doris L DL Maisey Suzanne S Johnson Cynthia C Squires Janet E JE Teare Gary G Estabrooks Carole A CA

BMC health services research 20100616

<h4>Background</h4>The Resident Assessment Instrument-Minimum Data Set (RAI-MDS) 2.0 is designed to collect the minimum amount of data to guide care planning and monitoring for residents in long-term care settings. These data have been used to compute indicators of care quality. Use of the quality indicators to inform quality improvement initiatives is contingent upon the validity and reliability of the indicators. The purpose of this review was to systematically examine published and grey resea ...[more]

PMID: 20550719

Similar Datasets

Project description:BackgroundThe Minimum Data Set (MDS) for nursing home resident assessment has been required in all U.S. nursing homes since 1990 and has been universally computerized since 1998. Initially intended to structure clinical care planning, uses of the MDS expanded to include policy applications such as case-mix reimbursement, quality monitoring and research. The purpose of this paper is to summarize a series of analyses examining the internal consistency and predictive validity of the MDS data as used in the "real world" in all U.S. nursing homes between 1999 and 2007.MethodsWe used person level linked MDS and Medicare denominator and all institutional claim files including inpatient (hospital and skilled nursing facilities) for all Medicare fee-for-service beneficiaries entering U.S. nursing homes during the period 1999 to 2007. We calculated the sensitivity and positive predictive value (PPV) of diagnoses taken from Medicare hospital claims and from the MDS among all new admissions from hospitals to nursing homes and the internal consistency (alpha reliability) of pairs of items within the MDS that logically should be related. We also tested the internal consistency of commonly used MDS based multi-item scales and examined the predictive validity of an MDS based severity measure viz. one year survival. Finally, we examined the correspondence of the MDS discharge record to hospitalizations and deaths seen in Medicare claims, and the completeness of MDS assessments upon skilled nursing facility (SNF) admission.ResultsEach year there were some 800,000 new admissions directly from hospital to US nursing homes and some 900,000 uninterrupted SNF stays. Comparing Medicare enrollment records and claims with MDS records revealed reasonably good correspondence that improved over time (by 2006 only 3% of deaths had no MDS discharge record, only 5% of SNF stays had no MDS, but over 20% of MDS discharges indicating hospitalization had no associated Medicare claim). The PPV and sensitivity levels of Medicare hospital diagnoses and MDS based diagnoses were between .6 and .7 for major diagnoses like CHF, hypertension, diabetes. Internal consistency, as measured by PPV, of the MDS ADL items with other MDS items measuring impairments and symptoms exceeded .9. The Activities of Daily Living (ADL) long form summary scale achieved an alpha inter-consistency level exceeding .85 and multi-item scale alpha levels of .65 were achieved for well being and mood, and .55 for behavior, levels that were sustained even after stratification by ADL and cognition. The Changes in Health, End-stage disease and Symptoms and Signs (CHESS) index, a summary measure of frailty was highly predictive of one year survival.ConclusionThe MDS demonstrates a reasonable level of consistency both in terms of how well MDS diagnoses correspond to hospital discharge diagnoses and in terms of the internal consistency of functioning and behavioral items. The level of alpha reliability and validity demonstrated by the scales suggest that the data can be useful for research and policy analysis. However, while improving, the MDS discharge tracking record should still not be used to indicate Medicare hospitalizations or mortality. It will be important to monitor the performance of the MDS 3.0 with respect to consistency, reliability and validity now that it has replaced version 2.0, using these results as a baseline that should be exceeded.

Project description:BACKGROUND:One way of measuring the quality of home care are quality indicators (QIs) derived from data collected with the Resident Assessment Instrument-Home Care (RAI-HC). In order to produce meaningful results for quality improvement and quality comparisons across home care organizations (HCOs) and over time, RAI-HC QIs must be valid and reliable. The aim of this systematic review was to identify currently existing RAI-HC QIs and to summarize the scientific knowledge on the validity and reliability of these QIs. METHODS:A systematic review was performed using the electronic databases PubMed, CINAHL, Embase, PsycINFO and Cochrane Library. Studies describing the development process or the psychometric characteristics of RAI-HC QIs were eligible. The data extraction involved a general description of the included studies as well as the identified RAI-HC QIs and information on validity and reliability. The methodological quality of the identified RAI-HC QI sets was assessed using the Appraisal of Indicators through Research and Evaluation (AIRE) instrument. RESULTS:Four studies out of 659 initial hits met the inclusion criteria. The included studies described the development and validation process of three RAI-HC QI sets comprising 48 unique RAI-HC QIs, which predominantly refer to outcome of care. Overall, the validity and reliability of the identified RAI-HC QIs were not sufficiently tested. The methodological quality of the three identified RAI-HC QI sets varied across the four AIRE instrument domains. None of the QI sets reached high methodological quality, defined as scores of 50% and higher in all four AIRE instrument domains. CONCLUSIONS:This is the first review that systematically summarized and appraised the available scientific evidence on the validity and reliability of RAI-HC QIs. It identified insufficient reporting of RAI-HC QIs validation processes and reliability as well as missing state-of-the-art methodologies. The review provides guidance as to what additional validity and reliability testing are needed to strengthen the scientific soundness of RAI-HC QIs. Considering that RAI-HC QIs are already implemented and used to measure and compare quality of home care, further investigations on RAI-HC QIs reliability and validity is recommended.

Project description:BACKGROUND:Currently, there are no formalized measures for the quality of home based palliative care in Ontario. This study developed a set of potential quality indicators for seriously ill home care clients using a standardized assessment. METHODS:Secondary analysis of Resident Assessment Instrument for Home Care data for Ontario completed between 2006 and 2013 was used to develop quality indicators (QIs) thought to be relevant to the needs of older (65+) seriously ill clients. QIs were developed through a review of the literature and consultation with subject matter experts in palliative care. Serious illness was defined as a prognosis of less than 6 months to live or the presence of severe health instability. The rates of the QIs were stratified across Ontario's geographic regions, and across four common life-limiting illnesses to observe variation. RESULTS:Within the sample, 14,312 clients were considered to be seriously ill and were more likely to experience negative health outcomes such as cognitive performance (OR?=?2.77; 95% CI: 2.66-2.89) and pain (OR?=?1.59; 95% CI: 1.53-1.64). Twenty subject matter experts were consulted and a list of seven QIs was developed. Indicators with the highest overall rates were prevalence of falls (50%) prevalence of daily pain (47%), and prevalence of caregiver distress (42%). The range in QI rates was largest across regions for prevalence of caregiver distress (21.5%), the prevalence of falls (16.6%), and the prevalence of social isolation (13.7%). Those with some form of dementia were most likely to have a caregiver that was distressed (52.6%) or to experience a fall (53.3%). CONCLUSION:Home care clients in Ontario who are seriously ill are experiencing high rates of negative health outcomes, many of which are amenable to change. The RAI-HC can be a useful tool in identifying these clients in order to better understand their needs and abilities. These results contribute significantly to the process of creating and validating a standardized set of QIs that can be generated by organizations using the RAI-HC as part of normal clinical practice.

Project description:BackgroundThe minimum data set (MDS) is a collection of data elements to be grouped using a standard approach to allow the use of data for clinical and research purposes. Health data are typically voluminous, complex, and sometimes too ambiguous to generate indicators that can provide knowledge and information on health. This complexity extends further to the rare disease (RD) domain. MDSs are essential for health surveillance as they help provide services and generate recommended population indicators. There is a bottleneck in international literature that reveals a global problem with data collection, recording, and structuring in RD.ObjectiveThis study aimed to identify and analyze the MDSs used for RD in health care networks worldwide and compare them with World Health Organization (WHO) guidelines.MethodsThe population, concept, and context methodology proposed by the Joanna Briggs Institute was used to define the research question of this systematic review. A total of 4 databases were reviewed, and all the processes were reported using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. The data elements were analyzed, extracted, and organized into 10 categories according to WHO digital health guidelines. The quality assessment used the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist.ResultsWe included 20 studies in our review, 70% (n=14) of which focused on a specific health domain and 30% (n=6) of which referred to RD in general. WHO recommends that health systems and networks use standard terminology to exchange data, information, knowledge, and intelligence in health. However, there was a lack of terminological standardization of the concepts in MDSs. Moreover, the selected studies did not follow the same standard structure for classifying the data from their MDSs. All studies presented MDSs with limitations or restrictions because they covered only a specific RD, or their scope of application was restricted to a specific context or geographic region. Data science methods and clinical experience were used to design, structure, and recommend a fundamental global MDS for RD patient records in health care networks.ConclusionsOur study highlights the difficulties in standardizing and categorizing findings from MDSs for RD because of the varying structures used in different studies. The fundamental RD MDS designed in this study comprehensively covers the data needs in the clinical and management sectors. These results can help public policy makers support other aspects of their policies. We highlight the potential of our results to help strategic decisions related to RD.Trial registrationPROSPERO CRD42021221593; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=221593.International registered report identifier (irrid)RR2-10.1016/j.procs.2021.12.034.

Project description:BackgroundDespite an increasing importance of home care, quality assurance in this healthcare sector in Switzerland is hardly established. In 2010, Swiss home care quality indicators (QIs) based on the Resident Assessment Instrument-Home Care (RAI-HC) were developed. However, these QIs have not been revised since, although internationally new RAI-HC QIs have emerged. The objective of this study was to assess the appropriateness of RAI-HC QIs to measure quality of home care in Switzerland from a public health and healthcare providers' perspective.MethodsFirst, the appropriateness of RAI-HC QIs, identified in a recent systematic review, was assessed by a multidisciplinary expert panel based on the RAND/UCLA Appropriateness Method taking into account indicators' public health relevance, potential of influence, and comprehensibility. Second, the QIs selected by the experts were afterwards rated regarding their relevance, potential of influence, and practicability from a healthcare providers' perspective in focus groups with home care nurses based on the Nominal-Group-Technique. Data were analyzed using median scores and the Disagreement Index.Results18 of 43 RAI-HC QIs were rated appropriate by the experts from a public health perspective. The 18 QIs cover clinical, psychosocial, functional and service use aspects. Seven of the 18 QIs were subsequently rated appropriate by home care nurses from a healthcare providers' perspective. The focus of these QIs is narrow, because three of seven QIs are pain-related. From both perspectives, the majority of RAI-HC QIs were rated inappropriate because of insufficient potential of influence, with healthcare providers rating them more critically.ConclusionsThe study shows that the appropriateness of RAI-HC QIs differs according to the stakeholder perspective and the intended use of QIs. The findings of this study can guide policy-makers and home care organizations on selecting QIs and to critically reflect on their appropriate use.

Dataset Information

The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review.

Background

Methods

Results

Conclusion

Publications

The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets